With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train ...With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.展开更多
This paper develops a many-objective optimization model, which contains objectives representing the interests of the electricity and gas networks, as well as the distributed district heating and cooling units, to coor...This paper develops a many-objective optimization model, which contains objectives representing the interests of the electricity and gas networks, as well as the distributed district heating and cooling units, to coordinate the benefits of all parties participated in the integrated energy system(IES). In order to solve the many-objective optimization model efficiently, an improved objective reduction(IOR) approach is proposed, aiming at acquiring the smallest set of objectives. The IOR approach utilizes the Spearman’s rank correlation coefficient to measure the relationship between objectives based on the Pareto-optimal front captured by the multi-objective group search optimizer with adaptive covariance and Lévy flights algorithm, and adopts various strategies to reduce the number of objectives gradually. Simulation studies are conducted on an IES consisting of a modified IEEE 30-bus electricity network and a 15-node gas network. The results show that the many-objective optimization problem is transformed into a bi-objective formulation by the IOR. Furthermore,our approach improves the overall quality of dispatch solutions and alleviates the decision making burden.展开更多
Degree reduction of parametric curves and surfaces is an important process in data communication between CAD systems. The degenerate condition of Bezier curves and the constrained optimization method are used to devel...Degree reduction of parametric curves and surfaces is an important process in data communication between CAD systems. The degenerate condition of Bezier curves and the constrained optimization method are used to develop a new degree reduction method for Bezier curves. An error analysis of the degree reduction is also given. The degree reduction scheme is combined with a subdivision algorithm to generate lower degree approximations which are within some preset error tolerance of the prescribed Bezier curve. Geometric continuity between adjacent curve segments is also considered in the subdivision/degree reduction process.展开更多
In the present paper, an ‘in-house＇ genetic algorithm was numerically and experimentally validated. The genetic algorithm was applied to an optimization problem for improving the aerodynamic performances of an aircr...In the present paper, an ‘in-house＇ genetic algorithm was numerically and experimentally validated. The genetic algorithm was applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The optimization was performed for 16 flight cases expressed in terms of various combinations of speeds, angles of attack and aileron deflections. The displacements resulted from the optimization were used during the wind tunnel tests of the wing tip demonstrator for the actuators control to change the upper surface shape of the wing. The results of the optimization of the flow behavior for the airfoil morphing upper-surface problem were validated with wind tunnel experimental transition results obtained with infra-red Thermography on the wing-tip demonstrator. The validation proved that the 2D numerical optimization using the ‘in-house＇ genetic algorithm was an appropriate tool in improving various aspects of a wing＇s aerodynamic performances.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 50823004)the National Key Technology R&D Program of China (No. 2009BAG12A01-C09)+1 种基金the 2013 Doctoral Innovation Funds of Southwest Jiaotong Universitythe Fundamental Research Funds for the Central Universities, China
文摘With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.
基金supported by the State Key Program of National Natural Science Foundation of China(No.51437006)Guangdong Innovative Research Team Program(No.201001N0104744201)
文摘This paper develops a many-objective optimization model, which contains objectives representing the interests of the electricity and gas networks, as well as the distributed district heating and cooling units, to coordinate the benefits of all parties participated in the integrated energy system(IES). In order to solve the many-objective optimization model efficiently, an improved objective reduction(IOR) approach is proposed, aiming at acquiring the smallest set of objectives. The IOR approach utilizes the Spearman’s rank correlation coefficient to measure the relationship between objectives based on the Pareto-optimal front captured by the multi-objective group search optimizer with adaptive covariance and Lévy flights algorithm, and adopts various strategies to reduce the number of objectives gradually. Simulation studies are conducted on an IES consisting of a modified IEEE 30-bus electricity network and a 15-node gas network. The results show that the many-objective optimization problem is transformed into a bi-objective formulation by the IOR. Furthermore,our approach improves the overall quality of dispatch solutions and alleviates the decision making burden.
文摘Degree reduction of parametric curves and surfaces is an important process in data communication between CAD systems. The degenerate condition of Bezier curves and the constrained optimization method are used to develop a new degree reduction method for Bezier curves. An error analysis of the degree reduction is also given. The degree reduction scheme is combined with a subdivision algorithm to generate lower degree approximations which are within some preset error tolerance of the prescribed Bezier curve. Geometric continuity between adjacent curve segments is also considered in the subdivision/degree reduction process.
基金Bombardier Aerospace,Thales Canada,The Consortium in Research and Aerospace in Canada(CRIAQ)the Natural Sciences and Engineering Research Council of Canada(NSERC)for their financial support
文摘In the present paper, an ‘in-house＇ genetic algorithm was numerically and experimentally validated. The genetic algorithm was applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The optimization was performed for 16 flight cases expressed in terms of various combinations of speeds, angles of attack and aileron deflections. The displacements resulted from the optimization were used during the wind tunnel tests of the wing tip demonstrator for the actuators control to change the upper surface shape of the wing. The results of the optimization of the flow behavior for the airfoil morphing upper-surface problem were validated with wind tunnel experimental transition results obtained with infra-red Thermography on the wing-tip demonstrator. The validation proved that the 2D numerical optimization using the ‘in-house＇ genetic algorithm was an appropriate tool in improving various aspects of a wing＇s aerodynamic performances.
