• Journal of Aerospace System Engineering
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• v.7 no.4
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• pp.1-11
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• 2013

In this study, probabilistic reliability analysis was conducted for hybrid rocket performance using Monte-Carlo Simulation. For the accuracy, reliability analysis was performed with experimental data. To simplify the analysis process, the oxidizer was supplied with constant pressure, so that pressure variation with time can be eliminated. And time-space averaged regression rate model was used. The regression rate is obtained with a series of experiments. For reliability analysis of thrust, constant exponent of regression rate is assumed that has probabilistic character. So, the efficiency of characteristic velocity has also probabilistic values. As a results, probability distribution of the thrust is obtained by Monte-Carlo simulation using random samples of the input parameter and validated under the 95% confidence level.

• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.98-103
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• 2003

Based on ASME probabilistic risk assessment (PRA) and NEI PRA peer review guidance, we evaluate a human reliability analysis (HRA) in probabilistic safety assessment (PSA) for Korea standard nuclear power plants, Ulchin Unit 3&4, to improve it performed at under design. The HRA for Ulchin Unit 3&4 is assessed as higher than Grade I based on ASME PRA standard and as higher than Grade 2 based on NEI PRA peer review guidance. The major items to be improved identified through the evaluation process are the documentation, the systematic human reliability analysis, the participitation of operators in the works and review of HRA. We suggest the guidance on the identification and qualitative screening analysis for pre-accident human errors and solve some items to be improved using the suggested guidance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.453-462
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• 2006

This paper evaluates the reliability of KEPCO system using TRELSS, which is a probabilistic reliability evaluation program for large-scaled power system. In order to reflect the characteristic of KEPCO system, the sensitivity of reliability indices such as LOLP, EDLC, EENS and Energy Curtailment for variations of TRELSS parameter and input data was analyzed. Additionally, probabilistic reliability of KEPCO system reflecting sensitivity analysis results was systematically evaluated and simulated. Finally, maximum acceptable FOR of KEPCO system to satisfy reliability criterion, which meet in process of establishing the basic plan for long-term electricity supply and demand is suggested.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.643-654
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• 2015

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.3
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• pp.49-59
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• 2004

The paper describes the preliminary ship design method using deterministic approach and probabilistic approach. In deterministic approach, there are computational aspects to applying not only the integration concurrently of principal dimension decisions and hull form variations but also hydrostatic coefficients that applied to optimization iterative process. Therefore, this paper developed that actual design concept at the preliminary ship design more than sequential design which separated in principal dimension decisions and hull form variations. Furthermore, a probabilistic approach at the preliminary ship design is applied to efficiently solve design information uncertainty that compared to deterministic approach.

• Smart Structures and Systems
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• v.32 no.3
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• pp.167-177
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• 2023

A probabilistic micromechanical framework is proposed to quantify numerically the self-healing capabilities of polymers containing microcapsules. A two-step self-healing process is designed in this study: A probabilistic micromechanical framework based on the ensemble volume-averaging method is derived for the polymers, and a hitting probability model combined with a crack nucleation model is then utilized for encountering microcapsules and microcracks. Using this framework, a series of parametric investigations are performed to examine the influence of various model parameters (e.g., the volume fraction of microcapsules, microcapsule radius, radius ratio of microcracks to microcapsules, microcrack aspect ratio, and scale parameter) on the self-healing capabilities of the polymers. The proposed framework is also implemented into a finite element code to solve the self-healing behavior of tapered double cantilever beam specimens.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.109-141
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• 1998

Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.

• Architectural research
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• v.15 no.3
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• pp.151-158
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• 2013

Offshore oil and gas process plants are exposed to hazardous accidents such as explosion and fire, so that the structural components should resist such accidental loads. Given the possibilities of thousands of different scenarios for the occurrence of an accidental hazard, the best way to predict a reasonable size of a specific accidental load would be the employment of a probabilistic approach. Having the fact that a specific procedure for probabilistic accidental hazard analysis has not yet been established especially for explosion and fire hazards, it is widely accepted that engineers usually take simple and conservative figures in assuming uncertainties inherent in the procedure, resulting either in underestimation or more likely in overestimation in the topside structural design for offshore plants. The variation in the results of a probabilistic approach is determined by the assumptions accepted in the procedures of explosion probability computation, explosion analysis, and structural analysis. A design overpressure load for a sample offshore plant is determined according to the proposed probabilistic approach in this study. CFD analysis results using a Flame Acceleration Simulator, FLACS_v9.1, are utilized to create an overpressure hazard curve. Moreover, the negative impulse and frequency contents of a blast wave are considerably influencing structural responses, but those are completely ignored in a widely used triangular form of blast wave. An idealistic blast wave profile deploying both negative and positive pulses is proposed in this study. A topside process module and piperack with blast wall are 3D FE modeled for structural analysis using LS-DYNA. Three different types of blast wave profiles are applied, two of typical triangular forms having different impulse and the proposed load profile. In conclusion, it is found that a typical triangular blast load leads to overestimation in structural design.

• Earthquakes and Structures
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• v.13 no.3
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• pp.221-230
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• 2017

One of the important phases of probabilistic performance-based methodology is establishing appropriate probabilistic seismic demand models (PSDMs). These demand models relate ground motion intensity measures (IMs) to demand measures (DMs). The objective of this paper is selection of the optimal IMs in probabilistic seismic demand analysis (PSDA) of the RC high-rise buildings. In selection process features such as: efficiency, practically, proficiency and sufficiency are considered. RC high-rise buildings with core wall structural system are selected as a case study building class with the three characteristic heights: 20-storey, 30-storey and 40-storey. In order to determine the most optimal IMs, 720 nonlinear time-history analyses are conducted for 60 ground motion records with a wide range of magnitudes and distances to source, and for various soil types, thus taking into account uncertainties during ground motion selection. The non-linear 3D models of the case study buildings are constructed. A detailed regression analysis and statistical processing of results are performed and appropriate PSDMs for the RC high-rise building are derived. Analyzing a large number of results it are adopted conclusions on the optimality of individual ground motion IMs for the RC high-rise building.

• Composites Research
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• v.26 no.1
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• pp.29-35
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• 2013

Composite sandwich structure can improve the specific bending stiffness significantly and save the weight nearly 30 percent compared with the composite laminates. However, it has more inherent uncertainties of the material property caused by manufacturing process than metals. Therefore, the reliability-based probabilistic design approach is required. In this paper, the PMS(Probabilistic Margin of Safety) is calculated for the simplified fuselage structure made of composite sandwich to provide the probabilistic reasonable evidence that the classical design method based on the safety factor cannot ensure the structural safety. In this phase, the probability density function estimated by CMCS(Crude Monte-Carlo Simulation) is used. Furthermore, the RBDO(Reliability-Based Design Optimization) under the probabilistic constraint are performed, and the RBDO-MPDF(RBDO by Moving Probability Density Function) is proposed for an efficient computation. The examined results in this paper can be helpful for advanced design techniques to ensure the reliability of structures under the uncertainty and computationally inexpensive RBDO methods.