Xueguan Song

Multiobjective Design Optimization of IGBT Power Modules Considering Power Cycling and Thermal Cycling

Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.

Blowdown prediction of a conventional pressure relief valve with a simplified dynamic model

Abstract In this research, a simplified dynamic model (SDM) is developed to predict the dynamic characteristics during the reclosing process and blowdown of a conventional pressure relief valve (PRV). The principle of the SDM is based on the equation of motion for one degree of freedom system. The damping effect is ignored due to its little effect on the reclosing time; a pressure drop condition based on lots of experiments is assumed. In addition, it is very novel that the SDM combines the static CFD analysis result, that is, the lift force coefficient of the valve at several fixed lifts is calculated with static CFD analysis, and then imported into the SDM as the inherent characteristics of the valve. The case study proved that the SDM is very reliable to predict the dynamic characteristics and blowdown of the conventional PRV.

Performance comparison and erosion prediction of jet pumps by using a numerical method

Abstract The jet pump has been studied and improved continuously for many years. The improvement of the jet pump’s efficiency brings economic advantages. In this study, the commercial software ANSYS CFX is firstly employed to investigate and compare the performance of a newly designed jet pump with two classical types. Performances such as mass flow ratio, pressure ratio and efficiency are compared at three types of working condition. It’s found that the newly designed type of jet pump has the best performance under the designed working condition. Then, this paper presents erosion evaluation for the new type of jet pump by using a CFD-based particle erosion model. The similar CFD model is conducted for the calculations of the fluid velocity field. A particle-tracking model of the sand particles is used to track the trajectory of sand particles, and Finnie’s model is used as the erosion prediction model. The results demonstrate the erosion intensity and distribution in the jet pump and show the effect of the bended pipe on the erosion in the suction chamber. The results show that numerical simulation can be very helpful for the erosion prediction and further optimization of the jet pump even though the accuracy has not been validated for this study.

Surrogate-Based Analysis and Optimization for the Design of Heat Sinks With Jet Impingement

Heat sinks are widely used for cooling electronic devices and systems. Their thermal performance is usually determined by the material, shape, and size of the heat sink. With the assistance of computational fluid dynamics (CFD) and surrogate-based optimization, heat sinks can be designed and optimized to achieve a high level of performance. In this paper, the design and optimization of a plate-fin-type heat sink cooled by impingement jet is presented. The flow and thermal fields are simulated using the CFD simulation; the thermal resistance of the heat sink is then estimated. A Kriging surrogate model is developed to approximate the objective function (thermal resistance) as a function of design variables. Surrogate-based optimization is implemented by adaptively adding infill points based on an integrated strategy of the minimum value, the maximum mean square error approach, and the expected improvement approaches. The results show the influence of design variables on the thermal resistance and give the optimal heat sink with lowest thermal resistance for given jet impingement conditions.

Structural optimization for ball valve made of CF8M stainless steel

Abstract The mechanical and chemical properties of CF8M were studied through experiments. An application of CF8M in valve body was analyzed by using finite element method(FEM) to evaluate the structural safety. An optimization containing several variables based on the response surface method(RSM) was conducted to find the optimum dimension of the valve. The results show that using this process can save valve mass as well as the computational expense effectively.

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machines previous operational performance, the DFIGs stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Analysis and optimization of nitrile butadiene rubber sealing mechanism of ball valve

Abstract An approach for analyzing and optimizing sealing mechanism of ball valve made of nitrile butadiene rubber(NBR) with finite element method was presented. The Mooney-Rivlin hyperelastic material model was chosen to characterize NBR sealing, as it has been recommended in the similar applications. That is, NBR sealing was modeled as incompressible hyperelasticity, as well as the assumption of isotropic flow. The results illustrate the structural pressure and contact pressure on the contact surface, which shows that the NBR sealing mechanism is very suitable for sealing after dimension optimization.

FLUID AND STRUCTURAL ANALYSIS OF LARGE BUTTERFLY VALVE

A butterfly valve of large diameter is commonly used as control equipments in applications where the inlet velocity is fast and the pressure is relatively high. Because of the size of the valve is too large, therefore it’s too difficult to conduct the experiment in a laboratory. In this paper, the numerical simulation using commercial package‐CFX and ANSYS was conducted. In order to do fluid analysis and structural analysis perfectly, large valve models are generated in three dimensions without much simplification, the result of fluid analysis is also fully coupled to the structural domain by the fluid‐structural interface to provide an exacter initial condition. In addition to describe the flow patterns and to measure the performance coefficients when the valves with various open angles were used, the verification of the safety performance whether the valve could work normally at those conditions or not was conducted. Fortunately, the result shows this type valve is safe in a given inlet velocity of 3m/s...

An Advanced and Robust Ensemble Surrogate Model: Extended Adaptive Hybrid Functions

Hybrid or ensemble surrogate models developed in recent years have shown a better accuracy compared to individual surrogate models. However, it is still challenging for hybrid surrogate models to always meet the accuracy, robustness, and efficiency requirements for many specific problems. In this paper, an advanced hybrid surrogate model, namely, extended adaptive hybrid functions (E-AHF), is developed, which consists of two major components. The first part automatically filters out the poorly performing individual models and remains the appropriate ones based on the leave-one-out (LOO) crossvalidation (CV) error. The second part calculates the adaptive weight factors for each individual surrogate model based on the baseline model and the estimated mean square error in a Gaussian process prediction. A large set of numerical experiments consisting of up to 40 test problems from one dimension to 16 dimensions are used to verify the accuracy and robustness of the proposed model. The results show that both the accuracy and the robustness of E-AHF have been remarkably improved compared with the individual surrogate models and multiple benchmark hybrid surrogate models. The computational time of E-AHF has also been considerately reduced compared with other hybrid models. [DOI: 10.1115/1.4039128]

Optimization of Switched Reluctance Motor for Efficiency Improvement Using Response Surface Model and Kriging Model

This paper presented an optimization of switched reluctance motor for higher efficiency. The motor in this study was designed based on the magnetic energy conversion loop according to the power requirements of application system. Its found that besides the width of air gap, the stack length and turns of winding influenced the electric and magnetic excitation greatly. Hence, in this study, the stack length, turns of winding and width of air gap were optimized as the design variables, surrogate models including response surface model and kriging model are employed to formulate the objective i.e. the efficiency, in which optimal Latin hypercube sampling and sequential sampling are implemented. Dynamic FEM analysis coupling with external circuit is utilized to conduct computer experiments of the various models. The results demonstrate the capability and potential of this approach in solving the efficiency design of reluctance motors.