• International Journal of Fluid Machinery and Systems
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• 제10권3호
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• pp.240-253
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• 2017

Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The important findings are illustrated using Box-plots. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. To build a surrogate model, it is recommended to use an initial sample size equal to 15 times the number of design variables. The study will provide useful guidelines on the effect of initial sample size and distribution on surrogate construction and subsequent optimization using LHS sampling plan.

• 한국자동차공학회논문집
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• 제21권3호
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• pp.74-81
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• 2013

Due to its accuracy and efficiency, reduced kinetic mechanism of diesel surrogate is widely used as fuel model when applying 3-D diesel engine simulation. But for the well-developed prediction of diesel surrogate reduced kinetic mechanism, it is important to know some meaningful factors which affect to ignition delay time. Meanwhile, ignition delay time consists of two parts. One is the chemical ignition delay time related with the chemical reaction, and the other is the physical ignition delay time which is affected by physical behavior of the fuel droplet. Especially for chemical ignition delay time, chemical properties of each fuel were studied for a long time, but researches on their mixtures have not been done widely. So it is necessary to understand the chemical characteristics of their mixtures for more precise and detailed modeling of surrogate diesel oil. And it shows same ignition trend of paraffin mixture with those of single component, and shorter ignition delay at low/high initial temperature when mixing paraffin and toluene.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4181-4194
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• 2022

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 k-sigma 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.

• 한국항공우주학회지
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• 제42권2호
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• pp.108-118
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• 2014

근사모델을 이용한 최적설계 문제에서는 설계변수의 수가 증가함에 따라 근사모델의 정확도를 확보하기 위한 계산 횟수가 급격히 증가한다. 이를 해결하기 위해 저정확도 모델을 바탕으로 고정확도 모델로 보정하는 Variable-Fidelity Modeling을 이용하였다. 본 논문에서 Variable-Fidelity Model로는 계층적 크리깅 모델을 이용하였으며, 다목적 유전자 알고리즘과 결합하여 최적화 프레임워크를 제안하였다. 이 방법의 유용성을 검증하기 위하여 천음속 영역에 대한 익형 최적 설계를 하였다. 설계변수로는 PARSEC의 파라메터를 이용하였으며, 서로 다른 격자수를 가지는 경우 그리고 서로 다른 정확도를 가지는 해석자를 이용한 경우에 관하여 해석을 수행하였다. 검증을 위해 단일 정확도 모델에 대한 최적화 결과와 비교하였다. 모든 경우에 관하여 파레토 라인이 유사하게 나오는 것을 확인 할 수 있었으며, 계산시간은 계층적 크리깅 모델을 이용한 Variable-Fidelity Model이 단일 정확도 모델에 비하여 훨씬 줄어들었다. 이를 바탕으로 본 논문의 방법이 단일 정확도를 가지는 모델에 대한 최적화 방법과 유사한 정확도를 가지며 더욱 효율적임을 확인 할 수 있다.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.3088-3101
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• 2023

A pressurized vessel-pipe-safety valve (PVPSV) combination is a commonly used configuration in nuclear power plants, and a good numerical model is essential for the system design, sizing and performance optimization. However, owing to the large-scale and cross-scale features, it is still a challenge to build a system level numerical model with both high accuracy and efficiency. To overcome this, a novel system level modeling method which can synthesize the advantages of various models is proposed in this paper. For system modeling, the analytical approach, the method of characteristics (MOC) and the surrogate model approach are respectively adopted to predict the dynamics of the pressure vessel, the connecting pipe and the safety valve, and different models are connected through data interfaces. With this system model, dynamic simulations were carried out and both the stable and the unstable system responses were obtained. For the model verification purpose, the simulation results were compared with those obtained from experiments and full CFD simulations. A good agreement and a better efficiency were obtained, verifying the ability of the model and the feasibility of the modeling method proposed in this paper.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2552-2557
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• 2007

Shape optimization of an internal cooling passage with staggered dimples on single surface is performed and performances of surrogates are evaluated in this paper. Optimizations are performed so that turbulent heat transfer can be enhanced compromising with pressure loss due to friction. The three-dimensional governing differential equations have been solved to find the overall Nusselt number and friction factor which are related to the objective functions of this problem. Three design variables were selected among the dimensionless geometric variables. Basic surrogate models such as second order polynomial response surface approximation (RSA), Kriging meta-modeling technique, radial basis neural network (RBNN), and derived press based averaged (PBA) surrogate model are constructed. The optimal points are searched from the above constructed surrogates by sequential quadratic programming (SQP). It is shown that use of multiple surrogates can increase the robustness in prediction of better design with minimum computational cost.

• 한국유체기계학회 논문집
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• 제16권2호
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• pp.35-41
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• 2013

Inlet part of a printed circuit heat exchanger has been optimized by using three-dimensional Reynolds-Averaged Navier-Stokes analysis and surrogate modeling techniques. Kriging model has been used as the surrogate model. The objective function for the optimization has been defined as a linear combination of uniformity of mass flow rate and the pressure loss with a weighting factor. For the optimization, the angle of the inlet plenum wall, radius of curvature of the inlet plenum wall, and width of the inlet pipes have been selected as design variables. Twenty six design points are obtained by Latin Hypercube Sampling in design space. Through the optimization, considerable improvement in the objective function has been obtained in comparison with the reference design of PCHE.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2010년 춘계학술대회논문집
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• pp.187-194
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• 2010

Shape optimization of an upper plenum of PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of eight of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.

• 한국전산유체공학회지
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• 제15권3호
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• pp.16-23
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• 2010

Shape optimization of an upper plenum of a PBMR type gas cooled nuclear reactor has been performed by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. The objective function is defined as a linear combination of uniformity of flow distribution in the core and pressure drop in the upper plenum and the core. The ratio of thickness of slot to diameter of rising channels, ratio of height of upper plenum to diameter of rising channels, and ratio of height of the slot at inlet to outlet, are used as design variables for optimization. Design points are selected through Latin-hypercube sampling. The optimal point is determined through surrogate-based optimization method which uses 3-D RANS analyses at design points. The results show that the optimum shape represent remarkably improved performance in flow uniformity and friction loss than the reference shape.

• International Journal of Fluid Machinery and Systems
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• 제9권4호
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• pp.313-324
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• 2016

Surrogate model based shape optimization methodology to enhance performance of a centrifugal pump has been implemented in this work. Design variables, such as blade number and blade angles defining the pump impeller blade shape were selected and a three-level full factorial design approach was used for efficiency enhancement. A three-dimensional simulation using Reynolds-averaged Navier Stokes (RANS) equations for the performance analysis was carried out after designing the geometries of the impellers at the design points. Standard $k-{\varepsilon}$ turbulence model was used for steady incompressible flow simulations. The optimized impeller incurred lower losses by shifting the trailing edge towards the impeller pressure side. It is observed that the surrogates are problem dependent and most accurate surrogate does not deliver the best design always.