• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1289-1296
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• 2019

Non-functional requirements plays a critical role in designing variety of applications domain ranges from safety-critical systems to simple gaming applications. Performance is one of the crucial non-functional requirement, especially in control and safety systems, that validates the design. System risk can be quantified as a product of probability of system failure and severity of its impact. In this paper, we devise a technique to do the performance analysis of safety critical and control systems and to estimate performance based risk factor. The technique elaborates Petri nets to estimate performability to ensure system dependability requirements. We illustrate the technique on a case study of Nuclear Power Plant system. The technique has been validated on 17 safety critical and control systems of Nuclear Power Plant.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.709-716
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• 2005

As a way to build more efficient and intelligent container cranes for todays hub ports, communication networks are used to interconnect numerous sensors, actuators, controllers, and operator switches and consoles that are spatially distributed over a crane. Various signals such as sensor values and operator's commands are digitized and broadcast on the network instead of using separate wiring cables. This not only makes the design and manufacturing of a crane more efficient, but also easier implementation of intelligent control algorithms. This paper presents the performance evaluation of CAN(Controller Area Network), TTP(Time Triggered Protocol) and Byteflight that can be used for cranes. Through discrete event simulation, several important quantitative performance factors such as the probability of a transmission failure, average system delay (data latency) and maximum system delay have been evaluated.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.3
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• pp.276-285
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• 2020

In this study, accelerated chloride diffusion tests were performed on OPC(Ordinary Portland Cement) and FA(Fly Ash) concrete considering three levels o f W/B(Water to Binder) ratio o n 1,095 curing days. The accelerated chloride diffusion coefficient and the passed charge were evaluated in accordance with Tang's method and ASTM C 1202, and the resistance performance to chloride attack improved over time. FA concrete showed excellent resistance performance against chloride penetration with help of pozzolanic reaction. As the result of the passed charge, FA concrete showed durability improvement, "low" grade to "very low" grade, but OPC concrete changed "moderate" grade to "low" grade at 1,095 curing days. After assuming the design variables used for durability design as normal distribution functions, the service life of each case was evaluated by the probabilistic analysis method based on MCS(Monte Carlo Simulation). In FA concrete, the increase of probability of durability failure was lower than that of OPC concrete with increasing time, because the time-dependent coefficient of FA concrete was up to 3.2 times higher than OPC concrete. In addition, the service life by probabilistic analysis was evaluated lower than the service life by deterministic analysis, since the target probability of durability failure was set to 10%. It is considered that more economical durability design will be possible if the mo re suitable target probability of durability failure is set for various structures through researches on actual conditions and indoor tests under various circumstances.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.95-113
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• 1997

This paper outlines a framework for a diagnosis of a complex system with uncertain information. Sensor validation ploys a vital role in the ability of the overall system to correctly determine the state of a system monitored by imperfect sensors. Here, emphases are put on the heuristic technology and post-processor for reasoning. Heuristic Sensor Validation (HSV) exploits deeper knowledge about parameter interaction within the plant to cull sensor faults from the data stream. Finally the modified probability distributions and validated data are used as input to the reasoning scheme which is the runtime version of the influence diagram. The output of the influence diagram is a diagnostic mapping from the symptoms or sensor readings to a determination of likely failure modes. Once likely failure modes are identified, a detailed diagnostic knowledge base suggests corrective actions to improve performance. This framework for a diagnostic expert system with sensor validation and reasoning under uncertainty applies in $HEATXPRT^{TM}$ a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants [1].

• International Journal of Aeronautical and Space Sciences
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• v.16 no.4
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• pp.537-547
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• 2015

A Monte Carlo (MC) simulation was conducted to predict the reliability of a newly developed pyrotechnic pin puller. The reliability model is based on the stress-strength interference model that states that failure occurs if the stress exceeds the strength. In this study, the stress is considered to be the energy consumed by movement of a pin shaft, and the strength is considered to be the energy generated by pyrotechnic combustion for driving the pin shaft. Failure of the pin puller can thus be defined as the consumed energy being greater than the generated energy. These energies were calculated using a performance model formulated in the previous study of the present authors. The MC method was used to synthesize the probability densities of the two energies and evaluate the reliability of the pin puller. From a probabilistic perspective, the calculated reliability was compared to a deterministic safety factor. A sensitivity analysis was also conducted to determine which design parameters most affect the reliability.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.593-609
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• 2004

Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.2
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• pp.199-204
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• 2013

Recently, the demand for fuel efficient electric vehicles (EVs) and hybrid electric vehicles (HEVs) has been growing globally. Due to the increased number of switching devices in the electrified vehicles, the probability of the semiconductor device failure is much higher than in other application areas. A sudden failure in one of the power switches and insufficient power management ability in the systems not only decreases system performance, but also leads to critical safety problems. In this paper, novel switch open circuit fault detection method is proposed, and the proposed approach is verified by experiments.

• Computational Structural Engineering
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• v.1 no.1
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• pp.79-85
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• 1988

The inverse algorithm of Point-Fitted Paraboloid Approximation is derived and used in reliability-based calculations. The algorithm of Reliability- Conditioned method is modified in the calculation of failure points such that nonlinear performance functions can be treated in like manner as linear cases without new formulations. SOSM/RC combined method results in probability of failure closed to specified one, and partial safety factors become nearly constant for a wide range of load ratio.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.184-189
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• 2006

This research presents the performance analysis of the linear type pneumatic actuators that are used in semi-conductor assembly line to transfer some product with high accuracy. To increase positioning and repetitive accuracies, a cross roller guide is implemented inside the pneumatic actuator. The finite element method is used to verify the force against working moments, and reliability analysis is performed to classify the breakdown cases. Also, reliability, failure rate, probability density function, and $B_{10}$ to life are estimated under the boundary of thrust or air leakage conditions. In this study, the failure probabilistic function of the pneumatic actuators is analyzed using Weibull distribution.