Search

The feeding unit is an important functional part in the paper industry that requires the development of effective maintenance plan based on its reliability analysis. This study analyzes reliability of the considered unit employing trapezoidal fuzzy numbers in fuzzy λ – τ methodology with Petri net modeling. In this analysis, the collected crisp input data of each subsystem has been fuzzified using trapezoidal fuzzy numbers. Then fuzzy values of several reliability factors of feeding unit, namely, failure rate, repair time, reliability, availability, etc. at ±15%, ±25% and ±40% spread levels have been calculated. Further, the obtained fuzzy values of reliability factors have been defuzzified to analyze system behavior of feeding unit. The analysis is useful for plant maintenance and operation management to understand the behavior of feeding unit in a more realistic manner. [ABSTRACT FROM AUTHOR]

This paper pertains to the reliability analysis of transmission tower foundations under variable wind loads. The reliability analysis of the anchor foundation, frequently employed for transmission towers due to their huge uplift capacity at shallow depth, is presented using a systematic probabilistic approach. The paper presents the design of an anchor foundation for a typical transmission tower based on loads obtained by applying lateral wind velocity on the tower. The Multivariate Adaptive Regression Splines (MARS) surrogate model is first developed to construct a deterministic prediction model for the anchor uplift capacity. The developed model is further used in the reliability analysis of the anchor foundation considering variabilities in the soil properties and the uplift load, and the results of the probabilistic analysis are reported in the paper. The results indicate the importance of incorporating variability in design variables for the proper safety of the structure. Soil cohesion is found to be the most sensitive parameter in the uplift capacity of the tower foundation. The comparison of the deterministic factor of safety and failure probability of the foundation brings out the importance of the reliability-based design methodology. [ABSTRACT FROM AUTHOR]

This study addresses the challenges of accurately analyzing the reliability of aviation power systems (APS) using traditional models by introducing the Aviation Power System Reliability Probability Network Model (APS-RPNM). The model directly transforms the system architecture into an equivalent probability network, aiming to develop a precise reliability model that captures system functions and fault logic. By classifying APS components into five distinct structural patterns and mapping them to corresponding nodes in the APS-RPNM, the model is successfully constructed. Specifically, None-Input-to-Multiple-Output components are transformed into two-state nodes, while Multiple-Input-to-None-Output, Single-Input-to-Multiple-Output, and Multiple-Input-to-Single-Output components are mapped to three-state nodes. For Multiple-Input-to-Multiple-Output components, a novel approach employing multiple two-state sub-nodes is adopted to capture their complex functional logic. A case study comparing the performance of the APS-RPNM with the traditional minimal path set method in reliability analysis was conducted. The results demonstrate that the APS-RPNM not only simplifies the model construction process and eliminates errors stemming from subjective engineering judgments but also enables the efficient computation of power supply reliability for all load points in a single inference by integrating all of the components. This significantly improves computational efficiency and system dependency analysis capabilities, highlighting the APS-RPNM's tremendous potential in optimizing the reliability design of APS. [ABSTRACT FROM AUTHOR]

The paper focuses on presenting the concept of two-dimensional modeling of passenger car reliability during the warranty period. The main objective of this paper is to detect the regularity in the intensity of the number of first failure reports during the warranty period. The two-dimensional distribution of the time and mileage of failure-free exploitation is estimated. The period from the date of purchase to the first warranty repair is analysed. The concept presented incorporates the existing state of knowledge on two-dimensional warranties, expanding it through the use of a nonparametric approach and probability smoothing with the use of P-splines. The estimation involved censored data, i.e., data on vehicles that were not submitted for warranty repair within the warranty limits of time and mileage. The originality of this paper entails the combination of a nonparametric approach with probability smoothing. The statistical analyses presented in the paper were carried out on a population of 1005 vehicles of two car brands sold and serviced in 2011-2021 at the Authorized Service Station (Dealership). There were sales, repair, and warranty claim databases. [ABSTRACT FROM AUTHOR]

This paper introduces a novel probability distribution known as the Ejaz distribution (ED), which is characterized by two parameters. The study offers a comprehensive analysis of this distribution, including an examination of key properties such as moments, moment-generating functions, order statistics, and reliability functions. Additionally, the paper explores the graphical representation of essential functions like the probability density function, cumulative distribution function, and hazard rate function, enhancing our visual understanding of their behavior. The distribution's parameters are estimated using the widely accepted method of maximum likelihood estimation. Through real-world examples, the paper highlights the practical applicability of the Ejaz distribution, demonstrating its performance and relevance in diverse scenarios. [ABSTRACT FROM AUTHOR]

As offshore wind farms move into deeper waters, around 80 m, the high costs necessitate replacing bottom-fixed turbines with floating offshore wind turbines, which require mooring systems to maintain stability within design limits. Data from previous projects in China indicate that mooring systems can constitute about 20% of the total investment. Thus, reducing mooring system costs can significantly benefit the development of next-generation floating wind farms. This paper discusses the reliability analysis of mooring chains for floating wind turbines to optimize inspection plans and strategies, thereby saving on maintenance costs over their design lifetime. A case study on S-N curve based fatigue reliability analysis is conducted using both Monte Carlo Simulation and First Order Reliability Method (FORM), with consistent results from both methods. Additionally, three sensitivity analysis cases identify key parameters for the fatigue reliability analysis. [ABSTRACT FROM AUTHOR]

In this paper, we generalize two new statistical distributions, to improve the ability to model failure rates with non-monotonic, monotonic, and mainly bathtub curve behaviors. We call these distributions Generalized Powered Uniform Distribution and MOE-Powered Uniform. The proposed distributions' approach is based on incorporating a parameter k in the power of the values of the random variables, which is associated with the Probability Density Function and includes an operator called the Powered Mean. Various statistical and mathematical features focused on reliability analysis are presented and discussed, to make the models attractive to reliability engineering or medicine specialists. We employed the Maximum Likelihood Estimator method to estimate the model parameters and we analyzed its performance through a Monte Carlo simulation study. To demonstrate the flexibility of the proposed approach, a comparative analysis was carried out on four case studies with the proposed MOE-Powered Uniform distribution, which can model failure times as a bathtub curve. The results showed that this new model is more flexible and useful for performing reliability analysis. [ABSTRACT FROM AUTHOR]

In recent years, the high-strength friction-grip bolt (HSFGB) shear connectors in steel-concrete composite beams as deconstructable connectors are of great research interest since they are aligned with sustainable construction. However, the design strength equation for this type of connector has not yet been provided by the design codes such as AISC and Eurocode 4. In this paper, with regard to the reliability aspect, the design strength equation of HSFGB shear connectors is investigated which is projected into a partial safety factor according to Eurocode 4. Accordingly, the three-dimension finite element (FE) push-out model of the composite connection is developed and verified via experimental results to predict the load-slip behavior and failure modes in this type of bolted shear connector. Then One-Factor-at-a-Time (OFAT) method as a sensitivity analysis and Plackett-Burman (PB) design method as a screening analysis are utilized to identify the effective factors of the ultimate strength of HSFGB connectors. Finally, based on a complete database of all existing experimental findings, the results obtained from 55 three-dimension finite element models conducted in this paper, and appropriate statistical analysis, a high-precision equation for predicting ultimate strength is provided. Then the value of the partial safety factor is determined through a reliability study in accordance with EN1990, which provides an acceptable level of safety for the proposed design equation based on Eurocodes. Reliability analysis found that a partial factor of 1.52 was justified for the design strength of HSFGB connectors, which differed from the partial factor of 1.25 stated in the EC for welded stud shear connectors. [ABSTRACT FROM AUTHOR]

The global shear capacity of steel–concrete composite downstand cellular beams with precast hollow-core units is an important calculation as it affects the span-to-depth ratios and the amount of material used, hence affecting the embodied CO2 calculation when designers are producing floor grids. This paper presents a reliable tool that can be used by designers to alter and optimise grip options during the preliminary design stages, without the need to run onerous calculations. The global shear capacity prediction formula is developed using five machine learning models. First, a finite element model database is developed. The influence of the opening diameter, web opening spacing, tee-section height, concrete topping thickness, interaction degree, and the number of shear studs above the web opening are investigated. Reliability analysis is conducted to assess the design method and propose new partial safety factors. The Catboost regressor algorithm presented better accuracy compared to the other algorithms. An equation to predict the shear capacity of composite cellular beams with hollow-core units is proposed using gene expression programming. In general, the partial safety factor for resistance, according to the reliability analysis, varied between 1.25 and 1.26. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design. The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads. The topology optimization formula is combined with the ordered solid isotropic material with penalization (ordered-SIMP) multi-material interpolation model. The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function. Furthermore, the sequential optimization and reliability assessment (SORA) is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization (DTO) problem. Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point (MPP). In each cycle, the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle. The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method (MMA) is used to update design variables. Finally, the validity and feasibility of the method are verified by the numerical example of L-shape beam design, T-shape structure design, steering knuckle, and 3D T-shaped beam. [ABSTRACT FROM AUTHOR]

This paper first explores the use of digital technology in health management and the functional modules of digital health management and establishes a digital health system. Then the penetration of digital health in intelligent vocational education in colleges and universities is studied, and different forms of penetration are used according to different teaching contents. Then the health literacy of students in vocational colleges and universities was measured, and the data were analyzed by exploratory factor analysis and reliability analysis to comprehensively assess the level of students' digital health literacy and the influencing factors. Finally, the efficiency of digital health education integration in higher education institutions was analyzed, and the overall efficiency evaluation of basic digital health education teaching in each discipline before SFA correction was obtained. The total score of the scale and the scores of each dimension were positively correlated with the total score of the e-health literacy scale and the scores of each dimension with correlation coefficients > 0.4, indicating that the validity of the calibration correlation of the data was good. The overall efficiency of the process output of digital health education teaching before SFA revision items showed an overall increasing trend with an average annual increase of 16.0%. The research in this paper provides a reference for improving people's digital health and promoting the healthy development of China's digital health service system. [ABSTRACT FROM AUTHOR]

Turning is one of the most common cutting methods in metal machining. During turning, relative movement occurs between the lathe, the tool, and the workpiece, causing self-excited vibration, i.e., chatter. Moreover, the structural and dynamic parameters of the turning system are uncertain due to the inevitable effect of the processing environment, assembly errors, and other factors. To better predict and prevent turning chatter, it is necessary to analyze the chatter stability and reliability of the turning tool system with its dynamic characteristics to better predict and avoid turning chatter. Despite the importance of chatter prediction in turning, there is a lack of research on the reliability of chatter stability for the turning tool system. In this paper, the dynamic model and the chatter stability model of a turning tool system are established, and the measured parameters are used to analyze the chatter stability of the system. Modal test, static stiffness test, and cutting force tests of the turning system are conducted on a CNC lathe test platform to determine the dynamic parameters of the turning chatter stability analysis. Parameter randomness is considered, and the distribution and characteristic numbers of the parameters are analyzed. The results are consistent with the turning test results, verifying the accuracy of the chatter stability model of the turning tool and machining systems. Furthermore, the chatter reliability model of a turning tool system is established. Since the turning chatter reliability model is more complex and nonlinear, this paper proposes an efficient method for solving the high nonlinear reliability problem is proposed in this paper. The control variable (CV) method is used, and the second-order reliability method is introduced. In addition, a small number of samples generated by Latin hypercube sampling are used to estimate the failure probability by the saddle point approximation method. The applicability of this method is verified by comparison with a variety of methods. The results show that the proposed improved CV method can efficiently analyze the chatter reliability of the turning tool system. [ABSTRACT FROM AUTHOR]

Offshore floating structures rely heavily on their mooring systems, which can be disrupted by various events during long‐term operation. These could lead to a mooring failure, affecting the usual operations of the structure or even causing more severe hazards. Resilience provides a comprehensive evaluation of how the mooring system performs after a disaster, which is key to optimizing the structural design and operational safety. In this paper, we develop a general and user‐friendly method to quantitatively assess the resilience of mooring systems under mooring failure. We use the reliability index to represent the performance of the mooring system. We then derive its RV, ACI, and RCI, which are based on a system performance curve and reliability analysis. We also consider the effects of climate change and the corrosion of the mooring chain. These factors can significantly affect environmental loads, structural performance, and the recovery process. Moreover, an illustrative example is provided that guides us through the methodology. The proposed method is applied to assess the resilience of a certain mooring system in the South China Sea over a 30‐year service life under different failure scenarios. Our results indicate that overlooking climate change in the design and operation of the mooring system can lead to a significant overestimation of its reliability index and resilience value. [ABSTRACT FROM AUTHOR]

The study presents a comparative analysis of the reliability of marine and industrial diesel engines, emphasizing the role of heat exchangers. Diesel engines in marine vessels and industrial applications face distinct challenges, influencing their reliability. This paper examines these differences, focusing on operational conditions, load profiles, redundancy, safety measures, and maintenance practices. Three types of heat exchangers (Fin fan, Plate, and Shell & Tube) are analyzed which are used in these engines. The assessment covers failure rates, Mean Time to Failure (MTTF), and the impact of independent and dependent failures on reliability. The study identifies unique failure modes like insufficient heat transfer, external leakage, parameter deviation, and structural deficiencies and their differing impacts in marine and industrial contexts. The research highlights the sensitivity of marine engine heat exchangers to seawaterinduced corrosion and fouling, affecting heat transfer efficiency. In contrast, industrial engines display varying failure characteristics due to system controls and operational parameters. A significant finding is the decrease in reliability over time for all heat exchanger types, underscoring the importance of maintenance and monitoring. Our results show slight shifts in failure rates due to equipment inefficiencies markedly affecting heat exchangers' operational lifecycles. The study concludes with a necessity for tailored maintenance strategies and design considerations for marine and industrial diesel engine heat exchangers. This focused approach offers insights into optimizing diesel engine reliability, particularly by understanding the main role of heat exchangers. [ABSTRACT FROM AUTHOR]

In this study, we explore a new probability distribution termed as the Length-Biased Transmuted Mukherjee-Islam (LBTMI) distribution. This exploration enhances the conventional Transmuted Mukherjee-Islam distribution by integrating a weighted transformation approach. The paper examines the probability density function and the corresponding cumulative distribution function associated with the LBTMI distribution. A comprehensive examination of the unique structural properties of the proposed model is carried out, including the survival function, conditional survival function, hazard function, cumulative hazard function, mean residual life, moments, moment generating function (MGF), characteristic function (CF), cumulant generating function (CGF), likelihood ratio test, ordered statistics, entropy measures, and Bonferroni and Lorenz curves. To ensure precise estimation of model parameters, the study employs the maximum likelihood estimation method, contributing significantly to the advancement of statistical modelling in this domain. [ABSTRACT FROM AUTHOR]

In this study, we employ a weighted transformation approach to introduce a novel model that generalises the Transmuted Mukherjee-Islam distribution. The resulting generalized distribution is referred to as the Weighted Transmuted Mukherjee-Islam (WTMI) distribution The paper thoroughly explores the probability density function (PDF) and the corresponding cumulative distribution function (CDF) associated with the WTMI distribution. A thorough investigation of the distinctive structural properties of the proposed model is conducted, including survival function, conditional survival function, hazard function, cumulative hazard function, mean residual life, moments, moment generating function (MGF), characteristics function (CF), cumulant generating function (CGF), likelihood ratio test, ordered statistics, entropy measures, and Bonferroni and Lorenz curves. The maximum likelihood estimation method is employed for the precise estimation of model parameters. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) systems are becoming increasingly popular because they offer a sustainable and cost-effective solution for generating electricity. PV panels are the most critical components of PV systems as they convert solar energy into electric energy. Therefore, analyzing their reliability, risk, safety, and degradation is crucial to ensuring continuous electricity generation based on its intended capacity. This paper develops a failure mode and effects analysis (FMEA) methodology to assess the reliability of and risk associated with polycrystalline PV panels. Generalized severity, occurrence, and detection rating criteria are developed that can be used to analyze various solar PV systems as they are or with few modifications. The analysis is based on various data sources, including field failures, literature reviews, testing, and expert evaluations. Generalized severity, occurrence, and detection rating tables are developed and applied to solar panels to estimate the risk priority number (RPN) and the overall risk value. The results show that the encapsulant, junction box, and failures due to external events are the most critical components from both the RPN and risk perspectives. Delamination and soiling are the panels' most critical FMs, with RPN values of 224 and 140, respectively, contributing 16.2% to the total RPN. Further, moderately critical FMs are also identified which contribute 56.3% to the RPN. The encapsulant is the most critical component, with RPN and risk values of 940 (40.30%) and 145 (23.40%), respectively. This work crucially contributes to sustainable energy practices by enhancing the reliability of solar PV systems, thus reducing potential operational inefficiencies. Additionally, recommendations are provided to enhance system reliability and minimize the likelihood and severity of consequences. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new algorithm for rare event estimation based on adaptive importance sampling. We consider a smoothed version of the optimal importance sampling density, which is approximated by an ensemble of interacting particles. The particle dynamics is governed by a McKean--Vlasov stochastic differential equation, which was introduced and analyzed in [Carrillo et al., Stud. Appl. Math., 148 (2022), pp. 1069-1140] for consensus-based sampling and optimization of posterior distributions arising in the context of Bayesian inverse problems. We develop automatic updates for the internal parameters of our algorithm. This includes a novel time step size controller for the exponential Euler method, which discretizes the particle dynamics. The behavior of all parameter updates depends on easy to interpret accuracy criteria specified by the user. We show in numerical experiments that our method is competitive to state-of-the-art adaptive importance sampling algorithms for rare event estimation, namely a sequential importance sampling method and the ensemble Kalman filter for rare event estimation. [ABSTRACT FROM AUTHOR]

Six-phase motors are becoming more popular because of their advantages such as lower torque ripple, better power distribution per phase, higher efficiency, and fault-tolerant capability compared to three-phase ones. This paper presents the fault-tolerant capability analysis of a symmetrical six-phase induction motor equipped with distributed, conventional concentrated, and pseudo-concentrated windings under opencircuit fault scenarios. For further investigation, different load types such as constant-speed, constant-torque, and constant-power are applied to the motor. Two concepts of magnetic and physical phase separations are introduced as factors affecting motor reliability. Analytically, these factors give an insight into how the pseudo-concentrated winding could be a fault-tolerant alternative. Moreover, five parameters including change of output power, power loss, power factor, efficiency, and expected load loss are considered as fault-tolerant capability parameters to evaluate the windings' reliability. The aforementioned parameters are reported using infinite element analysis for different fault scenarios and load types. Although the baseline motor dimensions are not optimized for applying the pseudo-concentrated winding, the pseudo-concentrated winding shows promising performance with high fault-tolerant capability. [ABSTRACT FROM AUTHOR]

The B4 topology is an interesting alternative to the conventional B6 inverter due to its reduced number of parts and lower cost. Although it has been widely used in the past, especially in low-power motor drive applications, its application as a grid-connected inverter is an open area of research. In this regard, this paper analyses the feasibility of the B4 inverter topology for grid-connected applications. A versatile 7 kW inverter prototype, which may be configured as B4 and B6, was built, allowing for a comprehensive evaluation of the performance of both topologies. Through an analytical study and experimental tests, the performance of the B4 and B6 topologies was comparatively evaluated in terms of efficiency, total harmonic distortion of line currents, current unbalance, cost, and mean time between failures. The study was carried out in the context of microgrid systems, highlighting their role in the integration of renewable energy and distributed generation. [ABSTRACT FROM AUTHOR]

Quantum neural networks (QNNs) leverage the strengths of both quantum computing and neural networks, offering solutions to challenges that are often beyond the reach of traditional neural networks. QNNs are being used in areas such as computer games, function approximation, and big data processing. Moreover, quantum neural network algorithms are finding utility in social network modeling, associative memory systems, and automatic control mechanisms. Nevertheless, ensuring the reliability of quantum neural networks is crucial as it directly influences network performance and stability. To investigate the reliability of quantum neural networks, this paper proposes a methodology wherein operator measurements are performed on the final states of the output quantum states of a quantum neural network. The proximity of these measurements to the target value is compared, and the fidelity value, combined with a quantum gate operation, is utilized to assess the reliability of the quantum neural network. Through network training, the results demonstrate that, under optimal parameters, both the fidelity of the final state measurement value and the target value of the model approach are approximately equal to 1. It indicates that training mitigates the errors stemming from encoding into the initial quantum state, thereby resulting in enhanced system reliability and accuracy. [ABSTRACT FROM AUTHOR]

A major challenge in structural reliability is that computational accuracy and efficiency are hard to balance, especially the time-variant hybrid reliability problem. To improve the reliability analysis efficiency under the condition that the accuracy is assured, this paper develops a new learning function named Regional Learning with Weighted Simulation (RLWS) to estimate the failure probability. The Kriging model is first employed as a response surface to fit the response of limit state function. An adaptive regional learning model as the core of the most probable point is then proposed to update the Kriging model, where the boundary of the updated region is determined by an attenuation function. Furthermore, based on the RLWS model, this paper develops a continuous maximin salp swarm algorithm to calculate the upper bound of the response value for time-variant hybrid performance function. Meanwhile, the Salp Swarm Algorithm is employed to calculate the lower bound of the response value. The Monte Carlo simulation can thus facilitate evaluation based on the final generated Kriging response surface. Several case studies are performed to test and validate the effectiveness of the proposed method and its applicability to practical engineering problems. [ABSTRACT FROM AUTHOR]

Analytical probability density function of acceleration random response for cubic nonlinear product package has seldomly been investigated due to the difficulty of solving nonlinear random problem and less attention paid to the acceleration response. In this paper, the analytical solution for the probability density function of linear package acceleration response under random vibration is obtained, and on this basis, the equivalent linearization method is introduced to further explore the approximate analytical solution of acceleration response probability density function for cubic nonlinear product package under random vibration. Some suggestions on packaging optimal design are given by analyzing the sensitivity of acceleration random response to the external excitation and system parameters, and the first-passage failure probability for the acceleration response of cubic nonlinear package under random vibration is analyzed. The results show that the equivalent linearization method can precisely predict the acceleration response probability density function for the cubic nonlinear package under certain conditions, and the applicable range of the method is given by the equivalent stiffness formula. Nonlinear characteristic parameter γ of the cubic package activates acceleration response a completely different trend from the quasi-linear system. Properly increasing the system stiffness and decreasing the damping ratio can effectively reduce the acceleration response strength of the product package. As the vibration time increases and the product fragility decreases, the first-passage failure probability of the product package increases. The analysis provides theoretical foundation and guidance for packaging optimization design. [ABSTRACT FROM AUTHOR]

Temperature and humidity coupling has a more significant effect on the failure properties of bonded joints than a single factor, and there is not enough research on this. In this paper, joints bonded with strong toughness structural adhesives are selected for the experimental analysis of joints aged for 240 h, 480 h, and 720 h at temperatures of 40 °C and 60 °C and a humidity of 95% and 100%. The sequential double Fick's model was used to fit the water absorption of the joints, and the comparison yielded that the water absorption of the adhesive was in accordance with Fick's law. The quasi-static tensile tests revealed that the reduction in mechanical properties of the joints was positively correlated with the moisture content in the environment, while the competing mechanisms of post-temperature curing and hydroplasticization resulted in a slight increase in the failure strength and energy uptake of the aged joints, which is in agreement with the experimental results of the Fourier infrared spectroscopy. A combination of macroscopic failure sections and scanning electron microscope (SEM) images yielded that the failure mode of the joints changed from cohesive failure to interfacial failure with increasing ageing time. In addition, reliability analyses for the fatigue testing of joints are expected to provide guidance for the life design of bonding technology in the vehicle service temperature range. [ABSTRACT FROM AUTHOR]

The ACC (adaptive cruise control) system has developed rapidly in recent years, and its reliability and safety have also attracted a lot of attention. The ACC system can realize automatic driving following the vehicle in the longitudinal range, and its reliability is closely related to the synchronization between two vehicles. Combined with formal modelling methods, this paper analyzes and detects the logical flaw that is poor synchronization in the following process of the ACC system from the perspective of synchronization. Aiming at avoiding this kind of logical flaw, this paper presents a novel optimized modelling solution based on the synchronization theory of Petri nets and further improves the calculation method of the synchronic distance. The simulation results reduce the token accumulation by an average of 91.357%, which demonstrates that the improved model can effectively improve reliability and reduce the risk of rear-end collision. [ABSTRACT FROM AUTHOR]

The charging modules of Electric vehicles (EVs) always run in a complex and variable state. As the weakness in the reliable operation of charging modules, the accurate lifetime prediction of aluminum electrolytic capacitors (Al-caps) is important for the later maintenance and reliability design. The hotspot temperature calculation method and lifetime model limit the accuracy of aluminum electrolytic capacitors lifetime prediction methods, which cannot meet the increasing requirements for reliability. In order to solve the problems above, this paper has proposed a hotspot temperature calculation method based on the ripple current with frequency characteristics and the cooling conditions on the heat generation and thermal conductivity of the capacitors. Furthermore, the lifetime model under reference voltage has been constructed with 3D surface fitting toolbox, which describes the trends of capacitor lifetime with ambient temperature and hotspot temperature under the constant voltage condition. Considering the variation of voltage, the multiple lifetime model of capacitor is established with a voltage correction coefficient. With the proposed method, it can be realized about the real-time lifetime prediction of capacitors under multiple operating profiles such as ripple current, thermal dissipation conditions, ambient temperature and operating voltage. Finally, the effectiveness of the proposed method is verified with the annual profiles of a 30 kW EV charging module. [ABSTRACT FROM AUTHOR]

This paper, based on the E-Bayesian estimation (expected Bayesian estimation), introduced the definition of E-posterior risk (expected posterior risk); we will derive the expressions of E-Bayesian estimation and their E-posterior risk for failure probability under the compound symmetric LINEX loss function, and will compare the results with the corresponding results under the square loss function. Monte Carlo simulations compared the performances of the proposed the estimation method, and compared the results on the basis of E-posterior risk. Finally, combined with the life testing data from a type of aero engine, the calculation and reliability analysis are performed, with E-Bayesian estimation and hierarchical Bayesian estimation, respectively (also using the MCMC method). When considering evaluating the E-Bayesian estimations under different loss functions, in this paper the E-posterior risk as an the evaluation standard is proposed. [ABSTRACT FROM AUTHOR]

Due to the importance of both environmental protection and economic development, environmental auditing and accounting is a crucial subject. To assess the acceptable amount of environmental deterioration and the level of development, a detailed analysis of the benefits and costs of environmental harm is required. This paper provides guidelines on economic, social, and environmental issues for green accounting and reporting practises (GARPs) in the Indian automobile industry. A critical aspect in GARP is the implementation and evaluation of key performance indicators (KPIs). The data analysis for this work uses both qualitative and quantitative methodologies. A systematic questionnaire was utilised to gather the data, and barriers were found using the MINITAB analysis of variance (ANOVA) programme. The reliability of the identified KPI was tested using reliability analysis. The weights of KPI are calculated by analytical hierarchical process (AHP) analysis. The study report identified the lack of knowledge and inadequate strategic planning as significant barriers with a mean value of 3.53 and 3.3, and the calculated index value by AHP analysis for economic, social, and environmental factors is 0.364, 0.342, and 0.294. The identified weight of each GARP-KPI helps to automobile industries with self-assessment. It also supports improving the present situation by comparing the organisations on the basis of the KPI of GARP. This method compares the entire GARP performance and serves as a useful manual for an organisation looking to improve its green audit and reporting procedures. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Geological Hazard & Control is the property of China Institute of Geological Environmental Monitoring (CIGEM) Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces a new cubic transmutation of the inverse Weibull distribution, known as a cubic transmuted inverse Weibull distribution. The model is thought to be useful for the analysis of complex life data, modeling failure times, accessing product reliability, and many other fields like economics, hydrology, biology, and engineering. Some statistical features of the proposed distribution are explored. These include moments, generating functions, quantile functions, reliability functions, and hazard rate functions. The distribution of order statistics for the proposed cubic transmuted inverse Weibull distribution is also studied. The maximum likelihood estimation approach is used to estimate the model parameters. The effectiveness of the estimation is investigated through extensive simulation study. The suitability of the proposed distribution has been studied by using five real-life datasets. It is found that the proposed distribution is the most suitable fit for the used data sets. [ABSTRACT FROM AUTHOR]

Offshore aquaculture is gaining traction due to space limitations in nearshore waters, more pristine water, cooler temperatures, and better waste dispersal. This move has spurred the development of new technologies for offshore aquaculture. Despite the numerous analysis methods for designing aquaculture infrastructure, limitations and challenges remain in modeling the influence of fish cages on flow fields and in addressing fluid–structure interaction. This paper presents a comprehensive review of analysis methods and modeling techniques applied in the design of offshore aquaculture systems, emphasizing the structural reliability analysis. This review includes statistical and predictive analysis of extreme sea conditions, evaluation of environmental loads and hydrodynamic analysis, structural reliability modeling and assessment, and seabed geotechnical responses to mooring anchors. For each design consideration, the relevant theories and applicability are elaborated upon and discussed. This review provides valuable insights for engineers involved in the development and design of offshore aquaculture infrastructure. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive framework for the reliability analysis of ship local structures. Existing reliability analysis of ship local structures relies on empirical analysis without experimental validation. The presented framework improves the probabilistic simulation process by combining finite element analysis and the Kriging surrogate model to increase the computational efficiency in uncertainty quantification. In addition, ultimate strength test data are introduced to update the prior distribution based on Bayesian data fusion. A cross-deck structure of a ship is studied in detail to present the application of this work. The framework provides a valuable reference for the reliability analysis of ship local structures and promotes the development of reliability-based design code. The novelty of this paper is that it introduces the combination of testing and probabilistic simulation into the reliability analysis of ship local structures. [ABSTRACT FROM AUTHOR]

Phyllostachys edulis (P. edulis) bamboo is the most widely distributed and used bamboo species, and it is an ideal building material. With the in-depth implementation of the sustainable development strategy, modern bamboo structures have broad application prospects in green buildings. In order to promote the efficient utilization of bamboo resources and facilitate the design and application of bamboo structures, the bending strength test and classification of P. edulis bamboo were carried out, the factors affecting the reliability were analyzed, and the design values of the bending strength of P. edulis bamboo were proposed based on the reliability analysis. The research results show that dividing P. edulis bamboo into three levels (grade I, grade II, and grade III) can achieve efficient use of P. edulis bamboo resources; 75% fitting data points and normal distribution were used to analyze the reliability of the bending strength of P. edulis bamboo. The analysis of factors affecting reliability makes the calculation of strength design values more reliable. The reliability increases with the increase of the load ratio and the partial factor for resistance. Under the same load ratio and reliability, the partial factor for resistance of the combination of constant load and snow load is the largest, and the partial factor for resistance of the combination of constant load and office building load is the smallest. Under the same load combination and reliability, the partial factor for resistance decreases as the load ratio increases. Under the same load ratio and load combination, the partial factor for resistance of grade III is the largest, and grade I is the smallest. The bending strength design values of grade I, grade II, and grade III are 29.54 MPa, 29.62 MPa, and 30.63 MPa, respectively. This paper innovatively proposed the design values of bending strength of P. edulis bamboo based on classification. The P. edulis bamboo grading method established in this paper and the bending strength design values of P. edulis bamboo proposed can provide references for the design and engineering application of bamboo structures. [ABSTRACT FROM AUTHOR]

A novel computational model is proposed in this paper considering reliability analysis in the modelling of reinforced concrete beams at elevated temperatures, by assuming that concrete and steel materials have random mechanical properties in which those properties are treated as random variables following a normal distribution. Accordingly, the reliability index is successfully used as a constraint to restrain the modelling process. A concrete damage plasticity constitutive model is utilized in this paper for the numerical models, and it was validated according to those data which were gained from laboratory tests. Detailed comparisons between the models according to different temperatures in the case of deterministic designs are proposed to show the effect of increasing the temperature on the models. Other comparisons are proposed in the case of probabilistic designs to distinguish the difference between deterministic and reliability-based designs. The procedure of introducing the reliability analysis of the nonlinear problems is proposed by a nonlinear code considering different reliability index values for each temperature case. The results of the proposed work have efficiently shown how considering uncertainties and their related parameters plays a critical role in the modelling of reinforced concrete beams at elevated temperatures, especially in the case of high temperatures. [ABSTRACT FROM AUTHOR]