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This paper proposes a hybrid technique for optimizing Combined Cooling, Heating, and Power (CCHP) systems integrating a diverse set of components including geothermal heat pumps, gas turbines, absorption chillers/heaters, and photovoltaic/thermal collectors, along with storage units like batteries and water tanks. The innovation lies in combining the Capuchin Search Algorithm (CapSA) with the Wild Horse Optimizer (WHO) to concurrently optimize primary energy savings, cost reductions, and carbon dioxide emissions. Parametric distributions are used in probabilistic strategies to resolve uncertainty in solar radiation and building load. CapSA optimizes the CCHP system’s design, while WHO enhances its performance. The effectiveness of the proposed strategy is demonstrated through implementation in MATLAB, where it achieves an average ACSR (Average Comprehensive Saving Rate) enhancement of 5.48%. This numerical result highlights a substantial improvement over existing methodologies, showcasing the superior performance of the hybrid optimization approach in enhancing energy efficiency and environmental sustainability of CCHP systems. [ABSTRACT FROM AUTHOR]

The system reliability analysis of complex engineering structures remains a challenge in the field of reliability. In this work, a high-order moment method using generalized factorized dimensional reduction method (GF-DRM) and iterative maximum entropy method (IMEM) is proposed for structural system reliability assessment. Firstly, the performance functions are described uniformly by equivalent description methods for various system reliability problems. Secondly, a novel point estimation method (PEM) based on GF-DRM is proposed for the high-order moments estimation of the equivalent performance function. Thirdly, the system failure probability of the structures is accurately determined by using the IMEM, which can automatically determine the order of moments. Finally, four examples, including numerical and engineering cases, are investigated to demonstrate the accuracy and efficiency of the proposed method, in which results obtained from the proposed method are compared with some other existing moment methods and Monte Carlo simulation (MCS) method. The results of the examples show the proposed method has fairly high accuracy and efficiency for structural highorder moments estimation and system reliability analysis. [ABSTRACT FROM AUTHOR]

In this paper, we look at the distributions of runs and scans in multistate Markov exchangeable sequences. The joint distributions of runs of several lengths under four types of enumeration schemes are analyzed. We evaluate the upper tail probabilities for ratchet scan statistics exactly. By utilizing the expansion of the generating functions, we propose effective computational tools for the derivation of probability functions. The results presented here provide approaches for the evaluation of the exact distributions of runs and scans in a wide class of practical problems. Finally, we discuss several applications and numerical examples to show how our theoretical results are applied to the investigation of runs and scans, as well as a parameter estimation problem. [ABSTRACT FROM AUTHOR]

Increasing demand for power generation, slow lessening of fossil fuel resources, and carbon footprint enhancement because of their continuous maltreatment have increased the demand for different energy sources for energy generation. Wind energy systems generate power with a reduction in environmental pollution as well as it improves the reliability and stability of the power system. For long-term planning and future capacity expansion and to ensure that the installed generation capacity is sufficient to meet the load demand, the evaluation of generation system reliability indices is a key factor. Hence, this paper proposed the innovative four-parameter-based progressive alpha model method (FPBPAMM) based on generalized functions analysis for improving the power system reliability with the insertion of wind energy generation. Therefore, the effect of the penetration of wind energy generation on the reliability of the power system is examined. Moreover, power system reliability enhancement using the wind energy system is calculated. Full risk analysis and case study have been performed to explain the effectiveness of the proposed technique and to provide a good understanding of the power system reliability impact consequential for the wind power system merging into the main grid. [ABSTRACT FROM AUTHOR]

Many systems connected in series are subject to failure earlier in their design life. The failure rate of such systems has been described by a two-sided power distribution, which enables modeling the entirety of the bathtub curve failure modes with a single distribution. We propose a time-dependent reliability optimization model for improving a system's reliability through the optimal allocation of redundant components whose failure distribution follows a two-sided power distribution. To solve the multi-criteria optimization model, we propose an algorithm that (i) identifies the scale tolerance at which a selected component will have a higher mean residual life, (ii) identifies the level of redundancy for enhancing system reliability, and (iii) identifies other optimal system characteristics, including minimized cost and minimized volume. Two sided power (TSP) distribution with four parameters (a, b, c, η) models time-to-failure. We consider an n-stage series system and assign redundancy within the stages. We propose a multi-objective optimization problem to assign redundancy, accounting for reliability, cost, and system volume. An illustrative example is solved using the NSGA-II algorithm. [ABSTRACT FROM AUTHOR]

Probabilistic analysis has been widely used to assess the inherent uncertainty of variables in laterally loaded pile systems, but the calculation is still difficult and time-consuming. The present study presents an efficient probabilistic analysis framework for a laterally loaded pile system. The performance of the system is defined as the lateral deflection at the pile head and maximum bending moment of the pile shaft, corresponding to two failure modes. Within this framework, the spatial variability of the soil and the correlation between failure modes are considered by the random field theory and the First-Order Reliability Method, respectively. Moreover, the Sequential Compounding Method is used as an efficient tool to determine the system reliability indexes. The framework is confirmed by comparing the reliability indexes of failure modes and systems with those of the Monte Carlo Simulation Method. Furthermore, a parametric analysis and system sensitivity analysis are performed. The results show that the auto-correlation distance, allowable lateral displacement at the pile head, and allowable bending moment of the pile shaft have a great influence on reliability indexes of failure modes and system, and the major parameter of soil in affecting pile is the elastic modulus compared with the undrained shear strength. [ABSTRACT FROM AUTHOR]

Contact wires are critical components of railway overhead infrastructure which provide power for trains. This paper proposes an innovative method to determine the service life of worn contact wires under three failure modes: tension, fatigue, and attrition. The tensile stress, fatigue damage, and cross-section loss of contact wire have been modelled as stochastic processes following lognormal distribution. The first-passage probability method is then used to determine the time-dependent failure probability for contact wires under each failure mode. The service life of the contact wire is determined through system reliability analysis. This method has then been applied to a case study to provide information on behaviour evaluation of contact wire. It has been found that the service life of contact wire can be underestimated without considering the wear effect on fatigue failure mode. Also, through sensitive analysis, it has been determined that the wear rate of contact wire can affect the probability of fatigue failure considerably in the longer term. The methodology proposed in this paper can help engineers and asset managers in making optimum decisions regarding the time of repair and/or maintenance of contact wire exposed to wear. [ABSTRACT FROM AUTHOR]

A slope system is a series system with numerous potential slip surfaces (PSSs), and its failure probability is commonly evaluated by several significant failure surfaces, or representative slip surfaces (RSSs). Previous efforts have mainly identified the RSSs in spatially variable soils from the perspective of the correlations between different PSSs, the effects of the failure probabilities of the PSSs were rarely considered. With the goal of identifying RSSs from the perspective of the system failure probability, a method adopting the second-order reliability method (SORM) and the multimodal optimisation is proposed. In this method, the spatial variability of soil properties along the slip surface is characterised by local averaging to reduce the number of variables in SORM. Equations for calculating the correlation coefficient between different PSSs with correlated variables are derived. The task of RSS identification is transformed as a multimodal optimisation problem, and the PSSs that make great contributions to the system failure probability are determined as RSSs. The proposed method and the derived equations are demonstrated using two slope examples. The results show that the proposed method is capable of identifying RSSs with significant contributions, and it provides a proper estimate of the system failure probability. [ABSTRACT FROM AUTHOR]

Fatigue is among the most critical forms of deterioration damage that occurs to steel bridges. The performance of steel bridges, which may be seriously affected due to fatigue, should be assessed and predicted. However, the code-based reliability assessment only provides a clear criterion for single details. The whole bridge or a splitting system from the bridge may contain many details which brings system impact on the fatigue assessment. In this paper the system reliability of steel bridges is addressed with focus on the influence of spatial correlations between similar fatigue sensitive details. The study is conducted on a typical riveted railway bridge, from which a subsystem is selected and modelled as a weakest link system. It is assumed that all details in the system are equicorrelated. An efficient modeling approach has been developed to quantify the correlation and help estimate the system reliability analytically. A parametric study was performed to determine the system effects on the fatigue reliability assessment and identify the decisive variables. [ABSTRACT FROM AUTHOR]

In the light of Industry 4.0 revolution, the Industrial Internet of Things (IIoT) allows digitalizing manufacturing processes and increasing the digital connectivity and automation in the smart factories and industrial systems. The reliability of a system is considered as a key performance indicator that defines how accurately and perfectly the system works. Ensuring reliability in the IIoT systems presents several challenges due to the presence of uncertain and dynamics in the industry environment as well as the complex nature of industrial systems. While there are no standard frameworks proposed and applied for the IIoT systems with multiple reliability levels, the challenges reveal many promising opportunities for the research and practical implementation including advancing technologies and systematic designs such as algorithms, architectures, and devices. However, there are a few works studying the reliability-related aspects of the industrial systems in the existing literature, they lack a framework to conduct the study and examination of reliability of IIoT systems in a holistic manner. In this regard, this article will elucidate and survey several performance-improvement methods and techniques for better reliability and further challenges to be overcome for highly reliable IIoT systems. Finally, by defining several open research issues, we expect to draw more attention for both the academic researchers and practitioners toward designing and developing reliable solutions and frameworks. [ABSTRACT FROM AUTHOR]

Working vacation queues with breakdowns and customers impatience have many applications in different real-life situations. The development of these models to determine their performance is extremely important. In this paper, we deal with a finite population Markovian multi-server machine system with breakdowns, repairs, Bernoulli feedback, balking, reneging, and retention of reneged customers, under multiple synchronous working vacations. The investigated model has a potential application in the real-world machine systems, such as the automated manufacturing systems with limited space. For the analysis purpose, we employ Q-matrix method in order to obtain the steady-state probabilities as well as closed-form expressions for several system characteristics. Particular cases of the current study are presented. We construct the expected cost function and develop an optimization problem to determine the optimum cost. The direct search method and the Quasi–Newton method are applied to find the optimum system capacity, the minimum number of servers, and the optimum service rates during both working vacation and regular busy periods at minimum cost. Lastly, a sensitivity analysis for the numerical simulation is carried out. [ABSTRACT FROM AUTHOR]

To enhance the computational efficiency in slope reliability analyses, a binary classification method (BCM) that takes advantage of a judgement-based strength reduction method (SRM) and an active-learning support vector machine (SVM) was developed to conduct system reliability analyses of layered soil slopes. The SVM was naturally employed to establish a binary classifier via the judgment technique to approximate the true limit state function because the stability state (e.g. stable or unstable) of a slope can be determined without calculating its exact factor of safety according to the SRM. An active-learning technique was developed to iteratively search training samples in the vicinity of the border between safe and failure domains, to update the SVM classifier with the aid of a modified initial sampling rule. Then, Latin hypercube sampling was employed, together with the obtained SVM classifier, to compute the slope system probability of failure. Three representative examples taken from the literature were employed to evaluate the performance of the proposed method. The proposed BCM shows great computational efficiency compared with existing methods. It reduced the computational cost to several minutes for simple slopes and to approximately 30 minutes for a complex real case, while maintaining a good computational accuracy. [ABSTRACT FROM AUTHOR]

This article presents a novel system reliability-based framework for multi-objective optimisation of preventive maintenance (PM) management of in-service asphalt pavement. To accurately predict the international roughness index (IRI) sequence of pavement sections, a long short-term memory (LSTM) neural network that considers the spatiotemporal correlations between IRI sequences is trained with data retrieved from the long-term pavement performance (LTPP) program. Based on time-dependent limit-state functions (LSFs) incorporating the uncertainty associated with LSTM neural network prediction and the observational error involved in IRI measurement, Monte Carlo simulation (MCS) with importance sampling (IS) is adopted to calculate the reliability of pavement sections. Pavement sections located in New Mexico and Montana are selected as illustrative examples. Tri-objective optimisation processes are investigated by maximising user benefits (i.e. improved system reliability) and agency benefits (i.e. extended service life) while minimising the associated life-cycle cost (LCC) (i.e. user and agency costs) with multi-objective genetic algorithms (GAs). The obtained Pareto solution sets may assist decision-makers in the selection of well-balanced solutions to identify the optimal timing for applying PM treatments to in-service asphalt pavement. [ABSTRACT FROM AUTHOR]

System with self-healing mechanism has been successfully applied in many practical engineering fields. When we discuss the reliability performance of system subject to shocks, cumulative shocks have the greatest impact on most systems fields such as high-speed railway systems or civil structural components. In the present paper, we deal with two different types of cumulative shock models in discrete time with self-healing effect. We study a system with self-healing mechanism from a reliability point of view under these two shock models. The self-healing system will fail when the cumulative damage effect exceeds the given threshold. In the first model, there are shock events at instant of time i (i = 1 , 2 , ...) , while in the second model at some time point there was no shock occurring event. Along with the work in this article, the system reliability formulas and the means and variances of their lifetimes are given under two different types shock models proposed, then simulation methods are adopted to analyze the reliability of the system for the second cumulative model. Finally, numerical examples and future researches are discussed. [ABSTRACT FROM AUTHOR]

For a multicomponent system, a maintenance strategy based on system structure updating and group importance measure is proposed. First, a system structure is determined by redefining its component grades, furthermore, the system structure updating is realized by introducing its survival signature. And based on the current system structure, a corrective maintenance that combines sequentially minimal repair with corrective replacement is formulated. Second, a two-level preventive maintenance (PM) is formulated based on a new group importance measure which is designed by considering two indicators, one is the system reliability calculated through its survival signature, the other is PM costs. The two indicators are calculated after its several components are updated preventively. Then, a cost-rate model is developed to find the optimal maintenance strategy. Finally, 6-component system and 10-component system are given to demonstrate the performance of the proposed strategy, and the result shows the strategy leads to significant profits when compared with existing strategies. [ABSTRACT FROM AUTHOR]

Network structures have been diffusely adopted in logistics systems, where the most critical target is completing the delivery within the promised timeframe. This paper focuses on a single commodity in a multistate intermodal logistics network (MILN) with transit stations and routes to involve three parameters: a route’s capacity, delivery time and time window. There is a carrier along each route whose number of available containers is multistate because the containers can be occupied by other customers. The delivery time consisting of the service time, travel time and waiting time varies with the number of containers and vehicle type. The arrival time at the transit station should be within the time window, the interval between the earliest and latest acceptable arrival times. This paper evaluates the system reliability, the probability that the MILN can successfully deliver sufficient amount of the commodity to meet market demand via several transit stations under the delivery time threshold and time windows. The system reliability can be treated as a delivery performance index and is evaluated with a proposed algorithm in terms of minimal paths. A practical case of scooter parts distribution between Taiwan and China is presented to emphasise the management implications of system reliability. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to minimize the fuel consumption of diesel-electric vessels using marine diesel generators as their energy source. The suggested method provides equal power distribution between the identical generators, taking into account the optimum fuel consumption resulting from electrical energy generation on board. The proposed approach was applied to a diesel-electric vessel model equipped with four 1900 kW generators and tested for power requirements between 380–6840 kW. Then, the power distribution and fuel consumption behaviors of the generators were examined. To verify the results of the study, the suggested method was compared with the genetic algorithm methodology. The results show that although the power distribution behavior between energy sources is different in both methods, they tend to meet the same power demand with almost similar fuel consumption. In addition, less fuel consumption could be achieved with the proposed approach for power needs in the range of 1520–1900 kW, 3230–3610 kW, and 4560–5320 kW. This means that, thanks to the proposed approach, both the fuel consumption of the generators and the problems that may occur due to the unbalanced power distribution of the electrical system can be minimized. [ABSTRACT FROM AUTHOR]

Probabilistic methods are increasingly used to quantify the effect of uncertainties on slope stability assessment. The shear strength reduction method can be used for slope stability analysis without prior assumption on the shape of the failure surfaces, and hence is an attractive method for slope stability analysis. Since it is computationally more demanding than limit equilibrium methods, reliability analysis based on the shear strength reduction method is often considered as computationally challenging. In this paper, an importance sampling method is suggested to conduct system reliability analysis of soil slopes based on the shear strength reduction method. In the suggested method, the design points are first identified using a response surface method. Then, a sampling function is constructed centred at the design points. An efficient method is used to identify the failure samples based on the shear strength reduction method. Results from two illustrative examples show that the suggested importance sampling method is an effective and robust tool for system reliability analysis of soil slopes. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing interest in comparing the reliability of systems with dependent components. Most of the recent works consider Archimedean copulas to define the dependency structure of systems and examine specific familiy of distributions. In this work, we provide distribution-free results to compare, in the usual stochastic order under some majorization conditions, coherent systems with heterogeneous and dependent components where the dependency structure can be defined by any copula. Applications of our main results for specific copulas and different families of marginal distributions are also given. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy-based assessment model to evaluate system reliability of a labour-intensive manufacturing system with repair actions. Due to the uncertainty in human performance, labour-intensive manufacturing systems must determine the capacity of each labourer in order to accurately characterise the performance of the systems. Therefore, we model such a manufacturing system as a fuzzy multi-state network in order to characterise the labourers’ influence on workstation performance. First, the workstation reliability is defined according to the loading state by three fuzzy membership functions, namely ‘under loading’, ‘normal loading’ and ‘over loading’, respectively. The system reliability is subsequently evaluated with fuzzy intersection operations in terms of these workstation reliabilities. Thus, the system reliability is defined as a fuzzy membership function to assess whether the manufacturing system performance is sufficient to satisfy the demand reliably. A case study of a footwear manufacturing system is illustrated to explain the proposed model. Furthermore, we apply the proposed model to a non-labour-intensive manufacturing network in order to validate the applicability to this class of systems. [ABSTRACT FROM PUBLISHER]

For a bridge, its columns or piers, which are the main seismically resistant members of the bridge, are generally retrofitted to improve seismic performance. However, retrofitting may cause unexpected damage to the non-retrofitted components/members. Therefore, a corresponding retrofitting of these components/members should be considered as part of any retrofitting method to eliminate unexpected damage. This work is to develop an estimating procedure of the seismic reliability of the system for a bridge considering the seismic reliability of each specified component/member. Additionally, the damage state of bridge for the system reliability analysis is built based on the engineering judgement. For the convenience of the calculation, the seven-point estimation method and the Nataf transformation method are combined to calculate the first four moment values of a specified limit state function in the moment-based system reliability analysis. For determining the retrofitting strategy, this work also presents a method for calculating the relationship between the resilience in functionality and seismic intensity that is achieved using a particular retrofitting method. Moreover, the system reliability and recovery time of each damaged component/member are considered in a resilience analysis. Finally, a bridge is selected as an example to demonstrate the application of this work. [ABSTRACT FROM AUTHOR]

There are many studies on standby redundant systems, since those are the most standard models for ensuring reliability in systems. Particularly, two-component priority standby redundant systems are one of the most fundamental and important redundant models in the reliability theory. In recent years, the procedure for evaluating the mean time to failure (MTTF) of the two-component priority standby redundant system has been proposed by using mixed Erlang distributions as approximate distributions. In this study, by expanding the idea on evaluating MTTF proposed in the previous research, an evaluation method for the variance of failure times (VOFT) in the two-component priority standby redundant system has been presented. Furthermore, we have proposed a procedure for deriving the reliability function in the system based on the maximum entropy principle by utilizing MTTF and VOFT. Through some numerical applications, the validity of the procedures for deriving the reliability function developed in this study has been shown. [ABSTRACT FROM AUTHOR]

This paper develops a three-phase procedure to measure the performance of a highly value-added footwear manufacturing system taking reworking actions into account, in which the system consists of multiple production lines. We mainly address the system reliability as a performance indicator to evaluate the possibility of demand satisfaction. First, we construct the manufacturing system as a manufacturing network by graphical transformation and decomposition. Second, capability analysis is implemented to determine the input flow of each station based on the manufacturing network. Third, a simple algorithm is proposed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. We evaluate the system reliability in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy. Whenever the system state changes, the proposed performance evaluation procedure can be implemented easily and flexibly. [ABSTRACT FROM PUBLISHER]

From the perspective of network analysis, the manufacturing system can be constructed as a stochastic-flow network, since the capacity of each machine is stochastic (i.e. multistate) owing to the failure, partial failure, and maintenance. Considering reworking action and different failure rates of machines, the input flow (raw materials/work in process) processed by each machine might be defective, and therefore the output flow (work in process/products) would be less than the input amount. To evaluate the capability of the manufacturing system, we measure the probability that the manufacturing network can satisfy demand. Such a probability is defined as the system reliability. A decomposition method is first proposed to divide the manufacturing network into one general processing path and one reworking path. Subsequently, two algorithms are utilised for different network models to generate the lower boundary vector of machine capacity to guarantee that the manufacturing network is able to produce sufficient products fulfilling the demand. The system reliability of the manufacturing network can be derived in terms of such a capacity vector afterwards. [ABSTRACT FROM PUBLISHER]

This paper is concerned with system reliability improvement at as early as the system's embodiment design stage. Design decisions made at this stage, including component reliability specifications, will have long-term impacts on the entire lifecycle of the system, but they are also difficult to make because the knowledge of system and/or subsystem performance is most likely incomplete at this moment. Thus the system reliability function cannot be fully defined analytically. Because of this inherent uncertainty at early design stage, the traditional reliability evaluation methods, which assume deterministic reliability-wise structures and component reliability specifications, may not be appropriate in real-world applications. In this paper, a Nonparametric Bayesian Network (NPBN) approach is proposed to tackle such challenges at early design stage. The proposed method can represent the uncertainty in the structure of system reliability by combining any available information of component performance in some similar or past-generation systems. This approach can partially quantify the reliability function of the system under design and propose design change recommendations in order to achieve the targeted system reliability level. [ABSTRACT FROM AUTHOR]

Reliability assessment is an indispensable task in risk-based corroding ship maintenance planning. For simplicity and computational efficiency it is commonly assumed that the reliability of a ship is computed as a component-based reliability problem defined by the plastic collapse of the one-bay section at mid-ship. However, this assumption may underestimate the likelihood of ship failure since there are many bays of sections subjected to very high vertical bending moments near the mid-ship and the failure of any section can lead to the loss of the entire ship. The failures of the individual one-bay sections are spatially dependent due to the spatial variability of variables, such as corrosion and yield strength, among others. Therefore, system-based reliability is more appropriate for describing the safety level of ships under uncertainty. This paper utilises an improved first-order reliability method (FORM) recently developed to assess ship system reliability. The methodology developed is demonstrated on a double hull girder tanker subjected to corrosion. The effect of the spatial dependence among the variables associated with different sections on the computed failure probability of the ship is studied by parametric analysis. The results indicate that the dependence of the model error for predicting the bending capacity associated with different sections impacts the failure probability significantly, and the underestimation of this probability can be non-trivial if only a single one-bay section is considered. [ABSTRACT FROM AUTHOR]

Maintenance is indispensable for ensuring that multi-component systems successfully complete the next mission. Maintenance activities require an enormous amount of energy consumption in engineering problems. For selective maintenance, many studies focus on the trade-off between system reliability and other resources, such as time and cost. The enormous energy consumption of maintenance processes has been ignored in previous research. In this work, a novel energy consumption model considering the actual maintenance process is proposed. Moreover, system reliability is added to the optimization model as a crucial constraint, which makes the optimization process of energy consumption meaningful. The selective maintenance process is a complex combinatorial optimization problem. Hence, a hybrid differential evolution and gravitational search algorithm (DGSA) is proposed to solve the selective maintenance problem considering energy consumption. In addition, several experiments with DGSA, particle swarm optimization and differential evolution are designed to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In the case where strength and stress both follow exponential distributions, this paper considers the maximum likelihood estimator (MLE) of the system reliability based on L ranked set sampling (LRSS). The proposed MLE is shown to have existence, uniqueness and asymptotic normality, and its asymptotic variance is obtained by the Fisher information matrix of LRSS. The values of asymptotic relative efficiencies show that the proposed MLE is always more efficient than the MLE using simple random sampling (SRS). However, the MLE using LRSS cannot be written in closed form. Therefore, the modified MLE is proposed using the technique replaced some terms in the maximum likelihood equations by their expectations. The newly modified MLE using LRSS is shown to be superior to the MLE using SRS. Finally, the proposed method is applied to a real data set on metastatic renal carcinoma study. [ABSTRACT FROM AUTHOR]

Estimating system reliability has been recognized as a critical step in reliability-based design optimization for structural systems. The estimation of system reliability entails multi-dimensional integration, which is very difficult and numerically expensive. The proposed hybrid method integrates the concepts of saddlepoint approximation, the dimension reduction method (DRM) and copulas. The moment-based saddlepoint approximation enhanced by the DRM is used to calculate the component reliability. The copula method is adopted to realize the joint failure probability modelling between two failure modes. Reliability-based sensitivity analysis for the reliability-based robust design optimization is carried out as well. The structural system optimization model is established, including the Euclid norm of the reliability sensitivity as an optimization objective and system reliability as a constraint. Examples demonstrate that the optimization results obtained by the proposed approach ensure the maximization of the robustness of the structural system. [ABSTRACT FROM AUTHOR]

Multi-state systems (MSS) are systems whose stochastic degradation process is characterised by several performance levels varying from nominal functioning to complete failure. MSS arise naturally in many application areas. MSS reliability evaluation and estimation has received much attention from researchers and a wide range of papers dealing with MSS have been published. In this paper, an approach based on Kronecker algebra combined with stochastic processes is proposed to evaluate the reliability of a series–parallel MSS. The main advantage of the proposed approach is that the mathematical expressions of the MSS reliability indices are derived from data of individual elementary components without generating the whole, possibly huge, MSS state space. Furthermore, the approach is well formalised and easy to implement thanks to Kronecker algebra operators. Examples are given to illustrate the proposed approach. [ABSTRACT FROM PUBLISHER]

Research on reliability for balanced systems has become an important issue in the reliability field; it is being intensively studied both in theory and applications. The concept of balance has many implications, which results in various balanced systems needing to be studied in reliability modelling, analysis and optimization and so on. In the present article, two balanced reliability systems are introduced and their reliability models are developed, then formulas for system reliability, probability density functions, and moments of lifetimes under two models are obtained using the results in aggregated stochastic processes or phase-type distributions for two-dimensional and high-dimensional situations. In addition, a matrix operator, the Kronecker product operator, is used to create concise forms for the related formulas. An algorithm for computing these reliability indexes is given to facilitate use. Some examples including symbolic and numerical ones for the simplest case, the two-dimensional situation, are shown to illustrate the presented results. The presented work may shed light on future research on reliability and safety for balanced systems under different concepts of balance. [ABSTRACT FROM AUTHOR]

Reliability analyses of nail pullout, nail-in-tension, and system reliability of internal limit states are presented for both permanent and temporary soil nails that are designed using default Federal Highway Administration nail load and resistance models within traditional deterministic allowable stress design (ASD) framework. The model uncertainty, correlations between soil strength parameters, between model factor, and nominal load term, and between the two internal limit states, and influence of model factor fittings are all addressed in the analyses. This study provides a general idea of the reliability that is implicitly embedded in current ASD-based soil nail internal limit state designs. [ABSTRACT FROM AUTHOR]

The performance of certain critical complex systems, such as the power output of ground photovoltaic (PV) modules or spacecraft solar arrays, exhibits a multi-phase degradation pattern due to the redundant structure. This pattern shows a degradation trend with multiple jump points, which are mixed effects of two failure modes: a soft mode of continuous smooth degradation and a hard mode of abrupt failure. Both modes need to be modeled jointly to predict the system residual life. In this paper, an autoregressive moving average model-filtered hidden Markov model is proposed to fit the multi-phase degradation data with unknown number of jump points, together with an iterative algorithm for parameter estimation. The comprehensive algorithm is composed of non-linear least-square method, recursive extended least-square method, and expectation-maximization algorithm to handle different parts of the model. The proposed methodology is applied to a specific PV module system with simulated performance measurements for its reliability evaluation and residual life prediction. Comprehensive studies have been conducted, and analysis results show better performance over competing models and more importantly all the jump points in the simulated data have been identified. Also, this algorithm converges fast with satisfactory parameter estimates accuracy, regardless of the jump point number. [ABSTRACT FROM AUTHOR]

The cables in a cable-stayed bridge are critical components supporting the long-span girders and ensuring their functionality. However, cables are prone to fatigue damage and atmospheric corrosion, which directly affect the bridge safety. This study presents a framework for system reliability evaluation of in-service cable-stayed bridges subjected to cable degradation. The effect of cable strength degradation on the system reliability is demonstrated through simulation on a parallel-series system representation. Learning machines are utilised to approximate the non-linear and dynamic response functions of critical components due to cable rupture, and the system reliability is finally evaluated from the event tree established by the β-unzipping method. Both short-span and long-span cable-stayed bridges are selected as prototypes to investigate the influence of cable degradation on the system reliability. On this basis it is revealed that cable degradation can significantly influence the collapse mechanism of a cable-stayed bridge and thereby lead to a significant reduction in the system reliability. This phenomenon is associated with cable spacing, where a spare cable system seems more sensitive to cable gradation. It is demonstrated that the consideration of cable corrosion and correlation is essential for lifetime safety evaluation of in-service cable-stayed bridges. [ABSTRACT FROM AUTHOR]

Many key aspects of bridge design are governed by site-related, geometric, functional and constructional constraints. Economy is yet another decisive factor in public works, whilst enhanced sensitivity to aesthetics is driving the demand for more than merely utilitarian structures. Such exacting boundary conditions often spur careful or even innovative structural design. Since the successful translation of numerous constraints into a reliable, functional, cost-effective structure with aesthetic appeal is primarily a question of sound conceptual design, the importance of this step in the design process as a whole cannot be overstated. This paper summarises the more prominent aspects of conceptual bridge design, particularly in connection with meeting and duly balancing non-standardised economy- and aesthetics-related objectives. Taking the outcome of the conceptual design stage as a starting point, the paper also addresses the use of digital design tools for the development of other construction documents. By way of illustration, the ideas underlying the conceptual design for the Butarque footbridge in Leganés, Spain are discussed, in connection primarily with the specific boundary conditions but also with the actual layout, detailing and construction. The example shows that a modern, technologically advanced design may be compatible with a solution whose elegance meets the most exacting aesthetic standards. It also shows that when the conceptual approach is well thought out, the solution is subject to only minor change in subsequent design stages. [ABSTRACT FROM AUTHOR]

The present study evaluated three automation modes for improving performance in an X-ray luggage screening task. One hundred and forty participants were asked to detect the presence of prohibited items in X-ray images of cabin luggage. Twenty participants conducted this task without automatic support (control group), whereas the others worked with either indirect cues (system indicated the target presence without specifying its location), or direct cues (system pointed out the exact target location) or adaptable automation (participants could freely choose between no cue, direct and indirect cues). Furthermore, automatic support reliability was manipulated (low versus high). The results showed a clear advantage for direct cues regarding detection performance and response time. No benefits were observed for adaptable automation. Finally, high automation reliability led to better performance and higher operator trust. The findings overall confirmed that automatic support systems for luggage screening should be designed such that they provide direct, highly reliable cues.Practitioner summary: The present study confirmed previous findings showing better detection performance in X-ray images of luggage when supported by automation providing direct, highly reliable cues. Furthermore, participants used adaptable automation only to select their preferred level of automation. This behaviour did not provide the benefits expected under adaptable automation. [ABSTRACT FROM AUTHOR]

This article presents a three-stage approach for solving multi-objective system reliability optimization problems considering uncertainty. The reliability of each component is considered in the formulation as a component reliability estimate in the form of an interval value and discrete values. Component reliability may vary owing to variations in the usage scenarios. Uncertainty is described by defining a set of usage scenarios. To address this problem, an entropy-based approach to the redundancy allocation problem is proposed in this study to identify the deterministic reliability of each component. In the second stage, a multi-objective evolutionary algorithm (MOEA) is applied to produce a Pareto-optimal solution set. A hybrid algorithm based on k-means and silhouettes is performed to select representative solutions in the third stage. Finally, a numerical example is presented to illustrate the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

Prediction of the service lifetime of concrete structures with respect to chloride ingress involves a number of parameters that are associated with large uncertainties. Hence, full-scale measurements are strongly in demand. This paper begins by summarizing statistical distributions based on measurements taken from the Gimsøystraumen Bridge in Norway. A large number of chloride profiles are available based on concrete coring samples, and for each of these profiles the diffusion coefficient and surface concentration (due to sea spray) are estimated. Extensive measurements of the concrete cover depth are also performed. The probability distributions are input into a prediction model for chloride concentration at the steel reinforcement. By also introducing the critical chloride concentration as a random variable, the probability of exceeding the critical threshold is determined as a function of time. To address chloride attack on the entire bridge, a system model with 90 components is introduced. Reliability updating based on observations at multiple sites along the bridge is also investigated. First-order reliability methods typically become inaccurate for large systems of this type, so an enhanced Monte Carlo simulation method is applied. It is shown that the corresponding computation time is significantly reduced compared to crude Monte Carlo methods. [ABSTRACT FROM AUTHOR]

It is aimed to propose a copula based systematic quantitative method for system reliability analysis of engineering structures considering multiple dependent failure modes. The principles of the moment matching method, the copula theory and the bound theory are combined to achieve the purpose. As the very first step, the moment estimation of the limit state function of each component is calculated by anchored ANOVA (Analysis of Variance) expansion. The third moment saddle point approximation is then applied to derive the distribution of each performance function and evaluate the reliability index with obtained moments. By introducing copula functions into the narrow bounds theory, the traditional reliability method is improved. The best-fitting copula function is determined to ensure the accuracy of the joint probabilistic modeling between the dependent failure modes. A novel feature of the proposed method is the use of the copula concept, instead of traditional numerical integration commonly used in the joint failure probability estimation. Examples are presented to illustrate the accuracy and applicability of the presented method. [ABSTRACT FROM AUTHOR]

Civil infrastructure systems provide physical supports to a community’s functionalities and are expected to achieve acceptable safety levels subjected to extreme load effects. However, these systems may deteriorate with time as a result of aggressive environmental or operating conditions in service, implying that the system reliability may decline beyond the baseline as assumed for design. Moreover, the increasing trend of the external loads may also contribute to the reduction of the system reliability. In this paper, a semi-analytical method is proposed for assessing the reliability of aging systems subjected to non-stationary loads. The series system is considered, where the system failure is defined as the failure of any single component (structure) among the system. The application of the proposed method is illustrated using a representative series bridge network with several individual bridges. The role of parameters such as the variations in the load intensity, resistance correlation and number of components under attack in the system reliability are investigated. [ABSTRACT FROM PUBLISHER]

The low- and intermediate-level radioactive wastes are generally disposed in near-surface disposal facility (NSDF). The NSDF is composed of engineered barriers. The probabilistic safety assessment model has been developed to analyse the performance of NSDF. The endpoints of the assessment are the concentration of the radionuclide in the groundwater and the corresponding dose rate of the radionuclide. The barrier system can have multiple failure modes but practically the possible failure modes are failure of top cover, failure of waste container, degradation of waste form and failure of bottom cover, which are usually considered as independent failure events. Through a sensitivity analysis, the most critical parameters affecting the design reliability for failure criteria are identified as the groundwater velocity and distribution coefficient. The study shows that for the NSDF considered, there is a high degree of dependence between the failure modes, and demonstrates the probability of the simultaneous occurrence of failures. Thus, the need to consider the system reliability in the NSDF is highlighted. The study also advocates the use of optimisation techniques to evaluate the probability of failure, which provides a better estimate of the probability of failure, as validated from the results obtained from Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

A methodology that employs the first-order reliability method is proposed to evaluate the time-dependent system reliability of a segment of a pressurised steel pipeline containing multiple active corrosion defects. The methodology considers the leak and burst failure modes of the pipe segment and takes into account the correlations among limit state functions at different corrosion defects. The methodology involves first constructing two linearised equivalent limit state functions for the pipe segment in the standard normal space and then evaluating the probabilities of leak and burst of the segment incrementally over time based on the equivalent limit state functions. The applicability and accuracy of the proposed methodology is illustrated through system reliability analyses of three pipeline examples, each containing ten active corrosion defects whose growth over time is characterised by the linear, nonlinear and homogeneous gamma process-based models. [ABSTRACT FROM PUBLISHER]

Themain purpose of this article is to introduce the E-Bayesian approach to gain flexibility in the reliability-availability system estimation. This approach will be used in series systems, parallel systems, and k-out-ofm systems, based on exponential distribution under squared error loss function, when time is continuous. We use three prior distributions to investigate its impact on the E-Bayesian approach, those prior distributions cover a big spectrum of possibilities. We showin real examples and also by simulations, howthe procedure behaves. In the simulation study alsowe explore the impact on this estimation approach, when the number of components of the system increases. [ABSTRACT FROM AUTHOR]

Current life-critical system designs fully incorporate digital instrumentation and control systems. Due to safety significance of such systems, these need to be designed carefully to ensure their safety requirements. However, digital systems have some unique characteristics, such as using software, and may have different failure causes and/or modes than the analog systems; hence, their incorporation into life critical systems, safety analysis entails special challenges. The strategy to perform safety analysis using Petri net for full proof design is discussed in this paper. The technique is demonstrated on a safety critical system of nuclear power plant. [ABSTRACT FROM AUTHOR]

Many engineering systems have multiple components with more than one degradation measure which is dependent on each other due to their complex failure mechanisms, which results in some insurmountable difficulties for reliability work in engineering. To overcome these difficulties, the system reliability prediction approaches based on performance degradation theory develop rapidly in recent years, and show their superiority over the traditional approaches in many applications. This paper proposes reliability models of systems with two dependent degrading components. It is assumed that the degradation paths of the components are governed by gamma processes. For a parallel system, its failure probability function can be approximated by the bivariate Birnbaum–Saunders distribution. According to the relationship of parallel and series systems, it is easy to find that the failure probability function of a series system can be expressed by the bivariate Birnbaum–Saunders distribution and its marginal distributions. The model in such a situation is very complicated and analytically intractable, and becomes cumbersome from a computational viewpoint. For this reason, the Bayesian Markov chain Monte Carlo method is developed for this problem that allows the maximum likelihood estimates of the parameters to be determined in an efficient manner. After that, the confidence intervals of the failure probability of systems are given. For an illustration of the proposed model, a numerical example about railway track is presented. [ABSTRACT FROM AUTHOR]

Unreliability of water systems has become a major concern in many developing countries. A referendum-format contingent valuation (CV) survey was implemented to investigate household preferences, in monetary terms, for improved water services in the small town of San Lorenzo, Guatemala. A random sample of 500 households report that they currently adopt a variety of averting measures (e.g. in-home water storage and treatment) to cope with service interruptions and low water quality. Findings also indicate that households are willing to pay an increase of more than 200% in their water bill for reliable supplies of safe drinking water. [ABSTRACT FROM AUTHOR]

In this study, a support vector regression (SVR) model is developed for reliability estimation. An imperialist competitive algorithm is applied for selecting the SVR parameters such as ∁,. The proposed model is validated by applying it to a benchmark data set. Satisfactory performance of the proposed model with respect to the data set is demonstrated through a comparative study. A shearing machine operating at an electric tableau manufacturing company is considered a case study. A set of data representing the time-to-failure (TTF) of the shearing machine is used to calculate the cumulative TTF for reliability modelling. The experimental results indicate that the proposed model achieves high estimation accuracy. [ABSTRACT FROM AUTHOR]

Components in cold-standby state are usually assumed to be as good as new when they are activated. However, even in a standby environment, the components will suffer from performance degradation. This article presents a study of a redundancy allocation problem (RAP) for cold-standby systems with degrading components. The objective of the RAP is to determine an optimal design configuration of components to maximize system reliability subject to system resource constraints (e.g. cost, weight). As in most cases, it is not possible to obtain a closed-form expression for this problem, and hence, an approximated objective function is presented. A genetic algorithm with dual mutation is developed to solve such a constrained optimization problem. Finally, a numerical example is given to illustrate the proposed solution methodology. [ABSTRACT FROM PUBLISHER]

Consider a finite sequence of independent binary (zero-one) random variables ordered on a line or on a circle. The number of the ℓ-overlapping runs of ones of a fixed length k is studied for both types of the concerned ordering. Recurrences for the exact probability mass functions for these numbers are obtained via simple probabilistic arguments. Exact closed formulae, for the mean and variance of the studied numbers are obtained via their representations through properly defined indicators. Two application case studies, concerning record sequences and reliability of consecutive systems, clarify further the theoretical results. [ABSTRACT FROM PUBLISHER]

This paper investigates the effects of post-failure material behaviour on redundancy factor for the design of structural components in nondeterministic systems. The procedure for evaluating the redundancy factors of components of ductile and brittle nondeterministic systems is demonstrated using systems consisting of two to four components. The effects of the number of brittle components in a mixed (ductile–brittle) system and the post-failure behaviour factor on the redundancy factor are also studied using these systems. An efficient approach for simplifying the system model in the redundancy factor analysis of brittle systems with a large number of components is proposed. In order to generate standard tables to facilitate the design process, the redundancy factors and the associated component reliability indices of nondeterministic ductile and brittle systems with large number of components are calculated considering three correlation cases and two probability distribution types. Finally, a bridge example is used to demonstrate the application of the redundancy factor in the design of steel girders taking into account their post-failure behaviour. [ABSTRACT FROM PUBLISHER]