In design optimization of crane metal structures, present approaches are based on simple models and mixed variables, which are difficult to use in practice and usually lead to failure of optimized results for rounding...In design optimization of crane metal structures, present approaches are based on simple models and mixed variables, which are difficult to use in practice and usually lead to failure of optimized results for rounding variables. Crane metal structure optimal design（CMSOD） belongs to a constrained nonlinear optimization problem with discrete variables. A novel algorithm combining ant colony algorithm with a mutation-based local search（ACAM） is developed and used for a real CMSOD for the first time. In the algorithm model, the encoded mode of continuous array elements is introduced. This not only avoids the need to round optimization design variables during mixed variable optimization, but also facilitates the construction of heuristic information, and the storage and update of the ant colony pheromone. Together with the proposed ACAM, a genetic algorithm（GA） and particle swarm optimization（PSO） are used to optimize the metal structure of a crane. The optimization results show that the convergence speed of ACAM is approximately 20% of that of the GA and around 11% of that of the PSO. The objective function value given by ACAM is 22.23% less than the practical design value, a reduction of 16.42% over the GA and 3.27% over the PSO. The developed ACAM is an effective intelligent method for CMSOD and superior to other methods.展开更多
Proprietary metal 3D printing is still relegated to relatively expensive systems that have been constructed over years of expensive trial-and-error to obtain optimum 3D printing settings.Low-cost open-source metal 3D ...Proprietary metal 3D printing is still relegated to relatively expensive systems that have been constructed over years of expensive trial-and-error to obtain optimum 3D printing settings.Low-cost open-source metal 3D printers can potentially democratize metal additive manufacturing;however,significant resources are required to redevelop optimal printing parameters for each metal on new machines.In this study,the particle swam optimization(PSO)experimenter,a free and open-source software package,is utilized to obtain the optimal printing parameters for a tungsten inert gas-based metal open source 3D printer.The software is a graphical user interface implementation of the PSO method and is designed specifically for hardware-in-loop testing.It uses the input of experimental variables and their respective ranges,and then proposes iterations for experiments.A custom fitness function is defined to characterize the experimental results and provide feedback to the algorithm for low-cost metal additive manufacturing.Four separate trials are performed to determine the optimal parameters for 3D printing.First,an experiment is designed to deposit and optimize the parameters for a single line.Second,the parameters for a single-layer plane is optimized experimentally.Third,the optimal printing parameters for a cube is determined experimentally.Fourth,the line optimization experiment is revised and reconducted using different shield gas parameters.The results and limitations are presented and discussed in the context of expanding wire arc additive manufacturing to more systems and material classes for distributed digital manufacturing.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.51275329)the Youth Fund Program of Taiyuan University of Science and Technology,China(Grant No.20113014)
文摘In design optimization of crane metal structures, present approaches are based on simple models and mixed variables, which are difficult to use in practice and usually lead to failure of optimized results for rounding variables. Crane metal structure optimal design（CMSOD） belongs to a constrained nonlinear optimization problem with discrete variables. A novel algorithm combining ant colony algorithm with a mutation-based local search（ACAM） is developed and used for a real CMSOD for the first time. In the algorithm model, the encoded mode of continuous array elements is introduced. This not only avoids the need to round optimization design variables during mixed variable optimization, but also facilitates the construction of heuristic information, and the storage and update of the ant colony pheromone. Together with the proposed ACAM, a genetic algorithm（GA） and particle swarm optimization（PSO） are used to optimize the metal structure of a crane. The optimization results show that the convergence speed of ACAM is approximately 20% of that of the GA and around 11% of that of the PSO. The objective function value given by ACAM is 22.23% less than the practical design value, a reduction of 16.42% over the GA and 3.27% over the PSO. The developed ACAM is an effective intelligent method for CMSOD and superior to other methods.
文摘Proprietary metal 3D printing is still relegated to relatively expensive systems that have been constructed over years of expensive trial-and-error to obtain optimum 3D printing settings.Low-cost open-source metal 3D printers can potentially democratize metal additive manufacturing;however,significant resources are required to redevelop optimal printing parameters for each metal on new machines.In this study,the particle swam optimization(PSO)experimenter,a free and open-source software package,is utilized to obtain the optimal printing parameters for a tungsten inert gas-based metal open source 3D printer.The software is a graphical user interface implementation of the PSO method and is designed specifically for hardware-in-loop testing.It uses the input of experimental variables and their respective ranges,and then proposes iterations for experiments.A custom fitness function is defined to characterize the experimental results and provide feedback to the algorithm for low-cost metal additive manufacturing.Four separate trials are performed to determine the optimal parameters for 3D printing.First,an experiment is designed to deposit and optimize the parameters for a single line.Second,the parameters for a single-layer plane is optimized experimentally.Third,the optimal printing parameters for a cube is determined experimentally.Fourth,the line optimization experiment is revised and reconducted using different shield gas parameters.The results and limitations are presented and discussed in the context of expanding wire arc additive manufacturing to more systems and material classes for distributed digital manufacturing.
