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Accurately analyzing the reliability of driveshaft systems is crucial in engineering vehicles and mechanical equipment. A complex system reliability modeling and analysis method based on a dynamic Bayesian network (DBN) is proposed to repair accurately and reduce the cost in time. Considering the logical structure of the drive shaft system, the reliability block diagram (RBD) of the manufacturing system is constructed in a hierarchical and graded manner, and a method of obtaining the Bayesian network (BN) directly from the RBD is adopted based on the conversion relationship between the RBD, fault tree and BN. A variable‐structure DBN model of the system is constructed based on a static BN extended in time series and incorporating dynamic reliability parameters of the components. Reliability analyses based on DBN reasoning, including reliability assessment, significance metrics, and sensitivity analyses, were performed to identify critical subsystems and critical components. This research contributes to enhancing product reliability, equipment utilization, and improving economic efficiency. [ABSTRACT FROM AUTHOR]

Fatigue testing is a crucial technique for assessing the fatigue performance of materials and components. However, the testing process often involves numerous uncertainties, such as variations in part roughness and size, and the collected data typically constitutes small samples. This paper proposes an improved bootstrap method with cycle of uncertainty to address the limitations of traditional bootstrap methods in estimating uncertainties in small sample sizes. The proposed method was applied to estimate the effect of surface roughness and common normal size on fatigue tests, resulting in improved estimation accuracy. The research contributes to the development of improved methods for fatigue life estimation, which has practical implications for mechanical component design and optimization. Highlights: Virtual data are expanded by assigning samples to a normal distribution.Bootstrap method is improved by introducing cycle of uncertain.The effect of uncertainties is considered in the fatigue test on the results. [ABSTRACT FROM AUTHOR]

Automotive drive shaft is an indispensable key component of the transmission system, and the use of composite drive shafts has shown great promise. The epoxy matrix of the shaft is susceptible to the effects of temperature in comparison to carbon fiber. To investigate the influence of the environmental temperature on the fatigue life of a carbon fiber‐reinforced plastic drive shaft, a temperature‐based property curve and performance fraction model for the shaft are established. The temperature coefficient is calculated and introduced by combining the collected temperature data with the property fraction function. A generalized S‐N surface of the composite drive shaft is proposed based on experimental data. The fatigue life under collected and processed random loads of the carbon fiber‐reinforced plastic drive shaft is predicted by modified Miner's law. The effect of mean, amplitude of load and ambient temperature on fatigue life are taken into account. Highlights: Drive shaft load spectrum was acquired and preprocessed.Model of the carbon fiber‐reinforced plastic (CFRP) drive shaft was built for torsion strength with temperature.The temperature coefficient was calculated via temperature distribution and the model.Fatigue life of CFRP drive shaft was predicted by combining improved S‐N surfaces. [ABSTRACT FROM AUTHOR]

Springs are widely used in the automobile industry. They can produce large elastic deformation under the action of load. The fracture failure of springs will cause significant loss or maintenance costs. The fatigue life of springs is greatly affected by load eccentricity and residual stress. Some existing methods are not accurate enough to predict the life of springs. The cracked spring stresses are computed considering load eccentricity. Based on the Walker model, a method for predicting the spring fatigue life is proposed. The model combines the superposition principle and the closure effect, and it can consider residual stress, crack closure effect, and load eccentricity at the same time. The results demonstrate that the improved model has a better performance than the Walker model. Highlights: Load eccentricity is used to correct the critical crack size.Superposition principle is applied to spring life prediction.A spring life model considering crack closure effect and residual stress is proposed.This model is suitable for the fatigue life of coil springs. [ABSTRACT FROM AUTHOR]

To meet the different functional requirements of the components, irregularities and geometric discontinuities occur in the structural design of the components. These geometrical discontinuities lead to local stress concentrations, which inevitably introduce notch effects. The unyielding internal material still supports the high‐stress area on the plane due to the supporting effect of the notch. This effect can lead to inaccurate prediction of fatigue life. So, the notch support factor and strain were used as damage parameters to modify the life prediction model of the notched specimens in this research. And an improved critical plane method is applied in selecting damaged planes. It considers the damage at the notch before loading and uses dynamic weights to measure the effect of the maximum stress plane on the damaged plane. The model was validated using TC4 and GH4169 notch data and compared with other models, and the revised model has higher accuracy. The damaged plane and damage parameters to modify the fatigue life of the notched specimen make more physical sense and are more consistent with the fatigue failure mechanism. Highlights: Correction of multiaxial fatigue life models using damage parameters.Improving critical plane model by considering damage before loading of notched members.A fatigue life model was developed using modified critical plane and damage parameters. [ABSTRACT FROM AUTHOR]

The fatigue life for the rear suspension lower arm of the passenger car is investigated. The road load signals collected by the sextant force measuring instrument are processed. And the frequency histogram of it is plotted and its distribution characteristics are analyzed. The load signal is extrapolated to a cumulative frequency of 106 using the parametric method, and the one‐dimensional load spectrum of the lower arm is compiled. Based on the nonlinear fatigue cumulative damage theory, Corten–Dolan model is modified by introducing the kth power of the stress ratio between two adjacent levels. The improved fatigue life prediction model is established and the validity of the model was determined by experimental data. And the improved Corten–Dolan and the linear cumulative damage model are used to predict the life of the lower arm under one‐dimensional load spectrum respectively. Highlights: The load signals are analyzed and the one‐dimensional load spectrum is compiled.Corten–Dolan is modified by the kth power of the stress ratio between two adjacent levels.The modified model is verified with experimental data.The fatigue life of the lower arm is predicted via the modified model. [ABSTRACT FROM AUTHOR]

The small load has fuzziness on the strengthening and damage of the component under the action of random fatigue load. This paper introduces the two‐dimensional membership function in fuzzy mathematics to characterize the relationship between stress amplitude, mean value, and damage below the fatigue limit. An exponential function is used to describe the strengthening effect. Under the two‐dimensional load spectrum, the influence of various levels on the component's life is comprehensively considered, and the fatigue life prediction model under random load is proposed. Through the small sample experiment of the car swing support rod, the relevant parameters of the model are obtained. The difference between the modified two‐dimensional and the two‐dimensional load spectrum is compared in fatigue life prediction results. The rules of membership function selection and parameter setting are summarized, and it makes the estimation of component load spectrum life more reasonable. [ABSTRACT FROM AUTHOR]

Effects of dietary bile acids on the growth performance, lipid metabolism, non‐specific immunity and intestinal microbiota of Pacific white shrimp (Litopenaeus vannamei) were studied. Five diets were formulated to contain 0, 0.1, 0.2, 0.3 and 0.5 g kg−1 (control, BA1, BA2, BA3 and BA4) of bile acids, respectively. Shrimp (1.09 ± 0.04 g) were assigned randomly to 15 tanks (400 L, three tanks in each group, 60 shrimp in each tank) for 60 days. Results indicated that BA2 group had the highest final weight and weight gain. The contents of triglyceride decreased significantly with increasing bile acids level (p <.05). The contents of high‐density lipoprotein and glutathione, total antioxidant capacity as well as protease, lipase and superoxide dismutase activities in BA2‐4 groups increased significantly (p <.05). Additionally, bile acids enhance the immune response of shrimp through NF‐κB‐mediated signalling pathway and 0.5g kg−1 bile acids could cause oxidative damage to shrimp. High‐throughput sequencing analysis revealed that the intestinal microbiota diversity and richness were significantly altered by bile acids, and functional genes associated with metabolism and bile acids biotransformation were strongly activated in BA2 and BA4 groups. Together, we recommend the shrimp diet supplemented with bile acids at the level of 0.2 g kg−1. [ABSTRACT FROM AUTHOR]

Purpose: Understanding the spectrum of ocular pathogens in a given geographic region is important for devising appropriate practical treatment. Therefore, we examined the pathogen spectrum and antibiotic resistance of microbial keratitis in northeast China. Methods: In this retrospective observational study, we reviewed the microbiology laboratory records of patients diagnosed with microbial keratitis in a tertiary eye hospital in Harbin, northeast China, between 2017 and 2019, and analysed the pathogen spectrum and antibiotic susceptibility. Results: We collected 462 specimens, of which 282 exhibited positive cultures. Among these cultures, 257 were bacterial and 25 were fungal. Of the 257 bacterial isolates, 214 (83.27%) were gram positive whereas 43 (16.73%) were gram negative. The most prevalent gram‐positive pathogen was coagulase‐negative staphylococcus (CoNS; 58.37%), followed by Staphylococcus aureus (S. aureus; 20.62%) and Streptococcus pneumoniae (2.33%). Of the gram‐negative bacterial isolates, 10 were Pseudomonas aeruginosa (3.89%). The most frequently detected ocular pathogens from fungal isolates were Fusarium species (40%). We also found more culture‐positive cases of bacterial keratitis in summer. Overall, 16.98% S. aureus and 64.00% CoNS isolates were methicillin resistant. These methicillin‐resistant bacteria were also more likely to be resistant to other antibiotics, with multidrug resistance found in 77.78% methicillin‐resistant S. aureus and 90.63% methicillin‐resistant CoNS. However, all gram‐positive isolates were sensitive to vancomycin and linezolid. Conclusion: Coagulase‐negative staphylococcus are the most common ocular pathogens in northeast China. We also show the prevalence of methicillin resistance and concurrent multidrug resistance among staphylococcal isolates. Monitoring the patterns of antimicrobial resistance could help in the management selection. [ABSTRACT FROM AUTHOR]

The improvement of mechanical parts inherent reliability has an impact on the reputation and performance of the company. To estimate the inherent reliability of products more conveniently and economically, a hidden quality cost‐production cost (HQC‐PC) reliability prediction model is put forward. To estimate the hidden quality cost (HQC) of products more accurately, a quadratic exponential quality loss function model is established, which is different from Taguchi's quadratic quality loss function (QLF) and the modified QLFs. In the new quality loss model, the growth rate of quality loss on both sides of the target value is considered. Under the condition that the quality characteristic value obeys normal distribution, the general estimation formulas of HQC in the tolerance range is obtained considering sampling error and the numerical model of inherent reliability is established. The effect of different parameters on the inherent reliability of products is discussed with practical case, such as design and production parameters. Then, the appropriate process capability index (PCI) is selected according to different production processes. The relationship between the HQC‐PC reliability prediction model and PCI is derived by a numerical model of inherent reliability. A new analysis method of inherent reliability is proposed. [ABSTRACT FROM AUTHOR]

There are differences among sampling data and representation types of uncertain interval, fuzzy and random variables, which increases the complexity of structure reliability analysis. A α, β‐Cut‐FORM is proposed to analyze structure reliability considering the mixed uncertain variables. Fuzzy variables are optimized on the interval under two cut sets (α, β) based on the theory of cut set optimization. Interval variables are modeled with probability using a uniformity method. The proposed method involves the nested probabilistic analysis and interval analysis. The first‐order reliability method (FORM) is used for probabilistic analysis and nonlinear optimization is used for interval analysis. The excavator boom performance function is established for reliability analysis considering the mixed uncertain input variables, which verifies the effectiveness and advantages of the proposed method. And it has great application for safe and reliable design of excavator boom. [ABSTRACT FROM AUTHOR]

To accurately predict quality loss of high reliability and long‐life product in service, a dynamic quality characteristics model is established based on linear degeneration and random error. According to this model, the expectation and variance of dynamic quality characteristics can be figured out. Moreover, assuming that the quality characteristics follow the normal distribution at the initial stage, the expectation of quality loss and the life distribution of dynamic quality characteristics follow three types are derived, such as L‐type (Larger is better), S‐type (Smaller is better), and N‐type (Nominal is better). According to the discount theory of quality loss, the present value model of dynamic quality loss based on the life is derived by combining life and the present value of dynamic quality loss. Then, this model is used to evaluate the quality loss of a GaAs laser and the rationality of the model is analyzed. [ABSTRACT FROM AUTHOR]

To further study the law of strength degradation, the residual strength degradation model is established based on the definition of fatigue damage, considering the interaction of various uncertain factors and time factors in service environment. Combined with equivalent damage model, a nonlinear cumulative damage model is proposed, which takes the interaction among loading loads into account and improves the accuracy of calculation. Additionally, the equivalent transformation of multistage load is studied using interval theory. According to the interval dynamic nonprobability reliability prediction model, a dynamic reliability analysis of the interval model is carried out. Dynamic reliability of the component is analyzed under multistage load accumulation damage to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

To accurately predict the degraded fatigue life of components under random loads, anelasticity effect of metal on life estimation needs to be explored. Weighting coefficient and dynamic elastic modulus are introduced to modify the calculation process of the model. By establishing an equal‐amplitude fatigue median surface and applying Miner linear fatigue cumulative damage theory, a fatigue life prediction model of the component under random loads is proposed. The model can be used to calculate the degraded fatigue life of components, which provides a theoretical basis for life estimation under random load spectrum. The two‐dimensional load spectrum is compared with the unprocessed two‐dimensional load spectrum and the one‐dimensional program spectrum in life prediction results. With the comparison of the target life and simulation life and the data calculated by the model of the automobile front stabilizer bar, it is concluded that the data obtained by the modified model are more reasonable and accurate. [ABSTRACT FROM AUTHOR]

In the field of fatigue crack, crack size is a worthy topic to discuss. The relationship between crack length and depth is studied based on the Paris law, and a numerical model is established. The validity of the model is proved by comparing theoretical data with experimental data. In addition, the analysis of stress distribution of liquid-storage tank is carried out and the influence of hoop stress on the liquid-storage tank is considered. Remaining life of the tank is predicted through the numerical model. The feasibility of the numerical method is verified by predicting the remaining life of the tank, which provides a simple way for fatigue life prediction of the liquid-storage tank. [ABSTRACT FROM AUTHOR]

Fatigue life prediction is an important part of the reliability and durability analysis of automobile components. Based on Wang and Brown's framework, multiaxial random fatigue damage was adopted to predict the fatigue life of half-shaft. The stress analysis of half-shaft was resolved analytically to determine the local stress tensor in the potential area of fracture. The maximum shear strain fatigue damage parameter and the normal stress fatigue damage parameter were evaluated to predict the fatigue life of half-shaft. The results show that the prediction method is reliable and meets the service life and safety requirements. [ABSTRACT FROM AUTHOR]

To eliminate the limitations of the peak‐over‐threshold (POT) extrapolation method, the paper proposes an improved POT extrapolation method to reconstruct the load sequence and frequency of the part. A threshold model is established based on a generalized Pareto distribution (GPD). Assuming a road surface's irregularity obeys a normal distribution, the load between the upper and lower thresholds is reconstructed to obtain more dynamic road load data. Rain‐flow counting method is used to calculate the peak‐to‐valley value and frequency of the load signal, and the characteristics of the load mean and amplitude before and after the improvement of the POT extrapolation method were discussed. The effectiveness and conservativeness of the enhanced method are verified by predicting the fatigue life of a swing support rod. [ABSTRACT FROM AUTHOR]

The greenfin horse‐faced filefish, Thamnaconus septentrionalis, is a valuable commercial fish species that is widely distributed in the Indo‐West Pacific Ocean. This fish has characteristic blue–green fins, rough skin and a spine‐like first dorsal fin. Thamnaconus septentrionalis is of conservation concern because its population has declined sharply, and it is an important marine aquaculture fish species in China. Genomic resources for the filefish are lacking, and no reference genome has been released. In this study, the first chromosome‐level genome of T. septentrionalis was constructed using nanopore sequencing and Hi‐C technology. A total of 50.95 Gb polished nanopore sequences were generated and were assembled into a 474.31‐Mb genome, accounting for 96.45% of the estimated genome size of this filefish. The assembled genome contained only 242 contigs, and the achieved contig N50 was 22.46 Mb, a surprisingly high value among all sequenced fish species. Hi‐C scaffolding of the genome resulted in 20 pseudochromosomes containing 99.44% of the total assembled sequences. The genome contained 67.35 Mb of repeat sequences, accounting for 14.2% of the assembly. A total of 22,067 protein‐coding genes were predicted, 94.82% of which were successfully annotated with putative functions. Furthermore, a phylogenetic tree was constructed using 1,872 single‐copy orthologous genes, and 67 unique gene families were identified in the filefish genome. This high‐quality assembled genome will be a valuable resource for a range of future genomic, conservation and breeding studies of T. septentrionalis. [ABSTRACT FROM AUTHOR]

To predict the service life of clutch sleeve, major reasons for the change of clearance between the clutch sleeve and shell in service period are analysed. A mathematical model of the clearance is established considering abrasion of the step outside sleeve caused by friction. To determine the size of abrasion, a micro‐convex body model for the friction surface is built. Based on surface fatigue abrasion theory, an abrasion model is established. A life model is established based on the entire abrasion of the sleeve. Fatigue life of sleeve is predicted using the model based on actual surface morphology parameters of the enterprise products. Major factors affecting the abrasion speed are discussed and determined after the prediction result is analysed. [ABSTRACT FROM AUTHOR]

A fuel cell vehicle (FCV) is composed of many subsystems; it is necessary to reallocate subsystem reliability to improve FCV system reliability. A comprehensive evaluation method considering uncertainty is proposed to obtain the interval value of feasibility factor. The FCV cost uncertainty model is established on the basic of parameters such as feasibility factor, initial reliability, limit reliability, and subsystem cost. To solve the optimization problem for cost uncertainty, the cost interval model is transformed into a deterministic model by interval order relation. An improved differential evolution (DE) algorithm is proposed to reallocate subsystem reliability for minimum cost. [ABSTRACT FROM AUTHOR]

The traditional quality evaluation method believed that when the product quality characteristic was within the specification limit, no loss was produced. Taguchi proposed that even if the characteristic was within the range of users' demand, the fluctuation of quality characteristic would still cause loss to users and society. Therefore, he proposed a quadratic quality loss function to describe this loss. The function was established based on the Taylor expansion. It neglected terms with powers higher than 2, which would cause a certain deviation between the calculated and true value. Moreover, the tolerance and loss in the quadratic loss function must satisfied specific relationship, which limited its use. In this paper, the Taylor expansion items are raised to third order. The quality loss coefficients are discussed and analyzed so that the cubic quality loss function is established. In addition, the method of calculating hidden quality cost is given by using the cubic loss function. The hidden quality cost is affected by the quality loss coefficients and should be a range. The cubic quality loss function studies the inapplicability of quadratic loss function, so it widens the scope of application of quality loss function. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary arterial hypertension (IPAH) is a severe cardiovascular disease that is a serious threat to human life. However, the specific diagnostic biomarkers have not been fully clarified and candidate regulatory targets for IPAH have not been identified. The aim of this study was to explore the potential diagnostic biomarkers and possible regulatory targets of IPAH. We performed a weighted gene coexpression network analysis and calculated module‐trait correlations based on a public microarray data set (GSE703) and six modules were found to be related to IPAH. Two modules which have the strongest correlation with IPAH were further analyzed and the top 10 hub genes in the two modules were identified. Furthermore, we validated the data by quantitative real‐time polymerase chain reaction (qRT‐PCR) in an independent sample set originated from our study center. Overall, the qRT‐PCR results were consistent with most of the results of the microarray analysis. Intriguingly, the highest change was found for YWHAB, a gene encodes a protein belonging to the 14‐3‐3 family of proteins, members of which mediate signal transduction by binding to phosphoserine‐containing proteins. Thus, YWHAB was subsequently selected for validation. In congruent with the gene expression analysis, plasma 14‐3‐3β concentrations were significantly increased in patients with IPAH compared with healthy controls, and 14‐3‐3β expression was also positively correlated with mean pulmonary artery pressure (R2 = 0.8783; p < 0.001). Taken together, using weighted gene coexpression analysis, YWHAB was identified and validated in association with IPAH progression, which might serve as a biomarker and/or therapeutic target for IPAH. Using weighted gene coexpression analysis, YWHAB was identified and validated in association with IPAH progression, which might serve as a biomarker and/or therapeutic target for IPAH. [ABSTRACT FROM AUTHOR]

Abstract: The state‐of‐power (SOP) of a Li‐ion battery (LIB) is an important evaluation index for safety control and energy recovery in electric vehicles. Major state estimation methods are only applicable to fixed room temperature at 20 °C, although the battery capacity and resistance vary dramatically with a change in battery surface temperature in the working process of the battery. This causes significant errors in state estimation if only room temperature is assumed. The inaccurate state may cause further excessive current at high or low temperatures to affect safety and life cycle of the battery. Therefore, a novel state estimation method applicable to various battery surface temperatures is developed here. This method uses capacity–temperature and resistance–temperature relationships from experimental data to more accurately predict battery capacity and resistance over the full temperature range. It then applies the extended Kalman filter (EKF) technique to estimate the state‐of‐charge, and a method of constrained multi‐parameter algorithm (CMPA) to estimate the SOP of LIBs. Simulation and experimental results show that the proposed method can obtain accurate SOP results at different temperatures. [ABSTRACT FROM AUTHOR]

The study discusses how some challenges from a small sample fatigue test can be analysed statistically and resolved. In terms of data dispersion, fatigue data are initially processed by confidence, and then, the fatigue life curve is replaced by the parabolic reliability approximation. Fatigue data under various reliability levels are obtained. Instead of the traditional single S-N curve, the mean value curve and mean square deviation curve of the S-N curve are computed based on the processed fatigue data. The S-N curve with reliability is deduced by applying quantile theory. The S-N curve is improved by considering the effects of low-amplitude load strengthening. The benefits of the modification are visible in the comparison of the fatigue life before and after low-amplitude load strengthening. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The estimation of state-of-charge (SOC) is crucial to determine the remaining capacity of the Lithium-Ion battery, and thus plays an important role in many electric vehicle control and energy storage management problems. The accuracy of the estimated SOC depends mostly on the accuracy of the battery model, which is mainly affected by factors like temperature, State of Health (SOH), and chemical reactions. Also many characteristic parameters of the battery cell, such as the output voltage, the internal resistance and so on, have close relations with SOC. Battery models are often identified by a large amount of experiments under different SOCs and temperatures. To resolve this difficulty and also improve modeling accuracy, a multiple input parameter fitting model of the Lithium-Ion battery and the factors that would affect the accuracy of the battery model are derived from the Nernst equation in this paper. Statistics theory is applied to obtain a more accurate battery model while using less measurement data. The relevant parameters can be calculated by data fitting through measurement on factors like continuously changing temperatures. From the obtained battery model, Extended Kalman Filter algorithm is applied to estimate the SOC. Finally, simulation and experimental results are given to illustrate the advantage of the proposed SOC estimation method. It is found that the proposed SOC estimation method always satisfies the precision requirement in the relevant Standards under different environmental temperatures. Particularly, the SOC estimation accuracy can be improved by 14% under low temperatures below 0 °C compared with existing methods. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

State of Health (SOH) is one of the most important parameters of lead-acid batteries. Most of the existing SOH estimation methods only take the influence of charge cycles into consideration, and the estimation accuracy is limited. Batteries in the substations have two typical states: one is the check-discharge state, in which the batteries are discharged for 8 h at 0.1 C (Capacity) to determine whether the battery pack has certain reliability. The other is the floating charge state, in which the batteries are connected to the charger to maintain full power. This paper proposes a novel SOH estimation method based on the two states. In the check-discharge state, the relationship between the voltage and the age of battery is analysed. The health index, which is introduced in this model, is affected by the age of battery. In the floating state, the relationship between the internal resistance and the age of battery is discussed. Another SOH model is established based on the change of the internal resistance. By combining the two models, the estimation method can achieve real-time estimation and high accuracy for substation application. An accelerated life test is applied to verify the theoretical analysis. The experimental results demonstrate that the SOH estimation error is less than 3% which is very satisfactory for practical applications. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The differential is an important part of a driveline, and differential performance is related to the handling and stability performance of a vehicle. Thus, a differential with sound design structure and reasonable form and size parameters could lead to satisfactory driving performance. In this work, we analyze and evaluate the reliability of the key parts of a differential system. Firstly, each of key parts is regarded as a subsystem of a differential system, so the subsystem reliability models are obtained. A system reliability model is built based on the paths of the forces from the differential system, and system reliability is calculated. Secondly, according to the result of the analysis of system reliability and the use of the six sigma method, 45 steel or 1Cr18Ni9Ti utilized as the material for the worm shaft, system reliability is analyzed and discussed separately. Then, the reliability of the key parts and the overall system reliability increase with the low load strengthening characteristic of the material. Finally, according to the analysis and discussion, the level of system reliability matches that required for differential systems, and the cost is also considerably reduced, as demonstrated using the stress-strength interference and low-load strengthening models. These results provide a theoretical basis for the improvement of the design of Torsen differentials. Similar methods can be used to develop automobile subsystems in the future. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The failures of complex systems always arise from different causes in reliability test. However, it is difficult to evaluate the failure effect caused by a specific cause in presence of other causes. Therefore, a generalize reliability analysis model, which takes into account of the multiple competing causes, is highly needed. This paper develops a statistical reliability analysis procedure to investigate the reliability characteristics of multiple failure causes under independent competing risks. We mainly consider the case when the lifetime data follow log-location-scale distributions and may also be right-censored. Maximum likelihood (ML) estimators of unknown parameters are derived by applying the Newton-Raphson method. With the large-sample assumption, the normal approximation of the ML estimators is used to construct the asymptotic confidence intervals in which the standard error of the variance-covariance matrix is calculated by using the delta method. In particular, the Akaike information criterion is utilized to determine the appropriate fitted distribution for each cause of failure. An illustrative numerical experiment about the fuel cell engine (FCE) is presented to demonstrate the feasibility and effectiveness of the proposed model. The results can facilitate continued advancement in reliability prediction and reliability allocation for FCE, and also provide theoretical basis for the application of reliability concepts to many other complex systems. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A fuel cell vehicle (FCV) is a type of alternative energy vehicle that could help resolve the energy crisis, mitigate environmental problems, and contribute to sustainable development. Developing an FCV with high reliability is an important goal for automobile factories and research institutions. Other key factors required by FCVs include mass production and customer approval. An FCV is a complex mechanism composed of many subsystems. During the development of the overall vehicle, steps should be taken to ensure that every subsystem is reliable. However, such development must also consider costs, which must be kept as low as possible. To ensure the reliability of FCV while operating under conditions that demand minimal cost, a genetic algorithm is employed to reallocate the reliability of the overall vehicle system. First, the growth factor of the reliability-feasibility of each subsystem is determined according to the complexity, importance, and technological level of the FCV subsystems. The FCV cost model is then established on the basis of such parameters as subsystem cost, reliability-feasibility growth factor, initial reliability, limit reliability, and so on. A genetic algorithm is then used to compute for the reliability of FCV subsystems. The rationality of reliability reallocation is verified according to the subsystem importance coefficient. This method considers the benefits for both enterprises and customers by applying principles of engineering and conducting a reliability study. [ABSTRACT FROM AUTHOR]

Metal welding structural strength was affected by the quality of automobile welding structure. Many accidents of the machines are caused by welding defects of automobile structure. Many welding parts are applied in the automobile. Reliability of automobile welding structure is studied and discussed in this paper. Failure modes and ultimate strength of automobile welding structure are obtained with bench test. The results show that all the failures happen in the welded region between clutch hub and clutch hub axle. Finite element model is built, and automobile welding structural strength is analyzed. And simulation results are in line with that of the experiment. Based on stress and strength interference model, automobile welding structure reliability is studied and discussed with theory of probability and reliability. In accordance with matching working load with structural strength, a new method of improvement design is proposed with the aim of automobile welding structural strength reliability. It provides a theoretical basis for automobile welding structure improvement design. And similar methods can be used to develop automobile welding structure and laser welding processes in future. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]