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RISReinforcement Learning for Efficient Design Space Exploration With Variable Fidelity Analysis Models
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Reinforcement learning algorithms can autonomously learn to search a design space for highperformance solutions. However, modern engineering often entails the use of computationally intensive simulation, which can lead to ...
Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations
Publisher: The American Society of Mechanical Engineers (ASME)
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, ...
Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
Capturing Human Sequence-Learning Abilities in Configuration Design Tasks Through Markov Chains
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
Pulling at the Digital Thread: Exploring the Tolerance Stack Up Between Automatic Procedures and Expert Strategies in Scan to Print Processes
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
Data-Driven Heuristic Induction From Human Design Behavior
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
The Prototyping Behaviors of Startups: Exploring the Relationship Between Prototyping Behaviors and Startup Strategies
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
An Adversarial Agent-Based Design Method Using Stochastic Stackelberg Game Conditions
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Products must often endure challenging conditions while fulfilling their intended functions. Game-theoretic methods can readily create a wide variety of these conditions to consider when creating designs. This work introduces ...
Expanding the Solution Space in Engineering Design Education: A Simulation-Based Investigation of Product Dissection
Publisher: The American Society of Mechanical Engineers (ASME)
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, ...