Classification correction of polynomial response surface methods for accurate reliability estimation

Rashki, Mohsen; Azarkish, Hassan; Rostamian, Mehdi; Bahrpeyma, Abdolhamid

doi:10.1016/j.strusafe.2019.101869

Cited by 39 publications

(14 citation statements)

References 37 publications

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“…Also, it is recommended that researchers refer to the authentic papers [26,29] for more information about MCS and score function. With regarding to high computational efforts of MCS, application of meta-model techniques in structural reliability problems has been developed and proposed [30,31,32].…”

Section: Mcs and Score Function Approachmentioning

confidence: 99%

Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions

Sadeghi

Kazemi

Samadi

2021

Frattura Ed Integrità Strutturale

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The ground external columns of buildings are vulnerable to the extreme actions such as a vehicle collision. This event is a common scenario of buildings' damages. In this study, a nonlinear model of 2-story steel moment-resisting frame (SMRF) is made in OpenSees software. This paper aims investigating the reliability analysis of aforementioned structure under heavy vehicle impact loadings by Monte Carlo Simulation (MCS) in MATLAB software. To reduce computational costs, meta-model techniques such as Kriging, Polynomial Response Surface Methodology (PRSM) and Artificial Neural Network (ANN) are applied and their efficiency is assessed. At first, the random variables are defined. Then, the sensitivity analyses are performed using MCS and Sobol's methods. Finally, the failure probabilities and reliability indices of studied frame are presented under impact loadings with various collision velocities at different performance levels and thus, the behavior of selected SMRF is compared by using fragility curves. The results showed that the random variables such as mass and velocity of vehicle and yield strength of used materials were the most effective parameters in the failure probability computation. Among the meta-models, Kriging can estimate the failure probability with the least error, sample number with minimum computer processing time, in comparison with MCS.

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Section: Mcs and Score Function Approachmentioning

confidence: 99%

Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions

Sadeghi

Kazemi

Samadi

2021

Frattura Ed Integrità Strutturale

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“…The response surface method (RSM) develops in 50 s, and it is widely used in many technical fields [ 31 ], especially in process design and optimization [ 32 ]. RSM provides optimization with the help of polynomials adapted to the data obtained from optimization procedure-designed experiments.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Fermentation Process of Pomegranate Peel and Schisandra Chinensis and the Biological Activities of Fermentation Broth: Antioxidant Activity and Protective Effect Against H2O2-induced Oxidative Damage in HaCaT Cells

Liu

Cheng

et al. 2021

Molecules

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In this study, the lactobacillus fermentation process of pomegranate (Punica granatum L.) peel and Schisandra chinensis (Turcz.) Baill (PP&SC) was optimized by using the response surface method (RSM) coupled with a Box-Behnken design. The optimum fermentation condition with the maximal yield of ellagic acid (99.49 ± 0.47 mg/g) was as follows: 1:1 (w:w) ratio of pomegranate peel to Schisandra chinensis, 1% (v:v) of strains with a 1:1 (v:v) ratio of Lactobacillus Plantarum to Streptococcus Thermophilus, a 37 °C fermentation temperature, 33 h of fermentation time, 1:20 (g:mL) of a solid–liquid ratio and 3 g/100 mL of a glucose dosage. Under these conditions, the achieved fermentation broth (FB) showed stronger free radical scavenging abilities than the water extract (WE) against the ABTS+, DPPH, OH− and O2− radicals. The cytotoxicity and the protective effect of FB on the intracellular ROS level in HaCaT cells were further detected by the Cell Counting Kit-8 (CCK-8) assay. The results showed that FB had no significant cytotoxicity toward HaCaT cells when its content was no more than 8 mg/mL. The FB with a concentration of 8 mg/mL had a good protective effect against oxidative damage, which can effectively reduce the ROS level to 125.94% ± 13.46% (p < 0.001) compared with 294.49% ± 11.54% of the control group in H2O2-damaged HaCaT cells. The outstanding antioxidant ability and protective effect against H2O2-induced oxidative damage in HaCaT cells promote the potential for the FB of PP&SC as a functional raw material of cosmetics.

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“…The surrogate model [1][2][3][4][5], also called a "response surface model", a "meta model", an "approximate model" or a "simulator", has been applied to different engineering design fields. Commonly used surrogate models include PRS (polynomial response surface) [6,7], Kriging [8][9][10][11][12], RBF (radial basis function) [13,14], SVR (support vector regression) [15,16] and MARS (multiple adaptive spline regression). According to [17] et al, Kriging (also known as Gaussian process model) is widely used.…”

Section: Introductionmentioning

confidence: 99%

“…After calculating the covariance matrix using these 20 sampling points, the first principal direction (the dotted line) is formed by the eigenvector with the largest eigenvalue in the matrix. In Figure1(b), the original 20 sampling points are mapped to the first principal direction through the linear transformation of Equation(7).…”

mentioning

confidence: 99%

An Improved High-Dimensional Kriging Surrogate Modeling Method through Principal Component Dimension Reduction

Shi

Yin

et al. 2021

Mathematics

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The Kriging surrogate model in complex simulation problems uses as few expensive objectives as possible to establish a global or local approximate interpolation. However, due to the inversion of the covariance correlation matrix and the solving of Kriging-related parameters, the Kriging approximation process for high-dimensional problems is time consuming and even impossible to construct. For this reason, a high-dimensional Kriging modeling method through principal component dimension reduction (HDKM-PCDR) is proposed by considering the correlation parameters and the design variables of a Kriging model. It uses PCDR to transform a high-dimensional correlation parameter vector in Kriging into low-dimensional one, which is used to reconstruct a new correlation function. In this way, time consumption of correlation parameter optimization and correlation function matrix construction in the Kriging modeling process is greatly reduced. Compared with the original Kriging method and the high-dimensional Kriging modeling method based on partial least squares, the proposed method can achieve faster modeling efficiency under the premise of meeting certain accuracy requirements.

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Classification correction of polynomial response surface methods for accurate reliability estimation

Cited by 39 publications

References 37 publications

Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions

Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions

Optimization of Fermentation Process of Pomegranate Peel and Schisandra Chinensis and the Biological Activities of Fermentation Broth: Antioxidant Activity and Protective Effect Against H2O2-induced Oxidative Damage in HaCaT Cells

An Improved High-Dimensional Kriging Surrogate Modeling Method through Principal Component Dimension Reduction

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