Nose Shape Optimization of High-speed Train for Minimization of Tunnel Sonic Boom.

Kwon, Ho; Jang, Ki-hyeok; Kim, Yu-shin; Yee, Kwanjung; Lee, Dong‐Ho

doi:10.1299/jsmec.44.890

Cited by 49 publications

(35 citation statements)

References 8 publications

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“…In order to obtain a streamlined design with excellent aerodynamic performance and improve the optimization efficiency of a train head's aerodynamic shape, many scholars have done a lot of work (Kwon et al, 2001;Lee & Kim, 2008;Sun, Song, & An, 2010;Vytla, Huang, & Penmetsa, 2010;Yao, Guo, & Yang, 2012). Lee and Kim (2008) developed an optimization algorithm that combines successive quadratic programming (SQP) optimization with a support vector machine in order to reduce micro-pressure.…”

mentioning

confidence: 99%

A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train

Yao¹,

Guo

Sun

et al. 2015

Engineering Applications of Computational Fluid Mechanics

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Based on the concepts of niche count and crowding distance, a modified multi-objective particle swarm optimization (MPSO) is introduced. The niche count and crowding distance are used to determine the globally best particle across four test cases using an external file. A comparative analysis was carried out between MPSO and non-dominated sorting multiobjective adaptive genetic algorithms, both real-coded and binary-coded. The results show that MPSO based on the crowding distance is best for getting the Pareto front, especially for problems with high-dimensional and non-continuous Pareto fronts. In order to verify the efficiency of MPSO in solving engineering problems, the optimal design of the aerodynamic nose shape of high-speed trains was undertaken using a modified vehicle modeling function (MVMF) parametric method. Taking the aerodynamic drag of the whole train (Cd) and the aerodynamic lift of the trailer car (Cl) as the optimization goals, the Kriging surrogate model was introduced to reduce the computational time, and the MPSO based on crowding distance was used to find the Pareto front. The optimization results show that MPSO is efficient at getting the Pareto front; compared to the original shape, the Cd and Cl of the optimal shape are reduced by 1.6% and 29.74%, respectively.

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mentioning

confidence: 99%

A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train

Yao¹,

Guo

Sun

et al. 2015

Engineering Applications of Computational Fluid Mechanics

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show abstract

“…Currently, very few studies on multi-objective optimization design of train head can be found. Kwon et al (2001) studied the influence of the nose shape on the intensity of the pressure gradient of the compression wave at the tunnel entrance, where the response surface method was used as a basis for the optimization of nose shape of high-speed trains. The analytical results showed that the front 20% part of the train nose played the most important role in the minimization of the maximum pressure gradient.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization design method of the high-speed train head

Maruyama

Zhang

2013

J. Zhejiang Univ. Sci. A

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Abstract: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%.

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“…At present, there are few references on multi-objective optimization design of the aerodynamic shape of the highspeed train using both CFD and optimization algorithm. The existing research [5][6][7][8][9][10] mostly focuses on two-dimensional contour of trains or unconstrained single-objective optimization with less efficient optimization algorithm, and is difficult to be applied to practical engineering problems with constraints, large amounts of computation and a number of design parameters. Ku et al [5] combined two single-objective optimization processes, obtained the optimal rate of section change of streamlined parts of the leading car having micro-pressure waves as a goal which were generated through tunnels, and then completed the single-objective optimization design based on Kriging model and VMF (Vehicle Modeling Function) three-dimensional parametric approach to reduce aerodynamic drag of the leading car on the premise that the rate of section change is constant.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of the streamlined head of high-speed trains based on the Kriging model

Yao

Guo

Sun

et al. 2012

Sci. China Technol. Sci.

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As the running speed of high-speed trains increases, aerodynamic drag becomes the key factor which limits the further increase of the running speed and energy consumption. Aerodynamic lift of the trailing car also becomes the key force which affects the amenity and safety of the train. In the present paper, a simplified CRH380A high-speed train with three carriages is chosen as the model in order to optimize aerodynamic drag of the total train and aerodynamic lift of the trailing car. A constrained multi-objective optimization design of the aerodynamic head shape of high-speed trains based on adaptive non-dominated sorting genetic algorithm is also developed combining local function three-dimensional parametric approach and central Latin hypercube sampling method with maximin criteria based on the iterative local search algorithm. The results show that local function parametric approach can be well applied to optimal design of complex three-dimensional aerodynamic shape, and the adaptive non-dominated sorting genetic algorithm can be more accurate and efficient to find the Pareto front. After optimization the aerodynamic drag of the simplified train with three carriages is reduced by 3.2%, and the lift coefficient of the trailing car by 8.24%, the volume of the streamlined head by 2.16%; the aerodynamic drag of the real prototype CRH380A is reduced by 2.26%, lift coefficient of the trailing car by 19.67%. The variation of aerodynamic performance between the simplified train and the true train is mainly concentrated in the deformation region of the nose cone and tail cone. The optimization approach proposed in the present paper is simple yet efficient, and sheds lights on the constrained multi-objective engineering optimization design of aerodynamic shape of high-speed trains.

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Nose Shape Optimization of High-speed Train for Minimization of Tunnel Sonic Boom.

Cited by 49 publications

References 8 publications

A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train

A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train

Multi-objective optimization design method of the high-speed train head

Multi-objective optimization of the streamlined head of high-speed trains based on the Kriging model

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