Multidisciplinary design optimization of dental implant based on finite element method and surrogate models

Maolin Shi,Hongyou Li,Xiaomei Liu 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.10

This study aims to propose a Multidisciplinary design optimization (MDO) approach for dental implant based on Finite element method (FEM), surrogate model and a new MDO algorithm. FEM is used to calculate the stress at the implant-bone interface first. Two surrogate models, Support vector regression (SVR) and Kriging (KRG) are built to replace FEM in the following MDO of dental implant, and their verifications indicate their accuracies. A new multidisciplinary design optimization algorithm, named as Homogenizationtarget-values MDO algorithm (HTV-MDO), is established and first tested by a numerical example to demonstrate its effectiveness. After that, it is applied to the MDO of dental implant based on the SVM and KRG. The results indicate that the new MDO approach proposed in this study can effectively deal with the MDO of dental implant. The stress is reduced greatly with other characteristics of dental implant (contact area and volume of implant in this study) optimizing or slightly deteriorating. This approach can be expanded to other MDO of different bio-implants.

SVRT: a decision tree-assisted support vector regression for modeling engineering data with complex regression relationship

Maolin Shi 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5

Support vector regression has been widely used in engineering data modeling. The regression relationship of engineering data usually varies greatly, which results that it being difficult to evaluate through a unified prediction model. In this work, a decision tree-assisted support vector regression is proposed, which can take advantage of training samples partition to improve prediction accuracy. A decision tree is proposed to partition the training samples in such a way that the samples in the same part have a more similar regression relationship to each other than to those in the other parts. Support vector regression is used to evaluate the regression relationship, and an optimization algorithm is designed to search the best splitting input variable and division point at each node. For a new sample to predict, it is compared from the root node of the decision tree until reaches a certain leaf node, and the response is obtained according to the prediction model contained in the leaf node. Experiments show that the proposed method is able to provide competitive prediction results compared with the conventional prediction methods.

Modelling and study on the output flow characteristics of expansion energy used hydropneumatic transformer

Yan Shi,Tiecheng Wu,Maolin Cai,Chong Liu 대한기계학회 2016 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.30 No.3

Hydropneumatic transformer (short for HP transformer) is used to pump pressurized hydraulic oil. Whereas, due to its insufficient usage of energy and low efficiency, a new kind of HP transformer: EEUHP transformer (Expansion energy used hydropneumatic transformer) was proposed. To illustrate the characteristics of the EEUHP transformer, a mathematical model was built. To verify the mathematical model, an experimental prototype was setup and studied. Through simulation and experimental study on the EEUHP transformer, the influence of five key parameters on the output flow of the EEUHP transformer were obtained, and some conclusions can be drawn. Firstly, the mathematical model was proved to be valid. Furthermore, the EEUHP transformer costs fewer of compressed air than the normal HP transformer when the output flow of the two kinds of transformers are almost same. Moreover, with an increase in the output pressure, the output flow decreases sharply. Finally, with an increase in the effective area of hydraulic output port, the output flow increases distinctly. This research can be referred to in the performance and design optimization of the EEUHP transformers.

Dimensionless study on dynamics of pressure controlled mechanical ventilation system

Yan Shi,Jinglong Niu,Maolin Cai,Weiqing Xu 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.2

Dynamics of mechanical ventilation system can be referred in pulmonary diagnostics and treatments. In this paper, to convenientlygrasp the essential characteristics of mechanical ventilation system, a dimensionless model of mechanical ventilation system is presented. For the validation of the mathematical model, a prototype mechanical ventilation system of a lung simulator is proposed. Through thesimulation and experimental studies on the dimensionless dynamics of the mechanical ventilation system, firstly, the mathematical modelis proved to be authentic and reliable. Secondly, the dimensionless dynamics of the mechanical ventilation system are obtained. Last, theinfluences of key parameters on the dimensionless dynamics of the mechanical ventilation system are illustrated. The study provides anovel method to study the dynamic of mechanical ventilation system, which can be referred in the respiratory diagnostics and treatment.

Design optimization of a nuclear main steam safety valve based on an E-AHF ensemble surrogate model

Zong Chaoyong,Shi Maolin,Li Qingye,Liu Fuwen,Zhou Weihao,Song Xueguan 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.11

Main steam safety valves are commonly used in nuclear power plants to provide final protections from overpressure events. Blowdown and dynamic stability are two critical characteristics of safety valves. However, due to the parameter sensitivity and multi-parameter features of safety valves, using traditional method to design and/or optimize them is generally difficult and/or inefficient. To overcome these problems, a surrogate model-based valve design optimization is carried out in this study, of particular interest are methods of valve surrogate modeling, valve parameters global sensitivity analysis and valve performance optimization. To construct the surrogate model, Design of Experiments (DoE) and Computational Fluid Dynamics (CFD) simulations of the safety valve were performed successively, thereby an ensemble surrogate model (E-AHF) was built for valve blowdown and stability predictions. With the developed E-AHF model, global sensitivity analysis (GSA) on the valve parameters was performed, thereby five primary parameters that affect valve performance were identified. Finally, the ksigma method is used to conduct the robust optimization on the valve. After optimization, the valve remains stable, the minimum blowdown of the safety valve is reduced greatly from 13.30% to 2.70%, and the corresponding variance is reduced from 1.04 to 0.65 as well, confirming the feasibility and effectiveness of the optimization method proposed in this paper

Sealing design optimization of nuclear pressure relief valves based on the polynomial chaos expansion surrogate model

Zong Chaoyong,Shi Maolin,Li Qingye,Xue Tianhang,Song Xueguan,Li Xiaofeng,Chen Dianjing 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.4

Pressure relief valve (PRV) is one of the important control valves used in nuclear power plants, and its sealing performance is crucial to ensure the safety and function of the entire pressure system. For the sealing performance improving purpose, an explicit function that accounts for all design parameters and can accurately describe the relationship between the multi-design parameters and the seal performance is essential, which is also the challenge of the valve seal design and/or optimization work. On this basis, a surrogate model-based design optimization is carried out in this paper. To obtain the basic data required by the surrogate model, both the Finite Element Model (FEM) and the Computational Fluid Dynamics (CFD) based numerical models were successively established, and thereby both the contact stresses of valve static sealing and dynamic impact (between valve disk and nozzle) could be predicted. With these basic data, the polynomial chaos expansion (PCE) surrogate model which can not only be used for inputs-outputs relationship construction, but also produce the sensitivity of different design parameters were developed. Based on the PCE surrogate model, a new design scheme was obtained after optimization, in which the valve sealing stress is increased by 24.42% while keeping the maximum impact stress lower than 90% of the material allowable stress. The result confirms the ability and feasibility of the method proposed in this paper, and should also be suitable for performance design optimizations of control valves with similar structures.