Diesel engine piston thermo-mechanical coupling simulation and multidisciplinary design optimization

Qin, Zhaoju; Li, Ying-Song; Yang, Zhenzhong; Duan, Junfa; Wang, Lijun

doi:10.1016/j.csite.2019.100527

Cited by 18 publications

(7 citation statements)

References 5 publications

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“…The common method is to deduce through an empirical or semi-empirical formula. 36 The temperature boundary condition obtained by these formulas may have some errors, resulting in inaccurate simulation results. Therefore, it is necessary to compare and correct the simulation results with the actual results to improve the accuracy of the calculation further.…”

Section: Boundary Conditions and Methods For The Piston Finite Elemen...mentioning

confidence: 99%

Titanium alloy piston thermo-mechanical coupling simulation and multi-objective optimization design

Zheng

Lei

2022

Advances in Mechanical Engineering

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To solve the problem between temperature and thermal stress of a titanium alloy piston, a multi-objective optimization method combined response surface methodology and experiment design is performed to calculate an optimal design of the titanium alloy piston. Firstly, the thermo-mechanical coupling analysis, static and dynamic characteristics analysis are carried out. The analysis results show that the thermal load has a significant influence on the piston. Secondly, the five dimensional parameters are chose as the design variables through sensitivity analysis. The piston thermo-mechanical coupling stress, deformation, mass, and the first ring groove are selected as the objective functions. By using the optimal space-filling design method, the sample points between design variables and objective functions are gained. Then, the mathematical relationship between them is obtained by the response surface method. Finally, the multi-objective genetic algorithm is employed to optimize the mathematical model. After optimization, the maximum coupling deformation decreases by 3.05%, the maximum coupling stress decreases by 27.85%, the mass reduces by 5.46%. The maximum temperature of the first ring groove reduces by 12.54%. This study can provide a reference for the piston optimization design.

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Section: Boundary Conditions and Methods For The Piston Finite Elemen...mentioning

confidence: 99%

Titanium alloy piston thermo-mechanical coupling simulation and multi-objective optimization design

Zheng

Lei

2022

Advances in Mechanical Engineering

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“…The authors compare two materials when designing the piston, and judge the performance of the piston by indicators of stress state, thermal field, and model accuracy. Qin Zhaoju et al [5] analyze and optimize a piston in a diesel engine with finite element and multidisciplinary optimization methods. There are also some studies that focus on parameter study of piston [6], coated properties [7], diesel engine combustion [8], the geometry of piston [9], and stress analysis [10].…”

Section: Introductionmentioning

confidence: 99%

Creep–Fatigue Experiment and Life Prediction Study of Piston 2A80 Aluminum Alloy

Dong¹,

Liu²,

Liu³

et al. 2021

Materials

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In order to improve the reliability and service life of vehicle and diesel engine, the fatigue life prediction of the piston in a heavy diesel engine was studied by finite element analysis of piston, experiment data of aluminum alloy, fatigue life model based on energy dissipation criteria, and machine learning algorithm. First, the finite element method was used to calculate and analyze the temperature field, thermal stress field, and thermal–mechanical coupling stress field of the piston, and determine the area of heavy thermal and mechanical load that will affect the fatigue life of the piston. Second, based on the results of finite element calculation, the creep–fatigue experiment of 2A80 aluminum alloy was carried out, and the cyclic response characteristics of the material under different loading conditions were obtained. Third, the fatigue life prediction models based on energy dissipation criterion and twin support vector regression are proposed. Then, the accuracy of the two models was verified using experiment data. The results show that the model based on the twin support vector regression is more accurate for predicting the material properties of aluminum alloy. Based on the established life prediction model, the fatigue life of pistons under actual service conditions is predicted. The calculation results show that the minimum fatigue life of the piston under plain condition is 2113.60 h, and the fatigue life under 5000 m altitude condition is 1425.70 h.

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“…e validity of optimization was verified through tests. Zhaoju et al [19] studied the corresponding relationship among "height of the piston's top," the "holes on piston pin," "weight of piston," and "maximum temperature of piston," "maximum mechanical stress," and "maximum thermal-mechanical coupling stresses" by adopting experimental design methods. e weight of piston and maximum coupling stress were optimized based on the calculation results.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

Qi¹,

Dong²,

Liu³

et al. 2021

Mathematical Problems in Engineering

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In order to increase the reliability and service life of piston in a heavy-duty diesel engine, the geometric structure of piston was optimized based on its maximum temperature and maximum coupling stress. To begin with, the boundary conditions of thermal and stress fields are calculated, which include the heat produced by the combustion in cylinder, the friction-induced heat, and the heat transferred to cooling system. Then, the finite element model was established to calculate and analyse the temperature and thermal-mechanical coupling stress fields of the piston. By combining this simulation model with orthogonal experimental design methods, computations and analyses were performed to determine how the five geometric parameters (depth of intake and exhaust valve grooves, radius of valve grooves transition, radius of top of valve grooves, height of first piston ring groove, and depth of piston ring groove) influence the two evaluation indicators (maximum temperature and maximum stress of piston). Subsequently, using the proposed ABC-OED- FE (artificial bee colony, orthogonal experiment design, and fitting equations) method, the fitting equations between the geometric parameters and evaluation indicators were determined. Taking the minimum values of two evaluation indicators of piston as optimization objectives, artificial bee colony method was run to determine the values of parameters. At last, the two evaluation indicators of the optimized piston were computed. The results indicate that, after optimization, the maximum temperature of piston decreases to be 16.05 K and the maximum stress decreases to be 13.54 MPa. Both temperature and stress conditions of the optimized piston had been improved, which demonstrates the effectiveness of the optimization and the validity of the algorithm.

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Diesel engine piston thermo-mechanical coupling simulation and multidisciplinary design optimization

Cited by 18 publications

References 5 publications

Titanium alloy piston thermo-mechanical coupling simulation and multi-objective optimization design

Titanium alloy piston thermo-mechanical coupling simulation and multi-objective optimization design

Creep–Fatigue Experiment and Life Prediction Study of Piston 2A80 Aluminum Alloy

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

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