• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.97-109
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• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.110-120
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• 2023

Following the Fukushima accident, portable equipment employed as accident mitigating systems have been installed and operated to reduce core damage and large early release frequencies. In addition, the establishment of an accident management strategy has gained importance. This study investigated the current status of portable equipment including the international portable equipment FLEX (diverse and flexible coping strategies), and domestic portable equipment multi-barrier accident coping strategy (MACST). Research on optimal utilization of MACST remains insufficient. As a preliminary study for establishing an optimal strategy, sensitivity studies were conducted to facilitate the priority of use on portable equipment, number of portable equipment, and dependency of operator actions based on a multi-unit probabilistic safety assessment model. The results revealed the conditions that reduced the multi-unit and site conditional core damage probabilities, indicating the optimal strategy of MACST. The results of this study can be used as a reference for establishing an optimal strategy that utilizes domestic safety equipment in the future.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.287-288
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• 2007

This paper is for a Real-time Active Control System to operate a boiler. By sensing of flame we wanted to get status of a furnace as many as possible, like load, efficiency, and/or amount of pollutant. These data can be used to make optimal running point by controlling the ratio of air and fuel. So the last object is to make a closed actual control loop from optical head to valve controllers. The first job was to design and to develop a optical data acquisition system. including optical sensor module. And we gathered flame data in variable situations for taking the trend of flame against burning environment. Currently we are developing a general system model, designing some control strategy and testing this active control system.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.3.2-3.2
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• 2009

Development of printed electronics, which is occasionally referred to as 'flexible' or 'polymer' electronics, has attracted considerable world wide attention in recent years. Printed (or flexible) electronics is currently expected to represent a new form of electronics and open up wide ranging applications in displays, electron devices for medical use, sensors, and other areas. This presentation aims to provide a strategy for scalable and viable paths to accomplish flexible, printable, large area circuits displaying high performance. Novel approaches evolving from system on package (SoP) to system on flex (SoF) technology will allow the integration of heterogeneous materials platforms into a system which is needed to enhance the functionality of the system. The talk also includes speculations about areas on which future advances in printed electronics could have a substantial impact along with a brief introduction of the Korea Printed Electronics Association (KoPEA).

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.175.2-175.2
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• 2003

Inhibition of the protein-modifying enzyme farnesyltransferase is considered as a major emerging strategy in cancer therapy because of the involvement of farnesylated proteins in oncogensis. We studied the structure-activity relationship of a novel class of CAAX-peptidomimetic farnesyltransferase inhibitors based on the benzophenone scaffold. FlexX docking of inhibitors confirmed reasonable fit of the molecule into the peptide binding site of farnesyltransferase. We also performed a virtual screening with LeadQuest chemical library databases to idenfity novel inhibitors of farnesyltransferase. (omitted)

• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.51-59
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• 2019

After Fukushima Dai-ichi NPP accident, the need for implementation of diverse and flexible coping strategies (FLEX) became evident. However, to ensure the effectiveness of the safety strategy, it is essential to quantify the uncertainties associated with the station blackout (SBO) scenario as well as the operator actions. In this paper, a systems engineering approach for uncertainty analysis (UA) of a SBO scenario in advanced pressurized water reactor is performed. MARS-KS is used as a best estimate thermal-hydraulic code and is loosely-coupled with Dakota software which is employed to develop the uncertainty quantification framework. Furthermore, the systems engineering approach is adopted to identify the requirements, functions and physical architecture, and to develop the verification and validation plan. For the preliminary analysis, 13 uncertainty parameters are propagated through the model to evaluate the stability and convergence of the framework. The developed framework will ultimately be used to quantify the aleatory and epistemic uncertainties associated with an extended SBO accident scenario and assess the coping capability of APR1400 and the effectiveness of the implemented FLEX strategies.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.67-77
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• 2020

Traditionally nuclear thermal hydraulic and nuclear safety has relied on numerical simulations to predict the system response of a nuclear power plant either under normal operation or accident condition. However, this approach may sometimes be rather time consuming particularly for design and optimization problems. To expedite the decision-making process data-driven models can be used to deduce the statistical relationships between inputs and outputs rather than solving physics-based models. Compared to the traditional approach, data driven models can provide a fast and cost-effective framework to predict the behavior of highly complex and non-linear systems where otherwise great computational efforts would be required. The objective of this work is to develop an AI algorithm to predict the peak fuel cladding temperature as a metric for the successful implementation of FLEX strategies under extended station black out. To achieve this, the model requires to be conditioned using pre-existing database created using the thermal-hydraulic analysis code, MARS-KS. In the development stage, the model hyper-parameters are tuned and optimized using the talos tool.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1404-1404
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• 2011

Shortage of fossil fuel energy makes current industry to find a new energy sources. One of the solutions is using the renewable energy sources like wind, sun, water, and so on. If we think with flex idea, the existing PV system's role can be greatly changed. So in this paper, I want to suggest some ideas for PV systems as one of outstanding energy source. The specific and technical explanation will be shown in the following paper in detail.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.102-109
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• 2023

Following the accident at Fukushima, the true impact of multi-unit accidents came to light. Accordingly, research related to multi-unit accident effect analysis, risk evaluation, and accident prevention/prevention technology has been conducted. Specific examples are mobile/fixed equipment such as multi-barrier accident coping strategy (MACST) and diverse and flexible coping strategies (FLEX), which have been introduced and installed in multi-units for preventing and mitigating multi-unit accidents. These strategies are useful for enhancing the safety of nuclear power plants (NPPs); however, a more efficient strategy is required in terms of the costs of physical and human resources. To effectively and efficiently mitigate an increase in multi-unit accidents, it is necessary to not only to utilize mobile/fixed equipment but to also use crosstie options with resources that already exist at NPPs. Therefore, we analyzed the current international and domestic status of crosstie systems technology and propose a method to evaluate feasibility alongside risk based on a multi-unit probabilistic safety assessment (PSA). To analyze the international and domestic status of crosstie systems technology, actual cases and related research were studied, and a list of potential crosstie safety resources was derived. Additionally, a case study was performed on crosstie cases of two systems within the assumed six units on-site under a multi-unit accident, and a multi-unit PSA-based risk evaluation method is proposed.