... of chemical kinetics. This framework is based on a recent class of machine learning algorithms called neural ordinary differential equations (NODE) to build a multi-step chemistry integrator. The NODE algorithm, which is a discrete counterpart of ResNet [ 30 ], is a hybrid of neural net and differential...

.... , and Nguyen , P.-D. , 2021 , “ Machine Learning for Integrating Combustion Chemistry in Numerical Simulations ,” Energy AI , 5 , p. 100082 . 10.1016/j.egyai.2021.100082 [27] Chatzopoulos , A. K. , and Rigopoulos , S. , 2013 , “ A Chemistry Tabulation Approach Via Rate-Controlled...

...Xiaojie Xu; Yun Zhang Concrete mixture design usually requires labor-intensive and time-consuming work, which involves a significant amount of “trial batching” approaches. Recently, statistical and machine learning methods have demonstrated that a robust model might help reduce the experimental...

... 06 04 2022 09 05 2022 artificial intelligence machine learning graph neural networks design automation design for market systems National Science Foundation 10.13039/100000001 2005665 Complex engineering systems contain multiple stakeholders and individual...