Multi-failure Modes Research Articles

Buckling analysis of offshore buried pipeline under the combination of strike-slip faulting and pressure loading

Long-distance offshore pipelines often inevitably pass through seismic faults that may threaten pipeline safety. A buckling analysis was conducted on offshore buried pipelines crossing active strike-slip faults using nonlinear VFIFE shell elements and modified soil springs. With respect to practical pipeline performance criteria, deformation responses under three scenarios are examined, including the seismic response with different initial pressure conditions, post-earthquake recondition for pressurized pipelines, and post-earthquake resumption for unpressurized pipelines. The results have showed multi-failure modes, including over bending with excessive tensile strain, over bending with obvious depression deformation on the compressive side of the bends, and sequential local collapses accompanied by buckling propagation along the pipeline. For pressurized pipelines, the post-earthquake recondition has a compression effect and leads to greater sectional distortions, even local collapse accompanied by buckling propagation. For pipelines with the maximum flattening parameter smaller than 15.00% at zero-pressure, critical points of the first local collapse have a linear distribution. For unpressurized pipelines, the post-earthquake resumption improves the sectional deformation but intensifies the axial tensile strain. An unpressurized pipeline with a local collapse gains a V-shape dent during the final pressurization. The results are useful for developing performance-based seismic design methodologies for offshore pipelines.

Diagnostics and prognostics of multi-mode failure scenarios in miter gates using multiple data sources and a dynamic Bayesian network

Diagnostics and prognostics of multi-mode failure scenarios in miter gates using multiple data sources and a dynamic Bayesian network

Failure correlation evaluation for complex structural systems with cascaded synchronous regression

Failure correlation evaluation of complex structural systems is a complex analysis problem involving multiple disciplinary analyses and multiple response objectives, whose high-nonlinearity performance function makes the traditional methods are difficult to acquire acceptable computing accuracy and efficiency. In this case, a cascaded synchronous regression (CSR) method is proposed by combining the multi-level decomposition cooperation strategy and the random regression tree modeling algorithm. In CSR modeling, the multi-level and multi-stage complex structural system is first decomposed into several correlated single-level and single-stage distributed subsystems; moreover, based on the random regression tree algorithm, the corresponding nonlinear mapping model for each distributed subsystem are established; finally, by performing the CSR-based system reliability simulation and Copula functions, the failure correlation relationships can be quantified. The effectiveness of proposed method is validated by the multi-site and multi-mode failure correlation evaluation of aeroengine turbine disc. The current efforts open up an effective way to realize the high-accuracy failure correlation evaluation of complex structural systems, and shed a light on the structural reliability design theory.

Dynamic Process in Threshold Weighted Indecisive-Voting Systems

To model threshold weighted voting systems with multifailure modes, we analyze system performance in terms of system reliability by focusing on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">indecisive effect</i> . The measurement of system reliability is generated by the decision rule where we apply dynamic process on two major aspects including the indecisive parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\theta $ </tex-math></inline-formula> and voters’ errors resulting from various situations such as weights replacement and inputs discrepancy. The motivation is to make the existing model more applicable via the dynamic process. In this article, two major contributions are addressed as follows. First, the continuous distributed indecisive parameter gives an intuitive idea of how the model adapts from the decision rule, which provides the flexibility of adjustment to satisfy different applications. Second, the time delay degradation process on voters’ errors illuminates the opposite system performance for two types of inputs by considering different indecisive effects, which leads to further investigation of model sensitivity of input types.

Reliability analysis of composite sandwich structure for fuselage skin based on surrogate model

Composite structures are characterized by multiple source uncertainties in mechanical properties, geometric dimension, etc., and multiple failure modes, which bring challenges to their design and application. In order to explore the reliability analysis method of composite sandwich structures with multi-source uncertainties and multi-failure modes, a parametric finite element model and an acoustic boundary element model were established for deterministic analysis of a fuselage skin sandwich structure. Considering the randomness of the mechanical properties of composite materials and the laminate thickness, the structural reliability models were established for three typical failure modes of sandwich structures: static strength failure, global buckling and vibration noise. In order to reduce the computational effort, the Kriging surrogate models of failure modes were constructed, and the subset simulation method was used to predict the system failure probability of the sandwich structure of fuselage skin. The proposed computational framework provides support and tool for the fine design of composite sandwich structure.

Spare Parts Stocking Decision Strategy and Service Logistics Cost Optimization of Two-Echelon Service Logistics System considering Multifailure Mode.

For the repair level and spare parts stocking decision problems, generally METRIC type methods and level of repair analysis (LORA) are used separately. In practical engineering, the repair level of large-scale systems is usually judged according to the failure modes. The method of judging the repair level by the maintenance success rate is no longer applicable. In the case of multiple failure modes of a large-scale system, considering the requirements of system availability, we build a spare parts stocking decision and service logistics cost optimization model of a two-echelon service logistics system. Aiming at the spare parts stocking allocation problem caused by multiple failure modes, we improve the iterative greedy heuristic algorithm to find the global optimal stocking allocation strategies. Finally, through the analysis of typical examples, the correctness and effectiveness of the model and algorithm are verified. The impact of multifailure mode spare parts stocking allocation strategies on availability and service logistics cost is analyzed. The research results are helpful to simplify the support engineering design process of system engineers and have certain theoretical and application value.

Improved Kriging-based hierarchical collaborative approach for multi-failure dependent reliability assessment

Reliability assessment considering multi-failure dependency brings in highly complex computing tasks, which is impracticable for some complex structures like turbine cooling blades. To efficiently investigate the failure dependency between multiple frail sites and multiple failure modes, an improved Kriging (IK) model is first established by optimizing model parameters with dynamic hybrid ant colony optimal algorithm, and the IK-based hierarchical collaborative (IK-HC) method is further developed by absorbing the advantages of IK model into HC strategy. Based on the multidimensional Copula function with dependency capture power and the IK-HC method with high-fidelity computing power, the multi-failure dependent reliability framework is first built. The computing efficiency and accuracy of the proposed IK-HC method are pre-verified by several numerical cases, and the method is applied to the multi-site (i.e., blade root, front edge) multi-mode (i.e., low-cycle fatigue, creep fatigue) failure dependent reliability assessment of a high-pressure turbine cooling blades. Method comparisons reveal that the proposed method can perform the multi-failure dependent reliability assessment with high accuracy and efficiency.

The effect of thickness on the compression failure of composite laminates in fire

This paper presents an experimental and modelling study that determined the influence of thickness on the softening-rate, composite damage initiation and propagation, and structural survivability of composite structures in fire. Fire-under-compression load tests were conducted using glass fibre reinforced vinyl-ester laminates of varying thicknesses to quantify the influence of thickness on fire structural survivability. The matrix softening and degradation rates decreased as the composite thickness increased. The laminate thickness variations had a strong influence on the fire-under-compression load performance and failure mode. The analysis reveals complex multi-mode failure mechanisms involving global buckling and transitioning into shear dominated failure as the composite thickness increased. A thermal–mechanical model that can predict the time-to-failure of glass fibre reinforced composite subjected to a combined compression and fire load was developed and its validity was assessed by comparing the theoretical predictions to the experimental data.

Multi-failure mode correlation and dynamic reliability evaluation of helical gears of ring die pellet mill

Multi-failure mode correlation and dynamic reliability evaluation of helical gears of ring die pellet mill

Application of multi-failure mode reliability-based particle swarm optimization algorithm

Optimization and reliability is utilized in many fields such as architectural, mechanical and aerospace engineering. The particle swarm optimization (PSO) and multi-failure mode (MFM) reliability is combined and used in aeronautical engineering in this paper. This methodology is named MFM-based improved particle swarm reliability optimization (MFM-IPSRO). The obvious characteristic of this methodology is that it only requires the objective and constraint function information to find the optimal solution using the IPSRO without requiring the gradient information of function. To prove the effectiveness of the proposed method, experimental studies are conducted with three case studies, including two numerical examples and an engineering case study (aeroengine spindle). The results manifest that MFM-IPSRO is superior to the first-order second-moment in the accuracy and superior to the Monte Carlo in the efficiency, and the proposed approach has good search capability, high efficiency and accuracy in solving the reliability engineering.

Life-cycle seismic performance assessment of aging RC bridges considering multi-failure modes of bridge columns

Corrosion of steel reinforcements is a major factor causing seismic performance deterioration of reinforced concrete (RC) bridges. More critically, corrosion could induce failure mode shift of the bridge columns as evidenced by some recent experimental studies. This phenomenon has not been well considered in existing studies regarding seismic performance assessment of aging RC bridges. This paper presents seismic fragility analysis of aging RC bridges in a life-cycle context considering failure mode shift of the bridge columns. A numerical model that can capture shear capacity deterioration and flexure-shear coupling behaviors of the corroded columns are developed and validated with experimental tests results. A two-span RC bridge is selected to conduct seismic fragility analysis at variant corrosion time. Time-variant structural capacity of the bridge columns are investigated with the developed numerical model. Seismic fragility curves of the bridge component as well as the bridge system are developed via dynamic analysis using near fault ground motions. Results indicate that the bridge columns will experience failure mode shift due to corrosion effects. The columns will fail in flexure-shear mode at severer corrosion levels although they were initially ductile-designed. Seismic fragility of the bridge significantly increases in case of flexure-shear failure of the columns. The results highlight the importance of considering the potential shear failure of the bridge columns in life-cycle seismic performance assessment of aging RC bridges.

Dynamic reliability analysis of mechanical system with wear and vibration failure modes

The wear and vibration of machine tool system are coupled and time-variant, which have significant influences on the dynamic performance of machine tool feed drive system in different time scales. In this study, the coupling effects between the wear of linear guide and the vibration of machine worktable system are studied based on the infinitesimal method. A nonlinear dynamic model is developed to analyze the wear and vibration failure mechanisms considering the uncertainty of parameters. To evaluate the dynamic reliability of the machine worktable system under multi-failure modes, a time-variant and conditional reliability approach based on the active learning Kriging model and Monte Carlo Simulation is proposed. The approach gets rid of repeated calculating of the real limit state function values and the calculation efficiency is enhanced greatly. Additionally, reliability-based sensitivity indices are presented to investigate the significance of random parameters to the reliability of the system. Besides of the reliability analysis for machine worktable systems, the proposed framework and corresponding method are also suitable for the reliability evaluation of other complex mechanical systems with the conditional multi-failure modes.

Optimal production and maintenance scheduling for a degrading multi-failure modes single-machine production environment

Two important aspects of manufacturing systems are production scheduling and maintenance planning. These aspects are interdependent, but in most research work, this dependency is ignored. This paper proposed an integrated mathematical model for joint production scheduling and maintenance planning for a degrading multi-failure single-machine manufacturing system, in which the machine has discrete deterioration states. The machine is subject to different failure modes. The first failure mode is the machine’s full deterioration, which is detected at the end of a job’s processing, and the other failure mode is random breakdowns, which are detected at the time of failure. Two machine deterioration state-based thresholds are considered, and five different maintenance actions may carry out a replacement, preventive, and corrective perfect or imperfect maintenance. Since the machine’s states’ transitions follow an exponential distribution, a closed-form matrix-based mathematical model with probabilistic input parameters is presented. This paper aims to optimize the total system’s cost, including the maintenance cost, machine energy consumption cost as well as the makespan penalty for exceeding a pre-determined threshold. The proposed model determines the optimal jobs’ sequence as well as the machine’s deterioration state-based thresholds. Due to the complexity of the developed model, a genetic algorithm (GA), simulated annealing (SA) algorithm, and a teaching–learning-based optimization (TLBO) algorithm have been used to solve the presented model. The algorithms are validated using a full enumeration technique, and the model is validated by applying different maintenance strategies. Our results demonstrate the superiority of the GA compared to the other algorithms.

Reliability-based design optimization approach for compressor disc with multiple correlated failure modes

In this work, a reliability optimization method is proposed to resolve the multi-objective reliability-based design optimization (MORBDO) of the compressor disc with multiple correlated failure modes. The cost function-based reliability allocation model is firstly established to allocate the structural reliability into reliability under failure mode by minimizing the cost. During this process, the correlations among multi-failure modes are described by using the pair-copula function. Then, an improved MOPSO algorithm based on the niche sorting strategy and the dynamic inertia weight, is employed to solve the MORBDO problem while guaranteeing efficiency and accuracy. The proposed approach is verified by the MORBDO of the compressor disc considering low cycle fatigue (LCF), creep-fatigue (CF), and combined high and low cycle fatigue (H-LCF) failure modes. Strong non-linear positive correlations among the lifetimes of three failure modes are revealed. It is proved that ignoring the correlations among failure modes by assuming independent failure modes will result in an overly conservative reliability prediction, thus leading to redundancy of structural performance in MORBDO. Furthermore, the results proved that the improved MOPSO algorithm does not only provide a better Pareto front curve but also improves computational efficiency.

An efficient global reliability analysis method for turbine disc’s multi-failure modes considering importance distribution technology

This paper presents an improved efficient global reliability analysis (EGRA) method for a turbine disc considering the importance distribution of multi-failure modes, such as low cycle fatigue (LCF) and creep-fatigue (CF). Failure mode effects and criticality analysis (FMECA) technology is firstly used to analyse the criticality and occurrence probability of each failure mode. Importance factor S is then proposed to quantify the importance of the corresponding failure mode. In order to improve the reliability analysis’s efficiency, expected feasibility function (EFF) criterion in sequential sampling method is selected through numerical experiments to generate the samples of random variables. Secondly, EGRA method is established by combining sampling method with Kriging model, in which the performance function is fitted using the key sampling points near both the failure boundaries and high uncertainty region. On the basis of EFF criterion, the composite EFF criterion applied to EGRA method is developed. This method avoids repeated analysis on non-significant failure modes, which further improves the reliability analysis’s efficiency for the multi-failure modes system. Through a binary nonlinear example, it is proved that the prediction accuracy is 99.8% compared with Monte Carlo method. Moreover, the computational time of reliability is reduced by half compared with EFF criterion, which proves the prediction efficiency of composite EFF criterion. Finally, the reliability analysis on a turbine disc is conducted using the improved EGRA method combining with the failure mode importance distribution technology. Results show that the fatigue life at 99.9% reliability is decreased by 7.4% after considering the importance of failure modes, indicating that the ignoration of failure modes’ importance would lead to a more dangerous prediction result.

Truncated Sequential Sampling Plans of Electrical Products Having Two Failure Modes

It is of great significance to design an economic sampling plan for the electrical products in mega engineering projects. The existing traditional plan normally considers single failure mode of the item being inspected. However, the major products in mega engineering projects usually have different failure modes. To overcome the drawbacks of traditional plans, a truncated sequential sampling plan of electrical products having two failure modes is proposed in this paper. The newly proposed sequential sampling plan takes two different failure modes of an electrical product into consideration, consisting of the sequential sampling scheme for soft-failure mode and the sequential sampling scheme for catastrophic-failure mode. The concept of cut-off line is introduced, limiting the sample size within a certain range. At last, a numerical example is provided. This newly proposed sequential sampling plan provides a reference for the design of economic acceptance sampling plans for expensive electrical products and the products with multi-failure modes.

Reliability evaluation of local corrosion of X80 pipeline subjected to accidental earthquake considering geotechnical discontinuities

Local corrosion poses a big threat to the integrity and safety of steel pipelines. Investigation of the failure pressure of buried pipelines containing multiple corrosion defects subjected to earthquakes is vital for pipeline safety. In-line inspection (ILI) data is introduced to estimate and update the 3D random corrosion growth model, embedded in the development of a nonlinear finite element analysis (FEA) model of the X80 pressure pipeline. The novelty of this work lies in the development of a nonlinear FE dynamic model for the typical spatiotemporal evolution of corroded pipelines considering vertical heterogeneous soil structure, which further implements performance-based reliability assessment. The system reliability is estimated by combining the improved equivalent component approach (IECA) and extreme value theory (EVT). Numerical studies illustrate that the proposed model is feasible for corroded pipelines under an earthquake to execute a multi-failure mode reliability assessment to find the possible failure pressure.

Optimal preventive maintenance level for a repairable product under warranty subject to multimode failure process

PurposeThe purpose of this paper is to develop a model that determines whether how much effort of preventive maintenance action is worthwhile for the consumer over the post-sale product life cycle of a repairable complex product where the product is under warranty and subject to stochastic multimode failure process, that is, damaging failure and light failure with different probabilities.Design/methodology/approachThe expected life cycle cost is designed for a warranted product from the consumer perspective. The product failure is quantified with failure rate function, which is the number of failures incurred over the product life cycle. The authors consider the failure rate function reduction method in their model where the scale parameter of a failure rate function is maximized by applying the optimal preventive maintenance level. The scale parameter of any failure distribution refers to the meantime to failure (MTTF). The first-order condition is applied with respect to the maintenance level in order to achieve the convexity of the nonlinear function of the expected life cycle cost function.FindingsThe authors have found analytically the close form of the preventive maintenance level, which can be used to find the optimal reduced form of the failure rate function of the product and the minimum product expected life cycle cost under the given condition of multimode stochastic failure process. The authors have suggested different maintenance policies to consumers in order to implement the proposed preventive maintenance model under different conditions. A numerical example further illustrated the analytical model by considering the Weibull distribution.Practical implicationsThe consumer may use this study in the accurate modeling of the life cycle cost of a product that is under warranty and fails with a multimode failure process. Also, the suggested preventive maintenance approach of this study helps the consumer in making appropriate maintenance decisions such as to minimize the expected life cycle cost of a product.Originality/valueThis study proposes an accurate estimation of a life cycle cost for a product that is under the support of warranty and fails with multimode. Furthermore, for such a kind of product, which is under warranty and fails with multimode, this study suggests a new preventive maintenance approach that assures the minimum expected life cycle cost.

Application Research on Reliability Modeling of Multi-failure Modes Correlation System Based on Time Varying Copula Model

The reliability modeling of dynamic correlation system with multi-failure modes is studied in this paper. Firstly, Patton model, one of the time-varying copula models, is introduced. Secondly, multi-dimensional time-varying copula function of multi-failure modes correlation system is transformed into two-dimensional time-varying copula functions based on vine Copula function, and then reliability modeling and solution procedure of multi-failure modes correlation system is presented based on time-varying copula model. Finally, the above reliability modeling and solution procedures are demonstrated through a vehicle suspension system engineering case, and their correctness are proved by the results obtained in engineering case.

A Comprehensive Reliability Evaluation Model of Turbine Runner Blades under Complex Conditions

In this paper, a comprehensive method to evaluate the reliability of turbine runner blades under complex conditions has been proposed. The method takes into consideration the flow excitation parameters acting on the blades under different conditions, which present different uncertain information characteristics. The structural performance function of both vibration failure and fatigue failure of runner blades has been established, according to their vibration and fatigue characteristics. A probabilistic reliability model of the multi-failure modes of runner blades under their rated conditions has been established through application of random reliability theory, and a probabilistic non-probabilistic reliability model of the multi-failure modes of runner blades under non-rated conditions has been established by applying random reliability theory and non-probabilistic reliability theory, based on the structural performance function of both vibration failure and fatigue failure, taking into consideration the uncertain information characteristics of the flow excitation parameters that act on the runner blades under different conditions. On the basis of the two reliability models, a comprehensive model to evaluate the reliability of runner blades under complex conditions has been constructed. The reliability of the turbine runner blades under complex conditions has been analyzed through the use of examples, and the accuracy of the models has been proved using the Monte Carlo simulation (MCS).