Dynamic characterization of cross-physics coupling strengths, a methodology to coupling and reordering partitioned solvers for multiphysics applications
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引用次数: 0
Abstract
The role of dimensionless ratios in engineering and physics is ubiquitous; but their utility in the multiphysics community is sometimes overlooked. Notably, in the multiphysics modelling community, coupling methods are often discussed and developed without an explicit monitoring of the various dimensionless ratios of the various inter-physics coupling terms. However, it is evident that the varying strengths of the coupling terms in a multiphysics model of k physics solvers/modules will influence either the convergence rate, the stability of the coupling scheme and the program execution speed. In fact, it is well known that the “ordering” of the predictor physics modules is primordial to the performance characteristics of a multiphysics coupling scheme. However, the question of “how to order” (who came first, the chicken or the egg?) the k physics modules remains vaguely discussed. In fact, physics ordering is generally based on the scientist's experience or on problem specific stability analyses performed on academic computational configurations. In the case of generic multiphysics coupling, where volume, interface and/or surface coupling terms can manifest, the optimal ordering of the physics modules may strongly vary along simulation time (for the same application) and/or across applications. Motivated to find an approximate measure that does not resort to cumbersome and problem specific stability analyses, we borrow the concept of dimensionless numbers from physics and apply it to the algebraic systems that manifest in multiphysics computational models. The “chicken-egg” algorithm is based on a dimensionless methodology that serves to “reorder” the Jacobian matrix of an exact Newton-Raphson implicit scheme. The method poses a dimensionless preconditioner that estimates the different strengths of the various coupling terms found in the multiphysics application. The chicken-egg algorithm estimates at every given time step the order of magnitude of coupling terms and correspondingly orders the k partitioned physics solvers automatically. This algorithm is tested for the first time on a thermo-hygro-corrosive multiphysics model and shows promising results. Benchmarking against monolithic and diagonalised calculation strategies, the first numerical tests show a significant reduction in iterations before convergence and thus over a 1.7-fold improvement in program execution time.
无量纲比率在工程学和物理学中的作用无处不在,但它们在多物理场中的作用有时会被忽视。值得注意的是,在多物理场建模领域,耦合方法的讨论和开发往往没有明确监测各种物理场间耦合项的各种无量纲比率。然而,很明显,由 k 个物理求解器/模块组成的多物理场模型中耦合项的不同强度会影响收敛速度、耦合方案的稳定性和程序执行速度。事实上,众所周知,预测物理模块的 "排序 "对于多物理场耦合方案的性能特征至关重要。然而,关于 K 物理模块 "如何排序"(先有鸡还是先有蛋?事实上,物理排序通常基于科学家的经验或在学术计算配置上进行的特定问题稳定性分析。在一般的多物理场耦合情况下,体积、界面和/或表面耦合项都可能出现,物理模块的最佳排序可能会随着仿真时间(同一应用)和/或不同应用而发生很大变化。为了找到一种近似的测量方法,而不诉诸繁琐的、针对具体问题的稳定性分析,我们借用了物理学中的无量纲数概念,并将其应用于多物理场计算模型中的代数系统。鸡-蛋 "算法基于无量纲方法,用于 "重排 "精确牛顿-拉斐森隐式方案的雅各布矩阵。该方法采用了一个无量纲预处理器,用于估算多物理应用中各种耦合项的不同强度。鸡-蛋算法在每个给定的时间步估计耦合项的数量级,并相应地自动对 k 个分区物理求解器进行排序。该算法首次在热腐蚀多物理场模型上进行了测试,结果令人满意。首次数值测试显示,收敛前的迭代次数显著减少,因此程序执行时间缩短了 1.7 倍以上。
期刊介绍:
Computers & Structures publishes advances in the development and use of computational methods for the solution of problems in engineering and the sciences. The range of appropriate contributions is wide, and includes papers on establishing appropriate mathematical models and their numerical solution in all areas of mechanics. The journal also includes articles that present a substantial review of a field in the topics of the journal.