Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimizati...Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption. In this paper, a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger. This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts. In AOC, the hexagram operations in I Ching are generalized to binary string case and an iterative process, which imitates the I Ching inference, is defined. Before applying the AOC to the heat exchanger design problem, the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP). Based on the TSP results, the AOC is shown to be superior to the genetic algorithms (GA). The AOC is then used in the optimal design of heat exchanger. The shell inside diameter, tube outside diameter, and baffles spacing are treated as the design (or optimized) variables. The cost of the heat exchanger is arranged as the objective function. For the heat exchanger design problem, the results show that the AOC is comparable to the GA method. Both methods can find the optimal solution in a short period of time.展开更多
This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation o...This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation of its local search ability of genetic algorithm （GA） in solving a massive combinatorial optimization problem, simulated annealing （SA） is combined, the multi-parameter concatenated coding is adopted, and the memory function is added. Thus a hybrid genetic-simulated annealing with memory function is formed. Examples show that the modified algorithm can improve the local search ability in the solution space, and the solution quality.展开更多
As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weigh...As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.展开更多
Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,h...Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,have a minimum possible value and do not exceed the upper limit of a desired range of percentage variation.Also,it checks the feasibility of design outcome in presence of manufacturing tolerances in design variables.For any rolling element bearing,a long life indicates a satisfactory performance.In the present study,the dynamic load carrying capacity C,which relates to fatigue life,has been optimized using the robust design.In roller bearings,boundary dimensions(i.e.,bearing outer diameter,bore diameter and width)are standard.Hence,the performance is mainly affected by the internal dimensions and not the bearing boundary dimensions mentioned formerly.In spite of this,besides internal dimensions and their tolerances,the tolerances in boundary dimensions have also been taken into consideration for the robust optimization.The problem has been solved with the elitist non-dominating sorting genetic algorithm(NSGA-II).Finally,for the visualization and to ensure manufacturability of CRB using obtained values,radial dimensions drawing of one of the optimized CRB has been made.To check the robustness of obtained design after optimization,a sensitivity analysis has also been carried out to find out how much the variation in the objective function will be in case of variation in optimized value of design variables.Optimized bearings have been found to have improved life as compared with standard ones.展开更多
Effective optimization methods are used to guide the optimal design of coil parameters,which is significant for improving the transmission performance of the wireless power transfer(WPT)system.Traditional methods most...Effective optimization methods are used to guide the optimal design of coil parameters,which is significant for improving the transmission performance of the wireless power transfer(WPT)system.Traditional methods mostly rely on the exhaustive attack method and finite element analysis(FEA)to achieve the coil parameter design,which have the disadvantages of complex modeling and time-consumption.To overcome these limitations,this study proposes an optimization strategy based on the genetic algorithm(GA),which considers the actual requirements of the efficiency and power of the WPT system.First,a direct integration method is proposed to simplify the analytical solution process of the mutual inductance between the hexagonal coils.Based on the mutual inductance model,the transmission characteristics of the hexagonal coil WPT system are deeply analyzed by the control variable method.Most importantly,with the proposed optimization objective function and its constraints,the GA is used to automatically achieve multi-parameter optimization of the hexagonal coil.Finally,a 500 W WPT system experimental platform is established,and the experimental results verify the feasibility of the proposed optimization method.展开更多
In this paper, the design optimization of the structural parameters of multilayer conductors in high temperature superconducting （HTS） cable is reviewed. Various optimization methods, such as the particle swarm opti...In this paper, the design optimization of the structural parameters of multilayer conductors in high temperature superconducting （HTS） cable is reviewed. Various optimization methods, such as the particle swarm optimization （PSO）, the genetic algorithm （GA）, and a robust optimization method based on design for six sigma （DFSS）, have been applied to realize uniform current distribution among the multilayer HTS conductors. The continuous and discrete variables, such as the winding angle, radius, and winding direction of each layer, are chosen as the design parameters. Under the constraints of the mechanical properties and critical current, PSO is proven to be a more powerful tool than GA for structural parameter optimization, and DFSS can not only achieve a uniform current distribution, but also improve significantly the reliability and robustness of the HTS cable quality.展开更多
This study briefly reviews the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in geotechnical engineering since GA and PSO are widely used in civil engineering. The application of GA and P...This study briefly reviews the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in geotechnical engineering since GA and PSO are widely used in civil engineering. The application of GA and PSO is studied in three popular families of geotechnical problems including unconfined seepage analysis, slope stability analysis, and foundation design. In each category the available results from different studies are reviewed and compared. The comparison of results shows the desirable accuracy in the predicting of optimal values in the process of analysis and design. The presented methods perform successfully in the reviewed problems. However, PSO predicts the optimum values in fewer numbers of iterations, which suggests higher performance in term of implementation/application.展开更多
Clinching is a convenient and efficient cold forming process that can join two sheets without any additional part. This study establishes an intelligent system for optimizing the clinched joint. Firstly, a mathematica...Clinching is a convenient and efficient cold forming process that can join two sheets without any additional part. This study establishes an intelligent system for optimizing the clinched joint. Firstly, a mathematical model which introduces the ductile damage constraint to prevent cracking during clinching process is proposed.Meanwhile, an optimization methodology and its corresponding computer program are developed by integrated finite element model(FEM) and genetic algorithm(GA) approach. Secondly, Al6061-T4 alloy sheets with a thickness of 1.4 mm are used to verify this optimization system. The optimization program automatically acquires the largest axial strength which is approximately equal to 872 N. Finally, sensitivity analysis is implemented, in which the influence of geometrical parameters of clinching tools on final joint strength is analyzed. The sensitivity analysis indicates the main parameters to influence joint strength, which is essential from an industrial point of view.展开更多
基金supported by Science and Technology Development Fund of Macao SAR (Grant No. 033/2008/A2)Research Grant of University of Macao, China (Grant No. RG081/09-10S/TSC/FST)
文摘Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption. In this paper, a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger. This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts. In AOC, the hexagram operations in I Ching are generalized to binary string case and an iterative process, which imitates the I Ching inference, is defined. Before applying the AOC to the heat exchanger design problem, the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP). Based on the TSP results, the AOC is shown to be superior to the genetic algorithms (GA). The AOC is then used in the optimal design of heat exchanger. The shell inside diameter, tube outside diameter, and baffles spacing are treated as the design (or optimized) variables. The cost of the heat exchanger is arranged as the objective function. For the heat exchanger design problem, the results show that the AOC is comparable to the GA method. Both methods can find the optimal solution in a short period of time.
基金Project supported by the National Natural Science Foundation of China （Grant No.50375023）
文摘This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks （HMB）. Due to the limitation of its local search ability of genetic algorithm （GA） in solving a massive combinatorial optimization problem, simulated annealing （SA） is combined, the multi-parameter concatenated coding is adopted, and the memory function is added. Thus a hybrid genetic-simulated annealing with memory function is formed. Examples show that the modified algorithm can improve the local search ability in the solution space, and the solution quality.
基金Project (Nos. 2006BAK04A02-02 and 2006BAK02B02-08) sup-ported by the National Key Technology R&D Program, China
文摘As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.
文摘Optimization of cylindrical roller bearings(CRBs)has been performed using a robust design.It ensures that the changes in the objective function,even in the case of variations in design variables during manufacturing,have a minimum possible value and do not exceed the upper limit of a desired range of percentage variation.Also,it checks the feasibility of design outcome in presence of manufacturing tolerances in design variables.For any rolling element bearing,a long life indicates a satisfactory performance.In the present study,the dynamic load carrying capacity C,which relates to fatigue life,has been optimized using the robust design.In roller bearings,boundary dimensions(i.e.,bearing outer diameter,bore diameter and width)are standard.Hence,the performance is mainly affected by the internal dimensions and not the bearing boundary dimensions mentioned formerly.In spite of this,besides internal dimensions and their tolerances,the tolerances in boundary dimensions have also been taken into consideration for the robust optimization.The problem has been solved with the elitist non-dominating sorting genetic algorithm(NSGA-II).Finally,for the visualization and to ensure manufacturability of CRB using obtained values,radial dimensions drawing of one of the optimized CRB has been made.To check the robustness of obtained design after optimization,a sensitivity analysis has also been carried out to find out how much the variation in the objective function will be in case of variation in optimized value of design variables.Optimized bearings have been found to have improved life as compared with standard ones.
基金Supported by the Special Funding Support for the Innovative Construction in Hunan Province of China(2020GK2073).
文摘Effective optimization methods are used to guide the optimal design of coil parameters,which is significant for improving the transmission performance of the wireless power transfer(WPT)system.Traditional methods mostly rely on the exhaustive attack method and finite element analysis(FEA)to achieve the coil parameter design,which have the disadvantages of complex modeling and time-consumption.To overcome these limitations,this study proposes an optimization strategy based on the genetic algorithm(GA),which considers the actual requirements of the efficiency and power of the WPT system.First,a direct integration method is proposed to simplify the analytical solution process of the mutual inductance between the hexagonal coils.Based on the mutual inductance model,the transmission characteristics of the hexagonal coil WPT system are deeply analyzed by the control variable method.Most importantly,with the proposed optimization objective function and its constraints,the GA is used to automatically achieve multi-parameter optimization of the hexagonal coil.Finally,a 500 W WPT system experimental platform is established,and the experimental results verify the feasibility of the proposed optimization method.
文摘In this paper, the design optimization of the structural parameters of multilayer conductors in high temperature superconducting （HTS） cable is reviewed. Various optimization methods, such as the particle swarm optimization （PSO）, the genetic algorithm （GA）, and a robust optimization method based on design for six sigma （DFSS）, have been applied to realize uniform current distribution among the multilayer HTS conductors. The continuous and discrete variables, such as the winding angle, radius, and winding direction of each layer, are chosen as the design parameters. Under the constraints of the mechanical properties and critical current, PSO is proven to be a more powerful tool than GA for structural parameter optimization, and DFSS can not only achieve a uniform current distribution, but also improve significantly the reliability and robustness of the HTS cable quality.
文摘This study briefly reviews the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in geotechnical engineering since GA and PSO are widely used in civil engineering. The application of GA and PSO is studied in three popular families of geotechnical problems including unconfined seepage analysis, slope stability analysis, and foundation design. In each category the available results from different studies are reviewed and compared. The comparison of results shows the desirable accuracy in the predicting of optimal values in the process of analysis and design. The presented methods perform successfully in the reviewed problems. However, PSO predicts the optimum values in fewer numbers of iterations, which suggests higher performance in term of implementation/application.
基金the Fundamental Research Funds for the Central Universities of China(No.CDJZR14130006)
文摘Clinching is a convenient and efficient cold forming process that can join two sheets without any additional part. This study establishes an intelligent system for optimizing the clinched joint. Firstly, a mathematical model which introduces the ductile damage constraint to prevent cracking during clinching process is proposed.Meanwhile, an optimization methodology and its corresponding computer program are developed by integrated finite element model(FEM) and genetic algorithm(GA) approach. Secondly, Al6061-T4 alloy sheets with a thickness of 1.4 mm are used to verify this optimization system. The optimization program automatically acquires the largest axial strength which is approximately equal to 872 N. Finally, sensitivity analysis is implemented, in which the influence of geometrical parameters of clinching tools on final joint strength is analyzed. The sensitivity analysis indicates the main parameters to influence joint strength, which is essential from an industrial point of view.
