Self-updated four-node finite element using deep learning

This paper introduces a new concept called self-updated finite element (SUFE). The finite element (FE) is activated through an iterative procedure to improve the solution accuracy without mesh refinement. A mode-based finite element formulation is devised for a four-node finite element and the assumed modal strain is employed for bending modes. A search procedure for optimal bending directions is implemented through deep learning for a given element deformation to minimize shear locking. The proposed element is called a self-updated four-node finite element, for which an iterative solution procedure is developed. The element passes the patch and zero-energy mode tests. As the number of iterations increases, the finite element solutions become more and more accurate, resulting in significantly accurate solutions with a few iterations. The SUFE concept is very effective, especially when the meshes are coarse and severely distorted. Its excellent performance is demonstrated through various numerical examples.

Thermal Analysis of Thermoelectric Coolers for Processors

In this paper, a thermal analysis of thermoelectric coolers (TECs) is conducted for processors based on TEC module parameters. Two sets of analytical solutions for TECs in system constraints are derived for the junction temperature Tj at a fixed power Qc, and for Qc at fixed Tj, respectively. The major advantage of the present models lies in the fact that the solutions can be obtained based on the module parameters without prior knowledge of pellet details and iterative solution procedure, as often reported in literature. Two cooling scenarios, the processor test and the processor cooling under end-user conditions, are analyzed based on the present analysis models for two commercial TECs with high power capacities. Results show that significant thermal enhancements are achievable based on optimized current and power dissipation. The validation is also conducted through experimental measurements and comparison with previous iterative solutions.

An EHD Model to Predict the Interdependent Behavior of Two Dynamically Loaded Hybrid Journal Bearings

An elastohydrodynamic (EHD) analysis is performed for two misaligned hybrid journal bearings working on the same shaft. To predict the correct system behavior we are forced to consider the interdependence between the two bearings and the shaft. The presented algorithm is based on finite element discretization. It allows accurate analysis of film breakdown and reforming, during the functioning of actual devices. Active (full film) and inactive (cavitated) film zones are determined for nonstationary running conditions. Using a convenient iterative solution procedure, the converged solutions for lubricant flow and elastic deformation fields are obtained. The analysis of thickness, pressure, power loss, and elastic deformation of both bearings and shaft surface allows the optimization of any parameter for the two hybrid bearings.