Reliability Analysis Method Research Articles

A novel reliability-based robust design optimization method integrating a multivariate quality loss function and advanced finite step length

To enhance the robustness of mechanical structures and reduce fluctuations in reliability, a novel reliability-based robust design optimization method combining a multivariate quality loss function (MQLF) and advanced finite step length (AFSL) is proposed. Gaussian process regression is used to formulate an MQLF for mechanical structures, integrating multiple quality characteristic deviations, predicted quality and robustness. An AFSL method for structural reliability analysis is proposed, effectively enhancing the efficiency and accuracy of reliability calculations through conjugate gradient search and an adaptive step length adjustment formula, while also solving the reliability sensitivity using the AFSL method. A multi-objective reliability-based robust optimization model is established with the objective of the MQLF and reliability sensitivity, considering structural reliability and design variable tolerances as constraints. Practical examples demonstrate that the proposed method achieves an optimal equilibrium solution, accounting for both quality loss and reliability sensitivity, in contrast to the traditional approach.

High-throughput markerless pose estimation and home-cage activity analysis of tree shrew using deep learning.

Quantifying the rich home-cage activities of tree shrews provides a reliable basis for understanding their daily routines and building disease models. However, due to the lack of effective behavioral methods, most efforts on tree shrew behavior are limited to simple measures, resulting in the loss of much behavioral information. To address this issue, we present a deep learning (DL) approach to achieve markerless pose estimation and recognize multiple spontaneous behaviors of tree shrews, including drinking, eating, resting, and staying in the dark house, etc. RESULTS: This high-throughput approach can monitor the home-cage activities of 16 tree shrews simultaneously over an extended period. Additionally, we demonstrated an innovative system with reliable apparatus, paradigms, and analysis methods for investigating food grasping behavior. The median duration for each bout of grasping was 0.20 s. This study provides an efficient tool for quantifying and understand tree shrews' natural behaviors.

Automatic monitoring and on-line chiral separation of chiral drug synthesis.

Chiral synthesis of single chiral drugs offers high efficiency, controllable costs, and excellent enantioselectivity, making it crucial in the pharmaceutical industry. A significant number of studies on chiral drug synthesis primarily focuses on the design and synthesis of innovative chiral catalysts and ligands with extremely high selectivity, as well as the development of new methods and strategies. Nonetheless, the on-line monitoring of chiral drug synthesis and its underlying mechanisms remain obscure. The principal challenge lies in the diverse synthesis pathways and intricate mechanisms of chiral drugs, with numerous intermediates and by-products. To tackle this issue, employing the chiral drug omeprazole as a breakthrough, we design and establish a reliable and stable analytical method to monitor the synthesis process. By integrating electrokinetic chromatography technology with automatic sequence injection, the chiral synthesis of omeprazole can be comprehensively tracked and monitored throughout its entire process. During the chiral drug synthesis process, all compounds, containing all reagents and products (omeprazole sulfide, R-omeprazole, S-omeprazole, iodobenzene and iodobenzene diacetate) are efficiently separated and simultaneously detected through a single run. The method shows a high resolution greater than 1.2, a wide linear range with a detection limit as low as 0.008 μM, as well as exceptional repeatability in sequence analysis. Therefore, the proposed method has demonstrated significant value in the analysis of chiral drug synthesis and holds potential for extensive application in the industrial production of chiral compound synthesis.

Application of QuEChERS for analysis of contaminants in dairy products: a review.

The safety of dairy products is intrinsically linked to consumer health, and the exceedance of risk indicators, such as pesticide and veterinary drug residues, constitutes one of the primary issues affecting their quality and safety. To assess the safety of dairy products, it is crucial to develop accurate and reliable analytical methods for their detection. Food safety testing involving important indicators such as pesticide residues, veterinary drug residues, mycotoxins and unapproved additives has become a pivotal requirement in the industry field. The QuEChERS (Quick、Easy、Cheap、Effective、Rugged、Safe) method is widely acknowledged as a food safety analysis method currently. This method can effectively extract a wide range of compound classes from diverse matrices in food safety testing, thereby enhancing the accuracy of detection. Additionally, when combined with chromatographic-mass spectrometry techniques, it can simultaneously analyze hundreds of target analytes, rendering it widely applicable in the quality and safety testing of dairy products. Although QuEChERS has rapidly developed in the field of dairy product quality and safety analysis due to its efficiency and speed advantages, certain shortcomings remain, presenting considerable room for improvement. This paper presents a comprehensive review of the utilization and research advancements of the QuEChERS technique in dairy products, with the aim of providing more precise, expeditious, and reliable methods for the safety assessment of dairy products.

Finite-Element-Based Time-Dependent Service Life Prediction for Carbonated Reinforced Concrete Aqueducts

This study proposes a time-dependent reliability analysis method for aqueduct structures based on concrete carbonation and finite element analysis. The primary goal of this study is to improve the reliability assessment of reinforced concrete aqueducts by incorporating environmental factors such as carbonation over time. First, a three-dimensional finite element model of a reinforced concrete aqueduct is established using the Midas 2022 Civil software, incorporating a time-varying function derived from a predictive model of concrete carbonation depth. Point estimation is then integrated with structural finite element analysis to calculate the first four moments of random variables as functions of concrete carbonation. Additionally, the original performance function is transformed into a normal distribution using dual power transformation and the Jarque–Bera test. The high-order unscented transformation (HUT) is subsequently employed to estimate the first four moments of the transformed performance function, facilitating the calculation of time-varying reliability indices for the carbonated concrete aqueduct. Based on the time-varying reliability index data, a reliability function corresponding to different time points is fitted and applied to service life prediction. The results demonstrate that the proposed method effectively reduces large errors associated with the fourth-moment method in calculating large reliability indices. Furthermore, the comparison with Monte Carlo simulation (MCS) results validates the high efficiency and accuracy of the proposed method, offering a valuable tool for addressing the reliability challenges of aqueducts exposed to carbonation and other environmental factors over time.

Preparation of matrix-matched calibration standards for accurate determination of elemental concentrations in uric acid stones by LA-ICP-MS.

Accurate determination of elemental concentrations in uric acid (UA) stones is crucial for understanding their formation process. However, the lack of matrix-matched calibration standards has limited the application of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) in this field. This study addresses this limitation by preparing a synthetic UA precipitate (UA-1) doped with 17 elements using a recrystallization method. Reference concentrations of these elements were measured using pneumatic nebulization-ICP-MS (PN-ICP-MS) for calibration purposes. The synthetic standard was characterized through 30 random spot analyses, demonstrating a homogeneity of approximately 5%. Using this synthetic standard, a reliable analytical method was developed, achieving limits of detection (LODs) ranging from 0 to 0.42 μg g-1. The method's accuracy, with relative deviations between -8.33% and 0 and correlation coefficients (R2) greater than 0.99, confirms its reliability. Additionally, elemental distribution differences observed across various zones in a real UA stone suggest that this method offers a promising approach for the precise analysis of elemental concentrations in UA stones.

A novel self-adaptive step size first-order method for structural reliability analysis based on modified Sigmoid function and Armijo rule

A novel self-adaptive step size first-order method for structural reliability analysis based on modified Sigmoid function and Armijo rule

Microchip capillary electrophoresis-mass spectrometry for high-throughput simultaneous analysis of B-complex vitamins.

B-complex vitamins are essential micronutrients that maintaining health, and provide (individually/simultaneously) many important biological actions in organism. Therefore, sensitive, reliable analytical method to determine B-complex vitamins simultaneously in actual samples is significant. Conventional analytical methods for vitamins analysis are usually labor-intensive, time-consuming and mostly do not allow the simultaneous determination. Few papers have been published on capillary electrophoresis-mass spectrometry (CE-MS) analysis of individual vitamin B or B-complex vitamins. Microchip capillary electrophoresis (ME) offers less consumption of background electrolyte and reagents than CE, and fast separation as having several channels for high-throughput. ME based on ZipChip integrates sample injection, electrophoretic separation, and ESI functions into one platform, herein, for the first time, in this paper, the ME-MS based on ZipChip platform was investigated and demonstrated preliminarily a significant improvement over existing techniques. Because: the ME-MS method has a linear response with excellent precision for replicate injections and LODs lower than 4 ppb; The method is simple and fast (<3 min per sample), using a small amount of sample (∼5 nL) with low reagent consumption, making it suitable for high-throughput applications; The inter/intraday reproducibility (RSD %) is less than 3 %, which is important for clinic application.

Development and validation of a UHPLC-MS/MS method for the quantitative analysis of trans-ISRIB in human plasma.

The integrated stress response (ISR) is a cellular defense mechanism activated under stress conditions. When the ISR is activated, it slows the production of proteins, the building blocks that cells need to function. Trans-integrated stress response inhibitor (trans-ISRIB) is a compound that can reverse the effects of ISR activation, showing promise for treating neurodegenerative diseases. The preclinical and clinical evaluation of trans-ISRIB necessitates a reliable analytical method. This study presents the development and validation of an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for the quantitative analysis of trans-ISRIB in human plasma, conforming to the U.S. FDA's guidelines for bioanalytical method validation. The method developed utilizes a liquid-liquid extraction procedure to prepare plasma samples with a spiked internal standard (IS). The extracts containing trans-ISRIB and the IS were dried under nitrogen, reconstituted in the mobile phase, and separated on a Waters XSelect HSS T3 column under isocratic conditions with a mobile phase containing 0.1% acetic acid in 70% methanol aqueous solution at a flow rate of 0.500mL/min. Detection and quantification were accomplished using a positive electrospray ionization tandem mass spectrometer (ESI+-MS/MS) operated in multiple-reaction-monitoring (MRM) mode. The method demonstrated a linear calibration range for trans-ISRIB concentrations from 0.500 to 1.00x103 nM, with high specificity, precision, accuracy, and recovery. This method addresses a significant analytical gap, offering a robust tool for quantifying trans-ISRIB in human plasma. Chemical compounds studied in this article: 2-(4-chlorophenoxy)-N-[4-[[2-(4-chlorophenoxy)acetyl]amino]cyclohexyl]acetamide (trans-ISRIB) (CAS # 1597403-47-8); 2-(4-chlorophenoxy)-N-(2-{[(4-chlorophenoxy)acetyl]amino}ethyl)acetamide (CAS # 327071-30-7).

A high-dimensional reliability analysis method via subspace updating and Gaussian process

A high-dimensional reliability analysis method via subspace updating and Gaussian process

Validation of Wavelength-Dispersive X-Ray Fluorescence Technique for Rapid Screening Iron and Zinc Concentration in Rice Seed

This study focuses on the validation of a wavelength dispersive X-ray fluorescence (WD-XRF) spectrometer for the rapid determination of iron (Fe) and zinc (Zn) concentrations in certified reference materials (CRMs). Five CRMs were used to establish calibration curves. The results were analyzed in terms of accuracy, precision, repeatability and linearity to assess the performance of the WD-XRF method. Accuracy was evaluated by comparing measured values to certified values, with relative accuracy calculated for each sample. Precision was determined through repeatability, where samples were measured in at least 7 replicates across different days, and relative standard deviation (RSD) was calculated. Linearity was assessed by plotting measured intensities and concentrations against certified concentrations, with the correlation coefficient (R2) values close to 1, indicating a strong linear relationship. Additionally, the WD-XRF method demonstrated high repeatability, with low RSD values across multiple measurements. The study concluded that WD-XRF is a reliable method for the rapid analysis of elemental composition, providing strong accuracy, precision and linearity for Fe and Zn determination in CRMs and can be applied as a valuable method for rapid and non-destructive analysis in various agricultural and food-related applications. HIGHLIGHTS The effectiveness of wavelength dispersive X-ray fluorescence (WD-XRF) method was evaluated to confirm its reliability for determining the elemental composition, specifically iron (Fe) and zinc (Zn), in plant-based certified reference materials (CRMs). Five CRMs were used for calibration and 2 known samples were used as the test samples to determine the analytical performance of WD-XRF. The linearity and correlation with the certified values of WD-XRF results revealed strong correlation with R-square being greater than 0.95 and the recovery percentage of 2 known samples were range from 98.75 - 109.66 for Fe and Zn concentration. WD-XRF spectrometer can be used as a rapid method for determination of Fe and Zn concentrations in rice seeds. GRAPHICAL ABSTRACT

Reliability evaluation of rolling bearings based on generative adversarial network sample enhancement and maximum entropy method

Aiming at the difficulty of extracting vibration data under actual working conditions of rolling bearings, this paper proposes a bearing reliability evaluation method based on generative adversarial network sample enhancement and maximum entropy method under the condition of few samples. Based on generative adversarial network, data sample enhancement under few samples is carried out, and the reliability analysis model is established by using the maximum entropy principle and Poisson process. The reliability is evaluated according to the reliability variation frequency, variation speed and variation acceleration. The analysis results show that with the gradual increase of running time, the reliability variation frequency shows a nonlinear growth trend, which can be roughly divided into the initial running-in stage, the stable running-in stage and the intense running-in stage. The reliability variation speed is then used to distinguish the specific starting time of the three stages, and finally the preliminary relationship between the reliability variation acceleration and the remaining life is obtained. The experimental results of the XJTU-SY dataset show that compared with the existing reliability evaluation model, the proposed model has the advantages of less samples, no need for preprocessing and higher accuracy. The proposed model has made a beneficial supplement to the existing reliability analysis methods.

Concurrent Detection of Protein and miRNA at the Single Extracellular Vesicle Level Using a Digital Dual CRISPR-Cas Assay.

The simultaneous detection of proteins and microRNA (miRNA) at the single extracellular vesicle (EV) level shows great promise for precise disease profiling, owing to the heterogeneity and scarcity of tumor-derived EVs. However, a highly reliable method for multiple-target analysis of single EVs remains to be developed. In this study, a digital dual CRISPR-Cas-powered Single EV Evaluation (ddSEE) system was proposed to enable the concurrent detection of surface protein and inner miRNA of EVs at the single-molecule level. By optimizing simultaneous reaction conditions of CRISPR-Cas12a and CRISPR-Cas13a, the surface protein of EVs was detected by Cas12a using antibody-DNA conjugates to transfer the signal of the protein to DNA, while the inner miRNA was analyzed by Cas13a through EV-liposome fusion. A microfluidic chip containing 188,000 microwells was used to convert the CRISPR-Cas system into a digital assay format to enable the absolute quantification of miRNA/protein-positive EVs without bias through fluorescence imaging, which can detect as few as 214 EVs/μL. Finally, a total of 31 blood samples, 21 from breast cancer patients and 10 from healthy donors, were collected and tested, achieving a diagnostic accuracy of 92% in distinguishing patients with breast cancer from healthy donors. With its absolute quantification, ease of use, and multiplexed detection capability, the ddSEE system demonstrates its great potential for both EV research and clinical applications.

Optimal vibration control with considering non-probabilistic time-dependent reliability for hypersonic vehicles

Hypersonic vehicles have complex structures with multiple sources of uncertainties, and the presence of uncertainties may lead to the vehicles’ structural failure. Aiming to ensure the flight safety and structural reliability of a hypersonic vehicle, this study proposes a vibration optimization control method based on non-probabilistic time-dependent reliability. Due to the complex structure of the vehicle, its forebody and aftbody are modeled as two cantilever beams with the center of mass of the vehicle as the fixed fulcrum, respectively, and a vibration control model of cantilever is derived. Considering that the uncertainties in practical engineering are not easy to be counted, the uncertain parameters are quantified by using interval variables, and the dynamic response and time-dependent reliability of the uncertain system are analyzed based on the subinterval method and the non-probabilistic time-dependent reliability analysis method (NTRAM) designed in this paper. Further, to ensure the high reliability of the vehicle, an optimal robust linear quadratic regulator (ORLQR) method with the constraint of time-dependent reliability is proposed. The analysis of the numerical examples shows that the parameter uncertainty has a certain effect on the reliability of the vehicle, and verifies that the proposed ORLQR method can effectively control the vibration and slow down the reliability decline.

Identification of a novel imidazole-derived GABA agonist isopropoxate: simultaneous detection and quantification of imidazole-derived analogs from human hairs in abused cases by LC-MS/MS.

Distribution and abuse of imidazole-derived γ-aminobutyric acid (GABA) agonists, such as etomidate and metomidate, and their analogs have been encountered frequently especially in China. The aim of this study was to identify etomidate, metomidate, propoxate, and isopropoxate more accurately by establishing a gas chromatography-mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS) method and applying it to real forensic cases. Onemg of the seized powder was dissolved in 1mL of methanol, and subjected to GC-MS and LC-MS/MS. Hair samples were washed and cut into approximately 2mm sections, then ground to powder by a low-temperature grinder. Twenty mg of the hair powder was extracted with 1mL of methanol, and the supernatant was subjected to LC-MS/MS. Etomidate, metomidate, propoxate, and isopropoxate were chromatographically separated and each mass spectrum was obtained by GC-MS. For LC-MS/MS, tested validation data were all satisfactory. The seized powder samples contained isopropoxate, with an approximate content of 30.9%. Etomidate, etomidate acid, metomidate, and isopropoxate could be determined in the submitted hairs, ranging from 2.89 to 8.09ng/mg, 0.0591-0.177ng/mg, 0.342-2.77ng/mg, and 33.2-130ng/mg, respectively. Mass spectra and ion chromatograms of etomidate, metomidate, isopropoxate, and propoxate were obtained by GC-MS. We have also established a simultaneous and reliable analytical method for etomidate, etomidate acid, metomidate, and isopropoxate in human hair by LC-MS/MS. This is the first report to present analytical results of a novel imidazole-derived GABA agonist isopropoxate in drug abuse cases.

A Novel Two‐Stage Reliability Analysis Method Combining Improved Cross‐Entropy Adaptive Sampling and Relevant Vector Machine

ABSTRACTThe computational burden becomes unbearable when reliability analysis involves time‐consuming finite element analysis, especially for rare events. Therefore, reducing the number of performance function calls is the only way to improve computing efficiency. This paper proposes a novel reliability analysis method that combines relevant vector machine (RVM) and improved cross‐entropy adaptive sampling (iCE). In this method, RVM is employed to approximate the limit state surface and iCE is performed based on the constructed RVM. To guarantee the precision of RVM, the first level samples and the last level samples of iCE are used as candidate samples and the last level samples are regenerated along with the RVM updates. To prevent unnecessary updates of RVM, the proposed method considers the positions of the samples in the current design of experiment. In addition, based on the statistical properties of RVM and iCE, an error‐based stopping criterion is proposed. The accuracy and efficiency of the proposed method were validated through four benchmark examples. Finally, the proposed method is applied to engineering problems which are working in extreme environment.

A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure

In recent years, marine structures have been widely used in the world, making significant contributions to the utilization of marine resources. In the design of marine structures, there is a hybrid reliability problem arising from aleatory uncertainty and epistemic uncertainty. In many cases, epistemic uncertainty is estimated by interval parameters. Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. In response to this problem, this paper proposes a de-nesting hybrid reliability analysis method creatively. Firstly, it uses the p-box model to describe the epistemic uncertainty variables, and then the linear approximation (LA) model and the two-point adaptive nonlinear approximation (TANA) model are combined to approximate the upper and lower bounds of LSF with epistemic uncertainty. Based on the first-order reliability method (FORM), an iterative operation is used to obtain the interval of the non-probability hybrid reliability index. The traditional nested optimization structure is effectively eliminated by the above approximation method, which efficiently reduces the times of LSF calls and increases the calculation speed while preserving sufficient accuracy. Finally, one numerical example and two engineering examples are provided to show the greater effectiveness of this method than the traditional nested optimization method.

Phenolic Compounds and Antioxidant Activity in Monovarietal Red Wines from Lazio Cultivars: A Chemometric Evaluation

Background: Antioxidant activity is currently one of the most significant characteristics of red wines, mainly attributable to phenolic components, that enhance health-promoting effects. To this purpose, it is necessary to implement simple, and reliable analytical methods for evaluating such bioactive compounds in wines according to their background. Objective: This research aims to characterize the phenolic and antioxidant activity of 48 commercial monovarietal red wines produced from eight native Lazio cultivars (“Cesanese del Piglio”, “Cesanese di Olevano Romano”, “Cesanese da Castel Franco”, “Olivella del Frusinate”, “Nostrano”, “Syrah”, “Merlot”, and “Nero Buono”), according to different winemaking techniques and vintage. Methods: The characterization was carried out through the chromatographic determination of anthocyanins (HPLC-PDA), spectrophotometric assays for total phenolic content (TPC), total flavonoid content (TFC), total phenolic acid content (TPAC), and antioxidant activity (AA) through ABTS, and DPPH assays, coupled with chemometric tools (Principal Component Analysis and Cluster Analysis). Results: The quantitative determination of phenolic compounds showed significant (p &gt; 0.05) differences according to wine cultivars. Wine belonging to ‘Syrah’, ‘Nero Buono’, ‘Cesanese del Piglio’ and ‘Cesanese di Olevano Romano’ cultivars showed the highest TPC (2.673 – 4.094; 1.963 – 3.859, 2.104 – 3.794, and 2.668 – 3.549 mg GAE/L, respectively), as well as the highest TFC and TPAC. Conclusion: In addition, wines sharing cold maceration (i.e., COR and CP samples) resulted in the highest total anthocyanidin content with a variable malvidin and cyanidin distribution percentage; as well as younger wines (2019) showed the highest TPC and anthocyanidins content. In these regards, the natural groupings among samples obtained by chemometrics reinforce the influence of cultivar origin, the wine-making process, as well as wine aging on phenolic content and compositions, thus acting as fingerprints for specific grape cultivars.

From freeze to function: optimised cryopreservation and mitochondrial analysis workflow for skeletal muscle biopsies

BackgroundSkeletal muscle biopsies are valuable in clinical and research settings, contributing to advancements in diagnosing, understanding, and treating muscle-related conditions. Traditional freezing methods often cause artefacts mistaken for disease, leading to incorrect diagnoses or misinterpretation of research findings. Proper handling of muscle biopsies is critical for accurate histopathological and mitochondrial analysis. It is essential to preserve the entire tissue, especially for small needle biopsies. While most research focuses on mitochondrial analysis in cells, there are few studies on whole tissue samples. This study aimed to provide an effective methodological workflow to improve cryopreservation techniques for human and rodent muscle biopsies and create a reliable method for mitochondrial analysis in muscle tissues.MethodsHuman muscle samples were preserved with different concentrations of formaldehyde after freezing with liquid nitrogen to study the effects of freeze–thaw cycles. We compared the edge and belly of muscle samples embedded in Optimal Cutting Temperature compound (OCT) to see how OCT affects ice crystal formation. Rat muscle biopsies were frozen using six different methods, using liquid nitrogen and precooled isopentane as freezing media. Each medium involved direct immersion, OCT dip before immersion, and placement in histocassettes before immersion. Effectiveness of these methods was evaluated using histological and immunohistochemical staining. Mitochondrial analysis in type I and II myofibres was attempted by employing the Trainable Weka Segmentation plugin using Fiji.ResultsHistologically stained human tissue sections showed that freeze–thaw and formaldehyde fixation led to freezing artefacts, disrupted endomysium, and widely spaced cells. Quantitative differences in ice crystal artefacts between edge and belly of rat whole muscle samples demonstrated effects of OCT in crystal formation. Histological and immunohistochemical staining of sections from rat muscle biopsies frozen in six different cryopreservation techniques revealed that only isopentane/histocassette combination preserved tissue integrity in both core and periphery of tissue sections. Moreover, an optimised Fiji workflow enabled accurate quantification and mapping of mitochondrial networks.DiscussionThe isopentane/histocassette combination is an effective cryopreservation method, ensuring artefact-free preservation of both core and periphery of tissue sections. Our workflow utilising Trainable Weka Segmentation plugin provides a reliable method for mitochondrial analysis in skeletal muscle tissues, facilitating future studies in muscle research.

Methodology for Reliability Analysis of Reinforced Concrete Structures over time Considering Combined Corrosion

One of the main causes of deterioration in reinforced concrete structures (RC) is the corrosion of steel bars. Many factors, including materials, environments, and loading conditions, which often have uncertain characteristics, affect the performance of RC structures. Some uncertainties may depend on time and location, and associated reliability issues become more difficult to address. This study presents a comprehensive method for assessing the temporal reliability of reinforced concrete structures, taking into account combined effects of carbonation (general corrosion) and chloride penetration (pitting corrosion). Probabilistic models are used to capture uncertainties related to the beginning, propagation, and combined effects of corrosion on structural performance over time. The time-dependent reliability of bridge structures is evaluated using sophisticated numerical simulations in conjunction with the FORM method for reliability analysis. Both time and space variables are treated as uniformly distributed random variables within specific intervals when generating sample points. Engineers and decision-makers can assess the reliability of reinforced concrete bridges using a systematic framework that considers the complex interactions of corrosion mechanisms. This aids an informed maintenance planning and effective resource allocation to ensure long-term structural safety and durability. Finally, the suggested method is tested on a reinforced concrete bridge with corroded steel reinforcement bars. The original work is validated, and the results are compared with the crude Monte Carlo simulation (MCS) method.