Failure Distribution Research Articles

Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications

The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.

Sex differences in in-hospital management and outcomes of patients with acute pulmonary embolism

Abstract Background Acute pulmonary embolism (PE) is a life-threatening disease with specific risk factors among women. Systematic evaluation of contemporary quality of care and outcomes in women hospitalized with acute PE is needed. Methods The COPE Registry (COntemporary management of acute Pulmonary Embolism) is a nationwide registry that was run in Internal Medicine, Cardiology and Emergency Departments in Italy. Using data from the COPE Registry, we evaluated sex differences in acute management, medical therapies, in-hospital and 30-day mortality and major bleeding in 5,213 patients admitted for acute PE at 182 hospitals in Italy from 2018 to 2020. Results Women (n=2,728) were older than men (71.2 versus 66.6 years, P<0.001) and had different distribution of comorbidities, with dementia and severe renal failure being more prevalent (13.6 vs 6.4% and 6.1 vs 3.0%, respectively) and cancer, COPD and recent bed-rest less prevalent (15.2 vs 18.5% and 11.1 vs 14.5% and 23.5 vs 20.2%) in women than men. At presentation, PE was more severe in women than men in terms of hemodynamic instability (4.1 vs 2.7%), prevalence of right ventricle overload at echocardiography (64.5 vs 57%) and prevalence of sPESI=0 (29.4 vs 38.5%). Concerning the likelihood to receive evidence-based acute treatments for PE, women were more likely than men to receive reperfusion in the case of hemodynamic compromise at presentation after adjusting for age and dementia (63.1 vs 50.0%; OR 1.934, 95% CI 1.01-3.71), and to receive direct oral anticoagulants during hospitalization after adjusting for age, dementia and severe renal failure (50.9 vs 48.6%; OR 1.14, 95% CI 1.01-1.28); similar proportions of low-risk women and men were managed as outpatients or by short hospital stay (1.4% vs 1.4% and 8.6 vs 6.0%, respectively). In-hospital and 30-day mortality rates were not different in women and in men (3.7% versus 3.1% and 5.5 vs 4.8%), but PE-related mortality was higher in women than in men (2.1 vs 1.3%). The sex difference in PE-related mortality was no longer observed in after adjusting for age, hemodynamic instability and dementia (adjusted HR 1.20; 95% CI 0.77-1.88; P=0.415). Similar rates of early and delayed major bleedings occurred in women and in men, both at univariate analysis and after adjusting for age, creatinine clearance and use of thrombolysis. None of 22 pregnant women and 1 out of 204 women with estro-progestin associated PE died or experienced major bleeding. Conclusions Women hospitalized for acute PE in Italy received evidence-based acute treatments more commonly than men. The observed sex differences in PE-related mortality were mainly attributable to worse clinical profiles and older age. Women with sex-related risk factor for PE had favorable prognosis.

Data-driven corrosion failure probabilistic assessment model for reinforced concrete structures

The corrosion-induced failure of marine reinforced concrete structures, stemming from prolonged exposure to environments with elevated chloride content, poses a significant threat to structural integrity and serviceability. Traditional models predominantly depend on prior information to estimate the spatial stochastic degradation of aging structures, leading to a lack of comprehensiveness and accuracy in evaluation results. To address these limitations, a data-driven probabilistic assessment model for corrosion failure is proposed. This model incorporates a pre-training phase that integrates electrochemical simulations with long-term exposure data to establish the spatiotemporal distribution of corrosion failures, thereby facilitating a thorough assessment of overall damage by quantifying the corrosion failure proportion while propagating epistemic uncertainty. Subsequently, a multivariate function is derived using the non-dominated sorting genetic algorithm to elucidate the relationship between input and output variables. The efficacy of the data-driven model is evaluated through experimental observations and model predictions. The Hangzhou Bay Bridge project serves as a case study, wherein this model is demonstrated using actual data obtained from exposure experiments and field detection. Furthermore, the proposed model enables a rapid prejudgment of corrosion failure proportion, significantly reducing diagnostic time compared to conventional procedures.

Spare parts provisioning strategy of warranty repair demands for capital-intensive products

The inventory cost of stocking spare parts is a nonnegligible expenditure of providing after-sales service for the manufacturers making capital-intensive products, such as electric vehicles. Especially, for warranty repair service, it is important to manage the spare stock appropriately to satisfy the warranty claims of customers as well as reduce the associated inventory costs. In this paper, we investigate the spare parts inventory issue related to a critical component for under-warranty units of a product. In particular, under the free-replacement warranty policy, failed component will be replaced by a new one by consuming the spare stock. According to the field claim data, we find that the general trend of warranty claims is nonstationary, which will be affected by the product sales and under-warranty failures. Thus, we first propose a model to forecast the time-varying warranty repair demand by explicitly considering the randomness from two major sources, that is, product sales and under-warranty failures. Under the assumptions of Poisson sales process and exponential failure distribution, the closed-form expressions of mean and variance of cumulative warranty repair demand over time are obtained. Because the number of warranty claims in each period is a one-time data, the associated distribution information is unavailable. Then, based on the properties of the demand statistics, we derived a worst-case upper bound for the associated inventory cost and formulate a three-phase finite-horizon spare parts inventory model, which can be used to appropriately address the time-varying warranty claims. Finally, numerical experiments are conducted to investigate the key parameters affecting the optimal decisions where a case study based on real data is presented.

Enhancing Wireless Network Efficiency with the Techniques of Dynamic Distributed Load Balancing: A Distance-Based Approach.

The unique combination of the high data rates, ultra-low latency, and massive machine communication capability of 5G networks has facilitated the development of a diverse range of applications distinguished by varying connectivity needs. This has led to a surge in data traffic, driven by the ever-increasing number of connected devices, which poses challenges to the load distribution among the network cells and minimizes the wireless network performance. In this context, maintaining network balance during congestion periods necessitates effective interaction between various network components. This study emphasizes the crucial role that mobility management plays in mitigating the uneven load distribution across cells. This distribution is a significant factor impacting network performance, and effectively managing it is essential for ensuring optimal network performance in 5G and future networks. The study investigated the complexities associated with congested cells in wireless networks to address this challenge. It proposes a Dynamic Distance-based Load-Balancing (DDLB) algorithm designed to facilitate efficient traffic distribution among contiguous cells and utilize available resources more efficiently. The algorithm reacts with congested cells and redistributes traffic to its neighboring cells based on specific network conditions. As a result, it alleviates congestion and enhances overall network performance. The results demonstrate that the DDLB algorithm significantly improves key metrics, including load distribution and rates of handover and radio link failure, handover ping-pong, and failed attached requests.

Advancing the analysis of water pipe failures: a probabilistic framework for identifying significant factors

The failure of water pipes in Water Distribution Networks (WDNs) is associated with environmental, economic, and social consequences. It is essential to mitigate these failures by analyzing the historical data of WDNs. The extant literature regarding water pipe failure analysis is limited by the absence of a systematic selection of significant factors influencing water pipe failure and eliminating the bias associated with the frequency distribution of the historical data. Hence, this study presents a new framework to address the existing limitations. The framework consists of two algorithms for categorical and numerical factors influencing pipe failure. The algorithms are employed to check the relevance between the pipe’s failure and frequency distributions in order to select the most significant factors. The framework is applied to Hong Kong WDN, selecting 10 out of 21 as significant factors influencing water pipe failure. The likelihood feature method and Bayes’ theorem are applied to estimate failure probability due to the pipe materials and the factors. The results indicate that galvanized iron and polyethylene pipes are the most susceptible to failure in the WDN. The proposed framework enables decision-makers in the water infrastructure industry to effectively prioritize their networks’ most significant failure factors and allocate resources accordingly.

Stress Characteristics and Mechanical Behavior of Rock Masses with an Opening under Complex Deep Underground Stress Conditions

In this study, the impact of principal stress states on the stress characteristics and initial failure of the rock mass surrounding a three-center arch opening was investigated using complex variable function methods and Discrete Element Method (DEM) numerical modeling. First, the mapping function of the opening was determined using the trigonometric interpolation method, and the influence of the number of terms in the mapping function on its accuracy was revealed. Based on this, the far-field stress state of the underground rock mass was characterized by the ratio of the minimum to maximum principal stress (λ) and the angle (β) between the principal stress and the vertical direction. This stress state was then converted into normal and shear stresses. Using complex variable function theory, the stress characteristics at the boundary of the opening under different stress states were analyzed. Finally, DEM numerical modeling was employed to study the initial failure characteristics at the boundary of the opening and its relationship with the stress distribution. The results indicate that the lateral pressure coefficient significantly affects the stability of the opening by influencing stress concentration around the surrounding rock. Low lateral pressure coefficients lead to tensile stress concentration at the boundary perpendicular to the maximum principal stress. As the coefficient increases, tensile stress decreases, and compressive stress areas expand. While the principal stress direction has a minor effect on stress concentration, it notably impacts stress distribution at the boundary. When λ < 1.0 and β = 45°, stress distribution asymmetry is most pronounced, with the highest compressive stress. The early failure distribution aligns with stress concentration areas, validating the use of stress analysis in predicting opening stability and failure characteristics.

Assessment of loss of life owing to dam-failure flooding considering population distribution and evacuation

Dam failures pose a serious threat to the safety of downstream populations. Scientifically assessing loss of life (LOL) from dam-failure flooding contributes to the emergency response. Population distribution varies spatially and temporally even within a day, and has different information dissemination and response speeds, which impacts the chances of safe evacuation. This study established an LOL assessment model that considers the initial population distribution and population evacuation process. Shared bike big data and other multi-source data were used to identify daily population activity. The evacuation process includes receiving warnings, responses, and horizontal or vertical evacuation choices, and the evacuation results were then evaluated. This model was applied to a dam in China. During nighttime, commuting, and working hours, the issuance of warnings 214 min, 137 min, and 0 min prior to dam failure, respectively, significantly mitigated LOL. Under the same communication and response speeds, the commuting period poses the highest risk of LOL. Assessments of LOL due to dam failure flooding need to consider the impact of the timing of dam failure and population distribution. The model used in this study proposes varying effective early warning times based on the time of dam failure occurrence, which can contribute to effective dam risk management, helping prevent personnel loss.

Accounting for defect position in ultrasonic fatigue test specimen with heterogeneous stress distribution

To account for or neglect the defect position, i.e. the fatigue initiating defect location, both radially and axially, is evaluated for hourglass-shaped ultrasonic fatigue specimen. The commonly used analytical equations to calculate the stress is compared against a finite element (FE) based approach, which is able to fully considering the stress state at the defect position. Notably, the effects on several common fatigue analyses are evaluated: the fatigue strength distribution, the stress–life and the stress–defect relationships. Fracture mechanical assessment is also performed, for a comprehensive VHCF characterization of the EN-GJS-500-7 ductile cast iron used in the study. The VHCF properties are characterized up to 3⋅108 cycles, using the Step-Stress fatigue testing method under fully reversed loading. The FE-model and Weibull distribution as the choice of fatigue strength distribution, enables size effect evaluation by Weakest-link effective volume with the highly stressed volume method as benchmark. The work shows that it is imperative to use the local stress state at the defect position, as the distribution of failures can diverge largely from the center of the specimen, and that neglecting this causes systematic error and flawed potentially results.

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. This study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MWelec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

Estimation of Extreme Value Distribution and Probability of Minor Failures in Rockfill Dam Response to Non-Stationary Seismic Excitation

Estimation of Extreme Value Distribution and Probability of Minor Failures in Rockfill Dam Response to Non-Stationary Seismic Excitation

Effect of Different Primers on the Shear Bond Strength of Orthodontic Brackets Bonded to Reinforced Polyetheretherketone (PEEK) Substrate.

This in vitro study assessed the effect of different primers on the shear bond strength (SBS) and adhesive remnant index (ARI) of orthodontic brackets bonded to reinforced polyetheretherketone (PEEK) substrate. A total of 40 specimens were randomly distributed to two groups based on the primer used for orthodontic bonding: group 1 (control)-Transbond XT adhesive with Visio.link primer and group 2 (test)-orthodontic adhesive (Transbond XT) with traditional orthodontic primer. After bonding, specimens were thermocycled followed by SBS testing and ARI scoring of debonded specimens. Data were analyzed using the unpaired independent t-test and the Chi-square test. Group 1 specimens showed significantly higher SBS values (21.38 ± 1.48 MPa) compared to group 2 specimens (18.63 ± 1.29 MPa) (p < 0.0001). Adhesive remnant index scores showed no significant variations in bond failure modes and distributions between groups. The SBS obtained by the tested primers exceeded the clinically recommended value. Consequently, there is a comparable clinical application for both tested primers in orthodontic bonding, especially the traditional orthodontic primer, where the availability of Visio.link in clinical practice is not ensured.

The effect of ferrule and core material on fracture resistance of endodontically treated anterior teeth restored with ceramic crowns after artificial aging

ObjectivesTo assess the influence of ferrule and core type on the fracture strength of endodontically treated anterior teeth (ETAT) and identify the failure mode type and distribution across different core types and ferrule conditions. MethodsSixty extracted human central incisors were endodontically treated, decoronated and divided into two main groups (F=with ferrule, NF=no ferrule). Each main group was further subdivided into three subgroups according to the core material used: direct composite cores (DC), Ribbond fibre-reinforced composite cores (RIB-DC), and glass fibre post (GFP) with direct composite cores (GFP-DC). All specimens received E.max crowns and underwent thermal cycling and cyclic loading. Subsequently, the fracture resistance was tested with static loads applied to the crown restoration. Two-Way ANOVA and Chi square tests identified significant differences among the groups (p < 0.05). ResultsThe means and standard deviations (SD) of fracture loads in Newtons (N) for specimens in the F subgroups were RIB-DC: 465.0 (104.20), GFP-DC: 367.6 (79.59), DC: 275.8 (68.48), and in NF subgroups were RIB-DC: 110.8 (24.33), GFP-DC: 95.6 (25.47), DC: 67.4 (7.46). Specimens with ferrule yielded significantly higher fracture loads than those without ferrule (p = 0.0054). In the F groups, fracture loads of specimens with RIB-DC cores were significantly higher than those with GFP-DC (p = 0.0019) and those with DC (p = 0.0001). Moreover, fracture loads for the GFP-DC were significantly higher than those for the DC (p = 0.0026). The GFP-DC specimens showed the highest incidence of catastrophic failures (p = 0.0420). ConclusionsUsing fibre-reinforced composite (FRC) cores significantly increased fracture resistance in ETAT with ferrule. The failure modes repairable and possibly repairable were dominant in most specimens. Clinical significanceWhen restoring ETAT with insufficient coronal tooth structure, preserving 2 mm of tooth structure ferrule and preparing cores with FRC can increase fracture resistance and reduce the incidence of non-repairable catastrophic fractures of teeth.

Research on the upper limit of constant strain rates and dynamic fracture behavior for hybrid woven composite

Based on the analysis of stress wave propagation at both ends of the specimen, a formula for the upper limit of the constant strain rate is derived. The upper limit of constant strain rate is applicable to all the ratios of wave impedance, providing a broader applicability. The in-plane dynamic compressive behavior was obtained for 2D plain weave carbon/aramid hybrid composites at strain rates ranging from 195 to 790 s−1. The results validate the prediction of the upper limit of the constant strain rate. The strength exhibited sensitive to strain rate. A nonlinear constitutive model described the dynamic constitutive relationship effectively under different strain rates. The distribution of delamination failure significantly influenced the final failure shape of the specimens. Microscopic observations indicated that carbon fiber yarns and aramid fiber yarns exhibited different fracture modes.

Analyzing the effects of size and density on the ultimate compressive strength of structural laminated bamboo parallel to the grain

Considering the influence of natural flaws of raw materials and procedures, the size effect is an inherent characteristic that is critical when applying most construction materials. This study focuses primarily on the compressive properties of laminated bamboo, which has become increasingly popular in construction due to its durability and strength. Two specimen sizes (25 × 25 × 100 mm and 50 × 50 × 200 mm) and three densities (0.60, 0.67, and 0.69 g/cm3) were evaluated under uniaxial compression. As a result of this study, the size effect is examined in terms of failure mode, mechanical property, data distribution, and description model, as well as introducing the size effect model with density in an innovative manner. To investigate the effect of specimen size on compressive strength along the grain direction, data analyses were performed. These analyses included failure mechanism analysis, distribution testing, and descriptive model development. According to the results, the compressive strength decreases with increasing dimensions, averaging 62.29 MPa–56.93 MPa, with a decrease rate of 8.60 %, although the failure modes are seldom different. In accordance with the increase in density, the rate of strength reduction also increases, and shows an approximate linear relationship with density. With the change in size, the distribution of the data changes, resulting in a reduction of up to 13.34 % in the standard value. The weakness-link model is better suited for describing data than fracture energy models and fractal theory models, based on which reduction ratios are predicted. By adding density to the size effect model, a more accurate prediction model can be derived between size, density, and compressive strength. As a result of these investigations, we will gain a better understanding of the gap between small clear specimens and large members, as well as those key influences necessary to optimize the use of laminated bamboo in structural applications.

Estimation of the Time to Failure Distribution Function in a Highly Reliable N –1-Out-of-N: G Repairable System in the Case of Exponential Distributions of the Uptime Intervals of All Alternating Processes

Estimation of the Time to Failure Distribution Function in a Highly Reliable N –1-Out-of-N: G Repairable System in the Case of Exponential Distributions of the Uptime Intervals of All Alternating Processes

Assessment of computing systems reliability by non-parametric method by small samples of operational data

A new method for assessing the reliability of small computing systems that allows the generation of only small samples of operational data is proposed in the article. The result of applying the technique is the posterior failure distribution density, on the basis of which various reliability indicators can be calculated. The methodology consists of two stages: the first is the preparation of operational data, including detection of failures using machine learning methods, and the second is the construction of the failure distribution density using the adapted Rosenblatt–Parzen method. Increasing the efficiency of estimates using the proposed method is achieved by taking into account censored data, compensating for the shift of failure distribution densities and finding the optimal smoothing parameter.

Differences and Intersections in Renal Biopsy Findings in Patients with Asymptomatic Hyperuricemia and Gout

The aim of this study is to establish the association between asymptomatic hyperuricemia and gout with morphological and immunofluorescent changes in the renal biopsy. A total of 64 patients, 46 with asymptomatic hyperuricemia and 18 with gout were included in this retrospective study. Renal biopsy findings, clinical and laboratory data were analyzed by using medical documentation. We did not find a significant difference in the distribution of chronic renal failure between the two groups. In the gout group, the proportion of patients with nephrolithiasis was higher (p &lt;0.001), and the presence of erythrocyturia was more common (p = 0.047). The percentage of damaged glomeruli (p = 0.249) and the distribution of mesangial proliferation (p = 0.536) was similar in the groups. The proportion of patients with interstitial fibrosis &gt; 50$% was significantly higher in the gout group (p = 0.032), but no difference was observed in the distribution of tubular atrophy &gt; 50% (p = 0.183). In subjects not receiving urate-lowering therapy, serum uric acid levels were comparable in the different stages of tubular atrophy and interstitial fibrosis. We found that in both asymptomatic hyperuricemia and gout, there is a deposition of immune deposits subepithelially, subendothelially, in the mesangium and in the vessel walls. In gout, the kidneys are affected to a much greater extent. We consider that not only the increased serum uric acid is important, but also monosodium urate crystals deposited in the renal interstitium causing a chronic inflammatory process followed by fibrosis. We suggest that the activation of the innate immune system by soluble uric acid and crystals with the subsequent development of a proinflammatory state in the body has led to the activation of complement and deposition of immune deposits in the kidneys.

Effect of Load on Sequential Imperfect Preventive Maintenance and Replacement Schedules of Mechanically Repairable Machines

This paper examines the impact of load on the operational time and maintenance cost of mechanically repairable machines. Three different levels of load with multiplicative impact on the hazard rate of the failure distribution were applied to the working of a cassava grinding machine using a two-parameter Weibull distribution with respective hazard and cumulative hazard functions. Their effect on the preventive maintenance (PM) and replacement schedules revealed that at above maximum load level, the length of the machine’s operational time decreased drastically compared to the decrease at maximum load level and relative decrease at the below maximum load level when compared to the machine’s operational time at the minimum load level. The application of load also results in frequent preventive maintenance actions and an increase in machine downtime for a given cost ratio. This implies that the influence of load on the PM and replacement maintenance schedule of mechanically repairable machines is essential to the design and operation of such machines. The results also provide maintenance engineers with an operational guide for PM and replacement maintenance actions in order to prevent failure maintenance and increase the machine’s availability for enhanced productivity.

Intelligent optimal preventive replacement maintenance policy for non-repairable systems

This paper developed optimal maintenance policies for industrial machines to ensure uninterrupted production. Analytical and intelligent replacement models were constructed using real-time data from a commercial photocopier operator’s expenditure logbook between 2012 and 2023. A goodness-of-fit test affirmed a log-logistic failure distribution with shape and scale parameters of 1.7233 and 763.9220, respectively. Probability functions from this distribution established replacement models, determining optimal preventive maintenance conditions. Through feature engineering additional features crucial for operational and cost optimization were abstracted, with 4,881 unique data points simulated from boundary conditions defined by the original or raw data. Analytical results showed that the failure distribution-based replacement model outperformed the hazard function-based model in minimum replacement time and unit maintenance cost over time, while key parameters such as availability, reliability, and failure occurrence probability remained constant at 96 %, 94 %, and 0.07 %, respectively. Machine learning models (Extreme Gradient Boosting: XGBoost, Support Vector Machine: SVM, and Multilayer Perceptron: MLP) demonstrated very high accuracy in availability (XGBoost = 99.49 %, SVM = 99.18 %, RF = 100 %, MLP = 99.80 %), reliability (XGBoost = 99.49 %, SVM = 99.18 %, RF = 100 %, MLP = 99.80 %), and maintenance cost (XGBoost = 100 %, SVM = 100 %, RF = 100 %, MLP = 100 %), exceeding results of the analytical models.