ccm/publications huggingface dataset:
Comparing design outcomes achieved by teams of expert and novice designers through agent-based simulation
Authors: Harshika Singh and Gaetano Cascini and Christopher McComb
Published in: International Conference on Engineering Design, 2021

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 …
Designing Improved Teams for Crowdsourced Competitions
Authors: Christopher McComb and Torsten Maier
Published in: ASME 2018 International Design Engineering Technical Conferences and …, 2018

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.
Uncovering Potential Bias in Engineering Design: A Comparative Review of Bias Research in Medicine
Authors: Malena Agyemang and Adriana Andreae and Christopher McComb
Published in: Design Science, 2023

Engineering design research has focused on developing and refining methods and evaluating design education in design education, design research and design in practice. One important aspect that is not thoroughly investigated is the influence of bias on design within these spaces of design. Bias is known to impact the interpretation of information, decision-making and practices in all areas. These factors are vital in engineering design education, practice and research, emphasizing the importance of investigating bias. The first goal of this study is to highlight and synthesize existing bias research in design education, research and practice. The second goal is to identify areas where bias may be under-researched or under-reported in design. To achieve these goals, a comparative analysis is performed against a comparable field: medicine. Many parallels exist between both fields. Patient–provider and designer …
A Query Conundrum: The Mental Challenges of Using a Cognitive Assistant
Authors: Torsten Maier and Saeed Abdullah and Christopher McComb and Jessica Menold
Published in: SN Computer Science, 2021

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 …
Identifying Stress Signatures Across the Engineering Design Process: Perceived Stress During Concept Generation, Concept Selection, and Prototyping
Authors: Hannah Nolte and Christopher McComb
Published in: International Design Conference - DESIGN 2020, 2020

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.
The Prototyping Behaviors Of Startups: Exploring The Relationship Between Prototyping Behavior And The Financial Success Of Startups
Authors: Jacob Nelson and Tobias Mahan and Christopher McComb and Jessica Menold
Published in: ASME 2019 International Design Engineering Technical Conferences and …, 2019

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 …
A Two-Tiered Grammatical Approach For Agent-Based Computational Design
Authors: Lucas Puentes and Christopher McComb and Jonathan Cagan
Published in: ASME 2018 International Design Engineering Technical Conferences and …, 2018

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 …
Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump
Authors: Christopher McComb and Nathan G Johnson and Pablo S Santaeufemia and Brandon T Gorman and Brent Kolste and Alexander Mobley and Kenji Shimada
Published in: Development Engineering 3, 23-33, 2018

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 …
Emerging Technologies and Methods for Early-Stage Product Design and Development
Authors: Mohsen Moghaddam and Tucker Marion and Katja Holtta-Otto and Katherine Fu and Alison Olechowski and Christopher McComb
Published in: Journal of Mechanical Design, 2023

The early-stage product design and development (PDD) process fundamentally involves the processing, synthesis, and communication of a large amount of information to make a series of key decisions on design exploration and specification, concept generation and evaluation, and prototyping. Although most current PDD practices depend heavily on human intuition, advances in computing, communication, and human–computer interaction technologies can transform PDD processes by combining the creativity and ingenuity of human designers with the speed and precision of computers. Emerging technologies like artificial intelligence (AI), cloud computing, and extended reality (XR) stand to substantially change the way designers process information and make decisions in the early stages of PDD by enabling new methods such as natural language processing, generative modeling, cloud-based virtual …
Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion
Authors: Justin Pierce and Glen Williams and Timothy W. Simpson and Nicholas A. Meisel and Christopher McComb
Published in: ASME 2021 International Design Engineering Technical Conferences and …, 2021

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 …
Topic Modeling and Sentiment Analysis of Social Media Data to Drive Experiential Redesign
Authors: Binyang Song and Emmett Meinzer and Akash Agrawal and Christopher McComb
Published in: ASME 2020 International Design Engineering Technical Conferences and …, 2020

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 …
Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics
Authors: Christopher McComb and Jonathan Cagan and Kenneth Kotovsky
Published in: ASME 2017 International Design Engineering Technical Conferences and …, 2017

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 …
Studying Human Design Teams via Computational Teams of Simulated Annealing Agents
Authors: Christopher McComb and Jonathan Cagan and Kenneth Kotovsky
Published in: ASME 2015 International Design Engineering Technical Conferences and …, 2015

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 …
Research and Practice Group Methodology: A Case Study in Student Success
Authors: Christopher McComb and Fariborz M. Tehrani
Published in: Proceedings of the 2014 ASEE Pacific-Southwest Conference, 2014

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 …
Accelerating Thermal Simulations in Additive Manufacturing by Training Physics-Informed Neural Networks with Randomly-Synthesized Data
Authors: Jiangce Chen and Justin Pierce and Glen Williams and Timothy W Simpson and Nicholas A Meisel and Sneha Prabha Narra and Christopher McComb
Published in: Journal of Computing and Information Science in Engineering 24 (1), 011004, 2024

The temperature history of an additively-manufactured part plays a critical role in determining process-structure-property relationships in fusion-based additive manufacturing (AM) processes. Therefore, fast thermal simulation methods are needed for a variety of AM tasks, from temperature history prediction for part design and process planning to in-situ temperature monitoring and control during manufacturing. However, conventional numerical simulation methods fall short in satisfying the strict requirements of these applications due to the large space and time scales involved. While data-driven surrogate models are of interest for their rapid computation capabilities, the performance of these models relies on the size and quality of the training data, which is often prohibitively expensive to create. Physics-informed neural networks (PINNs) mitigate the need for large datasets by imposing physical principles during the …
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs
Authors: Adam Cobb and Anirban Roy and Daniel Elenius and F. Michael Heim and Brian Swenson and Sydney Whittington and James D. Walker and Theodore Bapty and Joseph Hite and Karthik Ramani and Christopher McComb and Susmit Jha
Published in: Advances in Neural Information Processing Systems (NeurIPS 2023) Datasets …, 2023

We present AircraftVerse, a publicly available aerial vehicle design dataset. Aircraft design encompasses different physics domains and, hence, multiple modalities of representation. The evaluation of these designs requires the use of scientific analytical and simulation models ranging from computer-aided design tools for structural and manufacturing analysis, computational fluid dynamics tools for drag and lift computation, battery models for energy estimation, and simulation models for flight control and dynamics. AircraftVerse contains  diverse air vehicle designs-the largest corpus of designs with this level of complexity. Each design comprises the following artifacts: a symbolic design tree describing topology, propulsion subsystem, battery subsystem, and other design details; a STandard for the Exchange of Product (STEP) model data; a 3D CAD design using a stereolithography (STL) file format; a 3D point cloud for the shape of the design; and evaluation results from high fidelity state-of-the-art physics models that characterize performance metrics such as maximum flight distance and hover-time. We also present baseline surrogate models that use different modalities of design representation to predict design performance metrics, which we provide as part of our dataset release. Finally, we discuss the potential impact of this dataset on the use of learning in aircraft design, and more generally, in the emerging field of deep learning for scientific design. AircraftVerse is accompanied by a datasheet as suggested in the recent literature, and it is released under Creative Commons Attribution-ShareAlike (CC BY-SA) license. The dataset with …
Virtual and face-to-face team collaboration comparison through an agent-based simulation
Authors: Harshika Singh and Gaetano Cascini and Christopher McComb
Published in: Journal of Mechanical Design, 2022

The ongoing COVID-19 pandemic has accelerated the acceptance of virtual team collaboration as a replacement for face-to-face collaboration. Unlike face-to-face collaboration, virtual collaboration is influenced by unique factors, such as technology mediation. However, there is a lack of rigorous research that assesses the impact of virtual collaboration on the engineering design process. Therefore, the current study investigates the effect of virtual team collaboration on design outcomes by means of the model of influence, learning, and norms in organizations (MILANO) framework. To tailor MILANO for virtual collaboration, this paper first presents an empirical study of human design teams, which shows how model parameter values for face-to-face collaboration (like self-efficacy, perceived influencers, perceived degree of influence, trust and familiarity) differ from appropriate parameter values for face-to-face …
Part Filtering Methods for Additive Manufacturing: A Detailed Review and a Novel Process-Agnostic Method  
Authors: Jennifer E Bracken and Timothy W Simpson and Christopher McComb and Kathryn Jablokow and Joseph Hamann
Published in: Additive Manufacturing, 2021

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 …
Novice Designers' Use of Prototypes as Communication Tools
Authors: Sandeep Krishnakumar and Carlye Lauff and Christopher McComb and Catherine GP Berdanier and Jessica Menold
Published in: International Conference on Engineering Design, 2021

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 …