Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperature...Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperatures.The stress−strain curve,ultimate strength,yield strength,modulus of elasticity,elongation after fracture,and percentage reduction of area of NPR steel bars were measured at 9 different temperatures ranging from 20 to 800℃.The experimental results indicate that high-temperature environments significantly affect the mechanical properties of NPR steel.However,compared to other types of steel,NPR steel exhibits better resistance to deformation.When the test temperature is below 700℃,NPR steel exhibits a ductile fracture characteristic,while at 800℃,it exhibits a brittle fracture characteristic.Finally,based on the experimental findings,a constitutive model suitable for NPR steel at high temperatures is proposed.展开更多
A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy syst...A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.展开更多
基金Projects(41702320,52104125)supported by the National Natural Science Foundation of ChinaProject(ZR2021MD005)+2 种基金supported by the Natural Science Foundation of Shandong Province,ChinaProject(TMduracon2022002)supported by the Engineering Research Center of Marine Environmental Concrete Technology,Ministry of Education,China。
文摘Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperatures.The stress−strain curve,ultimate strength,yield strength,modulus of elasticity,elongation after fracture,and percentage reduction of area of NPR steel bars were measured at 9 different temperatures ranging from 20 to 800℃.The experimental results indicate that high-temperature environments significantly affect the mechanical properties of NPR steel.However,compared to other types of steel,NPR steel exhibits better resistance to deformation.When the test temperature is below 700℃,NPR steel exhibits a ductile fracture characteristic,while at 800℃,it exhibits a brittle fracture characteristic.Finally,based on the experimental findings,a constitutive model suitable for NPR steel at high temperatures is proposed.
基金Project(61473298)supported by the National Natural Science Foundation of ChinaProject(2015QNA65)supported by Fundamental Research Funds for the Central Universities,China
文摘A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.
