Jinxiong Zhou's blog

This paper describes a hybrid proper orthogonal decomposition (POD) and artificial neural network (ANN) strategy to construct digital twins of a pressurizer surge line under thermal stratification conditions. The one-way coupled conjugate heat transfer and thermal stress analysis was conducted by use of parametric modeling and the introduction of the inverse distance weighted interpolation for the grid mapping, which allows for the mapped grids to have the same number of nodes regardless of variations of surge line geometries.

It is widely acknowledged that fluidelastic instability (FEI), among other mechanisms, is of the greatest concern in the flow-induced vibration (FIV) of tube bundles in steam generators and heat exchangers. A range of theoretical models have been developed for FEI analysis, and, in addition to the earliest semi-empirical Connors’ model, the unsteady model, the quasi-steady model and the semi-analytical model are believed to be three advanced models predominant in the literature.

It is widely acknowledged that fluidelastic instability (FEI), among other mechanisms, is of the greatest concern in the flow-induced vibration (FIV) of tube bundles in steam generators and heat exchangers. A range of theoretical models have been developed for FEI analysis, and, in addition to the earliest semi-empirical Connors’ model, the unsteady model, the quasi-steady model and the semi-analytical model are believed to be three advanced models predominant in the literature.

The composite tape-spring hinge (CTSH) is a lightweight structural connector widely employed in space structures, including spacecraft and satellites, due to its high specific strength and stiffness. Introducing cutouts enables CTSH to possess folding and deployment capability, while optimizing the cutouts finely to optimize the performance of CTSH. However, the interaction between cutout size and the dynamic deployment of CTSH is a novel topic.

The ABD matrix is a fundamental method to characterize the overall stiffness behavior of laminated composite structures. Although classical laminate theory has been widely used, it has limitations in predicting the ABD matrix for woven composites. To address this issue, this paper presents a mesoscale homogenization approach aimed at computing the ABD matrix for thin woven composites accurately. The mesoscale representative volume element (RVE) of the woven composite is generated using TexGen and imposed with periodic boundary conditions to enforce the Kirchhoff thin plate assumption.

To address the significant challenges in predicting high-dimensional chaotic systems, this paper introduces a novel hybrid strategy that combines proper orthogonal decomposition (POD), which serves as reduced order modeling (ROM), with next generation reservoir computing (NGRC), a data-driven prediction model. The POD-NGRC strategy harnesses the strengths of POD in extracting principal evolutionary features and reducing system complexity, along with the high accuracy, ease of design, enhanced robustness, and high computational efficiency offered by NGRC.