• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.91-96
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• 1996

The Dynamic Safety System (DSS) is a compute. based reactor protection system that has fail-safe nature and perform dynamic self-testing. In this paper, the implementation of DSS in PLC is presented for PWR. In order to choose adequate PLC implementation model of DSS, the reliability analysis is performed. The KO-RI unit 2 Nuclear power plant is selected as the reference plant, and the verification is carried out using the KO-RI unit 2 simulator FISA-2.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.575-584
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• 2014

In this study, the NREL 5 MW wind turbine tower model was optimized according to the multi-body dynamics and reliability-based design. The mathematical model was defined as a link-joint system including dynamic characteristics derived from Timoshenko's beam theory. For the optimization problem, the sensitivities to variations in the tower thicknesses and inner and outer diameters were acquired and arranged in terms of safety and efficiency according to bending stress and buckling standards. An optimal design was calculated with the advanced first-order second moment method and used to define a finite element model for validation. The finite element model was simulated by static analysis. The relationship between the multi-body dynamic and finite element method throughout the process was investigated, and the optimal model, which had high endurance despite its low mass, was determined.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.147-153
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• 2004

This paper presents an analytical modeling technique fer representing a hysteretic behavior of a multi-leaf spring used for a large truck. It divides a nonlinear hysteretic curve of the multi-leaf spring into four parts; loading part, unloading part and two transition parts. It provides conditions fur branching to a part of the curve corresponding to a current multi-leaf spring status. This paper also presents a computational modeling technique of the multi-leaf spring. It models the multi-leaf spring with three links and a shackle. It assumes those components as rigid bodies. The links are connected by rotational joints, and have rotational springs at the joints. The spring constants of the rotational springs are computed with a force from the analytical model of the hysteretic curve of the multi-leaf spring. Static and dynamic tests are performed to verify the reliability of the presented techniques. The tests are performed with various amplitudes and excitation frequencies. The hysteretic curves from the tests are compared with those from the simulations. Since th e presented techniques reproduce the hysteretic characteristic of the multi -leaf spring faithfully, they contribute on improving the reliability of the computational model of a large truck.

• Proceedings of the Korean Reliability Society Conference
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• 2011.06a
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• pp.107-113
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• 2011

The windshield wiper consists of 4 parts: a blade, an arm, a linkage and a motor. The wiper blade makes contact with the windshield and is designed to be operated normally at an angle of 30~50 degrees to the front glass. If the contact pressure between the wiper blade and windshield surface is too high, noise and wear of the rubber will result. On the other hand, if the contact pressure is too low, the performance will do badly, since foreign substances such as dust and stains will not be removed well. The pressure and friction of the wiper blade has a great influence on its effectiveness in cleaning the front window. This is due to the contact of the rubber with the window. This paper presents the dynamic analysis method to estimate the performance of the flat type blade of the wiper system. The blade has a nonlinear characteristic since the rubber is an incompressible hyper-elastic and visco-elastic material. Thus, Structural dynamic analysis using a complex contact model for the blade is performed to find the characteristics of the blade. The flexible multi-body dynamic model is verified by the comparison between test and analysis result. Also, the optimization using the central composite design table is performed.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.40-46
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• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.164-171
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• 2009

This paper presents new learning algorithm of dynamic Bayesian networks (DBN) by means of constrained least square (LS) estimation algorithm and gradient descent method. First, we propose constrained LS based parameter estimation for a Markov chain (MC) model given observation data sets. Next, a gradient descent optimization is utilized for online estimation of a hidden Markov model (HMM), which is bi-linearly constructed by adding an observation variable to a MC model. We achieve numerical simulations to prove its reliability and superiority in which a series of non stationary random signal is applied for the DBN models respectively.

• Earthquakes and Structures
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• v.24 no.2
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• pp.141-153
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• 2023

The presented paper considers infill masonry walls' influence on the seismic reliability of precast concrete frames. The recent Bojnord earthquake on May 13th, 2017 in Iran (MW 5.4) illustrated that the infill masonry walls play a crucial role in the damage extent and life safety issues of inhabitants in the precast concrete buildings. The incremental dynamic analysis (IDA) approach was used to determine the fragility curves of the represented damaged precast frame. Then, by integrating site hazard and structural fragilities, the seismic reliability of the represented precast frame was evaluated in different damage limit states. Additionally, the static pushover analysis (SPA) approach was used to assess the seismic performance assessment of the precast frame. Bare and infilled frames were modeled as 2D frames employing the OpenSees software platform. The multi-strut macro-model method was employed for infill masonry simulation. Also, a relatively efficient and straightforward nonlinear model was used to simulate the nonlinear behavior of the precast beam-column joint. The outputs show that consideration of the masonry infilled wall effect in all spans of the structural frame leads to a decrease in the possibility of exceedance of specified damage limit states in the structures. In addition, variation of hazard curves for buildings with and without consideration of infilled walls leads to a decrease in the reliability of the building's frames with masonry infilled walls. Furthermore, the lack of infill walls in the first story significantly affects the precast concrete frame's seismic reliability and performance.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.132-143
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• 1999

In this study, an intermediate model is presented as a new method for development of a parametric simulation program. This model enables us to analyze effectively the static and dynamic structure of a real production system. The static structure of the real system can be modelled in an entity-relationship diagram and the dynamic structure of the real system in a Petri net. The intermediate model consists of an entity-relationship diagram and a Petri net. Using this intermediate model man can not only reduce the time and cost for simulation program development, but also increase the modelling reliability of the developed simulation program. To show the usefulness of this intermediate model. the intermediate models for two production subsystems, manufacturing sub-system and transport subsystem, are set up.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.