Research on Multiphysics Coupling Relationship for the IPT System in Seawater Environment

Wireless charging in the marine environment has problems such as high loss and low efficiency. In order to solve these problems, based on the wireless power transmission technology in the seawater environment, this paper studies the multi-physical field coupling relationship of the underwater IPT system. Through researching on the law of mutual influence and interaction between the fields, the relationship between the physical fields is established. The software is used to establish a system simulation model, the dataset is solved and analyzed to get the distribution of electric field, magnetic field, thermal field, and flow field, which provides a theoretical basis for the model and optimization of the IPT system in the seawater.

The maximum entropy method for data fusion and uncertainty quantification in multifunctional materials and structures

The quantification of uncertainty in intelligent material systems and structures requires methods to objectively compare complex models to measurements, where the majority of cases include multiple model outputs and quantities of interests given multiphysics coupling. This creates questions about constructing appropriate measures of uncertainty during fusion of data and comparisons between data and models. Novel materials with complex or poorly understood coupling can benefit from advanced statistical analysis to judge models in light of multiphysics data. Here, we apply the Maximum Entropy (ME) method to more complicated ferroelectric single crystals containing domain structures and soft electrostrictive membranes under both mechanical and electrical loading. Multiple quantities of interest are considered, which requires fusing heterogeneous information together when quantifying the uncertainty of lower fidelity models. We find that parameters, which were initially unidentifiable using a single quantity of interest, become identifiable using multiple quantities of interest. We also show that posterior densities may broaden or narrow when multiple data sets are fused together. This is likely due to conflict or agreement, respectively, between the different quantities of interest and the multiple model outputs. Such information is important to advance our predictions of intelligent materials and structures from multi-model inputs and heterogeneous data.

Study on Multiphysics Coupling and Automatic Neutronic Optimization for Solid Tritium Breeding Blanket of Fusion Reactor

A tritium breeding blanket (TBB) is an essential component in a fusion reactor, which has functions of tritium breeding, energy generation and neutron shielding. Tritium breeding ratio (TBR) is a key parameter to evaluate whether the TBB could produce enough tritium to achieve tritium self-sufficiency (TBR > 1) for a fusion reactor. Current codes or software struggle to meet the requirements of high efficiency and high automation for neutronic optimization of the TBB. In this paper, the multiphysics coupling and automatic neutronic optimization method study for a solid breeder TBB is performed, and a corresponding code is developed. A typical module of China fusion engineering test reactor (CFETR) helium cooled ceramic breeder (HCCB) TBB was selected, and a 3D neutronics model of an initial scheme is developed. The automatic neutronic optimization was performed by using the developed code for verification. Results indicate that the TBR could increase from 1.219 to 1.282 (~5.17% improvement), and that the maximum temperature of each type of material in the optimized scheme is below the allowable temperature. It is of great scientific significance and engineering value to explore and study the algorithm for automatic neutronic optimization and the code development of the TBB.