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Keywords: Gaussian process
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Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A018, August 17–19, 2021
Paper No: DETC2021-71570
...Abstract Abstract Scientific and engineering problems often require an inexpensive surrogate model to aid understanding and the search for promising designs. While Gaussian processes (GP) stand out as easy-to-use and interpretable learners in surrogate modeling, they have difficulties...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A001, August 17–19, 2021
Paper No: DETC2021-66758
... of an optimal periodic microstructure at every discrete location, but do not necessarily embody a manufacturable structure. To address these limitations, this paper introduces a Gaussian process regression model-assisted MSTO method that features the optimal distribution of material at the macroscale...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A002, August 17–19, 2021
Paper No: DETC2021-67629
... features and a Gaussian Process the topological features of the cellular structures [11-16]. A (GP) model is employed to enable property-driven structure rational design methodology for discovering new metamaterials optimization. By comparing the GM-VAE and a regular with a wide bandgap is highly desired...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A018, August 17–19, 2020
Paper No: DETC2020-22212
... on Bayesian active learning is proposed to discover a feasible region of multi-disciplinary constraints concurrently. In the proposed method, Gaussian Process models of the multi-disciplinary constraints are trained. Based on posterior distributions of trained Gaussian Processes, new acquisition function...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A057, August 17–19, 2020
Paper No: DETC2020-22595
... spatially varying desired properties. The key challenge is the lack of inherent ordering or “distance” measure between different classes of unit cells in meeting a range of properties. To overcome this hurdle, we extend the newly developed latent-variable Gaussian process (LVGP) to creating multi-response...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A048, August 17–19, 2020
Paper No: DETC2020-22082
... structure, and characterization of the distortion pattern of an additively manufactured cellular structure. network uncertainty quantification Gaussian process topological domain conditional simulation QUANTIFICATION OF UNCERTAINTIES DISTRIBUTED IN NETWORK-LIKE SYSTEMS Zihan Wang, Hongyi Xu...