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Validation of Heat Transfer, Thermal Decomposition, and Container Pressurization of Polyurethane Foam Using Mean Value and latin hypercube sampling Approaches

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FIRE TECHNOLOGY 2016年第1期52卷 121-147页

作者： Scott, Sarah N. Dodd, Amanda B. Larsen, Marvin E. Suo-Anttila, Jill M. Erickson, Ken L. Sandia Natl Labs POB 969MS 9042 Livermore CA 94551 USA

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container in order to protect them from hostile environments or from accidents such as fire. In fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of polymeric methylene diisocyanate (PMDI)-polyether-polyol based polyurethane foam is presented and compared to experimental results to assess the validity of a 3-D finite element model of the heat transfer and degradation processes. In this series of experiments, 320 kg/m(3) PMDI foam in a 0.2 L sealed steel container is heated to 1,073 K at a rate of 150 K/min. The experiment ends when the can breaches due to the buildup of pressure. The temperature at key location is monitored as well as the internal pressure of the can. Both experimental uncertainty and computational uncertainty are examined and compared. The mean value method (MV) and latin hypercube sampling (LHS) approach are used to propagate the uncertainty through the model. The results of the both the MV method and the LHS approach show that while the model generally can predict the temperature at given locations in the system, it is less successful at predicting the pressure response. Also, these two approaches for propagating uncertainty agree with each other, the importance of each input parameter on the simulation results is also investigated, showing that for the temperature response the conductivity of the steel container and the effective conductivity of the foam, are the most important parameters. For the pressure response, the activation energy, effective conductivity, and specific heat are most important. The comparison to experiments and the identification of the drivers of uncertainty allow for targeted development

关键词： Uncertainty quantification Validation Pyrolysis Heat transfer Polyurethane foam Mean value method latin hypercube sampling

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The generalization of latin hypercube sampling

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2016年 148卷 96-108页

作者： Shields, Michael D. Zhang, Jiaxin Johns Hopkins Univ Dept Civil Engn Baltimore MD 21218 USA

latin hypercube sampling (LHS) is generalized in terms of a spectrum of stratified sampling (SS) designs referred to as partially stratified sample (PSS) designs. True SS and LHS are shown to represent the extremes of the PSS spectrum. The variance of PSS estimates is derived along with some asymptotic properties. PSS designs are shown to reduce variance associated with variable interactions, whereas LHS reduces variance associated with main effects. Challenges associated with the use of PSS designs and their limitations are discussed. To overcome these challenges, the PSS method is coupled with a new method called latinized stratified sampling (LSS) that produces sample sets that are simultaneously SS and LHS. The LSS method is equivalent to an Orthogonal Array based LHS under certain conditions but is easier to obtain. Utilizing an LSS on the subspaces of a PSS provides a sampling strategy that reduces variance associated with both main effects and variable interactions and can be designed specially to minimize variance for a given problem. Several high-dimensional numerical examples highlight the strengths and limitations of the method. The latinized partially stratified sampling method is then applied to identify the best sample strategy for uncertainty quantification on a plate buckling problem. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Uncertainty quantification Monte Carlo simulation Stratified sampling latin hypercube sampling

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Numerical analysis of a dual-fueled CI (compression ignition) engine using latin hypercube sampling and multi-objective Pareto optimization

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ENERGY 2014年 70卷 278-287页

作者： Park, Jungsoo Lee, Kyo Seung Kim, Min Su Jung, Dohoy Yonsei Univ Dept Mech Engn Grad Sch Seoul 120749 South Korea Gyeonggi Coll Sci & Technol Dept Automot Engn Siheung Si 429792 Gyonggi Do South Korea DYMCO Res Ctr Siheung Si 429396 Gyonggi Do South Korea Univ Michigan Dept Mech Engn Dearborn MI 48128 USA

Diesel/natural gas dual-fuel engines were studied numerically using latin hypercube sampling (LHS) and multi-objective Pareto optimization. The combustion characteristics were analyzed and performance metrics studied as a function of the exhaust gas recirculation (EGR) fraction, compression ratio, injection timing, and natural gas fraction (NGF). The fundamental effects of the NGF on the in-cylinder pressure, peak temperature, brake torque, and brake specific fuel consumption (BSFC) were investigated. Regression coefficients were obtained using LHS to describe the sensitivity of the brake torque, BSFC, and brake specific NOX (BSNOX) emission levels to the operating parameters. A response surface was found using Pareto optimization. The dominant parameters affecting the brake torque, BSFC, and BSNOX were the compression ratio and EGR fraction. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Dual-fuel Cycle simulation Multi-component Wiebe latin hypercube sampling Multi-objective Pareto

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Fault tree analysis of a hydraulic system based on the interval model using latin hypercube sampling

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第6期37卷 8345-8355页

作者： Zhang, Feng Cheng, Lei Gao, Yang Xu, Xiayu Wang, Yameng Northwestern Polytech Univ Sch Mech Civil Engn & Architecture Xian 710129 Shaanxi Peoples R China

There will inevitably be failures during the use of hydraulic systems in armored vehicles because of the detrimental environments in which they operate. In order to improve the reliability of such hydraulic systems, a fault tree model of top event 'hydraulic system failure' is established and analyzed in this study according to the system arrangement and potential fault mechanisms. To properly consider the uncertain probability of each basic failure event in the system, it is necessary to overcome the limitations of the traditional fault tree model. Accordingly, in this study, the importance of the basic event probability interval in describing the failure probability of the top event (hydraulic system failure) was calculated using latin hypercube sampling through interval modeling. This method offers significant benefits for the reliability assessment of hydraulic systems and can be used to provide guidance for improving system reliability.

关键词： Hydraulic system interval model fault tree analysis probability interval latin hypercube sampling

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Global sensitivity analysis of the reliability of the slope stability based on the moment-independent combine with the latin hypercube sampling technique

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2023年第6期37卷 2159-2171页

作者： Xu, Zhaoxia Wang, Xiuzhen Suqian Univ Sch Civil Engn & Architecture Suqian 223800 Peoples R China Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Suqian Univ Key Lab Geol Environm & Engn Hlth Monitoring Suqian 223800 Peoples R China Suqian Univ Jiangsu Prefabricated Bldg & Intelligent Construct Suqian 223800 Peoples R China

In parameter uncertainty analysis, traditional Monte Carlo simulation (MC) requires double sampling to calculate the importance index based on the moment-independent method, which takes a long time, especially when the failure probability is small. The latin hypercube sampling method is used to simulate the uncertainty of the random variables in this study, which can consider the correlation between random variables and guarantee the accuracy in the small sample size. The moment-independent method combined with orthogonal polynomial estimation and kernel density estimation is developed to estimate the unconditional and conditional probability density functions of the output response to calculate the importance index. The results of the proposed method are in good agreement with those of the verification example and MC, and the efficiency is higher than that of the MC. Subsequently, the influence of the correlation between the shear strength parameters is investigated, and the differences in the influence of the random variables on the safety factor (Fs) and failure probability (P-f) are compared. The results show that the correlation between the shear strength parameters will greatly affect the importance indices, and the cumulative impact of each random variable on the Fs and P-f is different. This difference indicates that the influence of the parameter uncertainty is different when different dependent variables are taken as the output responses. Moreover, the correlation should not be ignored.

关键词： Failure probability Orthogonal polynomial estimation Global sensitivity analysis Moment-independent latin hypercube sampling

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Neural network based modeling of HfO₂ thin film characteristics using latin hypercube sampling

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EXPERT SYSTEMS WITH APPLICATIONS 2007年第2期32卷 358-363页

作者： Kweon, Kyoung Eun Lee, Jung Hwan Ko, Young-Don Jeong, Min-Chang Myoung, Jae-Min Yun, Ilgu Yonsei Univ Dept Elect & Elect Engn Semicond Engn Lab Seoul 120749 South Korea Yonsei Univ Dept Mat Sci & Engn Informat & Elect Mat Res Lab Seoul 120749 South Korea

In this paper, the neural network based modeling for electrical characteristics of the HfO2 thin films grown by metal organic molecular beam epitaxy was investigated. The accumulation capacitance and the hysteresis index are extracted to be the main responses to examine the characteristics of the HfO2 dielectric films. The input process parameters were extracted by analyzing the process conditions and the characterization of the films. X-ray diffraction was used to analyze the characteristic variation for the different process conditions. In order to build the process model, the neural network model using the error back-propagation algorithm was carried out and those initial weights and biases are selected by latin hypercube sampling method. This modeling methodology can allow us to optimize the process recipes and improve the manufacturability. (C) 2005 Elsevier Ltd.. All rights reserved.

关键词： HfO2 process modeling neural networks latin hypercube sampling

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An Application of latin hypercube sampling Strategy for Cogging Torque Reduction of Large-Scale Permanent Magnet Motor

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IEEE TRANSACTIONS ON MAGNETICS 2008年第11期44卷 4421-4424页

作者： Shin, Pan Seok Woo, Sung Hyun Zhang, Yanli Koh, Chang Seop Hongik Univ Dept Elect Engn Jochiwon 339701 Chungnam South Korea Shenyang Univ Technol Sch Elect Engn Shenyang 110023 Liaoning Peoples R China Chungbuk Natl Univ Sch ECE Cheongju 361763 Chungbuk South Korea

An adaptive response surface method with latin hypercube sampling strategy is employed to optimize a magnet pole shape of large-scale brushless direct current (BLDC) motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1 + lambda) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive response surface method (RSM), an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite-element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.

关键词： Brushless direct current (BLDC) motor cogging torque latin hypercube sampling optimization response surface method

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An Improved latin hypercube sampling Method to Enhance Numerical Stability Considering the Correlation of Input Variables

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IEEE ACCESS 2017年 5卷 15197-15205页

作者： Xu, Qingshan Yang, Yang Liu, Yujun Wang, Xudong Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China State Grid Tianjin Elect Power Co Elect Power Res Inst Tianjin 300010 Peoples R China

latin hypercube sampling (LHS) method has difficulty in dealing with non-positive definite correlation matrices by traditional Cholesky decomposition, whereas it may often happen with the increasing scale of input variables. In order to improve the numerical stability of LHS, an improved LHS with modified alternating projections method (L-Mapm) is proposed in this paper. Compared with other two existing modified algorithms, L-Mapm is considered to possess accuracy, speediness, and controllability at the same time. The accuracy and effectiveness of L-Mapm applied to probabilistic load flow are proven by the comparative tests in the IEEE 33-bus system and PG& E 69-bus system. The simulation results show that L-Mapm has the best performance in modification and expands the application of LHS.

关键词： latin hypercube sampling correlation matrix non-positive definite matrix Cholesky decomposition alternating projections method

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A distribution-free test for the relationship between model input and output when using latin hypercube sampling

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2003年第3期79卷 333-339页

作者： Hora, SC Helton, JC Sandia Natl Labs Dept 6849 Albuquerque NM 87185 USA Arizona State Univ Dept Math Tempe AZ 85287 USA Univ Hawaii Hilo HI 96720 USA

A test for the detection of non-monotone relationships between the inputs and outputs of computer simulation models is described for use in sensitivity analyses employing latin hypercube sampling. The test is based on the squared differences of the consecutive ranks of the output variable when the values of the output variable have been ordered by the corresponding values of an input variable. The test is distribution-free and does not require the values of the output variable to be independent of one another. Instead, the weaker assumption of exchangeability is used. The resulting test statistic is shown to be independent of Spearman's rank correlation coefficient, and a simple method for combining the two statistics is discussed. The test is illustrated with an example from a recent performance assessment for the Waste Isolation Pilot Plant. Published by Elsevier Science Ltd.

关键词： rank statistics latin hypercube sampling exchangeability sensitivity analysis Spearman's rank correlation

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Probabilistic Load Flow Method Based on Nataf Transformation and latin hypercube sampling

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2013年第2期4卷 294-301页

作者： Chen, Yan Wen, Jinyu Cheng, Shijie Huazhong Univ Sci & Technol Coll Elect & Elect Engn State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China

This paper proposed a probabilistic load flow method that can address the correlated power sources and loads. The proposed probabilistic load flow method is based on the Nataf transformation and the latin hypercube sampling. The main advantage of the proposed method is that high accurate solution can be obtained with less computation. Also, it is almost unconstrained for the probability distributions of the input random variables. Considering the uncertainties of correlated wind power, solar energy and loads, the effectiveness and the accuracy of the proposed probabilistic load flow method are verified by the comparative tests in a modified IEEE 14-bus system and a modified IEEE 118-bus system.

关键词： Correlation latin hypercube sampling Monte Carlo simulation Nataf transformation probabilistic load flow

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