International Journal of Reliability, Risk and Safety: Theory and Application
Volume:4 Issue: 1, Jan 2021

Reconfiguration of distribution networks by a series of switching operations is a simple and inexpensive way to improve reliability and reduce power losses, which without the addition of additional equipment to the network, makes optimal use of distribution systems. In this paper, optimal reconfiguration is proposed to improve reliability and minimize power losses as objective functions. To demonstrate the functionality and applicability of the proposed method, five states are defined based on the trade-off between buyer-seller. Particle swarm optimization (PSO) algorithm has been used to solve this problem. Then, the proposed method has been implemented on the Lorestan Distribution Network.

One of the most hazardous phenomena leading to enormous monetary loss and threatening human life is slope instability. The major contributors to such disasters are slope geometry, slope material strength, geohydrological condition, structural discontinuity, weathering, development of weak zones, lithological disturbance, and heavy rainfall. As the accuracy of parameters obtained from geotechnical investigations is vital for a practical understanding of the geotechnical project, the back analysis is a pragmatic approach to forecast and control landslide and slope instability. The current paper presents a stochastic back analysis of a recent landslide near a highway located in the south of Iran. Some background information has been gathered through air photos, field observations, and photographs indicating slope failure is pretty recent, and some boreholes were drilled to obtain the required geotechnical parameters of the soil media. Due to the uncertainties in these parameters, the stochastic back analysis approach was adopted. To this end, soil strength parameters have been calculated using the FEM program coded in MATLAB. Results that properly aligned with the findings of the post-event investigations showed a computationally more efficient back analysis approach. The improved knowledge of the geotechnical strength parameters gained through the stochastic back analysis better elucidated the slope failure mechanism, which provides a basis for a more rational selection of remedial measures.

A comprehensive reliability analysis of moment resisting frame is presented in this article in which uncertainties in loadings, material properties, and member cross section properties are included. Performance of designed structures and their reliability in real earthquakes is an important issue these days. In this research study, two moment resisting concrete frame structures, which is the most common type of structures in Iran, are designed based on Section 9 of the Iran National Building Regulations and its analytical model is constructed. Using OpenSEES software, the finite element simulations and reliability analyses are performed with different distribution functions for the mentioned parameters. By using the generated parameters, the ultimate limit functions for structural failure are examined. Results show that incorporating uncertainties in loading, cross section dimension, and material properties could result in a considerable impact on reliability of designed structures.

This paper discusses the topic of probabilistic analysis of composite laminates rectangular plates containing a central circular hole under static tensile load. First, According to the continuum damage mechanics (CDM) approach, structural analysis models, the definition of damage and the treatment of random variables will be explored. Then, the matrix cracking and fiber/matrix debonding damage is modeled and the material constitutive relationships are implemented in the ABAQUS software by the subroutine. The probabilistic methods, first order reliability method (FORM) and second order reliability method (SORM) have been used to analyze the composite plates’ system failure probability. The failure functions and random variables have been obtained according to the CDM approach. Issues arising out of the use of composite material structures, in applications, due to non-homogeneity and anisotropic characteristics, and manufacturing defects will be highlighted, and uncertainties related to the material properties, loads, and boundary conditions will be discussed through examples. It is shown that the scatter in parameter values has a significant effect on damage development in the model.

The presence of chemicals in process industries such as the food industry has always been subject to risks like fire, explosion and release of toxic substances. The occurrence of such incidents have serious impact on the funds and life resources. In this article, we have tried to identify hazards of Ethanol storage tank with PHAST modeling to provide solutions to reduce and manage risks in Behnoush Iran Company. The most dangerous scenarios were selected according to the available conditions 100 mm diameter tank leakage, 3 Inches diameter short pipe leakage and Tank rupture in the summer and winter cases. According to the results, a leak with diameter of 100 mm with radiation of 37.5 KW/m2 and catastrophic rupture are also very dangerous due to the suddenness of the accident and has the ability to damage the tanks. Therefore, by modeling and evaluating the consequences of such accidents, it was proposed to reduce the hazards and prevent the occurrence of more serious accidents by using more advanced fire detection and firefighting equipment, the use of fireproof structures, continuous training of people, and the promotion of safety culture and fire team deployment.

The process of development and expansion of advanced industries reveals the need to implement more and more predictive methods and mechanisms in readiness to deal with possible failures. With complexities inherent in systems, having a proper and all-embracing model of the entirety of a system is not readily possible. Design structure matrices (DSMs) are regarded as great (a great) help in communicating, comparing, and integrating partial system models. Given that there are numerous relationships among subsystems in complex systems, it is expected that interactive failures occur giving rise to diverse problems as well as gradual or abrupt failures in the system. Correlational dependent (Correlational-dependent) failures, commonly known as interactive failures, most frequently occur in mechanical systems. In this study, we have exploited DSM for identifying interactive failures and the relationships existing among different components in complex systems. The latter matrix is generally used in industries for observing the strengths of existing relationships among interacting elements. From another perspective, by analyzing the relationships among elements and identifying coils and curls, it is possible to investigate the existing nodes in loops. Implementing this procedure leads to identifying critical components and interactive failures, eventually bringing about enhanced reliability in the system. The present paper, while considering prevailing methods adopted in previous studies for selecting critical parts and subsystems, proposes a new method for selecting critical parts so as (delete so as) to increase the reliability rates. The method set forth is derived from the Markov chain model in addition to employing mathematical methods in matrices.

A network bridge is a computer networking device that creates a single aggregate network from multiple communication network or network segments. One of the type of network bridge is transparent bridge saddle with responsibility of checking incoming network traffic to identify media access control addresses. In this present research work on series parallel computer network performance, availability and cost analysis of complex computer network was considered to focus on a network that has four subsystems A, B, C and D and all the subsystems are arranged in series-parallel, subsystem A and B are working on 1-out-of-2: G and 2-out-of-3: F policy respectively, C subsystem behaved as a bridge with one unit and D subsystem has five units and are working in 3-out-of-5: G scheme. The system has two types of failure, degraded (partial failure) or complete failed states. The system was analyzed using supplementary variables techniques and Laplace transform, general distribution and copula family were employed to restore the partial failure and complete failure states. Computed results have been highlighted by the means of tables and graphs to investigate the performance of computer network. The result has shown that computer network with transparent bridge will be more reliable to filter incoming frame and forward it to media access control (MAC).

Several statistical approaches have been developed to analyze the sampling of huge data and information. There are three significant factors for comparison of the strength of these methods that are argued in this paper; the proposed method is a compatible approach to various types of sampling methods and applied to improve the sampling efficiency and decrease uncertainties to reach accuracy in results. In argued methods, each element just belongs to one category and/ or strata, but in our approach, each element includes all groups with one exception that membership values are different. The case study results show that the proposed Fuzzy Strata Sampling (FSS) method better measures uncertainty and accuracy rate than the other existing sampling methods.

Rotating machine is one of the most important machines used in various sectors. The most important unit is the rotating part and the shaft held by bearings. Most of the maintenance and repair cost of these machines is related to the replacement and service of bearings. Therefore, it is very important to identify the damaged bearings and determine the location of the damage. Different methods have been developed to monitor their condition, including recording and analyzing the vibration signals of bearings. So far, vibration-based methods have often been used to analyze them. Recently, the use of machine learning and deep learning techniques have been considered. Therefore, in this paper, a convolutional neural network is developed that directly receives the raw information recorded by vibration sensors as input and after analysis, a healthy bearing is detected from a defective one, the location and size of the damage are determined. In this research, the data set of Case Western Reserve University is used to validate the model and the results show that the proposed model has very high accuracy for analysis of samples.

The work presented in this paper was to investigate whether a new intelligent decision-making system could have provided analysis using data sets and predicted the Buncefield UK catastrophe before it occurred. The new intelligent decision-making system is presented. It incorporates reliability engineering tools with multicriteria decision-making methods and artificial intelligence techniques. An intelligent system that recognises increasing level(s) and draws awareness to the possibility of additional increases before unsafe levels are reached is used to analyse and make critical decisions. The aim was to ensure that the causal factors of failure of the Buncefield UK incidents were predicted, ranked and solutions proffered one at a time to ensure that failures with high priority and high probability of re-occurrence were addressed.

The recursive approach for assessing the reliability, availability, maintainability, and dependability (RAMD) of five subsystems in a reverse osmosis (RO) machine was investigated in this study. The components include the raw water tank, precision filter, carbonated filter, reverse osmosis membrane, and water producing tank. Furthermore, the efficacy of a reverse osmosis (RO) unit, mean time to failure (MTTF), mean time to repair (MTTR), and dependability ratio were also assessed. The major aim is to maximize efficiency and identify the critical subsystem or component of the reverse osmosis machine. And finding out how to fix the problem. We utilized data from the RO unit with a repair rate and a failure rate over a 100-day period to validate the technique. There were numerical numbers for each subsystem's dependability, as well as comparisons between subsystem dependability and total system dependability.

Natural Circulation (NC) is an important mechanism in several industrial systems, and knowledge of its behavior is of interest to nuclear reactor design, operation and safety. The main safety issue in present nuclear reactors is to ensure the sufficient removal of decay heat during accidents. Recently, Small Modular Reactors (SMRs) have increasingly received a lot of positive attention and even several types of these reactors are in different stages of design and construction. Some of these SMRs, such as NuScale, are designed to operate in full NC mode as the main mechanism of the primary coolant drive force for heat removal from the reactor core during normal operation. The present study deals with the Natural Circulation Flow Map (NCFM) investigation in the NuScale reactor as one of the SMRs that operate in full NC mode. At first, NuScale reactor elements are modeled with RELAP5 thermal-hydraulic code. Then, after the verification of the steady-state modeling, the operational point of the NuScale reactor is indicated in NCFM that is based on the database of different PWR simulators (gathered from the experimental test facilities). The evaluation of Natural Circulation Performance (NCP) of this reactor has proved the good design of NCP during normal operation in comparing typical PWRs operations in high power cases.