A knowledge-based mesh generation system for forging simulation
We developed a knowledge-based system GENMAI (Artificial Intelligence Mesh GENerator) to auto-generate two-dimensional structured meshes. GENMAI is easily applicable to various kinds of application domains. Mesh generation is one of the major tasks confronted in computational simulation. The quality of generated meshes affects computational accuracy and computing time. Since various kinds of domain knowledge are needed to generate high quality structured meshes, the knowledge-based approach has been found effective and successful. Before designing GENMAI, we analyzed mesh generation jobs in plastic deformation analysis and computational fluid dynamics. Then, we formulate GENMAI so that it searches feasible plural divided patterns combinatorially and selects the best pattern. The characteristics of GENMAI are as follows: the meta-inference mechanism and its knowledge representation are widely applicable to various kinds of application domains; and plural patterns can be efficiently obtained at the same time by a search technique based on global dependency and local dependency. We applied GENMAI to forging simulation and developed AI-FESTE, which integrated a rigid-plastic deformation analysis program and GENMAI. Forging designers can easily decide shapes of a forging product and dies and also plan the forming sequence using AI-FESTE. AI-FESTE automates a series of forging analysis operations and shortens the execution time from 1 or 2 day(s) to a few hours. As a result, not only can AI-FESTE shorten the turn-around time, but it can improve the quality of product and die design.
mesh generation knowledge-based system meta inference search method numerical simulation