Failure Distribution Research Articles

Mechanism of Roof Deformation and Support Optimization of Deeply Buried Roadway under Mining Conditions

Large deformations in local areas during service in a mine roadway are prone to roofing hazards, seriously threatening people’s lives and urgently needing to be addressed by means of support optimization. Traditional methods of studying the stability of the roadway roof are mainly based on the theory of the surrounding rock loosening circle, but few studies analyze the stability of roadway roofs around the failure distribution and expansion of weak interlayers. Therefore, the relationship between the deformation characteristics of the tunnel envelope and the thickness of the soft and weak interlayer and the underlying hard rock layer was investigated using a comprehensive research method such as theoretical analysis, numerical simulation, and field monitoring. The results show that the form of roadway roof failure is determined by weak interlayer thickness. For a mining-disturbed roadway, if the weak interlayer thickness remains unchanged, as the underlying hard strata thickness increases, the existence of a more integral hard stratum cannot prevent plastic zones from forming in the weak interlayer but can prevent them from developing in the key layer 1. If the underlying hard strata thickness remains unchanged, the smaller the weak interlayer thickness, the smaller the area of plastic zone failure in the roadway roof. After the deformation characteristics of the roadway containing the weak interlayer were clarified, according to its characteristics, the support optimization method of increasing the length of anchor bolt and anchor cable is proposed. The displacement of the roadway roof was reduced by 35% after verification by numerical simulation. After applying the support optimization method on site, the roadway displacement basically stabilized after 40 days, with the roof slab sinkage, two gang convergence and bottom bulge reaching 53 mm, 42 mm and 39 mm, respectively. The overall deformation of the roadway was small, effectively controlling the surrounding rock deformation and reducing economic losses for the mine.

Pollination system and reproductive failure in an endangered semi-evergreen tree, Syzygium myhendrae (Bedd. ex Brandis) Gamble

• The relationship between the phenology of Syzygium myhendrae and climatic factors was studied. • Visitation frequency and visitor activity index were calculated for each floral visitor to confirm its pollination efficiency. • The flowers were exclusively visited by honeybees, rockbee, wasps, psyllids and beetles. • Eulophid and pteromalid parasitic wasps were limited the fruit set rate and induced premature fruit drop. • Higher bud drop, flower wastage and insect infestation on fruits decreased the fruit production. The present investigation has attempted to analyze the phenology, floral biology, pollination biology, fruit set and insect infestation on Syzygium myhendrae , an endemic and endangered semievergreen tree in the Western Ghats, India. This tree exhibited a bi-annual mode of flowering and fruiting behavior. The flowers lack strong fragrance, colorful and attractive petals, or sepals; however, the dense stamens functioned as a major floral advertisement. The flowers were exclusively visited by insects ( Apis dorsata, A. mellifera, A. cerana, A. florea, Tetragonula iridipennis , wasps, psyllids and beetles). Among these, A. dorsata was the most frequent and effective pollinator. The infestation by Eulophid and Pteromalid wasps has limited the fruit set rate and induced premature fruit drop in S. myhendrae. The damage incidence has ranged from 82% to 100%. Higher bud drop, flower wastage and insect infestation on fruits have resulted in lower fruit production in S. myhendrae . This endangered tree has reproduced via outcrossing using stamen advertisement and pollen rewards. Eventually, higher flower wastage and fruits infestation have resulted in lesser fruit production, seed maturation and seedling establishment. These factors might have jointly resulted in the reproductive failure and limited distribution of this endemic and endangered species.

Experimental Validation of a Novel Methodology for Electromigration Assessment in On-Chip Power Grids

A recently proposed theoretical methodology for the assessment of the electromigration (EM) induced IR-drop degradation in on-chip power/ground grids has been validated by means of measurements performed on real silicon. A voltage tapping technique was employed for the direct measurement of voltage variations at 162 nodes of the power net, stressed with 10 mA constant source current at an elevated temperature of 350 °C. A voltage drop between cathode and anode pads exceeding a specified threshold was considered as a failure. Times-to-failure (TTF) was measured on 19 packaged test grids and used for computing the mean TTF (MTTF). The EM-induced voltage degradation in this grid was also analyzed with an assessment methodology based on a simulation of stress evolution everywhere in the grid, resulting in a voiding in some of grid branches and corresponding resistance increase. A set of voiding compact models for different grid segments was developed and used in the simulations. The stochastic nature of the EM phenomenon was captured by introducing random distributions of atomic diffusivities and critical stresses across the grid and iterating them with Monte Carlo loops. A good fit between the measured voltage evolution kinetics at different grid nodes and that predicted by simulation, and the good agreement between measured and simulated failure distributions can be considered as the ever first experimental validation of this EM assessment methodology for on-chip power/ground (p/g) grids.

Optimization Model for Maintenance Planning of Loading Equipment in Open Pit Mines

Maintenance plays a significant role in operating costs in the mining industry. Improving this matter controls maintenance costs and enhances productivity and production effectively. Shovels are one of the most widely used loading machines in non-continuous activities. Thus, evaluating and optimizing their availability is one of the essential solutions to achieving high productivity and cost reduction. This paper presents a mathematical programming model to maximize availability and minimize the total expected costs. We programmed the proposed nonlinear planning model using the Symbiotic Organisms Search (SOS) meta-heuristic algorithm in Matlab software. It determines the optimal maintenance intervals for different parts of the shovel. The maintenance benefit analysis approach selects various maintenance activities in optimal maintenance intervals. The model is implemented in a practical case study, Chadormalu Iron Mine, to evaluate its performance. The failure distribution matches the Weibull distribution function. The computational results show the efficiency of the presented approach.

The Foot and Ankle Kinematics of a Simulated Progressive Collapsing Foot Deformity During Stance Phase: A Cadaveric Study.

Progressive collapsing foot deformity (PCFD) is a complex pathology associated with tendon insufficiency, ligamentous failure, joint malalignment, and aberrant plantar force distribution. Existing knowledge of PCFD consists of static measurements, which provide information about structure but little about foot and ankle kinematics during gait. A model of PCFD was simulated in cadavers (sPCFD) to quantify the difference in joint kinematics and plantar pressure between the intact and sPCFD conditions during simulated stance phase of gait. In 12 cadaveric foot and ankle specimens, the sPCFD condition was created via sectioning of the spring ligament and the medial talonavicular joint capsule followed by cyclic axial compression. Specimens were then analyzed in intact and sPCFD conditions via a robotic gait simulator, using actuators to control the extrinsic tendons and a rotating force plate underneath the specimen to mimic the stance phase of walking. Force plate position and muscle forces were optimized using a fuzzy logic iterative process to converge and simulate in vivo ground reaction forces. An 8-camera motion capture system recorded the positions of markers fixed to bones, which were then used to calculate joint kinematics, and a plantar pressure mat collected pressure distribution data. Joint kinematics and plantar pressures were compared between intact and sPCFD conditions. The sPCFD condition increased subtalar eversion in early, mid-, and late stance (P < .05), increased talonavicular abduction in mid- and late stance (P < .05), and increased ankle plantarflexion (P < .05), adduction (P < .05), and inversion (P < .05). The center of plantar pressure was significantly (P < .01) medialized in this model of sPCFD and simulated stance phase of gait. Subtalar and talonavicular joint kinematics and plantar pressure distribution significantly changed with the sPCFD and in the directions expected from a PCFD foot. We also found that ankle joint kinematics changed with medial and plantar drift of the talar head, indicating abnormal talar rotation. Although comparison to an in vivo PCFD foot was not performed, this sPCFD model produced changes in foot kinematics and indicates that concomitant abnormal changes may occur at the ankle joint with PCFD. This study describes the dynamic kinematic and plantar pressure changes in a cadaveric model of simulated progressive collapsing foot deformity during simulated stance phase.

Assessment of slope failure susceptibility along road networks in a forested region, northern Iran

The risk of slope failure is always associated with the roads constructed in mountain regions. Estimation of the susceptibility of roads to slope failure is a part of the solutions for decreasing road maintenance costs. In this study, we modeled the susceptibility of slope failure along a forest road in northern Iran using the random forest (RF) method. The distribution of past failures was surveyed during field reconnaissance to produce an inventory map. Then the failures were randomly divided into two groups such that 70% (176 locations) were used for model training and the remaining 30% (75 locations) were used for model validation. Eleven geoenvironmental factors (i.e., altitude, slope degree, slope direction, plan curvature, flow accumulation, stream power index, topographic wetness index, topographic position index, topographic roughness index, slope-length, and valley depth) that thought directly or indirectly affected slope failure were selected and linked to the failure locations. The spatial associations between the influencing factors and the failure locations were assessed using the RF method and used for generating spatially explicit maps of slope failure susceptibility. The results showed that stream power index, flow accumulation, and plan curvature with Gini coefficients of 74%, 66%, and 51%, respectively, were the most influential factors in the occurrence and distribution of slope failures. The slope failure susceptibility maps were classified using the natural breaks and geometrical intervals classification methods and showed that nearly 38.11% and 42.42% of the study area are in high to very high risk classes, respectively. Model validation using the sensitivity (92.31%), specificity (85.68%), accuracy (88.54%), root mean square error (RMSE) (0.303), and area under the curve (0.902) proved the excellent performance of the RF model in elucidating the failure mechanisms and predicting future failures. The slope failure susceptibility maps produced in this study allow the development of mitigation strategies for road construction projects.

Analysis of non-Markovian repairable fault trees through rare event simulation

Dynamic fault trees (DFTs) are widely adopted in industry to assess the dependability of safety-critical equipment. Since many systems are too large to be studied numerically, DFTs dependability is often analysed using Monte Carlo simulation. A bottleneck here is that many simulation samples are required in the case of rare events, e.g. in highly reliable systems where components seldom fail. Rare event simulation (RES) provides techniques to reduce the number of samples in the case of rare events. In this article, we present a RES technique based on importance splitting to study failures in highly reliable DFTs, more precisely, on a variant of repairable fault trees (RFT). Whereas RES usually requires meta-information from an expert, our method is fully automatic. For this, we propose two different methods to derive the so-called importance function. On the one hand, we propose to cleverly exploit the RFT structure to compositionally construct such function. On the other hand, we explore different importance functions derived in different ways from the minimal cut sets of the tree, i.e., the minimal units that determine its failure. We handle RFTs with Markovian and non-Markovian failure and repair distributions—for which no numerical methods exist—and implement the techniques on a toolchain that includes the RES engine FIG, for which we also present improvements. We finally show the efficiency of our approach in several case studies.

Reliability Analysis of a Helicopter Utility Hydraulic System Using Reliability-centered Maintenance and Bayesian Network

Purpose: Reliability-centered maintenance (RCM) provides a standardized procedure for maintenance decision-making. The Bayesian network (BN) is a powerful tool for estimating the posterior probability based on the likelihood and prior probability distribution of failures. This study demonstrates reliability analysis and maintenance decision-making using RCM and BN.BRMethods: Maintenance decisions are made following the RCM framework for the failure of the utility hydraulic system. Bayesian updating and reliability analysis can be performed using the BN model. Real cases of field failure and the survival data of AH-64E were used for this study. The common cause failure (CCF) mode was incorporated into the BN to consider aircraft battle damages.BRResults: Failure diagnostic ability was demonstrated, and the life of the system was obtained. The most effective maintenance action was suggested based on reliability calculation. In addition, the results offered support that CCF should be considered for reliability calculation.BRConclusion: Reliability analysis conducted using RCM and BN can prove beneficial for system-level maintenance decision-making. The BN with CCF revealed unforeseen risks of aircraft battle damage.

Experimental research on performance degradation of TSV microstructure under thermal cycling, vibration and electrical stress

Through‑silicon-via (TSV) microstructure is the key structure of 3D integrated packaging, and its reliability during service plays a very important role in the long-term reliable operation of the chip. However, the failure mechanism and reliability evaluation of the TSV structure in the service process of the chip have not been fully elucidated. Chips inevitably bear various stresses during the service process, such as thermal stress, vibration stress, electrical stress, etc. In this paper, a TSV reliability test chip that can be easily loaded with various stresses was designed first, and the resistivity of the TSV microstructure was tested. It is found that the resistivity of TSV has a significant scale effect. Then, thermal cycling, vibration and electromigration tests were carried out, and the failure mode, performance degradation trend and failure distribution of TSV microstructure under thermal cycling, vibration and electrical stress were analyzed. Finally, the failure analysis of the tested chip was carried out by scanning electron microscope (SEM) and high-resolution industrial micro-CT, and the potential failure mechanism were analyzed and discussed.

Aluminium corrosion in power semiconductor devices

In this study, insulated gate bipolar transistor (IGBT) power modules were exposed to high voltage, high humidity, high temperature and reverse bias (HV-H3TRB) conditions until end-of-life (EoL). The limited lifetime of power semiconductor devices when used in demanding applications involving high relative humidity during operation is commonly reported to be associated with the design of the edge termination in power transistor or diode chips. A physics-of-failure (PoF) oriented methodology was adopted in failure analysis, including using lock-in thermography (LiT) for failure localisation and using an advanced microwave-induced plasma (MIP) decapsulation technique for the selective etching of the edge termination polyimide passivation film. A focused ion beam (FIB) was utilised to create a cross-section of the samples for both scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) analysis. The evidence gathered using the physics-of-failure methodology were compared with the results from advanced statistical analysis of the failure distributions in Weibull plots, including comparison of α and β parameters. This analysis revealed correlation with the Weibull distributions and the results from the physics-of-failure. Aluminium corrosion products were systematically observed on guard rings (GR) and field plates (FP) showing that the migration of these corrosion products forming an electrical path between the guard rings that seems to be a major failure mechanism in high humidity environments when reverse bias voltage is applied.

Fluid-structure interaction simulation and evaluation of ballistic impact of STF impregnated UHMWPE fiber composites

This study reveals the fluid-structure interaction simulation of the ballistic impact of shear thickening fluid (STF) impregnated with ultra-high molecular weight polyethylene (UHMWPE) fiber composites. The STF/UHMWPE composites pull-out test results are fitted to obtain a similar STF rheological curve. The STF/UHMWPE composites fluid-structure interaction (FSI) model was established to reproduce the local failure and stress distribution at each stage of the ballistic impact process. The comparison of the finite element analysis (FEA) and the experimental results showed that the fitting degree of the STF/UHMWPE composites to the impact energy absorption was 94.74%. STF treatment has dual effects on the impact resistance of fabrics, increasing the friction and enhancing the thickening effect.

Reliability and maintainability optimization of load haul dump machines using genetic algorithm and particle swarm optimization

PurposeReliability and maintainability estimation of any system depends on the identification of the best-fitted probability distribution of failure and repair rates. The parameters of the best-fitted probability distribution are also contributing significantly to reliability estimation. In this work, a case study of load haul dump (LHD) machines is illustrated that consider the optimization of failure and repair rate parameters using two well established metaheuristic approaches, namely, genetic algorithm (GA) and particle swarm optimization (PSO). This paper aims to analyze the aforementioned points.Design/methodology/approachThe data on time between failures (TBF) and time to repairs (TTR) are collected for a LHD machine. The descriptive statistical analysis of TBF & TTR data is performed, trend and serial correlation tested and using Anderson–Darling (AD) value best-fitted distributions are identified for repair and failure times of various subsystems. The traditional methods of estimation like maximum likelihood estimation, method of moments, least-square estimation method help only in finding the local solution. Here, for finding the global solution two well-known metaheuristic approaches are applied.FindingsThe reliability of the LHD machine after 60 days on the real data set is 28.55%, using GA on 250 generations is 17.64%, and using PSO on 100 generations and 100 iterations is 30.25%. The PSO technique gives the global best value of reliability.Practical implicationsThe present work will be very convenient for reliability engineers, researchers and maintenance managers to understand the failure and repair pattern of LHD machines. The same methodology can be applied in other process industries also.Originality/valueIn this case study, initially likelihood function of the best-fitted distribution is optimized by GA and PSO. Reliability and maintainability of LHD machines evaluated by the traditional approach, GA and PSO are compared. These results will be very helpful for maintenance engineers to plan new maintenance strategies for better functioning of LHD machines.

Maintenance planning estimations and policies optimization for single-unit systems using Hawkes processes

ABSTRACT Maintenance planning and optimizations are very important issues in both theory and practice. In this paper, Hawkes processes, a tool for description of self-excited failure effects, are used to model the failure processes of single-unit systems under the assumption of neglected repair times. For such degraded single-unit systems, some maintenance planning estimations such as the distribution, mean and variance of failures or repairs by time , reliability, mean cost of maintenance, mean and variance of system lifetime are presented under the maximal entropy assumption on repair effects. Meanwhile, two optimization problems are developed by considering the lifetime mean of the single-unit system and total maintenance cost as objective functions and constraints alternatively. We have proved that both optimization problems can reduce to two simplified optimal cases, respectively, and their optimal policies are increasing stepwise sequences of increasing rates of failure rates, which greatly reduce the scope of optimal solutions. The relationships between the estimations and the optimizations are discussed. Furthermore, the detailed optimal maintenance policies for a special case are given as well including an algorithm.

Trade-in price and base warranty length: A heuristic algorithm for concurrent optimization

The companies producing durable products consider various strategies to attract customers’ attention and maximize their profit. The two inseparable policies utilized by these companies are free-replacement warranty and Trade-in. Both policies profoundly impact customers’ buying behavior and producers’ profit. In this article, we investigate a monopolist manufacturer producing durable products over a horizon of two periods. This manufacturer simultaneously implements trade-in and base warranty policies for the products and proffers them to strategic customers. The goal is to find the optimal products’ prices, warranty length, and trade-in price, considering the influences of these parameters on the manufacturer’s profit in each period. According to the warranty length and the length of each period, we developed two mathematical models. In these models, the uniform and exponential distributions are deemed as the failure distributions of the products, and a heuristic solution algorithm is then proposed based on the problems' convexity. The numerical study showed that the optimal warranty length and trade-in price are contingent on production costs, failure distributions, innovation, and strategy level. In addition, it is concluded that a higher trade-in price should be offered if the manufacturer chooses without warranty policy.

Reemergence of the Murine Bacterial Pathogen Chlamydia muridarum in Research Mouse Colonies.

Chlamydia muridarum (Cm) was detected in 2 colonies of mice with lymphoplasmacytic pulmonary infiltrates by using PCR and immunohistochemistry. This discovery was unexpected, as Cm infection had not been reported in laboratory mice since the 1940s. A Cm specific PCR assay was developed and testing implemented for the resident colonies of 8 vivaria from 3 academic institutions, 58 incoming mouse shipments from 39 academic institutions, and mice received from 55 commercial breeding colonies (4 vendors). To estimate Cm's global prevalence in research colonies, a database containing 11,387 metagenomic fecal microbiota samples from 120 institutions and a cohort of 900 diagnostic samples from 96 institutions were examined. Results indicate significant prevalence among academic institutions, with Cm detected in 63% of soiled bedding sentinels from 3 institutions; 33% of incoming mouse shipments from 39 academic institutions; 14% of 120 institutions submitting microbiota samples; and 16% of the diagnostic sample cohort. All samples from commercial breeding colonies were negative. In addition, naïve NOD. Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice exposed to Cm-shedding mice and/or their soiled bedding developed clinical disease at 21 to 28 d after exposure. These mice had a moderate-to-severe histiocytic and neutro- philic bronchointerstitial pneumonia, with their respiratory epithelium demonstrating inclusions, chlamydial major outer membrane protein immunostaining, and hybridization with a Cm reference sequence (GenBank accession no. U68436). Cm was isolated from lungs, cecum, and feces of a Cm-infected NSG mouse by using HeLa 229 cells. The considerable prevalence of Cm is likely due to widespread global interinstitutional distribution of unique mouse strains and failure to recognize that some of these mice were from enzootically infected colonies. Given that experimental Cm colonization of mice results in a robust immune response and, on occasion, pathology, natural infection may confound experimental results. Therefore, Cm should be excluded and eradicated from enzootically infected mouse colonies.

Graph reliability evaluation via random K-out-of-N systems

The present study was concerned with network failure problems for simple connected undirected graphs. A connected graph becomes unconnected through edge failure, under the assumptions that only edges can fail and each edge has an identical failure distribution. The main purpose of the present study was to show recurrent relations with respect to the number of edges in graph generation procedures. To this end, simple connected undirected graphs were correlated to random K-out-of-N systems, and key features of such systems were applied. In addition, some simple graph cases and examples were analyzed.

Improving the resilience of power grids against typhoons with data-driven spatial distributionally robust optimization.

In recent years, the increased frequency of natural hazards has led to more disruptions in power grids, potentially causing severe infrastructural damages and cascading failures. Therefore, it is important that the power system resilience be improved by implementing new technology and utilizing optimization methods. This paper proposes a data-driven spatial distributionally robust optimization (DS-DRO) model to provide an optimal plan to install and dispatch distributed energy resources (DERs) against the uncertain impact of natural hazards such as typhoons. We adopt an accurate spatial model to evaluate the failure probability with regard to system components based on wind speed. We construct a moment-based ambiguity set of the failure distribution based on historical typhoon data. A two-stage DS-DRO model is then formulated to obtain an optimal resilience enhancement strategy. We employ the combination of dual reformulation and a column-and-constraints generation algorithm, and showcase the effectiveness of the proposed approach with a modified IEEE 13-node reliability test system projected in the Hong Kong region.

Using two and three-parameter Weibull statistical model for predicting the loading rate effect on low-temperature fracture toughness of asphalt concrete with the ENDB specimen

Loading rate can affect significantly the load bearing capacity and cracking resistance of asphalt mixtures that are basically visco-elastic materials. On the other hand, the scatter of mechanical test results obtained from the asphalt mixtures (as multi ingredients and randomly distributed heterogeneous materials) would be high. Therefore, in this research the effect of loading rate on mode I fracture toughness of a fixed hot mix asphalt (HMA) mixture is investigated experimentally using several test replicates and the obtained data are analyzed using two and three parameter Weibull statistical models. The Edge Notch Disc Bend (ENDB) specimen, (that is a circular disc containing an edge crack along the diameter and loaded by three point bending) is utilized for conducting the KIc experiments under three loading rates of 0.5, 5 and 10 mm/min. For each loading rate, twenty five ENDB specimens are tested at a fixed low temperature of −12 °C and the probability of failure and Weibull distribution curves are obtained. It is shown that both two and three parameter Weibull models can be utilized successfully for predicting the mode I fracture behavior of tested asphalt material in the considered range for the loading rate. By increasing the loading rate from 0.5 to 10 mm/min, the mean KIc values and other Weibull parameters are increased. The Weibull distribution parameters obtained experimentally from the loading rates of 5 and 10 mm/min, are also predicted in terms of the Weibull parameters of the ENDB specimen tested at loading rate of 0.5 mm/min considered as a reference case.

Safety Analysis Method of Mixed Failure Model using Temporal Bayesian Network

&lt;p&gt;Dynamic Fault Tree (DFT) is used widely in the community of reliability and safety analysis of a complex system. DFT is a high-level modeling language lacking formal semantics, so we need to convert it to a mathematical model to analyze. The conventional analysis method can only solve the DFT with discrete or exponential distribution, but not the DFT with mixed distributions. To this end, we first propose a TBN framework to represent the DFT with mixed failure distribution by extending the BN and introduce Dirac delta functions and unit-step functions into the framework to represent the logical relationship and temporal relationship between the nodes, respectively. To run the standard BN inference algorithm over TBN, we fit the failure distribution of the nodes by using k-piece and n-degree polynomials. We then propose a transformation method from DFT to TBN and prove the equivalence of the transformation. Finally, the analysis of the DFT model of the X2000 avionics system shows that our approach can effectively analyze the reliability of mixed distribution failure models. Moreover, the accuracy and efficiency of the analysis are significantly better than current mainstream methods.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Discussion Guide for the Brogan Article.

Discussion Guide for the Brogan Article.