Configuration information acquisition and matching in self-reconfiguring process of modular self-reconfigurable robots

Configuration information acquisition and matching are two important steps in the self-reconfiguring process of self-reconfigurable robots. The process of configuration information acquisition was introduced, and a self-reconfiguring configuration matching strategy based on graded optimization mechanism was proposed. The first-grade optimization was to search common connection between matching scheme and goal configuration. The second-grade optimization, whose object function was constructed in terms of configuration connectivity, was to search connnon topology according to the results of the first-grade optimization. The entire process of configuration information acquisition and matching was verified by an experiment and genetic algorithm （GA）. The result shows the accuracy of the configuration information acquisition and the effectiveness of the configuration matching method.

The Application of RUF Series Catalysts and Its Grading Optimization Technology

Qilu Petrochemical Company in order to synchronize the replacement of catalysts in the upflow reactor (UFR) and fixed-bed reactors and achieve the 1.5-year operating cycle of the residue hydrotreating unit has revamped the UFR and optimized catalysts grading. Commercial operation results have revealed that the series of catalysts for residue hydrotreating after optimized grading achieved an operating cycle of 1.5 years with the quality of hydrotreated oil products meeting the requirements for FCC feedstock.

Lightweight topology optimization of graded lattice structures with displacement constraints based on an independent continuous mapping method

This paper presents a novel topology optimization method to design graded lattice structures to minimize the volume subject to displacement constraints based on the independent continuous mapping(ICM)method.First,the effective elastic properties of graded unit cells are analyzed by the strain energy-based homogenization method.A surrogate model using quartic polynomial interpolation is built to map the independent continuous topological variable to the effective elastic matrix of the unit cell and set up the relationship between the macroscale structure and microscale unit cells.Second,a lightweight topology optimization model is established,which can be transformed into an explicitly standard quadratic programming problem by sensitivity analysis and solved by dual sequential quadratic programming.Third,several numerical examples demonstrate that graded lattice structures have a better lightweight effect than uniform lattice structures,which validates the effectiveness and feasibility of the proposed method.The results show that graded lattice structures become lighter with increasing displacement constraints.In addition,some diverse topological configurations are obtained.This method provides a reference for the graded lattice structure design and expands the application of the ICM method.