Calculation Of Reliability Indices Research Articles

Enhancing reliability assessment in distributed generation networks: Incorporating dynamic correlation of wind-solar power output uncertainty

Amidst escalating environmental concerns and energy scarcity, the integration of distributed generation (DG) within distribution networks (DN) has emerged as a pivotal developmental trend. The uncertainty inherent in renewable energy output often disrupts DG networks. Notably, the dynamic correlation between key renewable sources, such as wind and solar energy, significantly influences the reliability analysis of these networks.To comprehensively assess the impact of wind-solar power output uncertainty and its dynamic correlation on DN reliability, this study leverages copula theory to express the dynamic correlation coefficient between wind and solar power. This coefficient is formulated as the dynamic correlation of wind-solar power through copula dynamic correlation coefficient. Employing an auto-regressive moving average (ARMA) model with constraints solved using maximum likelihood kernel (MLK), we construct the wind-solar joint output (WSJO) model. Subsequently, utilizing sequential Monte Carlo simulation (MCS) with the WSJO model, we analyze DN reliability. In case of DN failure, the WSJO model generates random samples of the wind-solar joint output sequence. Subsequent power restoration to governed islands enables the calculation of DN reliability indices. The WSJO model constructed in this study accounts for wind resource output uncertainty and dynamic correlation, aligning more closely with actual distributed generation output and enhancing the accuracy of reliability assessment. Finally, we simulate the improved IEEE-RBTS-BUS6-F4 system to underscore the crucial role of considering wind-solar energy's dynamic correlation in DN reliability assessment.

Reliability Evaluation of Distribution Networks Considering Natural Gas Network Integration

Abstract With the transformation of energy structure, the distribution network in the form of multi-energy interconnection is gradually emphasized. The access of gas turbines to the distribution network puts high requirements on the reliability assessment of the distribution network counting and natural gas network access. Models of distribution network components and natural gas network equipment are established. Based on the traditional sequential MC reliability assessment, the calculation of reliability indexes for the distribution network with gas turbine access is accomplished by identifying the islanded areas under fault conditions and judging the gas turbine output state, taking into account the energy flow constraints. The results of the calculations show that the reliability of the distribution network with natural gas network access is improved, and the reliability of the load nodes near the gas turbine is improved significantly.

Assessment of Organizational and Technological Reliability Monolithic Works

Every year in the construction process new technologies are introduced, the use of new building materials increases, a large number of contractors are involved, with a significant increase in the scale of construction and the need to ensure the reliability of construction. There arises a necessity to forecast and correct activities of construction organizations, to give adequate assessments of the adopted organizational and technological solutions (OTS), which, asa rule, leads to a decrease in the prescriptive term of construction. Monolithic structure construction process design is closely connected with the necessity of clear and correct choice of the necessary organizational-technological solutions. Depending on the made decisions it is possible to estimate the reliability of monolithic works. This in its turn gives the possibility to forecast the terms of production, the cost of monolithic works on the stage of design of dwelling buildings and industrial objects directly. The article offers a methodology for calculating the evaluation of organizational and technical reliability of the process of monolithic structures. For the successful performance of monolithic works it is necessary to ensure the reliable functioning of all participants of the process from designers to construction teams. The article presents the calculation of organizational and technological reliability index (OTR) of monolithic works. To calculate the index the author proposed a model and introduced the concept of reliability of the considered process of monolithic works as a probability of achieving the final goal. At the same time, the process of monolithic works performance both for residential and civil objects is taken as a complex stochastic system, which includes a set of co-dependent relations. The application of the assumed approach for the calculation of organizational and technological reliability of monolithic works with small changes, refinements can be applied to the calculation of other works in the construction of buildings and structures throughout the life cycle of construction. At the same time, this methodology makes it possible to obtain a numerical value of reliability assessment, which is very relevant when choosing organizational and technological solutions.

Analysis of reliability of a prefabricated conductive rail joint in context of heavy traffic

In this paper, the calculation of reliability indicators has been carried out in the article for two configurations of a prefabricated conductive rail joint: with fish plates, a welded and bypass connector, and a spring rail bond. The sections of the track where the probability of failure of the prefabricated conductive rail joint is increasing are identified. The destabilizing factors influencing the onset of failure of a prefabricated conductive rail joint earlier than the calculated values of the durability indicators are considered. A model for evaluating the reliability of the second configuration of a prefabricated conductive rail joint based on the Markov analytical model has been developed, and such reliability indicators have been calculated as the probability of its being in working condition, as well as the probability of failure of the prefabricated conductive rail joint due to the inoperability of the fish plates and the spring rail bond. The features of the configuration of a prefabricated conductive rail joint with a spring rail bond are taken into account, which consist in the fact that in order to eliminate the failure due to the inoperability of the spring rail bond, it is necessary to remove the fish plates.

Reliability across content areas in progress tests assessing medical knowledge: a Brazilian cross-sectional study with implications for medical education assessments.

Brazilian medical schools equitably divide their medical education assessments into five content areas: internal medicine, surgery, pediatrics, obstetrics and gynecology, and public health. However, this division does not follow international patterns and may threaten the examinations' reliability and validity. To assess the reliability indices of the content areas of serial, cross-institutional progress test examinations. This was an analytical, observational, and cross-sectional study conducted at nine public medical schools (mainly from the state of São Paulo) with progress test examinations conducted between 2017 and 2023. The examinations covered the areas of basic sciences, internal medicine, surgery, pediatrics, obstetrics and gynecology, and public health. We calculated reliability indices using Cronbach's α, which indicates the internal consistency of a test. We used simple linear regressions to analyze temporal trends. The results showed that the Cronbach's α for basic sciences and internal medicine presented lower values, whereas gynecology, obstetrics, and public health presented higher values. After changes in the number of items and the exclusion of basic sciences as a separate content area, internal medicine ranked highest in 2023. Individually, all content areas except pediatrics remained stable over time. Maintaining an equitable division in assessment content may lead to suboptimal results in terms of assessment reliability, especially for internal medicine. Therefore, content sampling of medical knowledge for general assessments should be reappraised.

Axial compression behavior of square section concrete-filled steel tubes reinforced with internal latticed steel angles

The axial compression behavior of square CFSTs (concrete-filled steel tubes) reinforced with internal latticed steel angles was investigated in this study, and the test results including load-displacement and load-strain behavior, failure modes, and ultimate load were obtained. The experimental results demonstrated that the steel angles exerted an additional confining effect on the enclosed concrete, and altered the stress distributions of the adjacent concrete. The corresponding finite element model was established subsequent to the experiment, and the analysis and discussion of the axial compression mechanisms was conducted. The parametric analysis was performed to evaluate the influence of main parameters on the load-displacement behavior, and the analysis results revealed that the concrete made the highest contribution to the ultimate load. Additionally, the formulas for calculating the ultimate load were proposed according to the superposition method, and the calculation results demonstrated that the design formula derives from the unified theory of CFSTs exhibit enhanced accuracy and reduced deviation. Finally, a reliability analysis was conducted to evaluate the feasibility of the proposed design formula, and the analysis results indicated the calculated reliability index decreases with an increase in the steel ratio, and for specimens with a higher steel ratio, a lower yield strength of steel tube leads to a lower reliability index.

A non-probabilistic reliability analysis method with the fuzzy failure criterion

In engineering practice, the failure boundary of structures is not usually distinct due to some ambiguous information, which brings a tricky challenge to reliability assessment. The fuzzy theory is introduced to solve it with the traditional probability assessment method. For the non-probabilistic reliability system, however, this problem tends to be at a dead end because it lacks some necessary probability information. In this study, the non-probabilistic reliability model with fuzzy failure criterion is established, which involves two different evaluation indices in terms of the limit state surface. Based on this, a corresponding calculation method is proposed to deal with it, and the interval model and the ellipsoid model are shown for instance. In addition, the HRHL-RF method owning strong robustness is utilized to calculate the index of the ellipsoid model. Eventually, an established algorithm frame can achieve the calculation of the unified fuzzy reliability index, and three examples with the classical fuzzy membership functions are computed to show its feasibility and efficiency.

Influence of data sampling on confidence in the calculation of reliability index for simple performance functions

The mean (point) estimate of reliability index (β) for simple limit state performance functions is most often based on load and resistance model bias statistics taken from bias data of limited size. The paper shows how the confidence in the point estimate of β can be computed using the bootstrap method and a closed-form solution for the special case of lognormally distributed nominal and bias random variables. Bias data collected for the pullout limit state for steel strip mechanically stabilized earth walls are used to demonstrate the approach but the method is general. Mean and confidence intervals on β are computed using the entire available bias data sets and smaller sample sizes located in the tails of the original populations, or smaller sample sizes that result in upper and lower extreme point estimates of β. The closed-form solution for β varies linearly with the logarithm of the nominal factor of safety for the example pullout limit state. Depending on the load and resistance bias sample sizes and where they are taken from in the original larger population, results in a wide range of nominal factors of safety to satisfy a target β at time of design.

Quantification of the reliability of concrete slabs subjected to natural fires designed using tabulated values according to Eurocodes

PurposeThe design check regarding the fire resistance of concrete slabs can be easily performed using tabulated values. These tables are based on experimental results, but the level of safety, which is obtained by this approach, is not known. On the other hand, performance-based methods are more accepted, but require a target reliability as performance criterion. Hence, there is a need for calibration of the performance-based methods using the results of the “traditional” descriptive approach.Design/methodology/approachThe calibration is performed for a single span concrete slab, where the axis distance of the reinforcement is chosen according to Eurocode 2 for a defined fire rating. A “standard” compartment is selected to cover typical fields of application. The opening factor is considered as parameter to obtain the maximum peak temperatures in the compartment. A Monte Carlo simulation, in combination with a response surface method, is set up to calculate the probabilities of failure.FindingsThe results indicate that the calculated reliability index for a standard is within the range, which has been used for the derivation of safety and combination factors in the Eurocodes. It can be observed that members designed for a fire rating R90 have a significant increase in the structural safety for natural fires compared to a design for a fire rating R30.Originality/valueThe level of safety, which is obtained by a design based on tabulated values, is quantified for concrete slabs. The results are a necessary input for the calibration of performance-based methods and could stimulate discussions among scientists and building authorities.

Reliability-constrained planning of community integrated energy systems based on fault incidence matrix

Reliability is a prerequisite for community integrated energy systems to provide consumers with uninterrupted high-quality energy supply. However, it is still challenging to consider reliability in the planning of community integrated energy systems due to the complexity of energy conversion relationships. Conventional reliability-constrained planning methods usually form a bi-level optimization problem in which the planning scheme optimization and reliability index calculation are separated into two subproblems. In this paper, a novel reliability-constrained planning method for community integrated energy systems is proposed. First, the fault incidence matrices are employed to construct the analytic reliability evaluation model of community integrated energy system. Then, the reliability evaluation model is linearized and explicitly integrated into the planning model, forming a mixed-integer linear programming model. This model can be efficiently solved by mathematical optimization algorithms while effectively balancing the operation cost and reliability at the planning stage. Case studies are conducted based on a practical community integrated energy system in North China to verify the effectiveness of the proposed method.

Finite element-based probabilistic framework including Bayesian inference for predicting displacements due to tunnel excavation

Excessive settlements due to tunnel excavation in urban sites may affect the stability of sensitive buildings, and additional design costs are needed to prevent these effects. In this article, a finite element-based probabilistic framework is presented and applied to a real-world case study to estimate tunnel-induced settlements. This probabilistic analysis framework consists of the following four fundamental elements: a sensitivity analysis to identify key parameters, an a priori reliability analysis using metamodels to calculate reliability indices and probabilities of failure, field monitoring results (e.g., settlements) and a Bayesian inverse analysis using the field measurements to update the probabilities of failure a posteriori. This framework is materialized through the linking of ZSOIL, a non-linear finite element soil–structure interaction software, and UQLab, a MATLAB®-based uncertainty quantification toolbox. With the application of this framework to a real-world case study in the Grand Paris Express project, key geotechnical parameters can be identified, reliability indices and probabilities of failure can be computed using metamodelling-powered Monte Carlo (MCS) and adaptive kriging Monte Carlo simulations (AKMCS). Finally, using Bayesian inverse analyses to update prior knowledge and refine posterior prediction, the probability that the settlements exceed acceptable values can be reduced, potentially leading to design cost savings.

Надійність і безпека стартових комплексів ракет-носіїв

This paper is concerned with the reliability and safety of launch complexes. The problems to be solved in launch complex reliability evaluation are identified: calculations of the probability of no-failure operation of passive redundancy systems with equal- and nonequal-reliability elements, reliability analysis for replacement redundancy with integer multiplicity and unloaded reserve; calculations of the probability of no-failure operation of the launch complex components in launch preparation, and calculations of the reliability indices of a component part as a whole and a comparison of the calculated reliability indices with the specification requirements. Since a launch complex consists both of renewable elements and of nonrenewable ones, the reliability indices must be calculated so that one may evaluate the reliability both of individual elements and of a system of different-type elements as a whole. These indices are characterized by the nonfailure operation time and recovery time distributions and show the probability of а serviceable state or a failure state of an element and a system. On condition that the nonfailure operation time and the recovery time can be described by the Weibull distribution, expressions are obtained for the availability factor, i.e., the probability of the launch complex being operative at an arbitrary time, except for scheduled periods during which the launch complex is not envisaged for use. Launch complex safety is evaluated by the probability of hazards, the identification of main ways to mitigate their consequences, and account for weight of the consequences of possible hazards in service. Launch complex safety indices are identified. It is shown that safety must be evaluated using indices suitable for the practical solution of problems of the justification and assurance of specified safety requirements against possible threats in the development of launch complexes. The adopted safety index is the probability that each hazard that occurs in a certain time will be eliminated. A renewal process is used to describe a random number of hazard occurrences. To determine the hazard frequency, it is recommended to use statistical data on launch complex accident rate and reliability, logical methods of event tree and fault tree analysis, accident simulation models, and expert judgments.

Comparing the construct validity of the Patient Health Questionnaire (PHQ-9) and the Major Depression Inventory (MDI) using Rasch analysis

ObjectiveThe Patient Health Questionnaire (PHQ-9) and the Major Depression Inventory (MDI) are psychometric instruments frequently used for depression diagnosis and monitoring in primary care settings. The goal of this study was to assess and compare the construct validity of the PHQ-9 and the MDI using Rasch analysis. MethodsThe PHQ-9 and the MDI were distributed in random ordering (first or last) to a waiting room sample of Danish primary care patients. Analysis of fit to the Rasch model, ordering of response categories, dimensionality-testing, test for differential item functioning, test for local dependency, and calculation of reliability indices were used to evaluate the psychometric characteristics of the instruments. ResultsA sample of 281 persons (18–87 years, 72 % females) responded to both instruments. Reliability was acceptable for PHQ-9 (PSI 0.80) and excellent for MDI (PSI 0.88). Both instruments demonstrated fit to the Rasch model after rescoring of all items. Dimensionality testing supports that both instruments are unidimensional. Indication of local dependency was observed for PHQ-9 item 2&6 and MDI item 1&4. No indication of differential item functioning regarding age, gender or ordering of instruments was found. ConclusionThe PHQ-9 and the MDI both demonstrate measurement problems. Modifying individual items and reducing the number of response categories in both instruments could potentially improve their measurement capabilities. Study findings do not provide a conclusive indication of which instrument has superior operating characteristics.

Expert Validation of a Python Test, Reliability, Difficulty and Discrimination Indices

In recent years, different countries have implemented the teaching of computer programming from the first grade in schools, with the aim of incorporating computational thinking as a new way of thinking that is a necessary skill for scientific and technological development, a fundamental axis for development in the 21st century. Recent reviews of the state of the art have shown that this task is only being carried out by countries that have given space to technology and science, incorporating it at the elementary school level. However, developing countries do not yet consider the significance of the issue, so to date they have not taken the necessary steps in this direction. In addition, learning computer programming is fundamental for countries to join technological development, so that they can be creators of technology and not just users of it. The problem is that there is no didactic development for the teaching of programming, nor validated evaluation instruments to quantify the learning of computer programming. The objective of this research is to validate a programming test that evaluates technical skills in the Python programming language. The instrument proposed to be validated is a 90-item test, which after validation by experts was reduced to 70 items, and after the psychometric analysis that considered the calculation of reliability, difficulty and discrimination indexes, resulted in the proposed 45-item instrument, as a standard instrument for the evaluation of learning in the Python programming language. It should be noted that the validation methodology was carried out using the classical theory of psychometric analysis.

A Branch-independence-based Reliability Assessment Approach for Transmission Systems

This paper proposes a branch-independence-based reliability assessment approach for transmission systems. The approach consists of branch decoupling and state-space partition techniques. By integrating an impact-increment-based reliability index calculation model and the proposed branch decoupling technique, a proportion of sampled contingency states no longer need to be analyzed using the time-consuming optimal power flow (OPF) algorithm. In this way, the technique speeds up the calculation of reliability indices. Since first-order contingency states have a high probability of being sampled, we propose a state-space partition technique to replace first-order contingency state simulation with first-order contingency state enumeration. Consequently, the calculation of reliability indices is further accelerated by avoiding a large amount of repetitive OPF analyses during simulation process without affecting reliability index accuracy. The validity and applicability of our approach are verified using the IEEE 118-bus and IEEE 145-bus systems. Numerical results indicate that the proposed approach can improve computational efficiency without decreasing accuracy.

Finding design point base on a quasi-importance sampling method in structural reliability analysis

Calculation of reliability index is still a significant challenge in reliability problems. The Monte Carlo simulation technique is beneficial for calculating failure probability, but given the need to generate many random samples, it has a high computational cost. Additionally, it cannot calculate the design point, while it can be important to determine the design point in large-scale practical problems.This paper develops an algorithm for calculating the design point using the modified importance-sampling method. In the proposed method, the standard deviation (SD) of sampling density-function is improved in each step. This enables the proposed algorithm to calculate the reliability index and design point using a small number of random samples. The examples are presented in this paper indicate the high efficiency of the proposed algorithm to calculate the reliability index and design point, even for nonlinear problems with correlated random variables.

Structural Reliability Analysis and Reliability Index Calculation Method Based on Measurement Uncertainty

Structural reliability is a probabilistic measure of structural reliability. Reliability indicators can be calculated from the average and standard deviation. The standard deviation only reflects the degree of dispersion of the series of measured values such as structural resistance and load effects. However, the acquisition of measurement values is related to the measurement objects, instruments, methods, conditions, and measurement personnel. It is difficult to reflect the impact of these five aspects on the measurement values of structural resistance and load effects using standard deviation. Based on this, this article deeply analyzes the measurement uncertainty evaluation theory and method and proposes to use the synthetic standard uncertainty instead of the standard deviation to calculate the standard value of the structural resistance and load effect. This article establishes the structural performance function, structural reliability calculation formula, the reliable index calculation formula, the calculation formula of variation coefficient and the calculation formula of the safety factor based on the measurement uncertainty. The conclusion of this article provides a new application approach for China national standard “Measurement Uncertainty Evaluation and Representation” and also builds a new bridge for the measurement uncertainty evaluation theory to enter the field of structural reliability analysis.

Seismic Performance-Based Evaluation of Cold-Rolled Steel Structures

Today, lighter buildings with a smaller share of seismic force are needed in the construction industry. Given the attractiveness of this construction method for researchers, it led them to conduct more and more accurate experiments to better understand these structures and, in particular, to study the lateral behavior of these structures. The aim of this study has been to calculate reliability index and probability of failure. In addition to this sources of uncertainty in structural system of cold-formed frames with sharp bracing have been ranked by application of reliability analysis method. To do this, considering sources of seismic and structural uncertainty such as spectral acceleration, live load, cross-sectional dimension, and modulus elasticity of steel has been selected. Then reliability analysis methods, FOSM and FORM, have been utilized to estimate the probability of failure based on limit-state function which is defined as relative displacement of floor to allowed limit. Results show that failure probability following a decreasing trend up to two story-floor frames increased up to five-floor frames. As a result of the analysis, it was found that, in the FOSM method, the reliability index increases with increasing floors in cold-rolled steel structures. In the FORM method, by increasing the floors up to the two-story frame, the reliability index has an ascending trend and up to the five-story frame has a descending trend with a very gentle slope. By increasing the distance, the value of the FOSM method reliability index is different from the value of this index in the FORM method to the extent that, in the Type 5 framework, this difference reaches five units. The probabilities of failure in one-story and three-story frames are the highest and the lowest, respectively. Uncertainty in the load applied to the structure was identified as the most important parameter. The uncertainty in the geometry of the members decreases with the increase of classes.

Reliability evaluation of community integrated energy systems based on fault incidence matrix

• An analytical reliability evaluation method for CIESs based on fault incidence matrix (FIM) is proposed. • The energy-bus-based unified reliability evaluation model of CIESs is presented to describe the energy flows of the system in a unified matrix form. • The case study is performed based on a practical CIES to demonstrate the advantages of the FIMs in reliability index calculation and vulnerability identification. Reliability evaluation is essential for the planning, operation, and analysis of community integrated energy systems (CIESs). However, it is still challenging to quantify the reliability of CIESs accurately and efficiently because of the diverse energy characteristics and energy conversion relationships. In this paper, a reliability evaluation method for CIESs based on fault incidence matrix (FIM) is proposed to analytically demonstrate the impact of equipment failures on system energy supply. The energy-bus-based unified reliability evaluation model of CIESs is presented to describe the energy flows of the system in a unified matrix form. Three types of FIMs are constructed to reveal the different consequences of device failures on energy supply. The reliability indices of a CIES can be directly calculated through simple algebraic and Boolean operations based on the FIMs, improving the calculation efficiency significantly. The FIMs make it easy to identify the vulnerability segments of the system, which is desirable in the practice of device maintenance or upgrade to improve the reliability of the CIES. Case studies are conducted on a typical CIES to verify the effectiveness and feasibility of the proposed method.

Multistate Reliability Analysis of Recessive Fault of Mechanical Meta-Action Unit Based on Markov Process

In order to clearly express the reliability dynamic change process of mechanical meta-action units with recessive fault on continuous time series, this paper proposes a reliability analysis method for multistate systems with recessive failures of mechanical meta-action units based on the fusion of vibration signal analysis and Markov process. By analyzing the vibration signal, five major recessive fault types of mechanical meta-action units are determined. By analyzing the experimental data and based on the average time of the first occurrence of five major recessive faults, a performance level state representation model of mechanical meta-action unit based on fault importance weight is established. Then, based on the repairable characteristics of the mechanical element action unit, the two-way state transition model and state probability differential equation of mechanical meta-action units are established, and the state probability of each state is obtained. Next, under the condition of determining the initial state, the change process curves of the instantaneous availability, instantaneous average performance, and instantaneous average performance deficit of the mechanical meta-action unit are obtained by solving the reliability index calculation formula. Finally, this paper takes the worm rotation meta-action unit as an example to verify the law and probability of the state transition of the mechanical meta-action unit, and the performance level change accompanying the state transition process, by analyzing the failure modes and causes of recessive faults, the corresponding reliability control measures are formulated, and the control effects before and after reliability control are analyzed. The research results show that this method can effectively improve the accuracy of the state probability when calculating the state probability of each state, and compared with the discrete Markov model, when studying the reliability of complex multistate systems, this method can dynamically describe the change process of state probability, instantaneous availability, instantaneous average performance, and instantaneous average performance deficit in real time under the condition of continuous time-dependent variables. It has certain guiding significance for the reliability analysis of mechanical element action units in the long-term range.