Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence spee...Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.展开更多
Due to the complex structures of multi-limbed parallel robots,conventional parallel robots generally have limited workspace,complex kinematics,and complex dynamics,which increases the application difficulty of paralle...Due to the complex structures of multi-limbed parallel robots,conventional parallel robots generally have limited workspace,complex kinematics,and complex dynamics,which increases the application difficulty of parallel robot in industrial engineering.To solve the above problems,this paper proposes a single-loop Sch?nflies motion parallel robot with full cycle rotation,the robot can generate Sch?nflies motion by the most simplified structure.The novel Sch?nflies motion parallel robot is a two-limb parallel mechanism with least links and joints,and each limb is driven by a 2-degree of freedom(DOF)cylindrical driver(C-driver).The full cycle rotation of the output link is achieved by“…R-H…”structure,where the revolute(R)and helical(H)joints are coaxial.Mobility,kinematics,workspace and singularity analysis of the novel Sch?nflies motion parallel robot are analyzed.Then,dynamic model is formulated based on the principle of virtual work.Moreover,a pick-and-place task is implemented by the proposed Sch?nflies motion parallel robot and a serial SCARA robot,respectively.The simulation results verify the correctness of the theoretical model.Furthermore,dynamics performances of the proposed Sch?nflies motion parallel robot and a serial SCARA robot are compared,which reveal the performance merits of the proposed Sch?nflies motion parallel robot.展开更多
This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimizat...This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.展开更多
In vehicle body manufacturing,there are small differences between the actual value and design value of,for example,plate thickness and material characteristics.This is caused by the processing technology,environment a...In vehicle body manufacturing,there are small differences between the actual value and design value of,for example,plate thickness and material characteristics.This is caused by the processing technology,environment and other uncertain factors.Therefore,the performance of the vehicle body processed according to the deterministic optimization solution fluctuates.The fluctuations may make structural performance fail to meet the design requirements.Thus,in this study,an optimization design is executed with 6σrobustness criteria and a Monte Carlo simulation single-loop optimization strategy based on the radial basis function neural network approximate model considering deviations in plate thickness,elastic modulus,and welding spot diameter,which is called the uncertainty optimization design method.As an example,considering the bending stiffness,torsion stiffness,and first-order frequency as constraints,the method is applied to the lightweight design of a car body structure,and the reliability of deterministic optimization design and uncertainty optimization design is compared.The results demonstrate that the uncertainty optimization design solution is effective and feasible without lowering the static stiffness and modal performance,and the weight is reduced.展开更多
基金funded by the National Key Research and Development Program(Grant No.2022YFB3706904).
文摘Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.
基金Supported by China Postdoctoral Science Foundation(Grant No.2023M740663)National Natural Science Foundation of China(Grant No.51975039)。
文摘Due to the complex structures of multi-limbed parallel robots,conventional parallel robots generally have limited workspace,complex kinematics,and complex dynamics,which increases the application difficulty of parallel robot in industrial engineering.To solve the above problems,this paper proposes a single-loop Sch?nflies motion parallel robot with full cycle rotation,the robot can generate Sch?nflies motion by the most simplified structure.The novel Sch?nflies motion parallel robot is a two-limb parallel mechanism with least links and joints,and each limb is driven by a 2-degree of freedom(DOF)cylindrical driver(C-driver).The full cycle rotation of the output link is achieved by“…R-H…”structure,where the revolute(R)and helical(H)joints are coaxial.Mobility,kinematics,workspace and singularity analysis of the novel Sch?nflies motion parallel robot are analyzed.Then,dynamic model is formulated based on the principle of virtual work.Moreover,a pick-and-place task is implemented by the proposed Sch?nflies motion parallel robot and a serial SCARA robot,respectively.The simulation results verify the correctness of the theoretical model.Furthermore,dynamics performances of the proposed Sch?nflies motion parallel robot and a serial SCARA robot are compared,which reveal the performance merits of the proposed Sch?nflies motion parallel robot.
基金the National Natural Science Foundation of China(No.10772070)Ph.D Programs Foundation of Ministry of Education of China(No.20070487064).
文摘This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.
基金the National Natural Science Foundation of China(51775193)the Science and Technology Planning Project of Guangdong Province,China(2016A050503021,2015B0101137002,and 2017B010119001).
文摘In vehicle body manufacturing,there are small differences between the actual value and design value of,for example,plate thickness and material characteristics.This is caused by the processing technology,environment and other uncertain factors.Therefore,the performance of the vehicle body processed according to the deterministic optimization solution fluctuates.The fluctuations may make structural performance fail to meet the design requirements.Thus,in this study,an optimization design is executed with 6σrobustness criteria and a Monte Carlo simulation single-loop optimization strategy based on the radial basis function neural network approximate model considering deviations in plate thickness,elastic modulus,and welding spot diameter,which is called the uncertainty optimization design method.As an example,considering the bending stiffness,torsion stiffness,and first-order frequency as constraints,the method is applied to the lightweight design of a car body structure,and the reliability of deterministic optimization design and uncertainty optimization design is compared.The results demonstrate that the uncertainty optimization design solution is effective and feasible without lowering the static stiffness and modal performance,and the weight is reduced.
