ccm/publications huggingface dataset:
Toward a Permafrost Vulnerability Index for Critical Infrastructure, Community Resilience and National Security
Authors: Lilian Alessa and James Valentine and Sean Moon and Christopher McComb and Sierra Hicks and Vladimir Romanovsky and Ming Xiao and Andrew Kliskey
Published in: Geographies, 2023

There has been a growth in the number of composite indicator tools used to assess community risk, vulnerability, and resilience, to assist study and policy planning. However, existing research shows that these composite indicators vary extensively in method, selected variables, aggregation methods, and sample size. The result is a plethora of qualitative and quantitative composite indices to choose from. Despite each providing valuable location-based information about specific communities and their qualities, the results of studies, each using disparate methods, cannot easily be integrated for use in decision making, given the different index attributes and study locations. Like many regions in the world, the Arctic is experiencing increased variability in temperatures as a direct consequence of a changing planetary climate. Cascading effects of changes in permafrost are poorly characterized, thus limiting response at multiple scales. We offer that by considering the spatial interaction between the effects of permafrost, infrastructure, and diverse patterns of community characteristics, existing research using different composite indices and frameworks can be augmented. We used a system-science and place-based knowledge approach that accounts for sub-system and cascade impacts through a proximity model of spatial interaction. An estimated ‘permafrost vulnerability surface’ was calculated across Alaska using two existing indices: relevant infrastructure and permafrost extent. The value of this surface in 186 communities and 30 military facilities was extracted and ordered to match the numerical rankings of the Denali Commission in their …
Smoothing the Rough Edges: Evaluating Automatically Generated Multi-Lattice Transitions
Authors: Martha Baldwin and Nicholas A Meisel and Christopher McComb
Published in: 3D Printing and Additive Manufacturing, 2023

Additive manufacturing is advantageous for producing lightweight components while addressing complex design requirements. This capability 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 beneficial to use multiple, distinct lattice cell types, resulting in multi-lattice structures. In such structures, abrupt transitions between unit cell topologies may cause stress concentrations, making the boundary between unit cell types a primary failure point. Thus, these regions require careful design to ensure the overall functionality of the part. Although computational design approaches have been proposed, smooth transition regions are still difficult to achieve, especially between lattices of drastically different topologies. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of …
Exploring the Impact of Set-Based Concurrent Engineering Through Multi Agent System Simulation
Authors: Sean Rismiller and Jonathan Cagan and Christopher McComb
Published in: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2023

Set-based concurrent engineering (SBCE), a process that develops sets of many design candidates for each subproblem throughout a design project, proposes several benefits compared to point-based processes, where only one design candidate for each subproblem is chosen for further development. These benefits include reduced rework, improved design quality, and retention of knowledge to use in future projects. Previous studies that introduce SBCE in practice achieved success and had very positive future outlooks, but SBCE encounters opposition because its core procedures appear wasteful as designers must divide their time among many designs throughout the process, most of which are ultimately not used. The impacts of these procedures can be explored in detail through open-source computational tools, but currently few exist to do this. This work introduces the Point/Set-Organized Research Teams …
MegaFlow2D: A Parametric Dataset for Machine Learning Super-resolution in Computational Fluid Dynamics Simulations
Authors: Wenzhuo Xu and Noelia Grande Gutierrez and Christopher McComb
Published in: 2023 IEEE Workshop on Design Automation for CPS and IoT (DESTION), 2023

 This paper introduces MegaFlow2D, a dataset of over 2 million snapshots of parameterized 2D fluid dynamics simulations of 3000 different external flow and internal flow configurations. It’s worth noting that, simulation results on both low and high mesh resolutions are provided to facilitate the training of machine learning (ML) models for super-resolution purposes. This is the first large-scale multi-fidelity fluid dynamics dataset ever provided. We build the entire data generation and simulation workflow on open-source and efficient interfaces that can be utilized for a variety of data samples according to the user’s specific needs. Finally, we provide a use case to demonstrate the potential value of the MegaFlow2D dataset in applications related to error correction.
Uncovering Hidden Patterns of Design Ideation Using Hidden Markov Modeling and Neuroimaging
Authors: Mo Hu and Christopher McComb and Kosa Goucher-Lambert
Published in: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2023

The study presented in this paper applies hidden Markov modeling (HMM) to uncover the recurring patterns within a neural activation dataset collected while designers engaged in a design concept generation task. HMM uses a probabilistic approach that describes data (here, fMRI neuroimaging data) as a dynamic sequence of discrete states. Without prior assumptions on the fMRI data's temporal and spatial properties, HMM enables an automatic inference on states in neurocognitive activation data that are highly likely to occur in concept generation. The states with a higher likelihood of occupancy show more activation in the brain regions from the executive control network, the default mode network, and the middle temporal cortex. Different activation patterns and transfers are associated with these states, linking to varying cognitive functions, for example, semantic processing, memory retrieval, executive control …
DTM Past, Present, and Future: Reflections on and by the Design Theory and Methodology Research Community
Authors: Christine Toh and Jonathan Cagan and Katherine Fu and Dan A. McAdams and Christopher McComb and Warren Seering and Deborah Thurston and Kristin Wood
Published in: ASME 2022 International Design Engineering Technical Conferences and …, 2022

This paper describes the results of an agenda-setting panel session that took place at the 2021 International Design Engineering Technical Conferences organized by the Design Theory and Methodology (DTM) research community. While the state of design research in engineering design has advanced tremendously in the last thirty-five years since the formation of the DTM community, reflecting on the successes and challenges faced by this community revealed several key directions and opportunities that this community is well positioned to take. Namely, panelists and audience members in the session identified five new agenda items that have the potential to further strengthen research on Design Theory and Methodology: 1) Ethics, Equity, and Justice-focused design research, 2) Design for Sustainability research programs, and 3) Research on Computational Agents as team members in the design …
Data on the Human versus Artificial Intelligence Process Management Experiment
Authors: Nicolas F Soria Zurita and Joshua T. Gyory and Corey Balon and Jay Martin and Kenneth Kotovsky and Jonathan Cagan and Christopher McComb
Published in: Data in Brief, 2022

Human subject experiments are performed to evaluate the influence of artificial intelligence (AI) process management on human design teams solving a complex engineering problem and compare that to the influence of human process management. Participants are grouped into teams of five individuals and asked to generate a drone fleet and plan routes to deliver parcels to a given customer market. The teams are placed under the guidance of either a human or an AI external process manager. Halfway through the experiment, the customer market is changed unexpectedly, requiring teams to adjust their strategy. During the experiment, participants can create, evaluate, share their drone designs and delivery routes, and communicate with their team through a text chat tool using a collaborative research platform called HyForm. The research platform collects step-by-step logs of the actions made by and …
Influencers in Design Teams: A Computational Framework to Study their Impact on Idea Generation
Authors: Harshika Singh and Gaetano Cascini and Christopher McComb
Published in: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2021

It is known that wherever there is human interaction, there is social influence. Here, we refer to more influential individuals as “influencers”, who drive team processes for better or worst. Social influence gives rise to social learning, the propensity of humans to mimic the most influential individuals. As individual learning is affected by the presence of an influencer, so is an individual's idea generation . Examining this phenomenon through a series of human studies would require an enormous amount of time to study both individual and team behaviors that affect design outcomes. Hence, this paper provides an agent-based approach to study the effect of influencers during idea generation. This model is supported by the results of two empirical experiments which validate the assumptions and sustain the logic implemented in the model. The results of the model simulation make it possible to examine the impact of …
Comparing Virtual and Face-to-Face Team Collaboration: Insights From an Agent-Based Simulation
Authors: Harshika Singh and Gaetano Cascini and Christopher McComb
Published in: ASME 2021 International Design Engineering Technical Conferences and …, 2021

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 has different factors like technology mediation influencing communication that affects a team’s processes. However, there is a lack of rigorous research that assesses the impact of virtual teaming on the engineering design process. Therefore, the current study investigates the effect of virtual team collaboration on design outcomes by means of the MILANO (Model of Influence, Learning, and Norms in Organizations) framework. To tailor MILANO for virtual collaboration, this paper first presents an empirical study of human design teams, that shows how the model parameters for face-to-face collaboration (like self-efficacy, perceived influencers, perceived degree of influence, trust and familiarity) must be modified. The …
Comparing Student and Sponsor Perceptions of Interdisciplinary Teams' Capstone Performance
Authors: Sandeep Krishnakumar and Catherine GP Berdanier and Christopher McComb and Matthew Parkinson and Jessica Menold
Published in: ASME 2020 International Design Engineering Technical Conferences and …, 2020

The purpose of this work is to investigate the relationship between the disciplinary diversity of capstone design teams and perceptions of success and engineering design abilities. Capstone design programs are effective environments for students to collaborate with industry sponsors on authentic design problems. They provide students with the opportunity to hone their technical and professional skills, often in teams. Previous work has demonstrated that interdisciplinary teams outperform within-discipline teams on complex open-ended tasks, but struggle to communicate across disciplinary boundaries. They also report lower levels of team cohesion and satisfaction with final outcomes. The results of the mixed-methods study conducted with 58 capstone design teams for this paper indicate that team diversity may be inversely related to students’ beliefs in their abilities to construct a prototype. Preliminary …
Modelling the Dynamics of Influence on Individual Thinking During Idea Generation in Co-design Teams
Authors: Harshika Singh and Christopher McComb and Gaetano Cascini
Published in: Ninth International Conference on Design Computing and Cognition, 2020

Social influence is not evenly distributed in teams. Some individuals, referred to here as influencers, become more influential than others. Consequentially, these influencers play a significant role in shaping project performance. The current work simulates the presence of influencers during idea generation in co-design teams to better understand emergent socio-cognitive phenomena. Besides providing, a novel approach for modelling learning in concept generation the model highlights the results related to individual cognition during idea generation. Idea quality and exploration of design space are affected by the presence of influencers in design teams. Teams with no well-defined influencers produce solutions with high general exploration but less quality. In contrast, the agents in the teams with only one influencer produce solutions high quality than those teams with no influencers.
Designing the Characteristics of Design Teams via Cognitively-Inspired Computational Modeling
Authors: Christopher McComb
Published in: Carnegie Mellon University, 2016

Teams are a ubiquitous part of the design process and a great deal of time and effort is devoted to managing them effectively. Although teams have the potential to search effectively for solutions, they are also prone to a number of pitfalls. Thus, a greater understanding of teams is necessary to ensure that they can function optimally across a variety of tasks. Teams are typically studied through controlled laboratory experiments or through longitudinal studies that observe teams in situ. However, both of these study types can be costly and time-consuming. Months, if not years, pass between the initial conception of a study and the final analysis of results. This work creates a computational framework that efficiently emulates human design teams, thus facilitating the derivation of a theory linking the properties of design problems to optimized team characteristics, effectively making it possible to design design teams.
Scenario-Based Robustness Analysis of Optimized I.D.E.-Style Treadle Pump Designs
Authors: Christopher McComb and Nathan G Johnson and Brandon T Gorman
Published in: ASME 2016 International Design Engineering Technical Conferences and …, 2016

Poverty affects hundreds of millions of people globally. Market-based strategies can help alleviate poverty in developing countries by encouraging entrepreneurial activity and have the potential to be more effective than traditional approaches, such as development aid from countries or non-governmental organizations. Development organizations often target the agricultural sector because of the prevalence of subsistence and small-scale farming, particularly in rural regions of developing countries. Improving the reliability of irrigation techniques can help farmers expand out of primarily subsistence farming and begin to sell a portion of their crop, thus achieving the objectives of market-based poverty alleviation. Human-powered pumps are a popular tool used in irrigation because they require low capital cost and negligible operating cost. Previous work provided a model for finding Pareto-optimal IDE-style treadle …
Identifying Technical and Economic Improvements to the MoneyMaker Hip Pump through Multi-Objective Optimization
Authors: Christopher McComb and Pablo S. Santaeufemia and Nathan G. Johnson and Kenji Shimada
Published in: IEEE Global Humanitarian Technology Conference, 2014

Water-lifting technologies in rural areas of the developing world have enormous potential to stimulate agricultural production and economic growth. The MoneyMaker Hip pump designed by Kickstart is a human-powered low cost pump, which can help subsistence farmers increase financial returns. This work optimizes the design of the MoneyMaker Hip pump, which is the cheapest and lightest portable water pump from Kickstart. A mathematical model of the working fluid and MoneyMaker Hip pump structure is developed. Deterministic optimization methods are then employed to maximize the flow rate of the groundwater pumped, maximize the lift height, and minimize the volume of material used for manufacturing. Design variables for the optimization included the dimensions of the pump, well depth, and speed of various parts of the system. The solutions are subject to constraints on the geometry of the system, the …
Exploring the Capabilities of Large Language Models for Generating Diverse Design Solutions
Authors: Kevin Ma and Daniele Grandi and Christopher McComb and Kosa Goucher-Lambert
Published in: Journal of Computing and Information Science in Engineering, 2024

Access to large amounts of diverse design solutions can support designers during the early stage of the design process. In this paper, we explore the efficacy of large language models (LLM) in producing diverse design solutions, investigating the level of impact that parameter tuning and various prompt engineering techniques can have on the diversity of LLM-generated design solutions. Specifically, LLMs are used to generate a total of 4,000 design solutions across five distinct design topics, eight combinations of parameters, and eight different types of prompt engineering techniques, comparing each combination of parameter and prompt engineering method across four different diversity metrics. LLM-generated solutions are compared against 100 human-crowdsourced solutions in each design topic using the same set of diversity metrics. Results indicate that human-generated solutions consistently have greater diversity scores across all design topics. Using a post hoc logistic regression analysis we investigate whether these differences primarily exist at the semantic level. Results show that there is a divide in some design topics between humans and LLM-generated solutions, while others have no clear divide. Taken together, these results contribute to the understanding of LLMs' capabilities in generating a large volume of diverse design solutions and offer insights for future research that leverages LLMs to generate diverse design solutions for a broad range of design tasks (e.g., inspirational stimuli).
Arctic geohazard mapping tools for civil infrastructure planning: A systematic review
Authors: Ziyi Wang and Ming Xiao and Min Liew and Anne Jensen and Louise Farquharson and Vladimir Romanovsky and Dmitry Nicolsky and Christopher McComb and Benjamin M Jones and Xiong Zhang and Lilian Alessa
Published in: Cold Regions Science and Technology, 103969, 2023

Civil engineers design buildings, roads, and utility pipelines in the Arctic to rest on firm frozen ground. But as permafrost thaws due to increased air temperature, the ground subsides and infrastructure fails. This paper assesses the current tools used for mapping Arctic geohazard for civil infrastructure planning in the warming Arctic. We formulate an integrated framework to inform science-based decisions and policymaking in response to the ongoing environmental changes. This study first conducts a systematic review of the Arctic geohazard mapping tools. Tools used for Arctic geohazard mapping fall into three categories: analytical or statistical equations for geohazard assessment, modeling approaches for predicting the extent of permafrost degradation, and remote and in-situ sensing for monitoring the natural and built environments and data collection. A description of these tools, along with their limitations and …
Does empathy lead to creativity? A simulation-based investigation on the role of team trait empathy on nominal group concept generation and early concept screening
Authors: Mohammad Alsager Alzayed and Scarlett R Miller and Jessica Menold and Jacquelyn Huff and Christopher McComb
Published in: AI EDAM 37, e23, 2023

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 become more 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, defined here as the average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes during nominal group concept generation and early concept screening. Therefore, the goal of the current study is to investigate the impact of team empathy on nominal group concept generation and …
Student and Instructor Reflections on Integrating Short Mindfulness-Based Meditation Practices into a First-Year Engineering Design Course
Authors: Hannah Nolte and Elizabeth Starkey and Nicolas F Soria Zurita and Christopher McComb
Published in: ASEE First Year Engineering Education Conference, 2022

Engineering students in the United States are experiencing substantial stress and threats to their well-being. Mindfulness-based meditation practice may help students to better manage these challenges as mindfulness-based interventions have been found to improve college students’ well-being and critical competencies. However, only limited mindfulness-based research has been conducted with the engineering student population. Nonetheless, this research indicates that engineering students are receptive to mindfulness-based interventions and perceive benefits from participating in these practices. This work integrated mindfulness-based meditations into a first-year engineering design course to explore how these practices affect engineering students. All practices were formatted as five-minute guided seated meditations. These practices were implemented as part of two larger studies. During the first study, the …
Comparing Nominal and Interacting Sub-Structured Teams in an Interdisciplinary Engineering Design Task
Authors: Joshua T Gyory and Nicolas F Soria Zurita and Jonathan Cagan and Christopher McComb
Published in: ASME 2022 International Design Engineering Technical Conferences and …, 2022

Teams are common throughout engineering practice and industry when solving complex, interdisciplinary problems. Previous works in engineering problem solving have studied the effectiveness of teams and individuals, showing that in some circumstances, individuals can outperform collaborative teams working on the same task. The current work extends these insights to novel team configurations in large interdisciplinary teams. In these team configurations, the meta-team as a whole can interact but the sub-teams within them may or may not. Here, team performance and process are studied within the context of a complex drone design and path-planning problem. Via a collaborative research platform called HyForm, communication and behavioral patterns can be tracked and analyzed throughout problem solving. This works shows that nominal sub-structured teams, where members work independently …