جستجوی مقالات مرتبط با کلیدواژه « reliability » در نشریات گروه « عمران »

Safety, reputation, customer satisfaction, operation and maintenance cost, repeat business and competitive advantage are among the reasons that emphasize the importance of reliability in transportation systems. Reliability plays an important role in the stable and safe operation of transportation systems, especially the rail industry. Attractive rail services can only be provided with quality subsystems that can guarantee the safety of operations and the availability of the rail network. In this article, a reliability optimization model is presented according to the characteristics of a passenger rail system, possible options with a case study of the Iranian railway; The proposed model can be used by considering service criteria in the railway system such as life cycle cost, punctuality and average time between failures to determine the optimal investment plan in order to design or update and upgrade the railway system with high reliability. be placed Paying attention to these criteria can influence the decision to buy parts with different quality levels.

Today, a huge amount of data is transmitted around the world through the high capacity of optical telecommunication networks. In railways, optical transmission telecommunication networks play a very important role in the transmission of critical a large amount of rail data. Reliability of telecommunication infrastructure is required to increase productivity, maintain safety and reduce maintenance costs. In this article, the existing reliability level and all relevant parameters (the number of network outages and the time between network failures, MTBF) of the railway optical transmission telecommunication network are obtained through the Reliability block diagram method and simulated through the Monte Carlo method and then optimized. Also, prediction of the network's behavior and obtaining the probability of its failures are done through three-layer perceptron neural networks and the results are presented. The network implemented in this article is the 654 km long optical telecommunication transmission network of the railway region of Azerbaijan.

Interlocking as a heart of railway signaling system is an important part of this safety-critical system. Looking at the interlocking tasks including correct routing, locking the routes and releasing them timely and commanding to wayside equipment, including signals, point machines and track circuits, will be revealed due to the critical nature of these tasks, interlocking necessarily must have a high tolerance against different probable faults. The best way to design a fault tolerant system is redundancy in processors. Structures with 2 processor units (dual hot stand-by), 3 processor units (3-vote-2 redundancy) and 4 processor units (double 2-vote-2 redundancy) are the most practical techniques which manufacturers have used in the interlocking systems. These redundancies improve reliability, safety and fault tolerancy of system. Each structure has its own advantage. In the Markov method by considering the different states of processors and failure rate, system state diagram is obtained. Then the system transitions between the various operating modes can be expressed by a matrix. The state transition equations formed the behavior of the system to fully assess the safety, reliability and mean time to failure of interlocking system to quantify these indexes. In this article we evaluate and compare the reliability and safety of mentioned structures and study the impact of system parameters (such as failure rate and coverage factor) on the dependability property. We showed that the increasing of coverage factor can straightly improve the safety and also reliability of the system, in addition the control strategy of switch in the hardware of redundant interlocking system is very important in the dependability of this system.

This study aims to assess reinforced concrete moment frames designed at varying ductility levels within a typical reinforced concrete structure, from a reliability perspective. The article explores the probabilistic methods for designing different ductility levels in the current Iranian Concrete Code, focusing on reliability. Specifically, a three-story concrete moment frame structure, designed to low, medium, and special ductility levels as per the Iranian code, is studied. The reliability analysis encompasses uncertainties in loading, dimensional parameters, and evaluating structural performance functions such as floor drift and acceleration. The study utilizes horizontal earthquake components specified by the FEMA P-695 standard to analyze earthquake record uncertainties. Furthermore, a comparison of the reliability index and probability of failure for each performance function is used to assess failure uniformity. The findings reveal a maximum probability of failure in collapse damage state of approximately 9%, 5%, and 2% for low, medium, and special ductility frames, respectively.

Availability means the stability of the network in operational conditions and at a given time. In other words, the network should not be turned off during operation, and if it is turned off, the failure must be fixed at a certain time. Availability is a combination of system reliability and maintainability. Broadband optical telecommunication networks are used to transfer high capacity domestic or international data in the form of data transmission. In the international traffic transfer agreements, there are network quality level agreements that, if the access level is lower than the agreed levels, or blackout. network, network owners suffer heavy losses. Also, in various industries such as the railway industry, train control structures are based on optical telecommunication networks, and reducing the level of network access may lead to blocked railway lines and irreparable accidents, so high availability leads to stability. network and reduce line congestion. In this article, in addition to modeling the increase in the access level of the optical transmission network (the implemented case example of the optical transmission network of the Hormozgan railway region) and observing its results in reducing the blockage of railway lines, the behavior of the network through the Monte Carlo method of prediction and simulation has been made

Today, a huge amount of data is transmitted around the world through the high capacity of optical telecommunication networks. In railways, optical transmission telecommunication networks play a very important role in the transmission of vital rail data and the safety of movement. Reliability stability of telecommunication infrastructure is essential in increasing productivity, maintaining safety and reducing maintenance costs. In this article, the existing reliability level and all relevant parameters (the number of network outages and the duration between network failures, MTBF) of the railway optical transmission telecommunication network to obtain the number of blocked railway lines through the block diagram method (Reliability block diagram model) created and simulated through the Monte Carlo method and then optimized with the aim of reducing line blocking, considering that with each network failure, rail lines are blocked, the number of network outages is equal to line blocking. Therefore, with optimization, the reliability of the line blocking network is reduced. Also, predicting the behavior of the network and obtaining the probability of its failure is done through perceptron three-layer neural networks and its results are presented. The network implemented in this article is an optical telecommunication transmission network. The railway zone of Azerbaijan is 654 km long.

In many practical applications of structural reliability analysis, one of the preferred sciences is the sensitivity analysis of failure probability based on design parameters under the limit state function. This information is needed, for example, in design optimization based on reliability. The design parameters are calculated by first- and second-order reliability methods FORM\SORM to sensitivity analysis of the probability of failure approximately. Therefore, in many cases, these methods are very inaccurate or difficult to solve problems. Accordingly, the Monte Carlo simulation method is very useful for determining the reliability sensitivity parameters. The derivation probability of failure into the parameters of the limit state function is calculated by integrating the surface of the performance function. By using the Monte Carlo simulation to determine this integral will not be efficient due to the small portion probability of failure and will have a high computational cost. Hence, some methods can be used to estimate Monte Carlo simulations that reduce the computational cost. One of these methods is linear sampling method. In this paper, an approximate method is used to determine the surface integral in terms of a domain integral. The integration domain can be calculated using standard Monte Carlo simulations or importance sampling simulations. This article presents two practical examples of sandwich panels to determine the effectiveness of parameters random variables are used in the design.

In railway signaling, the safety of the system refers to the protection of losses and economic losses. The connection of an interlocking system to wayside equipment such as signal, point machine, track circuit, etc. is carried out through the equipment’s control system. Since the data transmission and retrieval of wayside equipment through the system acts as a vital interface between the interlocking system and the wayside equipment; therefore, checking the status and accuracy of each function should be performed instantaneously; therefore, check of this system safety and reliability it is very important under all circumstances. Generally, these boards are made up of a controllable signal for tolerable breakdowns. Since reliability and safety calculations require field and laboratory tests, they should be done by modeling, simulating, and using numerical and analytical methods. In this paper, first, we introduce the OCS system and then the signal controller, and then introduce the reliability and quantity of the related. Then, the reliability of the signal-controller board is obtained by using a system block diagram and simulation with MATLAB software, In the next step, using hardware redundancy, a closer look at reliability is discussed; and finally, conclusions will be drawn and proposals will be made in the relevant field. The main innovation in this paper is the use of block diagrams and structural redundancy in calculating the reliability of signal-controller boards and simulation with MATLAB software.

Road user satisfaction is one of the most important factors indicating the optimal transportation system of countries. The difference between the passenger's expectations and the actual performance of the services provided will cause the passenger to be dissatisfied and will cause him to turn away; Therefore, it is important to study the relationship between the quality of traffic services and the satisfaction of road users. The process of conducting the present study is fieldwork and with the help of a questionnaire. The criteria of tangibles, reliability, assurance, responsiveness and compassion and commitment (empathy) are at a significant level. By paying attention to the coefficients of variables that have a significant level, it is clear that the effect and role of the tangibles in the importance of passenger satisfaction is more than other indicators. As a result, the presence of the necessary physical equipment and facilities, sufficient tools and machinery, and visible and suitable asphalt surfaces play the greatest role in passenger satisfaction.

Uncertainty of design parameters is one of the most important variables in determining the reliability of structures. In the design and analysis of steel frames, buckling-restrained brace (BRB) equipped with intelligent materials such as shape memory alloy (SMA), there are various variables such as gravity loads, lateral loads, material properties, and geometrical specifications that the uncertainty of each of which can have a significant effect on the safety of the structure. In this research, considering the existing uncertainties in material properties, loading and geometry of members, the reliability of steel BRB frames equipped with intelligent materials has been investigated. Evaluation of sensitivity and reliability analyses based on kriging meta-model of BRB frames with and without SMAs under artificial near-fault earthquakes are conducted. For this purpose, two frames 5 and 15-story with BRB with and without SMA have been studied under 9 artificial near-fault earthquakes. Nonlinear dynamic analyses were performed using OpenSees software and reliability analyses were performed by linking MATLAB software on frames. The results of this research showed that in the studied frames, the random variables of the length of SMA and the cross-sectional area of the BRB were the most effective variables in calculating the probability of failure in BRB frames with and without intelligent materials, respectively. Also, by increasing the height of the frames, the reliability index has decreased. For example, the reliability index of a 5-story BRB frame with SMA has decreased by approximately 17% compared to a 15-story frame. Meanwhile, the maximum values of the reliability index using SMA in 5 and 15-story frames have increased by 10 and 6%, respectively.

One-dimensional view of optimized design of engineering systems focusing on costs without considering other aspects such as risk and uncertainty in engineering design can increase risks during the operation of that engineering system. This paper indicates that if there are uncertainties in design parameters this cannot always cause poorly system operation, whereas may strengthen that system operation. For this purpose a gravity retaining wall is optimized and the optimal dimensions of that retaining wall are calculated. Then the effect of uncertainties, which are in the design parameters of that optimal gravity retaining wall, on the stability factors is calculated. Finally, using the concept of reliability, the risk in the safety factors of the retaining wall is obtained. In this paper, it is shown that if there is 10% uncertainty in design parameters the uncertainty propagation on safety factors is about (-80,+345)%, but this uncertainty propagation can increase the reliability(positive aspect of uncertainty) and risk(negative aspect of uncertainty) with a probability of 98.6039% and 1.3961% respectively. Then using the reliability block diagram, the total amount of reliability and risk for the gravity retaining wall is calculated which are equal to 79.3169 and 20.6830%, respectively. The innovations of this paper can be listed as below: 1) using Self-Adaptive Genetic Algorithm and Many Objective Genetic Algorithm, which have been used to optimize the retaining wall and calculate the uncertainty propagation on safety factors respectively. 2) calculating reliability and risk using fuzzy set theory.3) using reliability block diagram (RBD) to calculate the overall reliability and risk.

This paper presents a systematic and comprehensive analysis procedure for predicting the reliability of the railway industry in order to identify the factors affecting the reliability and obtain a more accurate estimate. This study will also help railway industry managers to better understand the importance of reliability and optimize important performance indicators in the railway industry and to understand the advances that can be made to improve reliability in the railway industry. This study also presents a comprehensive allocation framework with regard to the features of a passenger railway system and possible alternatives; In addition to system reliability, the proposed process can allocate life cycle costs and service reliability to determine the optimal investment plan for designing or updating the rail system. This comprehensive approach can help the rail industry in predicting the reliability of systems and subsystems and identifying the ideal balance between cost, reliability and timing of passenger trains in order to achieve optimal rail system design.

With recent technological developments in the mining industry, the issue of physical asset management has become more important. Asset management in the mining industry has a key role to achieve production goals and increase competitiveness in the market. Reliability is one of the key indicators of asset management. Reliability is a function of the failures time and various risk factors such as environmental and operational conditions. One of the most widely used methods for investigating the relationship between the risk factors and reliability is the proportional hazard regression model. The regression coefficients can be estimated using two approaches, i.e. parametric and semi-parametric. In this paper, the failure data of a dump truck in the Sungun copper mine is analyzed using both semi-parametric and parametric approaches. The results show that the obtained estimates of both approaches were close to each other, according to Akaike Information Criterion (AIC), the Weibull parametric model is more efficient than the semi-parametric model at describing the reliability and hazard rate. In addition, it is found that road condition; operator skill, ambient temperature, and haulage distance have a significant effect on the hazard rate of the dump truck. This analysis is applied to maintenance management to keep the reliability of the dump truck at an acceptable level.

Wood is one of the oldest materials that has always been known as a construction material. Despite its widespread application and unique properties, it has weaknesses such as relatively brittle behavior, especially in bending. In order to improve its performance and boost its features or strengthen wooden structural members, one solution is to employ FRP component, which is widely used as a rehabilitation tool. The lightness and ease of application for different materials such as concrete, wood, and steel have made it possible to increase the strength and ductility of structural elements. In this study, the few models that were available for the wood-FRP system were collected, and the uncertainty of six variables, as the most effective parameters in the strength of this system, was selected for reliability analysis. Also, during the steps, three live to dead load ratios equal to 0.75, 1, and 1.25 were assumed as the design loads. What was achieved during this research was that during the design process of wood-FRP, uncertainties had a significant impact on the reliability of existing models. Some models could be reliable enough to be applied for design purposes; however, uncertainties seriously affect the reliability of some models. Accordingly, the average reliability index of all six available models decreased from 4.88 in case one fails to consider uncertainties to 2.71 with uncertainties of the models. Among the five existing models presented in previous studies, the Palizi and Toufigh model with an average reliability index of 3.61 was the best-proposed model, which is in good agreement with the acceptable index of existing structural design criteria. It is worth noting that various variables affect the reliability of this system. However, in this study, only the uncertainty of the six variables of modulus of elasticity, thickness, length, and width of FRP, along with wood width and its compressive strength, was considered. Other sources of uncertainties may be considered while analyzing this system in future studies.

Recently, nonlinear viscous dampers have been widely used to improve the seismic performance of structures. These dampers dissipate the kinetic energy caused by the earthquake by producing a damping force. These dampers are designed in such a way that the force is proportional to the velocity. The Maxwell model is the most common model for modeling the behavior of nonlinear viscous dampers. In this model, the damping coefficient, the velocity exponent and the axial stiffness of the dampers are the key parameters. In most previous studies, the uncertainty of the underlying parameters in behaviour of viscous dampers has been ignored while it can has a significant effect on the seismic response of structures. In this study, first, the reliability analysis of a shear frame equipped with a nonlinear viscous damper was performed using the Monte Carlo sampling method. The results show that increasing the maximum drift from 0.015 to 0.02 reduces the probability of failure by 72%. Then, reliability-based sensitivity analysis of the studied frame was performed in order to determine the most effective random variable on the reliability of the frame. The results show that the velocity exponent is the most effective random variable on the reliability of the frame. Also, results indicate that importance of random variables depends on the used limit state function in the reliability analysis. For example, the imporatance value of the damping coefficient is 59% and 9.5% less than the velocity exponent with respect to the maximum drift of 0.015 and 0.025, respectively.

Maintenances are necessary to ensure the safety and serviceability of existing bridges. With the increasing number of existing bridges, maintenances cost a large proportion of financial fund and have significant impact on environment. Bridges like any other structure and perhaps more than most of them are affected by environment. Because they belong to sensitive and high costly structures, failure to maintain them will have devastating effects. Bridges are needed continuous maintenance in order to service properly during its life cycle. Therefore, in this study, the issue of maintenance and repair of urban bridges in Mazandaran province has been studied with regard to life cycle cost and reliability of bridges. To do this end, a mathematical programming model which is include minimizing maintenance and user costs as well as maximizing system reliability. In order to solve the proposed model, a multi-objective particle swarm optimization algorithm is developed. Also, a sensitive analysis is done on failure rate. Results show that increasing in this parameter cause to increasing cost and decreasing reliability, This indicates that the proposed algorithm is working properly and the results of this research can be trusted.

Travel time and its variation are among important aspects of transportation that are used as key indicators to evaluate network performance in transportation planning. Studies show that traffic congestion is an important factor effecting travel time reliability and is divided into two categories: Recurrent and Non-Recurrent. Studies show that Traffic incidents, Work zones, Weather, Demand fluctuations, Special events, Traffic control devices and bottlenecks are the seven major factors which cause travel time changes. This article aims to examine how changes in transit geometry (number of lanes), accidents, traffic volume, and weather conditions can affect travel time reliability. In order to do so, a variety of machine learning methods were used to study and model the Virginia highway network, including Support Vector Regression, Nearest Neighbor regression, and Decision Tree regression. The results of this study showed that these tools can reflect the changes in the average travel time to an appropriate extent. Among these methods, performance of the Nearest Neighbor was the best (coefficient of determination 0.85 and error 0.0012 for training set and coefficient of determination 0.57 and error 0.0014 for test set and stable performance equal to 1.47).