Global Reliability Research Articles

Global reliability sensitivity analysis of cradle-type double rotary table

The rotary table is a crucial component of the machine tool, and its accuracy and reliability have an important impact on the machining accuracy and machining efficiency of the machine tool. In this paper, a global reliability sensitivity analysis method of the rotary table is proposed considering the random uncertainty for material parameters of each component. Firstly, the mechanical model of the rotary table is established based on the finite element method. Subsequently, the functional relationship between the parameters of each component and the deformation of the rotary table is reconstructed using the adaptive Kriging surrogate model. Finally, a global reliability sensitivity analysis of the rotary table is performed based on the Bayesian formulation. The results show that the proposed global reliability sensitivity analysis method of the rotary table demonstrates satisfactory efficiency and can provide theoretical guidance for the design and optimization of the rotary table.

Hierarchical structure-based model for importance and reliability assessment of water distribution networks

The Segment-Valve (SV) model can be utilized to analyze the reliability of water distribution networks (WDNs). However, it often focuses on the impact of segment failures on themselves. The isolation of segments in the WDNs not only affects the segments themselves but also influences other segments through which the water supply path passes. Therefore, considering the water supply path and the interaction between upstream and downstream segments, we convert the loops in the SV graph to nodes to simplify them, clearly describing the segmented hierarchy and its interconnections in a tree-like form, termed SV-tree. Based on the SV-tree and complex network theory, a method is proposed to estimate the supply shortage rate using betweenness centrality to provide a detailed analysis for local importance on example WDNs. Meanwhile, new analysis indicators that can reflect the global reliability of the WDNs are constructed from the mutual influence between segments and the difficulty for users to obtain water. The results demonstrate the efficacy of the new importance assessment indicator across various WDNs configurations, and its calculation time is much lower than that of hydraulic simulation. In addition, the reliability assessment indicators are more practical and can effectively identify problems existing in the WDNs.

Global reliability assessment of coupled transmission tower-insulator-line systems considering soil-structure interaction subjected to multi-hazard of wind and ice

This study aims to assess the global reliability of coupled transmission tower-insulator-line systems considering soil-structure interaction (CTTILSs-SSI) subjected to multi-hazard of wind and ice. Firstly, two simplified models of CTTILSs-SSI under stochastic wind and ice loads are established, and their governing equations are derived through the Lagrange equation. On this basis, a global reliability assessment framework of CTTILSs-SSI is proposed based on the improved maximum entropy method, in which the global performance function of CTTILSs-SSI is defined via the state variable description method. Finally, a practical ultra-high voltage overhead transmission line located on the icing zone is chosen to illustrate the proposed framework. Moreover, to investigate the influence of soil-structure interaction (SSI) and soil types on the global reliability of transmission tower-insulator-line systems (TTILSs), the global reliability of CTTILSs-SSI with various soil types is compared with that of a fixed base system. The results indicate that under the in-plane wind and ice loads, the global failure probability of TTILSs is almost zero, and it is essentially not affected by the SSI effect and soil types. However, under the out-of-plane wind and ice loads, the global failure probability of CTTILSs-SSI is higher than that of the fixed base system, and the global failure probability of CTTILSs-SSI increases as the soil stiffness decreases. Accordingly, it may be more reasonable to consider the SSI effect into the global reliability analysis of TTILSs subjected to ice and out-of-plane wind loads, particularly when the soil is soft.

The "Flapbot": A Global Perspective on the Validity and Usability of a Flap Monitoring Chatbot.

The Flapbot chatbot assists in free-flap monitoring, emphasizing accessibility, user-friendliness, and global reliability. This study assesses Flapbot's worldwide validity and usability and uses qualitative analysis to identify areas for future enhancement. Flapbot, built on Google's DialogFlow, was evaluated by international plastic surgeons. Invitations were sent to the International Lower Limb Reconstruction Collaborative (INTELLECT), International Confederation of Plastic Surgery Societies (ICOPLAST), and the International Microsurgery Club. Out of the 42 surgeons who agreed to participate, 21 tested the Flapbot and completed an online survey on its validity and usability. The survey had 13 validity items and 10 usability items. Data analysis involved computing the individual content validity index (I-CVI) and scale-wide content validity index (S-CVI) for validity, and the system usability score (SUS) for usability. Thematic analysis distilled free-text responses to identify key themes. Nine of 13 items had an I-CVI over 0.78, denoting significant relevance. The S-CVI score stood at 0.82, indicating high relevance. The SUS score was 68, representing average usability. Themes highlighted issues with the current model, development suggestions, and surgeons' concerns regarding growing reliance on digital tools in health care. Flapbot is a promising digital aid for free-flap monitoring. While it showcases notable validity and usability, improvements in functionality, usability, and accessibility are needed for broader global use.

Psychometric Testing of the Thai Version of Self-Care of Chronic Illness Inventory Version 4c in Patients With Stroke.

Self-Care of Chronic Illness Inventory version 4c is a non-disease-specific self-care measure used in individuals with multiple chronic conditions. This instrument may be applied to patients with specific diseases such as stroke. The aim of this study was to evaluate the psychometric properties of the Thai version of the Self-Care of Chronic Illness Inventory version 4c in patients with stroke. This multicenter, cross-sectional study adhered to the COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) guidelines and enrolled patients with stroke from 16 primary care centers in southern Thailand. Structural validity was assessed using confirmatory factor analysis, internal consistency reliability using Cronbach α coefficient and global reliability index, and test-retest reliability using intraclass correlation coefficients. The final analysis included a total of 350 participants. Confirmatory factor analysis supported the 2-factor Self-Care Maintenance scale structure, although the item allocation to the dimensions differed from that of the original model. The Self-Care Monitoring scale demonstrated a 1-factor structure with permitted residual covariance. The Self-Care Management scale maintained a 2-factor structure, similar to that of the original model. Simultaneous confirmatory factor analysis of the combined items supported the general model with the 3 scales. The Self-Care Maintenance scale exhibited marginally adequate α (0.68) and ω (0.66) coefficients, and an adequate composite reliability index (0.79). The other 2 scales demonstrated adequate α (range, 0.79-0.86), ω (range, 0.75-0.86), and composite reliability (range, 0.83-0.86) indices. Intraclass correlation coefficients showed adequate test-retest reliability for all scales (range, 0.76-0.90). The generic self-care measure, Self-Care of Chronic Illness Inventory version 4c, demonstrated strong psychometric properties in patients with stroke. This instrument may be a valuable tool for assessing stroke self-care in Thailand.

Sequentially Quadratic Surrogate Algorithm for Time-dependent Reliability and Reliability Sensitivity Analysis

Time-dependent reliability and reliability sensitivity analysis in presence of random uncertainty is widespread in equipment structures. To this end, this paper establishes a sequentially quadratic surrogate method. Firstly, the global reliability sensitivity analysis (GRS) is transformed into the classification problem of the time-dependent performance function outputs by means of conditional probability formula. Secondly, referring to the strategy of the Meta-IS method, the Kriging model of time-dependent performance function is employed to construct the importance sampling function to generate the importance sampling (IS) samples of failure domain efficiently. Furthermore, the Kriging model is updated in the IS samples set through the single-loop adaptive Kriging method to realize the accurate identification of the failure indicator function of IS samples, as well as simulation of time-dependent failure probability. Finally, utilize the information of the failure samples obtained by the estimation of time-dependent reliability to evaluate GRS. The proposed algorithm has excellent computational efficiency and applicability due to the conversion of the conditional probability formula, which enables the computational consumption of the time-dependent reliability and GRS analysis independent of the dimensions of the inputs, as well as the Meta-IS method, which improves the sampling efficiency and is applicable to the case of complex implicit performance function. The given examples fully verify the conclusions.

An innovative adaptive Kriging-based parallel system reliability method under error stopping criterion for efficiently analyzing the global reliability sensitivity index

An innovative adaptive Kriging-based parallel system reliability method under error stopping criterion for efficiently analyzing the global reliability sensitivity index

Efficient Methods for Reliability Sensitivity Analysis of Distribution Parameters and Their Application

To efficiently evaluate the influence of the distribution parameters of the input variables on the failure probability of engineering structures and improve the reliability and safety of engineering structures in a targeted manner, new methods for the global reliability sensitivity analysis (RSA) of distribution parameters are proposed in this study based on the cubature formula (CF), surrogate sampling probability density function (SSPDF), and quasi-Monte Carlo (QMC) method. By introducing CF, the proposed methods can effectively improve the computational efficiency of the nested expectation and variance operators in the reliability sensitivity indices of the distribution parameters. Based on the concept of SSPDF, a surrogate importance sampling probability density function was developed. This not only overcomes the problem of the computational effort of propagating parameter uncertainty to the failure probability function (FPF), which depends on the dimensionality of the parameters; it also further improves the efficiency of the RSA of the parameters in the case of a small failure probability. Finally, by incorporating the idea of the QMC method, the process of calculating the reliability sensitivity indices of the parameters is reduced from a double-loop to a single-loop one. Three engineering examples are used in this study to demonstrate the efficiency and accuracy of the new algorithms.

A posteriori error estimates for the Richards equation

The Richards equation is commonly used to model the flow of water and air through soil, and it serves as a gateway equation for multiphase flows through porous media. It is a nonlinear advection–reaction–diffusion equation that exhibits both parabolic–hyperbolic and parabolic–elliptic kind of degeneracies. In this study, we provide reliable, fully computable, and locally space–time efficient a posteriori error bounds for numerical approximations of the fully degenerate Richards equation. For showing global reliability, a nonlocal-in-time error estimate is derived individually for the time-integrated H 1 ( H − 1 ) H^1(H^{-1}) , L 2 ( L 2 ) L^2(L^2) , and the L 2 ( H 1 ) L^2(H^1) errors. A maximum principle and a degeneracy estimator are employed for the last one. Global and local space–time efficiency error bounds are then obtained in a standard H 1 ( H − 1 ) ∩ L 2 ( H 1 ) H^1(H^{-1})\cap L^2(H^1) norm. The reliability and efficiency norms employed coincide when there is no nonlinearity. Moreover, error contributors such as space discretization, time discretization, quadrature, linearization, and data oscillation are identified and separated. The estimates are also valid in a setting where iterative linearization with inexact solvers is considered. Numerical tests are conducted for nondegenerate and degenerate cases having exact solutions, as well as for a realistic case and a benchmark case. It is shown that the estimators correctly identify the errors up to a factor of the order of unity.

Analysis of Importance of Components in Power Systems using Time Sequential Simulation

Power systems reliability analysis consists in evaluating the ability of a system to perform its function without failures. Usually, it is measured in failures per year (λ). In the present work, the reliability of the global system is used to obtain the importance of components in order to identify which parts of the network must be improved or which components are the less reliable and need to be upgraded. The objective is to increase the global reliability of the system by introducing better components or redundant branches to guarantee the best quality of the power in the load points. A Time Sequential Monte Carlo simulation has been implemented in Matlab® and tested in a HV/MV substation to determine the importance of its components.

DPIM-based global reliability analysis method for the cable-stayed bridges and the determination of global target reliability index

This study presents an approach to analyzing the dynamic global reliability of cable-stayed bridges using the direct probability integral method. The analysis considers the degradation of resistance in the concrete main beam, tower, and cables, as well as the time-varying nature of the load effect. Six types of limit state functions for failure modes are established, including bending failure of the beam, static torsional failure of the beam, wind vibration failure of the beam, transverse buckling failure of the tower, longitudinal strength failure of the tower, and strength failure of the stay cable due to fretting fatigue and corrosion. A time-dependent extreme value mapping is constructed in the time domain, then the joint probability density integral equation of time-varying extreme value mapping of multiple performance functions is established. According to the mean and variance of random variables in the evaluation reference period, the direct probability integral method with Heaviside function (DPIM-H) is employed to solve the equation, and the dynamic global reliability index of cable-stayed bridge is obtained. As an example, the Brotonne cable-stayed bridge’s global reliability is analyzed, and the reasonable value of the global target reliability index is studied considering the structural performance degradation.

Reliability-based design optimization scheme of isolation capacity of nonlinear vibration isolators

Nonlinear vibration isolators (NVIs) are beneficial to isolate or suppress the adverse effects caused by harmful vibration. To a large extent, the isolation capacity of NVIs depends on the selection of design parameters (including structural, geometric, and excitation parameters) of vibration isolators. However, existent uncertainties of these parameters are unavoidable, which influence the reliability of the isolation capacity of NVIs. In this respect, an effective reliability-based design optimization (RBDO) scheme of isolation capacity of NVIs is presented by taking into account the parameter uncertainties of NVIs. In the proposed RBDO scheme, the force transmissibility of nonlinear isolators is regarded as the objective function, and the fundamental frequency, the dynamic displacement response amplitude, and reliability of vibration isolation performance are supplied as the constraints to search the optimal design parameters of NVIs. Considering the influence degree of design parameters uncertainties, the global reliability sensitivity analysis is employed for identifying the critical design parameters in NVIs. A surrogate model of the failure probability function is established by the adaptive learning Kriging approach to decrease the computational cost of the reliability evaluation nested in the RBDO scheme. An advanced meta-heuristic algorithm is executed to search for the design parameters for optimal isolation capacity of NVIs. The proposed scheme provides a potential direction for optimizing the isolation capacity of complicated vibration isolators.

Reliability-based design optimization for seismic structures considering randomness associated with ground motions

When addressing the dynamic reliability analysis of structures, it becomes necessary to account for multiple limit state functions or their combinations. In scenarios where structures are subjected to random excitation, this can lead to intricate inter-dependencies among different limit states, and the computational workload can pose a substantial challenge in ensuring sufficient precision. Code-based design primarily ensures safety at the member level, while deterministic optimization fails to accommodate the inherent uncertainties associated with external excitation or the system as a whole. Therefore, in such cases, to address both the uncertainties in excitations and the presence of multiple limit states while mitigating computational challenges, equivalent extreme-value criteria are employed within the framework of the probability density evolution method to calculate the global reliability of the structure subjected to stochastic ground motions generated from the physically motivated stochastic ground motion model. Numerical optimization is subsequently conducted using genetic algorithms, aiming to minimize the cost of the superstructure while adhering to the design performance criteria related to the inter-story drift ratio and considering global reliability. Additionally, multi-objective optimization is carried out using NSGA-II, permitting the generation of multiple solutions, from which one can select the most suitable solution as needed. The numerical results illustrate the effectiveness of this technique in achieving an optimal balance between the cost of the structure and the consideration of global reliability, providing a comprehensive solution for dynamic reliability analysis and design optimization of structures under random excitations.

A novel method for global reliability sensitivity analysis by adaptive bivariate multiplicative dimensional reduction integral

The existing fractional moment-constrained maximum entropy method can efficiently analyse global reliability sensitivity (GRS). However, this method estimates the fractional moments by the univariate multiplicative dimensional reduction integral (UM-DR-I) that generates a significant error in GRS estimation, which may result from ignoring the interactions between input variables. Moreover, due to the direct bivariate decomposition of the fractional power performance function, the recently developed generalised bivariate additive dimensional reduction integral (GB-DR-I) may also result in higher computational cost and lower accuracy than that obtained with UM-DR-I regarding fractional moment and GRS estimations. To improve the efficiency of solving for GRS with an acceptable accuracy, a bivariate multiplicative dimensional reduction integral (BM-DR-I) is proposed to estimate the unconditional and conditional fractional moments required when estimating the GRS. The main innovation is that the proposed method analytically derives the BM-DR-I formulae for estimating the unconditional and conditional fractional moments; moreover, it discovers for the first time that the unconditional and conditional fractional moments can be estimated by sharing the same integral grid. Accordingly, the proposed BM-DR-I eliminates the dependence of the computational cost on the input dimensionality when estimating the GRS. In addition, to further improve the efficiency of estimating fractional moments and GRS sequentially with sufficient accuracy, an adaptive strategy for selecting effective bivariate terms was employed to construct an adaptive BM-DR-I. Four examples verify that adaptive BM-DR-I is superior to similar existing methods for estimating the GRS.

A novel Bayesian-inference-based method for global sensitivity analysis of system reliability with multiple failure modes

Global reliability sensitivity analysis aims at quantifying the effects of each random source on failure probability or reliability over their whole distribution range and is highly concerned in reliability design and uncertainty control. And in practice, a structure or product usually has more than one component impacting their performance safety, which is essentially a system reliability problem. Therefore, this paper proposes a novel Bayesian-inference-based method for moment-based global sensitivity analysis of system reliability with multiple failure modes. First, the limit-state function of each component involved in the system is linearly approximated based on the reliability index. Then, the global reliability sensitivity is transformed into a problem of multivariable Gaussian probability within a given safe region where the dimension number is double of the failure modes. In this case, the Bayesian-inference-driven expectation propagation technique is introduced to solve this intractable problem in an analytical manner, based on which the closed-form solution to the global reliability sensitivity for system with multiple components is accordingly derived. Finally, a numerical case, a vehicle subjected to impact, a cantilever beam and a practical engineering application to a four-panel spaceborne deployable plane antenna are studied to demonstrate the effectiveness of the proposed method by comparison with Monte Carlo simulation.

NPP as a technically complex facility. Global reliability management using “Between True and False” method

В представленной обзорной научно-исследовательской статье раскрываются современные аспекты понятия управления надежностью и рисками технически сложных объектов строительства на примере атомной электростанции (АЭС). Через анализ отечественного и зарубежного подходов к исследованию систем управления надежностью АЭС в работе определяется вектор развития прикладной науки в области оценки на­дежности проектов. Автором излагаются проблемы разработки интегрированной системы управления организационно-экономической надежностью основных фаз строительства объектов атомной энергетики. Содержатся основные тезисы и описание авторской разработки методики оценки надежности технически сложной системы АЭС на основе многокритериального подхода. Предлагается использовать стохастический и детерминированный методы оценки надежности технически сложной системы АЭС. Обосновывается актуальность применения теории нечетких множеств в контексте исследуемой проблематики при оценке степени надежности технически сложного объекта недвижимости — атомной станции. Метод построения сетевых графиков, заложенный в основу прикладного программного обеспечения организаций, выполняющих функции заказчика и исполнителя строительства АЭС, рассматривается как подоснова системы оценки надежности проекта по его этапам и стадиям. В статье формулируется проблематика управления надежностью и рисками, в выводах и рекомендациях обозначаются перспективы развития систем управления надежностью АЭС, определяется направление дальнейших исследований в данной области. Предлагается создание глобальной карты-схемы международного рынка объектов атомной промышленности на основе данных об их надежности. Обосновывается факт, что создание такой карты-схемы сделает возможным общедоступно информировать человечество о состоянии объектов энергетической системы, применяющих технологию «мирного атома».

PDEM-based multi-component and global reliability evaluation framework for steel tubular transmission towers with semi-rigid connections

The conventional analysis and design of transmission towers usually ignore the effect of semi-rigid behaviors of bolted joints and simplify the joints as the rigid or pinned connection, which might overestimate or underestimate the structural response of transmission towers and the reliability of structural components and systems. To consider the effect of semi-rigid connections on the reliability of transmission towers in this paper, a stochastic dynamic finite element model of steel tubular transmission towers with semi-rigid connections (STTTs-SRCs) is established by deriving their stiffness matrix, where the uncertainties of dimensions, material and semi-rigid connections are considered and the wind loads are simulated as stochastic processes by the dimension-reduced probabilistic simulation approach. Then, based on the equivalent extreme-value event, the multi-component and global performance functions with stress and displacement failure modes for STTTs-SRCs are established, respectively. Further, a reliability evaluation framework for STTTs-SRCs is proposed based on the probability density evolution method (PDEM). Finally, a practical engineering transmission tower is regarded as an example to demonstrate the implementation process of the proposed reliability evaluation framework. Moreover, the reliability of steel tubular transmission towers with rigid and pinned connections is compared with that of STTTs-SRCs to investigate the effect of semi-rigid connections on the reliability of transmission towers. In general, the semi-rigid connections would mainly affect the value of the multi-component failure probability, however, it would not change the location where the maximum failure probability of components occurs. Additionally, the semi-rigid connection significantly affects the global failure probability of towers for the stress failure mode while slightly affects the global failure probability of towers for the displacement failure mode. Therefore, it may be more appropriate to consider the semi-rigid connections into the analysis and design of steel tubular transmission towers.

RUN-AS: a novel approach to annotate news reliability for disinformation detection

The development of the internet and digital technologies has inadvertently facilitated the huge disinformation problem that faces society nowadays. This phenomenon impacts ideologies, politics and public health. The 2016 US presidential elections, the Brexit referendum, the COVID-19 pandemic and the Russia-Ukraine war have been ideal scenarios for the spreading of fake news and hoaxes, due to the massive dissemination of information. Assuming that fake news mixes reliable and unreliable information, we propose RUN-AS (Reliable and Unreliable Annotation Scheme), a fine-grained annotation scheme that enables the labelling of the structural parts and essential content elements of a news item and their classification into Reliable and Unreliable. This annotation proposal aims to detect disinformation patterns in text and to classify the global reliability of news. To this end, a dataset in Spanish was built and manually annotated with RUN-AS and several experiments using this dataset were conducted to validate the annotation scheme by using Machine Learning (ML) and Deep Learning (DL) algorithms. The experiments evidence the validity of the annotation scheme proposed, obtaining the best F1m\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extbf F_\ extbf 1\ extbf m$$\\end{document}, 0.948, with the Decision Tree algorithm.

Reliability assessment and performance improvement of long-span roof structure subjected to coupled wind-snow multi-hazard

Sensitivity to wind and snow loads has been the focus of reliability analysis and safety design of long-span roof structures in cold regions. In this study, the reliability assessment and performance improvement of a long-span roof structure subjected to coupled wind-snow multi-hazard are addressed. To this end, the average wind pressure coefficients of roof surface are first derived from wind tunnel tests, and the two-dimensional wind velocity field simulation is carried out by using the refined spectral representation scheme based on joint wavenumber-frequency power spectrum and stochastic harmonic function. The snow pressure coefficients of structural roof considering wind-induced snow drift effects are obtained by conducting computational fluid dynamics simulation. Then the global reliability of the structure subjected to coupled wind-snow multi-hazard with 100-yr return period is assessed using the probability density evolution method (PDEM). To improve structural performance, a control scheme of distributed tuned mass dampers (d-TMDs) is designed according to the structural dynamics of their deployment positions. Numerical results show that the fluctuating wind is a critical factor resulting in deformation failure of the long-span roof structure, and the proposed control scheme has sound effectiveness and robustness to mitigate the fluctuating wind effect and thus improve the structural performance.

On Second Order Rate Regions for the Static Scalar Gaussian Broadcast Channel

This paper considers the single antenna, static, scalar Gaussian broadcast channel in the finite blocklength regime. Second order achievable and converse rate regions are presented. Both a global reliability and per-user reliability requirements are considered. The two-user case is analyzed in detail, and generalizations to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> -user case are also discussed. The largest second order achievable regions presented here require both superposition and rate splitting in the code construction, as opposed to the (infinite blocklength, first order) capacity region which does not require rate splitting. Indeed, the finite blocklength penalty causes superposition alone to underperform other coding techniques in some parts of the region. In addition, the proposed scheme uses joint simultaneous decoding as opposed to successive interference cancellation. Interestingly, in the two-user case with per-user reliability requirements, the capacity achieving superposition encoding order (with the codeword intended for the user with the smallest received SNR as cloud center) does not necessarily give the largest second order region. Instead, the message of the user with the smallest point-to-point second order capacity should be encoded in the cloud center in order to obtain the largest second order region for the proposed scheme.