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@article{mccomb2015liftingtheveil:, abstract = {Novel design methodologies are often evaluated through studies involving human designers, but such studies can incur a high personnel cost. It can also be difficult to isolate the effects of specific team or individual characteristics. This work introduces the Cognitively-Inspired Simulated Annealing Teams (CISAT) modeling framework, a platform for efficiently simulating and analyzing human design teams. The framework models a number of empirically demonstrated cognitive phenomena …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Design Studies 40, 119-142, 2015}, journal = {Design Studies}, pages = {119-142}, pub_year = {2015}, publisher = {Elsevier}, title = {Lifting the Veil: Drawing Insights about Design Teams from a Cognitively-inspired Computational Model}, volume = {40} }
{ "ENTRYTYPE": "article", "ID": "mccomb2015liftingtheveil:", "abstract": "Novel design methodologies are often evaluated through studies involving human designers, but such studies can incur a high personnel cost. It can also be difficult to isolate the effects of specific team or individual characteristics. This work introduces the Cognitively-Inspired Simulated Annealing Teams (CISAT) modeling framework, a platform for efficiently simulating and analyzing human design teams. The framework models a number of empirically demonstrated cognitive phenomena …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Design Studies 40, 119-142, 2015", "conference": null, "journal": "Design Studies", "number": null, "pages": "119-142", "pub_year": 2015, "publisher": "Elsevier", "title": "Lifting the Veil: Drawing Insights about Design Teams from a Cognitively-inspired Computational Model", "volume": "40" }
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@article{raina2019learningtodesign, abstract = {Humans as designers have quite versatile problem-solving strategies. Computer agents on the other hand can access large-scale computational resources to solve certain design problems. Hence, if agents can learn from human behavior, a synergetic human-agent problem-solving team can be created. This paper presents an approach to extract human design strategies and implicit rules, purely from historical human data, and use that for design generation. A two-step framework that learns to imitate human design strategies from observation is proposed and implemented. This framework makes use of deep learning constructs to learn to generate designs without any explicit information about objective and performance metrics. The framework is designed to interact with the problem through a visual interface as humans did when solving the problem. It is trained to imitate a set of human designers by …}, author = {Ayush Raina and Christopher McComb and Jonathan Cagan}, citation = {Journal of Mechanical Design, 2019}, journal = {Journal of Mechanical Design}, pub_year = {2019}, title = {Learning To Design From Humans: Imitating Human Designers Through Deep Learning} }
{ "ENTRYTYPE": "article", "ID": "raina2019learningtodesign", "abstract": "Humans as designers have quite versatile problem-solving strategies. Computer agents on the other hand can access large-scale computational resources to solve certain design problems. Hence, if agents can learn from human behavior, a synergetic human-agent problem-solving team can be created. This paper presents an approach to extract human design strategies and implicit rules, purely from historical human data, and use that for design generation. A two-step framework that learns to imitate human design strategies from observation is proposed and implemented. This framework makes use of deep learning constructs to learn to generate designs without any explicit information about objective and performance metrics. The framework is designed to interact with the problem through a visual interface as humans did when solving the problem. It is trained to imitate a set of human designers by …", "author": "Ayush Raina and Christopher McComb and Jonathan Cagan", "citation": "Journal of Mechanical Design, 2019", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Learning To Design From Humans: Imitating Human Designers Through Deep Learning", "volume": null }
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/scholar?hl=en&cites=3420341011426968484
[ "3420341011426968484" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/141/11/111102/955339
/scholar?oi=bibs&hl=en&q=related:pAPONAd-dy8J:scholar.google.com/
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@article{williams2019designrepositoryeffectiveness, abstract = {Machine learning can be used to automate common or time-consuming engineering tasks for which sufficient data already exist. For instance, design repositories can be used to train deep learning algorithms to assess component manufacturability; however, methods to determine the suitability of a design repository for use with machine learning do not exist. We provide an initial investigation toward identifying such a method using “artificial” design repositories to experimentally test the extent to which altering properties of the dataset impacts the assessment precision and generalizability of neural networks trained on the data. For this experiment, we use a 3D convolutional neural network to estimate quantitative manufacturing metrics directly from voxel-based component geometries. Additive manufacturing (AM) is used as a case study because of the recent growth of AM-focused design repositories such as …}, author = {Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb}, citation = {Journal of Mechanical Design, 2019}, journal = {Journal of Mechanical Design}, pub_year = {2019}, title = {Design Repository Effectiveness for 3D Convolutional Neural Networks: Application to Additive Manufacturing} }
{ "ENTRYTYPE": "article", "ID": "williams2019designrepositoryeffectiveness", "abstract": "Machine learning can be used to automate common or time-consuming engineering tasks for which sufficient data already exist. For instance, design repositories can be used to train deep learning algorithms to assess component manufacturability; however, methods to determine the suitability of a design repository for use with machine learning do not exist. We provide an initial investigation toward identifying such a method using “artificial” design repositories to experimentally test the extent to which altering properties of the dataset impacts the assessment precision and generalizability of neural networks trained on the data. For this experiment, we use a 3D convolutional neural network to estimate quantitative manufacturing metrics directly from voxel-based component geometries. Additive manufacturing (AM) is used as a case study because of the recent growth of AM-focused design repositories such as …", "author": "Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb", "citation": "Journal of Mechanical Design, 2019", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Design Repository Effectiveness for 3D Convolutional Neural Networks: Application to Additive Manufacturing", "volume": null }
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/scholar?hl=en&cites=3123781173515911231
[ "3123781173515911231" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/141/11/111701/955346
/scholar?oi=bibs&hl=en&q=related:PwB4Q23mWSsJ:scholar.google.com/
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@article{zhang2021acautionarytale, abstract = {Recent advances in artificial intelligence (AI) offer opportunities for integrating AI into human design teams. Although various AIs have been developed to aid engineering design, the impact of AI usage on human design teams has received scant research attention. This research assesses the impact of a deep learning AI on distributed human design teams through a human subject study that includes an abrupt problem change. The results demonstrate that, for this study, the AI boosts the initial performance of low-performing teams before …}, author = {Guanglu Zhang and Ayush Raina and Jonathan Cagan and Christopher McComb}, citation = {Design Studies 72, 100990, 2021}, journal = {Design Studies}, pages = {100990}, pub_year = {2021}, publisher = {Elsevier}, title = {A cautionary tale about the impact of AI on human design teams}, volume = {72} }
{ "ENTRYTYPE": "article", "ID": "zhang2021acautionarytale", "abstract": "Recent advances in artificial intelligence (AI) offer opportunities for integrating AI into human design teams. Although various AIs have been developed to aid engineering design, the impact of AI usage on human design teams has received scant research attention. This research assesses the impact of a deep learning AI on distributed human design teams through a human subject study that includes an abrupt problem change. The results demonstrate that, for this study, the AI boosts the initial performance of low-performing teams before …", "author": "Guanglu Zhang and Ayush Raina and Jonathan Cagan and Christopher McComb", "citation": "Design Studies 72, 100990, 2021", "conference": null, "journal": "Design Studies", "number": null, "pages": "100990", "pub_year": 2021, "publisher": "Elsevier", "title": "A cautionary tale about the impact of AI on human design teams", "volume": "72" }
0P9w_S0AAAAJ:q3oQSFYPqjQC
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/scholar?hl=en&cites=13862579487630350310
[ "13862579487630350310" ]
https://www.sciencedirect.com/science/article/pii/S0142694X21000016
/scholar?oi=bibs&hl=en&q=related:5tfSzpjGYcAJ:scholar.google.com/
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@article{mccomb2015rollingwiththe, abstract = {Designers must often create solutions to problems that exhibit dynamic characteristics. For instance, a client might modify specifications after design has commenced, or a competitor may introduce a new technology or feature. This paper presents a cognitive study that was conducted to explore the manner in which design teams respond to such situations. In the study, teams of undergraduate engineering students sought to solve a design task that was subject to two large, unexpected changes in problem formulation that were introduced during solving. High-and low-performing teams demonstrated very different …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Design Studies 36, 99-121, 2015}, journal = {Design Studies}, pages = {99-121}, pub_year = {2015}, publisher = {Elsevier}, title = {Rolling with the Punches: An Examination of Team Performance in a Design Task Subject to Drastic Changes}, volume = {36} }
{ "ENTRYTYPE": "article", "ID": "mccomb2015rollingwiththe", "abstract": "Designers must often create solutions to problems that exhibit dynamic characteristics. For instance, a client might modify specifications after design has commenced, or a competitor may introduce a new technology or feature. This paper presents a cognitive study that was conducted to explore the manner in which design teams respond to such situations. In the study, teams of undergraduate engineering students sought to solve a design task that was subject to two large, unexpected changes in problem formulation that were introduced during solving. High-and low-performing teams demonstrated very different …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Design Studies 36, 99-121, 2015", "conference": null, "journal": "Design Studies", "number": null, "pages": "99-121", "pub_year": 2015, "publisher": "Elsevier", "title": "Rolling with the Punches: An Examination of Team Performance in a Design Task Subject to Drastic Changes", "volume": "36" }
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/scholar?hl=en&cites=4707453472868866956
[ "4707453472868866956" ]
https://www.sciencedirect.com/science/article/pii/S0142694X14000659
/scholar?oi=bibs&hl=en&q=related:jBsHD_47VEEJ:scholar.google.com/
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5
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@article{mccomb2017optimizingdesignteams, abstract = {The performance of a team with the right characteristics can exceed the mere sum of the constituent members' individual efforts. However, a team having the wrong characteristics may perform more poorly than the sum of its individuals. Therefore, it is vital that teams are assembled and managed properly in order to maximize performance. This work examines how the properties of configuration design problems can be leveraged to select the best values for team characteristics (specifically team size and interaction frequency). A computational model of design teams which has been shown to effectively emulate human team behavior is employed to pinpoint optimized team characteristics for solving a variety of configuration design problems. These configuration design problems are characterized with respect to the local and global structure of the design space, the alignment between objectives, and the resources …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Journal of Mechanical Design, 2017}, journal = {Journal of Mechanical Design}, pub_year = {2017}, title = {Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017optimizingdesignteams", "abstract": "The performance of a team with the right characteristics can exceed the mere sum of the constituent members' individual efforts. However, a team having the wrong characteristics may perform more poorly than the sum of its individuals. Therefore, it is vital that teams are assembled and managed properly in order to maximize performance. This work examines how the properties of configuration design problems can be leveraged to select the best values for team characteristics (specifically team size and interaction frequency). A computational model of design teams which has been shown to effectively emulate human team behavior is employed to pinpoint optimized team characteristics for solving a variety of configuration design problems. These configuration design problems are characterized with respect to the local and global structure of the design space, the alignment between objectives, and the resources …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Journal of Mechanical Design, 2017", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2017, "publisher": null, "title": "Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test", "volume": null }
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[ "10487496979515429608" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/139/4/041101/421818
/scholar?oi=bibs&hl=en&q=related:6NL_DvASi5EJ:scholar.google.com/
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@article{mccomb2017capturinghumansequence-learning, abstract = {Designers often search for new solutions by iteratively adapting a current design. By engaging in this search, designers not only improve solution quality but also begin to learn what operational patterns might improve the solution in future iterations. Previous work in psychology has demonstrated that humans can fluently and adeptly learn short operational sequences that aid problem-solving. This paper explores how designers learn and employ sequences within the realm of engineering design. Specifically, this work analyzes behavioral patterns in two human studies in which participants solved configuration design problems. Behavioral data from the two studies are first analyzed using Markov chains to determine how much representation complexity is necessary to quantify the sequential patterns that designers employ during solving. It is discovered that first-order Markov chains are capable of accurately …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Journal of Mechanical Design 139 (9), 2017}, journal = {Journal of Mechanical Design}, number = {9}, pub_year = {2017}, publisher = {ASME}, title = {Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains}, volume = {139} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017capturinghumansequence-learning", "abstract": "Designers often search for new solutions by iteratively adapting a current design. By engaging in this search, designers not only improve solution quality but also begin to learn what operational patterns might improve the solution in future iterations. Previous work in psychology has demonstrated that humans can fluently and adeptly learn short operational sequences that aid problem-solving. This paper explores how designers learn and employ sequences within the realm of engineering design. Specifically, this work analyzes behavioral patterns in two human studies in which participants solved configuration design problems. Behavioral data from the two studies are first analyzed using Markov chains to determine how much representation complexity is necessary to quantify the sequential patterns that designers employ during solving. It is discovered that first-order Markov chains are capable of accurately …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Journal of Mechanical Design 139 (9), 2017", "conference": null, "journal": "Journal of Mechanical Design", "number": "9", "pages": null, "pub_year": 2017, "publisher": "ASME", "title": "Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains", "volume": "139" }
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[ "6286221499622255408" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/139/9/091101/383821
/scholar?oi=bibs&hl=en&q=related:MGto6CUlPVcJ:scholar.google.com/
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@article{mccomb2017miningprocessheuristics, abstract = {Configuration design problems, characterized by the assembly of components into a final desired solution, are common in engineering design. Various theoretical approaches have been offered for solving configuration type problems, but few studies have examined the approach that humans naturally use to solve such problems. This work applies data-mining techniques to quantitatively study the processes that designers use to solve configuration design problems. The guiding goal is to extract beneficial design process heuristics that are generalizable to the entire class of problems. The extraction of these human problem-solving heuristics is automated through the application of hidden Markov models to the data from two behavioral studies. Results show that designers proceed through four procedural states in solving configuration design problems, roughly transitioning from topology design to shape and …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Journal of Mechanical Design, 2017}, journal = {Journal of Mechanical Design}, pub_year = {2017}, publisher = {ASME}, title = {Mining Process Heuristics from Designer Action Data via Hidden Markov Models} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017miningprocessheuristics", "abstract": "Configuration design problems, characterized by the assembly of components into a final desired solution, are common in engineering design. Various theoretical approaches have been offered for solving configuration type problems, but few studies have examined the approach that humans naturally use to solve such problems. This work applies data-mining techniques to quantitatively study the processes that designers use to solve configuration design problems. The guiding goal is to extract beneficial design process heuristics that are generalizable to the entire class of problems. The extraction of these human problem-solving heuristics is automated through the application of hidden Markov models to the data from two behavioral studies. Results show that designers proceed through four procedural states in solving configuration design problems, roughly transitioning from topology design to shape and …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Journal of Mechanical Design, 2017", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2017, "publisher": "ASME", "title": "Mining Process Heuristics from Designer Action Data via Hidden Markov Models", "volume": null }
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[ "3594119212580805377" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/139/11/111412/375543
/scholar?oi=bibs&hl=en&q=related:ARtJomHg4DEJ:scholar.google.com/
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@article{alzayed2021areyoufeeling, abstract = {Having empathy in the design process can help engineers relate to the end-user by identifying what and why certain experiences are meaningful. While there have been efforts to identify the factors that impact empathic tendencies in engineering, there has been limited evidence on how a students’ trait empathy or empathic self-efficacy develops over a design project or what factors impact this development. The current study was developed to explore the development of students’ trait empathy and empathic self-efficacy development and identify the underlying impact of the design project’s context and course instructor through a study with 103 engineering students. Students’ trait empathy and empathic self-efficacy were measured across each of the four design stages (problem formulation, concept generation, concept selection, and final conceptual design) during an 8-week project. The results highlight that …}, author = {Mohammad Alsager Alzayed and Christopher McComb and Jessica Menold and Jacquelyn Huff and Scarlett R Miller}, citation = {Journal of Mechanical Design, 2021}, journal = {Journal of Mechanical Design}, pub_year = {2021}, title = {Are you feeling me? An exploration of empathy development in engineering design education} }
{ "ENTRYTYPE": "article", "ID": "alzayed2021areyoufeeling", "abstract": "Having empathy in the design process can help engineers relate to the end-user by identifying what and why certain experiences are meaningful. While there have been efforts to identify the factors that impact empathic tendencies in engineering, there has been limited evidence on how a students’ trait empathy or empathic self-efficacy develops over a design project or what factors impact this development. The current study was developed to explore the development of students’ trait empathy and empathic self-efficacy development and identify the underlying impact of the design project’s context and course instructor through a study with 103 engineering students. Students’ trait empathy and empathic self-efficacy were measured across each of the four design stages (problem formulation, concept generation, concept selection, and final conceptual design) during an 8-week project. The results highlight that …", "author": "Mohammad Alsager Alzayed and Christopher McComb and Jessica Menold and Jacquelyn Huff and Scarlett R Miller", "citation": "Journal of Mechanical Design, 2021", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Are you feeling me? An exploration of empathy development in engineering design education", "volume": null }
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/scholar?hl=en&cites=3527662701135177656
[ "3527662701135177656" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/143/11/112301/1087576
/scholar?oi=bibs&hl=en&q=related:uKeOTInG9DAJ:scholar.google.com/
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@article{lapp2019kaboom:anagent-based, abstract = {The performance of a design team is influenced by each team member’s unique cognitive style – i.e., their preferred manner of managing structure as they solve problems, make decisions, and seek to bring about change. Cognitive style plays an important role in how teams of engineers design and collaborate, but the interactions of cognitive style with team organization and processes have not been well studied. The limitations of small-scale behavioral experiments have led researchers to develop computational models for simulating teamwork; however, none have modeled the effects of individuals’ cognitive styles. This paper presents the Kirton Adaption–Innovation Inventory agent-based organizational optimization model (KABOOM), the first agent-based model of teamwork to incorporate cognitive style. In KABOOM, heterogeneous agents imitate the diverse problem-solving styles described by the Kirton …}, author = {Samuel Lapp and Kathryn Jablokow and Christopher McComb}, citation = {Design Science, 2019}, journal = {Design Science}, pub_year = {2019}, title = {KABOOM: An Agent-Based Model for Simulating Cognitive Style in Team Problem Solving} }
{ "ENTRYTYPE": "article", "ID": "lapp2019kaboom:anagent-based", "abstract": "The performance of a design team is influenced by each team member’s unique cognitive style – i.e., their preferred manner of managing structure as they solve problems, make decisions, and seek to bring about change. Cognitive style plays an important role in how teams of engineers design and collaborate, but the interactions of cognitive style with team organization and processes have not been well studied. The limitations of small-scale behavioral experiments have led researchers to develop computational models for simulating teamwork; however, none have modeled the effects of individuals’ cognitive styles. This paper presents the Kirton Adaption–Innovation Inventory agent-based organizational optimization model (KABOOM), the first agent-based model of teamwork to incorporate cognitive style. In KABOOM, heterogeneous agents imitate the diverse problem-solving styles described by the Kirton …", "author": "Samuel Lapp and Kathryn Jablokow and Christopher McComb", "citation": "Design Science, 2019", "conference": null, "journal": "Design Science", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "KABOOM: An Agent-Based Model for Simulating Cognitive Style in Team Problem Solving", "volume": null }
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51
/scholar?hl=en&cites=4739586421082257884,30128802387191467
[ "4739586421082257884", "30128802387191467" ]
https://www.cambridge.org/core/journals/design-science/article/kaboom-an-agentbased-model-for-simulating-cognitive-style-in-team-problem-solving/DA2EA6A5A1E4472707B9C8C5FF642EA0
/scholar?oi=bibs&hl=en&q=related:3HnfEr1kxkEJ:scholar.google.com/
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@article{song2020towardhybridteams:, abstract = {Human-computer hybrid teams can meet challenges in designing complex engineered systems. However, the understanding of interaction in the hybrid teams is lacking. We review the literature and identify four key attributes to construct design research platforms that support multi-phase design, hybrid teams, multiple design scenarios, and data logging. Then, we introduce a platform for unmanned aerial vehicle (UAV) design embodying these attributes. With the platform, experiments can be conducted to study how designers and intelligent computational agents interact, support, and impact each other.}, author = {Binyang Song and Nicolas F. Soria Zurita and Guanglu Zhang and Gary Stump and Corey Balon and Simon W. Miller and Michael Yukish and Jonathan Cagan and Christopher McComb}, citation = {International Design Conference - DESIGN 2020, 2020}, conference = {International Design Conference - DESIGN 2020}, pub_year = {2020}, title = {Toward Hybrid Teams: A Platform To Understand Human-Computer Collaboration During the Design of Complex Engineered Systems} }
{ "ENTRYTYPE": "article", "ID": "song2020towardhybridteams:", "abstract": "Human-computer hybrid teams can meet challenges in designing complex engineered systems. However, the understanding of interaction in the hybrid teams is lacking. We review the literature and identify four key attributes to construct design research platforms that support multi-phase design, hybrid teams, multiple design scenarios, and data logging. Then, we introduce a platform for unmanned aerial vehicle (UAV) design embodying these attributes. With the platform, experiments can be conducted to study how designers and intelligent computational agents interact, support, and impact each other.", "author": "Binyang Song and Nicolas F. Soria Zurita and Guanglu Zhang and Gary Stump and Corey Balon and Simon W. Miller and Michael Yukish and Jonathan Cagan and Christopher McComb", "citation": "International Design Conference - DESIGN 2020, 2020", "conference": "International Design Conference - DESIGN 2020", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Toward Hybrid Teams: A Platform To Understand Human-Computer Collaboration During the Design of Complex Engineered Systems", "volume": null }
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[ "7263844905543200920" ]
https://www.cambridge.org/core/journals/proceedings-of-the-design-society-design-conference/article/toward-hybrid-teams-a-platform-to-understand-humancomputer-collaboration-during-the-design-of-complex-engineered-systems/43F715549D49ABD1BC90579425A8CDB9
/scholar?oi=bibs&hl=en&q=related:mPBuwnRczmQJ:scholar.google.com/
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@article{song2022decodingtheagility, abstract = {Although necessary for complex problem solving, such as engineering design, team agility is often difficult to achieve in practice. The evolution of Artificial Intelligence (AI) affords unique opportunities for supporting team problem solving. While integrating assistive AI agents into human teams has at times improved team performance, it is still unclear if, how, and why AI affects team agility. A large-scale human experiment answers these questions, revealing that, with appropriately interfaced AIs, AI-assisted human teams enjoy …}, author = {Binyang Song and Joshua T. Gyory and Guanglu Zhang and Nicolas F. Soria Zurita and Gary Stump and Jay Martin and Simon W Miller and Corey Balon and Michael Yukish and Christopher McComb and Jonathan Cagan}, citation = {Design Studies, 2022}, journal = {Design Studies}, pub_year = {2022}, title = {Decoding the Agility of Artificial Intelligence-Assisted Human Design Teams} }
{ "ENTRYTYPE": "article", "ID": "song2022decodingtheagility", "abstract": "Although necessary for complex problem solving, such as engineering design, team agility is often difficult to achieve in practice. The evolution of Artificial Intelligence (AI) affords unique opportunities for supporting team problem solving. While integrating assistive AI agents into human teams has at times improved team performance, it is still unclear if, how, and why AI affects team agility. A large-scale human experiment answers these questions, revealing that, with appropriately interfaced AIs, AI-assisted human teams enjoy …", "author": "Binyang Song and Joshua T. Gyory and Guanglu Zhang and Nicolas F. Soria Zurita and Gary Stump and Jay Martin and Simon W Miller and Corey Balon and Michael Yukish and Christopher McComb and Jonathan Cagan", "citation": "Design Studies, 2022", "conference": null, "journal": "Design Studies", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Decoding the Agility of Artificial Intelligence-Assisted Human Design Teams", "volume": null }
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[ "12483581656711157753" ]
https://www.sciencedirect.com/science/article/pii/S0142694X2200014X
/scholar?oi=bibs&hl=en&q=related:-dfZPGCXPq0J:scholar.google.com/
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@article{raina2019transferringdesignstrategies, abstract = {Solving any design problem involves planning and strategizing, where intermediate processes are identified and then sequenced. This is an abstract skill that designers learn over time and then use across similar problems. However, this transfer of strategies in design has not been effectively modeled or leveraged within computational agents. This note presents an approach to represent design strategies using a probabilistic model. The model provides a mechanism to generate new designs based on certain design strategies while solving configuration design task in a sequential manner. This work also demonstrates that this probabilistic representation can be used to transfer strategies from human designers to computational design agents in a way that is general and useful. This transfer-driven approach opens up the possibility of identifying high-performing behavior in human designers and using it to …}, author = {Ayush Raina and Jonathan Cagan and Christopher McComb}, citation = {Journal of Mechanical Design, 2019}, journal = {Journal of Mechanical Design}, pub_year = {2019}, title = {Transferring Design Strategies from Human to Computer and Across Design Problems} }
{ "ENTRYTYPE": "article", "ID": "raina2019transferringdesignstrategies", "abstract": "Solving any design problem involves planning and strategizing, where intermediate processes are identified and then sequenced. This is an abstract skill that designers learn over time and then use across similar problems. However, this transfer of strategies in design has not been effectively modeled or leveraged within computational agents. This note presents an approach to represent design strategies using a probabilistic model. The model provides a mechanism to generate new designs based on certain design strategies while solving configuration design task in a sequential manner. This work also demonstrates that this probabilistic representation can be used to transfer strategies from human designers to computational design agents in a way that is general and useful. This transfer-driven approach opens up the possibility of identifying high-performing behavior in human designers and using it to …", "author": "Ayush Raina and Jonathan Cagan and Christopher McComb", "citation": "Journal of Mechanical Design, 2019", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Transferring Design Strategies from Human to Computer and Across Design Problems", "volume": null }
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/scholar?hl=en&cites=13705217613876381624
[ "13705217613876381624" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/141/11/114501/955351
/scholar?oi=bibs&hl=en&q=related:uEeHdM62Mr4J:scholar.google.com/
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@article{mccomb2016utilizingmarkovchains, abstract = {Design often involves searching for a final design solution by iteratively modifying and adjusting a current design. Through this process designers are able to improve the quality of the current design and also learn what patterns of operations are most likely to lead to the quickest future improvements. Prior work in psychology has shown that humans can be adept at learning how to apply short sequences of operations for maximum effect while solving a problem. This work explores the sequencing of operations specifically within the domain of engineering design by examining the results of a human study in which participants designed trusses. A statistical analysis of the data from that study uses Markov Chains to show with high confidence that meaningful operation sequences exist. This work also uses an agent-based modeling framework in conjunction with Markov Chain concepts to simulate the …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Eight International Conference on Design Computing and Cognition, 2016}, pub_year = {2016}, publisher = {Springer}, title = {Utilizing Markov Chains to Understand Operation Sequencing in Design Tasks} }
{ "ENTRYTYPE": "article", "ID": "mccomb2016utilizingmarkovchains", "abstract": "Design often involves searching for a final design solution by iteratively modifying and adjusting a current design. Through this process designers are able to improve the quality of the current design and also learn what patterns of operations are most likely to lead to the quickest future improvements. Prior work in psychology has shown that humans can be adept at learning how to apply short sequences of operations for maximum effect while solving a problem. This work explores the sequencing of operations specifically within the domain of engineering design by examining the results of a human study in which participants designed trusses. A statistical analysis of the data from that study uses Markov Chains to show with high confidence that meaningful operation sequences exist. This work also uses an agent-based modeling framework in conjunction with Markov Chain concepts to simulate the …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Eight International Conference on Design Computing and Cognition, 2016", "conference": null, "journal": null, "number": null, "pages": null, "pub_year": 2016, "publisher": "Springer", "title": "Utilizing Markov Chains to Understand Operation Sequencing in Design Tasks", "volume": null }
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/scholar?hl=en&cites=5410037423659347493
[ "5410037423659347493" ]
https://link.springer.com/chapter/10.1007/978-3-319-44989-0_22
/scholar?oi=bibs&hl=en&q=related:Je7Iil9QFEsJ:scholar.google.com/
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@article{murphy2018usingautoencodedvoxel, abstract = {Additive Manufacturing (AM) allows designers to create intricate geometries that were once too complex or expensive to achieve through traditional manufacturing processes. Currently, designing parts using features specific to AM, commonly referred to as Design for Additive Manufacturing (DfAM), is restricted to experts in the field. As a result novices in industry may overlook potentially transformational design potential enabled by AM. This project aims to automate DfAM through deep learning making it accessible to a broader audience, and enabling designers of all skill levels to leverage unique AM geometries when creating new designs. To execute such an approach, a database of files was acquired from industry-sponsored AM challenges focused on lightweight design. These files were converted to a voxelized format, which provides more robust information for machine learning applications. Next, an autoencoder was constructed to a low-dimensional representation of the part designs. Finally, that autoencoder was used to construct a deep neural network capable of predicting various DfAM attributes. This work demonstrates a novel foray towards a more extensive DfAM support system that supports designers at all experience levels.}, author = {Christian Murphy and Nicholas A Meisel and Timothy W Simpson and Christopher McComb}, citation = {29th Annual International Solid Freeform Fabrication Symposium, 2018}, conference = {29th Annual International Solid Freeform Fabrication Symposium}, pub_year = {2018}, title = {Using Autoencoded Voxel Patterns To Predict Part Mass, Required Support Material, and Build Time} }
{ "ENTRYTYPE": "article", "ID": "murphy2018usingautoencodedvoxel", "abstract": "Additive Manufacturing (AM) allows designers to create intricate geometries that were once too complex or expensive to achieve through traditional manufacturing processes. Currently, designing parts using features specific to AM, commonly referred to as Design for Additive Manufacturing (DfAM), is restricted to experts in the field. As a result novices in industry may overlook potentially transformational design potential enabled by AM. This project aims to automate DfAM through deep learning making it accessible to a broader audience, and enabling designers of all skill levels to leverage unique AM geometries when creating new designs. To execute such an approach, a database of files was acquired from industry-sponsored AM challenges focused on lightweight design. These files were converted to a voxelized format, which provides more robust information for machine learning applications. Next, an autoencoder was constructed to a low-dimensional representation of the part designs. Finally, that autoencoder was used to construct a deep neural network capable of predicting various DfAM attributes. This work demonstrates a novel foray towards a more extensive DfAM support system that supports designers at all experience levels.", "author": "Christian Murphy and Nicholas A Meisel and Timothy W Simpson and Christopher McComb", "citation": "29th Annual International Solid Freeform Fabrication Symposium, 2018", "conference": "29th Annual International Solid Freeform Fabrication Symposium", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Using Autoencoded Voxel Patterns To Predict Part Mass, Required Support Material, and Build Time", "volume": null }
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/scholar?hl=en&cites=5897559700544115889,12210029693594976159
[ "5897559700544115889", "12210029693594976159" ]
https://repositories.lib.utexas.edu/items/8fe19724-ec9d-4fa9-ba5e-48e701726508
/scholar?oi=bibs&hl=en&q=related:sVSXEE1X2FEJ:scholar.google.com/
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@article{song2022whenfacedwith, abstract = {As artificial intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants’ design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study are analyzed to assess the design process and effectiveness using quantitative methods, such as hidden Markov models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but …}, author = {Binyang Song and Nicolas F Soria Zurita and Hannah Nolte and Harshika Singh and Jonathan Cagan and Christopher McComb}, citation = {Journal of Mechanical Design, 2022}, journal = {Journal of Mechanical Design}, pub_year = {2022}, title = {When faced with increasing complexity: The effectiveness of AI assistance for drone design} }
{ "ENTRYTYPE": "article", "ID": "song2022whenfacedwith", "abstract": "As artificial intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants’ design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study are analyzed to assess the design process and effectiveness using quantitative methods, such as hidden Markov models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but …", "author": "Binyang Song and Nicolas F Soria Zurita and Hannah Nolte and Harshika Singh and Jonathan Cagan and Christopher McComb", "citation": "Journal of Mechanical Design, 2022", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "When faced with increasing complexity: The effectiveness of AI assistance for drone design", "volume": null }
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/scholar?hl=en&cites=10123157834569502012
[ "10123157834569502012" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/144/2/021701/1114945
/scholar?oi=bibs&hl=en&q=related:PE26bmqufIwJ:scholar.google.com/
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@article{mccomb2022aconceptualframework, abstract = {The design community traditionally excels at multidisciplinary research efforts, integrating work from social science, engineering, computer science, and other disciplines. Simultaneously, design is also developing as a discipline in its own right. In order to balance a multidisciplinary 1 tradition against consolidation around a core set of disciplinary foundations, the design community must make intentional decisions about engaging in multidisciplinary research. Towards this end, we propose the Degrees of Disciplinarity Framework, a lingua franca for describing varying relationships between disciplines in a given research effort. We also introduce research archetypes in relation to this conceptual …}, author = {Christopher McComb and Kathryn Jablokow}, citation = {Design Studies, 2022}, journal = {Design Studies}, pub_year = {2022}, title = {A Conceptual Framework for Multidisciplinary Design Research with Example Application to Agent-Based Modeling} }
{ "ENTRYTYPE": "article", "ID": "mccomb2022aconceptualframework", "abstract": "The design community traditionally excels at multidisciplinary research efforts, integrating work from social science, engineering, computer science, and other disciplines. Simultaneously, design is also developing as a discipline in its own right. In order to balance a multidisciplinary 1 tradition against consolidation around a core set of disciplinary foundations, the design community must make intentional decisions about engaging in multidisciplinary research. Towards this end, we propose the Degrees of Disciplinarity Framework, a lingua franca for describing varying relationships between disciplines in a given research effort. We also introduce research archetypes in relation to this conceptual …", "author": "Christopher McComb and Kathryn Jablokow", "citation": "Design Studies, 2022", "conference": null, "journal": "Design Studies", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "A Conceptual Framework for Multidisciplinary Design Research with Example Application to Agent-Based Modeling", "volume": null }
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/scholar?hl=en&cites=2054999867637487909
[ "2054999867637487909" ]
https://www.sciencedirect.com/science/article/pii/S0142694X21000855
/scholar?oi=bibs&hl=en&q=related:JdkB5H3ThBwJ:scholar.google.com/
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@article{gyory2022humanversusartificial, abstract = {Managing the design process of teams has been shown to considerably improve problem-solving behaviors and resulting final outcomes. Automating this activity presents significant opportunities in delivering interventions that dynamically adapt to the state of a team in order to reap the most impact. In this work, an artificial intelligence (AI) agent is created to manage the design process of engineering teams in real time, tracking features of teams’ actions and communications during a complex design and path-planning task in multidisciplinary teams. Teams are also placed under the guidance of human process managers for comparison. Regarding outcomes, teams perform equally as well under both types of management, with trends toward even superior performance from the AI-managed teams. The managers’ intervention strategies and team perceptions of those strategies are also explored, illuminating …}, author = {Joshua T Gyory and Nicolas F Soria Zurita and Jay Martin and Corey Balon and Christopher McComb and Kenneth Kotovsky and Jonathan Cagan}, citation = {Journal of Mechanical Design, 2022}, journal = {Journal of Mechanical Design}, pub_year = {2022}, title = {Human versus Artificial Intelligence: A Data-Driven Approach to Real-Time Process Management During Complex Engineering Design} }
{ "ENTRYTYPE": "article", "ID": "gyory2022humanversusartificial", "abstract": "Managing the design process of teams has been shown to considerably improve problem-solving behaviors and resulting final outcomes. Automating this activity presents significant opportunities in delivering interventions that dynamically adapt to the state of a team in order to reap the most impact. In this work, an artificial intelligence (AI) agent is created to manage the design process of engineering teams in real time, tracking features of teams’ actions and communications during a complex design and path-planning task in multidisciplinary teams. Teams are also placed under the guidance of human process managers for comparison. Regarding outcomes, teams perform equally as well under both types of management, with trends toward even superior performance from the AI-managed teams. The managers’ intervention strategies and team perceptions of those strategies are also explored, illuminating …", "author": "Joshua T Gyory and Nicolas F Soria Zurita and Jay Martin and Corey Balon and Christopher McComb and Kenneth Kotovsky and Jonathan Cagan", "citation": "Journal of Mechanical Design, 2022", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Human versus Artificial Intelligence: A Data-Driven Approach to Real-Time Process Management During Complex Engineering Design", "volume": null }
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/scholar?hl=en&cites=4215114512571339010
[ "4215114512571339010" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/144/2/021405/1120421
/scholar?oi=bibs&hl=en&q=related:ApFoCVEYfzoJ:scholar.google.com/
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@article{goucher-lambert2019usinghiddenmarkov, abstract = {Recently, design researchers have begun to use neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) to understand a variety of cognitive processes relevant to design. However, common neuroimaging analysis techniques require significant assumptions relating temporal and spatial information during model formulation. In this work, we apply hidden Markov Models (HMM) in order to uncover patterns of brain activation in a design-relevant fMRI dataset. The underlying fMRI data comes from a prior research study in which participants generated solutions for twelve open-ended design problems from the literature. HMMs are generative models that are able to automatically infer the internal state characteristics of a process by observing state emissions. In this work, we demonstrate that distinct states can be extracted from the design ideation fMRI dataset, and that designers are likely to …}, author = {Kosa Goucher-Lambert and Christopher McComb}, citation = {International Conference on Engineering Design, 2019}, conference = {International Conference on Engineering Design}, pub_year = {2019}, title = {Using Hidden Markov Models to Uncover Underlying States in Neuroimaging Data for a Design Ideation Task} }
{ "ENTRYTYPE": "article", "ID": "goucher-lambert2019usinghiddenmarkov", "abstract": "Recently, design researchers have begun to use neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) to understand a variety of cognitive processes relevant to design. However, common neuroimaging analysis techniques require significant assumptions relating temporal and spatial information during model formulation. In this work, we apply hidden Markov Models (HMM) in order to uncover patterns of brain activation in a design-relevant fMRI dataset. The underlying fMRI data comes from a prior research study in which participants generated solutions for twelve open-ended design problems from the literature. HMMs are generative models that are able to automatically infer the internal state characteristics of a process by observing state emissions. In this work, we demonstrate that distinct states can be extracted from the design ideation fMRI dataset, and that designers are likely to …", "author": "Kosa Goucher-Lambert and Christopher McComb", "citation": "International Conference on Engineering Design, 2019", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Using Hidden Markov Models to Uncover Underlying States in Neuroimaging Data for a Design Ideation Task", "volume": null }
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/scholar?hl=en&cites=5818249137206786151
[ "5818249137206786151" ]
https://www.cambridge.org/core/journals/proceedings-of-the-international-conference-on-engineering-design/article/using-hidden-markov-models-to-uncover-underlying-states-in-neuroimaging-data-for-a-design-ideation-task/FFECA47BD9133021144EA4BF37D40BFA
/scholar?oi=bibs&hl=en&q=related:Z_jujcOSvlAJ:scholar.google.com/
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@article{krishnakumar2022usingworkplacethriving, abstract = {During the onset of the COVID‐19 crisis, universities rapidly pivoted to online formats and were often unable to adhere to the best practices of online learning highlighted in prior literature. It is well documented that a variety of barriers impeded “normal” educational practices.The purpose of this paper is to investigate the perceptions of first‐year engineering students enrolled in an introductory engineering design course during the rapid transition to online working environments. We view students' perceptions through the theoretical lens of workplace thriving theory, a framework that allowed us to capture aspects of education required for students to thrive in non‐optimum learning settings.This research employed semi‐structured interview methods with 13 students enrolled in an introductory engineering design course that relies on project‐based team learning. We …}, author = {Sandeep Krishnakumar and Torsten Maier and Catherine GP Berdanier and Sarah Ritter and Christopher McComb and Jessica Menold}, citation = {Journal of Engineering Education, 2022}, journal = {Journal of Engineering Education}, pub_year = {2022}, title = {Using Workplace Thriving Theory to Investigate First-Year Engineering Students’ Abilities to Thrive during the Transition to Online Learning due to COVID-19} }
{ "ENTRYTYPE": "article", "ID": "krishnakumar2022usingworkplacethriving", "abstract": "During the onset of the COVID‐19 crisis, universities rapidly pivoted to online formats and were often unable to adhere to the best practices of online learning highlighted in prior literature. It is well documented that a variety of barriers impeded “normal” educational practices.The purpose of this paper is to investigate the perceptions of first‐year engineering students enrolled in an introductory engineering design course during the rapid transition to online working environments. We view students' perceptions through the theoretical lens of workplace thriving theory, a framework that allowed us to capture aspects of education required for students to thrive in non‐optimum learning settings.This research employed semi‐structured interview methods with 13 students enrolled in an introductory engineering design course that relies on project‐based team learning. We …", "author": "Sandeep Krishnakumar and Torsten Maier and Catherine GP Berdanier and Sarah Ritter and Christopher McComb and Jessica Menold", "citation": "Journal of Engineering Education, 2022", "conference": null, "journal": "Journal of Engineering Education", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Using Workplace Thriving Theory to Investigate First-Year Engineering Students’ Abilities to Thrive during the Transition to Online Learning due to COVID-19", "volume": null }
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/scholar?hl=en&cites=10643487032490001201
[ "10643487032490001201" ]
https://onlinelibrary.wiley.com/doi/abs/10.1002/jee.20447
/scholar?oi=bibs&hl=en&q=related:MQMLfxBDtZMJ:scholar.google.com/
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@article{li2022usingphysics-informedgenerative, abstract = {Computational fluid dynamics (CFD) simulations are useful in the field of engineering design as they provide deep insights on product or system performance without the need to construct and test physical prototypes. However, they can be very computationally intensive to run. Machine learning methods have been shown to reconstruct high-resolution single-phase turbulent fluid flow simulations from low-resolution inputs. This offers a potential avenue towards alleviating computational cost in iterative engineering design applications. However, little work thus far has explored the application of machine learning image super-resolution methods to multiphase fluid flow (which is important for emerging fields such as marine hydrokinetic energy conversion). In this work, we apply a modified version of the super-resolution generative adversarial network (SRGAN) model to a multiphase turbulent fluid flow problem …}, author = {Matthew Li and Christopher McComb}, citation = {Journal of Computing and Information Science in Engineering, 2022}, journal = {Journal of Computing and Information Science in Engineering}, pub_year = {2022}, title = {Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations} }
{ "ENTRYTYPE": "article", "ID": "li2022usingphysics-informedgenerative", "abstract": "Computational fluid dynamics (CFD) simulations are useful in the field of engineering design as they provide deep insights on product or system performance without the need to construct and test physical prototypes. However, they can be very computationally intensive to run. Machine learning methods have been shown to reconstruct high-resolution single-phase turbulent fluid flow simulations from low-resolution inputs. This offers a potential avenue towards alleviating computational cost in iterative engineering design applications. However, little work thus far has explored the application of machine learning image super-resolution methods to multiphase fluid flow (which is important for emerging fields such as marine hydrokinetic energy conversion). In this work, we apply a modified version of the super-resolution generative adversarial network (SRGAN) model to a multiphase turbulent fluid flow problem …", "author": "Matthew Li and Christopher McComb", "citation": "Journal of Computing and Information Science in Engineering, 2022", "conference": null, "journal": "Journal of Computing and Information Science in Engineering", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations", "volume": null }
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/scholar?hl=en&cites=6987329233899323240
[ "6987329233899323240" ]
https://asmedigitalcollection.asme.org/computingengineering/article-abstract/22/4/044501/1133478
/scholar?oi=bibs&hl=en&q=related:aH9F8-r692AJ:scholar.google.com/
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@article{mccomb2018towardstherapid, abstract = {The design of a system commits a significant portion of the final cost of that system. Many computational approaches have been developed to assist designers in the analysis (e.g., computational fluid dynamics) and synthesis (e.g., topology optimization) of engineered systems.}, author = {Christopher McComb}, citation = {Eight International Conference on Design Computing and Cognition, 2018}, conference = {Eight International Conference on Design Computing and Cognition}, pub_year = {2018}, title = {Towards the Rapid Design of Engineered Systems Through Deep Neural Networks} }
{ "ENTRYTYPE": "article", "ID": "mccomb2018towardstherapid", "abstract": "The design of a system commits a significant portion of the final cost of that system. Many computational approaches have been developed to assist designers in the analysis (e.g., computational fluid dynamics) and synthesis (e.g., topology optimization) of engineered systems.", "author": "Christopher McComb", "citation": "Eight International Conference on Design Computing and Cognition, 2018", "conference": "Eight International Conference on Design Computing and Cognition", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Towards the Rapid Design of Engineered Systems Through Deep Neural Networks", "volume": null }
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/scholar?hl=en&cites=12473443512812928164
[ "12473443512812928164" ]
https://link.springer.com/chapter/10.1007/978-3-030-05363-5_1
/scholar?oi=bibs&hl=en&q=related:pHwdq8mSGq0J:scholar.google.com/
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@article{mehta2020miningdesignheuristics, abstract = {In this research, we collected eye-tracking data from nine engineering graduate students as they redesigned a traditionally manufactured part for additive manufacturing (AM). Final artifacts were assessed for manufacturability and quality of final design, and design behaviors were captured via the eye-tracking data. Statistical analysis of design behavior duration shows that participants with more than 3 years of industry experience spend significantly less time removing material and revising than those with less experience. Hidden Markov modeling (HMM) analysis of the design behaviors gives insight to the transitions between behaviors through which designers proceed. Findings show that high-performing designers proceeded through four behavioral states, smoothly transitioning between states. In contrast, low-performing designers roughly transitioned between states, with moderate transition probabilities …}, author = {Priyesh Mehta and Manoj Malviya and Christopher McComb and Guha Manogharan and Catherine GP Berdanier}, citation = {Journal of Mechanical Design 142 (12), 2020}, journal = {Journal of Mechanical Design}, number = {12}, pub_year = {2020}, publisher = {American Society of Mechanical Engineers Digital Collection}, title = {Mining Design Heuristics for Additive Manufacturing Via Eye-Tracking Methods and Hidden Markov Modeling}, volume = {142} }
{ "ENTRYTYPE": "article", "ID": "mehta2020miningdesignheuristics", "abstract": "In this research, we collected eye-tracking data from nine engineering graduate students as they redesigned a traditionally manufactured part for additive manufacturing (AM). Final artifacts were assessed for manufacturability and quality of final design, and design behaviors were captured via the eye-tracking data. Statistical analysis of design behavior duration shows that participants with more than 3 years of industry experience spend significantly less time removing material and revising than those with less experience. Hidden Markov modeling (HMM) analysis of the design behaviors gives insight to the transitions between behaviors through which designers proceed. Findings show that high-performing designers proceeded through four behavioral states, smoothly transitioning between states. In contrast, low-performing designers roughly transitioned between states, with moderate transition probabilities …", "author": "Priyesh Mehta and Manoj Malviya and Christopher McComb and Guha Manogharan and Catherine GP Berdanier", "citation": "Journal of Mechanical Design 142 (12), 2020", "conference": null, "journal": "Journal of Mechanical Design", "number": "12", "pages": null, "pub_year": 2020, "publisher": "American Society of Mechanical Engineers Digital Collection", "title": "Mining Design Heuristics for Additive Manufacturing Via Eye-Tracking Methods and Hidden Markov Modeling", "volume": "142" }
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/scholar?hl=en&cites=12651429260001919693
[ "12651429260001919693" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/142/12/124502/1086965
/scholar?oi=bibs&hl=en&q=related:zcJlv-Hnkq8J:scholar.google.com/
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@article{alzayed2020candesignteams, abstract = {Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has been invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes in the concept generation and selection stages of the design process. Therefore, the goal of the current study was to investigate the impact of team trait empathy on concept generation and selection in an engineering …}, author = {Mohammad Alsager Alzayed and Scarlett R Miller and Jessica Menold and Jacquelyn Huff and Christopher McComb}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {Can Design Teams Be Empathically Creative? A Simulation-Based Investigation on the Role of Team Empathy on Concept Generation and Selection} }
{ "ENTRYTYPE": "article", "ID": "alzayed2020candesignteams", "abstract": "Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has been invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes in the concept generation and selection stages of the design process. Therefore, the goal of the current study was to investigate the impact of team trait empathy on concept generation and selection in an engineering …", "author": "Mohammad Alsager Alzayed and Scarlett R Miller and Jessica Menold and Jacquelyn Huff and Christopher McComb", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Can Design Teams Be Empathically Creative? A Simulation-Based Investigation on the Role of Team Empathy on Concept Generation and Selection", "volume": null }
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/scholar?hl=en&cites=767391841868130843
[ "767391841868130843" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2020/1089999
/scholar?oi=bibs&hl=en&q=related:GyoVetBSpgoJ:scholar.google.com/
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@article{bayrak2021astrategicdecision-making, abstract = {Advances in artificial intelligence create new opportunities for computers to support humans as peers in hybrid teams in several complex problem-solving situations. This paper proposes a decision-making architecture for adaptively informing decisions in human-computer collaboration for large-scale competitive problems under dynamic environments. The proposed architecture integrates methods from sequence learning, model predictive control, and game theory. Computers in this architecture learn objectives and strategies from experimental data to support humans with strategic decisions while operational decisions are made by humans. The paper also presents data-driven methods for partitioning tasks among a team of computers in this architecture. The generalized methodology is illustrated on the real-time strategy game Starcraft II. The results from this application show that low-performing players can …}, author = {Alparslan Emrah Bayrak and Christopher McComb and Kenneth Kotovsky and Jonathan Cagan}, citation = {Decision Support Systems, 2021}, journal = {Decision Support Systems}, pub_year = {2021}, title = {A Strategic Decision-making Architecture Toward Hybrid Teams for Dynamic Competitive Problems} }
{ "ENTRYTYPE": "article", "ID": "bayrak2021astrategicdecision-making", "abstract": "Advances in artificial intelligence create new opportunities for computers to support humans as peers in hybrid teams in several complex problem-solving situations. This paper proposes a decision-making architecture for adaptively informing decisions in human-computer collaboration for large-scale competitive problems under dynamic environments. The proposed architecture integrates methods from sequence learning, model predictive control, and game theory. Computers in this architecture learn objectives and strategies from experimental data to support humans with strategic decisions while operational decisions are made by humans. The paper also presents data-driven methods for partitioning tasks among a team of computers in this architecture. The generalized methodology is illustrated on the real-time strategy game Starcraft II. The results from this application show that low-performing players can …", "author": "Alparslan Emrah Bayrak and Christopher McComb and Kenneth Kotovsky and Jonathan Cagan", "citation": "Decision Support Systems, 2021", "conference": null, "journal": "Decision Support Systems", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "A Strategic Decision-making Architecture Toward Hybrid Teams for Dynamic Competitive Problems", "volume": null }
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[ "16473698746400821994" ]
https://www.sciencedirect.com/science/article/pii/S0167923620302451
/scholar?oi=bibs&hl=en&q=related:6tIEfLpVnuQJ:scholar.google.com/
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@article{mccomb2016drawinginspirationfrom, abstract = {Insights uncovered by research in design cognition are often utilized to develop methods used by human designers; in this work, such insights are used to inform and improve computational methodologies. This paper introduces the heterogeneous simulated annealing team (HSAT) algorithm, a multiagent simulated annealing (MSA) algorithm. HSAT is based on a validated computational model of human-based engineering design and retains characteristics of the model that structure interaction between team members and allow for heterogeneous search strategies to be employed within a team. The performance of this new algorithm is compared to several other simulated annealing (SA) based algorithms on three carefully selected benchmarking functions. The HSAT algorithm provides terminal solutions that are better on average than other algorithms explored in this work.}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Journal of Mechanical Design, 2016}, journal = {Journal of Mechanical Design}, pub_year = {2016}, title = {Drawing Inspiration From Human Design Teams For Better Search And Optimization: The Heterogeneous Simulated Annealing Teams Algorithm} }
{ "ENTRYTYPE": "article", "ID": "mccomb2016drawinginspirationfrom", "abstract": "Insights uncovered by research in design cognition are often utilized to develop methods used by human designers; in this work, such insights are used to inform and improve computational methodologies. This paper introduces the heterogeneous simulated annealing team (HSAT) algorithm, a multiagent simulated annealing (MSA) algorithm. HSAT is based on a validated computational model of human-based engineering design and retains characteristics of the model that structure interaction between team members and allow for heterogeneous search strategies to be employed within a team. The performance of this new algorithm is compared to several other simulated annealing (SA) based algorithms on three carefully selected benchmarking functions. The HSAT algorithm provides terminal solutions that are better on average than other algorithms explored in this work.", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Journal of Mechanical Design, 2016", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2016, "publisher": null, "title": "Drawing Inspiration From Human Design Teams For Better Search And Optimization: The Heterogeneous Simulated Annealing Teams Algorithm", "volume": null }
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/scholar?hl=en&cites=14575987028316016155
[ "14575987028316016155" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/138/4/044501/474807
/scholar?oi=bibs&hl=en&q=related:G056sflOSMoJ:scholar.google.com/
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@article{raina2022designstrategynetwork:, abstract = {Generative design problems often encompass complex action spaces that may be divergent over time, contain state-dependent constraints, or involve hybrid (discrete and continuous) domains. To address those challenges, this work introduces Design Strategy network (DSN), a data-driven deep hierarchical framework that can learn strategies over these arbitrary complex action spaces. The hierarchical architecture decomposes every action decision into first predicting a preferred spatial region in the design space and then outputting a probability distribution over a set of possible actions from that region. This framework comprises a convolutional encoder to work with image-based design state representations, a multi-layer perceptron to predict a spatial region, and a weight-sharing network to generate a probability distribution over unordered set-based inputs of feasible actions. Applied to a truss design study …}, author = {Ayush Raina and Jonathan Cagan and Christopher McComb}, citation = {Journal of Mechanical Design 144 (2), 021404, 2022}, journal = {Journal of Mechanical Design}, number = {2}, pages = {021404}, pub_year = {2022}, publisher = {American Society of Mechanical Engineers}, title = {Design strategy network: a deep hierarchical framework to represent generative design strategies in complex action spaces}, volume = {144} }
{ "ENTRYTYPE": "article", "ID": "raina2022designstrategynetwork:", "abstract": "Generative design problems often encompass complex action spaces that may be divergent over time, contain state-dependent constraints, or involve hybrid (discrete and continuous) domains. To address those challenges, this work introduces Design Strategy network (DSN), a data-driven deep hierarchical framework that can learn strategies over these arbitrary complex action spaces. The hierarchical architecture decomposes every action decision into first predicting a preferred spatial region in the design space and then outputting a probability distribution over a set of possible actions from that region. This framework comprises a convolutional encoder to work with image-based design state representations, a multi-layer perceptron to predict a spatial region, and a weight-sharing network to generate a probability distribution over unordered set-based inputs of feasible actions. Applied to a truss design study …", "author": "Ayush Raina and Jonathan Cagan and Christopher McComb", "citation": "Journal of Mechanical Design 144 (2), 021404, 2022", "conference": null, "journal": "Journal of Mechanical Design", "number": "2", "pages": "021404", "pub_year": 2022, "publisher": "American Society of Mechanical Engineers", "title": "Design strategy network: a deep hierarchical framework to represent generative design strategies in complex action spaces", "volume": "144" }
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/scholar?hl=en&cites=18183872626828033344
[ "18183872626828033344" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/144/2/021404/1120713
/scholar?oi=bibs&hl=en&q=related:QL0I088XWvwJ:scholar.google.com/
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@article{alzayed2019expandingthesolution, abstract = {Product dissection has been highlighted as an effective means of interacting with example products in order to produce creative outcomes. While product dissection is often conducted as a team in engineering design education, the research on the effectiveness of product dissection activities has been primarily limited to individuals. Thus, the purpose of this study was to investigate the impact of the type(s) of product dissected in a team environment on encouraging creative design outcomes (variety, novelty, and quantity) and the underlying influence of educational level and dissection modality on these effects. This was accomplished through a computational simulation of 14,000 teams of noninteracting brainstorming individuals generated by a statistical bootstrapping technique using a design repository of 931 ideas generated by first-year and senior engineering students. The results of the study highlight the …}, author = {Mohammad Alsager Alzayed and Christopher McComb and Samuel T Hunter and Scarlett R Miller}, citation = {Journal of Mechanical Design 141 (3), 032001, 2019}, journal = {Journal of Mechanical Design}, number = {3}, pages = {032001}, pub_year = {2019}, publisher = {American Society of Mechanical Engineers}, title = {Expanding the Solution Space in Engineering Design Education: A Simulation-Based Investigation of Product Dissection}, volume = {141} }
{ "ENTRYTYPE": "article", "ID": "alzayed2019expandingthesolution", "abstract": "Product dissection has been highlighted as an effective means of interacting with example products in order to produce creative outcomes. While product dissection is often conducted as a team in engineering design education, the research on the effectiveness of product dissection activities has been primarily limited to individuals. Thus, the purpose of this study was to investigate the impact of the type(s) of product dissected in a team environment on encouraging creative design outcomes (variety, novelty, and quantity) and the underlying influence of educational level and dissection modality on these effects. This was accomplished through a computational simulation of 14,000 teams of noninteracting brainstorming individuals generated by a statistical bootstrapping technique using a design repository of 931 ideas generated by first-year and senior engineering students. The results of the study highlight the …", "author": "Mohammad Alsager Alzayed and Christopher McComb and Samuel T Hunter and Scarlett R Miller", "citation": "Journal of Mechanical Design 141 (3), 032001, 2019", "conference": null, "journal": "Journal of Mechanical Design", "number": "3", "pages": "032001", "pub_year": 2019, "publisher": "American Society of Mechanical Engineers", "title": "Expanding the Solution Space in Engineering Design Education: A Simulation-Based Investigation of Product Dissection", "volume": "141" }
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[ "1920675074486201721" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/141/3/032001/368528
/scholar?oi=bibs&hl=en&q=related:eW2y182bpxoJ:scholar.google.com/
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@article{menold2018"thus,ihad, abstract = {Effectively communicating designs to stakeholders or end users is a critical step in the design process yet can be a difficult challenge for engineers. Prototypes are unique tools that can enhance communication between these two groups, as prototypes are physical manifestations of the designer’s mental model. Previous work has demonstrated that novice designers often struggle to use prototypes as communication tools. We argue that it is critical that engineering students learn to fully leverage prototypes, and thus the current work sought to understand the relationship between argumentation, prototyping, and design decisions. In order to understand the communication patterns of novice designers during a prototyping task, a controlled study was conducted with a total of 46 undergraduate engineering students. The analysis of quantitative and qualitative data point to the intricate linkages between how students …}, author = {Jessica Menold and Catherine GP Berdanier and Christopher McComb and Emma Hocker and Lisa Gardner}, citation = {ASME 2018 International Design Engineering Technical Conferences and …, 2018}, conference = {ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2018}, title = {"Thus, I had to go with what I had": A Multiple Methods Exploration of Novice Designers Articulation of Prototyping Decisions} }
{ "ENTRYTYPE": "article", "ID": "menold2018\"thus,ihad", "abstract": "Effectively communicating designs to stakeholders or end users is a critical step in the design process yet can be a difficult challenge for engineers. Prototypes are unique tools that can enhance communication between these two groups, as prototypes are physical manifestations of the designer’s mental model. Previous work has demonstrated that novice designers often struggle to use prototypes as communication tools. We argue that it is critical that engineering students learn to fully leverage prototypes, and thus the current work sought to understand the relationship between argumentation, prototyping, and design decisions. In order to understand the communication patterns of novice designers during a prototyping task, a controlled study was conducted with a total of 46 undergraduate engineering students. The analysis of quantitative and qualitative data point to the intricate linkages between how students …", "author": "Jessica Menold and Catherine GP Berdanier and Christopher McComb and Emma Hocker and Lisa Gardner", "citation": "ASME 2018 International Design Engineering Technical Conferences and …, 2018", "conference": "ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "\"Thus, I had to go with what I had\": A Multiple Methods Exploration of Novice Designers Articulation of Prototyping Decisions", "volume": null }
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/scholar?hl=en&cites=10885619709891820035
[ "10885619709891820035" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2018/51845/275222
/scholar?oi=bibs&hl=en&q=related:A7oXoHN9EZcJ:scholar.google.com/
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@article{ma2023conceptualdesigngeneration, abstract = {Concept generation is a creative step in the conceptual design phase, where designers often turn to brainstorming, mindmapping, or crowdsourcing design ideas to complement their own knowledge of the domain. Recent advances in natural language processing (NLP) and machine learning (ML) have led to the rise of Large Language Models (LLMs) capable of generating seemingly creative outputs from textual prompts. The success of these models has led to their integration and application across a variety of domains, including art, entertainment, and other creative work. In this paper, we leverage LLMs to generate solutions for a set of 12 design problems and compare them to a baseline of crowdsourced solutions. We evaluate the differences between generated and crowdsourced design solutions through multiple perspectives, including human expert evaluations and computational metrics. Expert …}, author = {Kevin Ma and Daniele Grande and Christopher McComb and Kosa Goucher-Lambert}, citation = {International Design Engineering Technical Conferences and Computers and …, 2023}, conference = {International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2023}, title = {Conceptual Design Generation Using Large Language Models} }
{ "ENTRYTYPE": "article", "ID": "ma2023conceptualdesigngeneration", "abstract": "Concept generation is a creative step in the conceptual design phase, where designers often turn to brainstorming, mindmapping, or crowdsourcing design ideas to complement their own knowledge of the domain. Recent advances in natural language processing (NLP) and machine learning (ML) have led to the rise of Large Language Models (LLMs) capable of generating seemingly creative outputs from textual prompts. The success of these models has led to their integration and application across a variety of domains, including art, entertainment, and other creative work. In this paper, we leverage LLMs to generate solutions for a set of 12 design problems and compare them to a baseline of crowdsourced solutions. We evaluate the differences between generated and crowdsourced design solutions through multiple perspectives, including human expert evaluations and computational metrics. Expert …", "author": "Kevin Ma and Daniele Grande and Christopher McComb and Kosa Goucher-Lambert", "citation": "International Design Engineering Technical Conferences and Computers and …, 2023", "conference": "International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2023, "publisher": null, "title": "Conceptual Design Generation Using Large Language Models", "volume": null }
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[ "16608122350620813083" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2023/87349/1170650
/scholar?oi=bibs&hl=en&q=related:G6f6xkjne-YJ:scholar.google.com/
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@article{allison2022artificialintelligenceand, abstract = {Artificial intelligence (AI) has had a strong presence in engineering design for decades, and while theory, methods, and tools for engineering design have advanced significantly during this time, many grand challenges remain. Modern advancements in AI, including new strategies for capturing, storing, and analyzing data, have the potential to revolutionize engineering design processes in a variety of ways. The purpose of this special issue is to consolidate recent research activities that utilize existing or new AI methods to advance engineering design knowledge and capabilities.During the conception of this special issue, we identified three core interfaces between the research domains of engineering design and AI:(1) leveraging AI methods directly in engineering design methods,(2) creating new AI capabilities that are inspired by unique challenges that arise in engineering design, and (3) creating and analyzing …}, author = {James T Allison and Michel-Alexandre Cardin and Chris McComb and Max Yi Ren and Daniel Selva and Conrad Tucker and Paul Witherell and Yaoyao Fiona Zhao}, citation = {Journal of Mechanical Design 144 (2), 020301, 2022}, journal = {Journal of Mechanical Design}, number = {2}, pages = {020301}, pub_year = {2022}, publisher = {American Society of Mechanical Engineers}, title = {Artificial intelligence and engineering design}, volume = {144} }
{ "ENTRYTYPE": "article", "ID": "allison2022artificialintelligenceand", "abstract": "Artificial intelligence (AI) has had a strong presence in engineering design for decades, and while theory, methods, and tools for engineering design have advanced significantly during this time, many grand challenges remain. Modern advancements in AI, including new strategies for capturing, storing, and analyzing data, have the potential to revolutionize engineering design processes in a variety of ways. The purpose of this special issue is to consolidate recent research activities that utilize existing or new AI methods to advance engineering design knowledge and capabilities.During the conception of this special issue, we identified three core interfaces between the research domains of engineering design and AI:(1) leveraging AI methods directly in engineering design methods,(2) creating new AI capabilities that are inspired by unique challenges that arise in engineering design, and (3) creating and analyzing …", "author": "James T Allison and Michel-Alexandre Cardin and Chris McComb and Max Yi Ren and Daniel Selva and Conrad Tucker and Paul Witherell and Yaoyao Fiona Zhao", "citation": "Journal of Mechanical Design 144 (2), 020301, 2022", "conference": null, "journal": "Journal of Mechanical Design", "number": "2", "pages": "020301", "pub_year": 2022, "publisher": "American Society of Mechanical Engineers", "title": "Artificial intelligence and engineering design", "volume": "144" }
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https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/144/2/020301/1128870
/scholar?oi=bibs&hl=en&q=related:2HZa9BJevTcJ:scholar.google.com/
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@article{raina2021goal-directeddesignagents:, abstract = {Engineering design problems often involve large state and action spaces along with highly sparse rewards. Since an exhaustive search of those spaces is not feasible, humans utilize relevant domain knowledge to condense the search space. Deep learning agents (DLAgents) were previously introduced to use visual imitation learning to model design domain knowledge. This note builds on DLAgents and integrates them with one-step lookahead search to develop goal-directed agents capable of enhancing learned strategies for sequentially generating designs. Goal-directed DLAgents can employ human strategies learned from data along with optimizing an objective function. The visual imitation network from DLAgents is composed of a convolutional encoder–decoder network, acting as a rough planning step that is agnostic to feedback. Meanwhile, the lookahead search identifies the fine-tuned design …}, author = {Ayush Raina and Lucas Puentes and Jonathan Cagan and Christopher McComb}, citation = {Journal of Mechanical Design, 2021}, journal = {Journal of Mechanical Design}, pub_year = {2021}, title = {Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design} }
{ "ENTRYTYPE": "article", "ID": "raina2021goal-directeddesignagents:", "abstract": "Engineering design problems often involve large state and action spaces along with highly sparse rewards. Since an exhaustive search of those spaces is not feasible, humans utilize relevant domain knowledge to condense the search space. Deep learning agents (DLAgents) were previously introduced to use visual imitation learning to model design domain knowledge. This note builds on DLAgents and integrates them with one-step lookahead search to develop goal-directed agents capable of enhancing learned strategies for sequentially generating designs. Goal-directed DLAgents can employ human strategies learned from data along with optimizing an objective function. The visual imitation network from DLAgents is composed of a convolutional encoder–decoder network, acting as a rough planning step that is agnostic to feedback. Meanwhile, the lookahead search identifies the fine-tuned design …", "author": "Ayush Raina and Lucas Puentes and Jonathan Cagan and Christopher McComb", "citation": "Journal of Mechanical Design, 2021", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design", "volume": null }
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/scholar?hl=en&cites=7567886418252839904
[ "7567886418252839904" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/143/12/124501/1108251
/scholar?oi=bibs&hl=en&q=related:4Lt23JmIBmkJ:scholar.google.com/
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@article{nolte2021thecognitiveexperience, abstract = {The engineering design process can produce stress that endures even after it has been completed. This may be particularly true for students who engage with the process as novices. However, it is not known how individual components of the design process induce stress in designers. This study explored the cognitive experience of introductory engineering design students during concept generation, concept selection and physical modelling to identify stress signatures for these three design activities. Data were collected for the design activities using pre- and post-task surveys. Each design activity produced distinct markers of cognitive experience and a unique stress signature that was stable across design activity themes. Rankings of perceived sources of stress also differed for each design activity. Students, however, did not perceive any physiological changes due to the stress of design for any of the design …}, author = {Hannah Nolte and Christopher McComb}, citation = {Design Science, 2021}, journal = {Design Science}, pub_year = {2021}, title = {The Cognitive Experience of Engineering Design: An Examination of First-Year Student Stress Across Principal Activities of the Engineering Design Process} }
{ "ENTRYTYPE": "article", "ID": "nolte2021thecognitiveexperience", "abstract": "The engineering design process can produce stress that endures even after it has been completed. This may be particularly true for students who engage with the process as novices. However, it is not known how individual components of the design process induce stress in designers. This study explored the cognitive experience of introductory engineering design students during concept generation, concept selection and physical modelling to identify stress signatures for these three design activities. Data were collected for the design activities using pre- and post-task surveys. Each design activity produced distinct markers of cognitive experience and a unique stress signature that was stable across design activity themes. Rankings of perceived sources of stress also differed for each design activity. Students, however, did not perceive any physiological changes due to the stress of design for any of the design …", "author": "Hannah Nolte and Christopher McComb", "citation": "Design Science, 2021", "conference": null, "journal": "Design Science", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "The Cognitive Experience of Engineering Design: An Examination of First-Year Student Stress Across Principal Activities of the Engineering Design Process", "volume": null }
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[ "16049121280087902778" ]
https://www.cambridge.org/core/journals/design-science/article/cognitive-experience-of-engineering-design-an-examination-of-firstyear-student-stress-across-principal-activities-of-the-engineering-design-process/70CCB9552DB79C845074F46476DC27DC
/scholar?oi=bibs&hl=en&q=related:OkrNuMXuud4J:scholar.google.com/
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@article{raina2018designstrategytransfer, abstract = {Planning and strategizing are essential parts of the design process and are based on the designer’s skill. Further, planning is an abstract skill that can be transferred between similar problems. However, planning and strategy transfer within design have not been effectively modeled within computational agents. This paper presents an approach to represent this strategizing behavior using a probabilistic model. This model is employed to select the operations that computational agents should perform while solving configuration design tasks. This work also demonstrates that this probabilistic model can be used to transfer strategies from human data to computational agents in a way that is general and useful. This study shows a successful transfer of design strategy from human-to-computer agents, opening up the possibility of deriving high-performing behavior from designers and using it to guide computational …}, author = {Ayush Raina and Christopher McComb and Jonathan Cagan}, citation = {ASME 2018 International Design Engineering Technical Conferences and …, 2018}, conference = {ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2018}, title = {Design Strategy Transfer in Cognitively-Inspired Agents} }
{ "ENTRYTYPE": "article", "ID": "raina2018designstrategytransfer", "abstract": "Planning and strategizing are essential parts of the design process and are based on the designer’s skill. Further, planning is an abstract skill that can be transferred between similar problems. However, planning and strategy transfer within design have not been effectively modeled within computational agents. This paper presents an approach to represent this strategizing behavior using a probabilistic model. This model is employed to select the operations that computational agents should perform while solving configuration design tasks. This work also demonstrates that this probabilistic model can be used to transfer strategies from human data to computational agents in a way that is general and useful. This study shows a successful transfer of design strategy from human-to-computer agents, opening up the possibility of deriving high-performing behavior from designers and using it to guide computational …", "author": "Ayush Raina and Christopher McComb and Jonathan Cagan", "citation": "ASME 2018 International Design Engineering Technical Conferences and …, 2018", "conference": "ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Design Strategy Transfer in Cognitively-Inspired Agents", "volume": null }
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/scholar?hl=en&cites=17511203523048823620,4406218285409000388
[ "17511203523048823620", "4406218285409000388" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2018/V02AT03A018/273533
/scholar?oi=bibs&hl=en&q=related:RNvkbNNKBPMJ:scholar.google.com/
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@article{mccomb2017impossiblebydesign?, abstract = {The design process often requires work by teams, rather than individuals. During team based design it is likely that situations will arise in which individual members of the team have different opinions, yet a group decision must still be made. Unfortunately, Arrow’s impossibility theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of ‘fair’ conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow’s conditions, enabling decisions that are fairer in practice. First, experiential conjoint analysis was used to obtain individual empirical utility functions for drinking mug designs. Each empirical utility function represented individual members who were part of a design team. Then, a number of functions for constructing group preference were analysed using both randomly generated preferences and …}, author = {Christopher McComb and Kosa Goucher-Lambert and Jonathan Cagan}, citation = {Design Science, 2017}, journal = {Design Science}, pub_year = {2017}, title = {Impossible by design? Fairness, strategy, and Arrow’s impossibility theorem} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017impossiblebydesign?", "abstract": "The design process often requires work by teams, rather than individuals. During team based design it is likely that situations will arise in which individual members of the team have different opinions, yet a group decision must still be made. Unfortunately, Arrow’s impossibility theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of ‘fair’ conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow’s conditions, enabling decisions that are fairer in practice. First, experiential conjoint analysis was used to obtain individual empirical utility functions for drinking mug designs. Each empirical utility function represented individual members who were part of a design team. Then, a number of functions for constructing group preference were analysed using both randomly generated preferences and …", "author": "Christopher McComb and Kosa Goucher-Lambert and Jonathan Cagan", "citation": "Design Science, 2017", "conference": null, "journal": "Design Science", "number": null, "pages": null, "pub_year": 2017, "publisher": null, "title": "Impossible by design? Fairness, strategy, and Arrow’s impossibility theorem", "volume": null }
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/scholar?hl=en&cites=4806877638445848792
[ "4806877638445848792" ]
https://www.cambridge.org/core/journals/design-science/article/impossible-by-design-fairness-strategy-and-arrows-impossibility-theorem/9B16982AADECD218D8ACC50560ADA39F
/scholar?oi=bibs&hl=en&q=related:2FhVhr51tUIJ:scholar.google.com/
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@article{agrawal2021amulti-agentreinforcement, abstract = {Intelligent manufacturing (IM) embraces Industry 4.0 design principles to advance autonomy and increase manufacturing efficiency. However, many IM systems are created ad hoc, which limits the potential for generalizable design principles and operational guidelines. This work offers a standardizing framework for integrated job scheduling and navigation control in an autonomous mobile robot driven shop floor, an increasingly common IM paradigm. We specifically propose a multi-agent framework involving mobile robots, machines, humans. Like any cyberphysical system, the performance of IM systems is influenced by the construction of the underlying software platforms and the choice of the constituent algorithms. In this work, we demonstrate the use of reinforcement learning on a sub-system of the proposed framework and test its effectiveness in a dynamic scenario. The case study demonstrates collaboration …}, author = {Akash Agrawal and Sung Jun Won and Tushar Sharma and Mayuri Deshpande and Christopher McComb}, citation = {International Conference on Engineering Design, 2021}, conference = {International Conference on Engineering Design}, pub_year = {2021}, title = {A Multi-Agent Reinforcement Learning Framework for Intelligent Manufacturing with Autonomous Mobile Robots} }
{ "ENTRYTYPE": "article", "ID": "agrawal2021amulti-agentreinforcement", "abstract": "Intelligent manufacturing (IM) embraces Industry 4.0 design principles to advance autonomy and increase manufacturing efficiency. However, many IM systems are created ad hoc, which limits the potential for generalizable design principles and operational guidelines. This work offers a standardizing framework for integrated job scheduling and navigation control in an autonomous mobile robot driven shop floor, an increasingly common IM paradigm. We specifically propose a multi-agent framework involving mobile robots, machines, humans. Like any cyberphysical system, the performance of IM systems is influenced by the construction of the underlying software platforms and the choice of the constituent algorithms. In this work, we demonstrate the use of reinforcement learning on a sub-system of the proposed framework and test its effectiveness in a dynamic scenario. The case study demonstrates collaboration …", "author": "Akash Agrawal and Sung Jun Won and Tushar Sharma and Mayuri Deshpande and Christopher McComb", "citation": "International Conference on Engineering Design, 2021", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "A Multi-Agent Reinforcement Learning Framework for Intelligent Manufacturing with Autonomous Mobile Robots", "volume": null }
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[ "11114364921501013765" ]
https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/multiagent-reinforcement-learning-framework-for-intelligent-manufacturing-with-autonomous-mobile-robots/0F7B7B8155187863776936E24B73E615
/scholar?oi=bibs&hl=en&q=related:BVchegIoPpoJ:scholar.google.com/
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@article{prakash2020detectionofsystem, abstract = {Three-dimensional printing systems have expanded the access to low cost, rapid methods for attaining physical prototypes or products. However, a cyber attack, system error, or operator error on a 3D-printing system may result in catastrophic situations, ranging from complete product failure, to small types of defects which weaken the structural integrity of the product. Such defects can be introduced early-on via solid models or through G-codes for printer movements at a later stage. Previous works have studied the use of image classifiers to predict defects in real-time and offline. However, a major restriction in the functionality of these methods is the availability of a dataset capturing diverse attacks on printed entities or the printing process. This paper introduces an image processing technique that analyzes the amplitude and phase variations of the print head platform arising through induced system …}, author = {Sakthi Kumar Arul Prakash and Tobias Mahan and Glen Williams and Christopher McComb and Jessica Menold and Conrad Tucker}, citation = {Journal of Mechanical Design, 2020}, journal = {Journal of Mechanical Design}, pub_year = {2020}, title = {Detection Of System Compromise In Additive Manufacturing Using Video Motion Magnification} }
{ "ENTRYTYPE": "article", "ID": "prakash2020detectionofsystem", "abstract": "Three-dimensional printing systems have expanded the access to low cost, rapid methods for attaining physical prototypes or products. However, a cyber attack, system error, or operator error on a 3D-printing system may result in catastrophic situations, ranging from complete product failure, to small types of defects which weaken the structural integrity of the product. Such defects can be introduced early-on via solid models or through G-codes for printer movements at a later stage. Previous works have studied the use of image classifiers to predict defects in real-time and offline. However, a major restriction in the functionality of these methods is the availability of a dataset capturing diverse attacks on printed entities or the printing process. This paper introduces an image processing technique that analyzes the amplitude and phase variations of the print head platform arising through induced system …", "author": "Sakthi Kumar Arul Prakash and Tobias Mahan and Glen Williams and Christopher McComb and Jessica Menold and Conrad Tucker", "citation": "Journal of Mechanical Design, 2020", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Detection Of System Compromise In Additive Manufacturing Using Video Motion Magnification", "volume": null }
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/scholar?hl=en&cites=9923887783675662480
[ "9923887783675662480" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/142/3/031109/1070435
/scholar?oi=bibs&hl=en&q=related:kJDTOFy7uIkJ:scholar.google.com/
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null
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@article{mahan2018pullingatthe, abstract = {While the combination of 3D scanning and printing processes holds much promise for the field of new product development, problems with repeatability and accuracy have limited the wider spread adoption of some digital prototyping tools, such as 3D scanners. Studies have explored the errors inherent in higher fidelity scan to print (S2P) processes, yet few have explored the errors in S2P processes that leverage affordable rapid noncontact scanners. Studies have yet to explore the strategies that designers, who are experienced with additive manufacturing, employ to mitigate errors. To address these gaps, a controlled study was conducted using data from 27 scans collected with a prototypical off-the-shelf noncontact optical scanner. The geometric and dimensional integrity of the digital models was found to be significantly out of tolerance at various phases of the S2P process, as compared to the original physical …}, author = {Tobias Mahan and Nicholas A Meisel and Christopher McComb and Jessica Menold}, citation = {Journal of Mechanical Design, 2018}, journal = {Journal of Mechanical Design}, pub_year = {2018}, title = {Pulling at the Digital Thread: Exploring the Tolerance Stack Up Between Automatic Procedures and Expert Strategies in Scan To Print Processes} }
{ "ENTRYTYPE": "article", "ID": "mahan2018pullingatthe", "abstract": "While the combination of 3D scanning and printing processes holds much promise for the field of new product development, problems with repeatability and accuracy have limited the wider spread adoption of some digital prototyping tools, such as 3D scanners. Studies have explored the errors inherent in higher fidelity scan to print (S2P) processes, yet few have explored the errors in S2P processes that leverage affordable rapid noncontact scanners. Studies have yet to explore the strategies that designers, who are experienced with additive manufacturing, employ to mitigate errors. To address these gaps, a controlled study was conducted using data from 27 scans collected with a prototypical off-the-shelf noncontact optical scanner. The geometric and dimensional integrity of the digital models was found to be significantly out of tolerance at various phases of the S2P process, as compared to the original physical …", "author": "Tobias Mahan and Nicholas A Meisel and Christopher McComb and Jessica Menold", "citation": "Journal of Mechanical Design, 2018", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Pulling at the Digital Thread: Exploring the Tolerance Stack Up Between Automatic Procedures and Expert Strategies in Scan To Print Processes", "volume": null }
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/scholar?hl=en&cites=14757624482993515171
[ "14757624482993515171" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/141/2/021701/368160
/scholar?oi=bibs&hl=en&q=related:o6pvLUedzcwJ:scholar.google.com/
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@article{krishnakumar2021lostintranslation:, abstract = {Prototyping plays a pivotal role in the engineering design process. Prototypes represent physical or digital manifestations of design ideas, and as such act as effective communication tools for designers. While the benefits of prototyping are well-documented in research, the fundamental ways in which the construction of a prototype affects designers' reflection on and evaluation of their design outcomes and processes are not well understood. The relationships between prototypes, designers' communication strategies, and recollection of design processes is of particular interest in this work, as preliminary research suggests that novice designers tend to struggle to clearly articulate the decisions made during the design process. This work serves to extend prior work and build foundational knowledge by exploring the evaluation of design outcomes and decisions, and communication strategies used by novice …}, author = {Sandeep Krishnakumar and Catherine GP Berdanier and Christopher McComb and Jessica Menold}, citation = {Journal of Mechanical Design, 2021}, journal = {Journal of Mechanical Design}, pub_year = {2021}, title = {Lost in Translation: Examining the Complex Relationship between Prototyping and Communication} }
{ "ENTRYTYPE": "article", "ID": "krishnakumar2021lostintranslation:", "abstract": "Prototyping plays a pivotal role in the engineering design process. Prototypes represent physical or digital manifestations of design ideas, and as such act as effective communication tools for designers. While the benefits of prototyping are well-documented in research, the fundamental ways in which the construction of a prototype affects designers' reflection on and evaluation of their design outcomes and processes are not well understood. The relationships between prototypes, designers' communication strategies, and recollection of design processes is of particular interest in this work, as preliminary research suggests that novice designers tend to struggle to clearly articulate the decisions made during the design process. This work serves to extend prior work and build foundational knowledge by exploring the evaluation of design outcomes and decisions, and communication strategies used by novice …", "author": "Sandeep Krishnakumar and Catherine GP Berdanier and Christopher McComb and Jessica Menold", "citation": "Journal of Mechanical Design, 2021", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Lost in Translation: Examining the Complex Relationship between Prototyping and Communication", "volume": null }
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https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/143/9/091402/1096697
/scholar?oi=bibs&hl=en&q=related:ykkW_8rQQcQJ:scholar.google.com/
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@article{lapp2019collaboratingwithstyle:, abstract = {Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members’ abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents’ cognitive styles with their roles can improve …}, author = {Samuel Lapp and Kathryn Jablokow and Christopher McComb}, citation = {ASME 2019 International Design Engineering Technical Conferences and …, 2019}, conference = {ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2019}, title = {Collaborating with Style: Using an Agent-Based Model to Simulate Cognitive Style Diversity in Problem Solving Teams} }
{ "ENTRYTYPE": "article", "ID": "lapp2019collaboratingwithstyle:", "abstract": "Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members’ abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents’ cognitive styles with their roles can improve …", "author": "Samuel Lapp and Kathryn Jablokow and Christopher McComb", "citation": "ASME 2019 International Design Engineering Technical Conferences and …, 2019", "conference": "ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Collaborating with Style: Using an Agent-Based Model to Simulate Cognitive Style Diversity in Problem Solving Teams", "volume": null }
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/scholar?hl=en&cites=4482463696792225885,10484576357907451325
[ "4482463696792225885", "10484576357907451325" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/V007T06A029/1070182
/scholar?oi=bibs&hl=en&q=related:XYjirfvoND4J:scholar.google.com/
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@article{maier2019ananalysisof, abstract = {Often, it is assumed that teams are better at solving problems than individuals working independently. However, recent work in engineering, design and psychology contradicts this assumption. This study aims to examine the behavior of teams engaged in data science competitions. Crowdsourced competitions have seen increased use for software development and data science, and platforms often encourage teamwork between participants.We specifically examine the teams participating in data science competitions hosted by Kaggle. We analyze the data provided by Kaggle to compare the effect of team size and interaction frequency on team performance. We also contextualize these results through a semantic analysis.This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small, interacting …}, author = {Torsten Maier and Joanna DeFranco and Christopher McComb}, citation = {Team Performance Management, 2019}, journal = {Team Performance Management}, pub_year = {2019}, title = {An Analysis of Design Process and Performance in Distributed Data Science Teams} }
{ "ENTRYTYPE": "article", "ID": "maier2019ananalysisof", "abstract": "Often, it is assumed that teams are better at solving problems than individuals working independently. However, recent work in engineering, design and psychology contradicts this assumption. This study aims to examine the behavior of teams engaged in data science competitions. Crowdsourced competitions have seen increased use for software development and data science, and platforms often encourage teamwork between participants.We specifically examine the teams participating in data science competitions hosted by Kaggle. We analyze the data provided by Kaggle to compare the effect of team size and interaction frequency on team performance. We also contextualize these results through a semantic analysis.This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small, interacting …", "author": "Torsten Maier and Joanna DeFranco and Christopher McComb", "citation": "Team Performance Management, 2019", "conference": null, "journal": "Team Performance Management", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "An Analysis of Design Process and Performance in Distributed Data Science Teams", "volume": null }
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/scholar?hl=en&cites=6218576995548106460,9877453235763099643
[ "6218576995548106460", "9877453235763099643" ]
https://www.emerald.com/insight/content/doi/10.1108/TPM-03-2019-0024/full/html
/scholar?oi=bibs&hl=en&q=related:3I4PfNTSTFYJ:scholar.google.com/
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@article{dhengre2020towardsenhancedcreativity, abstract = {With an increase in the number of mobile apps making their way to users, there is a growing need for tools to support the app design process. While many tools focus on increasing the pace of development, few attempt to aide the designer in generating more creative solutions. In this work, we take creativity as the combination of novelty and utility. Particularly during development of user interfaces, assessment of utility (primarily usability) is iterative, rigorous, and time-consuming. The objective of the proposed work is to explore and evaluate the use of machine learning to predict usability measures for mobile app interfaces as a means to automate usability evaluations. Specifically, a convolutional neural network (CNN) is used to accurately (nearly 90%) predict three usability measures: regularity, complexity, and touchability. This tool automates the assessment of utility in app design, freeing up the designer to seek designs that are novel and thus creative.}, author = {Snehal Dhengre and Jayant Mathur and Farzaneh Oghazian and Xiaomei Tan and Christopher McComb}, citation = {Proceedings of the 11th International Conference on Computational Creativity, 2020}, conference = {Proceedings of the 11th International Conference on Computational Creativity}, pub_year = {2020}, title = {Towards Enhanced Creativity in Interface Design through Automated Usability Evaluation} }
{ "ENTRYTYPE": "article", "ID": "dhengre2020towardsenhancedcreativity", "abstract": "With an increase in the number of mobile apps making their way to users, there is a growing need for tools to support the app design process. While many tools focus on increasing the pace of development, few attempt to aide the designer in generating more creative solutions. In this work, we take creativity as the combination of novelty and utility. Particularly during development of user interfaces, assessment of utility (primarily usability) is iterative, rigorous, and time-consuming. The objective of the proposed work is to explore and evaluate the use of machine learning to predict usability measures for mobile app interfaces as a means to automate usability evaluations. Specifically, a convolutional neural network (CNN) is used to accurately (nearly 90%) predict three usability measures: regularity, complexity, and touchability. This tool automates the assessment of utility in app design, freeing up the designer to seek designs that are novel and thus creative.", "author": "Snehal Dhengre and Jayant Mathur and Farzaneh Oghazian and Xiaomei Tan and Christopher McComb", "citation": "Proceedings of the 11th International Conference on Computational Creativity, 2020", "conference": "Proceedings of the 11th International Conference on Computational Creativity", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Towards Enhanced Creativity in Interface Design through Automated Usability Evaluation", "volume": null }
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[ "10202765011752470594" ]
https://computationalcreativity.net/iccc20/papers/114-iccc20.pdf
/scholar?oi=bibs&hl=en&q=related:QkhKvLiAl40J:scholar.google.com/
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@article{puentes2020modelingastrategic, abstract = {Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology presented in this paper brings together the visual nature of design problem solving and design heuristics in a deep learning computational agent framework that emulates and enables human-mirrored design. When applied to a truss design task, results demonstrate superior results to those of human designers who provided the initial data.}, author = {Lucas Puentes and Ayush Raina and Jonathan Cagan and Christohper McComb}, citation = {International Design Conference - DESIGN 2020, 2020}, conference = {International Design Conference - DESIGN 2020}, pub_year = {2020}, title = {Modeling a Strategic Human Engineering Design Process: Human-Inspired Heuristic Guidance Through Learned Visual Design Agents} }
{ "ENTRYTYPE": "article", "ID": "puentes2020modelingastrategic", "abstract": "Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology presented in this paper brings together the visual nature of design problem solving and design heuristics in a deep learning computational agent framework that emulates and enables human-mirrored design. When applied to a truss design task, results demonstrate superior results to those of human designers who provided the initial data.", "author": "Lucas Puentes and Ayush Raina and Jonathan Cagan and Christohper McComb", "citation": "International Design Conference - DESIGN 2020, 2020", "conference": "International Design Conference - DESIGN 2020", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Modeling a Strategic Human Engineering Design Process: Human-Inspired Heuristic Guidance Through Learned Visual Design Agents", "volume": null }
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[ "10811380153634319613" ]
https://www.cambridge.org/core/journals/proceedings-of-the-design-society-design-conference/article/modeling-a-strategic-human-engineering-design-process-humaninspired-heuristic-guidance-through-learned-visual-design-agents/DAFA3970B77748BA38699C40BDE2516D
/scholar?oi=bibs&hl=en&q=related:_ewU9fe8CZYJ:scholar.google.com/
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@article{puentes2019heuristic-guidedsolutionsearch, abstract = {Grammar-based design is typically a gradual process; incremental design changes are performed until a problem statement has been satisfied. While they offer an effective means for searching a design space, standard grammars risk being computationally costly because of the iteration required, and the larger a given grammar the broader the search required. This paper proposes a two-tiered design grammar that enhances the computational design generation with generalized heuristics to provide a way to more efficiently search a design space. Specifically, this two-tiered grammar captures a combination of heuristic-based strategic actions (often observed in human designers) and smaller-scale modifications (common in traditional grammars). Rules in the higher tier are abstract and applicable across multiple design domains. Through associated guiding heuristics, these macrorules are translated down …}, author = {Lucas Puentes and Jonathan Cagan and Christopher McComb}, citation = {Journal of Computing and Information Science in Engineering, 2019}, journal = {Journal of Computing and Information Science in Engineering}, pub_year = {2019}, title = {Heuristic-Guided Solution Search through a Two-Tiered Design Grammar} }
{ "ENTRYTYPE": "article", "ID": "puentes2019heuristic-guidedsolutionsearch", "abstract": "Grammar-based design is typically a gradual process; incremental design changes are performed until a problem statement has been satisfied. While they offer an effective means for searching a design space, standard grammars risk being computationally costly because of the iteration required, and the larger a given grammar the broader the search required. This paper proposes a two-tiered design grammar that enhances the computational design generation with generalized heuristics to provide a way to more efficiently search a design space. Specifically, this two-tiered grammar captures a combination of heuristic-based strategic actions (often observed in human designers) and smaller-scale modifications (common in traditional grammars). Rules in the higher tier are abstract and applicable across multiple design domains. Through associated guiding heuristics, these macrorules are translated down …", "author": "Lucas Puentes and Jonathan Cagan and Christopher McComb", "citation": "Journal of Computing and Information Science in Engineering, 2019", "conference": null, "journal": "Journal of Computing and Information Science in Engineering", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Heuristic-Guided Solution Search through a Two-Tiered Design Grammar", "volume": null }
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/scholar?hl=en&cites=2460005216547535582
[ "2460005216547535582" ]
https://asmedigitalcollection.asme.org/computingengineering/article-abstract/20/1/011008/960539
/scholar?oi=bibs&hl=en&q=related:3nrs9bWxIyIJ:scholar.google.com/
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@article{berdanier2018opportunitiesfornatural, abstract = {This research full paper proposes opportunities to expand qualitative and textual data analysis using natural language processing (NLP), and demonstrates opportunities to use NLP in engineering education work in our presentation of two NLP-based projects as examples of how NLP can be used. The discipline of engineering education frequently employs qualitative data analysis techniques, but fundamentally, the analysis of large corpora of textual documents is limited by researcher's time. In this paper, we present a brief review literature of how NLP has been used in other qualitative research fields. This portion of the paper is aimed to provide a clear description of NLP for those unfamiliar with machine learning and natural language processing methods. The second part of the paper will provide two brief examples of how NLP is being employed in our research group. Example 1 is a study of engineering …}, author = {Catherine GP Berdanier and Eric Baker and Weiqin Wang and Christopher McComb}, citation = {IEEE Frontiers in Education Conference, 2018}, conference = {IEEE Frontiers in Education Conference}, pub_year = {2018}, title = {Opportunities for Natural Language Processing in Qualitative Engineering Education Research: Two Examples} }
{ "ENTRYTYPE": "article", "ID": "berdanier2018opportunitiesfornatural", "abstract": "This research full paper proposes opportunities to expand qualitative and textual data analysis using natural language processing (NLP), and demonstrates opportunities to use NLP in engineering education work in our presentation of two NLP-based projects as examples of how NLP can be used. The discipline of engineering education frequently employs qualitative data analysis techniques, but fundamentally, the analysis of large corpora of textual documents is limited by researcher's time. In this paper, we present a brief review literature of how NLP has been used in other qualitative research fields. This portion of the paper is aimed to provide a clear description of NLP for those unfamiliar with machine learning and natural language processing methods. The second part of the paper will provide two brief examples of how NLP is being employed in our research group. Example 1 is a study of engineering …", "author": "Catherine GP Berdanier and Eric Baker and Weiqin Wang and Christopher McComb", "citation": "IEEE Frontiers in Education Conference, 2018", "conference": "IEEE Frontiers in Education Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Opportunities for Natural Language Processing in Qualitative Engineering Education Research: Two Examples", "volume": null }
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/scholar?hl=en&cites=2792500118781780028
[ "2792500118781780028" ]
https://ieeexplore.ieee.org/abstract/document/8658747/
/scholar?oi=bibs&hl=en&q=related:PGA5DxD0wCYJ:scholar.google.com/
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@article{mccomb2018dataonthe, abstract = {This experiment was conducted in order to compare different approaches that human teams use to solve design problems that change dynamically during solving. Specifically, study participants were given the task of designing a truss structure (similar to a bridge spanning a chasm) in teams of three. At two points during design, the problem statement was changed unexpectedly, requiring participants to adapt. Two conditions were given different initial problem representations. During the study, every participant had access to a computer interface that allowed them to construct, test, and share solutions. The interface also made it possible to collect a step-by-step log of the actions made by participants during the study. This article contains data collected from 48 participants (16 teams). This data has been used previously in behavioral analyses, sequence-based analysis, and development of computational models.}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Data in Brief, 2018}, journal = {Data in Brief}, pub_year = {2018}, title = {Data on the Design of Truss Structures by Teams of Engineering Students} }
{ "ENTRYTYPE": "article", "ID": "mccomb2018dataonthe", "abstract": "This experiment was conducted in order to compare different approaches that human teams use to solve design problems that change dynamically during solving. Specifically, study participants were given the task of designing a truss structure (similar to a bridge spanning a chasm) in teams of three. At two points during design, the problem statement was changed unexpectedly, requiring participants to adapt. Two conditions were given different initial problem representations. During the study, every participant had access to a computer interface that allowed them to construct, test, and share solutions. The interface also made it possible to collect a step-by-step log of the actions made by participants during the study. This article contains data collected from 48 participants (16 teams). This data has been used previously in behavioral analyses, sequence-based analysis, and development of computational models.", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Data in Brief, 2018", "conference": null, "journal": "Data in Brief", "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Data on the Design of Truss Structures by Teams of Engineering Students", "volume": null }
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/scholar?hl=en&cites=10778446860037770150
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https://www.sciencedirect.com/science/article/pii/S2352340918302014
/scholar?oi=bibs&hl=en&q=related:psv5AlC8lJUJ:scholar.google.com/
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@article{liew2022synthesisofphysical, abstract = {Recent permafrost degradation across the high northern latitude regions has impacted the performance of the civil infrastructure. This study summarizes the current state of physical processes of permafrost degradation in a geotechnical context and the properties of permafrost-affected soils critical for evaluating the performance of infrastructures commonly built in the high northern latitude regions. We collected a total of 96 datasets with 3162 data points from 38 journal and conference publications and analyzed the variations of geomechanical and geophysical properties under the effects of permafrost degradation. The datasets represent a range of geomechanical and geophysical properties of permafrost-affected soils with different compositions under different testing conditions. While the data collected are highly scattered, regression analysis shows that most geomechanical and geophysical properties have …}, author = {Min Liew and Xiaohang Ji and Ming Xiao and Louise Farquharson and Dmitry Nicolsky and Vladimir Romanovsky and Matthew Bray and Xiong Zhang and Christopher McComb}, citation = {Cold Regions Science and Technology 198, 103522, 2022}, journal = {Cold Regions Science and Technology}, pages = {103522}, pub_year = {2022}, publisher = {Elsevier}, title = {Synthesis of physical processes of permafrost degradation and geophysical and geomechanical properties of permafrost}, volume = {198} }
{ "ENTRYTYPE": "article", "ID": "liew2022synthesisofphysical", "abstract": "Recent permafrost degradation across the high northern latitude regions has impacted the performance of the civil infrastructure. This study summarizes the current state of physical processes of permafrost degradation in a geotechnical context and the properties of permafrost-affected soils critical for evaluating the performance of infrastructures commonly built in the high northern latitude regions. We collected a total of 96 datasets with 3162 data points from 38 journal and conference publications and analyzed the variations of geomechanical and geophysical properties under the effects of permafrost degradation. The datasets represent a range of geomechanical and geophysical properties of permafrost-affected soils with different compositions under different testing conditions. While the data collected are highly scattered, regression analysis shows that most geomechanical and geophysical properties have …", "author": "Min Liew and Xiaohang Ji and Ming Xiao and Louise Farquharson and Dmitry Nicolsky and Vladimir Romanovsky and Matthew Bray and Xiong Zhang and Christopher McComb", "citation": "Cold Regions Science and Technology 198, 103522, 2022", "conference": null, "journal": "Cold Regions Science and Technology", "number": null, "pages": "103522", "pub_year": 2022, "publisher": "Elsevier", "title": "Synthesis of physical processes of permafrost degradation and geophysical and geomechanical properties of permafrost", "volume": "198" }
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/scholar?hl=en&cites=13289041947279055398
[ "13289041947279055398" ]
https://www.sciencedirect.com/science/article/pii/S0165232X22000416
/scholar?oi=bibs&hl=en&q=related:JlrVID4pbLgJ:scholar.google.com/
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@article{krishnakumar2022thestorynovice, abstract = {Communication with external audiences is a critical task within the design process. Yet, we lack fundamental knowledge about how designers communicate design solutions and decisions to such audiences. This is particularly problematic for novice designers, as without such knowledge, we cannot develop pedagogical interventions to train novices as effective communicators. In this work, we study two strategies used by novices to communicate design knowledge–argumentation and prototypes. Through a move analysis and Markov modelling, we identified six unique rhetorical moves and how novices transitioned between them. We also identified several …}, author = {Sandeep Krishnakumar and Catherine GP Berdanier and Carlye Lauff and Christopher McComb and Jessica Menold}, citation = {Design Studies 82, 2022}, journal = {Design Studies}, pub_year = {2022}, title = {The story novice designers tell: How rhetorical structures and prototyping shape communication with external audiences}, volume = {82} }
{ "ENTRYTYPE": "article", "ID": "krishnakumar2022thestorynovice", "abstract": "Communication with external audiences is a critical task within the design process. Yet, we lack fundamental knowledge about how designers communicate design solutions and decisions to such audiences. This is particularly problematic for novice designers, as without such knowledge, we cannot develop pedagogical interventions to train novices as effective communicators. In this work, we study two strategies used by novices to communicate design knowledge–argumentation and prototypes. Through a move analysis and Markov modelling, we identified six unique rhetorical moves and how novices transitioned between them. We also identified several …", "author": "Sandeep Krishnakumar and Catherine GP Berdanier and Carlye Lauff and Christopher McComb and Jessica Menold", "citation": "Design Studies 82, 2022", "conference": null, "journal": "Design Studies", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "The story novice designers tell: How rhetorical structures and prototyping shape communication with external audiences", "volume": "82" }
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/scholar?hl=en&cites=13741268919544309896
[ "13741268919544309896" ]
https://www.sciencedirect.com/science/article/pii/S0142694X22000539
/scholar?oi=bibs&hl=en&q=related:iOiNKEfLsr4J:scholar.google.com/
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@article{alzayed2020doesempathybeget, abstract = {The ability to understand and feel the needs and circumstances of others, also known as empathy, has been found to help engineering designers develop a deeper understanding of the design problems they solve. While prior work has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer’s empathic tendencies in driving creative idea generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in a humanitarian engineering design student project. In order to achieve this, a study was conducted with 103 first-year engineering students during three design stages of an 8-week design project (problem formulation, concept …}, author = {Mohammad Alsager Alzayed and Scarlett R Miller and Christopher McComb}, citation = {Design Computing and Cognition’20, 437, 2020}, journal = {Design Computing and Cognition’20}, pages = {437}, pub_year = {2020}, publisher = {Springer Nature}, title = {Does Empathy Beget Creativity? Investigating the Role of Trait Empathy in Idea Generation and Selection} }
{ "ENTRYTYPE": "article", "ID": "alzayed2020doesempathybeget", "abstract": "The ability to understand and feel the needs and circumstances of others, also known as empathy, has been found to help engineering designers develop a deeper understanding of the design problems they solve. While prior work has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer’s empathic tendencies in driving creative idea generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in a humanitarian engineering design student project. In order to achieve this, a study was conducted with 103 first-year engineering students during three design stages of an 8-week design project (problem formulation, concept …", "author": "Mohammad Alsager Alzayed and Scarlett R Miller and Christopher McComb", "citation": "Design Computing and Cognition’20, 437, 2020", "conference": null, "journal": "Design Computing and Cognition’20", "number": null, "pages": "437", "pub_year": 2020, "publisher": "Springer Nature", "title": "Does Empathy Beget Creativity? Investigating the Role of Trait Empathy in Idea Generation and Selection", "volume": null }
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https://link.springer.com/chapter/10.1007/978-3-030-90625-2_26
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@article{khanolkar2020predictingelasticstrain, abstract = {In this work, an image colorization algorithm based on convolutional neural networks is explored as an approach to predict tensile plane-strain field components of microstructures featuring porosity defects. For the same, microstructures featuring porosity of various shapes, sizes, area fractions and number densities were sampled on the gage section of ASTM-E8 sized numerical specimens whose tensile deformation was simulated in plane strain mode using commercial finite element analysis package Abaqus. Subsequently, the image colorization algorithm was trained by treating the microstructure featuring porosity defects as the gray scale image, and its strain field components as its color layers, analogous to the red-green-blue color components of traditional digital representations of images. Towards the same, various CNN frameworks were tested for optimization of its parameters, viz. number of layers, number …}, author = {Pranav Milind Khanolkar and Christopher McComb and Saurabh Basu}, citation = {Computational Material Science, 2020}, journal = {Computational Material Science}, pub_year = {2020}, title = {Predicting Elastic Strain Fields in Defective Microstructures using Image Colorization Algorithms} }
{ "ENTRYTYPE": "article", "ID": "khanolkar2020predictingelasticstrain", "abstract": "In this work, an image colorization algorithm based on convolutional neural networks is explored as an approach to predict tensile plane-strain field components of microstructures featuring porosity defects. For the same, microstructures featuring porosity of various shapes, sizes, area fractions and number densities were sampled on the gage section of ASTM-E8 sized numerical specimens whose tensile deformation was simulated in plane strain mode using commercial finite element analysis package Abaqus. Subsequently, the image colorization algorithm was trained by treating the microstructure featuring porosity defects as the gray scale image, and its strain field components as its color layers, analogous to the red-green-blue color components of traditional digital representations of images. Towards the same, various CNN frameworks were tested for optimization of its parameters, viz. number of layers, number …", "author": "Pranav Milind Khanolkar and Christopher McComb and Saurabh Basu", "citation": "Computational Material Science, 2020", "conference": null, "journal": "Computational Material Science", "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Predicting Elastic Strain Fields in Defective Microstructures using Image Colorization Algorithms", "volume": null }
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/scholar?hl=en&cites=13991899780223692101
[ "13991899780223692101" ]
https://www.sciencedirect.com/science/article/pii/S0927025620305590
/scholar?oi=bibs&hl=en&q=related:RW0Zxbc2LcIJ:scholar.google.com/
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@article{berdanier2020naturallanguageprocessing, abstract = {This research paper presents recent work exploring the power of natural language processing (NLP) methods applied to qualitative engineering education data. As NLP and other machine learning methods are developed for qualitative data, it is important to prioritize the role that theory plays in rigorous qualitative research, where the selection of a theoretical framework serves as the lens by which the research project is framed, results are analyzed, and findings are brought to light. Indeed, the view from a different theoretical lens can highlight novel or new findings. In this work, we seek to explore the viability of NLP methods for helping researchers select appropriate frameworks. In this work, we present our method to train a Python-based NLP algorithm to analyze an existing data set of interview data using one theoretical lens: Community of Practice theory, an oft-used theory in graduate education literature, which …}, author = {Catherine GP Berdanier and Christopher McComb and Weiwei Zhu}, citation = {IEEE Frontiers in Education Conference, 2020}, conference = {IEEE Frontiers in Education Conference}, pub_year = {2020}, title = {Natural Language Processing for Theoretical Framework Selection in Engineering Education Research} }
{ "ENTRYTYPE": "article", "ID": "berdanier2020naturallanguageprocessing", "abstract": "This research paper presents recent work exploring the power of natural language processing (NLP) methods applied to qualitative engineering education data. As NLP and other machine learning methods are developed for qualitative data, it is important to prioritize the role that theory plays in rigorous qualitative research, where the selection of a theoretical framework serves as the lens by which the research project is framed, results are analyzed, and findings are brought to light. Indeed, the view from a different theoretical lens can highlight novel or new findings. In this work, we seek to explore the viability of NLP methods for helping researchers select appropriate frameworks. In this work, we present our method to train a Python-based NLP algorithm to analyze an existing data set of interview data using one theoretical lens: Community of Practice theory, an oft-used theory in graduate education literature, which …", "author": "Catherine GP Berdanier and Christopher McComb and Weiwei Zhu", "citation": "IEEE Frontiers in Education Conference, 2020", "conference": "IEEE Frontiers in Education Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Natural Language Processing for Theoretical Framework Selection in Engineering Education Research", "volume": null }
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/scholar?hl=en&cites=14089298827769655560
[ "14089298827769655560" ]
https://ieeexplore.ieee.org/abstract/document/9274115/
/scholar?oi=bibs&hl=en&q=related:CLGJs6I-h8MJ:scholar.google.com/
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0.8623071908950806 ]
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@article{maier2020analyzingthecharacteristics, abstract = {The rapid digitalization of the world has affected engineering and design in a variety of ways, including the introduction of new computer-aided ideation tools. Cognitive assistants (CA), an increasingly common digital technology, use natural-language processing and artificial intelligence to provide computational support. Because cognitive assistants are capable of emulating humans in some tasks, they may be suited to support brainstorming activities when trained coaches or facilitators are not available. This study compared co-located brainstorming groups facilitated by human facilitators and a CA facilitator. Interaction Dynamics Notation was used to code the sessions, and Hidden Markov Models were used to define the group’s states. We found that human facilitation was associated with blocks/interruptions and responding to those while cognitive assistant facilitation was associated with deviations and …}, author = {Torsten Maier and Nicolas F Soria Zurita and Elizabeth Starkey and Daniel Spillane and Jessica Menold and Christopher McComb}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {Analyzing the Characteristics of Cognitive-Assistant-Facilitated Ideation Groups} }
{ "ENTRYTYPE": "article", "ID": "maier2020analyzingthecharacteristics", "abstract": "The rapid digitalization of the world has affected engineering and design in a variety of ways, including the introduction of new computer-aided ideation tools. Cognitive assistants (CA), an increasingly common digital technology, use natural-language processing and artificial intelligence to provide computational support. Because cognitive assistants are capable of emulating humans in some tasks, they may be suited to support brainstorming activities when trained coaches or facilitators are not available. This study compared co-located brainstorming groups facilitated by human facilitators and a CA facilitator. Interaction Dynamics Notation was used to code the sessions, and Hidden Markov Models were used to define the group’s states. We found that human facilitation was associated with blocks/interruptions and responding to those while cognitive assistant facilitation was associated with deviations and …", "author": "Torsten Maier and Nicolas F Soria Zurita and Elizabeth Starkey and Daniel Spillane and Jessica Menold and Christopher McComb", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Analyzing the Characteristics of Cognitive-Assistant-Facilitated Ideation Groups", "volume": null }
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/scholar?hl=en&cites=7373884721806825080
[ "7373884721806825080" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2020/83976/1090006
/scholar?oi=bibs&hl=en&q=related:eNb5ARZNVWYJ:scholar.google.com/
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@article{nelson2019theprototypingbehaviors, abstract = {Prototyping is a crucial part of new product development, and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best …}, author = {Jacob Nelson and Tobias Mahan and Christopher McComb and Jessica Menold}, citation = {Journal of Mechanical Design, 2019}, journal = {Journal of Mechanical Design}, pub_year = {2019}, title = {The Prototyping Behaviors of Startups: Exploring the Relationship Between Prototyping Behaviors and Startup Strategies} }
{ "ENTRYTYPE": "article", "ID": "nelson2019theprototypingbehaviors", "abstract": "Prototyping is a crucial part of new product development, and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best …", "author": "Jacob Nelson and Tobias Mahan and Christopher McComb and Jessica Menold", "citation": "Journal of Mechanical Design, 2019", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "The Prototyping Behaviors of Startups: Exploring the Relationship Between Prototyping Behaviors and Startup Strategies", "volume": null }
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https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/142/3/031107/1069610
/scholar?oi=bibs&hl=en&q=related:VfmdJoz-INoJ:scholar.google.com/
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@article{ostrander2019acomparativestudy, abstract = {Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantages over traditional computer-aided design (CAD) tools, and these advantages may be more evident as designs become more complex. The following study investigates two types of environments: 1) Immersive Virtual Reality (VR) and 2) Non-Immersive Virtual Reality (CAD) and the advantages that each environment gives to designers to assess parts for additive manufacturing. The two environments are compared to assess potential differences in DfAM decision-making. Participants familiar with DfAM are tasked with evaluating five designs of varying complexity using …}, author = {John Ostrander and Lauren Ryan and Snehal Dhengre and Christopher McComb and Timothy W Simpson and Nicholas A Meisel}, citation = {ASME 2019 International Design Engineering Technical Conferences and …, 2019}, conference = {ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2019}, title = {A Comparative Study Of Virtual Reality And Computer-Aided Design To Evaluate Parts For Additive Manufacturing} }
{ "ENTRYTYPE": "article", "ID": "ostrander2019acomparativestudy", "abstract": "Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantages over traditional computer-aided design (CAD) tools, and these advantages may be more evident as designs become more complex. The following study investigates two types of environments: 1) Immersive Virtual Reality (VR) and 2) Non-Immersive Virtual Reality (CAD) and the advantages that each environment gives to designers to assess parts for additive manufacturing. The two environments are compared to assess potential differences in DfAM decision-making. Participants familiar with DfAM are tasked with evaluating five designs of varying complexity using …", "author": "John Ostrander and Lauren Ryan and Snehal Dhengre and Christopher McComb and Timothy W Simpson and Nicholas A Meisel", "citation": "ASME 2019 International Design Engineering Technical Conferences and …, 2019", "conference": "ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "A Comparative Study Of Virtual Reality And Computer-Aided Design To Evaluate Parts For Additive Manufacturing", "volume": null }
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/scholar?hl=en&cites=13202684832238609316
[ "13202684832238609316" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/V02AT03A029/1069793
/scholar?oi=bibs&hl=en&q=related:pCMFc-dbObcJ:scholar.google.com/
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@article{mccomb2014quantitativecomparisonof, abstract = {Many design tasks are subject to changes in goals or constraints. For instance, a client might modify specifications after design has commenced, or a competitor may introduce a new technology or feature. A design team often cannot anticipate such changes, yet they pose a considerable challenge. This paper presents a study where engineering teams sought to solve a design task that was subject to two large, unexpected changes in problem formulation that occurred during problem solving. Continuous design data was collected to observe how the designers responded to the changes. We show that high- and low-performing teams demonstrated very different approaches to solving the problem and overcoming the changes. In particular, high-performing teams achieved simple designs and extensively explored small portions of the design space; low-performing teams explored complex designs with little …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {ASME 2014 International Design Engineering Technical Conferences and …, 2014}, conference = {ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2014}, title = {Quantitative Comparison of High- and Low-Performing Teams in a Design Task Subject to Drastic Changes} }
{ "ENTRYTYPE": "article", "ID": "mccomb2014quantitativecomparisonof", "abstract": "Many design tasks are subject to changes in goals or constraints. For instance, a client might modify specifications after design has commenced, or a competitor may introduce a new technology or feature. A design team often cannot anticipate such changes, yet they pose a considerable challenge. This paper presents a study where engineering teams sought to solve a design task that was subject to two large, unexpected changes in problem formulation that occurred during problem solving. Continuous design data was collected to observe how the designers responded to the changes. We show that high- and low-performing teams demonstrated very different approaches to solving the problem and overcoming the changes. In particular, high-performing teams achieved simple designs and extensively explored small portions of the design space; low-performing teams explored complex designs with little …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "ASME 2014 International Design Engineering Technical Conferences and …, 2014", "conference": "ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2014, "publisher": null, "title": "Quantitative Comparison of High- and Low-Performing Teams in a Design Task Subject to Drastic Changes", "volume": null }
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/scholar?hl=en&cites=18145434612967360856
[ "18145434612967360856" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2014/46407/256870
/scholar?oi=bibs&hl=en&q=related:WEn_UKSI0fsJ:scholar.google.com/
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1
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@article{liew2022understandingeffectsof, abstract = {This paper presents the results of a community survey that was designed to better understand the effects of permafrost degradation and coastal erosion on civil infrastructure. Observations were collected from residents in four Arctic coastal communities: Point Lay, Wainwright, Utqiaġvik, and Kaktovik. All four communities are underlain by continuous ice-rich permafrost with varying degrees of degradation and coastal erosion. The types, locations, and periods of observed permafrost thaw and coastal erosion were elicited. Survey participants also reported the types of civil infrastructure being affected by permafrost degradation and coastal erosion and any damage to residential buildings. Most survey participants reported that coastal erosion has been occurring for a longer period than permafrost thaw. Surface water ponding, ground surface collapse, and differential ground settlement are the three types of changes in ground surface manifested by permafrost degradation that are most frequently reported by the participants, while houses are reported as the most affected type of infrastructure in the Arctic coastal communities. Wall cracking and house tilting are the most commonly reported types of residential building damage. The effects of permafrost degradation and coastal erosion on civil infrastructure vary between communities. Locations of observed permafrost degradation and coastal erosion collected from all survey participants in each community were stacked using heatmap data visualization. The heatmaps constructed using the community survey data are reasonably consistent with modeled data synthesized from the scientific literature …}, author = {Min Liew and Ming Xiao and Louise Farquharson and Dmitry Nicolsky and Anne Jensen and Vladimir Romanovsky and Jana Peirce and Lilian Alessa and Christopher McComb and Xiong Zhang and Benjamin Jones}, citation = {Journal of Marine Science and Engineering, 2022}, journal = {Journal of Marine Science and Engineering}, pub_year = {2022}, title = {Understanding Effects of Permafrost Degradation and Coastal Erosion on Civil Infrastructure in Arctic Coastal Villages: A Community Survey and Knowledge Co-Production} }
{ "ENTRYTYPE": "article", "ID": "liew2022understandingeffectsof", "abstract": "This paper presents the results of a community survey that was designed to better understand the effects of permafrost degradation and coastal erosion on civil infrastructure. Observations were collected from residents in four Arctic coastal communities: Point Lay, Wainwright, Utqiaġvik, and Kaktovik. All four communities are underlain by continuous ice-rich permafrost with varying degrees of degradation and coastal erosion. The types, locations, and periods of observed permafrost thaw and coastal erosion were elicited. Survey participants also reported the types of civil infrastructure being affected by permafrost degradation and coastal erosion and any damage to residential buildings. Most survey participants reported that coastal erosion has been occurring for a longer period than permafrost thaw. Surface water ponding, ground surface collapse, and differential ground settlement are the three types of changes in ground surface manifested by permafrost degradation that are most frequently reported by the participants, while houses are reported as the most affected type of infrastructure in the Arctic coastal communities. Wall cracking and house tilting are the most commonly reported types of residential building damage. The effects of permafrost degradation and coastal erosion on civil infrastructure vary between communities. Locations of observed permafrost degradation and coastal erosion collected from all survey participants in each community were stacked using heatmap data visualization. The heatmaps constructed using the community survey data are reasonably consistent with modeled data synthesized from the scientific literature …", "author": "Min Liew and Ming Xiao and Louise Farquharson and Dmitry Nicolsky and Anne Jensen and Vladimir Romanovsky and Jana Peirce and Lilian Alessa and Christopher McComb and Xiong Zhang and Benjamin Jones", "citation": "Journal of Marine Science and Engineering, 2022", "conference": null, "journal": "Journal of Marine Science and Engineering", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Understanding Effects of Permafrost Degradation and Coastal Erosion on Civil Infrastructure in Arctic Coastal Villages: A Community Survey and Knowledge Co-Production", "volume": null }
0P9w_S0AAAAJ:2KloaMYe4IUC
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/scholar?hl=en&cites=7549467034974795020
[ "7549467034974795020" ]
https://www.mdpi.com/2077-1312/10/3/422
/scholar?oi=bibs&hl=en&q=related:DLUx_0QYxWgJ:scholar.google.com/
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@article{zhang2021dataonthe, abstract = {Human subject experiments are performed to assess the impact of artificial intelligence (AI) agents on distributed human design teams and individual human designers. In the team experiment, participants in teams of six develop and operate a drone fleet to deliver parcels routed to multiple locations of a target market. Among the design teams in the experiment, half of the design teams are human-only teams with no available AI agent. The other half of the design teams, designated as hybrid teams, have drone design and operation AI agents to advise them. Halfway through the team experiment, team structure is changed unexpectedly, requiring participants to adapt to the change. In the individual experiment, participants develop drones based on given design specifications, either on their own or with the availability of a drone design AI agent to advise them. During these experiments, participants configure, test …}, author = {Guanglu Zhang and Nicolas F Soria Zurita and Gary Stump and Binyang Song and Jonathan Cagan and Christopher McComb}, citation = {Data in Brief, 2021}, journal = {Data in Brief}, pub_year = {2021}, title = {Data on the Design and Operation of Drones by Both Individuals and Teams} }
{ "ENTRYTYPE": "article", "ID": "zhang2021dataonthe", "abstract": "Human subject experiments are performed to assess the impact of artificial intelligence (AI) agents on distributed human design teams and individual human designers. In the team experiment, participants in teams of six develop and operate a drone fleet to deliver parcels routed to multiple locations of a target market. Among the design teams in the experiment, half of the design teams are human-only teams with no available AI agent. The other half of the design teams, designated as hybrid teams, have drone design and operation AI agents to advise them. Halfway through the team experiment, team structure is changed unexpectedly, requiring participants to adapt to the change. In the individual experiment, participants develop drones based on given design specifications, either on their own or with the availability of a drone design AI agent to advise them. During these experiments, participants configure, test …", "author": "Guanglu Zhang and Nicolas F Soria Zurita and Gary Stump and Binyang Song and Jonathan Cagan and Christopher McComb", "citation": "Data in Brief, 2021", "conference": null, "journal": "Data in Brief", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Data on the Design and Operation of Drones by Both Individuals and Teams", "volume": null }
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/scholar?hl=en&cites=3478046114382203777
[ "3478046114382203777" ]
https://www.sciencedirect.com/science/article/pii/S2352340921002924
/scholar?oi=bibs&hl=en&q=related:gcsteIOARDAJ:scholar.google.com/
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@article{nolte2020assessingengineeringdesign:, abstract = {In response to calls for engineering programs to better prepare students for future careers, many institutions offer courses with a design component to first-year engineering students. This work proposes that traditional exam-based assessments of design concepts are inadequate, and alternative forms of assessment are needed to assess student learning in design courses. This paper investigates the self-efficacy differences between a traditional exam and a two-part practicum as a mid-semester assessment for introductory engineering students enrolled in a first-year design course. Increased self-efficacy has been linked to various positive student outcomes and increased retention of underrepresented students. The practicum consisted of an in-class team design task and an out-of-class individual reflection, while the exam was a traditional, individual written exam. All students completed a pre-assessment …}, author = {Hannah Nolte and Catherine GP Berdanier and Jessica Menold}, citation = {Journal of Mechanical Design, 2020}, journal = {Journal of Mechanical Design}, pub_year = {2020}, title = {Assessing Engineering Design: A Comparison of the Effect of Exams and Design Practica on First-Year Students Design Self-Efficacy} }
{ "ENTRYTYPE": "article", "ID": "nolte2020assessingengineeringdesign:", "abstract": "In response to calls for engineering programs to better prepare students for future careers, many institutions offer courses with a design component to first-year engineering students. This work proposes that traditional exam-based assessments of design concepts are inadequate, and alternative forms of assessment are needed to assess student learning in design courses. This paper investigates the self-efficacy differences between a traditional exam and a two-part practicum as a mid-semester assessment for introductory engineering students enrolled in a first-year design course. Increased self-efficacy has been linked to various positive student outcomes and increased retention of underrepresented students. The practicum consisted of an in-class team design task and an out-of-class individual reflection, while the exam was a traditional, individual written exam. All students completed a pre-assessment …", "author": "Hannah Nolte and Catherine GP Berdanier and Jessica Menold", "citation": "Journal of Mechanical Design, 2020", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Assessing Engineering Design: A Comparison of the Effect of Exams and Design Practica on First-Year Students Design Self-Efficacy", "volume": null }
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/scholar?hl=en&cites=11333903162726111422
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https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/143/5/052301/1088257
/scholar?oi=bibs&hl=en&q=related:vlj3fOAcSp0J:scholar.google.com/
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@article{mccomb2015enhancementofshear, abstract = {Reinforced concrete construction and steel construction are two of the most common contemporary construction methods. Both methods make use of composite decks as floor systems and diaphragms. During the design of composite decks, the interaction between the steel deck and concrete slab is typically disregarded when calculating the strength of the composite diaphragm due to lack of complete shear transfer, as existing practices such as stamping are not effective to provide substantial composite action. This conservative assumption essentially results in non-efficient use of material. This paper presents a method for ensuring shear transfer through the use of conventional sheet metal screws, driven through the corrugated steel deck and embedded in the fresh concrete. This method is proposed for use in the field between formed steel beams. Both experimental and analytical studies support an increase in …}, author = {Christopher McComb and Fariborz M Tehrani}, citation = {Engineering Structures 88, 251-261, 2015}, journal = {Engineering Structures}, pages = {251-261}, pub_year = {2015}, publisher = {Elsevier}, title = {Enhancement of Shear Transfer in Composite Deck with Mechanical Fasteners}, volume = {88} }
{ "ENTRYTYPE": "article", "ID": "mccomb2015enhancementofshear", "abstract": "Reinforced concrete construction and steel construction are two of the most common contemporary construction methods. Both methods make use of composite decks as floor systems and diaphragms. During the design of composite decks, the interaction between the steel deck and concrete slab is typically disregarded when calculating the strength of the composite diaphragm due to lack of complete shear transfer, as existing practices such as stamping are not effective to provide substantial composite action. This conservative assumption essentially results in non-efficient use of material. This paper presents a method for ensuring shear transfer through the use of conventional sheet metal screws, driven through the corrugated steel deck and embedded in the fresh concrete. This method is proposed for use in the field between formed steel beams. Both experimental and analytical studies support an increase in …", "author": "Christopher McComb and Fariborz M Tehrani", "citation": "Engineering Structures 88, 251-261, 2015", "conference": null, "journal": "Engineering Structures", "number": null, "pages": "251-261", "pub_year": 2015, "publisher": "Elsevier", "title": "Enhancement of Shear Transfer in Composite Deck with Mechanical Fasteners", "volume": "88" }
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/scholar?hl=en&cites=11481410782164355666
[ "11481410782164355666" ]
https://www.sciencedirect.com/science/article/pii/S014102961500067X
/scholar?oi=bibs&hl=en&q=related:Ugo_d0YqVp8J:scholar.google.com/
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@article{mccomb2013combiningmulti-bodydynamics, abstract = {Numerical simulations that predict the dynamics and performance of wave energy converters (WECs) require the simulation of complex fluid-structure interactions between a WEC device and the wave environment. Navier-Stokes computational fluid dynamics (CFD) simulations and fully time-domain boundary integral equation methods (BIEMs) can be coupled with multi-body dynamics solvers to simulate these problems. However, the computational resources that are required to perform these types of high-fidelity simulations are significant, precluding the use of CFD and time-domain BIEM for design optimization. One method for reducing the numerical complexity of WEC simulations is to model the hydrodynamics using frequency-domain simulations, while model the dynamic motion of the WEC device in the time-domain using multi-body dynamics methods. The primary objective of the work presented herein is to develop such a numerical tool using the multi-body solver SimMechanics and the frequency-domain hydrodynamics code WAMIT. The numerical tool was developed so that WEC devices comprised of arbitrarily connected bodies, power-take-off (PTO) systems, and mooring systems can be simulated in operational sea states, where the wave environment can be modeled under linear assumptions. The remainder of this paper describes the development and verification of the numerical tool.}, author = {Chris McComb and Michael Lawson and Yi-Hsiang Yu}, citation = {First Marine Energy Technology Symposium, 2013}, conference = {First Marine Energy Technology Symposium}, pub_year = {2013}, title = {Combining Multi-body Dynamics and Potential Flow Simulation Methods to Model a Wave Energy Converter} }
{ "ENTRYTYPE": "article", "ID": "mccomb2013combiningmulti-bodydynamics", "abstract": "Numerical simulations that predict the dynamics and performance of wave energy converters (WECs) require the simulation of complex fluid-structure interactions between a WEC device and the wave environment. Navier-Stokes computational fluid dynamics (CFD) simulations and fully time-domain boundary integral equation methods (BIEMs) can be coupled with multi-body dynamics solvers to simulate these problems. However, the computational resources that are required to perform these types of high-fidelity simulations are significant, precluding the use of CFD and time-domain BIEM for design optimization. One method for reducing the numerical complexity of WEC simulations is to model the hydrodynamics using frequency-domain simulations, while model the dynamic motion of the WEC device in the time-domain using multi-body dynamics methods. The primary objective of the work presented herein is to develop such a numerical tool using the multi-body solver SimMechanics and the frequency-domain hydrodynamics code WAMIT. The numerical tool was developed so that WEC devices comprised of arbitrarily connected bodies, power-take-off (PTO) systems, and mooring systems can be simulated in operational sea states, where the wave environment can be modeled under linear assumptions. The remainder of this paper describes the development and verification of the numerical tool.", "author": "Chris McComb and Michael Lawson and Yi-Hsiang Yu", "citation": "First Marine Energy Technology Symposium, 2013", "conference": "First Marine Energy Technology Symposium", "journal": null, "number": null, "pages": null, "pub_year": 2013, "publisher": null, "title": "Combining Multi-body Dynamics and Potential Flow Simulation Methods to Model a Wave Energy Converter", "volume": null }
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[ "20746837821804967" ]
https://engrxiv.org/preprint/view/149/
/scholar?oi=bibs&hl=en&q=related:p9GUmiO1SQAJ:scholar.google.com/
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@article{gyory2021communicationinai-assisted, abstract = {Human-artificial intelligent (AI) - assisted teaming is becoming a strategy for coalescing the complementary strengths of humans and computers to solve difficult tasks. Yet, there is still much to learn regarding how the integration of humans with AI agents into a team affects human behavior. Accordingly, this work begins to inform this research gap by focusing specifically on how the communication structure and interaction changes within AI-assisted human teams. The underlying discourse data for this work originates from a prior research study in which teams solve an interdisciplinary drone design and path-planning problem. Several metrics are employed in this work to study team discourse, including count, diversity, content richness, and semantic coherence. Results show significant differences in communication behavior in AI-assisted teams including more diversity and frequency in communication, more …}, author = {Joshua T Gyory and Binyang Song and Jonathan Cagan and Christopher McComb}, citation = {International Conference on Engineering Design, 2021}, conference = {International Conference on Engineering Design}, pub_year = {2021}, title = {Communication in AI-assisted Teams During an Interdisciplinary Drone Design Problem} }
{ "ENTRYTYPE": "article", "ID": "gyory2021communicationinai-assisted", "abstract": "Human-artificial intelligent (AI) - assisted teaming is becoming a strategy for coalescing the complementary strengths of humans and computers to solve difficult tasks. Yet, there is still much to learn regarding how the integration of humans with AI agents into a team affects human behavior. Accordingly, this work begins to inform this research gap by focusing specifically on how the communication structure and interaction changes within AI-assisted human teams. The underlying discourse data for this work originates from a prior research study in which teams solve an interdisciplinary drone design and path-planning problem. Several metrics are employed in this work to study team discourse, including count, diversity, content richness, and semantic coherence. Results show significant differences in communication behavior in AI-assisted teams including more diversity and frequency in communication, more …", "author": "Joshua T Gyory and Binyang Song and Jonathan Cagan and Christopher McComb", "citation": "International Conference on Engineering Design, 2021", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Communication in AI-assisted Teams During an Interdisciplinary Drone Design Problem", "volume": null }
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https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/communication-in-aiassisted-teams-during-an-interdisciplinary-drone-design-problem/FFA6D55B0D901CEB676FC15373322937
/scholar?oi=bibs&hl=en&q=related:RsCYOTJrlxkJ:scholar.google.com/
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@article{singh2020analysingtheeffect, abstract = {Social media influencers (SMI) are gaining interest and many are studying their influence on the online audience, little is known about the role played by them in offline teams. One such attempt to study the effect of influencers in co-design team is presented in this paper, where individuals who are confident in their abilities drive the team process. Thus, self-efficacy is considered for determining influencer behaviour. Results expose the relationship between self-efficacy and influencer status on the design process, besides briefly highlighting the effects on above-average teams.}, author = {Harshika Singh and Gaetano Cascini and C McComb}, citation = {Proceedings of the Design Society: DESIGN Conference 1, 2571-2580, 2020}, journal = {Proceedings of the Design Society: DESIGN Conference}, pages = {2571-2580}, pub_year = {2020}, publisher = {Cambridge University Press}, title = {Analysing the Effect of Self-Efficacy and Influencers on Design Team Performance}, volume = {1} }
{ "ENTRYTYPE": "article", "ID": "singh2020analysingtheeffect", "abstract": "Social media influencers (SMI) are gaining interest and many are studying their influence on the online audience, little is known about the role played by them in offline teams. One such attempt to study the effect of influencers in co-design team is presented in this paper, where individuals who are confident in their abilities drive the team process. Thus, self-efficacy is considered for determining influencer behaviour. Results expose the relationship between self-efficacy and influencer status on the design process, besides briefly highlighting the effects on above-average teams.", "author": "Harshika Singh and Gaetano Cascini and C McComb", "citation": "Proceedings of the Design Society: DESIGN Conference 1, 2571-2580, 2020", "conference": null, "journal": "Proceedings of the Design Society: DESIGN Conference", "number": null, "pages": "2571-2580", "pub_year": 2020, "publisher": "Cambridge University Press", "title": "Analysing the Effect of Self-Efficacy and Influencers on Design Team Performance", "volume": "1" }
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https://www.cambridge.org/core/journals/proceedings-of-the-design-society-design-conference/article/analysing-the-effect-of-selfefficacy-and-influencers-on-design-team-performance/FB7AF44CFEE4EFDC8AE77C2BE876990B
/scholar?oi=bibs&hl=en&q=related:wDwPoSgIKikJ:scholar.google.com/
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@article{mccomb2023focusandmodality:, abstract = {The evolution of Artificial Intelligence (AI) and Machine Learning (ML) enables new ways to envision how computer tools will aid, work with, and even guide human teams. This paper explores this new paradigm of design by considering emerging variations of AI-Human collaboration: AI used as a design tool versus AI employed as a guide to human problem solvers, and AI agents which only react to their human counterparts versus AI agents which proactively identify and address needs. The different combinations can be mapped onto a 2×2 AI-Human Teaming Matrix which isolates and highlights these different AI capabilities in teaming. The paper introduces the matrix and its quadrants, illustrating these different AI agents and their application and impact, and then provides a road map to researching and developing effective AI team collaborators.}, author = {Christopher McComb and Peter Boatwright and Jonathan Cagan}, citation = {International Conference on Engineering Design, 2023}, conference = {International Conference on Engineering Design}, pub_year = {2023}, title = {Focus and Modality: Defining A Roadmap to Future AI-Human Teaming in Design} }
{ "ENTRYTYPE": "article", "ID": "mccomb2023focusandmodality:", "abstract": "The evolution of Artificial Intelligence (AI) and Machine Learning (ML) enables new ways to envision how computer tools will aid, work with, and even guide human teams. This paper explores this new paradigm of design by considering emerging variations of AI-Human collaboration: AI used as a design tool versus AI employed as a guide to human problem solvers, and AI agents which only react to their human counterparts versus AI agents which proactively identify and address needs. The different combinations can be mapped onto a 2×2 AI-Human Teaming Matrix which isolates and highlights these different AI capabilities in teaming. The paper introduces the matrix and its quadrants, illustrating these different AI agents and their application and impact, and then provides a road map to researching and developing effective AI team collaborators.", "author": "Christopher McComb and Peter Boatwright and Jonathan Cagan", "citation": "International Conference on Engineering Design, 2023", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2023, "publisher": null, "title": "Focus and Modality: Defining A Roadmap to Future AI-Human Teaming in Design", "volume": null }
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/scholar?hl=en&cites=8259080243278385515
[ "8259080243278385515" ]
https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/focus-and-modality-defining-a-roadmap-to-future-aihuman-teaming-in-design/E8FFBB060C1D90D6CF000ECBCF0C3432
/scholar?oi=bibs&hl=en&q=related:axEOCLklnnIJ:scholar.google.com/
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@article{maier2022therelationshipbetween, abstract = {Artificial intelligence (AI) is fundamentally changing how people work in nearly every field, including online finance. However, our ability to interact with AI is moderated by factors such as performance, complexity, and trust. The work presented in this study analyzes the effect of performance on trust in a robo-advisor (AI which assists in managing investments) through an empirical investment simulation. Results show that for applications where humans and AI have comparable capabilities, the difference in performance (between the human and AI) is a moderate indicator of change in trust; however, human or AI performance individually were weak indicators. Additionally, results indicate that biases typically seen in human-human interactions may also occur in human-AI interactions when AI transparency is low.}, author = {Torsten Maier and Jessica Menold and Christopher McComb}, citation = {Frontiers in Artificial Intelligence, 2022}, journal = {Frontiers in Artificial Intelligence}, pub_year = {2022}, title = {The Relationship Between Performance and Trust in AI in E-Finance} }
{ "ENTRYTYPE": "article", "ID": "maier2022therelationshipbetween", "abstract": "Artificial intelligence (AI) is fundamentally changing how people work in nearly every field, including online finance. However, our ability to interact with AI is moderated by factors such as performance, complexity, and trust. The work presented in this study analyzes the effect of performance on trust in a robo-advisor (AI which assists in managing investments) through an empirical investment simulation. Results show that for applications where humans and AI have comparable capabilities, the difference in performance (between the human and AI) is a moderate indicator of change in trust; however, human or AI performance individually were weak indicators. Additionally, results indicate that biases typically seen in human-human interactions may also occur in human-AI interactions when AI transparency is low.", "author": "Torsten Maier and Jessica Menold and Christopher McComb", "citation": "Frontiers in Artificial Intelligence, 2022", "conference": null, "journal": "Frontiers in Artificial Intelligence", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "The Relationship Between Performance and Trust in AI in E-Finance", "volume": null }
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/scholar?hl=en&cites=3799917827576729254
[ "3799917827576729254" ]
https://www.frontiersin.org/articles/10.3389/frai.2022.891529/full
/scholar?oi=bibs&hl=en&q=related:po5ioCEFvDQJ:scholar.google.com/
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@article{rismiller2020stochasticstackelberggames, abstract = {Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Game-theoretic methods make it possible for designers to design solutions that are robust against complicated conditions, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a game-theoretic agent-based architecture that generates solutions robust to variation, and models problems with elementary information, making it easily extendable. The platform was used to generate designs under consideration of a multidimensional attack. Designs were produced under various adversarial settings and compared to designs generated without considering adversaries to validate the model. The process successfully created robust designs able to withstand multiple combined …}, author = {Sean C Rismiller and Jonathan Cagan and Christopher McComb}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {Stochastic Stackelberg Games for Agent-Driven Robust Design} }
{ "ENTRYTYPE": "article", "ID": "rismiller2020stochasticstackelberggames", "abstract": "Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Game-theoretic methods make it possible for designers to design solutions that are robust against complicated conditions, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a game-theoretic agent-based architecture that generates solutions robust to variation, and models problems with elementary information, making it easily extendable. The platform was used to generate designs under consideration of a multidimensional attack. Designs were produced under various adversarial settings and compared to designs generated without considering adversaries to validate the model. The process successfully created robust designs able to withstand multiple combined …", "author": "Sean C Rismiller and Jonathan Cagan and Christopher McComb", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Stochastic Stackelberg Games for Agent-Driven Robust Design", "volume": null }
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/scholar?hl=en&cites=2812207060433061980
[ "2812207060433061980" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2020/84003/1090228
/scholar?oi=bibs&hl=en&q=related:XEj192v3BicJ:scholar.google.com/
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@article{maier2019towardsanontology, abstract = {Cognitive assistants such as IBM Watson and Siri are at the forefront of social and technological innovation and have the potential to solve many unique problems. However, the lack of standardization and classification within the field impedes critical analysis of existing cognitive assistants and may further inhibit their growth into more useful applications. This paper discusses the development of an ontology, its classes, and subclasses that may serve as a foundation for defining and differentiating CAs. Specifically, the four suggested classes include: learning, intelligence, autonomy, and communication. Various assistants are described and categorized using the proposed system. Our novel ontological framework is the first step towards a classification system for this burgeoning field.}, author = {Torsten Maier and Jessica Menold and Christopher McComb}, citation = {International Conference on Engineering Design, 2019}, conference = {International Conference on Engineering Design}, pub_year = {2019}, title = {Towards an Ontology of Cognitive Assistants} }
{ "ENTRYTYPE": "article", "ID": "maier2019towardsanontology", "abstract": "Cognitive assistants such as IBM Watson and Siri are at the forefront of social and technological innovation and have the potential to solve many unique problems. However, the lack of standardization and classification within the field impedes critical analysis of existing cognitive assistants and may further inhibit their growth into more useful applications. This paper discusses the development of an ontology, its classes, and subclasses that may serve as a foundation for defining and differentiating CAs. Specifically, the four suggested classes include: learning, intelligence, autonomy, and communication. Various assistants are described and categorized using the proposed system. Our novel ontological framework is the first step towards a classification system for this burgeoning field.", "author": "Torsten Maier and Jessica Menold and Christopher McComb", "citation": "International Conference on Engineering Design, 2019", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Towards an Ontology of Cognitive Assistants", "volume": null }
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https://www.cambridge.org/core/journals/proceedings-of-the-international-conference-on-engineering-design/article/towards-an-ontology-of-cognitive-assistants/1B860F4AD8AE238AC9204D984513AD14
/scholar?oi=bibs&hl=en&q=related:sRG2b7juCpcJ:scholar.google.com/
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@article{agrawal2023reinforcementlearningfor, abstract = {Reinforcement learning algorithms can autonomously learn to search a design space for high-performance solutions. However, modern engineering often entails the use of computationally intensive simulation, which can lead to slower design timelines with highly iterative approaches such as reinforcement learning. This work provides a reinforcement learning framework that leverages models of varying fidelity to enable an effective solution search while reducing overall computational needs. Specifically, it utilizes models of varying fidelity while training the agent, iteratively progressing from low- to high fidelity. To demonstrate the effectiveness of the proposed framework, we apply it to two multimodal multi-objective constrained mixed integer nonlinear design problems involving the components of a ground and aerial vehicle. Specifically, for each problem, we utilize a high-fidelity and a low-fidelity deep neural …}, author = {Akash Agrawal and Christopher McComb}, citation = {Journal of Computing and Information Science in Engineering, 2023}, journal = {Journal of Computing and Information Science in Engineering}, pub_year = {2023}, title = {Reinforcement Learning for Efficient Design Space Exploration with Variable Fidelity Analysis Models} }
{ "ENTRYTYPE": "article", "ID": "agrawal2023reinforcementlearningfor", "abstract": "Reinforcement learning algorithms can autonomously learn to search a design space for high-performance solutions. However, modern engineering often entails the use of computationally intensive simulation, which can lead to slower design timelines with highly iterative approaches such as reinforcement learning. This work provides a reinforcement learning framework that leverages models of varying fidelity to enable an effective solution search while reducing overall computational needs. Specifically, it utilizes models of varying fidelity while training the agent, iteratively progressing from low- to high fidelity. To demonstrate the effectiveness of the proposed framework, we apply it to two multimodal multi-objective constrained mixed integer nonlinear design problems involving the components of a ground and aerial vehicle. Specifically, for each problem, we utilize a high-fidelity and a low-fidelity deep neural …", "author": "Akash Agrawal and Christopher McComb", "citation": "Journal of Computing and Information Science in Engineering, 2023", "conference": null, "journal": "Journal of Computing and Information Science in Engineering", "number": null, "pages": null, "pub_year": 2023, "publisher": null, "title": "Reinforcement Learning for Efficient Design Space Exploration with Variable Fidelity Analysis Models", "volume": null }
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/scholar?hl=en&cites=14437886537111824093
[ "14437886537111824093" ]
https://asmedigitalcollection.asme.org/computingengineering/article-abstract/23/4/041004/1150961
/scholar?oi=bibs&hl=en&q=related:3ebxb0-tXcgJ:scholar.google.com/
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@article{alzayed2021empathiccreativity:can, abstract = {Over the past decade, engineering design research has seen a significant surge of the discussion of empathy. As such, design researchers have been devoted in devising and assessing empathic design activities. While prior research has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer's empathic tendencies in driving creative concept generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in an engineering design student project. In order to achieve this objective, a study was conducted with 103 first-year engineering students during two design stages of an 8-week design project (concept generation and …}, author = {Mohammad Alsager Alzayed and Scarlett R Miller and Christopher McComb}, citation = {AI EDAM 35 (4), 369-383, 2021}, journal = {AI EDAM}, number = {4}, pages = {369-383}, pub_year = {2021}, publisher = {Cambridge University Press}, title = {Empathic creativity: can trait empathy predict creative concept generation and selection?}, volume = {35} }
{ "ENTRYTYPE": "article", "ID": "alzayed2021empathiccreativity:can", "abstract": "Over the past decade, engineering design research has seen a significant surge of the discussion of empathy. As such, design researchers have been devoted in devising and assessing empathic design activities. While prior research has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer's empathic tendencies in driving creative concept generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in an engineering design student project. In order to achieve this objective, a study was conducted with 103 first-year engineering students during two design stages of an 8-week design project (concept generation and …", "author": "Mohammad Alsager Alzayed and Scarlett R Miller and Christopher McComb", "citation": "AI EDAM 35 (4), 369-383, 2021", "conference": null, "journal": "AI EDAM", "number": "4", "pages": "369-383", "pub_year": 2021, "publisher": "Cambridge University Press", "title": "Empathic creativity: can trait empathy predict creative concept generation and selection?", "volume": "35" }
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https://www.cambridge.org/core/journals/ai-edam/article/empathic-creativity-can-trait-empathy-predict-creative-concept-generation-and-selection/879FD1D11B3AD76D87519F16A96EAAE1
/scholar?oi=bibs&hl=en&q=related:3dSpE2R22R4J:scholar.google.com/
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@article{puentes2020data-drivenheuristicinduction, abstract = {Through experience, designers develop guiding principles, or heuristics, to aid decision-making in familiar design domains. Generalized versions of common design heuristics have been identified across multiple domains and applied by novices to design problems. Previous work leveraged a sample of these common heuristics to assist in an agent-based design process, which typically lacks heuristics. These predefined heuristics were translated into sequences of specifically applied design changes that followed the theme of the heuristic. To overcome the upfront burden, need for human interpretation, and lack of generality of this manual process, this paper presents a methodology that induces frequent heuristic sequences from an existing timeseries design change dataset. Individual induced sequences are then algorithmically grouped based on similarity to form groups that each represent a shared …}, author = {Lucas Puentes and Jonathan Cagan and Christopher McComb}, citation = {Journal of Computing and Information Science in Engineering, 2020}, journal = {Journal of Computing and Information Science in Engineering}, pub_year = {2020}, title = {Data-Driven Heuristic Induction from Human Design Behavior} }
{ "ENTRYTYPE": "article", "ID": "puentes2020data-drivenheuristicinduction", "abstract": "Through experience, designers develop guiding principles, or heuristics, to aid decision-making in familiar design domains. Generalized versions of common design heuristics have been identified across multiple domains and applied by novices to design problems. Previous work leveraged a sample of these common heuristics to assist in an agent-based design process, which typically lacks heuristics. These predefined heuristics were translated into sequences of specifically applied design changes that followed the theme of the heuristic. To overcome the upfront burden, need for human interpretation, and lack of generality of this manual process, this paper presents a methodology that induces frequent heuristic sequences from an existing timeseries design change dataset. Individual induced sequences are then algorithmically grouped based on similarity to form groups that each represent a shared …", "author": "Lucas Puentes and Jonathan Cagan and Christopher McComb", "citation": "Journal of Computing and Information Science in Engineering, 2020", "conference": null, "journal": "Journal of Computing and Information Science in Engineering", "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Data-Driven Heuristic Induction from Human Design Behavior", "volume": null }
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[ "8255694073045419871" ]
https://asmedigitalcollection.asme.org/computingengineering/article-abstract/21/2/024501/1086976
/scholar?oi=bibs&hl=en&q=related:X4cr1gQeknIJ:scholar.google.com/
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@article{bracken2020areviewof, abstract = {As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has its own benefits and drawbacks. This paper reviews popular methods of part filtering and elaborates on the advantages and disadvantages of the various approaches. The approaches for part filtering, and the example methods, are categorized and sorted along a continuum of opportunistic and restrictive methods in order to clarify use cases for various part filtering techniques. The approaches are also examined through the lens of specificity of process, as some are designed to be process agnostic, while others are customized for a specific AM technology or even a …}, author = {Jennifer E. Bracken and Christopher McComb and Timothy W. Simpson and Kathryn Jablokow}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {A Review of Part Filtering Methods for Additive Manufacturing} }
{ "ENTRYTYPE": "article", "ID": "bracken2020areviewof", "abstract": "As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has its own benefits and drawbacks. This paper reviews popular methods of part filtering and elaborates on the advantages and disadvantages of the various approaches. The approaches for part filtering, and the example methods, are categorized and sorted along a continuum of opportunistic and restrictive methods in order to clarify use cases for various part filtering techniques. The approaches are also examined through the lens of specificity of process, as some are designed to be process agnostic, while others are customized for a specific AM technology or even a …", "author": "Jennifer E. Bracken and Christopher McComb and Timothy W. Simpson and Kathryn Jablokow", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "A Review of Part Filtering Methods for Additive Manufacturing", "volume": null }
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https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2020/84003/1090234
/scholar?oi=bibs&hl=en&q=related:DukQQxb4Uj0J:scholar.google.com/
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@article{mccomb2017dataonthe, abstract = {This experiment was carried out to record the step-by-step actions that humans take in solving a configuration design problem, either in small teams or individually. Specifically, study participants were tasked with configuring an internet-connected system of products to maintain temperature within a home, subject to cost constraints. Every participant was given access to a computer-based design interface that allowed them to construct and assess solutions. The interface was also used to record the data that is presented here. In total, data was collected for 68 participants, and each participant was allowed to perform 50 design actions in solving the configuration design problem. Major results based on the data presented here have been reported separately, including initial behavioral analysis (McComb et al.) [1], [2] and design pattern assessments via Markovian modeling (McComb et al., 2017; McComb et al., 2017 …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {Data in Brief, 2017}, journal = {Data in Brief}, pub_year = {2017}, title = {Data on the Configuration Design of Internet-Connected Home Cooling Systems by Engineering Students} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017dataonthe", "abstract": "This experiment was carried out to record the step-by-step actions that humans take in solving a configuration design problem, either in small teams or individually. Specifically, study participants were tasked with configuring an internet-connected system of products to maintain temperature within a home, subject to cost constraints. Every participant was given access to a computer-based design interface that allowed them to construct and assess solutions. The interface was also used to record the data that is presented here. In total, data was collected for 68 participants, and each participant was allowed to perform 50 design actions in solving the configuration design problem. Major results based on the data presented here have been reported separately, including initial behavioral analysis (McComb et al.) [1], [2] and design pattern assessments via Markovian modeling (McComb et al., 2017; McComb et al., 2017 …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "Data in Brief, 2017", "conference": null, "journal": "Data in Brief", "number": null, "pages": null, "pub_year": 2017, "publisher": null, "title": "Data on the Configuration Design of Internet-Connected Home Cooling Systems by Engineering Students", "volume": null }
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/scholar?hl=en&cites=13230962903758905556,3634236465210730361
[ "13230962903758905556", "3634236465210730361" ]
https://www.sciencedirect.com/science/article/pii/S2352340917304274
/scholar?oi=bibs&hl=en&q=related:1KDrCqnSnbcJ:scholar.google.com/
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@article{mccomb2016linkingpropertiesof, abstract = {A team with the right characteristics can exceed the sum of their individual efforts. However, a team having the wrong characteristics may perform more poorly than the sum of its individuals. Therefore, it is crucial that teams are assembled and managed properly in order to maximize performance. This work examines how the properties of a design problem can be used to select the best values for team characteristics. Two characteristics are considered: team size and interaction frequency. A computational model of design teams that has been shown to effectively emulate human team behavior is leveraged to pinpoint optimized team characteristics for solving a variety of fluid and structural design problems. The nature of each design problem is characterized with respect to local and global behavior of the design space, alignment between objective functions, and the resources allotted for solving the problem …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {ASME 2016 International Design Engineering Technical Conferences and …, 2016}, conference = {ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2016}, publisher = {ASME}, title = {Linking Properties of Design Problem to Optimal Team Characteristics} }
{ "ENTRYTYPE": "article", "ID": "mccomb2016linkingpropertiesof", "abstract": "A team with the right characteristics can exceed the sum of their individual efforts. However, a team having the wrong characteristics may perform more poorly than the sum of its individuals. Therefore, it is crucial that teams are assembled and managed properly in order to maximize performance. This work examines how the properties of a design problem can be used to select the best values for team characteristics. Two characteristics are considered: team size and interaction frequency. A computational model of design teams that has been shown to effectively emulate human team behavior is leveraged to pinpoint optimized team characteristics for solving a variety of fluid and structural design problems. The nature of each design problem is characterized with respect to local and global behavior of the design space, alignment between objective functions, and the resources allotted for solving the problem …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "ASME 2016 International Design Engineering Technical Conferences and …, 2016", "conference": "ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2016, "publisher": "ASME", "title": "Linking Properties of Design Problem to Optimal Team Characteristics", "volume": null }
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https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2016/50190/258458
/scholar?oi=bibs&hl=en&q=related:Lk7v_6JoYqEJ:scholar.google.com/
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null
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@article{mccomb2015fairnessandmanipulation:, abstract = {The design process often requires work by teams, rather than individuals. During these times it is likely that situations will arise in which members of a team have different opinions, yet a group decision must still be made. Unfortunately, Arrow’s Impossibility Theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of “fair” conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow’s conditions. Experiential conjoint analysis was used to obtain empirical utility functions for drinking mug designs. A number of functions for constructing group preference were then analysed using both empirical conjoint preferences and randomly generated preferences. This analysis involved checking each of Arrow’s conditions, as well as computing the likelihood that a method will be susceptible to manipulation by a dishonest individual. Based on the results, methods that should be used to aggregate group preference in practice are recommended.}, author = {Christopher McComb and Kosa Goucher-Lambert and Jonathan Cagan}, citation = {International Conference on Engineering Design, 2015}, conference = {International Conference on Engineering Design}, pub_year = {2015}, title = {Fairness and Manipulation: An Empirical Study of Arrow’s Impossibility Theorem} }
{ "ENTRYTYPE": "article", "ID": "mccomb2015fairnessandmanipulation:", "abstract": "The design process often requires work by teams, rather than individuals. During these times it is likely that situations will arise in which members of a team have different opinions, yet a group decision must still be made. Unfortunately, Arrow’s Impossibility Theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of “fair” conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow’s conditions. Experiential conjoint analysis was used to obtain empirical utility functions for drinking mug designs. A number of functions for constructing group preference were then analysed using both empirical conjoint preferences and randomly generated preferences. This analysis involved checking each of Arrow’s conditions, as well as computing the likelihood that a method will be susceptible to manipulation by a dishonest individual. Based on the results, methods that should be used to aggregate group preference in practice are recommended.", "author": "Christopher McComb and Kosa Goucher-Lambert and Jonathan Cagan", "citation": "International Conference on Engineering Design, 2015", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2015, "publisher": null, "title": "Fairness and Manipulation: An Empirical Study of Arrow’s Impossibility Theorem", "volume": null }
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/scholar?hl=en&cites=2532161900391412017
[ "2532161900391412017" ]
https://www.designsociety.org/publication/37857/fairness_and_manipulation_an_empirical_study_of_arrow%E2%80%99s_impossibility_theorem
/scholar?oi=bibs&hl=en&q=related:MbGbGtULJCMJ:scholar.google.com/
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@article{raina2023learningtodesign, abstract = {Building an Artificial Intelligence (AI) agent that can design on its own has been a goal since the 1980s. Recently, deep learning has shown the ability to learn from large-scale data, enabling significant advances in data-driven design. However, learning over prior data limits us only to solve problems that have been solved before and biases data-driven learning toward existing solutions. The ultimate goal for a design agent is the ability to learn generalizable design behavior in a problem space without having seen it before. We introduce a self-learning agent framework in this work that achieves this goal. This framework integrates a deep policy network with a novel tree search algorithm, where the tree search explores the problem space, and the deep policy network leverages self-generated experience to guide the search further. This framework first demonstrates an ability to discover high-performing …}, author = {Ayush Raina and Jonathan Cagan and Christopher McComb}, citation = {Journal of Mechanical Design, 2023}, journal = {Journal of Mechanical Design}, pub_year = {2023}, title = {Learning to design without prior data: Discovering generalizable design strategies using deep learning and tree search} }
{ "ENTRYTYPE": "article", "ID": "raina2023learningtodesign", "abstract": "Building an Artificial Intelligence (AI) agent that can design on its own has been a goal since the 1980s. Recently, deep learning has shown the ability to learn from large-scale data, enabling significant advances in data-driven design. However, learning over prior data limits us only to solve problems that have been solved before and biases data-driven learning toward existing solutions. The ultimate goal for a design agent is the ability to learn generalizable design behavior in a problem space without having seen it before. We introduce a self-learning agent framework in this work that achieves this goal. This framework integrates a deep policy network with a novel tree search algorithm, where the tree search explores the problem space, and the deep policy network leverages self-generated experience to guide the search further. This framework first demonstrates an ability to discover high-performing …", "author": "Ayush Raina and Jonathan Cagan and Christopher McComb", "citation": "Journal of Mechanical Design, 2023", "conference": null, "journal": "Journal of Mechanical Design", "number": null, "pages": null, "pub_year": 2023, "publisher": null, "title": "Learning to design without prior data: Discovering generalizable design strategies using deep learning and tree search", "volume": null }
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/scholar?hl=en&cites=2685048048870743069
[ "2685048048870743069" ]
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/145/3/031402/1150239
/scholar?oi=bibs&hl=en&q=related:HdzLdfk0QyUJ:scholar.google.com/
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null
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@article{mccomb2018designingimprovedteams, abstract = {Teams are ubiquitous, woven into the fabric of engineering and design. Often, it is assumed that teams are better at solving problems than individuals working independently. Recent work in engineering, design, and psychology has indicated that teams may not be the problem-solving panacea that they were once thought to be. Crowdsourcing has seen increased interest in engineering design recently, and platforms often encourage teamwork between participants. This work undertakes an analysis of the performance of different team styles and sizes in crowdsourced competitions. This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small interacting teams are more likely to win competitions. These results are discussed in the context of motivation for crowdsourcing participants.}, author = {Christopher McComb and Torsten Maier}, citation = {ASME 2018 International Design Engineering Technical Conferences and …, 2018}, conference = {ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2018}, title = {Designing Improved Teams for Crowdsourced Competitions} }
{ "ENTRYTYPE": "article", "ID": "mccomb2018designingimprovedteams", "abstract": "Teams are ubiquitous, woven into the fabric of engineering and design. Often, it is assumed that teams are better at solving problems than individuals working independently. Recent work in engineering, design, and psychology has indicated that teams may not be the problem-solving panacea that they were once thought to be. Crowdsourcing has seen increased interest in engineering design recently, and platforms often encourage teamwork between participants. This work undertakes an analysis of the performance of different team styles and sizes in crowdsourced competitions. This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small interacting teams are more likely to win competitions. These results are discussed in the context of motivation for crowdsourcing participants.", "author": "Christopher McComb and Torsten Maier", "citation": "ASME 2018 International Design Engineering Technical Conferences and …, 2018", "conference": "ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "Designing Improved Teams for Crowdsourced Competitions", "volume": null }
0P9w_S0AAAAJ:hFOr9nPyWt4C
9
/scholar?hl=en&cites=17681983420603040298
[ "17681983420603040298" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2018/51845/275186
/scholar?oi=bibs&hl=en&q=related:KgJk5TwGY_UJ:scholar.google.com/
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@article{maier2022comparinghumanand, abstract = {The rapid digitalization of the world has affected engineering and design in a variety of ways, including the introduction of new computer-aided ideation tools. Cognitive assistants (CA), an increasingly common digital technology, use natural-language processing and artificial intelligence to provide computational support. Because CAs are capable of emulating humans in some tasks, they may be suited to support ideation activities when trained coaches or facilitators are not available. However, the effects and perception of CA-facilitated ideation are not fully understood. This study compared co-located brainstorming groups facilitated by human facilitators and a CA facilitator. We found that human facilitation was associated with the blocks/interruptions state because they used these moments to initiate facilitation; conversely, cognitive assistant facilitation was associated with the deviations and silence state. Human …}, author = {Torsten Maier and Nicolas F. Soria Zurita and Elizabeth Starkey and Daniel Spillane and Jessica Menold and Christopher McComb}, citation = {Journal of Engineering Design, 2022}, journal = {Journal of Engineering Design}, pub_year = {2022}, title = {Comparing Human and Cognitive Assistant Facilitated Brainstorming Sessions} }
{ "ENTRYTYPE": "article", "ID": "maier2022comparinghumanand", "abstract": "The rapid digitalization of the world has affected engineering and design in a variety of ways, including the introduction of new computer-aided ideation tools. Cognitive assistants (CA), an increasingly common digital technology, use natural-language processing and artificial intelligence to provide computational support. Because CAs are capable of emulating humans in some tasks, they may be suited to support ideation activities when trained coaches or facilitators are not available. However, the effects and perception of CA-facilitated ideation are not fully understood. This study compared co-located brainstorming groups facilitated by human facilitators and a CA facilitator. We found that human facilitation was associated with the blocks/interruptions state because they used these moments to initiate facilitation; conversely, cognitive assistant facilitation was associated with the deviations and silence state. Human …", "author": "Torsten Maier and Nicolas F. Soria Zurita and Elizabeth Starkey and Daniel Spillane and Jessica Menold and Christopher McComb", "citation": "Journal of Engineering Design, 2022", "conference": null, "journal": "Journal of Engineering Design", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Comparing Human and Cognitive Assistant Facilitated Brainstorming Sessions", "volume": null }
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/scholar?hl=en&cites=9203264417513646248
[ "9203264417513646248" ]
https://www.tandfonline.com/doi/abs/10.1080/09544828.2022.2032623
/scholar?oi=bibs&hl=en&q=related:qKjkCzqQuH8J:scholar.google.com/
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@article{maier2021aqueryconundrum:, abstract = {Cognitive assistants use vocal interfaces and artificial intelligence to assist humans with complex tasks. While much research has focused on the application of these devices, a few studies have addressed how these devices affect the way humans work. To fill this gap, this research studied the effects of a cognitive assistant on mental workload, frustration, and effort. Participants worked with a Wizard-of-Oz style assistant and completed the Wisconsin Card-Sorting Task and engaged in a peripheral-detection task in a two-sample study that compared participants (n = 21) who worked with the assistant to those who did not. Follow-up interviews were also completed. Results suggest that onboarding techniques, such as tutorials, are important for developing analogical trust before regular use. Additionally, results suggest that keeping the mental model of the CA clear, simple, and intuitive is important to reduce …}, author = {Torsten Maier and Saeed Abdullah and Christopher McComb and Jessica Menold}, citation = {SN Computer Science, 2021}, journal = {SN Computer Science}, pub_year = {2021}, title = {A Query Conundrum: The Mental Challenges of Using a Cognitive Assistant} }
{ "ENTRYTYPE": "article", "ID": "maier2021aqueryconundrum:", "abstract": "Cognitive assistants use vocal interfaces and artificial intelligence to assist humans with complex tasks. While much research has focused on the application of these devices, a few studies have addressed how these devices affect the way humans work. To fill this gap, this research studied the effects of a cognitive assistant on mental workload, frustration, and effort. Participants worked with a Wizard-of-Oz style assistant and completed the Wisconsin Card-Sorting Task and engaged in a peripheral-detection task in a two-sample study that compared participants (n = 21) who worked with the assistant to those who did not. Follow-up interviews were also completed. Results suggest that onboarding techniques, such as tutorials, are important for developing analogical trust before regular use. Additionally, results suggest that keeping the mental model of the CA clear, simple, and intuitive is important to reduce …", "author": "Torsten Maier and Saeed Abdullah and Christopher McComb and Jessica Menold", "citation": "SN Computer Science, 2021", "conference": null, "journal": "SN Computer Science", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "A Query Conundrum: The Mental Challenges of Using a Cognitive Assistant", "volume": null }
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/scholar?hl=en&cites=6334895394025500844
[ "6334895394025500844" ]
https://link.springer.com/article/10.1007/s42979-021-00621-9
/scholar?oi=bibs&hl=en&q=related:rPAlEswR6lcJ:scholar.google.com/
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@article{nolte2020identifyingstresssignatures, abstract = {Various aspects of the design process often lead to stress. This study used pre- and post-task surveys to gather information regarding the designer's cognitive experience, physiological response, and perceived sources of stress during concept generation, concept selection, and prototyping. Results confirmed that design is highly cognitive, and that mental stress is present. Variability in the results also suggests that a physiological stress component might be present. Additionally, perceived sources of stress were examined, and recommendations were offered for instructors of design courses.}, author = {Hannah Nolte and Christopher McComb}, citation = {International Design Conference - DESIGN 2020, 2020}, conference = {International Design Conference - DESIGN 2020}, pub_year = {2020}, title = {Identifying Stress Signatures Across the Engineering Design Process: Perceived Stress During Concept Generation, Concept Selection, and Prototyping} }
{ "ENTRYTYPE": "article", "ID": "nolte2020identifyingstresssignatures", "abstract": "Various aspects of the design process often lead to stress. This study used pre- and post-task surveys to gather information regarding the designer's cognitive experience, physiological response, and perceived sources of stress during concept generation, concept selection, and prototyping. Results confirmed that design is highly cognitive, and that mental stress is present. Variability in the results also suggests that a physiological stress component might be present. Additionally, perceived sources of stress were examined, and recommendations were offered for instructors of design courses.", "author": "Hannah Nolte and Christopher McComb", "citation": "International Design Conference - DESIGN 2020, 2020", "conference": "International Design Conference - DESIGN 2020", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Identifying Stress Signatures Across the Engineering Design Process: Perceived Stress During Concept Generation, Concept Selection, and Prototyping", "volume": null }
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https://www.cambridge.org/core/journals/proceedings-of-the-design-society-design-conference/article/identifying-stress-signatures-across-the-engineering-design-process-perceived-stress-during-concept-generation-concept-selection-and-prototyping/CD7852943A179854E944071BA06FF1B5
/scholar?oi=bibs&hl=en&q=related:JTnT2p38zUoJ:scholar.google.com/
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@article{nelson2019theprototypingbehaviors, abstract = {Prototyping is a crucial part of new product development and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources, and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best …}, author = {Jacob Nelson and Tobias Mahan and Christopher McComb and Jessica Menold}, citation = {ASME 2019 International Design Engineering Technical Conferences and …, 2019}, conference = {ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2019}, title = {The Prototyping Behaviors Of Startups: Exploring The Relationship Between Prototyping Behavior And The Financial Success Of Startups} }
{ "ENTRYTYPE": "article", "ID": "nelson2019theprototypingbehaviors", "abstract": "Prototyping is a crucial part of new product development and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources, and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best …", "author": "Jacob Nelson and Tobias Mahan and Christopher McComb and Jessica Menold", "citation": "ASME 2019 International Design Engineering Technical Conferences and …, 2019", "conference": "ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "The Prototyping Behaviors Of Startups: Exploring The Relationship Between Prototyping Behavior And The Financial Success Of Startups", "volume": null }
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https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/59278/1070210
/scholar?oi=bibs&hl=en&q=related:oKGLz_vCSUQJ:scholar.google.com/
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@article{puentes2018atwo-tieredgrammatical, abstract = {Early stages of the engineering design process are vital to shaping the final design; each subsequent step builds from the initial concept. Innovation-driven engineering problems require designers to focus heavily on early-stage design generation, with constant application and evaluation of design changes. Strategies to reduce the amount of time and effort designers spend in this phase could improve the efficiency of the design process as a whole. This paper seeks to create and demonstrate a two-tiered design grammar that encodes heuristic strategies to aid in the generation of early solution concepts. Specifically, this two-tiered grammar mimics the combination of heuristic-based strategic actions and parametric modifications employed by human designers. Rules in the higher-tier are abstract and potentially applicable to multiple design problems across a number of fields. These abstract rules are translated into …}, author = {Lucas Puentes and Christopher McComb and Jonathan Cagan}, citation = {ASME 2018 International Design Engineering Technical Conferences and …, 2018}, conference = {ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2018}, title = {A Two-Tiered Grammatical Approach For Agent-Based Computational Design} }
{ "ENTRYTYPE": "article", "ID": "puentes2018atwo-tieredgrammatical", "abstract": "Early stages of the engineering design process are vital to shaping the final design; each subsequent step builds from the initial concept. Innovation-driven engineering problems require designers to focus heavily on early-stage design generation, with constant application and evaluation of design changes. Strategies to reduce the amount of time and effort designers spend in this phase could improve the efficiency of the design process as a whole. This paper seeks to create and demonstrate a two-tiered design grammar that encodes heuristic strategies to aid in the generation of early solution concepts. Specifically, this two-tiered grammar mimics the combination of heuristic-based strategic actions and parametric modifications employed by human designers. Rules in the higher-tier are abstract and potentially applicable to multiple design problems across a number of fields. These abstract rules are translated into …", "author": "Lucas Puentes and Christopher McComb and Jonathan Cagan", "citation": "ASME 2018 International Design Engineering Technical Conferences and …, 2018", "conference": "ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": null, "title": "A Two-Tiered Grammatical Approach For Agent-Based Computational Design", "volume": null }
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[ "2518009498725706579", "12679803814073384132" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2018/51753/273606
/scholar?oi=bibs&hl=en&q=related:U-uaUEzE8SIJ:scholar.google.com/
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null
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@article{mccomb2018multi-objectiveoptimizationand, abstract = {Water-lifting technologies for irrigation have significant potential to increase agricultural yields and stimulate economic growth in rural areas of the developing world. Human-powered water pumps have been used with great success in this rapidly developing market. KickStart's MoneyMaker Hip Pump is a human-powered water pump with additional design features that make it lightweight and portable for use in remote fields in several countries throughout Africa. This work first applied numerical optimization techniques to the design of the MoneyMaker Hip Pump and offers further improvements to its design. Deterministic multi-objective optimization methods were employed to maximize the flow rate of the pump, maximize the pumping height of water, and minimize cost. Following optimization, the robustness of the optimized pump design was analyzed under several modified scenarios, including fouling of the hoses …}, author = {Christopher McComb and Nathan G Johnson and Pablo S Santaeufemia and Brandon T Gorman and Brent Kolste and Alexander Mobley and Kenji Shimada}, citation = {Development Engineering 3, 23-33, 2018}, journal = {Development Engineering}, pages = {23-33}, pub_year = {2018}, publisher = {Elsevier}, title = {Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump}, volume = {3} }
{ "ENTRYTYPE": "article", "ID": "mccomb2018multi-objectiveoptimizationand", "abstract": "Water-lifting technologies for irrigation have significant potential to increase agricultural yields and stimulate economic growth in rural areas of the developing world. Human-powered water pumps have been used with great success in this rapidly developing market. KickStart's MoneyMaker Hip Pump is a human-powered water pump with additional design features that make it lightweight and portable for use in remote fields in several countries throughout Africa. This work first applied numerical optimization techniques to the design of the MoneyMaker Hip Pump and offers further improvements to its design. Deterministic multi-objective optimization methods were employed to maximize the flow rate of the pump, maximize the pumping height of water, and minimize cost. Following optimization, the robustness of the optimized pump design was analyzed under several modified scenarios, including fouling of the hoses …", "author": "Christopher McComb and Nathan G Johnson and Pablo S Santaeufemia and Brandon T Gorman and Brent Kolste and Alexander Mobley and Kenji Shimada", "citation": "Development Engineering 3, 23-33, 2018", "conference": null, "journal": "Development Engineering", "number": null, "pages": "23-33", "pub_year": 2018, "publisher": "Elsevier", "title": "Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump", "volume": "3" }
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[ "16943771088046317877" ]
https://www.sciencedirect.com/science/article/pii/S2352728515300737
/scholar?oi=bibs&hl=en&q=related:NeGIWgheJOsJ:scholar.google.com/
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@article{wang2023arcticcoastalhazard, abstract = {The thawing of permafrost in the Arctic has led to an increase in coastal land loss, flooding, and ground subsidence, seriously threatening civil infrastructure and coastal communities. However, a lack of tools for synthetic hazard assessment of the Arctic coast has hindered effective response measures. We developed a holistic framework, the Arctic Coastal Hazard Index (ACHI), to assess the vulnerability of Arctic coasts to permafrost thawing, coastal erosion, and coastal flooding. We quantified the coastal permafrost thaw potential (PTP) through regional assessment of thaw subsidence using ground settlement index. The calculations of the ground settlement index involve utilizing projections of permafrost conditions, including future regional mean annual ground temperature, active layer thickness, and talik thickness. The predicted thaw subsidence was validated through a comparison with observed long-term …}, author = {Ziyi Wang and Ming Xiao and Dmitry Nicolsky and Vladimir Romanovsky and Christopher McComb and Louise Farquharson}, citation = {Environmental Research Letters, 2023}, journal = {Environmental Research Letters}, pub_year = {2023}, title = {Arctic Coastal Hazard Assessment Considering Permafrost Thaw Subsidence, Coastal Erosion, and Flooding} }
{ "ENTRYTYPE": "article", "ID": "wang2023arcticcoastalhazard", "abstract": "The thawing of permafrost in the Arctic has led to an increase in coastal land loss, flooding, and ground subsidence, seriously threatening civil infrastructure and coastal communities. However, a lack of tools for synthetic hazard assessment of the Arctic coast has hindered effective response measures. We developed a holistic framework, the Arctic Coastal Hazard Index (ACHI), to assess the vulnerability of Arctic coasts to permafrost thawing, coastal erosion, and coastal flooding. We quantified the coastal permafrost thaw potential (PTP) through regional assessment of thaw subsidence using ground settlement index. The calculations of the ground settlement index involve utilizing projections of permafrost conditions, including future regional mean annual ground temperature, active layer thickness, and talik thickness. The predicted thaw subsidence was validated through a comparison with observed long-term …", "author": "Ziyi Wang and Ming Xiao and Dmitry Nicolsky and Vladimir Romanovsky and Christopher McComb and Louise Farquharson", "citation": "Environmental Research Letters, 2023", "conference": null, "journal": "Environmental Research Letters", "number": null, "pages": null, "pub_year": 2023, "publisher": null, "title": "Arctic Coastal Hazard Assessment Considering Permafrost Thaw Subsidence, Coastal Erosion, and Flooding", "volume": null }
0P9w_S0AAAAJ:WZBGuue-350C
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/scholar?hl=en&cites=12886341126849971523
[ "12886341126849971523" ]
https://iopscience.iop.org/article/10.1088/1748-9326/acf4ac/meta
/scholar?oi=bibs&hl=en&q=related:Q0Vm6Pp61bIJ:scholar.google.com/
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7
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@article{williams2022designforartificial, abstract = {The intersection between engineering design, manufacturing, and artificial intelligence offers countless opportunities for breakthrough improvements in how we develop new technology. However, achieving this synergy between the physical and the computational worlds involves overcoming a core challenge: few specialists educated today are trained in both engineering design and artificial intelligence. This fact, combined with the recency of both fields’ adoption and the antiquated state of many institutional data management systems, results in an industrial landscape that is relatively devoid of high-quality data and individuals who can rapidly use that data for machine learning and artificial intelligence development. In order to advance the fields of engineering design and manufacturing to the next level of preparedness for the development of effective artificially intelligent, data-driven analytical and …}, author = {Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb}, citation = {Journal of Computing and Information Science in Engineering, 2022}, journal = {Journal of Computing and Information Science in Engineering}, pub_year = {2022}, title = {Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling} }
{ "ENTRYTYPE": "article", "ID": "williams2022designforartificial", "abstract": "The intersection between engineering design, manufacturing, and artificial intelligence offers countless opportunities for breakthrough improvements in how we develop new technology. However, achieving this synergy between the physical and the computational worlds involves overcoming a core challenge: few specialists educated today are trained in both engineering design and artificial intelligence. This fact, combined with the recency of both fields’ adoption and the antiquated state of many institutional data management systems, results in an industrial landscape that is relatively devoid of high-quality data and individuals who can rapidly use that data for machine learning and artificial intelligence development. In order to advance the fields of engineering design and manufacturing to the next level of preparedness for the development of effective artificially intelligent, data-driven analytical and …", "author": "Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb", "citation": "Journal of Computing and Information Science in Engineering, 2022", "conference": null, "journal": "Journal of Computing and Information Science in Engineering", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling", "volume": null }
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/scholar?hl=en&cites=11370795399135551731
[ "11370795399135551731" ]
https://asmedigitalcollection.asme.org/computingengineering/article-abstract/22/6/060903/1147242
/scholar?oi=bibs&hl=en&q=related:8-AeoysuzZ0J:scholar.google.com/
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@article{agrawal2022comparingstrategiesfor, abstract = {The design of cyber-physical systems often involves search within high-dimensional design spaces. When evaluating the performance of algorithms in tasks such as these, the patterns of exploration are often informative and can help support algorithm selection. However, accurately representing these patterns in a way that is human understandable while still preserving the nuanced search complexities in the high-dimensional space is nontrivial. This work specifically examines approaches for visualizing the search trajectories of reinforcement learning agents. We assess trajectories on two exemplar problems: the design of a racecar and the design of an aerial vehicle. We compare and contrast the visualizations produced using PCA, t-SNE, UMAP, TriMap, and PaCMAP. Future work should extend this comparison to a wider variety of exemplar design problems and consider the additional challenges posed by set …}, author = {Akash Agrawal and Christopher McComb}, citation = {2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION), 2022}, conference = {2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)}, pub_year = {2022}, title = {Comparing Strategies for Visualizing the High-Dimensional Exploration Behavior of CPS Design Agents} }
{ "ENTRYTYPE": "article", "ID": "agrawal2022comparingstrategiesfor", "abstract": "The design of cyber-physical systems often involves search within high-dimensional design spaces. When evaluating the performance of algorithms in tasks such as these, the patterns of exploration are often informative and can help support algorithm selection. However, accurately representing these patterns in a way that is human understandable while still preserving the nuanced search complexities in the high-dimensional space is nontrivial. This work specifically examines approaches for visualizing the search trajectories of reinforcement learning agents. We assess trajectories on two exemplar problems: the design of a racecar and the design of an aerial vehicle. We compare and contrast the visualizations produced using PCA, t-SNE, UMAP, TriMap, and PaCMAP. Future work should extend this comparison to a wider variety of exemplar design problems and consider the additional challenges posed by set …", "author": "Akash Agrawal and Christopher McComb", "citation": "2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION), 2022", "conference": "2022 IEEE Workshop on Design Automation for CPS and IoT (DESTION)", "journal": null, "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "Comparing Strategies for Visualizing the High-Dimensional Exploration Behavior of CPS Design Agents", "volume": null }
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/scholar?hl=en&cites=4272110270192051872
[ "4272110270192051872" ]
https://ieeexplore.ieee.org/abstract/document/9805401/
/scholar?oi=bibs&hl=en&q=related:oGYY-KeVSTsJ:scholar.google.com/
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@article{singh2021comparingdesignoutcomes, abstract = {Previous research has shown that experienced and novice individuals behave and think differently. Although experienced individuals are better at solving problems, organisations are constantly forming teams of experienced and novice designers to work together on their projects. It is crucial to understand how these teams affect the design outcomes. Therefore, the aim of the study is to investigate how collaborative design teams perform when composed of varying numbers of experienced and novice agents. Specifically in this paper, teams work on a routine task and design outcomes are measured in terms of quality, variety, and exploration of the design space. Since the parameters in the empirical laboratory experiments are difficult to control, an agent-based model was used to simulate these teams. In general, the results show that a team of novice agents with a small number of experienced agents produces …}, author = {Harshika Singh and Gaetano Cascini and Christopher McComb}, citation = {International Conference on Engineering Design, 2021}, conference = {International Conference on Engineering Design}, pub_year = {2021}, title = {Comparing design outcomes achieved by teams of expert and novice designers through agent-based simulation} }
{ "ENTRYTYPE": "article", "ID": "singh2021comparingdesignoutcomes", "abstract": "Previous research has shown that experienced and novice individuals behave and think differently. Although experienced individuals are better at solving problems, organisations are constantly forming teams of experienced and novice designers to work together on their projects. It is crucial to understand how these teams affect the design outcomes. Therefore, the aim of the study is to investigate how collaborative design teams perform when composed of varying numbers of experienced and novice agents. Specifically in this paper, teams work on a routine task and design outcomes are measured in terms of quality, variety, and exploration of the design space. Since the parameters in the empirical laboratory experiments are difficult to control, an agent-based model was used to simulate these teams. In general, the results show that a team of novice agents with a small number of experienced agents produces …", "author": "Harshika Singh and Gaetano Cascini and Christopher McComb", "citation": "International Conference on Engineering Design, 2021", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Comparing design outcomes achieved by teams of expert and novice designers through agent-based simulation", "volume": null }
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https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/comparing-design-outcomes-achieved-by-teams-of-expert-and-novice-designers-through-agentbased-simulation/C23E83FB5880190DE522A17D1181535B
/scholar?oi=bibs&hl=en&q=related:wT5In29hdqUJ:scholar.google.com/
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@article{pierce2021stochastically-trainedphysics-informedneural, abstract = {Modern digital manufacturing processes, such as additive manufacturing, are cyber-physical in nature and utilize complex, process-specific simulations for both design and manufacturing. Although computational simulations can be used to optimize these complex processes, they can take hours or days — an unreasonable cost for engineering teams leveraging iterative design processes. Hence, more rapid computational methods are necessary in areas where computation time presents a limiting factor. When existing data from historical examples is plentiful and reliable, supervised machine learning can be used to create surrogate models that can be evaluated orders of magnitude more rapidly than comparable finite element approaches. However, for applications that necessitate computationally-intensive simulations, even generating the training data necessary to train a supervised machine learning model can …}, author = {Justin Pierce and Glen Williams and Timothy W. Simpson and Nicholas A. Meisel and Christopher McComb}, citation = {ASME 2021 International Design Engineering Technical Conferences and …, 2021}, conference = {ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2021}, title = {Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion} }
{ "ENTRYTYPE": "article", "ID": "pierce2021stochastically-trainedphysics-informedneural", "abstract": "Modern digital manufacturing processes, such as additive manufacturing, are cyber-physical in nature and utilize complex, process-specific simulations for both design and manufacturing. Although computational simulations can be used to optimize these complex processes, they can take hours or days — an unreasonable cost for engineering teams leveraging iterative design processes. Hence, more rapid computational methods are necessary in areas where computation time presents a limiting factor. When existing data from historical examples is plentiful and reliable, supervised machine learning can be used to create surrogate models that can be evaluated orders of magnitude more rapidly than comparable finite element approaches. However, for applications that necessitate computationally-intensive simulations, even generating the training data necessary to train a supervised machine learning model can …", "author": "Justin Pierce and Glen Williams and Timothy W. Simpson and Nicholas A. Meisel and Christopher McComb", "citation": "ASME 2021 International Design Engineering Technical Conferences and …, 2021", "conference": "ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion", "volume": null }
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[ "10402445181379724165" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2021/V03AT03A004/1128307
/scholar?oi=bibs&hl=en&q=related:hcOcJ8foXJAJ:scholar.google.com/
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@article{song2020topicmodelingand, abstract = {The elicitation of customer pain points is a crucial early step in the design or redesign of successful products and services. Online, user-generated data contains rich, real-time information about customer experience, requirements, and preferences. However, it is a nontrivial task to retrieve useful information from these sources because of the sheer amount of data, often unstructured. In this work, we build on previous efforts that used natural language processing techniques to extract meaning from online data and facilitate experiential redesign and extend them by integrating a sentiment analysis. As a use case, we explore the airline industry. A considerable portion of potential passengers opt out of traveling by airplane due to aviophobia, a fear of flying. This causes a market loss to the industry and inconvenience for those who experience aviophobia. The potential contributors to aviophobia are complex and …}, author = {Binyang Song and Emmett Meinzer and Akash Agrawal and Christopher McComb}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {Topic Modeling and Sentiment Analysis of Social Media Data to Drive Experiential Redesign} }
{ "ENTRYTYPE": "article", "ID": "song2020topicmodelingand", "abstract": "The elicitation of customer pain points is a crucial early step in the design or redesign of successful products and services. Online, user-generated data contains rich, real-time information about customer experience, requirements, and preferences. However, it is a nontrivial task to retrieve useful information from these sources because of the sheer amount of data, often unstructured. In this work, we build on previous efforts that used natural language processing techniques to extract meaning from online data and facilitate experiential redesign and extend them by integrating a sentiment analysis. As a use case, we explore the airline industry. A considerable portion of potential passengers opt out of traveling by airplane due to aviophobia, a fear of flying. This causes a market loss to the industry and inconvenience for those who experience aviophobia. The potential contributors to aviophobia are complex and …", "author": "Binyang Song and Emmett Meinzer and Akash Agrawal and Christopher McComb", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Topic Modeling and Sentiment Analysis of Social Media Data to Drive Experiential Redesign", "volume": null }
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/scholar?hl=en&cites=6122755667427636823
[ "6122755667427636823" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2020/V11AT11A019/1090203
/scholar?oi=bibs&hl=en&q=related:V7aI-9Zl-FQJ:scholar.google.com/
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@article{mccomb2017validatingatool, abstract = {The performance of a team is highly dependent on how the team is structured, how individuals in the team communicate with one another, and the properties exhibited by the problem being solved. It is generally assumed that teams are a superior approach in problem-solving and design. However, this work shows that for a configuration design problem of moderate size, the optimal approach for a homogenous team is in fact for members of the team to work independently, with the best solution from the individuals chosen at the end. Moreover, this work demonstrates that this surprising strategy can be predicted from knowledge of the problem’s properties through a computationally-derived set of response surfaces. First, a novel design problem is defined that requires solvers to create a system of internet-connected products to maintain the temperature within a home. Next, the characteristics of this new design …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {ASME 2017 International Design Engineering Technical Conferences and …, 2017}, conference = {ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2017}, publisher = {ASME}, title = {Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics} }
{ "ENTRYTYPE": "article", "ID": "mccomb2017validatingatool", "abstract": "The performance of a team is highly dependent on how the team is structured, how individuals in the team communicate with one another, and the properties exhibited by the problem being solved. It is generally assumed that teams are a superior approach in problem-solving and design. However, this work shows that for a configuration design problem of moderate size, the optimal approach for a homogenous team is in fact for members of the team to work independently, with the best solution from the individuals chosen at the end. Moreover, this work demonstrates that this surprising strategy can be predicted from knowledge of the problem’s properties through a computationally-derived set of response surfaces. First, a novel design problem is defined that requires solvers to create a system of internet-connected products to maintain the temperature within a home. Next, the characteristics of this new design …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "ASME 2017 International Design Engineering Technical Conferences and …, 2017", "conference": "ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2017, "publisher": "ASME", "title": "Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics", "volume": null }
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https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2017/V007T06A020/258764
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@article{mccomb2015studyinghumandesign, abstract = {Novel design methodologies are often evaluated through empirical studies involving human designers. However, such empirical studies can incur a high personnel cost. Further, it can be difficult to isolate the effects of specific team or individual characteristics. These limitations could be bypassed by employing a computational model of design teams. This work introduces the Cognitively-Inspired Simulated Annealing Teams (CISAT) modeling framework, an agent-based platform that provides a means for efficiently simulating human design teams. A number of empirically demonstrated cognitive phenomena are modeled within the platform, striking a balance between model simplicity and direct applicability to engineering design problems. This paper discusses the composition of the CISAT modeling framework and demonstrates how it can be used to simulate the performance of human design teams in a cognitive …}, author = {Christopher McComb and Jonathan Cagan and Kenneth Kotovsky}, citation = {ASME 2015 International Design Engineering Technical Conferences and …, 2015}, conference = {ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2015}, publisher = {ASME}, title = {Studying Human Design Teams via Computational Teams of Simulated Annealing Agents} }
{ "ENTRYTYPE": "article", "ID": "mccomb2015studyinghumandesign", "abstract": "Novel design methodologies are often evaluated through empirical studies involving human designers. However, such empirical studies can incur a high personnel cost. Further, it can be difficult to isolate the effects of specific team or individual characteristics. These limitations could be bypassed by employing a computational model of design teams. This work introduces the Cognitively-Inspired Simulated Annealing Teams (CISAT) modeling framework, an agent-based platform that provides a means for efficiently simulating human design teams. A number of empirically demonstrated cognitive phenomena are modeled within the platform, striking a balance between model simplicity and direct applicability to engineering design problems. This paper discusses the composition of the CISAT modeling framework and demonstrates how it can be used to simulate the performance of human design teams in a cognitive …", "author": "Christopher McComb and Jonathan Cagan and Kenneth Kotovsky", "citation": "ASME 2015 International Design Engineering Technical Conferences and …, 2015", "conference": "ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2015, "publisher": "ASME", "title": "Studying Human Design Teams via Computational Teams of Simulated Annealing Agents", "volume": null }
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/scholar?hl=en&cites=14974866277703304526,2804882543431237485
[ "14974866277703304526", "2804882543431237485" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2015/V007T06A030/257659
/scholar?oi=bibs&hl=en&q=related:TkV7EYpp0c8J:scholar.google.com/
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@article{mccomb2014researchandpractice, abstract = {Experiential learning is a key component in engineering education. In civil engineering, this component is typically delivered through multiple projects. These projects may include term projects for individual courses, senior design projects, theses, or independent studies. The focus of these experiences may gradually shift from practice-oriented projects in undergraduate studies to research-oriented projects in graduate studies. Thus, learning objectives should always address both areas with a strong emphasis on common fields, such as applied research. Experiential learning has the capacity to include various program-level outcomes, such as technical knowledge, communication and teamwork. Development of a research and practice group facilitates these outcomes by creating an environment to share the learning experience. Such a group should replicate the working environment of civil engineers by incorporating multidisciplinary projects and diverse individuals, including cross-generational members. As a case study, this work examines a Research and Practice Group at California State University Fresno. This group consists of junior and senior undergraduates, graduate students, and former members who are participating as alumni. The major focus of research within the group is resilient and sustainable structural mechanics and design. This paper outlines the methodology that has been employed to ensure academic and professional success for members of the group. This methodology incorporates a recruitment process, meetings, consultation, mentorship, networking, and support. The level of student success achieved by the group …}, author = {Christopher McComb and Fariborz M. Tehrani}, citation = {Proceedings of the 2014 ASEE Pacific-Southwest Conference, 2014}, conference = {Proceedings of the 2014 ASEE Pacific-Southwest Conference}, pub_year = {2014}, title = {Research and Practice Group Methodology: A Case Study in Student Success} }
{ "ENTRYTYPE": "article", "ID": "mccomb2014researchandpractice", "abstract": "Experiential learning is a key component in engineering education. In civil engineering, this component is typically delivered through multiple projects. These projects may include term projects for individual courses, senior design projects, theses, or independent studies. The focus of these experiences may gradually shift from practice-oriented projects in undergraduate studies to research-oriented projects in graduate studies. Thus, learning objectives should always address both areas with a strong emphasis on common fields, such as applied research. Experiential learning has the capacity to include various program-level outcomes, such as technical knowledge, communication and teamwork. Development of a research and practice group facilitates these outcomes by creating an environment to share the learning experience. Such a group should replicate the working environment of civil engineers by incorporating multidisciplinary projects and diverse individuals, including cross-generational members. As a case study, this work examines a Research and Practice Group at California State University Fresno. This group consists of junior and senior undergraduates, graduate students, and former members who are participating as alumni. The major focus of research within the group is resilient and sustainable structural mechanics and design. This paper outlines the methodology that has been employed to ensure academic and professional success for members of the group. This methodology incorporates a recruitment process, meetings, consultation, mentorship, networking, and support. The level of student success achieved by the group …", "author": "Christopher McComb and Fariborz M. Tehrani", "citation": "Proceedings of the 2014 ASEE Pacific-Southwest Conference, 2014", "conference": "Proceedings of the 2014 ASEE Pacific-Southwest Conference", "journal": null, "number": null, "pages": null, "pub_year": 2014, "publisher": null, "title": "Research and Practice Group Methodology: A Case Study in Student Success", "volume": null }
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https://engrxiv.org/preprint/view/224/
/scholar?oi=bibs&hl=en&q=related:SDEmn8c0wTYJ:scholar.google.com/
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@article{nolte2022notimefor, abstract = {Engineering design induces mental stress for students and the sources of stress for each stage of design are unique. Therefore, strategies are needed to manage the stress of engineering design that are applicable across the design process. This study investigated the effect of a brief mindfulness-based intervention on first-year students’ cognitive stress during concept generation, concept selection and physical modelling. It was found that the mindfulness-based intervention did increase one aspect of students’ state mindfulness (though the effect was small). While prior work indicates that increased mindfulness can lower perceived stress, the increase in students’ state mindfulness during this study was not found to have an observable impact on students’ stress experience. However, students were receptive to completing a mindfulness-based activity in-class and perceived multiple benefits. Physical modelling was …}, author = {Hannah Nolte and Jacquelyn Huff and Christopher McComb}, citation = {Design Science, 2022}, journal = {Design Science}, pub_year = {2022}, title = {No Time for That?: An Investigation of Mindfulness and Stress in First-Year Engineering Design} }
{ "ENTRYTYPE": "article", "ID": "nolte2022notimefor", "abstract": "Engineering design induces mental stress for students and the sources of stress for each stage of design are unique. Therefore, strategies are needed to manage the stress of engineering design that are applicable across the design process. This study investigated the effect of a brief mindfulness-based intervention on first-year students’ cognitive stress during concept generation, concept selection and physical modelling. It was found that the mindfulness-based intervention did increase one aspect of students’ state mindfulness (though the effect was small). While prior work indicates that increased mindfulness can lower perceived stress, the increase in students’ state mindfulness during this study was not found to have an observable impact on students’ stress experience. However, students were receptive to completing a mindfulness-based activity in-class and perceived multiple benefits. Physical modelling was …", "author": "Hannah Nolte and Jacquelyn Huff and Christopher McComb", "citation": "Design Science, 2022", "conference": null, "journal": "Design Science", "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "No Time for That?: An Investigation of Mindfulness and Stress in First-Year Engineering Design", "volume": null }
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[ "11393745730042978349" ]
https://www.cambridge.org/core/journals/design-science/article/no-time-for-that-an-investigation-of-mindfulness-and-stress-in-firstyear-engineering-design/DAA4C26F4B576CB38B04AC457FC443FC
/scholar?oi=bibs&hl=en&q=related:LeBV9F-3Hp4J:scholar.google.com/
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@article{krishnakumar2021novicedesigners'use, abstract = {Prototypes are critical design artifacts, and recent studies have established the ability of prototypes to facilitate communication. However, prior work suggests that novice designers often fail to perceive prototypes as effective communication tools, and struggle to rationalize design decisions made during prototyping tasks. To understand the interactions between communication and prototypes, design pitches from 40 undergraduate engineering design teams were collected and qualitatively analysed. Our findings suggest that students used prototypes to explain and persuade, aligning with prior studies of design practitioners. The results also suggest that students tend to use prototypes to justify design decisions and adverse outcomes. Future work will seek to understand novice designers’ use of prototypes as communication tools in further depth. Ultimately, this work will inform the creation of pedagogical strategies …}, author = {Sandeep Krishnakumar and Carlye Lauff and Christopher McComb and Catherine GP Berdanier and Jessica Menold}, citation = {International Conference on Engineering Design, 2021}, conference = {International Conference on Engineering Design}, pub_year = {2021}, title = {Novice Designers' Use of Prototypes as Communication Tools} }
{ "ENTRYTYPE": "article", "ID": "krishnakumar2021novicedesigners'use", "abstract": "Prototypes are critical design artifacts, and recent studies have established the ability of prototypes to facilitate communication. However, prior work suggests that novice designers often fail to perceive prototypes as effective communication tools, and struggle to rationalize design decisions made during prototyping tasks. To understand the interactions between communication and prototypes, design pitches from 40 undergraduate engineering design teams were collected and qualitatively analysed. Our findings suggest that students used prototypes to explain and persuade, aligning with prior studies of design practitioners. The results also suggest that students tend to use prototypes to justify design decisions and adverse outcomes. Future work will seek to understand novice designers’ use of prototypes as communication tools in further depth. Ultimately, this work will inform the creation of pedagogical strategies …", "author": "Sandeep Krishnakumar and Carlye Lauff and Christopher McComb and Catherine GP Berdanier and Jessica Menold", "citation": "International Conference on Engineering Design, 2021", "conference": "International Conference on Engineering Design", "journal": null, "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Novice Designers' Use of Prototypes as Communication Tools", "volume": null }
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/scholar?hl=en&cites=13706191423121443183
[ "13706191423121443183" ]
https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/novice-designers-use-of-prototypes-as-communication-tools/5E978390B30FC49EA79DDB1FFD628373
/scholar?oi=bibs&hl=en&q=related:b8moFnssNr4J:scholar.google.com/
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@article{williams2020derivingmetamodelsto, abstract = {The widespread growth of additive manufacturing, a field with a complex informatic “digital thread”, has helped fuel the creation of design repositories, where multiple users can upload distribute, and download a variety of candidate designs for a variety of situations. Additionally, advancements in additive manufacturing process development, design frameworks, and simulation are increasing what is possible to fabricate with AM, further growing the richness of such repositories. Machine learning offers new opportunities to combine these design repository components’ rich geometric data with their associated process and performance data to train predictive models capable of automatically assessing build metrics related to AM part manufacturability. Although design repositories that can be used to train these machine learning constructs are expanding, our understanding of what makes a particular design repository useful as a machine learning training dataset is minimal. In this study we use a metamodel to predict the extent to which individual design repositories can train accurate convolutional neural networks. To facilitate the creation and refinement of this metamodel, we constructed a large artificial design repository, and subsequently split it into sub-repositories. We then analyzed metadata regarding the size, complexity, and diversity of the sub-repositories for use as independent variables predicting accuracy and the required training computational effort for training convolutional neural networks. The networks each predict one of three additive manufacturing build metrics: (1) part mass, (2) support material mass, and (3) build time. Our …}, author = {Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb}, citation = {ASME 2020 International Design Engineering Technical Conferences and …, 2020}, conference = {ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2020}, title = {Deriving Metamodels to Relate Machine Learning Quality to Repository Characteristics in the Context of Additive Manufacturing} }
{ "ENTRYTYPE": "article", "ID": "williams2020derivingmetamodelsto", "abstract": "The widespread growth of additive manufacturing, a field with a complex informatic “digital thread”, has helped fuel the creation of design repositories, where multiple users can upload distribute, and download a variety of candidate designs for a variety of situations. Additionally, advancements in additive manufacturing process development, design frameworks, and simulation are increasing what is possible to fabricate with AM, further growing the richness of such repositories. Machine learning offers new opportunities to combine these design repository components’ rich geometric data with their associated process and performance data to train predictive models capable of automatically assessing build metrics related to AM part manufacturability. Although design repositories that can be used to train these machine learning constructs are expanding, our understanding of what makes a particular design repository useful as a machine learning training dataset is minimal. In this study we use a metamodel to predict the extent to which individual design repositories can train accurate convolutional neural networks. To facilitate the creation and refinement of this metamodel, we constructed a large artificial design repository, and subsequently split it into sub-repositories. We then analyzed metadata regarding the size, complexity, and diversity of the sub-repositories for use as independent variables predicting accuracy and the required training computational effort for training convolutional neural networks. The networks each predict one of three additive manufacturing build metrics: (1) part mass, (2) support material mass, and (3) build time. Our …", "author": "Glen Williams and Nicholas A Meisel and Timothy W Simpson and Christopher McComb", "citation": "ASME 2020 International Design Engineering Technical Conferences and …, 2020", "conference": "ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Deriving Metamodels to Relate Machine Learning Quality to Repository Characteristics in the Context of Additive Manufacturing", "volume": null }
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/scholar?hl=en&cites=13905421858802690086,7815522752740393145
[ "13905421858802690086", "7815522752740393145" ]
https://par.nsf.gov/biblio/10171192
/scholar?oi=bibs&hl=en&q=related:JujiqYH7-cAJ:scholar.google.com/
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@article{saravanan2019decision-makinginthe, abstract = {Prosthetists face a daunting number of decisions that directly affect an amputee’s ability to walk and indirectly affect the overall quality of life of that amputee. In addition, the lack of resources in low-income countries provides a barrier to receive care after an amputation, and approximately 80% of amputees in low-income countries lack appropriate prosthetic care. In this research, we are motivated to understand what factors affect the decision-making strategies of prosthetists and podiatrists when prescribing prosthetics and orthotics to partial foot amputees. This work establishes a decision-making framework as a step towards automated methods that may reduce the complexities and decision-making burden of prosthetic prescription, ultimately increasing the efficiency of prosthetic prescription in low-resourced areas. A decision-making model is proposed based on an extensive literature review of over 100 …}, author = {Pratima Saravanan and Charity Hippie and Jingxin Wang and Christopher McComb and Jessica Menold}, citation = {ASME 2019 International Design Engineering Technical Conferences and …, 2019}, conference = {ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2019}, title = {Decision-Making In The Prescription Of Orthotics And Prosthetics For Partial-Foot Amputees} }
{ "ENTRYTYPE": "article", "ID": "saravanan2019decision-makinginthe", "abstract": "Prosthetists face a daunting number of decisions that directly affect an amputee’s ability to walk and indirectly affect the overall quality of life of that amputee. In addition, the lack of resources in low-income countries provides a barrier to receive care after an amputation, and approximately 80% of amputees in low-income countries lack appropriate prosthetic care. In this research, we are motivated to understand what factors affect the decision-making strategies of prosthetists and podiatrists when prescribing prosthetics and orthotics to partial foot amputees. This work establishes a decision-making framework as a step towards automated methods that may reduce the complexities and decision-making burden of prosthetic prescription, ultimately increasing the efficiency of prosthetic prescription in low-resourced areas. A decision-making model is proposed based on an extensive literature review of over 100 …", "author": "Pratima Saravanan and Charity Hippie and Jingxin Wang and Christopher McComb and Jessica Menold", "citation": "ASME 2019 International Design Engineering Technical Conferences and …, 2019", "conference": "ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Decision-Making In The Prescription Of Orthotics And Prosthetics For Partial-Foot Amputees", "volume": null }
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https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/V02BT03A001/1069758
/scholar?oi=bibs&hl=en&q=related:sHAf74zj9ScJ:scholar.google.com/
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@article{alzayed2018helpingteamsexpand, abstract = {Product dissection has been highlighted as an effective means of interacting with example products in order to produce creative outcomes. While product dissection is often conducted as a team in engineering design education as a component of larger engineering design projects, the research on the effectiveness of product dissection activities has been primarily limited to individuals. Thus, the goal of this study was to investigate the impact of the type (s) of product dissected in a team environment on the breadth of the design space explored and the underlying influence of educational level on these effects. This was accomplished through a computational simulation of 7,000 nominal brainstorming teams generated by a statistical bootstrapping technique that accounted for all possible team configurations. Specifically, each team was composed of four team members based on a design repository of 463 ideas generated by first-year and senior engineering design students after a product dissection activity. The results of the study highlight that simulated senior engineering design teams explored a larger solution space than simulated first-year teams and that dissecting different types of products allowed for the exploration of a larger solution space for all of the teams. The results also showed that dissecting two analogically far and two simple products was most effective in expanding the solution space for simulated senior teams. The findings presented in this study can lead to a better understanding of how to most effectively deploy product dissection modules in engineering design education in order to maximize the solution space explored.}, author = {Mohammad Alsager Alzayed and Christopher McComb and Samuel T Hunter and Scarlett R Miller}, citation = {ASME 2018 International Design Engineering Technical Conferences and …, 2018}, conference = {ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2018}, publisher = {American Society of Mechanical Engineers Digital Collection}, title = {Helping Teams Expand the Breadth of Their Solution Space Through Product Dissection: A Simulation Based Investigation} }
{ "ENTRYTYPE": "article", "ID": "alzayed2018helpingteamsexpand", "abstract": "Product dissection has been highlighted as an effective means of interacting with example products in order to produce creative outcomes. While product dissection is often conducted as a team in engineering design education as a component of larger engineering design projects, the research on the effectiveness of product dissection activities has been primarily limited to individuals. Thus, the goal of this study was to investigate the impact of the type (s) of product dissected in a team environment on the breadth of the design space explored and the underlying influence of educational level on these effects. This was accomplished through a computational simulation of 7,000 nominal brainstorming teams generated by a statistical bootstrapping technique that accounted for all possible team configurations. Specifically, each team was composed of four team members based on a design repository of 463 ideas generated by first-year and senior engineering design students after a product dissection activity. The results of the study highlight that simulated senior engineering design teams explored a larger solution space than simulated first-year teams and that dissecting different types of products allowed for the exploration of a larger solution space for all of the teams. The results also showed that dissecting two analogically far and two simple products was most effective in expanding the solution space for simulated senior teams. The findings presented in this study can lead to a better understanding of how to most effectively deploy product dissection modules in engineering design education in order to maximize the solution space explored.", "author": "Mohammad Alsager Alzayed and Christopher McComb and Samuel T Hunter and Scarlett R Miller", "citation": "ASME 2018 International Design Engineering Technical Conferences and …, 2018", "conference": "ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2018, "publisher": "American Society of Mechanical Engineers Digital Collection", "title": "Helping Teams Expand the Breadth of Their Solution Space Through Product Dissection: A Simulation Based Investigation", "volume": null }
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@article{santaeufemia2014improvingirrigationin, abstract = {Water-lifting technologies in rural areas of the developing world have enormous potential to stimulate agricultural and economic growth. The treadle pump, a human-powered low-cost pump designed for irrigation in developing countries, can help farmers maximize financial return on small plots of land by ending their dependency on rain-fed irrigation systems. The treadle pump uses a suction piston to draw groundwater to the surface by way of a foot-powered treadle attached to each suction piston. Current treadle pump designs lift water from depths up to 7 meters at a flow-rate of 1–5 liters per second. This work seeks to optimize the design of the Dekhi style treadle pump, which has gained significant popularity due to its simplicity. A mathematical model of the working fluid and treadle pump structure has been developed in this study. Deterministic optimization methods are then employed to maximize the flow rate …}, author = {Pablo S. Santaeufemia and Nathan G Johnson and Christopher McComb and Kenji Shimada}, citation = {ASME 2014 International Design Engineering Technical Conferences and …, 2014}, conference = {ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2014}, title = {Improving Irrigation in Remote Areas: Multi-objective Optimization of a Treadle Pump} }
{ "ENTRYTYPE": "article", "ID": "santaeufemia2014improvingirrigationin", "abstract": "Water-lifting technologies in rural areas of the developing world have enormous potential to stimulate agricultural and economic growth. The treadle pump, a human-powered low-cost pump designed for irrigation in developing countries, can help farmers maximize financial return on small plots of land by ending their dependency on rain-fed irrigation systems. The treadle pump uses a suction piston to draw groundwater to the surface by way of a foot-powered treadle attached to each suction piston. Current treadle pump designs lift water from depths up to 7 meters at a flow-rate of 1–5 liters per second. This work seeks to optimize the design of the Dekhi style treadle pump, which has gained significant popularity due to its simplicity. A mathematical model of the working fluid and treadle pump structure has been developed in this study. Deterministic optimization methods are then employed to maximize the flow rate …", "author": "Pablo S. Santaeufemia and Nathan G Johnson and Christopher McComb and Kenji Shimada", "citation": "ASME 2014 International Design Engineering Technical Conferences and …, 2014", "conference": "ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2014, "publisher": null, "title": "Improving Irrigation in Remote Areas: Multi-objective Optimization of a Treadle Pump", "volume": null }
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/scholar?hl=en&cites=3163948522165700926,17197199320482730626
[ "3163948522165700926", "17197199320482730626" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2014/V02AT03A049/255967
/scholar?oi=bibs&hl=en&q=related:PglP52qa6CsJ:scholar.google.com/
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@article{baldwin2022adata-drivenapproach, abstract = {Additive manufacturing is advantageous for producing lightweight components while maintaining function and form. This ability has been bolstered by the introduction of unit lattice cells and the gradation of those cells. In cases where loading varies throughout a part, it may be necessary to use multiple lattice cell types, also known as multi-lattice structures. In such structures, abrupt transitions between geometries may cause stress concentrations, making the boundary a primary failure point; thus, transition regions should be created between each lattice cell type. Although computational approaches have been proposed, smooth transition regions are still difficult to intuit and design, especially between lattices of drastically different geometries. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of transitional lattice cells. In particular, the work focuses on identifying the relationships that exist within the latent space produced by the variational autoencoder. Through computational experimentation, it was found that the smoothness of transition regions was higher when the endpoints were located closer together in the latent space.}, author = {Martha Baldwin and Nicholas A Meisel and Christopher McComb}, citation = {2022 International Solid Freeform Fabrication Symposium, 2022}, conference = {2022 International Solid Freeform Fabrication Symposium}, pub_year = {2022}, title = {A Data-driven Approach for Multi-Lattice Transitions} }
{ "ENTRYTYPE": "article", "ID": "baldwin2022adata-drivenapproach", "abstract": "Additive manufacturing is advantageous for producing lightweight components while maintaining function and form. This ability has been bolstered by the introduction of unit lattice cells and the gradation of those cells. In cases where loading varies throughout a part, it may be necessary to use multiple lattice cell types, also known as multi-lattice structures. In such structures, abrupt transitions between geometries may cause stress concentrations, making the boundary a primary failure point; thus, transition regions should be created between each lattice cell type. Although computational approaches have been proposed, smooth transition regions are still difficult to intuit and design, especially between lattices of drastically different geometries. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of transitional lattice cells. In particular, the work focuses on identifying the relationships that exist within the latent space produced by the variational autoencoder. Through computational experimentation, it was found that the smoothness of transition regions was higher when the endpoints were located closer together in the latent space.", "author": "Martha Baldwin and Nicholas A Meisel and Christopher McComb", "citation": "2022 International Solid Freeform Fabrication Symposium, 2022", "conference": "2022 International Solid Freeform Fabrication Symposium", "journal": null, "number": null, "pages": null, "pub_year": 2022, "publisher": null, "title": "A Data-driven Approach for Multi-Lattice Transitions", "volume": null }
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/scholar?hl=en&cites=5791427426123906708
[ "5791427426123906708" ]
https://par.nsf.gov/biblio/10439734
/scholar?oi=bibs&hl=en&q=related:lP6RTI9IX1AJ:scholar.google.com/
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@article{bracken2021partfilteringmethods, abstract = {As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has its own benefits and drawbacks. This paper reviews 13 published part filtering methods and compares their advantages and disadvantages. The methods for part filtering are categorized and sorted along a continuum of opportunistic and restrictive design for AM guidelines in order to ascertain how parts are evaluated and screened. The methods are also examined through the lens of process-specificity, as some are designed to be process-agnostic, while others are customized for a specific AM technology or even a specific AM system. Based upon this analysis, a novel …}, author = {Jennifer E Bracken and Timothy W Simpson and Christopher McComb and Kathryn Jablokow and Joseph Hamann}, citation = {Additive Manufacturing, 2021}, journal = {Additive Manufacturing}, pub_year = {2021}, title = {Part Filtering Methods for Additive Manufacturing: A Detailed Review and a Novel Process-Agnostic Method  } }
{ "ENTRYTYPE": "article", "ID": "bracken2021partfilteringmethods", "abstract": "As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has its own benefits and drawbacks. This paper reviews 13 published part filtering methods and compares their advantages and disadvantages. The methods for part filtering are categorized and sorted along a continuum of opportunistic and restrictive design for AM guidelines in order to ascertain how parts are evaluated and screened. The methods are also examined through the lens of process-specificity, as some are designed to be process-agnostic, while others are customized for a specific AM technology or even a specific AM system. Based upon this analysis, a novel …", "author": "Jennifer E Bracken and Timothy W Simpson and Christopher McComb and Kathryn Jablokow and Joseph Hamann", "citation": "Additive Manufacturing, 2021", "conference": null, "journal": "Additive Manufacturing", "number": null, "pages": null, "pub_year": 2021, "publisher": null, "title": "Part Filtering Methods for Additive Manufacturing: A Detailed Review and a Novel Process-Agnostic Method  ", "volume": null }
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[ "7304706871351085343", "9465173075577055743" ]
https://www.sciencedirect.com/science/article/pii/S2214860421002803
/scholar?oi=bibs&hl=en&q=related:H4k8jzKIX2UJ:scholar.google.com/
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@article{khanolkar2020usingdeepimage, abstract = {The microstructure of a material governs mechanical properties such as strength and toughness. Various finite element analysis (FEA) software packages are used to perform structural analyses such as predicting the flow of strain or strain fields in a microstructure. Engineers frequently operate these software packages to evaluate mechanical behavior and predict failure. Even though these FEA software packages provide highly accurate analyses, they are computationally intensive, taking a significant amount of time to produce a solution. The time required by the FEA software packages to achieve accurate results largely depends on microstructure details and mesh resolution, thus providing a trade-off between fidelity and computation time. This research proposes the use of Deep Learning algorithms to achieve a significant reduction in the time required to predict high-accuracy strain fields in a two-dimensional …}, author = {Pranav Milind Khanolkar and Aaron Abraham and Christopher McComb and Saurabh Basu}, citation = {North American Manufacturing Research Conference, 2020}, conference = {North American Manufacturing Research Conference}, pub_year = {2020}, title = {Using Deep Image Colorization to Predict Microstructure-Dependent Strain Fields} }
{ "ENTRYTYPE": "article", "ID": "khanolkar2020usingdeepimage", "abstract": "The microstructure of a material governs mechanical properties such as strength and toughness. Various finite element analysis (FEA) software packages are used to perform structural analyses such as predicting the flow of strain or strain fields in a microstructure. Engineers frequently operate these software packages to evaluate mechanical behavior and predict failure. Even though these FEA software packages provide highly accurate analyses, they are computationally intensive, taking a significant amount of time to produce a solution. The time required by the FEA software packages to achieve accurate results largely depends on microstructure details and mesh resolution, thus providing a trade-off between fidelity and computation time. This research proposes the use of Deep Learning algorithms to achieve a significant reduction in the time required to predict high-accuracy strain fields in a two-dimensional …", "author": "Pranav Milind Khanolkar and Aaron Abraham and Christopher McComb and Saurabh Basu", "citation": "North American Manufacturing Research Conference, 2020", "conference": "North American Manufacturing Research Conference", "journal": null, "number": null, "pages": null, "pub_year": 2020, "publisher": null, "title": "Using Deep Image Colorization to Predict Microstructure-Dependent Strain Fields", "volume": null }
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/scholar?hl=en&cites=4376103210618094478
[ "4376103210618094478" ]
https://www.sciencedirect.com/science/article/pii/S2351978920315900
/scholar?oi=bibs&hl=en&q=related:joNWOa8KuzwJ:scholar.google.com/
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@article{maier2019assessingtheimpact, abstract = {Cognitive assistants, such as Apple’s Siri or Amazon’s Alexa, are increasingly becoming routine elements of our daily lives, yet the effects of such devices on the humans using them has been largely unstudied. While much research has proposed new intelligent systems for specific contexts, few studies have characterized the dynamics between cognitive assistants and humans. In an effort to address this gap, this research study investigates the effect of cognitive assistants on mental workload. Participants perform the Wisconsin Card Sorting Task while working with a fake cognitive assistant (Mary) and concurrently completing a secondary speed and accuracy test. Performance with the cognitive assistant was found to be higher but with no significant difference in mental workload. Participants working with the cognitive assistant were found to be less frustrated than those completing the task without it.}, author = {Torsten Maier and Vincent Donghia and Chaoran Chen and Jessica Menold and Christopher McComb}, citation = {ASME 2019 International Design Engineering Technical Conferences and …, 2019}, conference = {ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, pub_year = {2019}, title = {Assessing The Impact Of Cognitive Assistants On Mental Workload In Simple Tasks} }
{ "ENTRYTYPE": "article", "ID": "maier2019assessingtheimpact", "abstract": "Cognitive assistants, such as Apple’s Siri or Amazon’s Alexa, are increasingly becoming routine elements of our daily lives, yet the effects of such devices on the humans using them has been largely unstudied. While much research has proposed new intelligent systems for specific contexts, few studies have characterized the dynamics between cognitive assistants and humans. In an effort to address this gap, this research study investigates the effect of cognitive assistants on mental workload. Participants perform the Wisconsin Card Sorting Task while working with a fake cognitive assistant (Mary) and concurrently completing a secondary speed and accuracy test. Performance with the cognitive assistant was found to be higher but with no significant difference in mental workload. Participants working with the cognitive assistant were found to be less frustrated than those completing the task without it.", "author": "Torsten Maier and Vincent Donghia and Chaoran Chen and Jessica Menold and Christopher McComb", "citation": "ASME 2019 International Design Engineering Technical Conferences and …, 2019", "conference": "ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference", "journal": null, "number": null, "pages": null, "pub_year": 2019, "publisher": null, "title": "Assessing The Impact Of Cognitive Assistants On Mental Workload In Simple Tasks", "volume": null }
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/scholar?hl=en&cites=9101161226199272232
[ "9101161226199272232" ]
https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2019/59278/1070129
/scholar?oi=bibs&hl=en&q=related:KIsqS-rRTX4J:scholar.google.com/
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