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RISMixed-Variable Global Sensitivity Analysis for Knowledge Discovery and Efficient Combinatorial Materials Design
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Global Sensitivity Analysis (GSA) is the study of the influence of any given input on the outputs of a model. In the context of engineering design, GSA has been widely used to understand both individual and collective ...
Data-Driven Topology Optimization With Multiclass Microstructures Using Latent Variable Gaussian Process
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The data-driven approach is emerging as a promising method for the topological design of multiscale structures with greater efficiency. However, existing data-driven methods mostly focus on a single class of microstructures ...
Effects of Carbonization on the Co-Activation of Sludge and Biomass to Produce Activated Coke
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Activated coke was prepared by mixing sewage sludge and waste poplar bark biomass from furniture manufacturing. The physical activation method of these feedstocks with steam for 1 h at 850 °C was implemented. The elemental ...
t-METASET: Task-Aware Acquisition of Metamaterial Datasets Through Diversity-Based Active Learning
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Inspired by the recent achievements of machine learning in diverse domains, data-driven metamaterials design has emerged as a compelling paradigm that can unlock the potential of multiscale architectures. The model-centric ...
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, ...