Ultrasonic Physics and Testing Lab held three academic salons in the past two months this year, which received good feedback from the staff members and students in the lab. In order to maintain the sound atmosphere, the lab held the 4th salon recently. Two reporters shared their research experience with the audience.
The first reporter was Dr. Che Chengxuan. His report;s title was "The Spectral Element Method for Elastic Wave Simulation in a Formation with a Topographic Traction Free Surface". At the beginning of the report, he made an overall introduction of several numerical simulation methods in common use and their advantages and flaws. Then he detailedly talked about the Spectral Element Method (SEM). Through the introduction of the basic theory and key technology of SEM, he presented the results of elastic wave simulation in formation with topographic traction free surface obtained by SEM and made an detailed analysis. Finally he got the conclusion that SEM was a novel numerical modeling method, which has particular excellence in modeling model with a complex free surface and could calculate the complex model both accurately and effectively.
The second speaker was Li Yong'an. His report's title was "Brief Introduction of Optimization Algorithm". Firstly, he stated the basic characteristics of optimization algorithm. After that, he introduced the Simulated Annealing Algorithm, Tabu Search Algorithm and Genetic Algorithm. Simulated annealing (SA) algorithm is a generic probabilistic metaheuristic for the global optimization problem of applied mathematics, namely locating a good approximation to the global minimum of a given function in a large search space; Tabu search is a mathematical optimization method, belonging to the class of local search techniques. Tabu search enhances the performance of a local search method by using memory structures: once a potential solution has been determined, it is marked as "taboo" ("tabu" being a different spelling of the same word) so that the algorithm does not visit that possibility repeatedly; Genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover (also called recombination).
The two reports obtained warm applause from the audience and a warm discussion was followed.
