System Reliability Evaluation Research Articles

A Markovian approach to reliability estimation of series-parallel system with Fermatean fuzzy sets

Markov process has been an extremely contributive method in the reliability evaluation of electrical systems for the past many decades, as a result, it has been extended by numerous researchers to address various types of issues occurring in different types of engineering systems. However, one thing it fails to address is the fuzziness in real-life systems. This fuzziness or randomness can occur either because of incomplete awareness of the operating conditions or the application of different numerical assessment methods by different operators, causing inconsistency in a system’s assessment. It can be dealt with the incorporation of the concept of fuzzy sets in the reliability analysis. This study aims to incorporate fuzzy sets, specifically, Fermatean fuzzy sets (FFS) with the Markov procedure for assessing the fuzzy reliability, availability, and sensitivity of fuzzy reliability of a system. The described approach is justified with an example of a generic series–parallel system and its fuzzy reliability and availability are computed by Markov modelling where failure rates are characterized by triangular Fermatean fuzzy numbers (TFFN). It is obtained that the behaviour of reliability, availability and sensitivity are the same as in conventional reliability evaluation, thus establishing that the proposed technique is valid. The parameters thus obtained are also depicted both in tabular and graphical forms to achieve conclusive results.

Reliability Evaluation of Composite Power Systems Integrated with Wind and Solar Energy Sources: A Comprehensive Review

Reliability Evaluation of Composite Power Systems Integrated with Wind and Solar Energy Sources: A Comprehensive Review

An Exhaustive Examination of the Motor System’s Reliability in Electric Vehicles

Due to their unique zero carbon emission feature, electric vehicles (EVs) have garnered increasing interest in recent years. However, concerns persist regarding their reliability, particularly concerning critical components. Efforts have been made to assess the reliability of drive motors in EVs. Yet, given the integration of drive motors and motor controllers as a single system in EVs, a combined assessment is essential for a more accurate reliability prediction. Additionally, considering the multiple components within both drive motors and motor controllers, their structure, type, and characteristics may influence the overall reliability of the motor system, a factor overlooked in previous research. To bridge this knowledge gap, this study investigates the reliability of the entire motor system in pure electric vans, encompassing both drive motors and motor controllers. The research begins with predicting the theoretical failure rates of subassemblies and components within the drive motor and motor controller. Subsequently, based on these predictions, the reliability of the entire motor system is assessed. The findings highlight vulnerable subassemblies and components within the motor system, shedding light on potential shortcomings in existing reliability research. These new insights are deemed crucial for informing future reliability design and maintenance practices for pure electric vans. This study undertakes an exhaustive investigation into the reliability of the motor system in EVs. As EVs gain prominence for their environmental benefits and increasing market share, concerns regarding the reliability of critical components, such as the drive motor and associated control systems, become paramount. While prior research has addressed component-level reliability, this study takes a holistic approach by assessing the entire motor system. Through theoretical modeling and empirical analysis, the study predicts failure rates of subassemblies and components within the drive motor and control systems, culminating in an evaluation of the overall motor system reliability. By uncovering vulnerabilities and potential areas for improvement, this research offers valuable insights to advance the design, development, and maintenance of reliable electric vehicles.

The acute toxic effect of Chinese medicine Fuzi is exacerbated in kidney yang deficiency mice due to metabolic difference

Ethnopharmacological relevanceThe proper application of toxic medicines is one of the characteristics of traditional Chinese medicines, and the use of traditional Chinese medicines follows the principle of dialectical treatment. It is necessary to combine different “syndrome” or “disease” states with the toxicity of traditional Chinese medicines to form a reliable toxicity evaluation system. Fuzi, the lateral root of Aconitum carmichaelii Debx, is recognized as a panacea for kidney yang deficiency syndrome, however, its toxic effects significantly limit its clinical application. Aim of the studyHerein, our research aimed to explore the toxic effects of Fuzi on syndrome models, and tried to reveal the underlying mechanisms. Materials and methodsFirstly, the mouse model of kidney yang deficiency syndrome was established through intramuscular injection of 25 mg/kg hydrocortisone per day for 10 consecutive days. Then, the acute toxicity of Fuzi in normal mice and kidney yang deficiency model mice was explored. Finally, the plasma metabolite concentrations and liver CYP3A4 enzyme activity were analyzed to reveal the possible mechanisms of the different pharmacological and toxicological effects of Fuzi in individuals with different physical constitutions. ResultsIt was found that the treatment with Fuzi (138 g/kg) had serious toxic effects on kidney yang deficiency mice, leading to the death of 80% of the mice, whereas it showed no lethal toxicity in normal mice. This indicates that Fuzi induced greater toxicity in kidney yang deficiency mice than in normal ones. The liver CYP3A4 enzyme activity in kidney yang deficiency mice was decreased by 20% compared to the controls, resulting in slower metabolism of the toxic diester diterpenoid alkaloids in Fuzi. ConclusionIn conclusion, our study showed that changes of the metabolic enzyme activity in individuals with different syndromes led to different toxic effects of Chinese medicines, emphasizing the crucial importance of considering individual physical syndromes in the clinical application of traditional Chinese medicine, and the significance of conducting safety evaluations and dose predictions on animal models with specific syndromes for traditional Chinese medicines.

Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures

Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures

Dynamic Survival Risk Prognostic Model and Genomic Landscape for Atypical Teratoid/Rhabdoid Tumors: A Population-Based, Real-World Study.

An atypical teratoid/rhabdoid tumor (AT/RT) is an uncommon and aggressive pediatric central nervous system neoplasm. However, a universal clinical consensus or reliable prognostic evaluation system for this malignancy is lacking. Our study aimed to develop a risk model based on comprehensive clinical data to assist in clinical decision-making. We conducted a retrospective study by examining data from the Surveillance, Epidemiology, and End Results (SEER) repository, spanning 2000 to 2019. The external validation cohort was sourced from the Children's Hospital Affiliated to Chongqing Medical University, China. To discern independent factors affecting overall survival (OS) and cancer-specific survival (CSS), we applied Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) regression analyses. Based on these factors, we structured nomogram survival predictions and initiated a dynamic online risk-evaluation system. To contrast survival outcomes among diverse treatments, we used propensity score matching (PSM) methodology. Molecular data with the most common mutations in AT/RT were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. The annual incidence of AT/RT showed an increasing trend (APC, 2.86%; 95% CI:0.75-5.01). Our prognostic study included 316 SEER database participants and 27 external validation patients. The entire group had a median OS of 18 months (range 11.5 to 24 months) and median CSS of 21 months (range 11.7 to 29.2). Evaluations involving C-statistics, DCA, and ROC analysis underscored the distinctive capabilities of our prediction model. An analysis via PSM highlighted that individuals undergoing triple therapy (integrating surgery, radiotherapy, and chemotherapy) had discernibly enhanced OS and CSS. The most common mutations of AT/RT identified in the COSMIC database were SMARCB1, BRAF, SMARCA4, NF2, and NRAS. In this study, we devised a predictive model that effectively gauges the prognosis of AT/RT and briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges.

Reliability and Performance Evaluation of Safety-Critical Instrumentation and Control Systems of Nuclear Power Plant

Instrumentation and control systems are nervous systems of nuclear power plant (NPP). These systems interact with several safety-critical components of the NPP, such as actuators, transformers, control valves, sensors, circuit breakers, signal processing units, controllers, and heat exchangers. Therefore, the failure of these systems could result in significant financial loss, harm to human resources, or environmental damage. As a result, these systems need to be highly reliable and accurate. In this article, we suggest a framework, based on the batch deterministic and stochastic Petri nets (BDSPNs) to measure the reliability and performance of safety-critical system. The framework consists of three phases. In the first phase, the system is modeled using the BDSPN to derive the transition rate among the system states. In phase 2, the transition rate matrix is utilized to compute the steady-state probability values, which help to evaluate the response time of the system using Little's law. The third phase uses a transition probability matrix to assess the reliability of the system. The technique is illustrated on shutdown system of NPP and is validated on the operational profile data. The obtained accuracy of 99.9905% in measurement of reliability validates the approach.

An efficient cross-entropy method addressing high-dimensional dependencies for composite systems reliability evaluation

Cross-entropy (CE) based importance sampling (IS) accelerates the reliability evaluation of power system greatly, but is mainly focused on the CEIS of independent random variables (RVs) or low-dimensional correlated RVs (CRVs). To extend the CE method to high-dimensional CRVs while avoiding the “curse of dimensionality” in optimizing a high-dimensional IS probability density function (IS-PDF), an efficient CE method termed as CE-DRDM, is developed from a dimension-reduced dependence model (DRDM). First, based on the DRDM’s original hierarchical disaggregate structure (HDS), the CE-DRDM which conducts the CEIS for a single aggregate RV rather than the high-dimensional CRVs is proposed. Second, to solve the issue that the performance of CE-DRDM may degrade in the case of high penetration of renewable energy, the CE-DRDM is enhanced by improving the DRDM’s HDS, and then a novel CE optimization method is proposed, through which the analytical updating formulas of IS-PDF parameters can be derived. Thirdly, the CE-DRDM is further enhanced by using a sparse density estimator, based on which the number of IS-PDF parameters needed to be optimized in the CE optimization reduces greatly, and consequently the optimization accuracy improves accordingly. Finally, the validity of CE-DRDM is verified by several numerical cases with high-dimensional dependencies.

Cross-entropy based importance sampling for composite systems reliability evaluation with consideration of multivariate dependence

Multivariate kernel density estimation (KDE) is powerful for dependence modeling, but producing a non-sparse probability density estimation model. To address this issue, a sparse density estimation technique termed as generalized cross-entropy (GCE) density estimator, is proposed to estimate the joint probability density function (PDF) of correlated random variables (RVs). Moreover, to effectively accelerate the composite systems reliability evaluation, a unified cross-entropy based importance sampling (CEIS) method accommodating both GCE and KDE density estimators is presented, and a creative CE optimization approach is also developed based on the composition sampling algorithm, through which the analytical updating rules of IS-PDF parameters can be derived even though GCE and KDE estimators do not belong to the exponential distribution family (EF). Compared to the KDE estimator, the GCE estimator encounters much less dimensionality difficulty in CE optimization due to the model sparsity merit, and consequently achieves more accurate IS-PDF parameters and better CEIS efficiency. The superiority of GCE estimator over KDE estimator in correlation modeling and CEIS is verified by several numerical tests.

Reliability analysis of interval-valued multi-state sliding window system for sequential tasks

In industrial applications, an interval variable with both an upper and a lower bound is utilized to define the bounded or ranged performance of a system or its elements. This paper proposes a new interval-valued multi-state sliding window system for sequential tasks (IMSWS-ST). The proposed system consists of n circularly or linearly connected multi-state elements (MEs) with their performance states described as interval-valued variables. The system function is determined by the ability of any group of r consecutive MEs for completing predetermined sequential tasks with interval-valued demands. To describe and evaluate system reliability, a universal generating function technique is employed, considering the differences between linear and circular configurations. Additionally, we develop a state aggregation method to reduce the computational burden during reliability evaluation. Numerical experiments are then conducted to demonstrate the proposed system model and validate the suggested algorithms. Finally, we investigate the optimal sequencing problem for MEs within the IMSWS-ST to achieve higher system reliability.

Study on Reliability of PACSs with Integrated Consideration of Both Basic and Mission Reliability

Protective relays play a fundamental role in power systems, whose functions consist of three parts, namely protection, automation, and control, thus called the PAC altogether. It turns out that the architecture of a PACS (protection, automation, and control system) may exert a direct impact on the reliability of protective relay systems, previous studies of which are often conducted on the assumption that intelligent electronic devices (IEDs) have a constant fault rate with only mission reliability of the systems considered. To obtain a more accurate evaluation of system reliability bearing system maintenance in mind, this article proposes a novel method to appraise the reliability of PACSs with integrated consideration of basic and mission reliability. Firstly, the basic reliability of IEDs is calculated by parts count prediction, which will provide a more precise fault rate of IEDs. Secondly, the reliability of PACSs is analyzed by the reliability diagram and Markov model. By using the parts count prediction method to calculate the failure rate of the device, the steady-state probability rate will be accurate more than 0.0107%. At last, a quantitative criterion is finalized for selecting a suitable architecture easily.

Quantitative evaluation of tourism crisis response policies: overview and lessons from China’s tourism epidemic response policies

ABSTRACT Governments and DMOs have enacted a number of policies to cope with the impacts of unpredictable disruptions, such as COVID-19, on recovering regional tourism industries. Retrospective analysis and scientific evaluation of the content, quality, and implementation efficacy of existing policies serve as an important reference for future policy formulation, modification, and improvement. This study utilized the PMC-AE index model to construct an evaluation model of the tourism epidemic response policy and then evaluated and compared China’s tourism policies at the national and provincial levels from the perspective of policy formulation. The results indicated that: First, China’s tourism epidemic response policy included four categories: epidemic prevention and control and follow-up supervision, relief support and recovery development, resumption of work and production, and consumption promotion. Second, most of the policies remain relatively high, and the scores at national and provincial levels decline from high to low, forming a ‘top-down’ pattern to cope with the epidemic’s impact effectively. Simultaneously, there were no significant differences between policy types and regions, but provincial policies were significantly more targeted than specialized policies. Lastly, some tourism epidemic response policies remained problematic, particularly concerning insufficient predictive content, a single target audience, the structural imbalance of incentive methods, and the lack of cooperation between the publishing parties. This study validated the reliability and efficacy of the PMC-AE policy evaluation system in tourism policy research and provided a reference for formulating future epidemic response policies.

A subset simulation analysis framework for rapid reliability evaluation of series-parallel cold standby systems

A subset simulation analysis framework for rapid reliability evaluation of series-parallel cold standby systems

Modeling Multi-Temporal Correlation of PV Stations Output via Improved Nonparametric Disaggregation Method in Power System Reliability Evaluation

Modeling Multi-Temporal Correlation of PV Stations Output via Improved Nonparametric Disaggregation Method in Power System Reliability Evaluation

System reliability evaluation of 12-pulse series converter station based on improved Dijkstra algorithm

System reliability evaluation of 12-pulse series converter station based on improved Dijkstra algorithm

Reliability Evaluation and Improvement of Power Transmission Systems Using Series Compensation

Reliability Evaluation and Improvement of Power Transmission Systems Using Series Compensation

Application of REPAS to analyze the sump clogging issue following a LOCA and its impact on the reliability of the ECCS long-term core cooling function

Sump clogging has been identified as a relevant issue after an accident occurred in the Barsebäck-2 nuclear power plant in Sweden (1992). Following a steam line Loss of Coolant Accident (LOCA) due to the inadvertent opening of a safety relief valve, the jet stripped some insulation material from nearby pipes. The insulation debris were transported to the inlet of the strainers for the drywell spray system, thus clogging the intake. The accident was not serious but showed that the Emergency Core Cooling System (ECCS) could have failed. As a consequence, several actions have been undertaken by international organizations, regulatory bodies and nuclear power plant owners to characterize this issue, and propose solutions and improvements. In the present paper, the Reliability Evaluation of Passive Safety Systems (REPAS) methodology is applied to analyze the sump clogging issue and its effect on the long-term core cooling function. Originally developed to evaluate the reliability of passive systems, REPAS is here applied for the first time to an active system. The application is performed using the TRAC/RELAP Advanced Computational Engine (TRACE) code, developed by the USNRC, to simulate a generic three-loop PWR, with an active decay heat removal system.

Reliability evaluation of radial distribution system considering common mode failures and different weather effects

Reliability evaluation of distribution systems plays a crucial role in ensuring the uninterrupted supply of electricity to consumers. This paper presents a comprehensive analysis of distribution system reliability using the Failure Mode and Effects Analysis (FMEA) technique. The study focuses on evaluating the reliability of the distribution system considering various failure modes, including busbar failure, section failure, distributor failure, transformer failure, maintenance-related issues, transient failures, and the impact of weather conditions. The findings of this research can assist utilities and system operators in identifying critical failure modes and implementing appropriate measures to enhance the reliability of distribution systems, ensuring continuous and reliable electricity supply to consumers.

Reliability evaluation of phased-mission systems exposed to random shocks

The paper aims to examine the reliability analysis problem of phased-mission systems that execute multiple consecutive non-overlapping mission phases in a random shock environment. Each phase is carried out by several subsystems which consist of non-repairable components connected in different topology configurations. The random shocks, modeled by a Poisson process, significantly affect the failure rate of components within the dynamic subsystems. The system configuration, success criteria, and component failure behavior may differ from phase to phase. The paper presents technical methodologies to evaluate the mission success probabilities of subsystems in various configurations and proposes a modularization method to compute the reliability of phased-mission systems by combining the mission success probabilities of all subsystems. Finally, a numerical example is provided to illustrate the proposed model and method.

QMU Analysis of Flexoelectric Timoshenko Beam by Evidence Theory

In recent years, with the rapid development of nanotechnology, a new type of electromechanical coupling effect similar to the piezoelectric effect, the flexoelectric effect, has gradually come into the public’s view. The flexoelectric beam that is the main structural unit of the flexoelectric signal output has broad application prospects in the next generation of micro- and nanoelectromechanical systems. Therefore, the investigation of flexoelectric materials and structures has important scientific and engineering application significances for the design of flexoelectric devices. In this paper, a model of flexoelectric Timoshenko beam is established, the deflection, rotation angle, and dynamic electrical signal output of the forced vibration are taken as the system response, and the density ρ , shear correction factor κ , and frequency ratio λ are selected as the key performance parameters of the system. The combination of available data and engineers’ experience suggests that there are random and cognitive uncertainties in the parameters. Therefore, the probability distribution of the system performance response is expressed by the likelihood function and belief function through the quantification of margins and uncertainties (QMUs) analysis methodology under the framework of evidence theory, and the system reliability or performance evaluation is measured by the calculated confidence factors. These results provide a theoretical basis for accurate analysis of flexoelectric components and provide guidance for the design of flexoelectric components with excellent performance.