Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks-Reference-Cited by-同舟云学术

Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks

Published:2022-08-07 Issue: Volume: Page:1-18
ISSN:0010-2202
Container-title:Combustion Science and Technology
language:en
Short-container-title:Combustion Science and Technology

Author:

Armstrong Elizabeth¹^ORCID,Hansen Michael A.²,Knaus Robert C.²,Trask Nathaniel A.³,Hewson John C.⁴,Sutherland James C.¹

Affiliation:

1. Department of Chemical Engineering, University of Utah, Salt Lake City, Utah, USA

2. Computational Thermal and Fluid Mechanics, Sandia National Laboratories, Albuquerque, New Mexico, USA

3. Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico, USA

4. Fire Science and Technology, Sandia National Laboratories, Albuquerque, New Mexico, USA

Funder

Sandia National Laboratories

Publisher

Informa UK Limited

Subject

General Physics and Astronomy,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00102202.2022.2102908

Reference25 articles.

1. Abadi, M., A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, et al. 2016. TensorFlow: Large-scale machine learning on heterogeneous systems. https://arxiv.org/abs/1603.04467v2

2. The Gap between Theory and Practice in Function Approximation with Deep Neural Networks

3. Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques

4. A single-step time-integrator of a methane–air chemical system using artificial neural networks

5. A self-organizing-map approach to chemistry representation in combustion applications

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