K., "Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials," Computer Methods in Applied Mechanics and Engineering, vol. 306, 2016, pp. 319-341.Z. Liu, M. Be
This section provides a concise overview and analysis of prior CE models. The conventional CE framework can be distilled into two principal processes: acquiring requisite base clustering results for consensus and the subsequent consensus clustering process. ...
Self-consistent-clustering-analysis-An-efficient-multi-scale-scheme-for-inelastic-heterogeneous-materials_2016_Computer-Methods-in-Applied-Mechanics-a 热度: 相关推荐 a r X i v : a s t r o - p h / 9 3 0 3 0 1 0 v 1 1 9 M a r 1 9 9 3 APPROXIMATESELF-CONSISTENTMODELSFORTIDALL...
Virtual and self-consistent clustering analysisConvergenceMachine learningLippmann-Schwinger equationIn this paper, we propose a new homogenization algorithm, virtual clustering analysis (VCA), as well as provide a mathematical framework for the recently proposed self-consistent clustering analysis (SCA) (...
Virtual and self-consistent clustering analysisIn this paper, we propose a new homogenization algorithm, virtual clustering analysis (VCA), as well as provide a mathematical framework for the recently proposed self-consistent clustering analysis......
Another very recent method to reduce the computational effort of a microscale simulation is the selfヽonsistent clustering analysis [?,?]. Such a selfヽonsistent clustering analysis is split into an offline and an online stage. Within the offline stage, the material points of the high‐fidelity...
In this paper, we have extended the self-consistent clustering analysis (SCA) method for efficient and accurate modeling of thermal residual stress for thermoelastic heterogeneous materials. The governing equations of the thermoelasticity has been implemented through a eigenstrain problem and solved using...
Cheng YuWing Kam LiuZ. Liu, O. L. Kafka, C. Yu, W. K. Liu, Data-driven self-consistent clustering analysis of heterogeneous materials with crystal plasticity, in: Advances in Computational Plasticity, Springer, 2018, pp. 221-242.
Self-consistent Clustering Analysis-Based Moving Morphable Component (SMMC) Method for Multiscale Topology Optimizationdoi:10.1007/s10338-023-00433-9Topology optimizationMoving morphable component methodMultiscale concurrent designReduced-order modelCurrent multiscale topology optimization restricts the solution ...
For the time-invariant contribution, the catalog is declustered using the clustering technique of the STEP model; the smoothed seismicity model is generated from the declustered catalog. The time-varying contribution is what distinguishes the two implementations: 1) for one implementation (STEP-LG), ...