• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• Korean Journal of Weed Science
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• v.18 no.2
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• pp.122-127
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• 1998

This experiment was conducted to investigate the response of the fertilizer three factors on the growth of Alopeuclus aequalis Sobol. var. amurensis(Kom.) Ohwi. The growth of Alopeuclus aequalis Sobol. var. amurensis(Kom.) Ohwi. such as plant height, tiller number and dry matter production were vigorous on the plot fertilized with phosphate(P, NP, PK, NPK). The main effect of plant height elongation and dry matter production were significant for phosphate and nitrogen, and their interaction effect was recognized, too. Tiller growth and panicle number were mainly affected by phosphate. The growth of Alopeuclus aequalis Sobol. var. amurensis(Kom.) Ohwi. depended mostly on phosphate among the fertilizer three factors. The effect of nitrogen fertilizer was very different according to phosphate fertilizer treatment.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.5
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• pp.177-185
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• 2020

The building energy performance indicator, called Energy Performance Index (EPI), has been used for the past decades in South Korea. It has a list of design variables assigned with weighting factors (a, b). Unfortunately, the current EPI method is not performance-based but very close to a prescriptive rating. With this in mind, this study aims to propose a new performance-based EPI method. For this purpose, a global sensitivity analysis method, Sobol, is employed. The Sobol method is suitable for complex nonlinear models and can decompose all the output variance due to every input. The Sobol sensitivity index of each variable is defined as 0 to 1 (0 to 100%), and the sum of all sensitivity indices is equal to 1 (100%). In this study, an office building was modeled using EnergyPlus and then the Latin Hypercube Sampling (LHS) was conducted to generate a surrogate model to EnergyPlus. The sensitivity index was suggested to replace weight (a) in the existing EPI. In addition, the discrete weight (b) in the existing EPI was replaced by a set of continuous regression functions. Due to the introduction of the sensitivity index and the continuous regression functions, the new proposed approach can provide far more accurate outcome than the existing EPI (R²: 0.83 vs. R²: 0.01 for cooling, R²: 0.66 vs. R²: 0.01 for total energy). The new proposed approach proves to be more rational, objective and performance-based than the existing EPI method.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.316-324
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• 2020

This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

• Korean Journal of Medicinal Crop Science
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• v.22 no.2
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• pp.98-104
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• 2014

In the present study, we investigated the anti-inflammatory effects by Alopecurus aequalis Sobol on the lipopolysaccharide (LPS)-induced nitric oxide (NO) production by RAW 264.7 cell line. Consistent with these observations, DS reduced the LPS-induced expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) at the protein levels in a concentration-dependent manner. In addition, the release of tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) and interleukin-6 (IL-6) were also reduced by DS. Moreover, LPS increased expression phosphorylation of $I{\kappa}B{\alpha}$, but DS showed inhibitory effect by reducing LPS-inducible p-$I{\kappa}B{\alpha}$ expression level. These results suggest that the down regulation of iNOS, COX-2, TNF-${\alpha}$, and IL-6 expression by DS are achieved by the downregulation of NF-${\kappa}B$ activity, a transcription factor necessary for pro-inflammatory mediators, and that is also responsible for its anti-inflammatory effects.

• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• International journal of steel structures
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• v.18 no.5
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• pp.1684-1698
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• 2018

Fragility functions are determined for braced steel moment frames (SMFs) with plans such as square-, T-, L-, U-, trapezoidal-, and semicircular-shaped, subjected to blast. The frames are designed for gravity and seismic loads, but not necessarily for the blast loads. The blast load is computed for a wide range of scenarios involving different parameters, viz. charge weight, standoff distance, and blast location relative to plan of the structure followed by nonlinear dynamic analysis of the frames. The members failing in rotation lead to partial collapse due to plastic mechanism formation. The probabilities of partial collapse of the SMFs, with and without bracing system, due to the blast loading are computed to plot fragility curves. The charge weight and standoff distance are taken as Gaussian random input variables. The extent of propagation of the uncertainties in the input parameters onto the response quantities and fragility of the SMFs is assessed by computing Sobol sensitivity indices. The probabilistic analysis is conducted using Monte Carlo simulations. The frames have least failure probability for blasts occurring in front of their corners or convex face. Further, the unbraced frames are observed to have higher fragility as compared to counterpart braced frames for far-off detonations.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.115-125
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• 2021

Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the "curse of dimensionality" when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.

• Korean Journal of Weed Science
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• v.14 no.4
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• pp.239-244
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• 1994

As a fundamental study to control Alopeuclus aequalis Sobol. var. amurensis(Kom.) Ohwi., on dominant weed in barley and dry seeded rice cultivation on paddy fields, several factors which would have closer relations to its germination and emergence, were examined. The results are as follows. The dormancy of seeds were broken at dry-heat treatment of $30^{\circ}C$. The germination rate of the seeds was high in order of 15>10>20> $5^{\circ}C$ and was very low at more than $25^{\circ}C$. The emergence of A. aequalis was influenced little for the light, but had a tendency to be good on the dark condition. The seeds dried on room temperature germinated few but them treated on $30^{\circ}C$ for 24 hours were germinated over 80%. The A. aequalis occured few in the saline soil of salt concentration of more than 0.25% and the germination rate of seeds was very low on the over 0.5% solution of NaCl. On the solution of pH 6.0~12.0, the germination was not effected for pH but was very few on pH 2.0. At the paddy-lowland which have cultivated the soybean for three years A. aequalis emerged a few.

• Computers and Concrete
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• v.2 no.5
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• pp.411-421
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• 2005

A linear programming problem of the optimal proportioning of concrete aggregates is discussed; and a self-adaptive genetic algorithm is developed to solve this problem. The proposed method is based on changing a range of variables for capturing the feasible region of the optimum solution. A computational verification of this method is compared with the results of the linear programming.