Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout...Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout to minimize the manufacturing deformation.Firstly,a topological optimization model that takes the stiffness of ATWC as the objective function and the volume of the locating structure as the constraint is established.Secondly,ATWC and the locating structure are regarded as an integrated entity,and the variable-density method based topological optimization approach is adopted for the optimization of the locating structure using ABAQUS topology optimization module(ATOM).Thirdly,through a subsequent model reconstruction referring to the obtained topological structure,the optimal fixture locating layout is achieved.Finally,a case study is conducted to verify the proposed method and the comparison results with firefly algorithm(FA)coupled with finite element analysis(FEA)indicate that the number and positions of the locators for ATWC can be optimized simultaneously and successfully by the proposed topological optimization model.展开更多
An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing lit...An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.展开更多
Automation in the layout of fixture components is important to achieve efficiency and flexibility in computer aided fixture design. Based on basic genetic algorithm and particulars of different fixture components, a m...Automation in the layout of fixture components is important to achieve efficiency and flexibility in computer aided fixture design. Based on basic genetic algorithm and particulars of different fixture components, a method of layout space division is presented. Such techniques as suitable crossover rate, mutation rate and selection arithmetic element are adopted in the genetic operation. The results show that genetic algorithm can effectively be applied in the automatic layout of fixture components.展开更多
The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation met...The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.展开更多
There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to...There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.展开更多
基金supported by the National Natural Science Foundation of China(No.51375396)the Shaanxi Science and Technology Innovation Project Plan,China(No.2016KTCQ01-50)
文摘Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout to minimize the manufacturing deformation.Firstly,a topological optimization model that takes the stiffness of ATWC as the objective function and the volume of the locating structure as the constraint is established.Secondly,ATWC and the locating structure are regarded as an integrated entity,and the variable-density method based topological optimization approach is adopted for the optimization of the locating structure using ABAQUS topology optimization module(ATOM).Thirdly,through a subsequent model reconstruction referring to the obtained topological structure,the optimal fixture locating layout is achieved.Finally,a case study is conducted to verify the proposed method and the comparison results with firefly algorithm(FA)coupled with finite element analysis(FEA)indicate that the number and positions of the locators for ATWC can be optimized simultaneously and successfully by the proposed topological optimization model.
基金Supported by National Natural Science Foundation of China(Grant No.52005371)Shanghai Municipal Natural Science Foundation of China(Grant No.22ZR1463900)+1 种基金Fundamental Research Funds for the Central Universities of China(Grant No.22120220649)State Key Laboratory of Mechanical System and Vibration of China(Grant No.MSV202318).
文摘An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.
文摘Automation in the layout of fixture components is important to achieve efficiency and flexibility in computer aided fixture design. Based on basic genetic algorithm and particulars of different fixture components, a method of layout space division is presented. Such techniques as suitable crossover rate, mutation rate and selection arithmetic element are adopted in the genetic operation. The results show that genetic algorithm can effectively be applied in the automatic layout of fixture components.
基金the National Natural Science Foundation of China(Grant No.52005311)the Scientific and the National Science and Technology Major Project(Grant No.J2019-VII-0013-0153)Research Project Supported by Shanxi Scholarship Council of China(Grant No.2023-003).
文摘The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.
基金Supported by National Natural Science Foundation of China(Grant No.52005371)Shanghai Pujiang Program of China(Grant No.2020PJD071)+1 种基金Shanghai Municipal Natural Science Foundation of China(Grant No.22ZR1463900)Fundamental Research Funds for the Central Universities of China.
文摘There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.
