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Статті в журналах з теми "ELEMENT RELIABILITY"

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Автор: Grafiati

Опубліковано: 11 вересня 2023

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1

Koduru, Smitha D., and Terje Haukaas. "Uncertain reliability index in finite element reliability analysis." International Journal of Reliability and Safety 1, no. 1/2 (2006): 77. http://dx.doi.org/10.1504/ijrs.2006.010691.

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2

Sharifi, Mani, Ehsan Hashemi, and Peyman Farahpour. "Real Time Reliability Study of a Model with Increasing Failure Rates." Applied Mechanics and Materials 110-116 (October 2011): 2774–79. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2774.

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This paper deals with a system with elements with one element is the main element and the other elements are the spare parts of the main element. If one element fails, one of the spare parts starts working immediately. The failure rate of non working elements are zero and the failure rate of working element is time dependent as and the failed elements are not repairable. The system works until all elements failed. In the second part of this paper the differential equations between the state of the system are established and by solving this equation the reliability function of the system () is calculated. In the third part, a numerical example solved to determine the parameters of the system. Nomenclature The notations used in this paper are as follows: : Number of elements, : Failure rate of each element at time, : Probability that the system is in state with spare element at time, : Probability that system works at time, : Mean time to failure of the system,

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3

Chen, Gang, and Xu Chen. "Finite element analysis of fleXBGA reliability." Soldering & Surface Mount Technology 18, no. 2 (April 2006): 46–53. http://dx.doi.org/10.1108/09540910610665134.

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4

Der Kiureghian, Armen, and Yan Zhang. "Space-variant finite element reliability analysis." Computer Methods in Applied Mechanics and Engineering 168, no. 1-4 (January 1999): 173–83. http://dx.doi.org/10.1016/s0045-7825(98)00139-x.

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5

Szabó, B. A. "On reliability in finite element computations." Computers & Structures 39, no. 6 (January 1991): 729–34. http://dx.doi.org/10.1016/0045-7949(91)90216-9.

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6

MacNeal, Richard H. "The reliability of finite element tools." Finite Elements in Analysis and Design 2, no. 3 (October 1986): 249–57. http://dx.doi.org/10.1016/0168-874x(86)90029-6.

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7

Sudret, Bruno, and Armen Der Kiureghian. "Comparison of finite element reliability methods." Probabilistic Engineering Mechanics 17, no. 4 (October 2002): 337–48. http://dx.doi.org/10.1016/s0266-8920(02)00031-0.

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8

Followell, David, Salvatore Liguore, Rigo Perez, W. Yates, and William Bocchi. "Computer-Aided Reliability Finite Element Methods." Journal of the IEST 34, no. 5 (September 1, 1991): 46–52. http://dx.doi.org/10.17764/jiet.2.34.5.9720337614871186.

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Анотація:

Finite element analyses (FEA) have emerged as a process for assessing stresses and strains in electronic equipment in order to compute the expected structural life. However, potential pitfalls may compromise accuracy. Guidelines have been established to improve the accuracy of these results. A method has been outlined that allows simplified linear FEAs to be used instead of the more complex elastic-plastic nonlinear FEA. Guidelines for mesh generation have been established to eliminate arithmetic errors caused when materials with large stiffness differences are adjacent to each other. The accuracy of FEAs when dealing with very small dimensions has been verified. Procedures for combining various loadings in order to predict life have been established for materials that exhibit stress relaxation and for those that do not. With these guidelines, FEAs can be an effective tool to predict the structural life of electronic equipment.

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9

Volkov, Vladimir S. "Improving the reliability of transport vehicles based on element-by-element analysis." Nexo Revista Científica 34, no. 01 (April 15, 2021): 514–33. http://dx.doi.org/10.5377/nexo.v34i01.11328.

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The author considers two approaches to solving the problem of increasing the reliability of machine-building products: on the spot, at the enterprises that operate transport vehicles, via certain modifications of serial products, and at manufacturing sites, during production of subsequent products, via improving the design on the basis of operation data of the analogues. In this case, data collection and processing system should provide reliable data on failures and cases of non-serviceable condition of the machines operating under different conditions; prompt processing of statistical data and presentation of results in the most convenient form; registration and coordination of reliability improvement measures taken by developers, manufacturers and operators. The author analyzes the operation of distribution laws of random variables and the variety of their corresponding calculation systems for the determination of the product's reliability indices in an element-by-element, unit-wise, as well as synthesized form. This approach makes it possible to search for the least reliable elements of a system in order to align the machine's reliability indices. Purpose. Creation of a design system for determining reliability indices in a separate form at the levels of parts, units and for the machine as a whole for identifying its least reliable components for the purpose of their further improvement. Methods. The methodology is based on drawing up a structural chart of machine reliability and a consolidated list of failures that are identified during its operation. The reliability structural scheme includes all the machine elements. A summary cumulative list is compiled further, where data on the operating time of each object are recorded for each failure type. The data samples on the times to failure of a group of homogeneous components are output from the summary cumulative list per each element. Results. The methodology makes it possible to create a system with multiple ratios of reliability indices per components, as well as reduce expenses for service impacts and improve the effectiveness of their transportation work. The present research work contributes to the theory of predicting the reliability of mechanical systems, making it possible to solve important tasks at modernization and design stages.

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10

Gong, Zheng Xi, and Jian Guo Yang. "Fuzzy Matter-Element Evaluation Method for Reliability Analysis of an Existing Highway Tunnel." Advanced Materials Research 163-167 (December 2010): 3110–13. http://dx.doi.org/10.4028/www.scientific.net/amr.163-167.3110.

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Reliability analysis is the premise for reinforcement and maintenance of an existing highway tunnel. In order to understand the structure reliability of an existing highway tunnel, a fuzzy mat-ter-element evaluation method was put forward based on entropy weight according to the fuzzy matter-element analysis method. Firstly, levels of inspection results were regarded as objects of matter-element and composite fuzzy matter-elements were constructed considering such factors and their evaluation indexes as cracks of concrete lining, lining thickness, concrete strength, cavities behind the lining and water leakage conditions. Secondly, reliability evaluation results of the existing tunnel structure were obtained by calculating the relevancy. Lastly, fuzzy matter-element evaluation model was effectively used to evaluate reliability of one highway tunnel structure.

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11

Gallimard, L. "Error bounds for the reliability index in finite element reliability analysis." International Journal for Numerical Methods in Engineering 87, no. 8 (February 1, 2011): 781–94. http://dx.doi.org/10.1002/nme.3136.

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12

Pavlov, I. V., and L. K. Gordeev. "Reliability Interval Estimation for a System Model with Element Duplication in Different Subsystems." Herald of the Bauman Moscow State Technical University. Series Natural Sciences, no. 5 (92) (October 2020): 4–13. http://dx.doi.org/10.18698/1812-3368-2020-5-4-13.

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Анотація:

The problem was considered of estimating reliability for a complex system model with element duplication of various subsystems and ensuring possibility of additional redundancy in a more flexible dynamic (or 'sliding') mode in each of the subsystems, which significantly increases reliability of the system in general. For the system considered, general model and analytical expressions were obtained in regard to the main reliability indicators, i.e., probability of the system failure-free operation (reliability function) for a given time and mean time of the system failure-free operation. On the basis of these analytical expressions, the lower confidence limit for the system reliability function was found in a situation, where the element reliability parameters were unknown, and only results of testing the system elements for reliability were provided. It was shown that the system resource function was convex in the reliability parameters vector of the system separate elements various types. Based on this, the lower confidence boundary construction for the system reliability function was reduced to the problem of finding the convex function extremum on a confidence set in the system element parameter space. In this case, labor consumption of the corresponding computational procedure increases linearly with an increase in the problem dimension. Numerical examples of calculating the lower confidence boundary for the system reliability function were provided

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13

An, Hai, Wei Guang An, and Yong Yi Zhang. "The Influence of Stiffness Decay on Fatigue Reliability of Truss System." Key Engineering Materials 385-387 (July 2008): 325–28. http://dx.doi.org/10.4028/www.scientific.net/kem.385-387.325.

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Physical properties of element are very complex under fatigue loads.The structural system consisted of elements is not a simple topological structure,which the change of its physical properties is more complex.In order to analyze quantitatively the structural stiffness reliability of different design life,it is important to establish the accurate formula of physical properties decrease. In this paper, the formula of elements’ elastic modulus decrease is deduced by using damage mechanics theory combining with the model of residual strength of element. Moreover, stiffness reliability index of controlling node of truss system is solved by applying the Stochastic Finite Element Method in different service life.

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14

Kun, Chen Chong, Liu Yan, Wang Zhao Jun, Zhao Ji Fang, and Wang Meng. "Simulation design of reliability improvement of metal hose for rocket engine." Journal of Physics: Conference Series 2256, no. 1 (April 1, 2022): 012002. http://dx.doi.org/10.1088/1742-6596/2256/1/012002.

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Abstract Facing the new challenges of high-density space launches in the later period, this paper studies the numerical simulation of the metal hose used in the new generation of launch vehicle models to improve the reliability of the metal hose. Through the calculation of bellows with different elements, it is found that the calculation results of shell element and solid element are similar, and the calculation efficiency of shell element is much higher than that of solid element. Finally, it is established that the SHELL181 is used for the finite element calculation of the bellows. Based on the stiffness equivalent theory, an equivalent model of the net sleeve with strands as the unit is established. Through the verification of finite element and experiment, this equivalent model can better simulate the linear stage of metal mesh sleeve under tension. Finally, the modeling method of metal hose simulation design is established.

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15

Ulbrich, Dariusz, Jaroslaw Selech, Jakub Kowalczyk, Jakub Jóźwiak, Karol Durczak, Leszek Gil, Daniel Pieniak, Marta Paczkowska, and Krzysztof Przystupa. "Reliability Analysis for Unrepairable Automotive Components." Materials 14, no. 22 (November 19, 2021): 7014. http://dx.doi.org/10.3390/ma14227014.

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Анотація:

The analysis of the reliability parameters of a technical object and the determination of the change in the reliability of the object over time, requires the knowledge of the functional characteristics and reliability parameters of the elements included in a system. On the basis of the failure data of the selected element of the object, in this case the vehicle, it is possible to determine the average working time to failure of the element and the appropriate form of distribution that characterizes the reliability and durability parameters of the tested element. The main purpose of the research presented in the article was to develop a method of assessing the reliability of an electronic component of a vehicle-a boot lid contactor. This paper also presents three possible methods of repairing the boot lid contactor (sealing the housing with adhesive with better way, replacing the element with a new one or the most time-consuming solution, changing the shape of the boot lid). The authors also decided to determine the reliability and cost parameters that will allow preventive replacement of this element. The tests were carried out on a fleet of 61 vehicles of the same model, but with different body structures. Contactor failures were reported in 41 cases, of which 29 were in the hatchback construction and 12 in the estate type. The analysis of the distribution selection for the tested part of the passenger car-the boot lid contactor-was performed using the Likelihood Value (LKV) test to determine the rank of distributions. Also the maximum likelihood (MLE) method was used to estimate the distribution parameters. The three-parameter Weibull distribution was the best-fitted distribution in both cases. It was clearly defined that one model of car with two different types of body have vastly different reliability characteristic. Based on the reliability characteristic and parameters, the appropriate preventive actions can be taken, minimizing the risk of damage, thus avoiding financial losses and guaranteeing an appropriate level of vehicle safety.

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16

Huang, Xi Yong, and M. H. Aliabadi. "A Boundary Element Method for Structural Reliability." Key Engineering Materials 627 (September 2014): 453–56. http://dx.doi.org/10.4028/www.scientific.net/kem.627.453.

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In this paper a sensitivity formulation using the Boundary Element Method (BEM) is presentedfor analysis of structural reliability problems. The sensitivity formulation is based on implicit differentiation method where the first and second order derivatives of the random variables are obtained directly by differentiation of the discretised boundary integral equation. The structural reliability is assessed using the Monte Carlo Method and FORM with BEM sensitivity parameters. A benchmark example is presented to demonstrate the accuracy and efficiency of the BEM for both Monte Carlo and Sensitivity based FORM approaches.

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17

Koval, D. O., and H. L. Floyd. "Human element factors affecting reliability and safety." IEEE Transactions on Industry Applications 34, no. 2 (1998): 406–14. http://dx.doi.org/10.1109/28.663487.

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18

Mohammadi,, Jamshid. "Reliability Assessment Using Stochastic Finite Element Analysis." Journal of Structural Engineering 127, no. 8 (August 2001): 976–77. http://dx.doi.org/10.1061/(asce)0733-9445(2001)127:8(976.2).

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19

Mo, Wen Hui. "Reliability Calculation and Perturbation Stochastic Finite Element." Applied Mechanics and Materials 155-156 (February 2012): 570–73. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.570.

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This paper proposes a method of calculating reliability using perturbation stochastic finite element. The mean and variance of the stress can be computed by the perturbation stochastic finite element. Computer program is used to generate samples of stress and strength. If the stress is greater than the strength, the structure will fail. The Monte Carlo simulation is proposed to compute structural reliability. Reliability calculation using the Monte Carlo simulation is developed. A numerical example demonstrates the proposed method is feasible.

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20

Tan, Xiao-hui, and Jian-guo Wang. "Finite element reliability analysis of slope stability." Journal of Zhejiang University-SCIENCE A 10, no. 5 (May 2009): 645–52. http://dx.doi.org/10.1631/jzus.a0820542.

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21

Frangopol, Dan M., Yong-Hak Lee, and Kaspar J. Willam. "Nonlinear Finite Element Reliability Analysis of Concrete." Journal of Engineering Mechanics 122, no. 12 (December 1996): 1174–82. http://dx.doi.org/10.1061/(asce)0733-9399(1996)122:12(1174).

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22

Harkness, H. H., T. Belytschko, and W. K. Liu. "Finite element reliability analysis of fatigue life." Nuclear Engineering and Design 133, no. 2 (March 1992): 209–24. http://dx.doi.org/10.1016/0029-5493(92)90181-t.

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23

Lee, J. C., and A. H. S. Ang. "Finite element fracture reliability of stochastic structures." Structural Engineering and Mechanics 3, no. 1 (January 25, 1995): 1–10. http://dx.doi.org/10.12989/sem.1995.3.1.001.

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24

Aldosary, Muhannad, Jinsheng Wang, and Chenfeng Li. "Structural reliability and stochastic finite element methods." Engineering Computations 35, no. 6 (August 6, 2018): 2165–214. http://dx.doi.org/10.1108/ec-04-2018-0157.

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Анотація:

Purpose This paper aims to provide a comprehensive review of uncertainty quantification methods supported by evidence-based comparison studies. Uncertainties are widely encountered in engineering practice, arising from such diverse sources as heterogeneity of materials, variability in measurement, lack of data and ambiguity in knowledge. Academia and industries have long been researching for uncertainty quantification (UQ) methods to quantitatively account for the effects of various input uncertainties on the system response. Despite the rich literature of relevant research, UQ is not an easy subject for novice researchers/practitioners, where many different methods and techniques coexist with inconsistent input/output requirements and analysis schemes. Design/methodology/approach This confusing status significantly hampers the research progress and practical application of UQ methods in engineering. In the context of engineering analysis, the research efforts of UQ are most focused in two largely separate research fields: structural reliability analysis (SRA) and stochastic finite element method (SFEM). This paper provides a state-of-the-art review of SRA and SFEM, covering both technology and application aspects. Moreover, unlike standard survey papers that focus primarily on description and explanation, a thorough and rigorous comparative study is performed to test all UQ methods reviewed in the paper on a common set of reprehensive examples. Findings Over 20 uncertainty quantification methods in the fields of structural reliability analysis and stochastic finite element methods are reviewed and rigorously tested on carefully designed numerical examples. They include FORM/SORM, importance sampling, subset simulation, response surface method, surrogate methods, polynomial chaos expansion, perturbation method, stochastic collocation method, etc. The review and comparison tests comment and conclude not only on accuracy and efficiency of each method but also their applicability in different types of uncertainty propagation problems. Originality/value The research fields of structural reliability analysis and stochastic finite element methods have largely been developed separately, although both tackle uncertainty quantification in engineering problems. For the first time, all major uncertainty quantification methods in both fields are reviewed and rigorously tested on a common set of examples. Critical opinions and concluding remarks are drawn from the rigorous comparative study, providing objective evidence-based information for further research and practical applications.

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25

Gladilin, Valeriy, Tatiana Siroshtan, Irina Gamalij, Nataliia Shudra, and Petro Chulanov. "CONSTRUCTION OF GEODESIC NETWORKS ON THE BASIS OF THE THEORY OF MARKOV ACCIDENTAL PROCESSES AND THE THEORY OF RELIABILITY." Urban development and spatial planning, no. 80 (May 30, 2022): 115–30. http://dx.doi.org/10.32347/2076-815x.2022.80.115-130.

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Анотація:

As mentioned above, the theory of reliability was mainly developed for technical devices. However, nowadays it is widely used in construction, and is also beginning to be used in geodesy. By abstracting its position can be successfully transferred to systems that do not seem to be in a dynamic state. Take, for example, the polygon metric network in the city. It would seem that such a network is in a static state, but over time it undergoes changes, ie it is in subtle dynamics and its reliability is gradually declining. Reliability in the broadest sense of the word means the ability of a technical device (system, network) to uninterrupted (trouble-free) operation for a specified period of time under certain conditions. This period of time is usually due to the time of a task. Which is carried out by a device or system and is part of the overall operational task. Currently, the problem of reliability is becoming one of the key problems of technology and management. Ensuring the reliable operation of all elements of the system is of paramount importance. Improving reliability requires special study and quantitative analysis of the phenomena associated with accidental failures of devices or systems. At this time, the theory of reliability has become a special science that makes extensive use of probable methods of examination. In the theory of reliability there are two types of failures: sudden and gradual. Consider sudden failures. Sudden device failures are understood as an instantaneous failure, which means that it cannot be used, and these failures occur at some random point in time. The reliability of the system depends on the composition and number of elements included in it, on the type of integration into the system and on the characteristics of each individual element. An element is to be understood as any device that is not subject to further disconnection, the reliability of which is specified or determined experimentally. By assembling such elements in different ways into systems, we will solve the problem of determining the reliability of the system depending on the reliability of its elements. The reliability of elements and systems is determined by numerical characteristics. We give some definitions of these characteristics for the element and the system as a whole. The reliability of the element is the probability that the element in certain conditions will work flawlessly over time, its probability is denoted. With increasing time, reliability usually decreases; with probability. In the geodetic literature, the term "reliability" is often used, which means the accuracy of the obtained results of geodetic measurements. However, the reliability of a geodetic sign or network as a whole, from the point of view of reliability theory should be considered, for example, the ability of a sign or network to survive on the ground without changing location (without changing spatial coordinates) for a given period of time under certain conditions. In other words, the reliability of a geodetic sign or network as a whole is the probability that the sign or network in these conditions will fail to "work" until the end of a given time.

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26

Kumar, Akshay, and S. B. Singh. "Signature reliability of linear multi-state sliding window system." International Journal of Quality & Reliability Management 35, no. 10 (November 29, 2018): 2403–13. http://dx.doi.org/10.1108/ijqrm-04-2017-0083.

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Purpose The purpose of this paper is to deal with a linear multi-state sliding window coherent system which generalizes the consecutive k-out-of-r-from-n:F system in the multi-state case. The system has n linearly ordered multi-state elements consisting of m parallel independent and identically distributed elements. Every element of the system can have two states: completely working or totally failed. The system fails if the sum of performance rate is lower than the given weight. Design/methodology/approach The authors proposed to compute the signature, MTTF and Barlow–Proschan index with the help of UGF technique of multi-state SWS which consists of m parallel i.i.d. components in each multi-state window. Findings In the present study, the authors have evaluated the signature reliability, expected lifetime, cost analysis and Barlow–Proschan index. Originality/value In this study, the authors have studied a linear multi-state sliding window system which consists of n ordered multi-state element, and each multi-state element also consists of m parallel windows. The focus of the present paper is to evaluate reliability metrices of the considered system with the help of signature from using the universal generating function.

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27

Yusmye, A. Y. N., B. Y. Goh, and A. K. Ariffin. "Structural Reliability Analysis Using Fuzzy Finite Element Method." Applied Mechanics and Materials 471 (December 2013): 306–12. http://dx.doi.org/10.4028/www.scientific.net/amm.471.306.

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The main requirement in designing a structure is to ensure the structure is reliable enough to withstand loading and the reliability study of structure. Classical and probability approach was introduced to analyse structural reliability. However, the approaches stated above are unable to take into account and counter the uncertainties arising from the natural of geometry, material properties and loading. This leads to the reduction in accuracy of the result. The goal of this study is to assess and determine the reliability of structures by taking into consideration of the epistemic uncertainties involved. Since it is crucial to develop an effective approach to model the epistemic uncertainties, the fuzzy set theory is proposed to deal with this problem. The fuzzy finite element method (FFEM) reliability analysis conducted has shown this method produces more conservative results compared to the deterministic and classical method espacially when dealing with problems which have uncertainties in input parameters. In conclusion, fuzzy reliability analysis is a more suitable and practical method when dealing with structural reliability with epistemic uncertainties in structural reliability analysis and FFEM plays a main role in determining the structural reliability in reality.

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28

Ortiz, JO, German R. Betancur, J. Gómez, Leonel F. Castañeda, G. Zaja̧c, and RE Gutiérrez-Carvajal. "Detection of structural damage and estimation of reliability using a multidimensional monitoring approach." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 4 (May 11, 2017): 1021–32. http://dx.doi.org/10.1177/0954409717707122.

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Анотація:

Many structural elements are exposed to load conditions that are difficult to model during the design phase, such as environmental uncertainties, random impacts, and overloading, amongst others, thus increasing unprogrammed maintenance and reducing confidence in the reliability of the structure in question. One way to deal with this problem is to monitor the structural condition of the element. This approach requires supervising several signals coming from critical locations and then performing an accurate condition estimation of the element in question based on the data collected. This study implements a method to diagnose and evaluate the reliability of the bolster beam structure of the railway vehicle during a fatigue test. The results show that multidimensional monitoring not only diagnoses the element accurately but also results in correct estimation of reliability.

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29

LEVITIN, GREGORY. "OPTIMAL ALLOCATION OF MULTISTATE ELEMENTS IN LINEAR CONSECUTIVELY-CONNECTED SYSTEMS WITH DELAYS." International Journal of Reliability, Quality and Safety Engineering 09, no. 01 (March 2002): 89–108. http://dx.doi.org/10.1142/s0218539302000688.

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Анотація:

A linear consecutively-connected system consists of N + 2 linear ordered positions. The first position contains a source of a signal and the last one contains a receiver. M statistically independent multistate elements (retransmitters) with different characteristics are to be allocated at the N intermediate positions. The elements provide retransmission of the received signal to the next few positions. Each element can have different states determined by a number of positions that are reached by the signal generated by this element. The probability of each state for any given element depends on the position where it is allocated. The signal retransmission process is associated with delays. The system fails if the signal generated by the source can not reach the receiver within a specified time period. A problem of finding an allocation of the multistate elements that provides the maximal system reliability is formulated. An algorithm based on the universal generating function method is suggested for the system reliability determination. This algorithm can handle cases where any number of multistate elements are allocated in the same position while some positions remain empty. It is shown that such an uneven allocation can provide greater system reliability than an even one. A genetic algorithm is used as an optimization tool in order to solve the optimal element allocation problem.

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30

Pei, Yanhu, Zhifeng Liu, Jingjing Xu, Baobao Qi, and Qiang Cheng. "Grouping Preventive Maintenance Strategy of Flexible Manufacturing Systems and Its Optimization Based on Reliability and Cost." Machines 11, no. 1 (January 6, 2023): 74. http://dx.doi.org/10.3390/machines11010074.

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A flexible manufacturing system (FMS) improves productivity and makes it more efficient. Maintaining reliability levels and reducing costs through proper maintenance strategies are key problems for the development and application of a FMS. This paper proposes a grouping preventive maintenance strategy of a FMS with optimized parameters by considering both reliability and cost. In this work, a three-layer evaluation index system is first presented to accurately estimate the reliability of the FMS; index weights of each layer were obtained by reliability importance modeling and analysis, considering maintenance strategies. An element-grouping preventive strategy is proposed based on an influencing analysis, and a parameter optimization problem (considering reliability and maintenance costs) was established. In this strategy, three maintenance methods are presented for the elements, including low-level maintenance with a large period, low-level maintenance with a small period, as well as the combination of low-level maintenance with a small period and high-level maintenance with a large period; the effects of reliability improvement of the elements on the subsystem’s reliability were analyzed to provide evidence for element grouping. Finally, the proposed method was applied to a box-part finishing FMS; the results indicate that this method can effectively reduce maintenance costs on the premise of satisfying the reliability requirements.

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31

Kotes, Peter, and Josef Vican. "Mutli-element system reliability using markov chain model." Communications - Scientific letters of the University of Zilina 6, no. 3 (September 30, 2004): 17–21. http://dx.doi.org/10.26552/com.c.2004.3.17-21.

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32

Mo, Wen Hui. "Dynamic Reliability Based on Perturbation Stochastic Finite Element." Applied Mechanics and Materials 155-156 (February 2012): 47–50. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.47.

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Анотація:

This paper proposes a method of calculating dynamic reliability using perturbation stochastic finite element. Dynamic analysis of perturbation stochastic finite element is introduced and the mean and variance of the stress can be obtained. Samples of stress and strength are generated by computer program. The Monte Carlo simulation is proposed to compute dynamic reliability of structure. Dynamic reliability of structure is computed by the stress-strength interference model. The proposed methods are demonstrated by a numerical example of axle.

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33

Lau, J. H., and L. B. Lian-Mueller. "Finite Element Modeling for Optimizing Hermetic Package Reliability." Journal of Electronic Packaging 111, no. 4 (December 1, 1989): 255–60. http://dx.doi.org/10.1115/1.3226544.

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The thermal stresses in microwave packages are studied by the finite element method. Emphasis is placed on the effects of material construction and design on the reliability of very small hermetic packages. Three different microwave packages have been designed and six finite element models (two for each design) have been analyzed. To verify the validity of the finite element results, some leak tests have been performed and the results agree with the analytical conclusions. The results presented herein should provide a better understanding of the thermal behavior of hermetic packages and should be useful for their optimal design.

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34

Dodagoudar, G. R., and B. Shyamala. "Finite element reliability analysis of shallow foundation settlements." International Journal of Geotechnical Engineering 9, no. 3 (July 31, 2014): 316–26. http://dx.doi.org/10.1179/1939787914y.0000000069.

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35

Hojjati, M. H., and A. Sadighi. "Reliability Based Finite Element Analysis of Mechanical Components." Multidiscipline Modeling in Materials and Structures 5, no. 2 (February 2009): 151–62. http://dx.doi.org/10.1163/157361109787959886.

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36

Sayed, Sajna, G. R. Dodagoudar, and K. Rajagopal. "Finite element reliability analysis of reinforced retaining walls." Geomechanics and Geoengineering 5, no. 3 (August 17, 2010): 187–97. http://dx.doi.org/10.1080/17486020903576788.

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37

Ghanem, Roger G., and Pol D. Spanos. "Spectral Stochastic Finite‐Element Formulation for Reliability Analysis." Journal of Engineering Mechanics 117, no. 10 (October 1991): 2351–72. http://dx.doi.org/10.1061/(asce)0733-9399(1991)117:10(2351).

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38

Liu, Pei‐Ling, and Armen Der Kiureghian. "Finite Element Reliability of Geometrically Nonlinear Uncertain Structures." Journal of Engineering Mechanics 117, no. 8 (August 1991): 1806–25. http://dx.doi.org/10.1061/(asce)0733-9399(1991)117:8(1806).

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39

Sehgal, R., O. P. Gandhi, and S. Angra. "Reliability evaluation and selection of rolling element bearings." Reliability Engineering & System Safety 68, no. 1 (April 2000): 39–52. http://dx.doi.org/10.1016/s0951-8320(99)00081-2.

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40

Jensen, H. A., F. Mayorga, and C. Papadimitriou. "Reliability sensitivity analysis of stochastic finite element models." Computer Methods in Applied Mechanics and Engineering 296 (November 2015): 327–51. http://dx.doi.org/10.1016/j.cma.2015.08.007.

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41

Alduaij, J. A. "Reliability of structural networks by macro element idealization." Computers & Structures 52, no. 4 (August 1994): 789–93. http://dx.doi.org/10.1016/0045-7949(94)90360-3.

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42

Koduru, S. D., and T. Haukaas. "Feasibility of FORM in finite element reliability analysis." Structural Safety 32, no. 2 (March 2010): 145–53. http://dx.doi.org/10.1016/j.strusafe.2009.10.001.

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43

Der Kiureghian, Armen, and Jyh-Bin Ke. "The stochastic finite element method in structural reliability." Probabilistic Engineering Mechanics 3, no. 2 (June 1988): 83–91. http://dx.doi.org/10.1016/0266-8920(88)90019-7.

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44

Choi, Kie-Yong, Soon-Heung Chang, and Young-Ku Yoon. "A dynamic reliability model for nuclear fuel element." Reliability Engineering & System Safety 31, no. 1 (January 1991): 111–16. http://dx.doi.org/10.1016/0951-8320(91)90040-e.

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45

Wang, Zhi Qiang, Ke Hong Zheng, and Xiao Bin Wu. "Compressive Resistance Reliability Analysis of Gravity Dam Based on Elastic Stochastic Finite Element." Advanced Materials Research 926-930 (May 2014): 537–40. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.537.

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Анотація:

When calculating compressive resistance reliability of gravity dam using the elasticity stochastic finite element method, as a result of stress singularity of dam toe, elements near the dam toe has been encrypted to different mesh size, find a point along the foundation plane that its compressive resistance reliability index is not sensitive to mesh and it is nearest to the dam toe, select the compressive resistance reliability index of the point as the compressive resistance reliability index of gravity dam. Take Longtan RCC gravity dam as an example and give the analysis results.

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46

Zhang, Da Qian, Xin Ping Fu, and Xiao Dong Tan. "Structural Reliability Analysis for UAV Center Wing Based on Stochastic Finite Element." Applied Mechanics and Materials 684 (October 2014): 208–12. http://dx.doi.org/10.4028/www.scientific.net/amm.684.208.

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Анотація:

In general it is difficult to obtain the results directly during process of structural reliability designing because of the complexity of the structure. It can calculate the structure reliability and failure probability effectively according to the combination of finite element method and theory of reliability. This paper introduces a method of structure reliability based on finite element method, summarizes a common method which has an important engineering application value to calculate the reliability such as using Monte-Carlo method to calculate reliability analysis combining with finite element method, recommends a common used software to reliability design and shows the process of using the software to reliability analysis.

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47

Zhu, Chang Shun, Guo Lin Wang, Ping Ping Li, and Ru Yu Ma. "Reliability Analysis of Radial Tire." Applied Mechanics and Materials 120 (October 2011): 436–39. http://dx.doi.org/10.4028/www.scientific.net/amm.120.436.

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Aimed at the radial tire's randomness in the structural parameters and material properties, etc., took the strain energy density of the tire carcass ply turn-up end as the objective function on the basis of analysis of the tire’s main failure modes, chose the tire carcass ply turn-up height and the rubber material parameters as random variable by using the Finite Element sensitivity analysis method(DSA), On this basis, adopted Monte-Carlo stochastic finite element method to calculate the reliability of the fatigue life of tire.

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48

Grishin, Vyacheslav, and Trong Vu. "Research methods to improve reliability of passive redundant control subsystems of aircraft with due consideration of tolerances." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2020, no. 1 (January 27, 2020): 18–28. http://dx.doi.org/10.24143/2072-9502-2020-1-18-28.

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The paper studies the reliability of passively redundant subsystems of aircraft, taking into account tolerances for a decrease in their output parameters in case of sudden component failures. The influence of the reliability values of elements, tolerances of two levels and the redundancy ratio on the reliability of passively redundant subsystems as a whole have been investigated; the examples of such subsystems have been given. There have been presented the results of analysis of the aircraft subsystems features with allowance for tolerances. First of all, these include the availability of technical specifications and realized tolerances determined by the reservation structure; implementing each tolerance with different values of the multiplicities of redundancy; using the main tolerance grid by multiple backup methods; presence of critical probabilities narrowing the reliability range of the elements, where this type of reservation is beneficial from the range 0–1 to the range of the supercritical area (pkr–1). The influence of the element reliability values, tolerances of two levels and the redundancy ratio on the failure-free operation of passively redundant subsystems in general and in supercritical areas has been investigated. It is shown that the minimum redundancy multiplicities in the interests of increasing the reliability of the considered subsystems of aircraft are advantageous to use only with large tolerances and low probabilities of failure-free operation of their elements. Under close tolerances and any reliability values of elements, as well as with large tolerances (more than 25%), high reliability values of this class of aircraft subsystems can be achieved only with large redundancy multiplicities. It has been inferred that there are extreme reliability differences of a passively redundant subsystem and its element, which allows to set the task of developing highly reliable passively redundant subsystems of aircraft taking into account tolerances from relatively unreliable elements.

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49

NEMENKO, A. V., and M. M. NIKITIN. "FORECAST EVALUATION OF A COMPLEX MECHANICAL SYSTEM TECHNICAL STATE." Fundamental and Applied Problems of Engineering and Technology, no. 1 (2021): 39–44. http://dx.doi.org/10.33979/2073-7408-2021-345-1-39-44.

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Анотація:

A method is proposed for estimating of a mechanical system technical state by its element that requires priority replacement at a selected future point in time, in the case of specifying quantitative indicators of reliability in the form of a time series. The method is applicable both for serial-parallel systems and for the general case of connecting elements along a complete graph, the special cases of which can be represented by all other methods of the reliability analysis scheme. To predict the state of each element, an approximation is used.

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50

Beyko, E., and M. M. Bernitsas. "Reliability of Complex Structures by Large Admissible Perturbations." Journal of Offshore Mechanics and Arctic Engineering 115, no. 3 (August 1, 1993): 167–78. http://dx.doi.org/10.1115/1.2920109.

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The perturbation approach to reliability (PAR) is a powerful methodology for reliability analysis and design of large structures. Its main features are: F1) PAR provides the exact global failure equation for any failure criterion for which the corresponding structural analysis can be performed by finite elements. F2) Geometry, material, and loads appear explicitly in the global failure equations and are treated as random variables. No need arises for load path selection or load pattern specification. F3) PAR introduces an invariant and consistent redundancy definition as an injective mapping restricted on the failure surface. Thus, the redundancy/reliability of the structure is expressed in terms of the redundancy/reliability of its structural components. F4) The norm of the Rosenblatt transformed reliability injection is the reliability index. F5) For each global failure equation or combination of failure equations, PAR computes the individual or joint design points without enumerating paths to failure, trial and error, or repeated finite element analyses. F6) Serviceability or ultimate global structural failure is defined by specifying a threshold value of any quantity that can be computed by finite elements: natural frequencies, dynamic normal modes, static deflections, static stresses, buckling loads, and buckling modes are implemented in PAR. Stress failure equations are used along with linearized plasticity surfaces to identify element failure. Several applications are presented to assess PAR.

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