Search

Structural reliability assessment is of great significance for the safety and maintenance of structures. In recent years, the moment method has been rapidly developed and applied widespread for its simplicity and performance. Sometimes, the accuracy of the moment method, using only the first four moments (i.e., mean value, standard deviation, skewness, and kurtosis), is not sufficient in evaluating the reliability index of strong non-Gaussian performance functions. In this study, a method based on the quartic normal transformation (QNT) is proposed for structural reliability assessment, which enables incorporation of the first five moments, including the super-skewness, of performance function. The structural reliability index based on the QNT model is derived. The first five moments of the performance function are estimated by introducing the point estimate method. Seven engineering examples are employed to demonstrate the efficacy of the QNT. The results show that the computational efficiencies of CNT and QNT were close to each other and both superior to that of MCS. The results also show that the performance of QNT is superior to CNT in aspect of accuracy and robustness in particular to performance functions with strong non-Gaussianity. [ABSTRACT FROM AUTHOR]

Retaining walls are important structural systems used in the construction of highways. With asset management methods for retaining wall inventories lagging those developed for highway bridges, there is a need to develop risk management methods for these critical structural systems. A major challenge is the vast inventories of retaining walls that asset managers must manage and the inherent limitations of visual inspections. This study proposes an asset management framework for retaining walls based on risk assessments using structural monitoring data. First, a long-term wireless monitoring solution is proposed to measure wall tilt and strain over long periods of time. Second, an analytical framework is developed to separate wall thermal responses from lateral earth pressures responses with the latter used to extract estimated lateral earth pressure distributions. A statistical distribution of lateral earth pressures are used in a reliability assessment of the wall to provide a measure of failure probability that can be combined with failure consequences to estimate asset risk. To illustrate the proposed methodology, a reinforced concrete cantilever retaining wall panel is selected for long-term structural health monitoring. A wireless structural health monitoring system is installed to measure the tilt, strain, and temperature response of the wall continuously over 15 months. The study reveals the wall exhibits strong diurnal and seasonal variations offering insight into wall behavior under operational conditions. Hypothesized levels of corrosion in the steel reinforcement at the base of the wall are explored to estimate the wall reliability. Even under the assumption of 20% reinforcement section loss, the monitored wall was found to have a reliability index well above 3.0. [ABSTRACT FROM AUTHOR]

Due to the complexity of the transmission tower structure and the correlation between wind and ice loads in the actual project, it is difficult to analyze the reliability of transmission towers with traditional methods. To solve this problem, the unscented transformation (UT) principle is presented concisely and used in the reliability analysis of transmission towers in this paper. Moreover, the finite element model of the target transmission tower is created. The reliability indices of the transmission tower under various loading cases are evaluated using UT and analyzed relative to the outcomes of the Monte Carlo method (MCS). Lastly, by analyzing and validating a wine-cup shape tangent tower, the simulation results show that the UT yields reliability indices with less than 6% relative error compared with MCS results for the transmission towers with lower reliability, which are more important in engineering. Variations in error caused by the change in correlation coefficients among variables are small. Consequently, the efficiency of calculations is improved by the UT-based reliability calculations for transmission towers in the case of correlated variables, which better meet engineering application requirements. It is proved that the method of reliability analysis for transmission towers based on the UT is applicable. [ABSTRACT FROM AUTHOR]

Digital image correlation (DIC), a widely used non-contact measurement technique, often requires empirical tuning of several algorithmic parameters to strike a balance between computational accuracy and efficiency. This paper introduces a novel uncertainty analysis approach aimed at optimizing the parameter intervals of a DIC algorithm. Specifically, the method leverages the inverse compositional Gauss–Newton algorithm combined with a prediction-correction scheme (IC-GN-PC), considering three critical parameters as interval variables. Uncertainty analysis is conducted using a non-probabilistic interval-based multidimensional parallelepiped model, where accuracy and efficiency serve as the reliability indexes. To achieve both high computational accuracy and efficiency, these two reliability indexes are simultaneously improved by optimizing the chosen parameter intervals. The optimized algorithm parameters are subsequently tested and validated through two case studies. The proposed method can be generalized to enhance multiple aspects of an algorithm's performance by optimizing the relevant parameter intervals. [ABSTRACT FROM AUTHOR]

The estimation of the resistance factor in load and resistance factor design (LRFD) calibration for simple soil–structure limit states is most often based on model bias data of limited size. Frequently, the bias data are only available or required for the resistance term. In this study, the confidence in the estimate of the mean of the resistance factor is computed for the case of one resistance factor and one load factor where limited model bias data are available for both load and resistance terms. The bootstrap method is used to compute synthetic load and resistance bias data sets from which confidence intervals on the point (mean) estimate of the resistance factor and load factor are computed. A closed-form solution is used to calculate the resistance factor for a single prescribed load factor and target reliability index, bias data, and nominal load and resistance variables that are lognormally distributed. However, the approach is general using Monte Carlo simulation. The method is demonstrated using the case of the internal stability pullout limit state for steel strip mechanically stabilized earth walls. The example demonstrates the quantitative influence on pullout design using upper and lower 95% confidence interval limits for load and resistance factors. [ABSTRACT FROM AUTHOR]

This study characterizes the statistical uncertainties in the bivariate distribution of friction angle and cohesion of soils using bootstrap method and explores its application to the reliability‐based design of slopes. First, the bivariate distribution of friction angle and cohesion is modelled using the copula approach based on limited test data. Then, the statistical uncertainties in the derived bivariate distribution of friction angle and cohesion are characterized by the bootstrap method. Finally, an infinite slope is employed to investigate the impact of the statistical uncertainties in friction angle and cohesion on slope reliability. The reliability‐based designs of slopes based on the point and interval estimate of reliability index are compared. The results indicate that the bivariate distribution of friction angle and cohesion derived from limited test data exhibits large statistical uncertainties. The reliability index of the infinite slope shows visible variation because of the large statistical uncertainties in friction angle and cohesion. The reliability index of slopes considering the statistical uncertainties in friction angle and cohesion is presented as a confidence interval. The interval estimate of reliability index gives a more comprehensive description of slope reliability than the point estimate of reliability index. Furthermore, the reliability‐based design of slopes based on the interval estimate of reliability index can reflect the effect of the amount of test data on the design and link the site investigation efforts and investments on shear tests to final design savings. [ABSTRACT FROM AUTHOR]

Background The study aimed to study the relative and absolute indicators of liver cancer (C22) in Kazakhstan over 10 years in the prism of a trend indicator (moving average), coefficient of variation (Cv), accounting reliability index (Idi).In 2022, in Kazakhstan, the incidence of liver cancer (C22) was 5.1 per 100 thousand people, mortality was 2.9, respectively, the index of reliability of accounting was 0.2.The unified risk of morbidity of the population of Kazakhstan with liver cancer for the period 2013-2022 amounted to 28.6%, mortality - 33.5%, respectively. Result Over the period 2013-2022, newly diagnosed liver cancer in Kazakhstan increased by 31%, the rate of decrease in the number of newly diagnosed liver cancers varied unevenly over the years, which demonstrates a high rate and amplitude of change from 105 to -140, which significantly complicates the prediction of this pathology. Conclusion: For the period 2013-2022, posthumously registered liver cancer consistently occupied the first place in the structure of specific gravity among all malignant neoplasms in Kazakhstan. [ABSTRACT FROM AUTHOR]

In this work, we performed a reliable study of the IEF model, which calculates the critical stress intensity factor, KIC, already studied in our previous article (Daoud et al. Int J Adv Manuf Technol 92:569–581, 2017), by the Phimeca-soft, where we performed a parametric study of the variation of the reliability index (β) as a function of the crack length (a) of the three states G1(x), G2(x) and G3(x) of the four sample types (R2, R4, R10 and R80), and also found the FORM/SORM results, as well as the histogram of elasticity of all variables used in the reliability study for the four sample types, with E26 galvanized sheet, safety and failure domains depending on the limit state used and importance of calculation variables on the reliability of the fracture. Then, the critical stress intensity factor (KIC) was found by the analytical method (IEF Model) equal to 63.13 MPa.m1/2 (accurate but not precise value), by the numerical method using the software Franc2D equal to 57.94 ± 4.29 MPa.m1/2 (precise but not accurate value) and by the reliability method using the software Phimeca-soft equal to 38.93 ± 0.83 MPa.m1/2 (accurate and precise value). [ABSTRACT FROM AUTHOR]

In this paper, a novel statistical vibration-based damage detection method is developed considering uncertainties in measured resonance frequencies. The proposed method is based on the application of resonance frequencies as the most accurate and easiest measurable vibration feature. For proof of efficiency of the proposed method, case studies were undertaken using two identical composite plates, one delaminated and the other pristine. In this respect, the frequency response functions (FRFs) were measured and used as the main input to the Resonance Detection Algorithm as the proposed method. Applying these FRFs to a Resonance Detector Function can determine the resonant frequencies and their statistical distribution. Through the statistical distributions of the corresponding resonant frequencies, their reliability of detecting damage has been obtained via the beta distribution. By observing the damage detection reliability of the two sets of corresponding resonant frequencies, it has been determined that the changes in natural frequencies are due to structural changes and not random errors through measurement. [ABSTRACT FROM AUTHOR]

In the context of this research, understanding the reliability of a power generator is essential as a criterion for assessing its suitability for use or the need for further development. The method used in this study is reliability analysis, known as "Expected Energy Not Supplied (EENS)." The initial step of this method is to calculate the FOR (Forced Outage Rate) to determine the level of disturbances in the generator unit. The subsequent process involves calculating individual probabilities, analyzing the generator load curve, determining the EENS values of three generators, and comparing them with the EENS standards established by the National Electricity Market. These standards stipulate that EENS should not exceed 0.002% of the total energy consumption in the region. This research marks a significant milestone as the first endeavour conducted on Lombok Island within this specific context. The study was conducted by analyzing three operational Micro-Hydro Power (MHP) units on Lombok Island. The research findings indicate that the EENS metric for MHP on Lombok Island stands at 2.822%. This result suggests that the reliability of MHP on Lombok Island falls below the established criterion, which is less than 0.002% annually. In practical terms, these findings imply that MHP plants located on Lombok Island may not be relied upon as the primary source to meet the electricity demands of the Lombok region in 2022. This research provides valuable insights into the challenges of energy reliability on Lombok Island and serves as a crucial foundation for further considerations in the development of renewable energy sources in the region. [ABSTRACT FROM AUTHOR]

This paper employs probability methods to evaluate the fire safety performance of prestressed steel–concrete beam bridges based on simulation experimental research. Firstly, fire simulation experimental sample analysis was conducted on actual small box girder bridges to assess the structural response of prestressed steel–concrete structures to fire, as is in line with engineering practice. Next, we constructed a reliability analysis model to investigate the fire resistance performance of prestressed steel–concrete beam bridges. Combining reliability theory with the finite element method, we established a reliability analysis method for the fire resistance performance of prestressed steel–concrete beam bridges. Subsequently, we proposed a safety factor evaluation model for the fire resistance performance of prestressed steel–concrete beam bridges and then established a safety factor evaluation method for the fire resistance performance of prestressed steel–concrete beam bridges based on reliability back analysis. Finally, based on the analysis of the post-fire structural response in the specific case of a steel–concrete continuous beam bridge project moving from conditions of being simply supported to continuously prestressed, a structural resistance sample of the prestressed steel–concrete beam bridge was generated via the uniform design method, and statistical analysis was conducted. Subsequently, probability methods were used to evaluate the safety of the prestressed steel–concrete beam bridge after a fire. Through analysis, we concluded that the duration of the fire had a significant impact on the structural performance of prestressed steel–concrete beam bridges and that the randomness of parameters had a significant impact on the safety reserve of prestressed steel–concrete beam bridges following the fire. Going forward, it is necessary to pay attention to this factor in specific engineering practices and strengthen the monitoring and statistical analysis of structural random characteristics. [ABSTRACT FROM AUTHOR]

Chloride‐induced corrosion in concrete bridges is a common problem in coastal regions. This study assesses the reliability‐based service life of a reinforced concrete (RC) T‐girder bridge subjected to pitting rebar corrosion. The impact of spatial variability of rebar pitting corrosion has been considered to accurately predict the service life. Service life models have been applied to both strength and serviceability parameters for coastal bridges in India. The results indicate that rebar corrosion influences the shear resistance deterioration of the bridge girder more rapidly than the flexure resistance deterioration, which significantly impacts the bridge's reliability and service life. Further, it has also been observed that due to chloride‐induced corrosion, the serviceability parameters are impacted more than the strength parameter leading to an early requirement of repair for the serviceability conditions. [ABSTRACT FROM AUTHOR]

The reliability of the electricity supply is important since any interruption to the supply has direct and indirect consequences for its users. A reliable electricity supply requires a reliable electrical grid system to transmit and distribute the power from the generating plants to the consumers. This study reviewed the literature to find out how the reliability concept has been understood with a special focus on grid electricity reliability, what factors influence grid electricity reliability, what measures have been used to measure grid electricity reliability, which theories and methodologies have been applied to study grid electricity reliability and what are the likely research gaps that require future address. This review found that the literature documents four categories of factors that influence grid electricity reliability, and these are environmental, security, organizational and technical. The biggest influencers of grid electricity reliability were the technical-related factors followed by the environmental-related factors. In addition, we found that sixty studies focused on one subsystem, eleven on two subsystems while seven studies considered three subsystems. Most studies were found to address the distribution of subsystem reliability. As per the methodology adopted, this review found that eleven studies used a qualitative approach, forty-five studies used a quantitative approach, while eleven studies used a case study approach to study the concept of grid electricity reliability. In addition, we found that thirty-seven studies used the duration and frequency of power outages to measure grid electricity reliability. [ABSTRACT FROM AUTHOR]

A reasonable lateral stiffness of the bridge mid-tower should ensure that the deflection-to-span ratio and sliding resistance coefficient satisfy the design requirements. However, if this stiffness is determined by the deterministic parametric analysis, the above two verification indices may exceed the threshold due to the randomness of the high-dimensional structure and load parameters. To satisfy the structural safety requirements of a three-tower suspension bridge during its design life, this study proposes a method to quickly and accurately evaluate the reliability indices of the deflection-to-span ratio and sliding resistance coefficient of the three-tower suspension bridge. Based on advanced first-order second-moment, the proposed method transforms the reliability problem into an optimization problem with constraint functions, uses the single-cable theory to establish the limit state function, and combines the manta ray foraging optimization algorithm and penalty function to derive the reliability index. The effectiveness of the proposed method is verified by performing Latin hypercube sampling for an examplary three-tower suspension bridge. These results prove that the new technique avoids tedious finite element simulation and surrogate model fitting, ensuring the accuracy of the reliability index while improving the calculation efficiency. The study further identifies critical structural parameters by parametric analysis. Based on the inverse reliability, the dimensionless stiffness range for the mid-tower with the randomness of the parameters is derived, and the preliminary design method of the lateral stiffness of the mid-tower based on the reliability is established. [ABSTRACT FROM AUTHOR]

In line with the principles of modern design a building structure should not only be safe but also optimized. In deterministic optimization, the uncertainties of the structures are not explicitly taken into account. Traditionally, uncertainties of the structural system (i.e. material parameters, loads, dimensions of the cross-sections) are considered by means of partial safety factors specified in design codes. Worth noticing, that optimal structures are sensitive to randomness design parameters and deterministic optimal solutions may lead to reduced reliability levels. It therefore seems natural to extend the formulation of deterministic optimization with the random scatter of parameter values. Such a formulation is offered by robust optimization and reliability-based design optimization. The applicability of RBDO is strongly dependent on the availability of the joint probability density function. A formulation of non-deterministic optimization that better adapts to the design realities is robust optimization. Unlike RBDO optimization, this formulation does not require estimation of failure probabilities. In the paper using the examples of steel beams, the authors compare the strengths and weaknesses of both formulations. [ABSTRACT FROM AUTHOR]

Uncertainties in seismic demand and structural capacity create conservatism in the acceptance criteria of structural performance levels. This conservatism can be reduced and designs optimised by considering and reducing uncertainties. In seismic rehabilitation, a secondary system added to an existing structure has probabilistic parameters that can lead to changes in existing uncertainties. In this work, a steel moment frame was rehabilitated with a steel shear wall (SSW). Structural uncertainties were investigated by considering probabilistic variables of the force–deformation relationship of the SSW. The results showed that structural uncertainty increased the total uncertainty by 2.0–9.3%. Previous studies that have not considered structural uncertainty due to the force–deformation relationship and may not provide results with appropriate conservatism. As a result, the dispersion of the total uncertainties of a structure rehabilitated with a SSW is close to the dispersion value of a moment frame equipped with a brace, but is more than the dispersion value of the moment frame structure. A parametric study of the reliability index was performed based on probabilistic variables. Based on the results, the structural uncertainty reduced the reliability index by 0.57–1.28%. [ABSTRACT FROM AUTHOR]

A database was compiled to establish the site-specific measured load–displacement responses of piles from different sites across the globe, which contains 188 curves from 12 sites. A curve-fitting technique was applied to each measured curve by using a two-parametric power law regression modeling. For an entire construction site, the scatter in the load–displacement behavior of multiple curves was incorporated in the uncertainty of the regression pairs. Consequently, environmental contours for regression pairs were developed by using the Nataf transformation or a normal copula. Such a contour was generated to quantify the uncertainty in the regression pairs in which the target reliability index of piles is specified, as demonstrated in various cases with two, three, and four variables. Most importantly, the environmental contour bounded by the serviceability limit state of piles at each site was presented and the reliability index was solved through an evolution of the environmental contours. The computed reliability index of the bearing resistance for piles was compared with the values yielded by the geometric reliability analysis and the first-order reliability method (FORM). Since the reliability index was solved in the original physical variable space, it made the reliability theory easy to understand. Such a site-specific reliability assessment of piles could be helpful for a practical project to implement quality control during the construction of pile foundations. [ABSTRACT FROM AUTHOR]

The long-term quality assurance of bridges demands an adequate quality control plan detailing the main required activities and assessment tools. This paper presents the application of a quality control plan on two existing reinforced concrete bridges located in Portugal and North Macedonia. Based on the available results from visual inspections and non-destructive tests, defects and corresponding damage processes were identified. The structural safety of the case studies was assessed by means of a reliability index considering the identified damages. The reliability index computation was supported by a nonlinear finite element analysis. The computed reliability index that reflects the actual ('today') bridge condition was used as the base information in the preparation of possible maintenance scenarios. Three different maintenance scenarios were considered, namely, the improvement (corrective scenario), reduction (do nothing and rebuilt scenario), or delay in the reduction (preventative scenario) of the performance of the structure. By comparison of normalised net present values of the key performance indicators (reliability, safety, availability and costs), the most appropriate scenarios are found. [ABSTRACT FROM AUTHOR]

Asymptotic sampling (AS) is an efficient simulation-based technique for estimating the small failure probabilities of structures. AS utilizes the asymptotic behavior of the reliability index with respect to the standard deviations of random variables. In this method, the standard deviations of random variables are progressively inflated using a scale parameter to obtain a set of scaled reliability indices. The collection of the standard deviation scale parameters and corresponding scaled reliability indices are called support points. Then, least squares regression is performed using these support points to establish a relationship between the scale parameter and scaled reliability indices. Finally, extrapolation is performed to estimate the actual reliability index. Various extrapolation models have been used in AS to improve accuracy. Moreover, a mean extrapolation formulation using the average value of different extrapolation models was proposed to further improve its accuracy. Although the mean extrapolation formulation protects against using the wrong extrapolation model, it did not guarantee a reliability estimation better than that of the best available extrapolation model. In this paper, we propose a weighted average AS formulation in which the weight factors are optimized to minimize the variance of the reliability index estimation through the bootstrapping method. In the weight factor determination, both convex and affine formulations are considered and the results are compared. The performance of the proposed method is evaluated using six benchmark example problems and a complicated engineering problem. It is found that the proposed weighted average formulation has higher accuracy than the mean extrapolation formulation. For weight factor optimization, the affine formulation yields more accurate results than the convex formulation in most cases. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the plastic response of reinforced concrete tapered beams when subjected to random steel reinforcement volumes, using both deterministic and probabilistic analyses, with the complementary strain energy as a boundary in the first case, and the reliability index as a boundary in the second. The first step in this study was to use a previously studied model and perform a deterministic analysis, assuming that the complementary strain energy is a limiting factor and controller of the plastic behaviour. Next, a probabilistic analysis is applied, with the reliability index as a limitation. At the same time, the volume of the reinforcement steel used, and the complementary strain energy were treated as probabilistic variables with mean values and specific standard deviations. This novel method highlighted the plastic behaviour limiting procedure and provided results that highlighted the nature of the model's changed behaviour when the complementary strain energy was controlled and when applying probabilistic properties with reliability index limitation. [ABSTRACT FROM AUTHOR]

Aiming at the issue of spatial variability of soil mechanical parameters in slope stability analysis, this paper proposed a stochastic finite element method for calculating the distribution of FS（factor of safety） of embankment slopes, and Monte Carlo（MC） strength reduction combined method and MC direct method were proposed to calculate the reliability of slope. Taking isotropic two-dimensional slope as an example, firstly, sampling to get the corresponding random field of material properties, and then the slope displacement, stress and plasticity zone results were calculated; then on the basis of NMC times sampling of random field, the failure probability of the slope was obtained and the reliability index was solved and analyzed by the following methods of a) combined method（M1）: the strength reduction method was used to get the reduction coefficient of each sample and its distribution; b) MC direct method（M2）: using viscoplastic method to solve directly to judge the instability of slopes, and the instability cases under all sample conditions were counted. The results show that the slope stability analysis considering the material properties random field, the mean, variance, distribution of FS and reliability indexes are integrated to evaluate the slope safety, which can get the real and reliable slope stability analysis results. [ABSTRACT FROM AUTHOR]

The paper examines the quantitative influence of uncertainty in the estimate of geosynthetic reinforcement stiffness on numerical outcomes using analytical solutions for a) the maximum outward facing deformation in mechanically stabilized earth (MSE) walls, b) maximum reinforcement tensile loads and strain in MSE walls under operational conditions, and c) the mobilized reinforcement stiffness in a geosynthetic layer used to reinforce a fill over a void. The stiffness of the reinforcement is modelled using an isochronous two-parameter hyperbolic load-strain model. A linear relationship between isochronous stiffness and the ultimate tensile strength of the reinforcement is used to estimate reinforcement stiffness when product-specific creep data are not available at time of design. Solution outcomes are presented deterministically and probabilistically. The quantitative link between nominal factor of safety used in deterministic working stress design practice and reliability index is provided. The latter is preferred in modern performance-based design to quantify margins of safety within a probabilistic framework. Finally, the paper highlights the practical benefit of using product-specific isochronous secant stiffness data when available, rather than estimates of isochronous stiffness values based on reinforcement type or pooled data. • Uncertainty in the estimate of geosynthetic stiffness is investigated for three geosynthetic-reinforced soil applications. • The stiffness of the reinforcement is modelled using an isochronous two-parameter hyperbolic load-strain model. • Isochronous secant stiffness estimated using: a) product-specific creep data; b) type of reinforcement; and c) pooled data. • Closed-form solutions linking the nominal factor of safety to the reliability index for each application are provided. • Solution outcomes are presented deterministically and probabilistically. [ABSTRACT FROM AUTHOR]

The plastic behavior of strengthened haunched beams utilizing carbon fiber-reinforced polymers (CFRP) was investigated using a probabilistic design that took into account random concrete properties, CFRP properties, and complementary strain energy values, with the reliability index serving as a limiting index, as the proposed method considers a novel method that deals with probabilistic parameters for models with limited plastic behavior designed based on the reliability index. The data used in this research were gathered and evaluated in a recent study on simply supported haunched beams reinforced with carbon fiber-reinforced polymers. The purpose of this research was to use the reliability limitation index for simulated strengthened haunched beams by taking into account randomness in concrete and CFRP properties and the complementary strain energy value, which is considered a plastic behavior controller that provides an illustration of the damage amount within the reinforcement steel bars. The results indicate how randomness affects the behavior of the presented models, which are chosen to have different numbers of CFRP strips. The variable randomness affects load and deflection values where the reliability index value increases as the corresponding load value decrease, reflecting the increased probability of failure in models subjected to higher loading conditions, while tension concrete damage percentages are reflected in the damage pattern presented in the results, showing that as the produced load increases, so does the damage intensity. It is also obvious that the reliability index served as a limitation index while taking concrete characteristics and complementary strain energy as random variables. [ABSTRACT FROM AUTHOR]

This paper discusses the second-order reliability-based design optimization (SORBDO) of unsaturated finite slopes. An efficient search algorithm is proposed to locate the most probable slip surfaces using the Morgenstern–Price method of slices. The variability of fitting parameters of the soil water characteristic curve (SWCC) and shear strength parameters have been taken into account for evaluating the reliability of unsaturated finite slopes. Six unsaturated shear strength (USS) models are considered for the analysis of unsaturated soils. The most conservative model for the optimum design of finite slopes is recommended. Moreover, the results indicate that the mean and standard deviation of the fitting parameters of SWCC have a significant effect on the critical centers, critical slip surfaces, and reliability index of the unsaturated finite slopes. The results demonstrate a significant change in the critical centers associated with critical slip surfaces due to the change in the mean and coefficient of variation of the fitting parameters of SWCC. Statistical analysis of the experimental data shows that a positive correlation exists between fitting parameters of SWCC related to air entry value (af) and residual water content (mf). Negative correlations are found between the fitting parameters of SWCC related to air entry value (af) and slope (nf). Similarly, the SWCC fitting parameters related to residual water content (mf) and slope (nf) have negative correlations for clayey soils. It is observed that the correlated value of the reliability index is overestimated with reference to the uncorrelated value for clayey soil slopes. The proposed design charts are beneficial for engineers and practitioners for the sustainable design of unsaturated finite slopes. Overall, the developed rigorous SORBDO framework offers a more rational approach for assessing critical failure surfaces and critical centers, considering the interdependency of random variables. [ABSTRACT FROM AUTHOR]

Reliability-based Design Optimization (RBDO) is a nested optimization approach. This paper emphasizes the importance of improving computational efficiency by reducing the number of evaluations of the performance function, which is the bottleneck for practical engineering applications. Aim at this issue, the paper proposes to reduce the function evaluation number caused by gradient calculations as the important direction for improving RBDO's efficiency, as it takes up the majority of the total evaluation number of RBDO. Within the above important direction, the paper introduces a new hybrid inverse reliability method for searching the minimum performance target point (MPTP). It integrates the traditional Advanced Mean Value (AMV) with an innovative MPTP-searching approach, where the new format of gradient computation is dependent on one variable other than muliti-ones. This can effectively eliminate a drawback of conventional gradient computation, whose evaluation number is influenced by the dimensionality of random variables. Furthermore, its operational simplicity is highlighted by the absence of chaos control factors, making it more convenient for real engineering applications compared to methods like Chaos Control (CC) or Modified Chaos Control (MCC). Lastly, the numerical examples are investigated to validate the accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Wind power, as a sustainable clean energy source, has been widely used in power systems. However, the intermittency of wind power poses a threat to the reliability of these systems. One solution to address this issue is the integration of electric vehicle (EV) scheduling. By using EVs with Vehicle-to-Grid (V2G) technology, grid reliability can be improved: EVs can charge when there is excess wind power and discharge when there is a shortage. Another technology that enhances wind power system reliability is Dynamic Thermal Line Rating (DTLR). The DTLR system increases transmission line capacity based on actual weather conditions, helping to alleviate network congestion. Despite the benefits of these technologies, their coordinated operation has not been jointly modeled for reliability purposes before. This study presents, for the first time, a reliability model for the coordinated operation of these two technologies and introduces a new reliability index, the Smart Regulation Reliability Index (SRRI). Simulations were conducted using the IEEE 24-bus reliability test system. The results show that the coordinated operation of these technologies reduces Expected Energy Not Supplied (EENS) by nearly 28.8 % and increases SRRI by about 12.9 %. [Display omitted] • VMD and PACF process meteorological data for accurate DTLR and wind power prediction. • A new model analyzes the impact of DTLR and EV scheduling on network reliability. • A new reliability index assesses the performance of the EV scheduling model. [ABSTRACT FROM AUTHOR]

Reinforced concrete (RC) columns in frame structures are often subjected to biaxial bending and axial compression under both horizontal loads (e.g., wind load in a given direction) and vertical loads (e.g., gravity). Owing to the random properties of loads, it is important to consider the uncertainties of biaxial eccentricity. However, the fixed eccentricity criterion used in the conventional design methods cannot capture the effects of random biaxial eccentricity on reliability. Based on the reciprocal load method, the reliability is analyzed for columns with both the fixed eccentricity and random eccentricity criteria by Monte Carlo simulation. It is demonstrated that random biaxial eccentricity has a significant influence on the reliability of RC columns with wind-dominated combination. [ABSTRACT FROM AUTHOR]

Rehabilitation of parking garages – when and why? Existing models for the evaluation of the durability of reinforced concrete structures allow to prognose the limit state condition of the structure during its service life by means of the reliability index. Furthermore, in the decision‐making process, a fixed (limit) value for the reliability can be defined, which refers to a maximum acceptable probability of occurrence of a selected (undesirable) event (limit state). The worse the condition, the higher the expected rehabilitation costs. If it is possible to describe the expected rehabilitation costs as a function of the reliability index, the repair times can be determined in a cost‐optimal way. Therefore, expert reports with extensively documented inspection results and associated costs of underground parking garage repairs were analyzed. The main cause of the repairs was in all cases chloride‐induced reinforcement corrosion. Three approximation methods were used to estimate the reliability of column and wall bases and compared with each other. At the structure, i.e. object level, it was not possible to establish a clear relationship between reliability and repair costs. However, at the structural component level, this was achieved for a single project. This provides a starting point for cost‐optimized determination of repair times. [ABSTRACT FROM AUTHOR]

Flood scouring can expose the foundation and cause stiffness degradation of masonry structures and is often overlooked by designers and engineers. The seismic performance of a structure cannot be guaranteed when stiffness degradation reaches a certain critical level, which is usually difficult to control. Investigating structural performance under the combined action of earthquakes and flood scouring is very significant for regions that have both a high seismicity and a high flood risk. In this paper, a method for evaluating the failure probability of masonry structures under flood scouring and earthquakes based on risk theory is proposed. According to the performance requirements of masonry structures under natural hazards, the performance indexes of structures are quantified, and the fragility of masonry structures under the combined action of flood scouring and earthquakes is analyzed. Flood scouring and earthquake hazard risks and structural fragility under multiple hazards are comprehensively considered to obtain the structural failure exceedance probabilities in different damage states. Then, the critical scour depth at which the seismic resistance of the structure drops abruptly due to flood scouring is calculated. Furthermore, the loss ratio and the cumulative failure probability of a structure are introduced to determine the failure risk and reliability index of the structure in the full-performance state and to ultimately evaluate the multihazard structural performance. Based on the method proposed in this paper, the multihazard failure risk of a one-story masonry structure is analyzed. The results show that earthquakes are the main force controlling the structural performance, and flood scouring has a relatively small influence on the fragility of structures in slight damage and moderate damage states and a relatively large influence on structures in severe damage and collapse states. In addition, a critical scour depth exists, beyond which the structural fragility changes sharply. Compared with the failure risk of the case in which only earthquakes are considered, the failure risk of the structure under each damage state increases substantially when the combined action of flood scouring and earthquakes is taken into account. Therefore, the influence of flood scouring on the seismic performance of structures must be considered. [ABSTRACT FROM AUTHOR]

This study presents a robust reinforced concrete planar frame automated seismic design procedure incorporating reliability analysis and heuristic optimization. The limit-state function selected corresponds to the story drift. In order to reduce the computational burden and make a real-life practical application, the response surface method was employed to obtain the limit-state function. Then, two methods, the Hasofer-Lind and Rackwitz-Fiessler and the Monte Carlo simulation, were applied to determine the reliability index β. The story drift limitstate was evaluated using linear elastic analysis in a reinforced concrete planar frame with five stories and three spans under gravitational and seismic loads, including all sway special moment frame constraints, as per the Colombian code for seismic-resistant buildings NSR-10. The weight of the reinforced concrete planar frame was minimized by employing particle-swarm optimization and a genetic algorithm, considering its crosssections and longitudinal reinforcement as discrete optimization variables. Two general optimization scenarios developed in the software MATLAB® 2019b were considered: (I) including a minimum β as a design constraint and (II) without including a minimum β as a design constraint. For scenario (I), the compressive strength of concrete and the seismic load were considered random variables. The results show an increase in the weight of the reinforced concrete planar frame for scenario (I) of 11.63% (Hasofer-Lind and Rackwitz-Fiessler) and 16.89% (Monte Carlo simulation) when compared to scenario (II). Nonetheless, β values for scenario (I) were 1.534 (Hasofer-Lind and Rackwitz-Fiessler) and 1.713 (Monte Carlo simulation), which were significantly higher than the 0.065 β-value for scenario (II). In conclusion, in all design examples, achieving satisfactory reliability levels (β) means increasing the cross-sectional area of the reinforced concrete planar frame beyond the Colombian code for seismic-resistant buildings, NSR-10, minimal requirements. Finally, from the structural safety point of view, the presented procedures permit fast reinforced concrete planar frame designs incorporating reliability analysis and heuristic optimization with good computational times. [ABSTRACT FROM AUTHOR]

The increase of road freight around the world, alongside limited funding on bridge infrastructure, demands objective and accurate safety assessments for greater loads to achieve better utilization of existing aging bridges. Probability-based bridge assessment (PBBA) is already recommended around the world as a higher-tier assessment beyond current deterministic methods. However, its uptake in international practice lags behind that merited. The promotion of PBBA in practice hinges on four aspects: (i) justification, through proof of concept; (ii) accessibility, through integration into current practice; (iii) effectiveness, through utilizing state-of-the-art tools, and; (iv) familiarity, through clear communication and education. This paper describes a recent Austroads research project that has developed solutions to these aspects to promote the adoption of PBBA in Australia. The experience gained in developing the freely available guideline is described in this paper to support the promotion of PBBA adoption in other countries. [ABSTRACT FROM AUTHOR]

In structural reliability analysis, Hasofer-Lind and Rackwitz-Fiessler (HL-RF) method is a widely used approximation method for evaluating the reliability index. However, by increasing the nonlinearity or complexity in the limit state function of a structure, HL-RF may get in trouble for convergence. This paper represents an iterative algorithm that tries to minimize the Lagrange function, associated with the reliability problem. In each iteration of this method, two steps are followed, to satisfy the minimization condition and the existing constraint. In the first step, a movement for minimization in a descent direction is followed. In the second step, another search direction contributes to approach limit state surface, and therefore the next iteration can start from the vicinity of the surface. Employing Lagrange reliability function and limit state function simultaneously in the proposed two-step Lagrangian-based method (TSLB) can help to control the numerical instability in highly nonlinear problems. The accuracy and robustness of the proposed algorithm are shown in illustrative examples of the literature. Keywords two-step Lagrangian-based method (TSLB), reliability index, limit state function, HL-RF method [ABSTRACT FROM AUTHOR]

The failure probability and the reliability index have been determined for a pipe submitted to internal pressure, exhibiting a corrosion defect, embedded in a soil with a ground reaction, and submitted to displacement due to seismic activity. Results are obtained by computing the condition of failure: strain demand higher than strain resistance which is typically the Strain Based Design (SBD) basis. From the probabilistic point of view, this condition results as the product of the two probability distributions, demand and resistance. An analytical method is proposed to compute the common area between the strain demand and resistance distribution and then get the probability of failure. The strain demand is assumed to follow a power-law distribution and the strain resistance, a Normal one. The strain demand is computed assuming that the probability density of seism follows a Gutenberg –Richter distribution law as it is found in the south of France. This simple method is also used to predict the failure probability of different reference periods or seismic zone. It is also used to examine the influence of the coefficient of variation of the strain resistance distribution when using vintage pipe steels. [ABSTRACT FROM AUTHOR]

The design of mechanically stabilized earth (MSE) walls depends greatly on the maximum tensile loads developed in the reinforcement layers. In practice, it has been found that the measured tensile loads significantly differ from the predicted values, and it is quantified by a bias value named load bias. It is defined as the ratio of the measured to the predicted maximum tensile load. Further, to evaluate the load bias, prediction of the maximum tensile load in reinforcements needs to be assessed properly for wall safety. Therefore, in this paper, a new artificial neural network (ANN)-based response surface method has been proposed to predict the maximum tensile load developed in reinforcements of MSE walls reinforced with steel strips. Both tensile strength and pullout limit states have been considered in this study. The sensitivity of the proposed load model on the design outcome (reliability index or probability of failure) has been assessed and compared with the existing response surface-based load model. One practical example problem has been considered, and the feasibility of the proposed model in predicting the reliability index (or probability of failure) is examined for different values of coefficient of variation of the nominal load and resistance. Design charts in terms of the failure probability of the wall over depth are presented throughout this study for both tensile strength and pullout limit states, and results reveal that the satisfactory performance of the proposed load model is achieved in predicting the reliability of the wall. [ABSTRACT FROM AUTHOR]

This paper presents the results of a reliability analysis of the service life of hydraulic structures made of C50 coral aggregate seawater concrete (CASC) in the splash zone of the South China Sea. The analysis was conducted using the ChaDuraLife V1.0 software, which is based on reliability theory and modified chloride diffusion theory. Several parameters such as the surface free chloride concentration (C s), chloride binding capacity (R), free chloride diffusion coefficient (D f), apparent chloride diffusion coefficient (D a), and time-dependent index (m) were considered in this analysis. The (1-m) boundary condition is adopted in this study. The effect of concrete cover thickness on the service life of CASC structures was discussed. The influence of rebar types and external protective measures on the service life was also investigated. Durability recommendations for C50CASC hydraulic structures in the splash zone were proposed. The minimum concrete cover thickness needed to achieve the service life of 30a to 100a was determined to provide theoretical support for the application of CASC in island and reef engineering. The results found that the best technical measures for extending the service life were the application of 2205 duplex stainless steel bars and silane protective coating on the surface of concrete structures. A concrete cover thickness of 6–7 cm could achieve the service life of 50a, while a thickness of 8.5–10 cm, could achieve the service life of 100a. • A reliability analysis of the service life of C50CASC structures in the splash zone of the South China Sea was conducted. • The influence of concrete cover thickness on the service life of CASC structures was discussed. • Durability recommendations for C50CASC structures in the splash zone of the South China Sea were proposed. • The minimum concrete cover thickness needed to meet the service life of 30a to 100a was determined. [ABSTRACT FROM AUTHOR]

This study develops a practical copula-based FORM in an original physical space for an efficient slope reliability analysis involving correlated non-normal variables. First, the copula theory for modeling the joint probability distribution of cohesion and friction angle of soils is briefly introduced. Second, the traditional expanding dispersion ellipse perspective of the FORM is reviewed. Then, a new expanding dispersion contour perspective of the copula-based FORM is formulated in detail. Finally, two illustrative slope examples are presented to illustrate and demonstrate the developed copula-based FORM and its expanding dispersion contour perspective. The results indicate that the developed copula-based FORM has good accuracy and efficiency in deriving the reliability index and design point for a typical slope reliability problem. It operates in an original physical space and thus is suitable for a complex slope reliability problem with an implicit performance function. The copulas for characterizing various dependence structures between the cohesion and friction angle of soils have a significant impact on slope reliability index, especially under a high reliability level and a strong degree of negative correlation. The proposed expanding dispersion contour perspective facilitates the understanding of the copula-based FORM, which can readily explain the slope reliability results produced by various copulas. The derived design points are obtained by simultaneously considering the marginal distributions, correlation as well as various non-Gaussian dependence structures of soil parameters. [ABSTRACT FROM AUTHOR]

Prediction about the failure probability of a product or system is essential in reliability engineering, where a decision‐making process is carried out on a regular basis. This paper proposes a novel index, that allows to predict the failure rate on products recently launched into the market; its calculation is based on sales information and failure reports. Maximum likelihood method is used to derive a mathematical expression for this index, and prediction intervals are obtained throughout a bootstrap approach. A good performance regarding the mean square error and coverage probability is observed in the simulation study included here. Monthly sales data and mobile phone failure reports, provided by the company in charge of the warranty policy process, were used to illustrate our proposal that emerged from an academic‐industry collaboration. [ABSTRACT FROM AUTHOR]

Structural reliability analysis involving the non‐normal random variables are commonly encountered in practical engineering. Furthermore, some random variables are often unknown probability distributions, and the probabilistic characteristic of these variables may be expressed using only statistical moments. In this contribution, an efficient algorithm for structural reliability analysis considering the random variables with non‐normal and unknown probability distributions is proposed, in which high‐order unscented transformation (HUT) and fourth‐moment methods are adopted to efficiently evaluate the structural reliability index. By introducing the Rosenblatt transformation and third‐order polynomial transformation (TPT) techniques, random variables with non‐normal or unknown distributions are transformed into standard normal distributions. Accordingly, the performance functions can be reconstructed using standard normal random variables, and HUT is then employed to efficiently estimate the first four moments (i.e., mean, standard deviation, skewness, and kurtosis) of the performance function. Based on the Hermite polynomial model, the complete expression of fourth‐moment reliability index is derived for estimating the reliability index using the first four moments of the performance function. The efficiency and accuracy of the proposed algorithm are demonstrated through six numerical examples. The results show that the proposed algorithm is applicable to estimating reliability index of both static and dynamic reliability problems involving explicit and implicit performance functions. [ABSTRACT FROM AUTHOR]

Reliability-based design (RBD) can overcome some limitations and ambiguities in the partial factor design approach found in Eurocode 7 (EC7) and the load and resistance factor design (LRFD) method used in North America. The aim of this study is to show how RBD via the first-order reliability method (FORM) can complement LRFD and EC7 codes. Three geotechnical engineering examples are used to demonstrate that RBD-via-FORM can provide guidance to the partial factor design approach in situations with load-resistance duality, shear strength parameters with context-dependent sensitivities, parameters not covered in design codes, cross-correlated parameters, and designs aimed at a target reliability or failure probability. Insights from RBD-via-FORM are presented. The differences and similarities between the design points in RBD, partial factor, and LRFD methods are explained. Comparisons are made with Monte Carlo simulations, the mean-value first-order second-moment method, and the Bathurst–Javankhoshdel closed-form reliability index solution which is restricted to simple linear limit state performance functions with lognormally distributed load and resistance terms and bias factors. It is suggested that RBD-via-FORM can be conducted in tandem with EC7 and LRFD methods in order to overcome limitations and ambiguities which sometimes arise using these methods. [ABSTRACT FROM AUTHOR]

Summary: The Energy Management System (EMS) is a strong need for achieving cost‐effective, reliable, and pollution‐free operation of microgrids operating in isolated areas. Commonly, the EMS approaches use optimization and rolling‐horizon predictions. However, the inclusion of very short‐term predictions increases the complexity of the optimization, compromising its ability and reliability to operate online. In response to this problem, this paper proposes a rule‐based EMS (RB‐EMS) which uses neither optimization nor prediction horizons. Instead, the RB‐EMS evaluates historical data, and very short‐term predictions to calculate the setpoints of distributed energy resources, and schedulable loads in a cost‐effective, reliable, and sustainable manner. As a form of self‐regulation, the RB‐EMS introduces the Reliability Index to calculate the maximum state of charge of the energy storage system. Given the speed imposed by the very short‐term predictions, the RB‐EMS also introduces a start‐up manager for diesel units that present a dead time in their enlistment. The isolated ESUSCON‐HUATACONDO microgrid was used as a testbed for performance validation. The work shows a first scenario comparing the RB‐EMS against a rolling horizon EMS based on MILP optimization. A second scenario shows the energy management performance with 1 minute predictions. The better results obtained, and the computational simplicity of the RB‐EMS allows propose it to achieve faster and more reliable energy management in other isolated microgrids. [ABSTRACT FROM AUTHOR]

The current methods for reliability index calculation are less effective for in-plane shear failure of unreinforced masonry (URM) walls because there is significant uncertainty in the walls' mechanical parameters and resistance model. To address this issue, the authors propose a new method based on stochastic Gaussian process (GP) model. They conducted in-plane shear resistance experiments on six URM walls and converted the walls' deterministic shear resistance models to prior GP models, which they updated to posterior models using the experimental results. The posterior GP models specified normal probability density functions (PDFs) for shear resistance of the walls, and the PDFs linearized the walls' performance functions to the simplest form. With the linearized performance functions, the walls' failure probability was calculated by direct integration and their reliability indices were determined accordingly. The reliability indices are in good agreement with those given by the Monte Carlo simulation (MCS) using a large number of samples. The proposed method does not deal with high dimensional limit state surfaces, it relieves the influence of uncertainty of the shear resistance model, and it is time-efficient. With these features, the proposed method can facilitate the reliability index calculation for in-plane shear failure of the URM walls. [ABSTRACT FROM AUTHOR]

This paper analyses decadal climate phenomena and the phases of the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), and assesses the climate–water–energy nexus at the reservoir system of the São Francisco River Basin (SFRB), Brazil. This study brings a non-traditional approach focused on the link between climatic patterns and hydrological processes and their social-economic consequences, such as their effect on energy production. The methodology used data from the precipitation, natural streamflow, and AMO and PDO series. These variables were evaluated by wavelet transform analysis (WTA), flow duration curve (FDC), streamflow that is equalled or exceed ed 90% of the time (Q90), the reliability index (RI) for different demands and the hydropower generated. The results suggest that the WTA for the SFRB was more significant on the inter-annual scale, and the period with opposite phases of AMO(−) and PDO(+) showed the highest values of FDC, Q90, RI and hydropower generated simulated for the SFRB. [ABSTRACT FROM AUTHOR]

Reliability estimates of compaction characteristics of lime-iron ore tailings (IOT) modified tropical black clay (i.e black cotton soil, BCS) for use as road construction material was carried out. A model was generated from measured laboratory test results, and then used in a FORTRAN-based first-order reliability program (FORM) to generate reliability indices (RI). Samples tested in the laboratory were subjected to index tests and British standard light (BSL) compaction test. In the midst of all the variables, specific gravity (Gs) recorded the greatest significant effect followed by sand content (Sa) and then Iron ore tailing (IOT) and Lime (Li) content on MDD. In the case of optimum moisture content (OMC), specific gravity (Gs), iron ore tailing content (IOT) and lime content (Li) has the most significant influence on OMC followed by sand content (Sa). Generally, RI values were less than 1.0 and thus fails to meet the conditions of Nordic Committee on Building Regulation (NKP) for serviceability limit state design. Stochastically, BSL compactive efforts recorded positive results but did not meet the requirement for modeling compaction characteristics of lime-IOT treated BCS as pavement sub-base material. Finally, higher compactive effort is recommended to model compaction characteristics of lime-IOT treated BCS in other to achieve more effective RI which that can be prudently examined during field compaction. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to capture efficiently the probability distribution of the limit state function (LSF) for structural reliability analysis. This method works by decomposing the probability distribution of the LSF into a Gaussian mixture and applying the scaled unscented transformation to approximate the required statistics for each mixture component. The number of mixture components is specified according to Akaike's information criterion. Because the required sample size grows linearly with the number of random inputs, little computational effort is required to recover the entire distribution of the LSF with precision. The effectiveness of the proposed method was validated through numerical examples, in which the results obtained from pertinent Monte Carlo simulations and other approaches are compared. The results demonstrated that the proposed method efficiently can yield accurate estimates of the probability distribution of the LSF in the entire range, and the probability of failure accordingly can be evaluated straightforwardly. Issues that need to be studied further were discussed. [ABSTRACT FROM AUTHOR]

Summary: Distribution networks have problems such as an increase in active losses, overload on distribution substations, voltage drop, decrease in network reliability, increase in load unbalance and unbalance in line current due to variable characteristics in terms of load consumption. In this article, to reduce losses, improve the voltage profile and increase the reliability of the system, the UPQC (Unified Power Quality Controller) optimal placement and reconfiguration method have been used in the distribution network. The two objective functions of losses and the mean voltage deviation are defined by considering the reliability indices. Since the reconfiguration of distribution networks is a large‐scale nonlinear hybrid optimization problem with several constraints, the genetic algorithm combines genes including key numbers and UPQC location, UPQC series power size, UPQC shunt power size used to solve the problem. The proposed method is implemented in three steps on IEEE 33‐bus and 69‐bus standard networks by considering the load model by genetic algorithm (GA). In the first stage, without considering the UPQC in the network, it only deals with the reconfiguration of the distribution network; at the second stage, without considering the network reconfiguration, only the appropriate UPQC placement is considered and in the final stage, the network reconfiguration and UPQC placement in these two networks are examined simultaneously. In this study, all simulations were performed with MATLAB software, and finally, reviewing and comparing the obtained results according to the solution method and the intended objective functions showed the proper performance of the proposed method compared to other methods. [ABSTRACT FROM AUTHOR]

Asymptotic sampling is an efficient simulation-based technique for estimating small failure probabilities of structures. The concept of asymptotic sampling utilizes the asymptotic behavior of the reliability index with respect to the standard deviations of the random variables. In this method, the standard deviations of the random variables are progressively inflated using a scale parameter to obtain a set of scaled reliability indices. The collection of the standard deviation scale parameters and corresponding scaled reliability indices are called support points. Then, least square regression is performed using these support points to establish a relationship between the scale parameter and scaled reliability indices. Finally, an extrapolation is performed to estimate the actual reliability index. The accuracy and performance of the asymptotic sampling method are affected by various factors including the sampling method used, the values of the scale parameters, the number of support points, and the formulation of extrapolation models. The purpose of this study is to make a critical evaluation of the performance of the asymptotic sampling method for highly safe structures, and to provide some guidelines to improve the performance of asymptotic sampling method. A comprehensive numerical procedure is developed, and structural mechanics example problems with varying number of random variables and probability distribution types are used in assessment of the performance of asymptotic sampling method. It is found that generating the random variables by Sobol sequences and using the 6-model mean extrapolation formulation give slightly more accurate results. Besides, the optimum initial scale parameter is approximately around 0.3 and 0.4, and the optimum number of support points is typically four for all problems. As the reliability level increases, the optimum initial scale parameter value decreases, and the optimum number of support points increases. [ABSTRACT FROM AUTHOR]

Decision-makers encounter heightened challenges in analyzing risks due to the intricate nature and uncertainty inherent in complex product delivery scenarios. To address these challenges, a reliability index-based group decision-making approach is proposed. Firstly, considering the abundance of information sources complicates verifying their authenticity, a reliability index is introduced. This index combines evaluation information with the reliability index to form two-dimensional linguistic information. Secondly, recognizing the personalized nature of linguistic information poses hurdles in alternative selection, integrating personalized individual semantics into information aggregation is emphasized. To capture the authentic perspectives of decision-makers, two linguistic optimization models are developed. Thirdly, acknowledging the subconscious emotional interactions among decision-makers and the interplay of opinions among them significantly influencing final decisions, the integration of quantum probability theory is proposed to construct an expert weight optimization model. Ultimately, the effectiveness and feasibility of this method are verified within a manufacturing company, providing crucial insights into real-world complex product delivery risk mitigation strategies. The results demonstrate that our proposed model efficiently integrates two kinds of linguistic information from participants based on personalized cognitions and selects the optimal alternative based on dual belief superposition. This article proposes the first GDM method for analyzing risk factors in complex product delivery, emphasizing personalized cognition and dual belief superposition, which are important factors previously rarely accounted for. • A reliability index is proposed to measure information source reliability. • Two-dimensional linguistic information is used to optimize decision-making. • Two optimization models are set to solve personalized cognitive deviation. • Dual belief superposition is studied to mitigate decision result impact. • A real-world issue for complex product delivery is applied to show the feasibility. [ABSTRACT FROM AUTHOR]

Because of their high electrocatalytic activity, sensitivity, selectivity, and long-term stability in electrochemical sensors and biosensors, numerous nanomaterials are being used as suitable electrode materials thanks to developments in nanotechnology. Electrochemical sensors and biosensors are two areas where two-dimensional layered materials (2DLMs) are finding increasing utility due to their unusual structure and physicochemical features. Nanosensors, by their unprecedented sensitivity and minute scale, can probe deeper into the structural integrity of piles, capturing intricacies that traditional tools overlook. These advanced devices detect anomalies, voids, and minute defects in the pile structure with unparalleled granularity. Their effectiveness lies in detection and their capacity to provide real-time feedback on pile health, heralding a shift from reactive to proactive maintenance methodologies. Harvesting data from these nanosensors, data was incorporated into a probabilistic model, executing the reliability index calculations through Monte Carlo simulations. Preliminary outcomes show a commendable enhancement in the predictability of vertical bearing capacity, with the coefficient of variation dwindling by up to 12%. The introduction of nanosensors facilitates instantaneous monitoring and fortifies the long-term stability of pile foundations. This study accentuates the transformative potential of nanosensors in geotechnical engineering. • Nanosensors detect pile defects with unprecedented sensitivity. • Real-time pile health monitoring shifts to proactive maintenance. • Data from nanosensors enhance vertical bearing capacity predictability. • Monte Carlo simulations used to calculate reliability indices. • Study shows up to 12% improvement in bearing capacity accuracy. [ABSTRACT FROM AUTHOR]

• Identifying the spatiotemporal variability of chloride diffusion in concrete. • Constructing a probabilistic framework for diffusion coefficient. • Developing a probabilistic model for service life prediction of marine structure. • Identifying the influence of random and non-random variables. Chloride-induced corrosion involves multiple factors and uncertainties. This study focuses on the probabilistic and multifactorial prediction model for the reliability and service life of reinforced concrete structures in marine environments. We present a new probabilistic framework to quantify the uncertainty of chloride transport by mesoscopic statistics and Spearman correlation analysis and develop a modified chloride transport model, incorporating multi-factors such as time dependence, admixture usage, temperature, relative humidity, stress level, freeze-thaw cycles, chloride binding capacity, aggregate volume fraction, aggregate particle size, and concrete deterioration. Taking the Shenzhen-Zhongshan Bridge as an example, by considering the chloride diffusion coefficient, concrete cover thickness, convection zone thickness, critical chloride concentration, and surface chloride concentration as random variables, the first-order reliability method (FORM) was employed to determine the time-variant reliability index and service life of the example bridge in different environmental conditions, encompassing atmospheric, splashing, tidal, and submerged zones. The sensitivity of the time-variant reliability to these random variables and the impact of the non-random variables on the reliability index were investigated quantitatively and comparatively. The findings reveal significant temporal and spatial variability in chloride diffusion coefficients due to the random arrangement of aggregates within concrete. The study demonstrates that concrete cover thickness and chloride diffusion coefficient are the most influential variables on structural reliability and emphasizes the substantial impact of admixtures, concrete deterioration, and environmental factors on the time-variant reliability. This research offers a significant reference in the reliability design, safety assessment, and maintenance of concrete structures in chloride-rich environments. [ABSTRACT FROM AUTHOR]

This study aims to develop a new technique for deriving the reliability index in original physical space using C-vine copula models integrated with the environmental contour method. In the proposed approach, the minimum of the reliability index is considered an objective function, whereas the coordinates on the environmental contour satisfying the limit state equation are treated as the constraint. These components are formulated as a non-linear constrained optimisation problem. The validity of this method is illustrated through four examples of its application, and the computed reliability index is compared with the results yielded by the existing sampling method. The findings confirm the superiority of the proposed technique. Compared with sampling simulation techniques, it is easier to obtain the critical environmental contour and the design point. Due to a pair-copula construction technique being applied to obtain high-dimensional vine copula models, the multivariate environmental contours are determined, which overcomes the limitation of existing contour line methods that are only used for solving low-dimensional problems. Unlike the first-order reliability method constructed in standard normal space, this new algorithm solves in the original physical space of random variables, making the calculation principles more transparent and easier to understand. • Multivariate joint probability distribution is constructed using pair-copulas. • Environmental contours are generated for data-driven applications. • Alternative methods for estimating the reliability index are developed. • Critical contour is determined in original physical space of random variables. [ABSTRACT FROM AUTHOR]