Calculation Of Reliability Indices Research Articles

Reliability Analysis of Magnetic Resonance Imaging Equipment Based on Non-homogeneous Poisson Process

In order to evaluate the quality of different brands of magnetic resonance imaging system, optimize the quality of equipment repair and maintenance, and ensure the quality and safety of the equipment in clinical use. Meanwhile build the reliability evaluation model of magnetic resonance imaging equipment based on the large failure data collected by magnetic resonance repair system. In this paper, using the fault data of a certain brand of magnetic resonance in the past two years, applying the statistical judgment criterion, selecting the appropriate statistical distribution model, and finally fitting the equipment reliability evaluation model based on the non-homogeneous Poisson process, and then obtaining the magnetic resonance imaging equipment. Reliability evaluation indicators such as cumulative fault strength function, magnetic resonance imaging equipment fault density function, and mean time between failures. According to the calculated reliability index, on the one hand, it can evaluate the system reliability quality of a certain brand of magnetic resonance imaging equipment, and then evaluate the quality of different brands of magnetic resonance imaging equipment, on the other hand, it can help hospital equipment managers to carry out operational optimization, maintenance strategy development and safety management of magnetic resonance imaging equipment.

A GIS tool for infinite slope stability analysis (GIS-TISSA)

Landslides are one of the most common and a destructive natural hazard in mountainous terrain and thus evaluating their potential locations and the conditions under which they may occur is crucial for their hazard assessment. Shallow landslide occurrence in soil and regolith covered slopes are often modeled using the infinite slope model, which characterizes the slope stability in terms of a factor of safety (FS) value. Different approaches have been followed to also assess and propagate uncertainty through such models. Haneberg (2004) introduced the use of the First Order Second Moment (FOSM) method to propagate input uncertainty through the infinite slope model, further developing the model and implementing it in the PISA-m software package (Haneberg, 2007). Here we present an ArcPy implementation of PISA-m algorithms, which can be run from ESRI ArcMap in an entirely consistent georeferenced framework, and which we call “GIS Tool for Infinite Slope Stability Analysis” (GIS-TISSA). Users can select between different input options, e.g., following a similar input style as for PISA-m, i.e., using an ASCII.csv parameters input file, or providing each input parameter as a raster or constant value, through the program graphic user interface. Analysis outputs can include FS mean and standard deviation estimates, the probability of failure (FS < 1), and a reliability index (RI) calculation for FS. Following the same seismic analysis approach as in PISA-m, the Newmark acceleration can also be done, for which raster files of the mean, standard deviation, probability of exceedance, and RI are also generated. Verification of the code is done by replicating the results obtained with the PISA-m code for different input options, within a 10−5 relative error. Monte Carlo modeling is also applied to validate GIS-TISSA outputs, showing a good overall correspondence. A case study was performed for Kannur district, Kerala, India, where an extensive landslide database for the year 2018 was available. 81.19% of the actual landslides fell in zones identified by the model as unstable. GIS-TISSA provides a user-friendly interface, particularly for those users familiar with ESRI ArcMap, that is fully embedded in a GIS framework and which can then be used for further analysis without having to change software platforms and do data conversions. The ArcPy toolbox is provided as a .pyt file as an appendix as well as hosted at the weblink: https://pages.mtu.edu/~toommen/GeoHazard.html.

Analysis of the Steel Structural Reliability under the Big Data

In this paper, the reliability of steel roof under the big data loads is analyzed. Firstly, the roof of steel structure is shown. The relationship between roof span and stress composed of hollow steel joist beam is obtained, and the parameters of the structure of the open web steel joists that is made by the wide flange steel is given. Secondly, according to the random distribution parameters of steel roof and the big data loads, the limit state function of steel roof structural calculation is given. The function is an implicit function. Monte Carlo method is used to calculate reliability index of the steel structural roof with considering the dead loads and the big data loads. Finally, the reasonable suggestions for the reliability and safe operation of the steel structural roof are given from the reliability of the calculated of the steel structural roof.

Safety Effects of Horizontal Curve Reliability Index

Recent advancements in analytical processes have used probabilistic approaches to examine the efficacy of the point mass model (and other Green Book models) to develop reliability-based approaches for geometric design. However, there has been minimal research establishing the link between reliability measures and substantive safety (expressed through crash frequency). The objective of this paper is to use empirical data supporting the calculation of reliability index for existing horizontal curves and to estimate the relationship between reliability index and crash frequency. Other horizontal curve-related characteristics that may have an impact on crash frequency on horizontal curves for rural two-lane highways and rural freeway facilities are controlled for in the evaluation. The safety analysis showed that the wet pavement reliability index was significantly associated with crash frequency for total curve-related crashes, single-vehicle run-off-road crashes, rollover crashes, truck-related crashes, and weather-related crashes. The relationship was strongest for the reliability index in its continuous form, meaning that the effect is continuous across the range of wet pavement reliability that was observed.

Probabilistic evaluation of distribution power transformers reliability indices considering load transfers and mobile unit substations

This paper proposes a new and practical probabilistic method for calculating reliability indices and costs associated with distribution substations that share spare transformers of a same group. Based on Monte Carlo simulation, the proposed algorithm considers the chronological representation of failure occurrences, and enhances previous methods by modeling emergency actions, such as transferring load to neighboring feeders and connecting a mobile unit substation to ensure electricity supply to customers during the replacement of failed transformers. Thus, spare transformer requirements with new acquisitions to replenish the stock or even to expand the system are probabilistically assessed. All waiting times associated to these actions can be duly represented by any probability distribution, including the usual exponential model. A more accurate calculation of reliability indices and costs associated with the interruption of consumers is achieved. The corresponding computational algorithm is used in several numerical applications, considering a class of transformers of a Brazilian electricity utility. The results of these applications are deeply discussed to demonstrate the practical relevance of the proposed method.

Economical and Technical Assessment of Hybrid Renewable Energy Systems for Optimal Performance Applied in Hurghada, Egypt.

This paper deals with economic and technical evaluation of the hybrid power system which is fed six-megawatt load located in a city in Egypt called Hurghada. There is two types of economical evaluation. The first type is Economical evaluation which has two parts, the first part is cost estimation to know the price of generating power of the hybrid system in every season to reveal the lowest and the highest cost of the power unit in every season and The second part is an economic load dispatch for the six-megawatt load to know which hybrid system topology gives the required power at low cost and which topology gives the required power at a higher cost, economic load dispatch made for eight possible hybrid system topologies for four hybrid system units. The technical evaluation made by studying generating reliability indices Loss of Load Probability (LOLP), Loss of Load Expectation, (LOLE) Expected Energy Not Supplied (EENS) in every season of the year to know which season is more reliable to supply power to the load area. Studying generating reliability at the probabilities for generating units to achieve reliability index calculation according to the load duration curve of the load area in one year. The evaluation made by simulation of the hybrid system in MATLAB Simulink in every season and optimize power by using the Genetic Algorithm and Partial Swarm Optimization to ensure economical and technical optimal performance of the hybrid system.

Reliability Analysis of Distribution Network with Distributed Power Supply

In this paper, the reliability index calculation method of power equipment, load and system dispatching is studied. According to the location of the circuit breaker and disconnecting switch, the fault is partitioned, and the load reliability index is the same in each minimum distribution area, so that the reliability evaluation of the distribution network can improve the efficiency. On this basis, the partition coding table is also established, and the calculation of the minimum distribution area can be directly transformed into the calculation of the corresponding coding area. Combined with monte carlo method, the correctness of the method used in this paper is proved by comparing the example analysis with other literatures.

Calculation and analysis of bearing capacity reliability index of post-grouting pile

The bearing capacity of bored piles is significantly improved and the dispersion of bearing capacity is reduced obviously by employing the method of grouting. However, there is still a lack of systematic research on the calculation and analysis of the reliability index of post-grouting pile. In this paper, the static load test data of 152 non-grouted bored piles and 113 post-grouted bored piles are collected. The influence of factors such as safety factor K, types of load effect combination, and the pile diameter are taken into account. Then, the approximate probability method based on the first-order second-moment method (JC method) and Monte Carlo method is employed to analyze the reliability indexes of post-grouted bored piles and non-grouted ones.

Reliability-based evaluation for concrete-filled steel tubular (CFST) truss under flexural loading

Concrete-filled steel tubular (CFST) truss is now widely used in many large-span constructions. In the past, relevant studies on the reliability of CFST structures mostly focused on structural components such as individual columns and beams. In current practices, a simplified method based on the ultimate axial strengths of the chords is commonly adopted to predict the flexural strength of a CFST truss, since there is no mature system-based design regulations nor reliability evaluations on this complex composite system. This paper aims to address this gap by advanced structural reliability analysis of CFST truss through numerical approach considering both the structural nonlinearities and random uncertainties. The finite element models are validated against experimental results. Afterwards, a mass finite element simulation, taking into account the material and geometric nonlinearities, random initial imperfections and potential finite element model errors, is conducted to generate the statistics of the flexural strengths of CFST trusses. Reliability analysis is then conducted to calculate reliability indexes in respect of different resistance factors under various load cases based on AASHTO. Finally, reliability-based evaluation on the safety level of CFST truss design according to mainstream design guidelines such as ANSI/AISC 360–16, Eurocode 4:2004 and JGJ/T D65–06–2015 are carried out. Results show that the current component-based strength prediction of CFST trusses meet the target reliability while the current regulations provide uniform reliability.

Analysis and improvement on reliability of 66/11 kV distribution substation and its associated feeders: A case study of Lainchour substation in Nepal

Electric power interruption is becoming a day to day phenomenon in our distribution system. For distribution system to be effective there should be less outage in the system and if fault occur these faults should be cleared as soon as possible. Sustained power interruption occurs several times a day from few minutes to hours. Interruptions may be due to failure of substation equipment or failure of distribution network elements. This paper attempts to identify different causes of interruption and problems that customers in Nepal have been facing due to frequent planned and unplanned sustained interruptions by evaluating various reliability indices and parameters of Lainchaur distribution substation and its associated feeders operated under Nepal Electricity Authority. First, reliability analysis of substation configuration only is done followed by analysis of reliability improvement measures like use of double bus bar, parallel distribution feeders and underground cables in DIgSILENT PowerFactory only considering sustained failures of equipment and feeders. Calculated reliability indices like System Average interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), Energy Not Served (ENS) are compared for different cases so that it will be easy to make choice between options to the utility to upgrade/improve the system. Considering all feeders, result shows that main cause of interruption in the distribution system is failure of distribution lines showing 104 interruptions for total duration of 107 hours per annum in the system, followed by failure of distribution transformers indicating 19 interruptions for total duration of 47 hours per annum. Simulation result in DIgSILENT shows yearly total ENS of distribution system is high due to present configuration, and can be reduced by the use of parallel feeders and underground cables respectively. It is seen that ENS due to failure of substation components only is very low and huge revenues can be saved if auto-reclosures are used or a provision of charging feeders as soon as possible is made.

Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines

Epistemic uncertainties are critical for reliable design of corroded pipes made of high-strength grade steel. In this work, corrosion defects geometries and operating pressure are provided as the epistemic uncertainties in reliability analysis. A framework of an iterative approach-based bi-loop is presented for fuzzy reliability analysis (FRA) of corroded pipelines to evaluate the fuzzy reliability index-based various fuzzy-random variables (FRVs). In the inner loop, the conjugate first-order reliability method using adaptive finite-step size is applied for carried out the reliability analysis. The outer loop is structured based on the fuzzy analysis corresponding to a modified particle swarm optimization as an intelligent tool. The adaptive conjugate fine step size is dynamically computed to adjust the conjugate sensitivity vector in the reliability loop. The sufficient descent condition is satisfied based on three-term conjugate first-order reliability method. The performance function of corroded pipelines is defined based on average shear stress yield-based plastic flow theory, remaining strength factor, and operating pressure. Two applicable examples as corroded pipelines made from X100 high-strength steel are given to illustrate the effects of epistemic uncertainties under corrosion defects. Investigation the results has shown that modeling of epistemic uncertainty in the reliability analysis of high-grade steel pipelines could result more reasonable reliability indexes. In addition, results indicate that FRVs have significant influence on fuzzy reliability index calculations, especially corrosion defect depth and operating pressure (as FRVs). The sensitivity measure of FRA demonstrated that fuzzy reliability index of corroded X100 steel pipelines is more sensitive to the FRVs means.

Calculation of reliability index for in-plane shear failure of unreinforced masonry walls based on Gaussian process model

The current methods for reliability index calculation are less effective for in-plane shear failure of unreinforced masonry (URM) walls because there is significant uncertainty in the walls’ mechanical parameters and resistance model. To address this issue, the authors propose a new method based on stochastic Gaussian process (GP) model. They conducted in-plane shear resistance experiments on six URM walls and converted the walls’ deterministic shear resistance models to prior GP models, which they updated to posterior models using the experimental results. The posterior GP models specified normal probability density functions (PDFs) for shear resistance of the walls, and the PDFs linearized the walls’ performance functions to the simplest form. With the linearized performance functions, the walls’ failure probability was calculated by direct integration and their reliability indices were determined accordingly. The reliability indices are in good agreement with those given by the Monte Carlo simulation (MCS) using a large number of samples. The proposed method does not deal with high dimensional limit state surfaces, it relieves the influence of uncertainty of the shear resistance model, and it is time-efficient. With these features, the proposed method can facilitate the reliability index calculation for in-plane shear failure of the URM walls.

Importance Sampling Using Multilabel Radial Basis Classification for Composite Power System Reliability Evaluation

Resource additions to electric power grids are planned in advance to maintain reliability of electric power supply. This is achieved by performing reliability studies for calculating reliability indices at the planning stage to ensure that the required levels of reliability will be met. This article proposes a new state classification approach to calculate power system reliability indices using a combination of multilabel radial basis function (MLRBF) networks and importance sampling (IS) within the framework of Monte Carlo simulation process. Multilabel classification algorithms are different from single-label approaches, in which each instance can be assigned to multiple classes. This characteristic gives MLRBF the capability to classify composite power system states (success or failure), at the bus as well as system level. Bus level indices provide useful reliability information for locational reliability, which allows more rational and equitable distribution of resources. MLRBF classification does not require optimal power flow (OPF) analysis; however, OPF is required for the training and cross-entropy optimization phases. This article shows that the scope and computational efficiency to evaluate reliability indices can be significantly increased if the proposed MLRBF classifier is used together with well-known variance reduction technique of IS. As the classifier is trained to recognize the reliability status of a system state, it can also be used in operational planning when a number of scenarios need to be evaluated in a short time for their ability to satisfy load. The proposed method is illustrated using the IEEE reliability test system for different load levels. The outcomes of case studies show that MLRBF algorithm together with IS provides excellent classification accuracy in reliability evaluation while substantially reducing computation time and enhancing the scope of evaluation.

Design of onboard data server for the implementation as a part of onboard avionics equipment using concept of integrated modular avionics

Modern onboard equipment (OBE) includes systems that require storage and processing of large amount of information. At the same time real-time access to data is required. On the samples of national aircrafts, information is most often stored in computers, where the main functions are not data storage, but data processing. Most of the computing resources are spent on running applications. This results in slow processing of requests to a database (DB), which in turn affects the speed of systems that need data from the database or that keep records to the database. The article is devoted to the development of Onboard Data server (ODS) using the concept of integrated modular avionics (IMA) for the onboard avionics equipment of medium-range MS-21 aircraft. ODS is a separate data server computing platform, which provides running of several independent functional applications and carrying out interaction with onboard equipment via AFDX, USB, Ethernet, RS-232 interfaces. The article provides the requirements for the Onboard Data Server, software requirements, architecture, calculation of reliability indicators, four modes of operation: start mode, operating mode, extended control mode and technological mode, describes the algorithm of transition between the modes of operation of the ODS. The use of the ODS will allow reducing the load on the computers of the functional applications of the aircraft systems, simplifying the work of the ground crew interacting with the onboard maintenance system and the aircraft crew, which prepares the flight plan using the navigation data processed on the server.

Reliability assessment of cluster supercomputer configuration

The study of reliability indicators was carried out on the example of a cluster supercomputer configuration of “SKIF-GEO” (further cluster) worked out within the framework of the scientific and technical program “SKIF-Nedra” (2015–2018, Program of the Union State of Russia and Belarus). The cluster is a stationary supercomputer configuration designed to solve resource-intensive applications in data processing centers (DPC). Computing platforms and other cluster modules are located in the same 19′′ rack height of 42U. Theoretical peak performance of cluster – 100 Tflop/s. The basic architectural principles implemented in the cluster, the composition and structural-functional scheme of the cluster are given. A methodological support for calculating the reliability of the cluster, based on previous studies by the authors, is proposed. Taking into account these studies, the structural scheme of reliability (SSR) of the cluster, consisting of two parts – the cluster core and the combination of computing facilities (nodes) (CCF), is substantiated. The component parts (CP) include components of the cluster, the failure of which leads to a decrease in performance to zero. CCF includes CP of cluster, the failures of which lead to a decrease in cluster performance. The choice of the main indicators of the reliability of the cluster core and CCF is grounded and formulas for calculating these indicators are given. The analysis of the consequences of failures of cluster components is made. Taking into account the analysis, the SSR of the cluster core is determined, which allows to derive a formula for calculating the cluster core reliability indicators. A mathematical model of reliability (state graph) of an CCF cluster is proposed, which allows one to derive formulas for calculating the mean time to failure and the mean time for a failure of the CCF of cluster. An assessment of the reliability of CP cluster, for which there is no reliable information on their reliability, is determined based on the SSR of these CP. An assessment of the reliability of the cluster as a whole, based on the calculation of reliability indicators based on reference data on the reliability of components and components, as well as on data from the operation of supercomputers of family “SKIF” has been carried out. Taking into account this estimation and the calculated ratios obtained, the cluster reliability indicators for two options were calculated (in the presence and absence of a reserve of computing nodes). High values of cluster reliability indicators were achieved due to the architectural and structural solutions adopted in the process of its development, aimed at increasing its survivability.

Development and evaluation of the General Surgery Objective Structured Assessment of Technical Skill (GOSATS).

Technical skill acquisition is important in surgery specialty training. Despite an emphasis on competency-based training, few tools are currently available for direct technical skills assessment at the completion of training. The aim of this study was to develop and validate a simulated technical skill examination for graduating (postgraduate year (PGY)5) general surgery trainees. A simulated eight-station, procedure-based general surgery technical skills examination was developed. Board-certified general surgeons blinded to the level of training rated performance of PGY3 and PGY5 trainees by means of validated scoring. Cronbach's α was used to calculate reliability indices, and a conjunctive model to set a pass score with borderline regression methodology. Subkoviak methodology was employed to assess the reliability of the pass-fail decision. The relationship between passing the examination and PGY level was evaluated using χ2 analysis. Ten PGY3 and nine PGY5 trainees were included. Interstation reliability was 0·66, and inter-rater reliability for three stations was 0·92, 0·97 and 0·76. A pass score of 176·8 of 280 (63·1 per cent) was set. The pass rate for PGY5 trainees was 78 per cent (7 of 9), compared with 30 per cent (3 of 10) for PGY3 trainees. Reliability of the pass-fail decision had an agreement coefficient of 0·88. Graduating trainees were significantly more likely to pass the examination than PGY3 trainees (χ2 =4·34, P=0·037). A summative general surgery technical skills examination was developed with reliability indices within the range needed for high-stakes assessments. Further evaluation is required before the examination can be used in decisions regarding certification.

Improving Equipment Reliability and System Maintenance and Repair Efficiency

Mean time to failure of modern machinery and equipment, their individual parts and components can be calculated over the years. Methods for determining the optimal frequency of maintenance and repair, based on the collection and processing of information about the reliability of industrial facilities, during their testing in laboratories and at special sites, as well as through long, operational tests require considerable time and become expensive. The purpose of this work is to develop methods for processing information about the reliability of equipment in automated systems for maintenance and repair, which will reduce the time to collect information on equipment failures and improve the cost-effectiveness of maintenance and repair. Small, multiple-censored right-side samples of equipment operating time for failure are formed as a result of failure data collection in an automated system for equipment maintenance and repair. Calculation of reliability indicators for such samples is performed using the maximum likelihood estimation method. The article presents experimental studies of the accuracy of the maximum likelihood estimates of the parameter of the exponential distribution law for small, multiple right-censored samples. The studies were carried out by computer modeling of censored samples, similar to samples that are formed when monitoring equipment during operation. Methods of simulation modeling of random processes on a computer and methods of regression analysis were used. Analysis show that most of the maximum likelihood estimates obtained from small, multiple-censored right-side samples have significant deviations from the true values. A technique for improving the accuracy of maximum likelihood estimates is proposed. The scientific novelty is regression models are constructed that establish the relationship between the deviation of the maximum likelihood estimate from the true value and the parameters characterizing the sample structure. These models calculate and introduce corrections to maximum likelihood estimates. The use of the developed regression models will reduce the time to collect information about the reliability of the equipment, while maintaining the reliability of the results.

Integration of Accelerated Deep Neural Network Into Power Transformer Differential Protection

Differential protection scheme is the main protection scheme of power transformers, which still holds the risk of sending false trips subject to inrush currents. This article aims to develop a differential protection scheme to discriminate power transformer magnetizing current from internal faults to decrease the risk of false trips. In this article, an accelerated convolutional neural network (CNN) based approach is designed for the discrimination between internal faults and inrush current. The main competitive advantage of the proposed algorithm is its capability in fusing the feature extraction and fault detection blocks into a single deep neural network block by enabling the network to discover important features automatically. The result of this point is that the algorithm is more efficient in terms of speed, hardware usage, and accuracy. The proposed method is applied to a simulated 230-kV network and an experimental prototype. Different cases with various external factors are simulated to calculate reliability indexes. The comparison between the accelerated CNN, conventional CNN, and nine widely used methods demonstrates the faster and more reliable performance of the proposed algorithm.

Assessment of Psychometric Properties of the Postpartum Bonding Questionnaire (PBQ) in Jordanian Mothers

Background: Mother to infant bonding is the most important process in the puerperium, where many instruments have been designed to screen for mother-infant bonding issues. In this study, we will translate and validate the Postpartum Bonding Questionnaire (PBQ) to the Arabic and to measure the mother-infant bonding in a sample of Jordanian mothers.Materials and methods: This sample is a representative sample taken from multiple centers in Amman, Jordan. Post-partum lady who give a birth to a live healthy baby, regardless the mood of the delivery, who have been discharged with their babies home. Women with multiple pregnancies were also included. We calculated reliability indices and relevant statistics using SPSS.Results: A total of 120 participants included in this study. The mean age for the included sample was 28.1 (±6.3) years. Scale internal consistency measured via Cronbach’s alpha is 0.720. Average intraclass correlation coefficient for single measure is 0.067 (CI 0.045 to 0.097). Mean score for the 4 factors of the questionnaire were: Factor 1: 17.43 (±3.95), factor 2: 4.10 (±3.98), factor 3: 7.99 (±2.39), factor 4: 0.37 (±0.94).Conclusion: We translated and validated an Arabic version of the Postpartum Bonding Questionnaire (PBQ), an easy and widely used instrument to measure mother-infant bonding disorders. We observed a high frequency of bonding disorder among a Jordanian sample.

An Enhanced Algebraic Approach for the Analytical Reliability Assessment of Distribution Systems

The calculation of standard reliability indices is critical for assessing quality service and guiding the planning and operation of distribution systems. Traditionally, such calculation has relied on the application of analytical methods based on simulation techniques, which preclude the use of exact methodologies when reliability assessment is incorporated into operation and planning models. This shortcoming has been recently addressed by the development of two optimization-based approaches for the analytical reliability assessment of distribution systems. Unfortunately, both methods are either incomplete or computationally expensive as compared with those based on simulation. In order to overcome these issues, this paper presents a novel and efficient algebraic approach to calculate the standard network-dependent reliability indices of distribution systems. As a distinctive feature over previous non-simulation-based methods, no optimization process is involved. Thus, the proposed approach relies on the solution of a set of linear equations for which effective algorithms are available. Several benchmarks including a real-life 1080-node system have been used to demonstrate the computational superiority of the proposed method. The successful numerical experience supports the suitability of the proposed algebraic model for reliability-constrained distribution system operation and planning.