Structural System Reliability Research Articles

Fuzzy reliability of a turbines structure system using the right triangular fuzzy number

PurposeThe purpose of this paper is to investigate the performance of a turbine structure of the oil and gas Egyptian company in terms of reliability, mean time to failure (MTTF), mean time to repair (MTTR) and mean time between failures (MTBF) under fuzzy environment and working criteria. This paper examines the impact of the failure of various components on the complete turbine structure of the oil and gas system.Design/methodology/approachTo overcome the problem of uncertain behavior of available data for various components, the right triangular generalized fuzzy number (RTrGFN) is proposed to be taken into the account to express the uncertainty which attains some tolerance in data. Furthermore, reliability indices are calculated with the help of the Lambda Tau method and the arithmetic operations on right generalized triangular fuzzy numbers (RTrGFN).FindingsThis paper explores the reliability of a repairable 3 out of 4 structure of turbines and along with the other parameters namely MTTF, MTTR and MTBF; under a fuzzy environment. Failure rates and repair times are expected to be exponential. The ranking of components of the structure is being found to decide the priority for maintenance.Originality/valueThis paper investigates the performance of the system with different spread/tolerance like 15%, 25% and 50% of crisp data. It helps to predict realistic results in the range value. To enhance the system's performance, the most important item of the system requires greater attention. For this, the authors find the sensitive part by ranking. For ranking, an extended approach has been developed to find the sensitive unit of the system by using the right triangular generalized fuzzy number. This paper explores the most and least sensitive component of the system, which helps the maintenance department to plan the maintenance action.

Time-dependent structural system reliability analysis model and its efficiency solution

For the widely existing time-dependent structural system (TDSS), the current model ignores the interaction among multiple modes in the minimum transformation of the performance function of each mode w.r.t. the time, it may misjudge the state of the system at some instants and result in the error of estimating the reliability. To avoid this possible mistake, this paper proposes an improved reliability analysis model for the TDSS. In the proposed model, the TDSS performance function is transformed into the single-mode time-dependent performance function firstly according to the relationship of multiple modes. Then the failure probability of the TDSS can be estimated by the single-mode time-dependent performance function. The relationship of multiple modes is strictly considered in the proposed model. On the basis of the improved model, this paper also presents the Kriging surrogate model combined with the Monte Carlo simulation method to estimate the failure probability of the TDSS. In this Kriging method, the initial training samples are uniformly selected in the sample space and a new extremum learning function is proposed. Theoretical analysis verifies the rationality of the proposed reliability analysis model, and the efficiency of the proposed method is illustrated by the results of numerical examples.

Structural system reliability analysis based on multi-modal optimization and saddlepoint approximation

This paper studies reliability analysis of structures with multiple failure modes. The analysis consists of three parts. First, the memetic animal migration optimization algorithm, applied for multiple optimum points detection in a multimodal optimization problem, is used to search for the most probable points of the limit state functions of main failure modes. Next, the multi-point first-order reliability method is used to estimate the failure probability of structures with multiple failure modes. Last, the saddlepoint approximation based second-order reliability method is further extended to system reliability analysis, aiming to improve the accuracy of system reliability prediction.

An uncertainty-based structural design and optimization method with interval Taylor expansion

There are uncertain factors affecting structural performance in actual engineering. The uncertainty-based design and optimization (UBDO) is an effective strategy to deal with these uncertain factors and improve the reliability of structural systems. In UBDO, some non-probabilistic uncertainties are difficult to be described with a certain distribution information. In this situation, the interval uncertainty analysis (IUA) can be utilized to perform the reliability evaluation in UBDO. Generally, if IUA was performed directly in UBDO, the efficiency of UBDO with IUA (UBDO-IUA) cannot satisfy the requirements of actual engineering. To tackle this problem, in this study, an UBDO-IUA strategy based on the Taylor expansion is proposed. The particle swarm global optimization algorithm is also introduced in the given method as the optimization solver to further improve the computational efficiency. Two examples are introduced to show the utilization of the given method.

Assessing the Structural Characteristics of the Japanese Version of the Adult Social Care Outcomes Toolkit for Carers

Due to the absence of standardized Quality of Life (QoL) measures for informal family caregivers of recipients of long-term care (LTC) in Japan, translation and cross-cultural adapted LTC outcome measures are needed for research and evaluation. In this study, we assessed the validity and reliability of the factor structure and response system of the translated and cross-culturally adapted Japanese version of the Adult Social Care Outcomes Toolkit for Carer (J-ASCOT-Carer). Participants were 872 informal family caregivers of adults who lived at home and required LTC services. Almost half (46%) of the participants were between 50 and 59 years old, 85% were employed, and 69% resided with their care recipients. We used the combined factor analysis and item response theory approach. Model fit indices included factor loading, path coefficients, root mean square error of approximation, standardized root mean square residual, and comparative fit index. This study confirmed the one factor structure that was identified in the original English version of the ASCOT-Carer. The values for the model fit indices indicated a good fit. Moreover, the validity and reliability of the response system were confirmed. Therefore, the J-ASCOT-Carer is a reliable assessment instrument to measure QoL of Japanese caregivers of adults requiring LTC.

SYSTEM RELIABILITY UPDATING BASED ON THE REJECTION SAMPLING ALGORITHM

It studies the updating model of the reliability for structural systems considering the observation information and the corresponding rejection sampling strategy. The updating model of failure probabilities for structural systems is established based on the Bayesian theory. According to the type of observation information (i.e., inequality observation information and equality observation information), the likelihood function and the posterior probability density function for random variables are derived. The rejection sampling strategy of posterior samples for random variables is determined based on the observation information domain, and the efficiency of the rejection sampling strategy is illustrated. The estimated value and its standard deviation of updated failure probabilities for structural systems are formulated. To verify the availability of the proposed method, the failure probabilities of plane frames are updated based on the plastic theory considering various observation information. The results indicate that the conditional failure probability of the structural systems considering the observation information is the integral of the posterior joint probability density of random variables in the failure domain. The strategy is feasible for selecting the prior samples which satisfy the constructed observation information domain as the posterior samples for random variables. The proposed sampling strategy can be used to update the reliability of structural systems with multiple random variables and multiple types observation information. The updated failure probabilities of structural systems decrease as the detection values of the resistance-related random variables increase or as the proofed loads increase. To reduce the uncertainties of the observation information, standard derivations of detection error for resistance-related random variables should be well controlled.

Structural System Reliability: Overview of Theories and Applications to Optimization

This paper provides an overview of theories and applications of structural system reliability (SSR). The paper defines SSR problems and discusses the growing needs for SSR analysis and technical challenges. Detailed literature reviews are provided for three subtopics: SSR methods for Boolean system events, SSR methods for sequential failures, and SSR-based design/topology optimization. Discussions of each subtopic define the target problem using mathematical formulations and categorize existing SSR methods in terms of the characteristics of the problems and approaches. The paper summarizes SSR methods that are considered critical in the history and have introduced notable technological developments in recent years. In each subtopic or category, the reviewed methods are compared with each other in terms of accuracy, computational efficiency, and implementation issues to allow identifying apposite methods for SSR applications. The paper concludes with remarks on future research needs and opportunities.

Analysis and design of emergency field isolation hospital building using innovative rapidly construction prefabricated units to treat patients infected with COVID-19

Coronavirus pandemic is the most catastrophic phenomena of nature. In a major disaster which affected substantially to human lifecycle and property loss. Instant rehabilitation for the people affected with coronavirus was essential. As an immediate measure, it led to the application of light-gauge steel within Saudi Arabia for quick construction, in addition for the safety purposes during disaster in the forthcoming. Several hospital buildings with changeable categories of earthquake and seismic performance design needs are present. Broadly, the earthquake performance is categorized into two types: structural and non-structural, either under unsatisfactory conditions can be dangerous to occupants in the building once damage occurs. The deprivation in structural support of hospital building’s systems (i.e. lateral and vertical force resisting systems) like frames and walls in the hospital building comes under structural damage, whereas the non-structural damage means the damage which doesn’t affect the structural support system reliability such as pipes damage and pumps disruption, window breaking, breakdown of chimney viz. Furthermore, the non-structural damage is life intimidating also uneconomical.

An efficient dominant failure modes search strategy and an extended sequential compounding method of system reliability analysis and optimization

The structural system is a complex structural form in engineering practice. Under the condition of uncertainty, multiple failure modes may happen simultaneously and lead to the failure of the overall structure. To identify the dominant failure modes of structural systems, this paper proposes a dominant failure mode search method based on the differential evolution algorithm, which generates sample points on the limit state surface and uses the differential evolution algorithm to evolve. It can search for several dominant failure modes of structural systems without much structural analysis function calls. For the evaluation of the reliability of structural systems, this paper further proposes an extended sequential compound method, which can solve the correlation coefficients between compound events and its internal events. Therefore, it can calculate the failure probability for various failure modes and the correlation coefficient between failure modes simultaneously. Besides, a system reliability-based design optimization method is proposed under the framework of the reliability index method with an analytical method for solving the gradient of the system reliability index. Finally, several numerical examples are given to verify the efficiency and accuracy of the proposed methods.

A variable and mode sensitivity analysis method for structural system using a novel active learning Kriging model

In the frame of structural system reliability, quantifying the impact degree of random variables and failure modes on system output is indispensable. A generalized variable sensitivity analysis (VSA) index is introduced for measuring the effect of each random variable. Then a mode sensitivity analysis (MSA) index is proposed for quantifying the effect of each failure mode on system failure probability. Additionally, to estimate the system failure probability, VSA and MSA indices efficiently, a novel active learning Kriging model combined with the system importance sampling (SIS) density function is proposed for structural systems. The SIS density function is obtained by kernel density estimation-based importance sampling and weighted coefficients of failure modes, which is employed for generating the candidate population to reduce the computational cost on predicting the enormous candidates. The proposed called ALK-SIS model can precisely and effectively deal with small failure probability events as well as multiple most probable point problems, and estimate the system failure probability and sensitivity indices without calling the performance functions additionally. Four case studies are investigated to demonstrate the significance of proposed VSA and MSA indices on system reliability as well as the efficiency and accuracy of the ALK-SIS.

A PDEM-based perspective to engineering reliability: From structures to lifeline networks

Research of reliability of engineering structures has experienced a developing history for more than 90 years. However, the problem of how to resolve the global reliability of structural systems still remains open, especially the problem of the combinatorial explosion and the challenge of correlation between failure modes. Benefiting from the research of probability density evolution theory in recent years, the physics-based system reliability researches open a new way for bypassing this dilemma. The present paper introduces the theoretical foundation of probability density evolution method in view of a broad background, whereby a probability density evolution equation for probability dissipative system is deduced. In conjunction of physical equations and structural failure criteria, a general engineering reliability analysis frame is then presented. For illustrative purposes, several cases are studied which prove the value of the proposed engineering reliability analysis method.

Reliability evaluation and importance analysis of structural systems considering dependence of multiple failure modes

Many modern structural systems usually consist of multiple failure modes. One failure mode may affect other failure modes due to the same working environment and random input variables, meaning that these failure modes are not independent. The assumption of independence among failure modes simplifies the calculation of reliability of structural systems, but it adds approximation error. Different from the dependence between two failure modes, the dependence of multiple failure modes is more complicated. In this paper, on the basis of vine copula function, which is a flexible tool to describe the multivariate dependence, the dependence of multiple failure modes of the structural systems is mainly studied and analyzed. Then Rosenblatt transformation and Monte Carlo simulation method are utilized to evaluate the reliability of structural systems. Furthermore, in order to research the importance of failure modes, two indices combined with empirical copula functions are extended, which can quantitatively measure the importance of failure modes. The multiple failure modes can be ranked based on proposed importance analysis, and the ones that have greater influence on the system can be found out, thus simplifying the system analysis. Finally, in order to confirm the applicability and rationality of the proposed method, an engineering case about a mechanism system with five failure modes is presented.

Time-Dependent Reliability Analysis of Oil Derrick Structures in Mechanism Failure Mode

Most research studies on the reliability of oil derrick structures have focused on static reliability analysis. Strength degradation with time of oil derrick structures and mechanism failure should also be considered in reliability analysis. In order to address this issue, we propose a new time-dependent reliability analysis method for oil derrick structures in mechanism failure mode and apply it to a tower derrick structure. We used the Monte Carlo finite element method to compute the static failure probability of each derrick component, and steps were employed to determine the main failure mechanisms. The time-dependent failure probabilities of each derrick component in the main failure mechanisms were calculated by the total probability theorem. The time-dependent reliability of a derrick structure system was obtained by considering the system as a series of parallel subsystems. A tower derrick example was used to demonstrate the accuracy and applicability of the proposed method. The results revealed that the proposed method is accurate and reliable.

Evaluation of wind directionality on wind load effects and assessment of system reliability of wind-excited structures

This study re-evaluate wind directionality effect on various structural responses having distinct directionality characteristics using a relatively simple but sufficiently accurate approach with closed-form estimation of response with a given mean recurrence interval. The approach is established on the basis that the directional yearly maximum responses observed at different hours can be assumed to be mutually independent at the distribution upper tail region, even when the directional yearly maximum wind speeds can be correlated to some extent. This study also evaluates the performance of AIJ procedure and traditional sector-by-sector approach through comprehensive case studies. Furthermore, this study presents an analysis framework for assessing overall reliability/risk of a wind-exited structure associated with multiple limit state responses. The limit state responses can be considered to be mutually independent especially in the distribution upper tail region and when the wind directionality is further considered. Therefore, the failure probability associated with multiple limit state responses can be estimated as the sum of those associated with each response at each wind direction. The characteristics of failure probability influenced by wind directionality and structural orientation are investigated. This study also highlights the sensitivity of failure probability estimation to assumed probability distribution model of extreme response.

Reliability Analysis of Large Span Cable-stayed Bridges Based on Support Vector Machine

a method of combining the support vector machine and the intelligent algorithm to perform reliability analysis on large span cable-stayed bridges was proposed in this paper. The algorithm is verified by an example, which shows that the algorithm has higher precision and can be extended to the actual project. Therefore, this paper takes Jiangmen North Street Waterway Bridge as the engineering background, uses the finite element software ANSYS to establish the cable-stayed bridge model and MATLAB software to compile the intelligent algorithm and data processing. It mainly analyzes the reliability of the main beam mid-span deflection, the cable stress and main tower stress of the North Street Waterway Bridge. Finally, the general limit range method is used to estimate the reliability index of the North Street waterway bridge structure system. The results show that the cable stay failure has the greatest impact on the reliability of the entire structural system, so it is necessary to pay attention to the maintenance and monitoring of stay cables.

System Reliability Analysis of an Offshore Jacket Platform

This study investigates strategies for solving the system reliability of large three-dimensional jacket structures. These structural systems normally fail as a result of a series of different components failures. The failure characteristics are investigated under various environmental conditions and direction combinations. The β-unzipping technique is adopted to determine critical failure components, and the entire system is simplified as a series-parallel system to approximately evaluate the structural system reliability. However, this approach needs excessive computational effort for searching failure components and failure paths. Based on a trained artificial neural network (ANN), which can be used to approximate the implicit limit-state function of a complicated structure, a new alternative procedure is proposed to improve the efficiency of the system reliability analysis method. The failure probability is calculated through Monte Carlo simulation (MCS) with Latin hypercube sampling (LHS). The features and applicability of the above procedure are discussed and compared using an example jacket platform located in Chengdao Oilfield, Bohai Sea, China. This study provides a reference for the evaluation of the system reliability of jacket structures.

Seismic reliability analysis and estimation of multilevel response modification factor for steel diagrid structural systems

Diagrid systems are emerging as one of the structurally efficient and architecturally aesthetic solutions for tall buildings. Despite the fact that such systems are increasingly used in modern construction, current literature lacks detailed information regarding their structural behaviour and seismic design parameters to ensure satisfactory performance under different earthquake intensity levels. This study aims to assess the seismic reliability of diagrid structural systems and develop more efficient performance-based design methodologies. Demand and supply response modification factors are calculated for 16, 24 and 32-storey buildings with diagrid structural systems using 65° diagrid angle and designed in compliance with current standards under a set of 12 spectrum compatible earthquakes. The results are then used to develop a novel multi-level response modification factor (R-Factor) for diagrid structural systems as a function of site seismicity and acceptable damage level. Subsequently, comprehensive seismic reliability analyses are conducted to assess the seismic performance of the selected structures under intensity levels corresponding to DBE and MCE hazard levels (earthquake scenarios with return periods of 475 and 2475 years, respectively). In general, results of this study demonstrate acceptable seismic performance and reliability of steel diagrid systems. It is shown that even using an R-Factor equal to 4 in the seismic design process could ensure that diagrid structures remain in a performance level higher than Life Safety (LS) for both DBE and MCE hazard levels. Multi-level response modification factors proposed in this study can be directly used in performance-based design of diagrid structures to satisfy different performance targets under any seismic hazard level.

System-based calibration of offshore Malaysia environmental action factors for the ISO 19902 PETRONAS offshore fixed platforms

Previously, the action factors, which are generally used in the region of Malaysia is based on the data from the Gulf of Mexico (GoM) or the North Sea, where the environmental condition is much harsher than the offshore Malaysia. Direct application of the high load factors in these regions can result in a waste of economic resources. Based on a reliability-based Load and Resistance Factor Design approach, the current study is carried out for the provision of system-based approach for the calibration of Offshore Malaysia Annex Extreme Environmental Action Factors based on the data from Malaysian waters. With the accessible SEAFINE and HYCOM hindcast database, long-term statistics of extreme environmental load have been derived for six platform locations in Malaysian waters, following the response-based Load Statistics Module (LSM) process. The Generic Load Model (GLM) including the wave-in-deck forces, which has been employed for transferring the wave motion statistics to structural response statistics, is developed in the paper. The structural resistance uncertainty is characterised by the minimum reserve strength ratios (RSRs) derived from a theoretical model that relates with environmental load factor. A structural system reliability analysis based on the FORM method has been performed for a range of minimum values of theoretical RSR for jacket structures fully designed to ISO Code 19902. Partial action factors associated with extreme environmental loads are calibrated to achieve a target reliability level in terms of reliability index.

The analyses of dynamic response and reliability for failure-dependent stochastic micro-resonator with thermoelastic coupling effects

A crucial measure for the design of high-performance micro-resonators is to consider the randomness of structural parameters when analyzing the structural system reliability. In this work, the stochastic dynamic response analysis and subsequently, a dynamic reliability assessment of the random micro-resonators are originally presented, where the thermoelastic coupling effects are freshly incorporated in the models proposed. The dynamic characteristics equation of the deterministic micro-resonator is firstly established based on the finite element method. The random dynamic characteristics of the resonator are then solved by implementing the left and right eigenvectors and the block Lanczos algorithm, and the random temperature field and structural random dynamic stress are also tackled. Afterwards, the overall structural reliability is investigated with a comprehensive consideration of the strength failure and frequency resonance failure, in which the Copula function is used for describing the dynamic correlation between two failure modes. Finally, the feasibility and rationality of the method put forward are demonstrated via a practically motivated example.

AKOIS: An adaptive Kriging oriented importance sampling method for structural system reliability analysis

A major issue in the structural reliability analysis is to determine an accurate estimation result of the failure probability ideally based on a small number of model evaluations. In this regard, the active-learning Kriging based importance sampling method has been received considerable attentions. However, the utility of the most probable failure point (MPP) as the unique sampling center has limited its potential applications for multi-MPP problems. To this end, the paper presents an adaptive Kriging oriented importance sampling (AKOIS) approach. The outer active-learning loop of the AKOIS procedure is used to identify importance sampling centers, whereas its inner-loop is realized based on a rather small subregion centering at the sampling center to gain new training samples. Besides, numerical convergence of local active-learning iterations will immediately trigger another round of outer global search for a new importance sampling center. In this regard, the determined importance sampling centers are able to adaptively cover all branches of the investigated limit-state surface for structural system reliability analysis. Engineering applications of the data-driven importance sampling approach are demonstrated by several system reliability examples in the literature.