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RISPaDGAN: Learning to Generate High-Quality Novel Designs
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Deep generative models are proven to be a useful tool for automatic design synthesis and design space exploration. When applied in engineering design, existing generative models face three challenges: (1) generated designs ...
Untrained and Unmatched: Fast and Accurate Zero-Training Classification for Tabular Engineering Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In engineering design, navigating complex decision-making landscapes demands a thorough exploration of the design, performance, and constraint spaces, often impeded by resource-intensive simulations. Data-driven methods ...
Ranking Ideas for Diversity and Quality
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: When selecting ideas or trying to find inspiration, designers often must sift through hundreds or thousands of ideas. This paper provides an algorithm to rank design ideas such that the ranked list simultaneously maximizes ...
Range-Constrained Generative Adversarial Network: Design Synthesis Under Constraints Using Conditional Generative Adversarial Networks
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Typical engineering design tasks require the effort to modify designs iteratively until they meet certain constraints, i.e., performance or attribute requirements. Past work has proposed ways to solve the inverse design ...
BIKED: A Dataset for Computational Bicycle Design With Machine Learning Benchmarks
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In this paper, we present “BIKED,” a dataset composed of 4500 individually designed bicycle models sourced from hundreds of designers. We expect BIKED to enable a variety of data-driven design applications for bicycles and ...
Forming Diverse Teams From Sequentially Arriving People
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Collaborative work often benefits from having teams or organizations with heterogeneous members. In this paper, we present a method to form such diverse teams from people arriving sequentially over time. We define a monotone ...
Deep Generative Models in Engineering Design: A Review
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Automated design synthesis has the potential to revolutionize the modern engineering design process and improve access to highly optimized and customized products across countless industries. Successfully adapting generative ...
If a Picture is Worth 1000 Words, Is a Word Worth 1000 Features for Design Metric Estimation?
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A picture is worth a thousand words, and in design metric estimation, a word may be worth a thousand features. Pictures are awarded this worth because they can encode a plethora of information. When evaluating designs, we ...
Attention-Enhanced Multimodal Learning for Conceptual Design Evaluations
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Conceptual design evaluation is an indispensable component of innovation in the early stage of engineering design. Properly assessing the effectiveness of conceptual design requires a rigorous evaluation of the outputs. ...
METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Data-driven design of mechanical metamaterials is an increasingly popular method to combat costly physical simulations and immense, often intractable, geometrical design spaces. Using a precomputed dataset of unit cells, ...