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Summary: The reliability of power converters is crucial for achieving high‐performance operation in switched reluctance motor (SRM) systems. However, there is a notable deficiency in reliability‐oriented design of power converters that can effectively integrate both static and dynamic reliability indicators. To address this issue, this paper proposes a reliability design methodology for power converters based on the Lambert importance model, aimed at enhancing reliability of SRM systems. Firstly, the modeling principles of Lambert importance model are presented. Subsequently, a reliability design method is proposed to maximize reliability within a unit economic cost framework. Especially, the proposed design scheme is designed to maximize reliability enhancement potential through a two‐pronged approach: strategic topology selection informed by potential reliability assessments and component selection guided by importance calculations. Meanwhile, dynamic reliability evaluation is carried out to form a double‐loop reliability feedback and increase the credibility of design scheme. Finally, an example is developed to verify the validity of proposed reliability design scheme. [ABSTRACT FROM AUTHOR]

The reliability of a pitch-plunge hypersonic airfoil in random fluctuating flow with both cubic and freeplay nonlinearity is examined. The Hopf bifurcation and dynamic responses of the hypersonic airfoil are performed. To analyze the reliability, the effects of stochasticity on the dynamic behaviors of the hypersonic airfoil model are discussed in detail. Several unwanted phenomena that result in the failure of the airfoil structure are induced by random fluctuations. Subsequently, the reliability of the airfoil model is defined and analyzed according to the first passage failure criteria. The effects of different parameters on the reliability are investigated. Furthermore, a nonlinear energy sink is introduced to suppress the vibration of the airfoil and enhance the reliability. Two-dimensional reliability regions of the airfoil model are given to provide the safety parameter region. The results show that the reliability of the airfoil model is significantly improved with the nonlinear energy sink. This work will provide new insights into the safety design of hypersonic aircraft. [ABSTRACT FROM AUTHOR]

AbstractAfter conducting three World-Wide Failure Exercises (WWFEs), it has become apparent that existing strength theories or criteria have certain deficiencies, and no single theory can accurately match all experimental results. As a result, there is a growing focus on the uncertainties present in the macrocosm test data of composite materials. The paper introduces the concept of uncertainty into the collection of test data for the classical Tsai-Wu failure criterion and Hashin criterion. The method proposed involves fitting the coefficients of the failure criteria by treating experimental data as random variables, a technique that diverges significantly from the conventional method of using composite allowable values to define these coefficients. It also uses the probability of success as a constraint and defines the fitted error as an optimization objective. Monte Carlo sampling is employed to perform a reliability analysis, and six sigma is used for a reliability-based optimization of the failure criteria. The Multi-Island Genetic Algorithm is utilized to search for the optimal value. The approach presented in this study provides the ability to predict future failures in composite materials by considering the uncertainty of the test data. By incorporating uncertainties into the analysis and design process, a more accurate and reliable assessment of the performance of composite materials can be achieved. Moreover, there seems to be a significant difference in the fitting error between the mean data and the normal distribution data. Additionally, when Hashin criterion is modified, the test data matches the failure envelope more closely and the degree of fit between the experimental data and the failure envelope is higher. [ABSTRACT FROM AUTHOR]

The material behavior intrinsically possesses the aleatory uncertainty (i.e., the natural variability). Against uncertainty in a given data set of elastic material responses, this paper presents a data-driven approach to reliability-based truss topology optimization under the compliance constraint. We utilize the order statistics to guarantee the confidence level of the probability that the reliability on the compliance constraint is no smaller than the target reliability, and formulate the truss optimization problem in a bi-level optimization form. By using the duality of linear optimization, we recast this bi-level optimization problem as a single-level optimization problem, which can be solved with a standard nonlinear optimization approach. Numerical examples illustrate the validity, as well as the characteristic of optimal solutions, of the proposed method.

Existing studies often rely on deterministic numerical analyses for structural models. However, test results consistently highlight uncertainties, particularly in variables such as magnitude of the applied load, geometrical dimensions, material randomness, and limited experiential data. As a response, researchers have increasingly turned their attention to probabilistic design models, recognizing their crucial role in accurately predicting structural performance. This study aims to integrate reliability-based analysis into the numerical modeling of sinusoidal-web steel beams. Two sinusoidal-web beams are considered. The web and the flange thicknesses, in addition to the magnitude of the applied load, are treated as random variables with mean values and standard deviations. Notably, the study demonstrates the efficiency of the reliability index as a governing limit in the analysis process. A detailed comparison between deterministic and probabilistic designs of sinusoidal-web beams is conducted, focusing on the impact of introducing the nature of randomness. Therefore, this study's results deepen our understanding of how uncertainties significantly influence deformations and stresses. [ABSTRACT FROM AUTHOR]

Impact is the most important factor affecting the reliability of Micro-Electro-Mechanical System (MEMS) gyroscopes, therefore corresponding reliability design is very essential. This paper proposes a shock-protected structure (SPS) capable of withstanding a full temperature range from −40 °C to 80 °C to enhance the shock resistance of MEMS gyroscopes. Firstly, the shock transfer functions of the gyroscope and the SPS are derived using Single Degree-of-Freedom and Two Degree-of-Freedom models. The U-folded beam stiffness and maximum positive stress are deduced to evaluate the shock resistance of the silicon beam. Subsequently, the frequency responses of acceleration of the gyroscope and the SPS are simulated and analyzed in Matlab utilizing the theoretical models. Simulation results demonstrate that when the first-order natural frequency of the SPS is approximately one-fourth of the gyroscope's resonant frequency, the impact protection effect is best, and the SPS does not affect the original performance of the gyroscope. The acceleration peak of the MEMS gyroscope is reduced by approximately 23.5 dB when equipped with the SPS in comparison to its counterpart without the SPS. The anti-shock capability of the gyroscope with the SPS is enhanced by approximately 13 times over the full-temperature range. After the shock tests under the worst case, the gyroscope without the SPS experiences a beam fracture failure, while the performance of the gyroscope with the SPS remains normal, validating the effectiveness of the SPS in improving the shock reliability of MEMS gyroscopes. [ABSTRACT FROM AUTHOR]

The monitoring unit used in the nuclear magnetic resonance system, as an important unit of the system, faces a high thermal risk during its entire life cycle. This paper ensures the high efficiency and reliability of the thermal design of the product module from the two dimensions of structural design and device derating design. In order to reduce the risk of thermal design of electronic modules and comprehensively verify the effectiveness of thermal design of electronic modules, the design verification is carried out by combining simulation and experiment. In the simulation process, by establishing a thermal simulation model at the circuit board level, the crustal temperature of the core device is numerically calculated, and the index is compared with the thermal design index value and the test value, on the one hand, to verify the correctness of the simulation model. On the other hand, the validity of thermal design is verified. In the testing process, a thermal test platform for product modules is built, and the thermal characteristics test values of the core components of the module under extreme electrical conditions are obtained, and the corresponding conversion methods are used to predict the thermal performance and thermal design margin of the product at different altitudes. The results show that the electronic module can meet the thermal design requirements in terms of structural design and derating design of core components, and can ensure that the product module can work safely and reliably during the entire life cycle of the NMR system.

Reclaimed asphalt pavement (RAP) applications are largely limited by the insufficient performance of reclaimed asphalt (RA). To address this challenge, the composite crumb rubber-modified asphalt (CCRMA) with SBS and SBR modifiers was mixed with RA to prepare reconciling and reclaimed modified asphalt (RRMA) and evaluate its performance in laboratory tests. Experimental groups of RRMA included five RA contents (30%, 40%, 50%, 60%, and 70%) and three aging degrees. Results showed that RRMA's high-temperature and fatigue resistance performances improved by adding CCRMA, while this improvement was weakened with increasing RA content and aging degree. This was because the addition of CCRMA reduced the morphology of 'bee-like structures' and improved resistance to deformation. CCRMA slightly reduced moderate-temperature crack resistance but still improved low-temperature crack resistance because adding CCRMA reduced the internal adhesion of asphalt. The moderate-temperature crack resistance was below the threshold. However, it is necessary to consider adding other technical means when RRMA was aged for more than 20 hours with more than 60% RA content. Furthermore, the reliability of excellent performance was 85% for RRMA with 30% RA content under a short-term aging state, which provided a reference for the design of reclaimed asphalt binder. [ABSTRACT FROM AUTHOR]

The application of reclaimed asphalt pavement (RAP) can help reduce resource waste and environmental pollution in road construction. However, so far, only a small percentage of RAP materials can be used in road construction. The key obstacles to the application of a recycled asphalt mixture (RAM) with high RAP content are the variability of RAP materials and the difficulty of fully rejuvenating aged asphalt. However, there is still a lack of research on the effect of the variability of RAP materials and recycled asphalt on the quality control of a RAM. Therefore, this study investigates the effects of sieve pretreatment of RAP material using 4.75 mm sieve mesh and the use of composite crumb rubber-modified asphalt (CCRMA) to reclaim aged asphalt on the road performance and frame variability of reclaimed asphalt mixtures. Therefore, this study investigates the effects of the fractionation process of RAP material using 4.75 mm sieve mesh and the use of CCRMA to reclaim aged asphalt on the road performance of a RAM. The results show that the fractionation process can effectively reduce the mitigation of RAP agglomeration and reduce the variability of gradation, which in turn reduces the variability of road performance. The incorporation of CCRMA can effectively improve the high-temperature stability performance and low-temperature cracking resistance. The dynamic stability and the fracture energy of the CRAM (RAM prepared using CCRMA) were four and one and a half times as large as that of the NAM (RAM prepared using base asphalt), respectively. The fractionation process of RAP material and the utilization of CCRMA could help reduce the variability of the RAM while improving the road performance of the RAM. [ABSTRACT FROM AUTHOR]

A modular multilevel converter (MMC) synthesizes output voltages by combining voltages from various submodules (SMs) connected in series; thus, it is ideal for high-voltage transmission and distribution ranging from tens to several hundreds of kilovolts. However, MMCs incur high costs and losses, thus necessitating reliable operation. Research has been conducted to assess and enhance MMC reliability. Prior studies have presumed an exponential distribution for the reliability of SMs, including redundancy, thus implying that the failure rate does not change over time. This assumption signifies a constant system availability for the converter station, regardless of time, thus presenting a limitation in adequately comprehending the breakdown impact caused by a failure of the converter station. Additionally, as no standard exists for determining redundancy in medium-voltage direct current (MVDC) systems, a methodology is required to establish a redundancy criterion during the design process. Particularly for MVDC systems, the impact of power outages must be evaluated by considering the cost of expected outages based on system availability, as the load is interconnected. As a solution, we propose a method to assess the tradeoff between system availability and cost for an MVDC MMC, employing the Weibull distribution-based SM failure rate. The L-BFGS algorithm calculates the optimal value of the availability-cost function, and the number of redundant modules minimizing total operating cost is evaluated. Our case study determines the appropriate number of redundancy modules based on outage costs. The proposed methodology enables redundancy design that considers both reliability and operational costs, thus providing a practical solution to the problem of determining the number of redundant modules needed in MMCs.

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Existing studies often rely on deterministic numerical analyses for structural models. However, test results consistently highlight uncertainties, particularly in variables such as magnitude of the applied load, geometrical dimensions, material randomness, and limited experiential data. As a response, researchers have increasingly turned their attention to probabilistic design models, recognizing their crucial role in accurately predicting structural performance. This study aims to integrate reliability-based analysis into the numerical modeling of sinusoidal-web steel beams. Two sinusoidal-web beams are considered. The web and the flange thicknesses, in addition to the magnitude of the applied load, are treated as random variables with mean values and standard deviations. Notably, the study demonstrates the efficiency of the reliability index as a governing limit in the analysis process. A detailed comparison between deterministic and probabilistic designs of sinusoidal-web beams is conducted, focusing on the impact of introducing the nature of randomness. Therefore, this study’s results deepen our understanding of how uncertainties significantly influence deformations and stresses.

Recently, a mixed redundancy was introduced among the redundant design strategies to achieve a more reliable system within the equivalent resources. This study deals with a lifetime distribution for a mixed redundant system with an imperfect fault detector/switch. The lifetime distribution model was formulated using a structured continuous Markov chain (CTMC) and considers the time-to-failure (TTF) distribution of a component as a phase-type distribution (PHD). The model’s versatility and practicality are enhanced because the PHD can represent diverse degradation patterns of the components exposed to varied operating environments. The model provides accurate reliability for a mixed redundant system by advancing the approximate reliability function suggested in previous studies. Furthermore, the model would be useful in system design and management because it provides information such as the nth moment of the system’s lifetime distribution. In numerical experiments on some examples, the mixed redundancy was confirmed to devise a more reliable system than the existing active and standby redundancies, and the improvement effect increased as the number of redundant components decreased. The optimal structure for maximizing the expected lifetime of the system changes depends on the reliability of the components and fault detector/switch.

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Propose a strategy for reducing random variables in Karhunen-Loève expansion. • Validate performance of Kriging-Monte Carlo Simulation in calculating random capacity. • Conduct reliability analysis and design of multi-line dynamically installed anchor. A novel multi-line dynamically installed anchor was previously proposed by the authors to allow for the mooring of multiple floating offshore wind turbine, resulting in a significant reduction in the total number and cost of anchors required for floating wind farms. Considering the spatial variability of soil properties and the uncertainty of environmental loads, the present study performs reliability analysis and design of the multi-line dynamically installed anchor. Firstly, a strategy to repeatedly use fundamental random variables is proposed and validated for reducing the number of random variables used in Karhunen-Loève expansion in the simulation of random field of soil properties when the ratio of the soil domain dimension to the scale of fluctuation is large. Then, the efficiency, accuracy, and robustness of the RFEM (random finite element method) combined with K-MCS (Kriging model and Monte Carlo simulation) based on the proposed strategy are validated through examples of random capacity of foundations. Next, the random capacities and probabilistic VHMT failure envelopes of the multi-line dynamically installed anchor in spatially variable soil are investigated. Finally, the reliability design of multi-line dynamically installed anchors is conducted and compared with that of multi-line pile anchors, in which both the spatial variability of soil and the uncertainty of loads are condidered. The results show that the costs for multi-line dynamically installed anchors are obviously less than those of multi-line pile anchors. [ABSTRACT FROM AUTHOR]

Impact is the most important factor affecting the reliability of Micro-Electro-Mechanical System (MEMS) gyroscopes, therefore corresponding reliability design is very essential. This paper proposes a shock-protected structure (SPS) capable of withstanding a full temperature range from −40 °C to 80 °C to enhance the shock resistance of MEMS gyroscopes. Firstly, the shock transfer functions of the gyroscope and the SPS are derived using Single Degree-of-Freedom and Two Degree-of-Freedom models. The U-folded beam stiffness and maximum positive stress are deduced to evaluate the shock resistance of the silicon beam. Subsequently, the frequency responses of acceleration of the gyroscope and the SPS are simulated and analyzed in Matlab utilizing the theoretical models. Simulation results demonstrate that when the first-order natural frequency of the SPS is approximately one-fourth of the gyroscope’s resonant frequency, the impact protection effect is best, and the SPS does not affect the original performance of the gyroscope. The acceleration peak of the MEMS gyroscope is reduced by approximately 23.5 dB when equipped with the SPS in comparison to its counterpart without the SPS. The anti-shock capability of the gyroscope with the SPS is enhanced by approximately 13 times over the full-temperature range. After the shock tests under the worst case, the gyroscope without the SPS experiences a beam fracture failure, while the performance of the gyroscope with the SPS remains normal, validating the effectiveness of the SPS in improving the shock reliability of MEMS gyroscopes.

The application of reclaimed asphalt pavement (RAP) can help reduce resource waste and environmental pollution in road construction. However, so far, only a small percentage of RAP materials can be used in road construction. The key obstacles to the application of a recycled asphalt mixture (RAM) with high RAP content are the variability of RAP materials and the difficulty of fully rejuvenating aged asphalt. However, there is still a lack of research on the effect of the variability of RAP materials and recycled asphalt on the quality control of a RAM. Therefore, this study investigates the effects of sieve pretreatment of RAP material using 4.75 mm sieve mesh and the use of composite crumb rubber-modified asphalt (CCRMA) to reclaim aged asphalt on the road performance and frame variability of reclaimed asphalt mixtures. Therefore, this study investigates the effects of the fractionation process of RAP material using 4.75 mm sieve mesh and the use of CCRMA to reclaim aged asphalt on the road performance of a RAM. The results show that the fractionation process can effectively reduce the mitigation of RAP agglomeration and reduce the variability of gradation, which in turn reduces the variability of road performance. The incorporation of CCRMA can effectively improve the high-temperature stability performance and low-temperature cracking resistance. The dynamic stability and the fracture energy of the CRAM (RAM prepared using CCRMA) were four and one and a half times as large as that of the NAM (RAM prepared using base asphalt), respectively. The fractionation process of RAP material and the utilization of CCRMA could help reduce the variability of the RAM while improving the road performance of the RAM.

• VSM method is developed for the failure approximation of multi-objective reliability analysis. • VSM can synchronously approximate to many limit state functions of reliability problems. • Reliability design of turbine blisk with multi-failure modes is conducted to illustrate VSM. • VSM method holds superior accuracy, capability and efficiency in reliability modeling and simulations. To improve the computational cost and accuracy for the multi-objective reliability design of complex structures, a synchronous modeling concept is proposed by introducing matrix thought into the surrogate modeling methods, the purpose of which is to realize the transformation from single-objective reliability design to comprehensive (multiple objectives) reliability design. With respect to the synchronous modeling concept, vectorial surrogate modeling (VSM) method is developed to synchronously establish an overall model of complex structures with multiple objectives. Besides, the types of examples including a numerical example and four engineering cases are adopted to highlight the abilities of the developed VSM method in accuracy, computational efforts and capability. It is illustrated that (1) the developed VSM method is workable in the synchronous modeling and comprehensive reliability design of complex structures with many objectives; (2) the proposed VSM method has the superior performances in both computational efficiency and accuracy for high-dimensional nonlinear problems, by comparison of methods; (3) By comparing with the analytical approaches, the efficient results based on computational times and elevating the performance are provided using the proposed method for highly nonlinear problems; (4) the comprehensive reliability level of turbine blisk deformation, stress and strain is 0.9974 obtained by the VSM method, by considering the effect of fluid-thermal-structural interaction, when the allowable values are 4.3698 × 10−3 m, 1.0389 × 109 Pa and 6.4298 × 10−3 m/m (determined by 3-sigma level); (5) the modeling and simulation efficiencies of the VSM method are improved by 42.56% and 0.31% relative to the RSM. The VSM method are validated to hold high accuracy and high efficiency in modeling characteristics and simulation performance of high-dimensional structural reliability problems. The efforts of this study are to provide a promising synchronous modeling concept and methodology with the VSM method for the multi-objective reliability design of complex systems, which contributes to enrich mechanical reliability theory. [ABSTRACT FROM AUTHOR]

This numerical research reports results related to the implementation of innovative materials such as composite materials to a lifting apparatus and in particular a classic jib crane with a capacity of 500 kg. The work involves an initial analytical dimensioning followed by verifications conducted by finite element analysis. The parameters adopted are maximum displacement, safety coefficient with respect to maximum stress and with respect to buckling phenomena for both the boom and column. The materials assumed are classical steel, aluminum and composite materials with carbon and glass fibers. The performance in terms of stiffness and safety of the crane designed with the new materials should be very similar to that of the crane designed in steel. The last part of the research concerns the design of the crane by adopting probabilistic methods. It is clear from the results that the crane made of composite material and especially with carbon fibers has the lowest weight i.e., about 20% of the weight of the corresponding steel crane. In terms of reliability, assuming defined values in the dispersions, the different solutions are comparable.

As the feature size of integrated circuits decreases to the nanometer scale, process fluctuations, aging effects, and particle radiation have an increasing influence on the Failure Probability of Circuits (FPC), which brings severe challenges to chip reliability. The accurate and efficient estimation of logic circuit failure probability is a prerequisite for high-reliability design. It is difficult to calculate FPC due to a large number of reconvergent fanout structures and the resulting signal correlation, particularly for Very Large-Scale Integrated (VLSI) circuits. Accordingly, this paper presents a Correlation Separation Approach (COSEA) that aims to efficiently and accurately estimate the FPC. The proposed COSEA divides the circuit into several different fanout-relevant and fanout-irrelevant circuits. Moreover, the error probability of the nodes is expressed as the result of interactions between different structures. As a result, the problem of signal correlation can be efficiently solved. Because the computational complexity of COSEA is linearly related to the scale of the circuit, it has good scalability. Compared with the Probabilistic Transfer Matrices (PTM) method, Monte Carlo simulation (MC), and other failure probability calculation methods in the literatures, the experimental results show that our approach not only achieves fast speed and good scalability, but also maintains high accuracy. [ABSTRACT FROM AUTHOR]

Components that are vulnerable to the external environment and harsh working conditions easily fail during their life cycle under variable loads of offshore oil and gas equipment. The reliability of the system in the life cycle is reduced, various risks are increased, and substantial maintenance costs are generated. However, the current reliability-based design optimization method has difficulty meeting the situation that the life cycle is taken as the time dimension of design considering reliability, risk, and maintenance. To solve the problem, a life cycle integrity design optimization method considering robustness is proposed. A simplified integrity model is established through random load sampling and global sensitivity analysis. A multiobjective particle swam hierarchical optimization algorithm is proposed, in which hierarchical optimization order is determined by the priority of objectives, and the optimization design with structural integrity as the optimization objective is completed. The method is applied in the design of pressure pipeline of all-electric surface-controlled subsurface safety valve system. • A life cycle integrity design framework of offshore oil and gas equipment is proposed. • Reliability, risk control and maintenance economy are integrated. • A multi-objective particle swarm hierarchical optimization algorithm is proposed. [ABSTRACT FROM AUTHOR]

Automotive powertrain mounting systems (PMSs) may exhibit hybrid interval-random (HIR) uncertainties in engineering practice. In HIR case, the uncertain parameters of PMSs are characterized as the random variables with interval distributions. A comprehensive methodology is proposed for the design optimization of the PMSs involving HIR uncertainties in this study. The hybrid interval-random perturbation central difference method (HIRP-CDM) is firstly derived to calculate the uncertain responses of PMSs, in which HIR uncertainties are addressed by twice perturbation analyses and twice central difference analyses. Meanwhile, the hybrid interval-random Monte Carlo method is presented as a reference method. Then, reliability assessment models are constructed to evaluate the probability intervals of system inherent characteristics satisfying design requirements. Next, a design optimization model is formulated to explore the optimal design of PMSs. The expectation intervals and variance intervals of system inherent characteristics are taken to create optimization objective, and the minimal probabilities of system inherent characteristics meeting requirements are utilized to establish reliability constraints. Both robustness and reliability are considered in the optimization, and the optimization can be simplified with the aid of HIRP-CDM. The effectiveness of the proposed methodology is finally demonstrated by the numerical example. [ABSTRACT FROM AUTHOR]

Firstly,the concept of random events was introduced into the communication process,and the serial and parallel reliability algorithms were introduced.Secondly,the reliability design of virtual hosts,clusters and spine-leaf switching networks and their calculation methods were analyzed.Finally,the connection based on each component unit was analyzed.Based on the connection relationships among the components,the reliability design scheme of virtual nodes and its reliability algorithm was proposed.

Many current applications of maneuver design to astrodynamics consider a deterministic case, where statistics or uncertainty is left unquantified. When including constraints based on the probability of collision, any solution must be robust to the uncertainty of the system. This paper considers the methodology of separated representations for orbit uncertainty propagation and its subsequent application to a reliability design formulation of the maneuver design problem. Separated representations is a polynomial surrogate method that has been shown to be both efficient at propagating uncertainty when considering high stochastic dimension and accurate over long propagation times. This efficiency is leveraged to improve tractability when solving the reliability design problem using optimization under uncertainty. Two sequential, potential collisions are considered in the results of this paper, with one object able to maneuver. The optimization problem therefore seeks to avoid both collisions. The probability of each collision is estimated via large numbers of samples propagated via the separated representation. The accuracy of the surrogates is compared to that of a Monte Carlo reference, and the variability of the estimated probabilities of collision is analyzed. [ABSTRACT FROM AUTHOR]

The mechanical interface has the characteristics of low shock and vibration, and is emphasized in the aerospace and ocean engineering fields. In this paper, a mechanical interface based on coupled cylindrical cam mechanisms is designed. It can achieve the expected functions, but there exist faults in some times. The fault modes and causes of the interface are firstly analyzed. Then a design approach based on Monte Carlo simulation is presented for analyzing and optimizing its reliability. According to the fault modes, the performance functions of the interface are established for obtaining the optimal scheme. A case is given to illustrate the proposed method. The simulation results and the prototype experiments prove that the optimization scheme effectively improves the reliability of the interface, and has better performance than the original one. [ABSTRACT FROM AUTHOR]

This paper presents a joint optimization approach of reliability design (RD) and level of repair analysis (LORA) for fleet systems. A fleet is a multi-machine, multi-indenture system. The present paper investigates the interrelated effect of product design in terms of modularity and inherent reliability with maintenance repair strategy. It proposes a joint approach for the configured fleet system design of reliability and repair decisions at the initial design phase considering the time dependent failure rate of components. The consequences of each design options and level of repair decisions are evaluated based on life cycle cost performance. Additionally, the failure of the machine is modeled using time dependent failure rate models at the part level of the indenture. The methodology integrates many interdependent maintenance decisions such as location of maintenance, type of maintenance (repair/replacement/discard), and indenture level at which maintenance should be performed. The time dependent failure rate of components provides flexibility to consider the effect of practical behavior on the overall fleet level maintenance methodology. This makes the fleet methodology more realistic in terms of optimizing the reliability design and maintenance repair decisions (LORA). This joint problem is the complex combinatorial type problem. To obtain appropriate integrated and disintegrated results for fleet system design and level of repair decisions, genetic algorithm (GA)-based Monte Carlo simulation is used. [ABSTRACT FROM AUTHOR]

Extensive electrification of ship power systems appears to be a promising measure to meet stringent environmental requirements. The concept is to enable ship power management to allocate loads in response to load variations in an optimal manner. From a broader design perspective, the reliability of machinery operation is also of importance, especially with regard to the failure cost from power outages. In this paper, an approach for determining optimal power plants based on economic and environmental perspectives across several architecture choices is proposed. The design procedure involves the implementation of metaheuristic optimization to minimize fuel consumption and emissions released, while maintenance and repair services can be extracted using reliability assessment tools. The simulation results demonstrated that ship power management using the whale optimization algorithm (WOA) was able to reduce fuel consumption and corresponding emissions in a range from 4.04–8.86%, varying with the profiles, by eliminating inefficient working generators and distributing loads for the rest to the nearest possible energy-saving areas. There was also a trade-off between maintenance service and overall system expenses. Finally, a compromise solution was sought with the proposed holistic design for contradictory cost components by taking into account fuel operation consumption, shore electricity supply, maintenance service and investment expenditure.

In order to solve the problem of single drive function and poor reliability of the existing hydraulic press, in this research, the hydraulic drive system of the mechanical arm of the logger is studied. Firstly, according to the reliability theory, the reliability model of the hydraulic drive system is established. Then, the influence and danger of the fault mode of the hydraulic system are analyzed. Finally, the reliability test is predicted, analyzed, and designed under high temperature and high pressure, and the environmental stress screening experiment and reliability development experiment are simulated. The results show that the hydraulic drive system of the mechanical arm of the logger, which can withstand high temperature and high pressure, is finally developed by taking relevant measures according to the problems exposed in the experiment. It is hoped that the results in this study can improve the measuring depth of the logger and have a good guiding significance for improving the oil exploration technology in China. [ABSTRACT FROM AUTHOR]

Highlights • MINLP model that represents the stochastic process of system failures and repairs as a continuous-time Markov chain. • Model optimizes the selection of redundancy and the frequency of inspection and maintenance tasks for maximum profit. • Effective decomposition and scenario reduction methods are also proposed t handle large number of states. • Proposed model applied to small and medium scale examples, as well as to air separation process. Abstract This paper proposes an MINLP model that represents the stochastic process of system failures and repairs as a continuous-time Markov chain, based on which it optimizes the selection of redundancy and the frequency of inspection and maintenance tasks for maximum profit. The model explicitly accounts for every possible state of the system. Effective decomposition and scenario reduction methods are also proposed. A small example with two processing stage is solved to demonstrate the impact of incorporating maintenance considerations. A decomposition method and a scenario reduction method are applied to this example and are shown to drastically reduce the computational effort. A larger example with four stages, which is not directly solvable, is also successfully solved using the proposed algorithm. Lastly, we show that the proposed model and algorithms are capable of solving a practical problem based on the air separation process example that motivated our work, which features multiple stages, potential units and failure modes. [ABSTRACT FROM AUTHOR]

Abstract To improve the reliability of mechanical systems with inherited faulty designs, a reliability methodology utilizing parametric accelerated life testing (ALT) is suggested. It consists of: 1) a parametric ALT plan, 2) a load analysis, 3) a tailored series of parametric ALTs with action plans, and 4) an evaluation of the final designs to ensure the design requirements are satisfied. This parametric ALT should help an engineer uncover the design parameters affecting reliability during the design process of a mechanical system. As a case study, the hinge kit system (HKS) of a door in a refrigerator was redesigned to improve its reliability. Using a force and moment balance analysis, the mechanical impact loads in closing the door of the HKS were calculated. During the first ALT, the kit housing in the HKS fractured and the oil damper leaked when the HKS failed. The faults in the design of the HKS included the weakness of the housing hinge kit and the oil sealing structure of the oil damper. In the second ALT, the hinge cover fractured due to the impact of the damper support. The material in the hinge cover in the HKS was changed from plastic to aluminum. After three rounds of parametric ALTs, the reliability of the new HKS was guaranteed to be a 10 year life with an accumulated failure rate of 1%. Highlights • This papers discussed on parameter ALT that can improve the reliability of mechanical systems subjected to repetitive stresses. • It utilizes a generalized life-stress failure model with effort concepts, acceleration factor, and sample size equation. • Therefore, it can quickly discover the faulty designs of the mechanical system - automobile, refrigerator, appliance, and construction machine. • As a test case study, the hinge kit system (HKS) of a door in a refrigerator was studied to improve its design. [ABSTRACT FROM AUTHOR]