• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.501-508
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• 2000

It is demanded to find the dynamic model of a real structure to design a controller. However, as the structure has inherently infinite number of degree-of-freedom, it is impossible to obtain an exact dynamic model of the structure. Instead a reduction model with finite degree-of-freedom is used for the design of a controller. So there exists uncertainty between a real model and a reduction model which causes poor performance of control. All these uncertainties can degrade the control performance and even cause the control instability. Thus, robust control strategy considering the above uncertainties can be an alternative one to guarantee the performance and stability of the control. This study deals with the experimental verification of robust controller design for the active mass driver. $\mu$-synthesis technique is employed as a robust control strategy. Some weights are chosen based on the difference between the initial plant with which the controller is designed and the perturbed plant to be controlled having the actuator uncertainty. The robustness of $\mu$-synthesis technique is compared with the result of LQG strategy, which does not consider the uncertainty.

• Transactions of The Korea Fluid Power Systems Society
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• v.3 no.2
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• pp.14-20
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• 2006

A controller design procedure for an electro-hydraulic positioning systems has been developed using $H{\infty}$ control. The generalized plant models and weighting function for multiplicative uncertainty modelling error was presented along with $H{\infty}$ controller designs in order to investigate the robust stability and performance. Both disturbance rejection and command tracking performances were improved with the $H{\infty}$ controller, and the better uniformity of time response is achieved across wide range of operating conditions than the PID, LQR and LQG control scheme. The multiplicative uncertainty case was specifically suited for the design of an electro-hydraulic positioning control systems using $H{\infty}$ control.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.05a
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• pp.509-516
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• 1995

The uncertainty analysis for the in-vessel steam explosion during severe accidents at a nuclear power plant is performed using a probabilistic approach. This approach consists of four steps; 1) screening, 2) quantification of uncertainty 3) propagation of uncertainty, and 4) output analysis. And the specific methods which satisfy the sub-objectives of each step are prepared and presented. Compared with existing ones, the unique feature of this approach is the improved estimation of uncertainties through quantification, which ensures the defensibility of the resultant failure probability distributions. Using the approach, the containment failure probability due to in-vessel steam explosion is calculated. The results of analysis show that 1) pour diameter is the most dominant factor and slug condensed phase fraction is the least and 2) fraction of core molten is the second most dominant factor, which is identified as distinct feature of this study as compared with previous studies.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3097-3111
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• 2024

Since the level 2 PSA of OPR-1000 was the requirement for regulatory purposes, Cs-137 release estimation was contained as the Nuclear Safety Act of ROK in which the Cs-137 release frequency exceeding 100 TBq was determined to happen less than 1.0E-6 per year after the Fukushima Daiichi Accident. However, Cs-137 release estimation from the conventional level 2 PSA of OPR-1000 provided uncertainty due to dominant accident sequence consideration. Thus, this study aimed to develop systematic methods through the overall framework to quantify realistic uncertainty concerns of radioactive material release using sensitivity and uncertainty analysis methods and apply them to OPR-1000. This framework helped to quantify confidential value for the Cs-137 release under the BEPU approach using both parametric and non-parametric methods to cover both realistic and conservative points. Uncertainty propagation analysis showed the unexpected uncertainty increase of Cs-137 release exceeding 100 TBq. The non-parametric uncertainty analysis provided higher conservative concerns for safety than the realistic concerns in terms of economics when compared with the parametric uncertainty analysis. Wilks' uncertainty analysis showed the importance to consider conservative Cs-137 release in order to reach the higher safety need. Sensitivity analysis showed reasonable relationships between engineering safety parameters with the Cs-137 release.

• Journal of Power System Engineering
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• v.13 no.6
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• pp.43-50
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• 2009

If an internal combustion engine is operated by consolidated control, the minimum fuel consumption is achieved satisfying the demanded objectives. For this, it is necessary that the engine is operated on the ideal operating line which satisfies minimum fuel consumption. In this context of view, there are many tries to achieve given object. However, the parameter in the internal combustion engines are variable and depend on the operating points. Therefore, it is necessary to cope with the uncertainties such that the optimal operating may be possible. From this point of view, this paper gives a controller design method and a robust stability condition for engine torque control which satisfies the given control performance and robust stability in the presence of physical parameter perturbation. Exactly, the present paper considers a robust stability of this 2DOF servosystem with nonlinear type uncertainty in the engine system, and a robust stability condition for the servosystem is introduced. This result guarantees that if the plant uncertainty is in the permissible set defined by the given condition then a gain tuning can be carried out to suppress the influence of the plant uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1029-1037
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• 2010

If an internal combustion engine is operated by consolidated control, the minimum fuel consumption is achieved and the demanded objectives are satisfied. For this, it is necessary that the engine is operated on the ideal operating line which satisfies minimum fuel consumption. In this context of view, there are many tries to achieve given object. However, the parameters in the internal combustion engines are variable and depend on the operating points. Therefore, it is necessary to cope with the uncertainties such that the optimal operating may be possible. From this point of view, this paper gives a controller design method and a robust stability condition for engine torque control which satisfies the given control performance and robust stability in the presence of physical parameter perturbation. Exactly, in this paper, we consider the robust stability problem of this 2DOF servosystem with nonlinear type uncertainty in the engine system, and a robust stability condition for the servosystem is shown. This result guarantees that if the plant uncertainty is in the permissible set defined by the given condition, then a gain tuning can be carried out to suppress the influence of the plant uncertainties.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• Ocean Systems Engineering
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• v.6 no.2
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• pp.191-201
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• 2016

Stern bearing is a key component of marine propulsion plant. Its environment is diverse, working condition changeable, and condition severe, so that stern bearing load is of strong time variability, which directly affects the safety and reliability of the system and the normal navigation of ships. In this paper, three affecting factors of the stern bearing load such as hull deformation, propeller hydrodynamic vertical force and bearing wear are calculated and characterized by random theory. The uncertainty mathematical model of stern bearing load is established to research the relationships between factors and uncertainty load of stern bearing. The validity of calculation mathematical model and results is verified by examples and experiment yet. Therefore, the research on the uncertainty load of stern bearing has important theoretical significance and engineering practical value.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.311-322
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• 1999

Major problems involved in an electrical utility expansion planning within a time horizon are how to efficiently deal with objectives considering multiple factors and uncertainty. But justification factors in study these days have considered only quantitative factors except qualitative factors. Therefore, the purpose of this paper is to develop a new model for economic evaluation of nuclear power plants through the scoring model with the quantitative and qualitative factors under uncertainty. The quantitative factors use a levelized generation cost method considering time value of money. Especially, the environmental, risk, and safety factors in this paper have been also explained for the rational economic justification of the qualitative factors under uncertainty. This paper not only proposes a new approach method using the scoring model in evaluating economy of the nuclear power plant in the long term, but also provides the more efficient decision making criterion for nuclear power plants under uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.283-286
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• 1996

This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, fault-effect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.