This article introduces an innovative design automation method aimed at systematically exploring and categorizing various 3D spatial layouts within interconnected engineering systems, encompassing diverse applications such as automotive cooling systems and building HVAC designs.
In this study, we develop a cutting-edge method using graph neural networks to support the design decision-making of shared mobility systems, like bike-sharing programs.
This research presents an AI approach to designing linkage systems, which are crucial in engineering for transforming rotational movement into precise periodic paths.
This study examines how diverse initialization, such as Latin Hypercube Sampling (LHS) or Space-Filling Designs, impacts Bayesian Optimization (BO), one of the most widely used gradient-free optimizers.
Hongrui Chen, Aditya Joglekar, Kate S. Whitefoot, Levent Burak Kara ASME. J. Mech. Des. September 2023;
This featured article introduces a self-learning design agent, an innovative approach that doesn’t rely on human data or problem-specific knowledge. Instead, it uses deep learning and tree search to find high-performing and generalizable engineering design strategies.
In our modern world, complex systems such as power grids, transportation networks, and communication systems can be disrupted by both internal uncertainties and external factors like natural disasters. To make these systems more resilient, researchers have been working on design strategies that improve both reliability and recovery capabilities.
This article explores a vision of a holistic SPI2 design approach needed to develop next-generation automated design methods that dramatically reduce the time needed to design SPI2 systems and to increase the complexity of designable systems.
This work develops a methodology for combining predictive physics-based models with an interpretable machine learning technique in order to determine optimal sensor placement and dynamic sensor scheduling decisions for Digital Twins.
While designing a blade for an industrial gas turbine (IGT), one needs to consider multiple performance characteristics like aerodynamic efficiency, durability, and safety. The sequential and iterative nature of the process leads to extremely long cycle times and precludes a deeper understanding of the design space.
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