Low Failure Probability Research Articles

Accelerated statistical failure analysis of multifidelity TRISO fuel models

Statistical nuclear fuel failure analysis is critical for the design and development of advanced reactor technologies. Although Monte Carlo Sampling (MCS) is a standard method of statistical failure analysis for fuels, the low failure probabilities of some advanced fuel forms and the correspondingly large number of required model evaluations limit its application to low-fidelity (e.g., 1-D) fuel models. In this paper, we present four other statistical methods for fuel failure analysis in Bison, considering tri-structural isotropic (TRISO)-coated particle fuel as a case study. The statistical methods considered are Latin hypercube sampling (LHS), adaptive importance sampling (AIS), subset simulation (SS), and the Weibull theory. Using these methods, we analyzed both 1-D and 2-D representations of TRISO models to compute failure probabilities and the distributions of fuel properties that result in failures. The results of these methods compare well across all TRISO models considered. Overall, SS and the Weibull theory were deemed the most efficient, and can be applied to both 1-D and 2-D TRISO models to compute failure probabilities. Moreover, since SS also characterizes the distribution of parameters that cause TRISO failures, and can consider failure modes not described by the Weibull criterion, it may be preferred over the other methods. Finally, a discussion on the efficacy of different statistical methods of assessing nuclear fuel safety is provided.

Distributed collaboration and anti-interference optimization in edge computing for IoT

The edge computing (EC) systems for Internet of Things (IoT) can bring out low latency, high reliability, distributed intelligence, and network bandwidth savings to industrial real-time applications. However, limited computing and processing capabilities of edge devices remains to be difficult to meet complex data processing and artificial intelligence (AI) analysis requirements for diverse services. Besides, the scarcity of wireless spectrum resources in harsh industrial environment makes the interference between devices more serious. To address these challenges, this paper proposes an adaptive distributed collaborative anti-interference optimization scheme for IoT-edge system. Firstly, the EC system model is established, and the model of link failure probability is derived theoretically. Then, an Occupy-Interference Mitigation (O-IM) algorithm based on full-frequency multiplexing is proposed. The algorithm combines adaptive full-frequency multiplexing and interference mitigation to reduce the dependence of the reliable collaboration on bandwidth and signal-to-noise ratio (SNR). In addition, an anti-interference algorithm based on Interference Mitigation and inter-cellfrequency multiplexing Interference Avoidance (IM-IA) is proposed to balance bandwidth and SNR. This algorithm adopts interference cancellation scheme in the broadcasting phase, and adopts orthogonal frequency division in the collaboration phase. Extensive simulation results on Mininet platform verify that the proposals can obtain lower failure probability, and are less than traditional solutions in transmitting power, bandwidth, and SNR requirements. Moreover, the O-IM is suitable for low power scenarios, while the IM-IA is more suitable for high power case.

Difference between Pavement Thickness Design and Pavement Life Prediction for Rigid Aircraft Pavements

Aircraft pavements are generally designed using deterministic methods and using conservatively selected input parameter values, which combine to result in a low probability of structural failure occurring during the structural design life of the pavement. In contrast, when predicting the actual time until an as-constructed pavement will reach a structural failure condition, stochastic methods are required to take into account the inherently variable nature of pavement material properties and layer thicknesses, and the best-estimate of the input parameter values must replace the conservative values that are commonly used to introduce design reliability. A case study on a rigid aircraft pavement demonstrates the difference between pavement thickness design and pavement life prediction. Using Monte Carlo simulation, it was found that 98.5% of the as-constructed pavement was stronger than the designed pavement and that the predicted fatigue life of the pavement was approximately 180 times greater than the effective design life. It was concluded that the significant difference between pavement design and pavement life prediction explains the practical observation that rigid aircraft pavement service life generally exceeds typical structural design lives.

A New Stopping Sight Distance Model and Fuzzy Reliability Analysis Comparison

Aiming at the research on the stopping sight distance of the highway, on the basis of calculating the stopping sight distance in the current specification, the actual braking process of the car is divided into three stages: the driver’s reaction stage, the braking force rising stage and the continuous braking stage. The calculation model of the complete braking stage is analyzed by MATLAB, and then the calculation model of the stopping sight distance of the ESC system is proposed. Considering the ambiguity of the operating speed, the fuzzy reliability theory is introduced to establish the function of the fuzzy reliability of the stopping sight distance. Using the Gaussian fuzzy number and the center point method, the reliability index and failure probability of the stopping sight distance are obtained, and the safety of the stopping sight distance is evaluated. According to the "Uniform Standard for Reliability Design of Highway Engineering Structures", the traditional reliability calculation method and the fuzzy reliability calculation method are used to calculate the stopping sight distance value that meets the corresponding reliability index of the highway safety level. The calculated value of the system stopping sight distance model is used as a reference, and the reliability index and failure probability of the two reliability calculation methods are calculated. The calculation results show that: compared with the traditional reliability calculation method, the fuzzy reliability calculation method calculates the stopping sight distance value with higher reliability index, lower failure probability and higher calculation accuracy. Implementing the road design based on the stopping sight distance value calculated by the fuzzy reliability theory can improve the road safety.

Comparison of Shear Bond Strength of a Newly Introduced Primer with Conventional Primer Using Two Types of Brackets Bonded to Different Surfaces: An In Vitro Study

Background Increasing prevalence of adult orthodontics necessitates improvement in bonding techniques to different intraoral surfaces enamel composite amalgam porcelain. Research focusing on newer materials minimizing bond failures is important as replacing loose brackets is inefficient time-consuming and costly.Objective To compare the shear bond strength SBS and adhesive remnants achieved with the new Assure Plus AP primer versus conventional Transbond XT TXT primer for bonding metalceramic brackets to three different surfaces tooth enamel composite and porcelain-fused-to-metal PFM ceramic.Methods This in vitro study included 40 samples each of extracted teeth Group-1 composite restorations Group-2 and PFM crowns Group-3 mounted on acrylic blocks onto which metal Category-M or ceramic Category-C brackets were bonded using TXT Subgroup-A or AP primer Subgroup-B 10 samples in each class. Their SBS and Adhesive Remnant Index ARI were compared between and within the groups using ANOVA Tukeyrsquos post hoc analysis and Weibull analysis. The level of significance was set at p lt0.05.Results The two primers showed no significant differences in mean SBS within Groups-1 and 2 and in mean ARI within any group p gt0.05. Group-3 showed higher mean SBS with AP primer than with TXT primer BCgtBMgtACgtAM p lt0.001. Failure probability was also lower with AP than with TXT primer.Conclusion AP primer showed significantly greater SBS than TXT primer when used for bonding brackets to PFM crowns. AP primer also showed lower failure probability than TXT primer on all three surfaces tooth enamel composite PFM ceramic.

Using the Kriging Response Surface Method for the Estimation of Failure Values of Carbon-Fibre-Epoxy Subsea Composite Flowlines under the Influence of Stochastic Processes

This paper investigates the use of the Kriging response surface method to estimate failure values in carbon-fibre-epoxy composite flow-lines under the influence of stochastic processes. A case study of a 125 mm flow-line was investigated. The maximum stress, Tsai-Wu and Hashin failure criteria was used to assess the burst design under combined loading with axial forces, torsion and bending moments. An extensive set of measured values was generated using Monte Carlo simulation and used as the base case population to which the results from the response surfaces was compared. The response surfaces were evaluated in detail in their ability to reproduce the statistical moments, probability and cumulative distributions and failure values at low probabilities of failure. In addition, the optimisation of the response surface calculation was investigated in terms of reducing the number of input parameters and size of the response surface. Finally, a decision chart that can be used to build a response surface to calculate failures in a carbon fibre-epoxy-composite (CFEC) flow-line was proposed based on the findings obtained. The results show that the response surface method is suitable and can calculate failure values close to that calculated using a large set of measured values. The results from this paper provide an analytical framework for identifying the principal design parameters, response surface generation, and failure prediction for CFEC flow-lines.

Probabilistic analysis of geosynthetic-reinforced and pile-supported embankments

This paper presents a probabilistic analysis of a geosynthetics-reinforced and pile-supported (GRPS) embankment by using reliability, sensitivity and uncertainty propagation techniques. Compared to the traditional deterministic evaluation methods, the analyses performed in this work allow designers to rationally consider the uncertainties of material properties and quantify their influences on the embankment performance. Additionally, complementary information/results could be obtained which enables an informed design decision for engineers. This feature is further enhanced in the paper by proposing a new analysis procedure in which four carefully selected probabilistic techniques are combined with an efficient deterministic model. The contribution of the proposed procedure lies in providing a variety of valuable results (e.g., failure probability and sensitivity index) related to the GRPS embankment performance but with a limited computational time. An application of the procedure is presented in the paper. The obtained results revealed that the studied GRPS embankments have relatively low failure probabilities considering a usual traffic loading but could be risky under extreme loading conditions. Based on the sensitivity analysis, all the random parameters are ranked according to their quantified importance. Some discussions are also provided, trying to link the procedure with practical designs and to explain the uncertainty modeling with more details.

Prediction of cyclic durability and risk analysis of inconsistencies in the supporting structures of mobile vehicles

The reliability and safety of mobile vehicles is determined by their carrier system. Achieving a low probability of failure of structures and reducing the cost of equipment is possible by changing the traditional methods of predicting reliability and applying risk analysis, as well as using risk-based design. The aim of the work is to develop methods for predicting the cyclic durability of elements, fastening prefabricated load-bearing structures and analysis to achieve acceptable risks of mobile vehicles at the stages of risk-oriented design. The methods and standards were developed in order to provide methodological support of risk-based design. Those allow designers and engineers to use new methods of design and calculation of tractor and agricultural machinery. It is proposed to introduce into the existing notation system of design and technological documentation the identifiers for parameters as the priority indicators and to achieve when designing the probability of occurrence of each potential cause of failure up to a given level of risk, taking into account priority. The tool for achieving low failure probabilities is the construction of diagrams of cause-and-effect relationships of failures is the source of cause and effect based on the method of deduction and induction. A calculation and experimental method for predicting reliability, according to the criterion of cyclic durability of load-bearing structures and fasteners was developed. The technique is based on local modeling of damage initiation zones, taking into account the influence of design and technological factors of production, simulating the load mode of a mobile vehicle, its damage zones. The following are used for the calculation: finite element method, experimental load assessment, fatigue resistance characteristics of load-bearing elements, rivets and bolts, damage accumulation hypotheses. Risk analysis is carried out using the FMEA methodology. As a result of the risk analysis in a probabilistic formulation, a conclusion is made about the possible damage to the supplier the number of mobile vehicles that will not ensure the fulfillment of the stated requirements for a given resource and warranty mileage. Thus, data for assessing risks and making a decision on the advisability of redesigning equipment appear. The created methodological support for predicting cyclic durability and risk analysis for the implementation of risk-based design allows: to eliminate the uncompetitive level of product quality and production quality, as well as low efficiency and labor productivity; apply new design technologies, design and production preparation methods that reduce development time. The developed methods and means of the risk-based approach have been widely tested and are used in the practice of auto-tractor-agricultural machine building.

Approximation Algorithm for Vertex Cover with Multiple Covering Constraints

We consider the vertex cover problem with multiple coverage constraints in hypergraphs. In this problem, we are given a hypergraph \(G=(V,E)\) with a maximum edge size f, a cost function \(w: V\rightarrow {\mathbb {Z}}^+\), and edge subsets \(P_1,P_2,\ldots ,P_r\) of E along with covering requirements \(k_1,k_2,\ldots ,k_r\) for each subset. The objective is to find a minimum cost subset S of V such that, for each edge subset \(P_i\), at least \(k_i\) edges of it are covered by S. This problem is a basic yet general form of classical vertex cover problem and the edge-partitioned vertex cover problem considered by Bera et al. We present a primal-dual algorithm yielding an \(\left( f \cdot H_r + H_r\right) \)-approximation for this problem, where \(H_r\) is the \(r^{th}\) harmonic number. This improves over the previous ratio of \((3cf\log r)\), where c is a large constant used to ensure a low failure probability for Monte-Carlo randomized algorithms. Compared to the previous result, our algorithm is deterministic and pure combinatorial, meaning that no Ellipsoid solver is required for this basic problem. Our result can be seen as a novel reinterpretation of a few classical tight results using the language of LP primal-duality.

Seismic fragility analysis of nuclear shield building based on zoned structure

This paper focuses on the seismic fragility analysis of nuclear shield building. Combined with the characteristics of structural catastrophic damage, it is divided into 9 zones (RS-1, RS-2, RC-1 ∼ RC-7) along the height direction. An incremental dynamic analysis of 200 working conditions (PGA 0.3 g-2.1 g with an interval of 0.2 g) is carried out on the dynamic catastrophic behavior of the nuclear shield building. The seismic fragility analysis of nuclear shield building based on zoned and overall structure idea is compared and studied. The results show that the damage and failure of both the overall structure and the zoned structure are deepened as the PGA increases. In the light damage state and extended damage state (especially the latter), the overall structure has a lower failure probability of the tension and compression damage than the zoned structure (such as RC-1 ∼ RC-4 and RC-7). Based on the zoned structure, the seismic fragility analysis demonstrates that the nuclear shield building with shear failure characteristics has different damage state for each zone, which can effectively show the failure mode and provide a more accurate assessment basis for the damage state and the failure mode of such structures.

An efficient hybrid reliability analysis method based on active learning Kriging model and multimodal‐optimization‐based importance sampling

AbstractA novel method is proposed, which aims to solve rare‐event hybrid reliability problems with random and interval variables, where the performance function has various failure zones. It combines the active learning Kriging (ALK) model with importance sampling (IS) and evolutionary multimodal‐based multiobjective optimization (EMO‐MMO). The surrogate limit state surfaces (LSS) for the upper and lower failure probability bounds are respectively defined considering the Kriging variance. Failure candidate solutions located in different failure regions are generated by the EMO‐MMO method. Subsequently, all the most probable failure points (MPPs) are identified from those candidate solutions. The IS samples are simulated around the MPPs using the MPP‐based IS method. The IS samples located in unimportant regions are removed in order to improve the efficiency of approximating the surrogate LSSs. The optimal training points are selected from the truncated IS samples to update the Kriging model. After several training iterations, the surrogate LSSs are convergent. Ultimately, a reliable and unbiased estimation of the upper and lower failure probability bounds is provided. The performance of the ALK‐EMO‐IS‐HRA approach is verified through five application examples.

Seismic reliability evaluation of bridges under spatially varying ground motions using a four-parameter distribution

Large-span bridges are often subjected to spatially varying ground motion (SVGM) excitations. Meanwhile, bridge structures and ground motion excitations generally present a large degree of inherent uncertainties. Carrying out the seismic reliability analysis of bridges under SVGMs can provide a direct assessment for the safety probability of bridges during an earthquake event and is of paramount importance for the probabilistic performance analysis of bridges. To this end, this study proposes a new method for the seismic reliability evaluation of random nonlinear bridges subjected to SVGMs, which tackles the drawback of the current seismic reliability analysis method that can only be applied for uniform seismic excitations. To implement, the space correlated ground motions are first generated via a random function-based spectral representation method, based on which the uncertainty of ground motions is characterized by three elementary random variables. The first-passage probability of bridges under SVSGMs is then derived by the equivalent extreme value distribution (EVD), which is approximated by a flexible four-parameter distribution, i.e., shifted generalized lognormal distribution (SGLD). To estimate the parameters in the SGLD model with high efficiency and accuracy, a novel fractional moment-based method is proposed. A numerical example of a two-span continuous box-girder bridge subjected to space varying site conditions is investigated to verify and exemplify the proposed method. The results demonstrate that: 1) The proposed method is efficient and accurate for the seismic reliability of bridge under SVGM, even at low failure probability levels, and the computational burden of the proposed method is less than 2% of that of MCS; 2) The spatial variability is significantly influential on the seismic reliability of the bridge, ignoring the spatial variability of seismic excitation will significantly underestimate the failure probability of the bridge.

Predicting French SME failures: new evidence from machine learning techniques

ABSTRACT The aim of this study is to provide new insights into French small and medium-sized enterprises (SME) failure prediction using a unique database of French SMEs over the 2012–2018 period including both financial and nonfinancial variables. We also include text variables related to the type of activity. We compare the predictive performance of three estimation methods: a dynamic Probit model, logistic Lasso regression, and XGBoost algorithm. The results show that the XGBoost algorithm has the highest performance in predicting business failure from a broad dataset. We use SHAP values to interpret the results and identify the main factors of failure. Our analysis shows that both financial and nonfinancial variables are failure factors. Our results confirm the role of financial variables in predicting business failure, while self-employment is the factor that most strongly increases the probability of failure. The size of the SME is also a business failure factor. Our results show that a number of nonfinancial variables, such as localization and economic conditions, are drivers of SME failure. The results also show that certain activities are associated with a prediction of lower failure probability while some activities are associated with a prediction of higher failure.

Seismic performance assessment of NPP concrete containments considering recent ground motions in South Korea

Seismic fragility analysis, a part of seismic probabilistic risk assessment (SPRA), is commonly used to establish the relationship between a representative property of earthquakes and the failure probability of a structure, component, or system. Current guidelines on the SPRA of nuclear power plants (NPPs) used worldwide mainly reflect the earthquake characteristics of the western United States. However, different earthquake characteristics may have a significant impact on the seismic fragility of a structure. Given the concern, this study aimed to investigate the effects of earthquake characteristics on the seismic fragility of concrete containments housing the OPR-1000 reactor. Earthquake time histories were created from 30 ground motions (including those of the 2016 Gyeongju earthquake) by spectral matching to the site-specific response spectrum of Hanbit nuclear power plants in South Korea. Fragility curves of the containment structure were determined under the linear response history analysis using a lumped-mass stick model and 30 ground motions, and were compared in terms of earthquake characteristics. The results showed that the median capacity and high confidence of low probability of failure (HCLPF) tended to highly depend on the sustained maximum acceleration (SMA), and increase when using the time histories which have lower SMA compared with the others.

The role of the geological uncertainty in a geotechnical design – A retrospective view of Freeway No. 3 Landslide in Northern Taiwan

The importance of the geological model in a geotechnical engineering project has long been recognized. However, the uncertainty associated with the geological model has rarely been quantified and explicitly considered in the geotechnical design. This paper explores the role of the geological model uncertainty and the benefit of reducing such uncertainty in a geotechnical design. To this end, the landslide that occurred on 25 April 2010 at 3.3 K of Freeway No. 3 in Northern Taiwan, referred to herein as NH-3 Slope, is re-analyzed with an assumed geological model (a dip-slope model in this case) under various uncertainty scenarios. Traditionally, the design (i.e., a choice of design parameters such as slope height, slope angle, and supporting anchors) of a rock slope seeks to satisfy a target factor of safety (FS). In the case of NH-3 Slope, the apparent dip angle of the slip surface along the dip direction of slope constitutes the geological model of concern. Different survey techniques produce data with varying degrees of error (or uncertainty) in the measured apparent dip angle. For example, data from a Regional Geological Map (RGM) typically yields an estimate of the bedding plane attitude with a significant level of uncertainty due primarily to low data density. In contrast, LiDAR can significantly reduce the uncertainty of the derived bedding plane attitudes. By lowering this uncertainty, the variation (or uncertainty) in the computed FS may be reduced, which tends to yield a lower failure probability (Pf), given other conditions being the same. The benefit of lowering the geological model uncertainty in a geotechnical design is demonstrated through a retrospective analysis of the NH-3 Slope.

Study on Inelastic Strain-Based Seismic Fragility Analysis for Nuclear Metal Components

The main purpose of this study is to investigate the feasibility of the seismic fragility analysis (FA) with the strain-based failure modes for the nuclear metal components retaining pressure boundary. Through this study, it is expected that we can find analytical ways to enhance the high confidence of low probability of failure (HCLPF) capacity potentially contained in the conservative seismic design criteria required for the nuclear metal components. Another goal is to investigate the feasibility of the seismic FA to be used as an alternative seismic design rule for beyond-design-basis earthquakes. To do this, the general procedures of the seismic FA using the inelastic seismic analysis for the nuclear metal components are investigated. Their procedures are described in detail by the exampled calculations for the surge line nozzles connecting hot leg piping and the pressurizer, known as one of the seismic fragile components in NSSS (Nuclear Steam Supply System). To define the seismic failure modes for the seismic FA, the seismic strain-based design criteria, with two seismic acceptance criteria against the ductile fracture failure mode and fatigue-induced failure mode, are used in order to reduce the conservatism contained in the conventional stress-based seismic design criteria. In the exampled calculation of the inelastic seismic strain response beyond an elastic regime, precise inelastic seismic analyses with Chaboche’s kinematic and Voce isotropic hardening material models are used. From the results of the seismic FA by the probabilistic approach for the exampled target component, it is confirmed that the approach of the strain-based seismic FA can extract the maximum seismic capacity of the nuclear metal components with more accurate inelastic seismic analysis minimizing the number of variables for the components.

Who Could We Blame? The Impact of Strategic Orientations on the Failure of Financial Institutions

We evaluate the impact of strategic orientation on the failure probability of financial institutions. Using the US credit union industry as the empirical setting, we find that credit unions which exhibit preferential treatment to borrowers are more likely to fail, whereas those who set operational strategies towards balancing the benefits between savers and borrowers experience a lower failure probability. The impacts appear to be more pronounced in small credit unions and in credit unions which have a lower operating experience. We also find that borrower-oriented credit unions generate lower interest margins while neutral behavior credit unions generate higher margins.

Efficient reliability analysis combining kriging and subset simulation with two-stage convergence criterion

Reliability assessment of real-world structures is a significant challenge owing to its complex input variables, extremely low failure probability, and significant computational costs. In recent times, a series of surrogate models with variance reduction techniques have been proposed to address these limitations. However, achieving a balance between estimation accuracy and computational cost still remains challenging. To this end, this study proposes a novel two-stage convergence criterion that merges into the exterior subset simulation (SS) framework and the interior Kriging model to improve the efficiency of the active learning process. Based on the error analysis of the Kriging model, two groups of parameters are established to describe the estimation accuracy, eventually forming a two-stage convergence criterion. The first stage aims to control the hierarchical modeling error for each intermediate conditional failure event, and the second stage is devoted to ensuring the global accuracy of estimation of the final failure probability. To validate the proposed method, four case studies were performed, including three numerical examples with explicit limit state functions and a real-world model of a cracked steel deck with finite element analysis. The results indicate that the proposed method can both ensure accuracy and improve the efficiency of the reliability analysis.

A functional model-based approach for ship systems safety and reliability analysis: Application to a cruise ship lubricating oil system

The lubricating oil systems are essential for ensuring the safe and reliable operation of the cruise ships power plants as demonstrated by recent incidents. The aim of this study is to investigate the safety enhancement of a cruise ship lubricating oil system by employing safety, reliability, availability and diagnosability analyses, which are based on the system functional modelling implemented in the MADe™ software. The safety analysis is implemented by combining a Failure Modes, Effects and Criticality Analysis and the systems functional Fault Tree Analysis. Subsequently, Reliability Block Diagrams are employed to estimate the system reliability and availability metrics. The MADe™ toolbox for determining sensors locations is employed for a more advanced diagnostic system development. A number of design modifications are proposed and the alternative configurations reliability metrics are estimated. The derived results demonstrate that the suction strainer and the lubricating oil pump are the most critical system components. Seven additional sensors are proposed to enhance the original system design. Compared with the original system design, the investigated alternative designs exhibit significantly lower probabilities of failure and higher values of availability.

Determination of risk level, remaining life prediction, and risk based inspection planning based on API 581

Electricity can be produced through several types of plants, one of which is Geothermal Power Plant (PLTP). One company that manages Geothermal Power Plants in Indonesia is PT Indonesia Power. In processing geothermal into electricity, companies need machines that work well in any condition, one of which is a separator machine that functions as a separator of geothermal steam with impurities. To keep the separator machine working properly, proper inspection is needed. Inspections can be done by a variety of methods, but inspections of separators should use a risk-based inspection method. Therefore, the study was conducted by applying a risk based inspection method based on API 581 Second Edition to determine the level of risk, the remaining life of the machine, and the planning of inspections (intervals and inspection techniques) on the machine. The level of risk for all separator units is medium high with a risk category of 1E, which has a low probability of failure and high failure consequences. The estimated age of the remaining machines working according to their functions based on research for unit I is 25 years, for unit II 13 years, and for unit III 18 years. This affects the inspection intervals in each unit, unit I should be inspected every 6 years, unit II is inspected every 3 years, and unit III is inspected every 4 years with a thorough inspection and thickness measurement as an inspection technique.