• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.101-113
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• 2015

The Monte-Carlo (MC) technique is very efficient solution for statistical problem. Various MC methods can easily be applied to statistical circuit performance analysis. Recently, as the number of process parameters and their impact, has increasingly affected circuit performance, a sufficient sample size is required in order to consider high dimensionality, profound nonlinearity, and stringent accuracy requirements. Also, it is important to identify the performance of circuit as soon as possible. In this paper, Fast MC method is proposed for efficient analysis of circuit performance. The proposed method analyzes performance using enhanced-precision Latin Hypercube Sampling Monte Carlo (LHSMC). To increase the accuracy of the analysis, we calculate the effective dimension for the low discrepancy value on critical parameters. This will guarantee a robust input vector for the critical parameters. Using a 90nm process parameter and OP-AMP, we verified the accuracy and reliability of the proposed method in comparison with the standard MC, LHS and Quasi Monte Carlo (QMC).

• Journal of the Korean Society of Safety
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• v.17 no.3
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• pp.123-130
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• 2002

This paper presents a new dynamic human reliability analysis method and its application for quantifying the human error probabilities in implementing accident management actions. The action associated with implementation of the cavity flooding during a station blackout sequence is considered for its application. This method is based on the concept of the quantified correlation between the performance requirement and performance achievement. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which m most frequency used method in PSAs, are discussed. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the performance achievement parameter. Meanwhile, the value of the performance requirement parameter is obtained from interviews. Based on these stochastic obtained, human error probabilities are calculated with respect to the various means and variances of the things. It is shown that this method is very flexible in that it can be applied to any kind of the operator actions, including the actions associated with the implementation of accident management strategies.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.469-474
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• 1997

To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.1
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• pp.47-61
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• 2013

This study compares the Residual ultimate longitudinal strength - grounding Damage index (R-D) diagrams produced by two analysis methods: the ALPS/HULL Intelligent Supersize Finite Element Method (ISFEM) and the design formula (modified Paik and Mansour) method - used to assess the safety of damaged ships. The comparison includes four types of double-hull oil tankers: Panamax, Aframax, Suezmax and VLCC. The R-D diagrams were calculated for a series of 50 grounding scenarios. The diagrams were efficiently sampled using the Latin Hypercube Sampling (LHS) technique and comprehensively analysed based on ship size. Finally, the two methods were compared by statistically analysing the differences between their grounding damage indices and ultimate longitudinal strength predictions. The findings provide a useful example of how to apply the ultimate longitudinal strength analysis method to grounded ships.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.763-772
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• 2019

There is a need to use sheath flow nozzle to detect bioaerosol such as virus and bacteria due to their characteristics. In order to enhance the detection performance depending on nozzle parameters, numerical analysis was carried out using a commercial code, ANSYS CFX. Eulerian-lagrangian approach method is used in this simulation. Multiphase flow characteristics between primary fluid and solid were considered. The detection performance was evaluated based on the results of flow field in nozzle chamber such as focusing efficiency and swirl strength. In addition, Latin hypercube sampling(LHS) of design of experiment(DOE) was used for generating a near-random sampling. Then, the acceleration section is optimized using response surface method(RSM). Results show that the optimized model achieved a 6.13 % in a focusing efficiency and 11.47 % increase in swirl strength over the reference model.

• Journal of The Korea Institute of Healthcare Architecture
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• v.23 no.1
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• pp.7-14
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• 2017

Purpose: Since the large hospitals are one of the most intensive energy users among building types in Korea, it is important to investigate and apply appropriate energy conservation measures. There are many researches on energy conservation measures for HVAC system in hospitals, but only few useful guidelines for envelope design variables were existed. The building envelope is one of the important factors to building energy consumption and patients' comfort. The purpose of this study is to suggest the most influential envelope design variables for each end-use energy demand. Methods: 100 samples were generated by LHS(Latin Hypercube Sampling) method. After energy performance simulation, global sensitivity analysis was performed by the regression method. DesignBuilder, Simlab 2.2 and JEPlus were used in this process. Results: The most influencing variables are SHGC, SHGC and VT for heating, cooling, and lighting, respectively. However, the most influencing variable for total energy demand is WWR(Window to Wall Ratio). The analysis was conducted based on the coefficient of variance results. Implications: The six envelop design variables were ranked according to the end-use energy demand.

• Earthquakes and Structures
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• v.17 no.5
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• pp.463-475
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• 2019

In this paper, a procedure to develop fragility curves of structures equipped with semi-active tuned mass dampers (SATMDs) considering multiple failure criteria has been presented while accounting for the uncertainties of the input excitation, structure and control device parameters. In this procedure, Latin hypercube sampling (LHS) method has been employed to generate 30 random SATMD-structure systems and nonlinear incremental dynamic analysis (IDA) has been conducted under 20 earthquakes to determine the structural responses, where failure probabilities in each intensity level have been evaluated using Monte Carlo simulation (MCS) method. For numerical analysis, an eight-story nonlinear shear building frame with bilinear hysteresis material behavior has been used. Fragility curves for the structure equipped with optimal SATMDs have been developed considering single and multiple failure criteria for different performance levels and compared with that of uncontrolled structure as well as structure controlled using passive tuned mass damper (TMD). Numerical analysis has shown the capability of SATMDs in significant enhancement of the seismic fragility of the nonlinear structure. Also, considering multiple failure criteria has led to increasing the fragility of the structure. Moreover, it is observed that the influence of the uncertainty of input excitation with respect to the other uncertainties is considerable.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.690-703
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• 2010

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between $5^{th}$ and $95^{th}$ percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure.

• Clean Technology
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• v.26 no.4
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• pp.257-262
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• 2020

Two-dimensional (2D) metal organic framework (MOF) nanosheets (NSs) have recently gained considerable interest owing to their structural advantages, such as large surface area and exposed active sites. Two different types of 2D MOF NSs have been reported, including inherently layered MOFs and non-layered ones. Although several studies on inherently layered 2D MOFs have been reported, non-layered 2D MOFs have been rarely studied. This may be because the non-layered MOFs have a strong preference to form three-dimensionality intrinsically. Furthermore, the non-layered MOFs are typically synthesized in the presence of the surfactant or modulator, and thus developing facile and clean synthetic routes is highly pursued. In this study, a facile and clean synthetic methodology to grow non-layered 2D cobalt-based zeolitic imidazolate framework (ZIF-67) NSs is suggested, without using any surfactant and modulator at room temperature. This is achieved by directly converting ultrathin α-Co(OH)2 layered hydroxide salt (LHS) NSs into non-layered 2D ZIF-67 NSs. The comprehensive characterizations were conducted to elucidate the conversion mechanism, structural information, thermal stability, and chemical composition of the non-layered 2D ZIF-67. This facile and clean approach could produce a variety of non-layered 2D MOF NS families to extend potential applications of MOF materials.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.311-322
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• 2023

Riverine flood is one of the critical natural threats to river-crossing bridges. As floods are the most-occurred natural hazard worldwide, survival probability of bridges due to floods must be assessed in a speedy but precise manner. In this regard, the paper presents a reliability-based approach for a rapid assessment of failure probability of vulnerable bridge components under floods. This robust method is generic in nature and can be applied to both concrete and steel girder bridges. The developed methodology essentially utilizes limit state performance functions, expressed in terms of capacity and flood demand, for probable failure modes of various vulnerable components of bridges. Advanced First Order Reliability Method (AFORM), Monte Carlo Simulation (MCS), and Latin Hypercube Simulation (LHS) techniques are applied for the purpose of reliability assessment and developing flood fragility curves of bridges in which flow velocity and water height are taken as flood intensity measures. Upon validating the proposed method, it is applied to a case study bridge that experiences the flood scenario of a river in Gujarat, India. Research outcome portrays how effectively and efficiently the proposed reliability-based method can be applied for a quick assessment of flood vulnerability of bridges in any flood-prone region of interest.