A data-driven method for dissipative thermomechanics

被引：0
|
作者：
Ruiz, D. [1 ]
Portillo, D. [1 ,2 ]
Romero, I [1 ,2 ]
机构：
[1] Univ Politecn Madrid, Madrid 28006, Spain
[2] IMDEA Mat Inst, Madrid 28906, Spain
来源：
IFAC PAPERSONLINE | 2021年 / 54卷 / 19期
关键词：
Dissipative systems; GENERIC; Metriplectic systems; Lagrangian and Hamiltonian systems; Convex optimization; Data-driven; PRESERVE SYMMETRIES; COUPLED PROBLEMS; COMPLEX FLUIDS; THERMODYNAMICS; ALGORITHMS; LAWS; DYNAMICS;
D O I：
10.1016/j.ifacol.2021.11.096
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We present a method based on quadratic programming for learning dissipative models from data. For that, we take advantage of the metriplectic structure of the system to preserve the two laws of thermodynamcis, i.e. energy conservation and non-decreased entropy. This method can be used in conjunction with EEM integrators to generate structure preserving integrators for dissipative thermomechanics. We illustrate the results by an example. Copyright (C) 2021 The Authors.
引用
收藏
页码：315 / 320
页数：6
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