Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numeric...Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.展开更多
This paper introduces dynamic boundary updating-surrogate model-based(DBU-SMB),a novel evolutionary framework for global optimization that integrates dynamic boundary updating(DBU)within a surrogate model-based(SMB)ap...This paper introduces dynamic boundary updating-surrogate model-based(DBU-SMB),a novel evolutionary framework for global optimization that integrates dynamic boundary updating(DBU)within a surrogate model-based(SMB)approach.The method operates in three progressive stages:adaptive sampling,DBU,and refinement.In the first stage,adaptive sampling strategically explores the design space to gather critical information for improving the surrogate model.The second stage incorporates DBU to guide the optimization toward promising regions in the parameter space,enhancing consistency and efficiency.Finally,the refinement stage iteratively improves the optimization results,ensuring a comprehensive exploration of the design space.The proposed DBU-SMB framework is algorithm-agnostic,meaning it does not rely on any specific machine learning model or meta-heuristic algorithm.To demonstrate its effectiveness,we applied DBU-SMB to four highly nonlinear and non-convex optimization problems.The results show a reduction of over 90%in the number of function evaluations compared to traditional methods,while avoiding entrapment in local optima and discovering superior solutions.These findings highlight the efficiency and robustness of DBU-SMB in achieving optimal designs,particularly for large-scale and complex optimization problems.展开更多
Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or hig...Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.展开更多
Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The...Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The intense vibration during needle punching not only generates huge noise,but also substantially reduces the quality of the preform.It is imperative to perform a dynamic analysis and optimization of the entire needle punching machine.In this paper,the three-dimensional(3D)model of the entire double-shaft-driven needle punching machine for C/C crucible preforms is established.Based on the modal analysis theory,the modal characteristics of the needle punching machine under various operating conditions are analyzed and its natural frequencies and vibration modes are determined.The harmonic response analysis is then employed to obtain the amplitude of the needle plate at different frequencies,and the structural weak points of the needle punching machine are identified and improved.The feasibility of the optimized scheme is subsequently reevaluated and verified.The results indicate that the first six natural frequencies of the machine increase,and the maximum amplitude of the needle plate decreases by 70.3%.The enhanced dynamic characteristics of the machine significantly improve its performance,enabling more efficient needle punching of C/C crucible preforms.展开更多
Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fa...Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.展开更多
Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex str...Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.展开更多
With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competi...With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competitive products.This paper presents a brief description of the current status of structural optimization by reviewing some significant progress made in the last decades.Potential research topics are also discussed.The entire literatures of the field are not covered due to the limitation of the length of paper.The scope of this review is limited and closely related to the authors＇ own research interests.展开更多
Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to s...Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.展开更多
In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of sh...In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.展开更多
Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization...Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.展开更多
The Blended-Wing-Body(BWB) is an unconventional configuration of aircraft and considered as a potential configuration for future commercial aircraft. One of the difficulties in conceptual design of a BWB aircraft is s...The Blended-Wing-Body(BWB) is an unconventional configuration of aircraft and considered as a potential configuration for future commercial aircraft. One of the difficulties in conceptual design of a BWB aircraft is structural mass prediction due to its unique structural feature. This paper presents a structural mass prediction method for conceptual design of BWB aircraft using a structure analysis and optimization method combined with empirical calibrations. The total BWB structural mass is divided into the ideal load-carrying structural mass, non-ideal mass, and secondary structural mass. Structural finite element analysis and optimization are used to predict the ideal primary structural mass, while the non-ideal mass and secondary structural mass are estimated by empirical methods. A BWB commercial aircraft is used to demonstrate the procedure of the BWB structural mass prediction method. The predicted mass of structural components of the BWB aircraft is presented, and the ratios of the structural component mass to the Maximum TakeOff Mass(MTOM) are discussed. It is found that the ratio of the fuselage mass to the MTOM for the BWB aircraft is much higher than that for a conventional commercial aircraft, and the ratio of the wing mass to the MTOM for the BWB aircraft is slightly lower than that for a conventional aircraft.展开更多
The objective and constraint functions related to structural optimization designs are classified into economic and performance indexes in this paper.The influences of their different roles in model construction of str...The objective and constraint functions related to structural optimization designs are classified into economic and performance indexes in this paper.The influences of their different roles in model construction of structural topology optimization are also discussed.Furthermore,two structural topology optimization models,optimizing a performance index under the limitation of an economic index,represented by the minimum compliance with a volume constraint（MCVC）model,and optimizing an economic index under the limitation of a performance index,represented by the minimum weight with a displacement constraint（MWDC）model,are presented.Based on a comparison of numerical example results,the conclusions can be summarized as follows：（1）under the same external loading and displacement performance conditions,the results of the MWDC model are almost equal to those of the MCVC model;（2）the MWDC model overcomes the difficulties and shortcomings of the MCVC model;this makes the MWDC model more feasible in model construction;（3）constructing a model of minimizing an economic index under the limitations of performance indexes is better at meeting the needs of practical engineering problems and completely satisfies safety and economic requirements in mechanical engineering,which have remained unchanged since the early days of mechanical engineering.展开更多
A novel palletizing robot is presented and developed.By using the Newton-Euler method and the principle that the instantaneous inertial force system could be transformed into a static system,the force equilibrium equa...A novel palletizing robot is presented and developed.By using the Newton-Euler method and the principle that the instantaneous inertial force system could be transformed into a static system,the force equilibrium equations of the whole robot and its subsystem were derived and the robot＇s dynamic models were established.After that,an example simulation was performed by using Matlab software and the structural optimization of the robot＇s key parts were discussed and analyzed in ANSYS platform.The results show that the dynamic models are correct and can be helpful for the design,validation and kinetic control based on dynamics of this kind of palletizing robots.展开更多
This book presents general theories and applications of structural optimization methods. The first chapter of the book introduces various basic concepts of structural optimization through several illustrative examples...This book presents general theories and applications of structural optimization methods. The first chapter of the book introduces various basic concepts of structural optimization through several illustrative examples. Chapter 2 is devoted to a comprehensive review of math- ematical programming methods, including classical methods such as the simplex method, the （SLP） method, the interior point method and relatively new approaches such as genetic algo- rithms. The third chapter presents the main topic of this book, the SLP methods based on the incremental equations of structures. Some useful techniques in implementation of SLP, including the move limit, scaling and active constraint identifying, are discussed. In chapter 4, classical optimality criterion approaches, including the fully stress approach for truss struc- tures and its extensions for membrane and plate structures, are presented with demonstrative examples. The remaining chapters develop an overview of structural optimization problems, among which are dynamic optimization, multi-criterion optimization, earlier work on the op- timal layouts of plates, as well as some practical issues in general size and shape optimization problems.展开更多
Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,w...Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,we propose a hybrid optimization method for the structural design optimization of beam-plate structures,which covers three optimization levels:dimension optimization,topology optimization and section optimization.The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints.The kernel optimization procedure(KOP) uses BESO to obtain the optimal topology from a ground structure.To deal with beam-plate structures,the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure.In the first optimization level,a series of ground structures are generated based on different dimensional parameter combinations,the KOP is performed to all the ground structures,the response surface model of optimal objective values and dimension parameters is created,and then the optimal dimension parameters can be obtained.In the second optimization level,the optimal topology is obtained by using the KOP according to the optimal dimension parameters.In the third optimization level,response surface method(RSM) is used to determine the section parameters.The proposed method is applied to a hatch cover structure design.The locations and shapes of all the structural members are determined from an oversized ground structure.The results show that the proposed method leads to a greater weight saving,compared with the original design and genetic algorithm(GA) based optimization results.展开更多
A study is carried out on the structural design of wood-plastic composite floors. The geometric parameters of the cavities, the structure, and the means to optimize the performance of these light boards are investigat...A study is carried out on the structural design of wood-plastic composite floors. The geometric parameters of the cavities, the structure, and the means to optimize the performance of these light boards are investigated. Various structural parameters of the boards, such as size, shape, and the pattern of cavities are also studied. The optimal structure can be determined by calculation and analysis of the strength, stiffness, weight and cost of the material. A finite element model for the mechanical analysis of wood-plastic composite floors is established; and the results are used to verify the strength criteria under bending deformation, which is the most common loading condition of flooring board.展开更多
We propose the deep Lagrange method(DLM),which is a new optimization method,in this study.It is based on a deep neural network to solve optimization problems.The method takes the advantage of deep learning artificial ...We propose the deep Lagrange method(DLM),which is a new optimization method,in this study.It is based on a deep neural network to solve optimization problems.The method takes the advantage of deep learning artificial neural networks to find the optimal values of the optimization function instead of solving optimization problems by calculating sensitivity analysis.The DLM method is non-linear and could potentially deal with nonlinear optimization problems.Several test cases on sizing optimization and shape optimization are performed,and their results are then compared with analytical and numerical solutions.展开更多
In the design process of advanced aero-engines,it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization.Based on the str...In the design process of advanced aero-engines,it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization.Based on the structural composition and functions of aero-engines,the concept and contents of structural efficiency can reflect the relation between structural features and mechanical characteristics.In order to achieve the integrated design of structural and mechanical characteristics,one quantitative analysis method called Structural Efficiency Assessment Method(SEAM)was put forward.The structural efficiency coefficient was obtained by synthesizing the parameters to quantitatively evaluate the aero-engine structure design level.Parameterization method to evaluate structural design quality was realized.After analyzing the structural features of an actual dual-rotor system in typical high bypass ratio turbofan engines,the mechanical characteristics and structural efficiency coefficient were calculated.Structural efficiency coefficient of high-pressure rotor(0.43)is higher than that of low-pressure rotor(0.29),which directly shows the performance of the former is better,there is room for improvement in structural design of the low-pressure rotor.Thus the direction of structural optimization was pointed out.The applications of SEAM shows that the method is operational and effective in the evaluation and improvement of structural design.展开更多
Severe stress concentration occurs around circular vent holes of an industrial turbine sealing disk.This paper investigates the structural design and optimization for the vent holes to effectively reduce the maximum v...Severe stress concentration occurs around circular vent holes of an industrial turbine sealing disk.This paper investigates the structural design and optimization for the vent holes to effectively reduce the maximum von Mises stress and improve the fatigue life of the turbine sealing disk.An efficient integrated design optimization method is presented based on a novel non-circular vent hole design method in combination with a variable dimension sub-model method,a self-developed modeling and meshing tool,and the Multi-Island Genetic Algorithm.The proposed non-circular vent hole is biaxial symmetric and consists of four smoothly connected arcs.The variable dimension sub-model method is utilized to obtain accurate results in the fields around the vent holes within the computationally acceptable time.The modeling and meshing tool is developed by using the Tcl/Tk Scripts to rebuild the geometry and generate the high-quality hexahedral mesh automatically.The Multi-Island Genetic Algorithm is adopted to solve the studied constrained optimization problem.After optimization,the maximum von Mises stress is reduced from 1305.644 MPa to 963.435 MPa,and the fatigue life is increased from 3091 cycles to 30,297 cycles.The results show that the proposed design and optimization methods can significantly improve the performance of the turbine sealing disk along with the remarkable drop in stress concentration.展开更多
Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirect...Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirectional evolutionary structural optimization(BESO)under an aperiodic load is proposed in this paper.In viewof the severe nonlinearity of fatigue damagewith respect to design variables,effective stress cycles are extracted through transient dynamic analysis.Based on the Miner cumulative damage theory and life requirements,a fatigue constraint is first quantified and then transformed into a stress problem.Then,a normalized termination criterion is proposed by approximatemaximum stress measured by global stress using a P-normaggregation function.Finally,optimization examples show that the proposed algorithm can not only meet the requirements of fatigue life but also obtain a reasonable configuration.展开更多
基金Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120funded by the Research Council of Lithuania.
文摘Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.
文摘This paper introduces dynamic boundary updating-surrogate model-based(DBU-SMB),a novel evolutionary framework for global optimization that integrates dynamic boundary updating(DBU)within a surrogate model-based(SMB)approach.The method operates in three progressive stages:adaptive sampling,DBU,and refinement.In the first stage,adaptive sampling strategically explores the design space to gather critical information for improving the surrogate model.The second stage incorporates DBU to guide the optimization toward promising regions in the parameter space,enhancing consistency and efficiency.Finally,the refinement stage iteratively improves the optimization results,ensuring a comprehensive exploration of the design space.The proposed DBU-SMB framework is algorithm-agnostic,meaning it does not rely on any specific machine learning model or meta-heuristic algorithm.To demonstrate its effectiveness,we applied DBU-SMB to four highly nonlinear and non-convex optimization problems.The results show a reduction of over 90%in the number of function evaluations compared to traditional methods,while avoiding entrapment in local optima and discovering superior solutions.These findings highlight the efficiency and robustness of DBU-SMB in achieving optimal designs,particularly for large-scale and complex optimization problems.
基金Supported by the National Natural Science Foundation of China under Grant No.52271309Natural Science Foundation of Heilongjiang Province of China under Grant No.YQ2022E104.
文摘Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.
基金Open Project of Shanghai Key Laboratory of Lightweight Composite,China(No.2232021A4-04)。
文摘Double-shaft-driven needle punching machine is a specialized equipment designed for processing C/C crucible preforms.Its main needle punching module is operated by two sets of reciprocating crank-slider mechanisms.The intense vibration during needle punching not only generates huge noise,but also substantially reduces the quality of the preform.It is imperative to perform a dynamic analysis and optimization of the entire needle punching machine.In this paper,the three-dimensional(3D)model of the entire double-shaft-driven needle punching machine for C/C crucible preforms is established.Based on the modal analysis theory,the modal characteristics of the needle punching machine under various operating conditions are analyzed and its natural frequencies and vibration modes are determined.The harmonic response analysis is then employed to obtain the amplitude of the needle plate at different frequencies,and the structural weak points of the needle punching machine are identified and improved.The feasibility of the optimized scheme is subsequently reevaluated and verified.The results indicate that the first six natural frequencies of the machine increase,and the maximum amplitude of the needle plate decreases by 70.3%.The enhanced dynamic characteristics of the machine significantly improve its performance,enabling more efficient needle punching of C/C crucible preforms.
文摘Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.
文摘Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.
基金supported by the National Natural Science Foundation of China(10472022,10925209,90816025,10802016 and 10902018)the 973 Program of China(2010CB832703).
文摘With the fast development of computational mechanics and the capacity as well as the speed of modern computers,simulation-based structural optimization has become an indispensable tool in the design process of competitive products.This paper presents a brief description of the current status of structural optimization by reviewing some significant progress made in the last decades.Potential research topics are also discussed.The entire literatures of the field are not covered due to the limitation of the length of paper.The scope of this review is limited and closely related to the authors＇ own research interests.
文摘Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.
基金Supported by the Project of Ministry of Education and Finance (No.200512)the Project of the State Key Laboratory of Ocean Engineering (GKZD010053-10)
文摘In this paper a hybrid process of modeling and optimization, which integrates a support vector machine （SVM） and genetic algorithm （GA）, was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier （VLCC） ship was carried out according to the direct strength assessment method in common structural rules （CSR）, which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.
基金supported by National Natural Science Foundation of China(Grant No.51175086)
文摘Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.
基金supported by the National Natural Science Foundation of China (No. 11432007)
文摘The Blended-Wing-Body(BWB) is an unconventional configuration of aircraft and considered as a potential configuration for future commercial aircraft. One of the difficulties in conceptual design of a BWB aircraft is structural mass prediction due to its unique structural feature. This paper presents a structural mass prediction method for conceptual design of BWB aircraft using a structure analysis and optimization method combined with empirical calibrations. The total BWB structural mass is divided into the ideal load-carrying structural mass, non-ideal mass, and secondary structural mass. Structural finite element analysis and optimization are used to predict the ideal primary structural mass, while the non-ideal mass and secondary structural mass are estimated by empirical methods. A BWB commercial aircraft is used to demonstrate the procedure of the BWB structural mass prediction method. The predicted mass of structural components of the BWB aircraft is presented, and the ratios of the structural component mass to the Maximum TakeOff Mass(MTOM) are discussed. It is found that the ratio of the fuselage mass to the MTOM for the BWB aircraft is much higher than that for a conventional commercial aircraft, and the ratio of the wing mass to the MTOM for the BWB aircraft is slightly lower than that for a conventional aircraft.
基金supported by the National Natural Science Foundation of China(Grant 11172013)
文摘The objective and constraint functions related to structural optimization designs are classified into economic and performance indexes in this paper.The influences of their different roles in model construction of structural topology optimization are also discussed.Furthermore,two structural topology optimization models,optimizing a performance index under the limitation of an economic index,represented by the minimum compliance with a volume constraint（MCVC）model,and optimizing an economic index under the limitation of a performance index,represented by the minimum weight with a displacement constraint（MWDC）model,are presented.Based on a comparison of numerical example results,the conclusions can be summarized as follows：（1）under the same external loading and displacement performance conditions,the results of the MWDC model are almost equal to those of the MCVC model;（2）the MWDC model overcomes the difficulties and shortcomings of the MCVC model;this makes the MWDC model more feasible in model construction;（3）constructing a model of minimizing an economic index under the limitations of performance indexes is better at meeting the needs of practical engineering problems and completely satisfies safety and economic requirements in mechanical engineering,which have remained unchanged since the early days of mechanical engineering.
基金Sponsored by the National Natural Science Foundation of China (50675109)
文摘A novel palletizing robot is presented and developed.By using the Newton-Euler method and the principle that the instantaneous inertial force system could be transformed into a static system,the force equilibrium equations of the whole robot and its subsystem were derived and the robot＇s dynamic models were established.After that,an example simulation was performed by using Matlab software and the structural optimization of the robot＇s key parts were discussed and analyzed in ANSYS platform.The results show that the dynamic models are correct and can be helpful for the design,validation and kinetic control based on dynamics of this kind of palletizing robots.
文摘This book presents general theories and applications of structural optimization methods. The first chapter of the book introduces various basic concepts of structural optimization through several illustrative examples. Chapter 2 is devoted to a comprehensive review of math- ematical programming methods, including classical methods such as the simplex method, the （SLP） method, the interior point method and relatively new approaches such as genetic algo- rithms. The third chapter presents the main topic of this book, the SLP methods based on the incremental equations of structures. Some useful techniques in implementation of SLP, including the move limit, scaling and active constraint identifying, are discussed. In chapter 4, classical optimality criterion approaches, including the fully stress approach for truss struc- tures and its extensions for membrane and plate structures, are presented with demonstrative examples. The remaining chapters develop an overview of structural optimization problems, among which are dynamic optimization, multi-criterion optimization, earlier work on the op- timal layouts of plates, as well as some practical issues in general size and shape optimization problems.
基金the National Natural Science Foundation of China(No.51509033)
文摘Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,we propose a hybrid optimization method for the structural design optimization of beam-plate structures,which covers three optimization levels:dimension optimization,topology optimization and section optimization.The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints.The kernel optimization procedure(KOP) uses BESO to obtain the optimal topology from a ground structure.To deal with beam-plate structures,the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure.In the first optimization level,a series of ground structures are generated based on different dimensional parameter combinations,the KOP is performed to all the ground structures,the response surface model of optimal objective values and dimension parameters is created,and then the optimal dimension parameters can be obtained.In the second optimization level,the optimal topology is obtained by using the KOP according to the optimal dimension parameters.In the third optimization level,response surface method(RSM) is used to determine the section parameters.The proposed method is applied to a hatch cover structure design.The locations and shapes of all the structural members are determined from an oversized ground structure.The results show that the proposed method leads to a greater weight saving,compared with the original design and genetic algorithm(GA) based optimization results.
基金Project supported by the National 12th Five-Year Plan of Science and Technology with Grant No.2012BAD23B0203
文摘A study is carried out on the structural design of wood-plastic composite floors. The geometric parameters of the cavities, the structure, and the means to optimize the performance of these light boards are investigated. Various structural parameters of the boards, such as size, shape, and the pattern of cavities are also studied. The optimal structure can be determined by calculation and analysis of the strength, stiffness, weight and cost of the material. A finite element model for the mechanical analysis of wood-plastic composite floors is established; and the results are used to verify the strength criteria under bending deformation, which is the most common loading condition of flooring board.
文摘We propose the deep Lagrange method(DLM),which is a new optimization method,in this study.It is based on a deep neural network to solve optimization problems.The method takes the advantage of deep learning artificial neural networks to find the optimal values of the optimization function instead of solving optimization problems by calculating sensitivity analysis.The DLM method is non-linear and could potentially deal with nonlinear optimization problems.Several test cases on sizing optimization and shape optimization are performed,and their results are then compared with analytical and numerical solutions.
基金AECC Commercial Aircraft Engine Co.,LTD for providing the financial support。
文摘In the design process of advanced aero-engines,it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization.Based on the structural composition and functions of aero-engines,the concept and contents of structural efficiency can reflect the relation between structural features and mechanical characteristics.In order to achieve the integrated design of structural and mechanical characteristics,one quantitative analysis method called Structural Efficiency Assessment Method(SEAM)was put forward.The structural efficiency coefficient was obtained by synthesizing the parameters to quantitatively evaluate the aero-engine structure design level.Parameterization method to evaluate structural design quality was realized.After analyzing the structural features of an actual dual-rotor system in typical high bypass ratio turbofan engines,the mechanical characteristics and structural efficiency coefficient were calculated.Structural efficiency coefficient of high-pressure rotor(0.43)is higher than that of low-pressure rotor(0.29),which directly shows the performance of the former is better,there is room for improvement in structural design of the low-pressure rotor.Thus the direction of structural optimization was pointed out.The applications of SEAM shows that the method is operational and effective in the evaluation and improvement of structural design.
基金co-supported by the National Natural Science Foundation of China(No.52005421)the Natural Science Foundation of Fujian Province of China(No.2020J05020)the Project funded by China Postdoctoral Science Foundation(No.2020M682584)。
文摘Severe stress concentration occurs around circular vent holes of an industrial turbine sealing disk.This paper investigates the structural design and optimization for the vent holes to effectively reduce the maximum von Mises stress and improve the fatigue life of the turbine sealing disk.An efficient integrated design optimization method is presented based on a novel non-circular vent hole design method in combination with a variable dimension sub-model method,a self-developed modeling and meshing tool,and the Multi-Island Genetic Algorithm.The proposed non-circular vent hole is biaxial symmetric and consists of four smoothly connected arcs.The variable dimension sub-model method is utilized to obtain accurate results in the fields around the vent holes within the computationally acceptable time.The modeling and meshing tool is developed by using the Tcl/Tk Scripts to rebuild the geometry and generate the high-quality hexahedral mesh automatically.The Multi-Island Genetic Algorithm is adopted to solve the studied constrained optimization problem.After optimization,the maximum von Mises stress is reduced from 1305.644 MPa to 963.435 MPa,and the fatigue life is increased from 3091 cycles to 30,297 cycles.The results show that the proposed design and optimization methods can significantly improve the performance of the turbine sealing disk along with the remarkable drop in stress concentration.
基金Chinese National Natural Science Foundation(No.51890881)Science and Technology Project of Hebei Education Department(Nos.ZD2020156,QN2018228).
文摘Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirectional evolutionary structural optimization(BESO)under an aperiodic load is proposed in this paper.In viewof the severe nonlinearity of fatigue damagewith respect to design variables,effective stress cycles are extracted through transient dynamic analysis.Based on the Miner cumulative damage theory and life requirements,a fatigue constraint is first quantified and then transformed into a stress problem.Then,a normalized termination criterion is proposed by approximatemaximum stress measured by global stress using a P-normaggregation function.Finally,optimization examples show that the proposed algorithm can not only meet the requirements of fatigue life but also obtain a reasonable configuration.
