Comprehensive Reliability Assessment Research Articles

Introducing Copula Functions to Estimate the Reliability of Dependent Mechanical Systems

This paper addresses the challenge of assessing the reliability of complex mechanical systems where components are inherently correlated in their failure modes. Traditionally, the assumption of independence among these components has been employed, but it often fails to capture the real-world complexities. To overcome this limitation, copula functions are introduced as a robust methodology for modeling the dependent relationships between correlated variables within mechanical systems. This paper aims to demonstrate the utility of copulas in estimating system reliability while accounting for these dependencies. The results reveal that the Clayton copula emerges as the most suitable model for representing dependence in such systems. Importantly, the reliability estimates obtained through copula-based methods not only reflect the complex interdependencies accurately but also align with the principles of the boundary theory of reliability. This research underscores the potential of copula-based reliability estimation as a valuable alternative, offering a more comprehensive and precise assessment of reliability in complex mechanical systems and holding significant promise for practical engineering applications. This framework allows the consideration of dependence among the observed variables that is usually overlooked in engineering practice.

System-level optimisation of hybrid energy powered irrigation system

Renewable energy-powered irrigation systems have emerged as sustainable solutions, particularly for farmers in off-grid areas. While existing research often highlights tank storage-based systems as the most cost-effective option, large-scale deployment of water tanks incurs significant costs and maintenance challenges. Additionally, there is limited research on the feasibility and optimisation of battery-based irrigation systems, which are often deemed costly despite their potential benefits. This study addresses this gap by identifying the optimal storage solution for hybrid energy-powered irrigation systems through a system-level optimisation model. The model evaluates the suitability of three storage options: direct-coupled water tank storage, battery-coupled storage, and a hybrid battery-tank storage system. Optimisation criteria include life cycle cost (LCC), loss of power supply probability (LPSP), and loss of load probability (LOLP), ensuring a comprehensive assessment of both cost and reliability. Results indicate that the hybrid battery-tank storage system is the most reliable, followed by battery-only storage, while tank-only storage, despite its lower initial cost, poses scalability and maintenance challenges. The LCC over a 25-year project lifetime is £31 k for battery-tank, £26 k for battery-only, and £23.3 k for tank-only systems. Despite the lower cost of tank storage, its complexity and maintenance make it the least preferred option for large-scale systems.

Green stock investment preferences among adult investors in east Malaysia

Abstract In light of increasing concerns about environmental issues and a heightened focus on green stocks prompted by global warming and the COVID-19 pandemic, this research study aims to analyse the determinants influencing the investment intentions of working adults in Sarawak, Malaysia, regarding green stocks. This study emphasises comprehending how factors such as attitudes, social influences, affect, and perceived customer effectiveness impact the investment intentions of working adults in green stocks. This research adopts a quantitative methodology, employing hypothesis testing to analyse data obtained from 150 respondents in East Malaysia, who were selected using a convenience sampling technique and responded through a Google Form. Data analysis was conducted using SPSS version 27, with a comprehensive assessment of variable validity and reliability through various tests. Six hypotheses were formulated to establish a significant correlation between the dependent variable intention to invest in green stocks and the independent variables’ social factors, attitude, affect, perceived customer effectiveness, and financial literacy. Four independent variables significantly influence the dependent variable when investing in green stocks. Further, perceived customer effectiveness directly impacts investors’ intentions. Thus, financial literacy indirectly influences the intention to invest in green stocks through its mediation with attitude. The findings result in practical implications related to the determinants of green stock investment intention among working-age adults in Sarawak. To begin with, this study contributes to the body of knowledge concerning green investments by investigating the factors influencing the Sarawak residents’ intention to invest in green stocks, utilising the theory of interpersonal behaviour. Previous research has predominantly relied on the theory of reasoned action and the “theory of planned behaviour” to elucidate the factors impacting green investment intention. Therefore, this study’s adoption of the theory of interpersonal behaviour offers a special perspective and potential reference for future researchers. The knowledge gained from this study is pertinent to a broad spectrum of stakeholders, encompassing policymakers, government, professionals, and educators. It offers valuable insights that can shape decision-making and the development of strategic initiatives within green investments.

Performance-based target reliability analysis of offshore wind turbine mooring lines subjected to the wind and wave

Reliability assessment is a crucial aspect of the design and operation of structures, particularly in balancing safety and cost considerations. This paper introduces a novel method for evaluating the performance-based target reliability of floating wind turbine platforms in offshore environments. The method focuses on the platform's motion modes and wave frequencies, which significantly influence the system's structural integrity and performance. An improved limit state function is proposed to enhance the accuracy of reliability calculations, specifically for steady-state conditions. The platform's six degrees of freedom motions are carefully analyzed to investigate their dependence on wave frequencies. By considering the time response of these motions and accounting for uncertainties in wave characteristics, wave impact directions, and wind effects, a comprehensive reliability analysis is conducted to assess the stability modes of the platform. This paper introduces the term 'Reliability Performance-Based' (RPB) analysis as a new concept to evaluate the system's reliability at a given performance level. Furthermore, an optimal target reliability index is defined to address the economic aspect of the design process. The proposed methodology's PEB analysis focuses on capturing uncertainties in wave characteristics and wind effects on floating wind turbine platforms. This includes a detailed examination of wave and wind-induced loads and their propagation through the system concerning its performance level. Statistical models were integrated to quantify these uncertainties, applying Monte Carlo simulations to assess their effects on the platform's reliability. This approach allows for a nuanced understanding of the interactions between environmental factors and structural responses, enhancing the precision of our reliability assessments. It enables the consideration of economic efficiency alongside safety, ensuring a balanced approach to the design and operation of the floating wind turbine platform. By providing a comprehensive reliability assessment framework, it aids in the optimization of design and decision-making processes for floating wind turbine platforms.

Comprehensive assessment of buildings, structures and technical devices reliability of mining enterprises

Comprehensive assessment of buildings, structures and technical devices reliability of mining enterprises

The potential of Blockchain in improving the security of Websites

With digital transformation and the rise of cyber threats, website security has become a vital part of the Internet. Websites contain a large amount of sensitive information, such as user personal data, financial information and trade secrets. Criminals are constantly looking for vulnerabilities to attack and steal data, which can lead to serious consequences for users and website owners. This study provides an extensive analysis and comparative study of the effectiveness of blockchain technology compared to traditional website security methods. The main focus of the study is on evaluating key parameters such as decision accuracy, query processing speed, and overall system reliability. During the study, the influence of the number of blocks in the blockchain chain and the quality of encryption on the accuracy of decision-making was revealed. The ability of the system to effectively contain potential threats was analyzed. The speed of processing requests was evaluated taking into account the possible impact of increasing the number of blocks and the complexity of encryption on system performance. A comprehensive formula for assessing the overall reliability of the system has been developed, which combines the positive and negative aspects of blockchain technologies. The obtained results indicate that by integrating factors of accuracy and speed of processing into a comprehensive assessment of system reliability, the use of blockchain allows to increase the overall reliability of the website protection system.

Comprehensive Reliability Review and Assessment of Switched-Capacitor Step-Up DC–DC Converters

Comprehensive Reliability Review and Assessment of Switched-Capacitor Step-Up DC–DC Converters

A reliability assessment methodology of system-in-package based virtual qualification

System-in-Package (SiP) is a cutting-edge packaging technique that is flourishing in the semiconductor sector. Physical testing, which can be time-consuming and lead to design modification iterations delaying product release or delivery, has traditionally been used to assess the reliability of SiPs. Simulation methods that mimic physical tests can be used to shorten product development cycles, increase reliability, and lower development costs. This paper introduces a SiP reliability assessment methodology based on virtual qualification. A life prediction methodology of SiP based on physics-of-failure (PoF) is studied in conjunction with multi-source fusion life information of typical structures. Based on this, a comprehensive reliability assessment methodology of SiP is formed. The information input includes material types, structure size, and environmental load conditions. The finite element analysis (FEA) is used to analyze the typical structures. The life distribution of SiP components is obtained through the theory of the cumulative damage and competitive failure model. Through multi-source information fusion, the SiP comprehensive reliability assessment methodology is determined. Finally, a case study is done to determine the accuracy of the approach.

Development of new reliability metrics for microgrids: Integrating renewable energy sources and battery energy storage system

Microgrids (MGs) are gaining popularity due to their ability to provide reliable and resilient power supply, especially when integrated with renewable energy sources (RESs) and battery energy storage systems (BESS). Reliability is a critical factor for MG owners and policy makers. However, existing reliability indices such as loss of load expectation (LOLE) and expected energy not supplied (EENS) may not offer a comprehensive understanding of MG reliability and resiliency. To address this gap, this paper proposes three new indices for MGs to provide supplementary information on the performance of RESs: the Microgrid Resiliency Index (MRI), the Microgrid Renewable Energy Availability Index (MREAI), and the Microgrid Renewable Energy Energy Index (MREEI). The MRI assesses the MG’s ability to recover from interruptions, providing insights into its resiliency. The MREAI and MREEI offer additional information beyond LOLE and EENS, specifically highlighting the contribution of RESs to the availability and energy losses in the MG. These indices enable a more comprehensive assessment of MG reliability. The formulation for calculation of the indices are provided and applied to a MG with integrated solar photovoltaic (PV), wind turbine (WT), and BESS components. To evaluate the effectiveness of the proposed indices in providing supplementary information on resiliency and the contribution of RESs, various scenarios are examined. These scenarios include the impact of using BESS, changes in RES availability, and variations in RES output. The results demonstrate that the proposed indices effectively capture the contribution of RES to MG reliability and offer valuable insights for decision-making related to RES installation. Also, by integrating BESS, the contribution of RESs to outage hours and lost energy is effectively decreased from 89.41% and 87.41% to 32.69% and 28.94% respectively. Additionally, results highlight the substantial enhancement in the resiliency of the MG, which witnessed an impressive 68.43% improvement.

Reconstruction of eigenstrains and residual stresses in thin plates from modal sensitivity analysis

ABSTRACT Non-destructive evaluation of the spatially resolved residual stresses from limited measurement data is crucial for a comprehensive assessment of structural integrity and performance reliability of engineering components. Generally, residual stresses are caused by incompatible internal eigenstrains and along this line, a novel sensitivity-based eigenstrain reconstruction approach is developed in this work for residual stress identification in thin plates using vibrational modal data. There are two key ingredients in establishing the proposed approach. At first, residual stresses are parameterised through direct eigenstrain analysis and thereafter, residual stress reconstruction is recast as a parameter identification problem whose goal function is just the least-squares of the misfit between the measured and calculated data. Second, to minimise the nonlinear least-squares goal function, the modal sensitivity analysis is called to linearise the misfit and the trust-region constraint is invoked in conjunction with the Tikhonov regularisation to enhance the convergence. Numerical examples are investigated to verify the robustness, accuracy and efficiency of the proposed approach.

Comprehensive Reliability Assessment Method for Lithium Battery Energy Storage Systems

Electrochemical energy storage systems have the advantages of fast power response, intensive energy storage, flexible and convenient deployment, but the output characteristics of the battery system directly affect the service effect of the energy storage power plant. Therefore, it is quite necessary to analyze the reliability of battery energy storage and scientifically assess the system’s performance. This paper considers the aging state of the battery storage system as well as sudden failures and establishes a comprehensive reliability assessment method for battery energy storage systems that take into account the battery health index and the impact of thermal runaway failures, which makes up for the shortcomings of existing reliability assessment methods.

Reliability Assessment of Cyber–Physical Distribution Systems Considering Cyber Disturbances

With the development of communication technology, traditional distribution networks have gradually developed into cyber–physical systems (CPSs), from which the cyber system provides more protection for the grid and brings new security threat–cyber disturbances. Current research cannot scientifically measure the impact of cyber disturbances on the system and lacks reliability indices for a comprehensive quantitative assessment of CPS reliability from the perspective of cyber–physical fusion. If the impact of information disturbances on system reliability is not assessed accurately, it will not be possible to provide a scientific and reasonable decision basis for system planning and operation. Therefore, a set of reliability assessment methods and indices for distribution network CPSs considering cyber disturbances is proposed. Firstly, a reliability modeling method combining fault tree and Petri net is proposed to model the reliability of a distribution network CPS, which can improve the efficiency and accuracy of the modeling. Secondly, the system state is divided into two categories: normal operation state and cyberattack state. Then, generalized reliability indices considering cyber disturbances for distribution network CPSs are defined. Finally, through the tests on the modified IEEE RBTS BUS2 distribution network CPS, an analysis of the effects of information component failures, cyberattacks, and access network structures on system reliability is conducted in this paper to verify the efficiency of the proposed method and the rationality of the newly defined reliability indices.

Integration of multi-sensor MTInSAR and ground-based geomatic data for the analysis of non-linear displacements affecting the urban area of Chieuti, Italy

Slow instability phenomena can turn into rapid events, showing sudden accelerations and potentially developing in a threat for structures and people. In such scenarios, an in-depth understanding of the spatial and temporal evolution of the ground surface displacement field becomes essential for preventing potential catastrophes. In this work, Multi-Temporal Interferometry SAR (MTInSAR) technique based on COSMO-SkyMed and Sentinel-1 SAR acquisitions and ground measurements have been used to study an ongoing instability occurrence, affecting the urban area of Chieuti, a town located in the Southern Italy. Archives of C and X-band SAR data and geomatic monitoring observations spanning seven, five and one year, respectively, have been analyzed exploiting the complementary characteristics of these datasets. This enabled the accurate spatial-temporal characterization of the ground displacement field in the study area, the identification of sectors evidencing instability problems and a comprehensive reliability assessment of the detected displacements trends, characterized by strong non-linearities. Moreover, the multi-geometry DInSAR analysis allowed to evaluate the horizontal and vertical components of the detected motion, confirming the nature of the instability process, related to a deep landslide mechanism affecting the western slope of the town.

Test-retest reliability of modular-relevant analysis in brain functional network.

The human brain could be modeled as a complex network via functional magnetic resonance imaging (fMRI), and the architecture of these brain functional networks can be studied from multiple spatial scales with different graph theory tools. Detecting modules is an important mesoscale network measuring approach that has provided crucial insights for uncovering how brain organizes itself among different functional subsystems. Despite its successful application in a wide range of brain network studies, the lack of comprehensive reliability assessment prevents its potential extension to clinical trials. To fill this gap, this paper, using resting-state test-retest fMRI data, systematically explored the reliabilities of five popular network metrics derived from modular structure. Considering the repeatability of network partition depends heavily on network size and module detection algorithm, we constructed three types of brain functional networks for each subject by using a set of coarse-to-fine brain atlases and adopted four methods for single-subject module detection and twelve methods for group-level module detection. The results reported moderate-to-good reliability in modularity, intra- and inter-modular functional connectivities, within-modular degree and participation coefficient at both individual and group levels, indicating modular-relevant network metrics can provide robust evaluation results. Further analysis identified the significant influence of module detection algorithm and node definition approach on reliabilities of network partitions and its derived network analysis results. This paper provides important guidance for choosing reliable modular-relevant network metrics and analysis strategies in future studies.

A quantitative reliability assessment and risk quantification method for microgrids considering supply and demand uncertainties

Microgrids have received great interest in achieving high renewable energy penetration. However, intermittent renewable generation may cause reliability problem (i.e., power inadequacy), especially for islanded microgrids. A comprehensive quantitative reliability assessment of microgrids considering uncertainties is essential. Current uncertainty-based reliability assessment approaches usually consider the uncertainties on the supply side only or additionally consider the uncertainties on the demand side using a general distribution without considering the uncertainty characteristics of different demands. This may lead to unreliable assessment results. Besides, existing reliability performance indexes cannot measure the probability/risk of power inadequacy under uncertainties. In this study, a novel uncertainty-based reliability assessment approach is therefore developed for microgrids considering uncertainties at both supply and demand sides. A new reliability index is proposed and a risk quantification method is developed to measure the risk/probability of power inadequacy under uncertainties. The uncertainties at both supply and demand sides are detailedly quantified using a bottom-up approach. The proposed reliability assessment and risk quantification method are tested on an islanded hotel microgrid in Hong Kong. The results show that the proposed reliability assessment approach can provide more robust reliability assessment results while the conventional approach has a probability of 8% to underestimate the maximum outage power. The proposed risk quantification method can help to provide more comprehensive reliability assessment results under uncertainties. The risk quantification results indicate that the highest monthly power inadequacy risk of the hotel microgrid appears in August (i.e., 5.8%), while the highest hourly risk appears at 9:00 p.m. (i.e., 4.8%).

Development of a comprehensive system for assessing the reliability of thermal power equipment

The article reveals the necessity of monitoring the reliability of the electric power system as a complex technical system. Based on the consideration of the main regulatory documents, governing the assessment of the reliability of thermal power equipment and electrical networks, the article indicates the imperfections of the available methods of reliability assessment. A proposed comprehensive reliability assessment system allows a detailed assessment of the reliability of a complex system. The reliability of the power unit of the thermal power plant (TPP) was estimated by the logical-probabilistic method using the domestic software package. The existing problems of forecasting reliability indicators at various technical impacts are considered to obtain reliable calculation results.

On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach

Analyzing the reliability of autonomous ships has recently attracted attention mainly due to epistemic uncertainty (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended. While the reliability concept is touched upon well through the literature, the operational trustworthiness needs more elaboration to be established for system safety, especially within the maritime sector. Accordingly, in this paper, a probabilistic approach has been established to estimate the trusted operational time of the ship machinery system through different autonomy degrees. The uncertainty associated with ship operation has been quantified using Markov Chain Monte-Carlo simulation from likelihood function in Bayesian inference. To verify the developed framework, a practical example of a machinery plant used in typical short sea merchant ships is taken into account. This study can be exploited by asset managers to estimate the time in which the ship can be left unattended. Keywords: reliability estimation, Bayesian inference, autonomous ship, uncertainty.

A reliability-aware chance-constrained battery sizing method for island microgrid

Island Microgrids can coordinate local energy resources, provide post-fault reliability improvements for local customers, and aggregate local power and energy resources to offer services to the wider system. A crucial component of an Island Microgrid is the battery energy storage system, which can manage local imbalances, alleviate constraints, and improve reliability by enabling post-fault islanding. A planning and sizing method is required to quantify and maximize the benefits of battery energy storage while avoiding over-investment and under-utilization. This paper combines comprehensive reliability assessment with chance-constrained convex optimization, via second-order cone programming, to optimally size energy storage within an Island Microgrid. Chance constraints are applied to the battery state-of-charge to avoid sizing the energy storage to accommodate extreme cases of uncertainty, avoiding uneconomic investment. The probability of reaching a state-of-charge constraint also indicates the likelihood that the battery energy storage system will be unable to facilitate island operation in the event of an outage, which affects the Island Microgrid reliability. The method is demonstrated on a real Austrian distribution network as part of the MERLON project. Results illustrate that an optimal trade-off can be identified between system reliability and operating cost when the probability of violating the chance constraints is 4.8%.

Comprehensive assessment of reliability and validity for the clinical cases in simulated community pharmacy

Background: The objective structured clinical examination (OSCE) is used to measure the clinical competence of pharmacy students in a community pharmacy setup. However, the OSCE needs to be standardised to assess the clinical competence of the student accurately. Objectives: The present study was aimed to assess the reliability and validity of two clinical cases used in the simulated community pharmacy. Methods: OSCE simulation was performed by the students with two clinical cases in a simulated community pharmacy. The reliability was measured using Cronbach’s α and Mc Donald’s ω. Exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were used to measure the validity of the cases. Results: Among the two cases, the first case scenario was found to have a good model fit. However, the second case scenario has a poor model fit which was determined by the CFA. The inadequate sample size and factor loading in EFA were the main reasons for poor model fit in the second case scenario. Conclusion: The internal consistency, sample adequacy, factor loading, test for an exact fit, and fit measurements should be ensured for the clinical cases included in OSCE. This will help the academician to ensure the accurate assessment of the clinical competence of the student in a simulated community pharmacy.

STUDI PENILAIAN KEANDALAN BANGUNAN GEDUNG

Building reliability is the ability of a building to carry out its functions according to plan. But in reality there are cases where buildings are not reliable. Therefore it is necessary to assess the reliability of the building in order to know the value of the reliability of a building so that it can be concluded whether the building is still functional or not. So a study was conducted on the assessment of the reliability of buildings that cover 5 aspects of the building, namely aspects of architecture, structure, utilities, accessibility, and building and environmental layout. The assessment will be carried out according to the existing function weights for the five aspects of the assessment. Evaluation is broadly carried out using visual observation methods and specifically for the aspect of utility the document study method is used as an additional. Can be known reliability in each aspect with the existing reliability classification. After evaluating each aspect, a comprehensive reliability assessment will be carried out with the weight of existing functions and can be known whether the building is reliable, less reliable, or unreliable through the existing reliability classifications and it can be seen whether the building is still in a worthy condition or not.