Prediction of mechanical solutions for a laminated LCEs system fusing an analytical model and neural networks

This paper presents a convenient and efficient method to predict the mechanical solutions of a laminated Liquid Crystal Elastomers (LCEs) system subjected to combined thermo-mechanical load, based on a back propagation (BP) neural network which is trained by machine learning from a database established by analytical solutions. Firstly, the...

A neural network-assisted 3D theoretical thermoelastic solution for laminated liquid crystal elastomer plate used in restoring cardiac mechanical function

Some atrial contractile assist devices applied on the heart surface can be regarded as a laminated Liquid crystal elastomer (LCE) plate under steady temperature loads and a contact mechanical force. An exact solution for the deformation of the laminated LCE plate under combined thermal and mechanical loads is derived by solving the three...

Solder joint reliability risk estimation by AI-assisted simulation framework with genetic algorithm to optimize the initial parameters for AI models

Solder joint fatigue is one of the critical failure modes in ball-grid array packaging. Because the reliability test is time-consuming and geometrical/material nonlinearities are required for the physics-driven model, the AI-assisted simulation framework is developed to establish the risk estimation capability against the design and process...

Dynamic prediction of optical and chromatic performances for a light-emitting diode array based on a thermal-electrical-spectral model

Light-emitting diode (LED) arrays have attracted increased attention in the area of high power intelligent automotive headlamps because of their superiority in disposing of the power limit of an individual LED package and controllably luminous intensity and illumination pattern. The optical and chromatic performances of an LED array do not...