A multi-state Semi-Markov model for nuclear power plants piping systems subject to fatigue damage and random shocks under dynamic environments

Liang, Qingzhu; Peng, Changhong; Li, Xiangyu

doi:10.1016/j.ijfatigue.2022.107448

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…Let the decision function of the SVM binar y classifier be defined as equation (2). Then, the optimal decision surface is found by employing constraint equation (3)(4), classifying all data points accordingly.…”

Section: Support Vector Machinementioning

confidence: 99%

“…A misjudgment by the operators can lead to more severe consequences, as evidenced by the Three Mile Island nuclear incident. At present, there are different nuclear power fault diagnosis models based on different algorithms [1][2][3][4][5], which can quickly and accurately identify and evaluate the failure or component damage of the nuclear power system under their respective scenarios, significantly improving the safety and economy of nuclear power plants. Therefore, it is imperative to have a system capable of swiftly and accurately identifying the severity of faults wh en malfunctions occur in nuclear power plants.…”

Section: Introductionmentioning

confidence: 99%

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Fault severity classification based on information flow and support vector machines

Yang,

Liu,

Fang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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Fault severity describes the level of impact caused by a fault. In the event of a malfunction in a nuclear power plant, a vast amount of data and alarms are generated, making it challenging for operators to identify and determine the state of the power plant in a short time. If the fault severity can be effectively identified during a malfunction, it would allow the operators to respond quickly and prevent further losses. Compared to other machine learning methods, the Support Vector Machine (SVM) has superior classification capability in scenarios with limited nuclear power samples. However, if the feature representation of the SVM training sample is inadequate, resulting in similar, indistinguishable training data, it will affect the SVM's classification of fault severity. To address this issue, using the Liang-Kleeman Information Flow (IF) can characterize information transmission from a causal perspective. By introducing IF to combine features of the training data, insufficient sample features can be replaced with the IF that describes information from a causal viewpoint, thereby enhancing the SVM's accuracy in fault severity classification. This paper takes the Main Steam Line Break accident in the primary loop of the nuclear reactor as an example and conducts simulation experiments on the PCTRAN simulation platform. The experimental results show that under 5 different fault degrees, the accuracy of fault degree evaluation of SVM model combined with IF is improved. This method can effectively improve the classification accuracy of different fault severity degrees in MSLB steam flow data with similar changes.

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Section: Support Vector Machinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault severity classification based on information flow and support vector machines

Yang,

Liu,

Fang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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“…Polystyrene foam (EPS) is a highly versatile and widely used material due to its favorable properties, such as lightweight, low density, good temperature adaptability, and most importantly, strong buffering ability. [40][41][42][43] It finds application in material packaging, construction engineering, and road engineering. 44 When increasing the buried depth of the pipeline is not feasible, the efficacy of the PE pipeline under the impact of falling rock can be improved by adding an EPS cushion, which reduces the impact energy.…”

Section: Protective Measures Analysismentioning

confidence: 99%

Section: Pipeline Safety Analysismentioning

confidence: 99%

Dynamic response and safety analysis of polyethylene pipeline under rockfall conditions

Yang

Liu

Peng

et al. 2023

Quality & Reliability Eng

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The safety of buried gas pipelines in mountainous cities is at risk due to potential hazards such as landslides and rock falls. To ensure the safety of pipelines, this paper develops a three‐dimensional dynamic response model to reveal the impact of rockfall radius, rockfall impact velocity, and pipe burial depth on the dynamic response of buried polyethylene pipelines (PE pipelines) under rockfall conditions. Subsequently, an orthogonal experimental design and analysis of variance (ANOVA) are performed to identify critical factors. Ultimately, a multi‐factor limit state equation is constructed to assess the safety of PE pipelines accordingly failure prevention actions for buried gas pipelines under the impact of rockfall is specified. Overall, this proposed method contributes to safety analysis of buried PE pipelines in rockfall‐prone areas.

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“…Emergency circumstances in industries where butterfly check valves are used will not only cause harm to personnel and the plant but also adversely affect the environment [16,17]. Due regard for the operating conditions of the device and ensuring the reliability of the structure are two of the most significant tasks when designing safety fittings [18,19]. These indicators, in turn, represent the structural ability to maintain tightness and operability throughout its entire service life [20].…”

Section: Introductionmentioning

confidence: 99%

Operation Simulation for a Check Valve Used in High-Performance Systems

Soboleva,

Kerimov,

Anudinov

et al. 2023

Civ Eng J

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This research aims to increase the reliability and safety of pipeline systems by creating an improved model range of Butterfly Check Valves (BCV). Pipes through which working fluids are transported, parts related to shut-off and control valves, control measuring instruments, fasteners, anticorrosion elements, and other structural components are the main elements that make up pipelines. Fittings can be of different types; BCV refers to protective ones. These devices protect pipelines by disconnecting the working line in the event of a sudden change in the transported fluid parameters (pressure, flow direction), resulting in the failure of the entire system. Based on an analysis of the key requirements for valves, namely reliability, tightness of a closed system, ensuring safe operation, and analysis of existing BCVs, the design of the presented valve was created. Improved overall dimensions and tightness, both in the open and closed states, as opposed to the existing analogs, are distinctive features of the developed design of butterfly check valves. To confirm the results, the authors, using the finite element method, calculated the stress–strain state of the structure under normal conditions and with regard to the maximum temperatures of the working fluid. The reliability indicators of the developed elements were also calculated to confirm their operability. As a result, it was concluded that after the developed valves have passed acceptance tests, the research findings will make it possible to increase the reliability and safety of the valve itself and the entire pipeline system by introducing these structures into enterprises. Doi: 10.28991/CEJ-2023-09-12-017 Full Text: PDF

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A multi-state Semi-Markov model for nuclear power plants piping systems subject to fatigue damage and random shocks under dynamic environments

Cited by 10 publications

References 18 publications

Fault severity classification based on information flow and support vector machines

Fault severity classification based on information flow and support vector machines

Dynamic response and safety analysis of polyethylene pipeline under rockfall conditions

Operation Simulation for a Check Valve Used in High-Performance Systems

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