Optimal cross-sectional area distribution of a high-speed train nose to minimize the tunnel micro-pressure wave

Ku, Yo-Cheon; Rho, Joo-Hyun; Yun, Sangwoon; Kwak, Myounghai; Kim, Kyu Hong; Kwon, Ho; Lee, Dong‐Ho

doi:10.1007/s00158-010-0550-6

Cited by 53 publications

(34 citation statements)

References 10 publications

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“…(7) If the predicting accuracy of the testing samples is not met, these samples should be added to the training sample set, return to step (3), and reconstruct the Kriging model. (8) If the predicting accuracy is achieved, the Kriging model is recognized as correctly constructed. The Pareto solutions are then the final optimal solutions.…”

Section: Optimization Processmentioning

confidence: 99%

“…Meanwhile some methodology studies on two-dimensional profile of the streamlined head have been performed with gradient algorithms [3]. In order to reduce the computational cost and shorten the optimization cycle, some scholars introduce the response surface method (RSM) into the aerodynamic optimization [2][3][4][5][6][7][8][9][10]. In recent years, great progress has been obtained both for the response surface technique and the computer technique, which greatly improves the optimization efficiency and makes the engineering optimization of HST be possible.…”

Section: Introductionmentioning

confidence: 99%

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Optimization design for aerodynamic elements of high speed trains

et al. 2014

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a b s t r a c tThe complex wake flow of high speed trains severely influences the running safety and amenity of the trailing car. In this paper, based on the streamlined shape of CRH380A high speed train, taking the aerodynamic lift force of the trailing car and the volume of the streamlined head as the objectives, an efficient multi-objective optimization process based on the response surface has been constructed. The Kriging model has been constructed based on the cross-validation method and genetic algorithm (GA). This approach could decrease the number of training samples and improve the optimization efficiency while without decreasing its generalization. After the Pareto optimal solutions being obtained, four design points are chosen for comparative study with the original shape, and one of these points is chosen for the unsteady aerodynamic study together with the original shape. The results reveal that the variation trends of the lift force and the side force of the trailing car are the same as that of the drag of the whole train. After optimization, the volume of the streamlined head is almost the same as that of the original shape. Compared to the original shape, the lift force of the trailing car decreases by 27.86% of and the drag of the whole train decreases by 3.34% in conditions without crosswind, and the lift force of the trailing car decreases by 5.43%, the side force of the whole train decreases by 72.09% and the drag of the whole train decreases by 2.1% in the crosswind conditions. The optimal train benefits from low fluctuations of lift and side force of the trailing car. Besides, better wake flow could be obtained, and the wake vortices are suppressed, too. Consequently, the running safety and amenity of HST are improved a lot after optimization.

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Section: Optimization Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization design for aerodynamic elements of high speed trains

et al. 2014

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“…In order to reduce the intensity of micro-pressure waves, optimization design of longitudinal-type line of high-speed trains has been studied in refs. [6][7][8]. An optimization algorithm that combines successive quadratic programming (SQP) optimization with support vector machine (SVM) which can be used for classification and nonlinear regression has been developed in ref.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional aerodynamic optimization design of high-speed train nose based on GA-GRNN

Yao

Guo

Yang

2012

Sci. China Technol. Sci.

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With the speed upgrade of the high-speed train, the aerodynamic drag becomes one of the key factors to restrain the train speed and energy saving. In order to reduce the aerodynamic drag of train head, a new parametric approach called local shape function (LSF) was adopted based on the free form surface deformation (FFD) method and a new efficient optimization method based on the response surface method (RSM) of GA-GRNN. The optimization results show that the parametric method can control the large deformation with a few design parameters, and can ensure the deformation zones smoothness and smooth transition of different deformation regions. With the same sample points for training, GA-GRNN performs better than GRNN to get the global optimal solution. As an example, the aerodynamic drag for a simplified shape with head + one carriage + tail train is reduced by 8.7%. The proposed optimization method is efficient for the engineering design of high-speed train.aerodynamic drag, GA-GRNN, parametric, high-speed trains Citation:Yao S B, Guo D L, Yang G W. Three-dimensional aerodynamic optimization design of high-speed train nose based on GA-GRNN.

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“…In order to reduce the intensity of micro-pressure waves, unconstrained single-objective optimization design for the area change ratio of the streamlined head with different nose cone lengths based on BFGS (Broyden-Fletcher-Goldfarb) algorithm and response surface model was studied in ref. [7] by Ku et al Based on support vector machine model and continuous quadratic programming method, Lee et al [8] extracted 9 design variables, designed 100 experimental sample points for train longitudinal profile lines, and used single-objective optimization design of the train aerodynamic shape to reduce the intensity of micro-pressure waves. In the present paper, on the basis of the above literature, the local function parametric approach based on free form deformation is used for CRH380A high-speed train streamlined shape.…”

Section: Introductionmentioning

confidence: 99%

“…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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Optimal cross-sectional area distribution of a high-speed train nose to minimize the tunnel micro-pressure wave

Cited by 53 publications

References 10 publications

Optimization design for aerodynamic elements of high speed trains

Optimization design for aerodynamic elements of high speed trains

Three-dimensional aerodynamic optimization design of high-speed train nose based on GA-GRNN

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

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