• Geomechanics and Engineering
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• 제10권6호
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• pp.709-726
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• 2016

Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

• 대한기계학회논문집A
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• 제28권5호
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• pp.503-510
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• 2004

In this paper, the well-conditioned observer for a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic uncertainties such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic uncertainties such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_{2}$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic uncertainties. In stochastic viewpoints, the estimation variance represents the robustness to the stochastic uncertainties and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• 대한교통학회지
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• 제10권3호
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• pp.7-20
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• 1992

The common cycle time for the linded signals is usually determined for the critical intersecion, just because the cpacity of a signalized intersection depends on the cycle time. This may not be optimal since the interactions between the flow and the spatial structure of the route or the area are disregarded in this case. It is common to separate the total delay incurred at signals into two parts, a deterministic or uniform delay and a stochastic or random delay. The deterministic delays and the stochastic delays on the artery particularly related to signal cycle time. For this purpose a microscopic simulation technique is used to evaluate deterministic delays, and a macroscopic simulation technique based on the principles of Markov chains is used to evaluate stochastic delays with over flow queue. As a result of investigating the relations between deterministic delays and cycle time in the various circumstances of spacing of signals and traffic volume. As for stochastic delays the resalts of comparisons of the macroscopic simulation and Newell's approximation with the microscopic simulation indicate that the former is valid for the degree of saturation less than 0.95 and the latter is for that above 0.95. Newell's argument that the total stochastic delay on an arterial is dominated by that at or caused by critical intersection is certified by the simulation experiments. The comprehensive analyses of the values of optimal cycle time with various conditions lead to a model. The cycle time determined by this model shows to be approximately 70% of that calculated by Webster's.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• 한국군사과학기술학회지
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• 제24권5호
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• pp.558-568
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• 2021

The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

• 대한조선학회논문집
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• 제56권2호
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• pp.161-167
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• 2019

In general, fatigue analysis is performed by using deterministic model to estimate the optimal parameters. However, the deterministic model is difficult to clearly describe the physical phenomena of fatigue failure that contains many uncertainty factors. With regard to this, efforts have been made in this research to compare with the deterministic model and the stochastic models. Firstly, One deterministic S-N curve was derived from ordinary least squares technique and two P-S-N curves were estimated through Bayesian-linear regression model and Markov-Chain Monte Carlo simulation. Secondly, the distribution of Long-term fatigue damage and fatigue life were predicted by using the parameters obtained from the three methodologies and the long-term stress distribution.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2151-2161
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• 2021

Nuclear data (ND) sensitivity and uncertainty (S/U) quantification in shielding applications is performed using deterministic and probabilistic approaches. In this paper the validation of the newly developed deterministic program package ASUSD (ADVANTG + SUSD3D) is presented. ASUSD was developed with the aim of automating the process of ND S/U while retaining the computational efficiency of the deterministic approach to ND S/U analysis. The paper includes a detailed description of each of the programs contained within ASUSD, the computational workflow and validation results. ASUSD was validated on two shielding benchmark experiments from the Shielding Integral Benchmark Archive and Database (SINBAD) - the fission relevant ASPIS Iron 88 experiment and the fusion relevant Frascati Neutron Generator (FNG) Helium Cooled Pebble Bed (HCPB) Test Blanket Module (TBM) mock-up experiment. The validation process was performed in two stages. Firstly, the Denovo discrete ordinates transport solver was validated as a standalone solver. Secondly, the ASUSD program package as a whole was validated as a ND S/U analysis tool. Both stages of the validation process yielded excellent results, with a maximum difference of 17% in final uncertainties due to ND between ASUSD and the stochastic ND S/U approach. Based on these results, ASUSD has proven to be a user friendly and computationally efficient tool for deterministic ND S/U analysis of shielding geometries.

• 한국터널지하공간학회 논문집
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• 제12권3호
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• pp.265-274
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• 2010

터널에서 암반구조의 복잡성으로 인해 사전에 예측 할 수 없었던 암반의 붕락이 발생하여, 붕락대책에 막대한 비용과 시간을 낭비하는 사례가 많다. 암반 불연속면의 복잡성을 사전 조사 단계에서 충분히 파악하거나 대책을 수립하는 것은 어렵다. 최근 터널의 정보화 설계시공이 중요시 되어지고 있다. 본 연구에서는 터널의 굴착 전에 관찰된 정보를 최대한 활용하여 불안정한 암반블럭을 사전에 예측하기 위하여 신 하이브리드 추계학적-확정론적 암반블럭 해석기법을 제안하고, 현지에서 관찰한 불연속면 정보를 근거로 하여 터널현장에 적용했다. 터널현장에서의 해석결과를 비교 검토하여, 터널의 신 하이브리드 추계학적-확정론적 암반블럭 해석기법의 타당성과 적용성에 대한 검증을 하였다.

• 한국심리학회지 : 문화 및 사회문제
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• 제9권spc호
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• pp.123-147
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• 2003

이 연구에서는 토착 문화심리학을 토대로 사고와 안전에 대한 확률론적인 시각과 결정론적인 시각을 비교 분석하였다. 한국뿐만 아니라 대부분의 선진국이나 개발도상국에서 사고로 인한 사망과 재해는 예방이 가능하다. 이 연구의 첫 번째 부분에서는 사회과학과 응용과학에서 채택되어온 선형의 결정론적인 모형의 한계에 대해 설명하였다. 가정 직장과 사회에서 발생하는 사고와 안전의 확률론적인 속성에 대한 이해를 위해, 토착 문화심리학에서 주장되어온 상호작용 모형이 제안되었다. 두 번째로는 사고와 안전에 관련된 요소들을 검토하였다. 세 번째로는 한국사회에서 사고를 예방하고 안전을 증진하기 위해 확률론적 모형의 활용에 대해 설명하였다.

• 대한의용생체공학회:의공학회지
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• 제32권1호
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• pp.15-24
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• 2011

While Compton imaging is recognized as a valuable 3-D technique in nuclear medicine, reconstructing an image from Compton scattered data has been of a difficult problem due to its computational complexity. The most complex and time-consuming computation in Compton camera reconstruction is to perform the conical projection and backprojection operations. To alleviate the computational burden imposed by these operations, we investigate a rebinning method which can convert conical projections into parallel projections. The use of parallel projections allows to directly apply the existing deterministic reconstruction methods, which have been useful for conventional emission tomography, to Compton camera reconstruction. To convert conical projections into parallel projections, a cone surface is sampled with a number of lines. Each line is projected onto an imaginary plane that is mostly perpendicular to the line. The projection data rebinned in each imaginary plane can then be treated as the standard parallel projection data. To validate the rebinning method, we tested with the representative deterministic algorithms, such as the filtered backprojection method and the algebraic reconstruction technique. Our experimental results indicate that the rebinning method can be useful when the direct application of existing deterministic methods is needed for Compton camera reconstruction.