Academic literature on the topic 'Reliability (Engineering) Mathematical models'

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Journal articles on the topic "Reliability (Engineering) Mathematical models":

1

Tharmabala, T., and Andrzej S. Nowak. "Mathematical models for bridge reliability." Canadian Journal of Civil Engineering 14, no. 2 (April 1, 1987): 155–62. http://dx.doi.org/10.1139/l87-027.

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System reliability of bridge structures is investigated. Three terms are used to describe the standard reliability: structure function, reliability network, and reliability function. A bridge structure is represented by a reliability network which makes it possible to formulate the reliability function of the system. The reliability function is used to evaluate the reliability of the system. Reliability network and the reliability function are formulated for various types of bridges. Effects of component failures on system reliability are illustrated with examples. Key words: bridges, mathematical models, redundancy, system reliability.
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Feinberg, Alec. "Accelerated Reliability Growth Models." Journal of the IEST 37, no. 1 (January 1, 1994): 17–23. http://dx.doi.org/10.17764/jiet.2.37.1.f2u73m8022207868.

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Extending reliability growth so that it can be applied in the area of accelerated testing will enable one to apply all the reliability growth tools and their planning advantages. This paper describes linking these two areas together into what is termed accelerated reliability growth testing (ARGT). Mathematical equations of ARGT for both iso-stress and step-stress accelerated testing are modelled.
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Urbina, Angel, and Thomas Paez. "Statistical Validation of Structural Dynamics Models." Journal of the IEST 46, no. 1 (September 14, 2003): 141–48. http://dx.doi.org/10.17764/jiet.46.1.f430423634885g67.

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There is an increasing reliance in the engineering community on the use of mathematical models to characterize physical system behavior. This is happening even though mathematical models rarely simulate real system behavior perfectly. Due to this reliance, we require objective, well-founded mathematical techniques for model validation. This paper develops a formal approach to the validation of mathematical models of structural dynamics systems. It uses a probabilistic/statistical approach to the characterization of an important measure of behavior of dynamic systems subjected to random excitations, and seeks to validate a mathematical model in a statistical sense. An example is presented.
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Yi, Ping. "Discussion of Mathematical Models of Probabilistic Constraints Calculation in Reliability-Based Design Optimization." Advanced Materials Research 243-249 (May 2011): 5717–26. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5717.

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In a reliability-based design optimization (RBDO) problem, most of the computations are used for probabilistic constraints assessment, i.e., reliability analysis. Therefore, the effectiveness, especially the correctness of the reliability analysis is very important. If the probabilistic constraint is misjudged, the optimization iteration would have convergence problems or arrive at erratic solutions. The probabilistic constraint assessment can be carried out using either the conventional reliability index approach (RIA) or the performance measure approach (PMA). In this paper, the mathematical models to calculate the reliability index in RIA and to calculate the probabilistic performance measure (PPM) in PMA are discussed. In RIA, through estimating whether the mean-value point in safe domain or not, we should use a positive or negative reliability index respectively. In PMA, one should always minimize the performance measure to compute PPM whether the performance measure at the mean-value point is positive or negative, which puts right the wrong mathematical model in some literatures and makes it possible to produce effective and efficient approach for RBDO.
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Belov, Alexander, Dmitry Shaforost, and Viktor Chebotarev. "Mathematical Models for Assessing the Thermal Engineering Reliability of Boiler Units of Power Complexes." Известия высших учебных заведений. Электромеханика 64, no. 6 (2021): 88–93. http://dx.doi.org/10.17213/0136-3360-2021-6-88-93.

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The analysis is carried out and the definitions of the concept of thermal engineering reliability, the determining parameter and the determining function of boiler units, are given. A classification has been developed for the determining parameters of steam and hot water boilers by level in the chain of cause-and-effect relationships in the event of a thermal failure. It is proposed to divide the determining parameters and functions of boilers according to their spatial localization into integral and local. A lot of models for defining functions with different mathematical properties (for example, the presence or absence of discontinuities of the second kind) are considered. The defining functions (reliability criteria) currently used in boiler construction have been identified. The analysis of the safety factors for overturning and stagnation in direct-flow and drum boiler units is carried out. The incorrectness of the currently used dependence is shown. A formula has been proposed for these coefficients using internal useful heads, which is especially relevant for boilers with natural circulation at ultrahigh pressure.
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Heydorn, Richard P. "Reliability Engineering: Probabilistic Models and Maintenance Methods." Technometrics 48, no. 3 (August 2006): 446. http://dx.doi.org/10.1198/tech.2006.s412.

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Abdallah, Wafaa, Jacqueline Saliba, Ziubir-Mehdi Sbartaï, Marwan Sadek, Fadi Hage Chehade, and S. Mohammed ElAchachi. "Reliability analysis of non-destructive testing models within a probabilistic approach." MATEC Web of Conferences 281 (2019): 04003. http://dx.doi.org/10.1051/matecconf/201928104003.

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The diagnosis of reinforced concrete is essential to detect the degradation and thus maintain the structural performance of civil engineering structures. This paper aims to establish a mathematical relationship between the ultrasonic pulse velocity UPV (considered as an observable variable) and two concrete properties indicators (compressive strength fc and water content W) within a probabilistic framework. Synthetic simulations are proposed to derive a conversion model between the statistical properties of the output and the input parameters for a reinforced concrete structure by taking into account spatial variability of concrete.
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ROMANCHENKO, Ihor S., Oleh SEMENENKO, Maryna SLIUSARENKO, Mykola VASIANOVYCH, and Ihor LEVCHENKO. "On the development of mathematical models for the reliability evaluation of aircraft operation in combat conditions." INCAS BULLETIN 13, S (August 3, 2021): 169–78. http://dx.doi.org/10.13111/2066-8201.2021.13.s.16.

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The authors of this study propose a methodological approach to modelling the reliability evaluation of aircraft operation in combat conditions. When developing recommendations on operational and strategic requirements for promising aircraft, a very important aspect is the elicitation of the requirements for their reliability, namely no-failure operation. Reliability as a parameter of any equipment should be set in the technical specifications for development together with other operational requirements in the form of reasonable quantitative indicators – reliability standards. The establishment of specific reliability standards stimulates its growth and creates the basis for rational design, taking into account the requirements of reliable operation. The analysis showed that different models can be used to simulate aircraft reliability. In this case, for example, the final values of mean time to failure (MTTF) would be different. The test results show that the methods and mathematical models used to substantiate the values of time and probability of trouble-free operation of aircraft do not fully correspond to the actual processes of changing their state during the use in the military. This is confirmed by a significant discrepancy in the values of reliability indicators implemented in practice. This was due to the fact that the acquainted mathematical models of aircraft reliability do not take into account the combat conditions in which they are supposed to operate. In addition, the reliability indicators used do not take into account possible changes (decrease) in these indicators during the period of aircraft operation. In general, the shortcomings inherent in the methods and mathematical models currently used to describe the aircraft reliability reduce the accuracy of the results obtained, and also do not quite adequately reflect the features of the corresponding process. When using different models, the cost of time to failure differs significantly. The more factors are taken into account, the greater the operating time to failure will be. This means that when designing aircraft, it is necessary to set the value of this indicator greater than indicated in the form. Taking into account additional factors complicates the model, but at the same time makes it more accurate.
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Ya-jun, Wang, and Wang Jun. "Generalised Reliability On Hydro-Geo Objects." Open Civil Engineering Journal 9, no. 1 (July 31, 2015): 498–503. http://dx.doi.org/10.2174/1874149501509010498.

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This study established the fuzzy logic modeling of the stochastic finite element method based on the first-order approximation theorem. Fuzzy mathematical models of safety repertories were incorporated into the stochastic finite element method to analyze the stability of embankments and foundations in order to describe the fuzzy failure procedure for the random safety performance function. The fuzzy models were developed with membership functions with half depressed gamma distribution, half depressed normal distribution, and half depressed echelon distribution. The result shows that the middle region of the dike is the principal zone of concentrated failure due to local fractures. There is also some local shear failure on the dike crust. This study provides a referential method for solving complex multi-uncertainty problems in engineering safety analysis.
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Guo, R., and E. Love. "Reliability Modelling with Fuzzy Covariates." International Journal of Reliability, Quality and Safety Engineering 10, no. 02 (June 2003): 131–57. http://dx.doi.org/10.1142/s0218539303001056.

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In this research, we focus on covariate modelling to explore the interactions between industrial system and its enviroment in terms of the modelling fundamental characteristic — random and fuzzy uncertaity with an intention to decrease the fatal weakness of the modern dissection methodology. We extend the additive and multiplicative covariate models from these considering randomness alone into these considering both randomness and fuzziness in the sense as a mathematical extension to the existing covariate modelling. In terms of the form of logical function an engineering oriented fuzzy reliability model which could potentially count all the aspects associated with an operating system and its environment is proposed. Statistical estimation on the parameters of system fuzzy reliability is considered based on the general theory of the point processes. The impacts on the optimal plant maintenance from the engineering oriented fuzzy reliability modelling is also discussed. Finally we use an industrial example to illustrate the main theoretical developments.

Dissertations / Theses on the topic "Reliability (Engineering) Mathematical models":

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Lu, Jin 1959. "Degradation processes and related reliability models." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=39952.

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Reliability characteristics of new devices are usually demonstrated by life testing. When lifetime data are sparse, as is often the case with highly reliable devices, expensive devices, and devices for which accelerated life testing is not feasible, reliability models that are based on a combination of degradation and lifetime data represent an important practical approach. This thesis presents reliability models based on the combination of degradation and lifetime data or degradation data alone, with and without the presence of covariates. Statistical inference methods associated with the models are also developed.
The degradation process is assumed to follow a Wiener process. Failure is defined as the first passage of this process to a fixed barrier. The degradation data of a surviving item are described by a truncated Wiener process and lifetimes follow an inverse Gaussian distribution. Models are developed for three types of data structures that are often encountered in reliability studies, terminal point data (a combination of degradation and lifetime data) and mixed data (an extended case of terminal point data); conditional degradation data; and covariate data.
Maximum likelihood estimators (MLEs) are derived for the parameters of each model. Inferences about the parameters are based on asymptotic properties of the MLEs and on the likelihood ratio method. An analysis of deviance is presented and approximate pivotal quantities are derived for the drift and variance parameters. Predictive density functions for the lifetime and the future degradation level of either a surviving item or a new item are obtained using empirical Bayes methods. Case examples are given to illustrate the applications of the models.
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Jiang, Siyuan. "Mixed Weibull distributions in reliability engineering: Statistical models for the lifetime of units with multiple modes of failure." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185481.

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The finite mixed Weibull distribution is an appropriate distribution in modeling the lifetime of the units having more than one possible failure cause. Due to the lack of a systematic statistical procedure of fitting the distribution to a data set, it has not been widely used in lifetime data analyses. Many areas on this subject have been studied in this research. The following are the findings and contributions. Through a change of variable, 5 parameters in a two Weibull mixture can be reduced to 3. A parameter'vector (p₁, η, β) defines a family of two-Weibull mixtures which have common characteristics. Numerous probability plots are investigated on Weibull probability paper (WPP). For a given p₁ the η-β plane is partitioned into seven regions which are labeled by A through F and S. The Region S represents the two Weibull mixtures whose cdf curves are very close to a straight line. The Regions A through F represent six typical shapes of the cdf curves on WPP, respectively. The two-Weibull mixtures in one region have similar characteristics. Three important features of the two-Weibull mixture with well separated subpopulations are proved. Two existing methods for the graphical estimation of the parameters are discussed, and one is recommended over the other. The EM algorithm is successfully applied to solve the MLE for mixed Weibull distributions when m, the number of subpopulations in a mixture is known. The algorithms for complete, censored, grouped and suspended samples with non-postmortem and postmortem failures are developed accordingly. The developed algorithms are powerful, efficient and they are insensitive to the initial guesses. Extensive Monte Carlo simulations are performed. The distributions of the MLE of the parameters and of the reliability of a two Weibull mixture are studied. The MLEs of the parameters are sensitive to the degree of separation of the two subpopulation pdfs, but the MLE of the reliability is not. The generalized likelihood ratio (GLR) test is used to determine m. Under H₀: m=1 and H₁: m=m₁>1, ζ, the GLR is independent of the parameters in the distribution of H₀. The distributions of ζ or -21n(ζ) with n=50, 100 and 150 are obtained through Monte Carlo simulations. Compared with the chi-square distribution, they fall in between x²(4) and x²(6), and they are very close to x²(5). A FORTRAN computer program is developed to conduct simulation of the GLR test for 1 ≤ m₀ < m₁ ≤ 5.
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Hashemolhosseini, Sepehr. "Algorithmic component and system reliability analysis of truss structures." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85710.

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Thesis (MScEng)-- Stellenbosch University, 2013.
ENGLISH ABSTRACT: Most of the parameters involved in the design and analysis of structures are of stochastic nature. This is, therefore, of paramount importance to be able to perform a fully stochastic analysis of structures both in component and system level to take into account the uncertainties involved in structural analysis and design. To the contrary, in practice, the (computerised) analysis of structures is based on a deterministic analysis which fails to address the randomness of design and analysis parameters. This means that an investigation on the algorithmic methodologies for a component and system reliability analysis can help pave the way towards the implementation of fully stochastic analysis of structures in a computer environment. This study is focused on algorithm development for component and system reliability analysis based on the various proposed methodologies. Truss structures were selected for this purpose due to their simplicity as well as their wide use in the industry. Nevertheless, the algorithms developed in this study can be used for other types of structures such as moment-resisting frames with some simple modi cations. For a component level reliability analysis of structures different methods such as First Order Reliability Methods (FORM) and simulation methods are proposed. However, implementation of these methods for the statistically indeterminate structures is complex due to the implicit relation between the response of the structural system and the load effect. As a result, the algorithm developed for the purpose of component reliability analysis should be based on the concepts of Stochastic Finite Element Methods (SFEM) where a proper link between the finite element analysis of the structure and the reliability analysis methodology is ensured. In this study various algorithms are developed based on the FORM method, Monte Carlo simulation, and the Response Surface Method (RSM). Using the FORM method, two methodologies are considered: one is based on the development of a finite element code where required alterations are made to the FEM code and the other is based on the usage of a commercial FEM package. Different simulation methods are also implemented: Direct Monte Carlo Simulation (DMCS), Latin Hypercube Sampling Monte Carlo (LHCSMC), and Updated Latin Hypercube Sampling Monte Carlo (ULHCSMC). Moreover, RSM is used together with simulation methods. Throughout the thesis, the effciency of these methods was investigated. A Fully Stochastic Finite Element Method (FSFEM) with alterations to the finite element code seems the fastest approach since the linking between the FEM package and reliability analysis is avoided. Simulation methods can also be effectively used for the reliability evaluation where ULHCSMC seemed to be the most efficient method followed by LHCSMC and DMCS. The response surface method is the least straight forward method for an algorithmic component reliability analysis; however, it is useful for the system reliability evaluation. For a system level reliability analysis two methods were considered: the ß-unzipping method and the branch and bound method. The ß-unzipping method is based on a level-wise system reliability evaluation where the structure is modelled at different damaged levels according to its degree of redundancy. In each level, the so-called unzipping intervals are defined for the identification of the critical elements. The branch and bound method is based on the identification of different failure paths of the structure by the expansion of the structural failure tree. The evaluation of the damaged states for both of the methods is the same. Furthermore, both of the methods lead to the development of a parallel-series model for the structural system. The only difference between the two methods is in the search approach used for the failure sequence identification. It was shown that the ß-unzipping method provides a better algorithmic approach for evaluating the system reliability compared to the branch and bound method. Nevertheless, the branch and bound method is a more robust method in the identification of structural failure sequences. One possible way to increase the efficiency of the ß-unzipping method is to define bigger unzipping intervals in each level which can be possible through a computerised analysis. For such an analysis four major modules are required: a general intact structure module, a damaged structure module, a reliability analysis module, and a system reliability module. In this thesis different computer programs were developed for both system and component reliability analysis based on the developed algorithms. The computer programs are presented in the appendices of the thesis.
AFRIKAANSE OPSOMMING: Meeste van die veranderlikes betrokke by die ontwerp en analise van strukture is stogasties in hul aard. Om die onsekerhede betrokke in ontwerp en analise in ag te neem is dit dus van groot belang om 'n ten volle stogastiese analise te kan uitvoer op beide komponent asook stelsel vlak. In teenstelling hiermee is die gerekenariseerde analise van strukture in praktyk gebaseer op deterministiese analise wat nie suksesvol is om die stogastiese aard van ontwerp veranderlikes in ag te neem nie. Dit beteken dat die ondersoek na die algoritmiese metodiek vir komponent en stelsel betroubaarheid analise kan help om die weg te baan na die implementering van ten volle rekenaarmatige stogastiese analise van strukture. Di e studie se fokus is op die ontwikkeling van algoritmes vir komponent en stelsel betroubaarheid analise soos gegrond op verskeie voorgestelde metodes. Vakwerk strukture is gekies vir die doeleinde as gevolg van hulle eenvoud asook hulle wydverspreide gebruik in industrie. Die algoritmes wat in die studie ontwikkel is kan nietemin ook vir ander tipes strukture soos moment-vaste raamwerke gebruik word, gegewe eenvoudige aanpassings. Vir 'n komponent vlak betroubaarheid analise van strukture word verskeie metodes soos die "First Order Reliability Methods" (FORM) en simulasie metodes voorgestel. Die implementering van die metodes vir staties onbepaalbare strukture is ingewikkeld as gevolg van die implisiete verband tussen die gedrag van die struktuur stelsel en die las effek. As 'n gevolg, moet die algoritme wat ontwikkel word vir die doel van komponent betroubaarheid analise gebaseer word op die konsepte van stogastiese eindige element metodes ("SFEM") waar 'n duidelike verband tussen die eindige element analise van die struktuur en die betroubaarheid analise verseker is. In hierdie studie word verskeie algoritmes ontwikkel wat gebaseer is op die FORM metode, Monte Carlo simulasie, en die sogenaamde "Response Surface Method" (RSM). Vir die gebruik van die FORM metode word twee verdere metodologieë ondersoek: een gebaseer op die ontwikkeling van 'n eindige element kode waar nodige verandering aan die eindige element kode self gemaak word en die ander waar 'n kommersiële eindige element pakket gebruik word. Verskillende simulasie metodes word ook geïmplimenteer naamlik Direkte Monte Carlo Simulasie (DMCS), "Latin Hypercube Sampling Monte Carlo" (LHCSMC) en sogenaamde "Updated Latin Hypercube Sampling Monte Carlo" (ULHCSMC). Verder, word RSM tesame met die simulasie metodes gebruik. In die tesis word die doeltreffendheid van die bostaande metodes deurgaans ondersoek. 'n Ten volle stogastiese eindige element metode ("FSFEM") met verandering aan die eindige element kode blyk die vinnigste benadering te wees omdat die koppeling tussen die eindige element metode pakket en die betroubaarheid analise verhoed word. Simulasie metodes kan ook effektief aangewend word vir die betroubaarheid evaluasie waar ULHCSMC as die mees doeltre end voorgekom het, gevolg deur LHCSMC en DMCS. The RSM metode is die mees komplekse metode vir algoritmiese komponent betroubaarheid analise. Die metode is egter nuttig vir sisteem betroubaarheid analise. Vir sisteem-vlak betroubaarheid analise is twee metodes oorweeg naamlik die "ß-unzipping" metode and die "branch-and-bound" metode. Die "ß-unzipping" metode is gebaseer op 'n sisteem-vlak betroubaarheid ontleding waar die struktuur op verskillende skade vlakke gemodelleer word soos toepaslik vir die hoeveelheid addisionele las paaie. In elke vlak word die sogenaamde "unzipping" intervalle gedefinieer vir die identifikasie van die kritiese elemente. Die "branch-and-bound" metode is gebaseer op die identifikasie van verskillende faling roetes van die struktuur deur uitbreiding van die falingsboom. The ondersoek van die skade toestande vir beide metodes is dieselfde. Verder kan beide metodes lei tot die ontwikkeling van 'n parallelserie model van die strukturele stelsel. Die enigste verskil tussen die twee metodes is in die soek-benadering vir die uitkenning van falingsmodus volgorde. Dit word getoon dat die "ß-unzipping" metode 'n beter algoritmiese benadering is vir die ontleding van sisteem betroubaarheid vergeleke met die "branch-and-bound" metode. Die "branch-and- bound" metode word nietemin as 'n meer robuuste metode vir die uitkenning van die falings volgorde beskou. Een moontlike manier om die doeltre endheid van die "ß-unzipping" metode te verhoog is om groter "unzipping" intervalle te gebruik, wat moontlik is vir rekenaarmatige analise. Vir so 'n analise word vier hoof modules benodig naamlik 'n algemene heel-struktuur module, 'n beskadigde-struktuur module, 'n betroubaarheid analise module en 'n sisteem betroubaarheid analise module. In die tesis word verskillende rekenaar programme ontwikkel vir beide sisteem en komponent betroubaarheid analise. Die rekenaar programme word in die aanhangsels van die tesis aangebied.
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LEE, SEUNG JOO. "RELIABILITY-BASED OPTIMAL STRUCTURAL AND MECHANICAL DESIGN." Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184136.

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Structural reliability technology provides analytical tools for management of uncertainty in all relevant design factors in structural and mechanical systems. Generally, the goal of analysis is to compute probabilities of failure in structural components or system having single or multiple failure mode. Alternately, modern optimization methods provide efficient numerical algorithms for locating optima, particularly in large-scale systems having prescribed deterministic constraints. Optimization procedure can accommodate random variables either directly in its objective function or as one of the primary constraints. The combination of elementary optimization and probabilistic design techniques is the subject of this study. Presented herein is a general strategy for optimization when the design factors are random variables and some or all of the constraints are probability statements. A literature review has indicated that optimization technology in a reliability context has not been fully explored for the general case of nonlinear performance functions and nonnormal variates associated multiple failure modes. This research focuses upon development of the theory to address this general problem. Because analysis algorithms are complicated, a computer code, program RELOPT, is constructed to automate the analysis. The objective function to be minimized is arbitrary, but would generally be the total expected lifetime costs including all initial costs as well as all costs associated with failure. Uncertainty is assumed to be possible in all design factors (including the factors to be determined), and they are modeled as random variables. In general, all of the constraints can be probability statements. The generalized reduce gradient (GRG) method was used for optimization calculations. Options for point probability calculations are first order reliability analysis using the Rackwitz-Fiessler (R-F) or advanced reliability analysis using Wu/FPI. For system reliability analysis either the first order Cornell's bounds or the second order Ditlevsen's bounds can be specified. Several examples are presented to illustrate the full range of capabilities of RELOPT. The program is validated by checking with independent and exact solutions. An example is provided which demonstrates that the cost of running RELOPT can be substantial as the size of the problem increases.
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Jiang, Yu, and 姜宇. "Reliability-based transit assignment : formulations, solution methods, and network design applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/207991.

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Kim, Injoong. "Development of a knowledge model for the computer-aided design for reliability of electronic packaging systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/22708.

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Thesis (Ph. D.)--Mechanical Engineering, Georgia Institute of Technology, 2008.
Committee Co-Chair: Peak, Russell; Committee Co-Chair: Sitaraman, Suresh; Committee Member: Paredis, Christiaan; Committee Member: Pucha, Raghuram; Committee Member: Wong, C.
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O'Reilly, Małgorzata Marzena. "Necessary conditions for the variant optimal design of linear consecutive systems." Title page, contents and summary only, 2001. http://web4.library.adelaide.edu.au/theses/09PH/09pho668.pdf.

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"October 2001." Bibliography: leaves 99-103. Establishes several sets of conditioning relating to the variant optimal deign of linear consecutive-k-out-of-n systems and includes a review of existing research in the theory of variant optimal design of linear consecutive-k-out-of-n systems.
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Malada, Awelani. "Stochastic reliability modelling for complex systems." Thesis, Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-10182006-170927.

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Torng, Tony Yi. "Reliability analysis of maintained structural system vulnerable to fatigue and fracture." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184955.

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Metallic structures dominated by tensile loads are vulnerable to fatigue and fracture. Fatigue is produced by oscillatory loads. Quasi-static brittle or ductile fracture can result from a "large" load in the random sequence. Moreover, a fatigue or fracture failure in a member of a redundant structure produces impulsive redistributed loads to the intact members. These transient loads could produce a sequence of failures resulting in progressive collapse of the system. Fatigue and fracture design factors are subject to considerable uncertainty. Therefore, a probabilistic approach, which includes a system reliability assessment, is appropriate for design purposes. But system reliability can be improved by a maintenance program of periodic inspection with repair and/or replacement of damaged members. However, a maintenance program can be expensive. The ultimate goal of the engineer is to specify a design, inspection, and repair strategy to minimize life cycle costs. The fatigue/fracture reliability and maintainability (FRM) process for redundant structure can be a complicated random process. The structural model considered series, parallel, and parallel/series systems of elements. Applied to the system are fatigue loads including mean stress, an extreme load, as well as impulsive loads in parallel member systems. The failure modes are fatigue, brittle and ductile fracture. A refined fatigue model is employed which includes both the crack initiation and propagation phases. The FRM process cannot be solved easily using recently developed advanced structural reliability techniques. A "hybrid" simulation method which combines modified importance sampling (MIS) with inflated stress extrapolation (ISE) is proposed. MIS and ISE methods are developed and demonstrated using numerous examples which include series, parallel and series/parallel systems. Not only reasonable estimates of the probability of system failure but also an estimate of the distribution of time to system failure can be obtained. The time to failure distribution can be used to estimate the reliability function, hazard function, conditional reliability given survival at any time, etc. The demonstration cases illustrate how reliability of a system having given material properties is influenced by the number of series and parallel elements, stress level, mean stress, and various inspection/repair policies.
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Yim, Ka-wing, and 嚴家榮. "A reliability-based land use and transportation optimization model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B34618879.

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Books on the topic "Reliability (Engineering) Mathematical models":

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Epstein, Benjamin. Mathematical models for systems reliability. Boca Raton: Taylor & Francis, 2008.

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Ushakov, I. A. Probabilistic reliability models. San Diego, CA: Wiley, 2012.

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Aven, T. Stochastic models in reliability. New York: Springer, 1999.

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Kuo, Way. Optimal Reliability Modeling. New York: John Wiley & Sons, Ltd., 2002.

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Nachlas, Joel A. Reliability engineering: Probabilistic models and maintenance methods. Boca Raton: Taylor & Francis, 2005.

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Kuo, Way. Optimal reliability modeling: Principles and applications. Hoboken, NJ: John Wiley & Sons, 2003.

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Barlow, Richard E. Mathematical theory of reliability. Philadelphia: SIAM, 1996.

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C, Ionescu D., and Limnios N, eds. Statistical and probabilistic models in reliability. Boston: Birkhäuser, 1999.

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Pereguda, A. I. Modeli, pokazateli i metody ikh vychislenii︠a︡: Nauchnai︠a︡ monografii︠a︡. Obninsk: IATĖ, 2005.

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Beichelt, Frank. Reliability and maintenance: Networks and systems. Boca Raton, FL: CRC Press, 2012.

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Book chapters on the topic "Reliability (Engineering) Mathematical models":

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Vonta, Filia, and Alex Karagrigoriou. "Information Measures in Biostatistics and Reliability Engineering." In Mathematical and Statistical Models and Methods in Reliability, 401–13. Boston, MA: Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-4971-5_31.

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Dhillon, B. S. "Mathematical models for engineering systems reliability analysis and usability assurance." In Systems reliability and usability for engineers, 243–63. Boca Raton : Taylor & Francis, CRC Press, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429488528-13.

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Dhillon, B. S. "Mathematical Models for Performing Human Reliability and Error Analysis in Power Plants." In Springer Series in Reliability Engineering, 151–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04019-6_11.

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Chiodo, Elio, and Giovanni Mazzanti. "Mathematical and Physical Properties of Reliability Models in View of their Application to Modern Power System Components." In Springer Series in Reliability Engineering, 59–140. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-088-5_3.

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Falcone, Domenico, Alessandro Silvestri, Gianpaolo Di Bona, and Antonio Forcina. "Mathematical Models for Reliability Allocation and Optimization for Complex Systems." In Human Factors and Reliability Engineering for Safety and Security in Critical Infrastructures, 43–76. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62319-1_3.

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Greiner-Petter, André, Howard S. Cohl, Abdou Youssef, Moritz Schubotz, Avi Trost, Rajen Dey, Akiko Aizawa, and Bela Gipp. "Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra Systems." In Tools and Algorithms for the Construction and Analysis of Systems, 87–105. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_5.

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AbstractDigital mathematical libraries assemble the knowledge of years of mathematical research. Numerous disciplines (e.g., physics, engineering, pure and applied mathematics) rely heavily on compendia gathered findings. Likewise, modern research applications rely more and more on computational solutions, which are often calculated and verified by computer algebra systems. Hence, the correctness, accuracy, and reliability of both digital mathematical libraries and computer algebra systems is a crucial attribute for modern research. In this paper, we present a novel approach to verify a digital mathematical library and two computer algebra systems with one another by converting mathematical expressions from one system to the other. We use our previously developed conversion tool (referred to as "Image missing" ) to translate formulae from the NIST Digital Library of Mathematical Functions to the computer algebra systems and . The contributions of our presented work are as follows: (1) we present the most comprehensive verification of computer algebra systems and digital mathematical libraries with one another; (2) we significantly enhance the performance of the underlying translator in terms of coverage and accuracy; and (3) we provide open access to translations for and of the formulae in the NIST Digital Library of Mathematical Functions.
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Muir, Paul, and Jack Pew. "An Analysis of the Reliability of Error Control B-Spline Gaussian Collocation PDE Software." In Mathematical and Computational Approaches in Advancing Modern Science and Engineering, 459–68. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30379-6_42.

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Santagati, Pietro, and Valeriu Beiu. "A Mathematical Model for the Analysis of the Johnson-Nyquist Thermal Noise on the Reliability in Nano-Communications." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 49–59. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06944-9_4.

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Birolini, Alessandro. "Basic Mathematical Statistics." In Reliability Engineering, 435–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03792-8_16.

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Ben-Haim, Yakov. "Reliability of Mathematical Models." In Robust Reliability in the Mechanical Sciences, 155–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61154-4_6.

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Conference papers on the topic "Reliability (Engineering) Mathematical models":

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Bobalo, Yuriy, Leonid Nedostup, Oxana Lazko, and Volodymyr Glemba. "Mathematical models of reliability of components parametrical synthesis." In 2006 International Conference - Modern Problems of Radio Engineering, Telecommunications, and Computer Science. IEEE, 2006. http://dx.doi.org/10.1109/tcset.2006.4404645.

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Koltover, Vitaly K. "Mathematical Theory of Reliability and Aging: Teaching Comes from Kiev." In 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO). IEEE, 2016. http://dx.doi.org/10.1109/smrlo.2016.68.

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Vikram Kumar Kamboj, Amit Bhardwaj, Harkamaljeet Singh Bhullar, Krishan Arora, and Kulraj Kaur. "Mathematical model of reliability assessment for generation system." In 2012 IEEE International Power Engineering and Optimization Conference (PEOCO). IEEE, 2012. http://dx.doi.org/10.1109/peoco.2012.6231118.

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Kakubava, Revaz, Archil Prangishvili, and Grigol Sokhadze. "Closed and Mixed Type Queuing Systems as Mathematical Models of Reliability and Survivability." In 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO). IEEE, 2016. http://dx.doi.org/10.1109/smrlo.2016.15.

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Klymash, Mykhailo, and Roman Pavlyuk. "The Methodology of Determination of SDH-Network Structural Reliability. Mathematical and Imitating Models." In 2006 International Conference - Modern Problems of Radio Engineering, Telecommunications, and Computer Science. IEEE, 2006. http://dx.doi.org/10.1109/tcset.2006.4404641.

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Hao, Guangbo, and Liyang Xie. "Reliability Mathematical Model of Continuous System Based on Segment-Partition." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86857.

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For the purpose of reliability assessment of continuous system like long pipeline and wire cable, the object should be taken as a series system composed of a great number of segments. First of all, two factors concerning the strength distribution of the object, i.e. material inhomogeneity factor and material quality instability factor were discussed in detail. Then, a reliability mathematical model of the object considering dependent failure was presented based on order statistics of segment strength, which was verified by Monte Carlo method. The result shows that the proposed reliability model can reflect the effects of dependent failure, material inhomogeneity and material quality instability for the application of continuous system.
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Jiankang, Dong, Ma Hongyan, Chen Jingjie, and Liu Jiaxue. "Mathematical Model of Aircraft Reliability Based on Fault Diagnosis." In 2010 International Conference on Intelligent System Design and Engineering Application (ISDEA). IEEE, 2010. http://dx.doi.org/10.1109/isdea.2010.330.

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Pandey, Vijitashwa. "Quantum Mechanical Perspectives in Reliability Engineering and System Design." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98028.

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Abstract Engineering design under uncertainty is an established field. Attempts to extricate the human decision maker from the process generally do not succeed. Surprisingly, even the determination of system parameters and their admissible values needs as many interventional steps from human designers and operators, as the selection of final attributes of the system that the human end user is expected to only interact and be concerned with. In this light, it becomes important to consider the mathematical models that would explain and model the decision making behavior of human beings. Concerningly, this behavior has been seen to violate common sense probability axioms. In this paper, we propose an earnest look at the mathematics of quantum mechanical theory in modeling and manipulating the uncertainties involved in engineering systems. We propose that the state of a system be modeled as a point in an abstract complex vector space as in quantum mechanics. Additionally, at a given point in time it can be interpreted as a superposition of multiple pure states. This change in perspective allows explanation of many commonly observed behaviors, least of which is the inconsistencies in defining what constitutes the failure of a system. We present our approach in the context of reliability engineering as it sees some of the most prevalent use of uncertainty modeling and propagation techniques. However, the implications on design and design theory are also evident. Some motivating examples are provided and directions for future work are identified.
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Baghdasaryan, Lusine, Wei Chen, Thaweepat Buranathiti, and Jian Cao. "Model Validation via Uncertainty Propagation Using Response Surface Models." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/dac-34140.

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Model validation has become a primary means to evaluate accuracy and reliability of computational simulations in engineering design. Mathematical models enable engineers to establish what the most likely response of a system is. However, despite the enormous power of computational models, uncertainty is inevitable in all model-based engineering design problems, due to the variation in the physical system itself, or lack of knowledge, and the use of assumptions by model builders. Therefore, realistic mathematical models should contemplate uncertainties. Due to the uncertainties, the assessment of the validity of a modeling approach must be conducted based on stochastic measurements to provide designers with the confidence of using a model. In this paper, a generic model validation methodology via uncertainty propagation is presented. The approach reduces the number of physical testing at each design setting to one by shifting the evaluation effort to uncertainty propagation of the computational model. Response surface methodology is used to create metamodels as less costly approximations of simulation models for uncertainty propagation. The methodology is illustrated with the examination of the validity of a finite-element analysis model for predicting springback angles in a sample flanging process.
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Gliklikh, Yuri. "Stochastic Equations and Inclusions with Mean Derivatives and Their Applications to Mathematical Physics." In 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO). IEEE, 2016. http://dx.doi.org/10.1109/smrlo.2016.74.

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Reports on the topic "Reliability (Engineering) Mathematical models":

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Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova, and Pavlo P. Nechypurenko. Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3677.

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An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concept of modeling and technological integration of various organizational forms and teaching methods based on the concept of mobility. Within this approach, the leading learning tools of bachelors of electromechanics are mobile Internet devices (MID) – a multimedia mobile devices that provide wireless access to information and communication Internet services for collecting, organizing, storing, processing, transmitting, presenting all kinds of messages and data. The authors reveals the main possibilities of using MID in learning to ensure equal access to education, personalized learning, instant feedback and evaluating learning outcomes, mobile learning, productive use of time spent in classrooms, creating mobile learning communities, support situated learning, development of continuous seamless learning, ensuring the gap between formal and informal learning, minimize educational disruption in conflict and disaster areas, assist learners with disabilities, improve the quality of the communication and the management of institution, and maximize the cost-efficiency. Bachelor of electromechanics competency in modeling of technical objects is a personal and vocational ability, which includes a system of knowledge, skills, experience in learning and research activities on modeling mechatronic systems and a positive value attitude towards it; bachelor of electromechanics should be ready and able to use methods and software/hardware modeling tools for processes analyzes, systems synthesis, evaluating their reliability and effectiveness for solving practical problems in professional field. The competency structure of the bachelor of electromechanics in the modeling of technical objects is reflected in three groups of competencies: general scientific, general professional and specialized professional. The implementation of the technique of using MID in learning bachelors of electromechanics in modeling of technical objects is the appropriate methodic of using, the component of which is partial methods for using MID in the formation of the general scientific component of the bachelor of electromechanics competency in modeling of technical objects, are disclosed by example academic disciplines “Higher mathematics”, “Computers and programming”, “Engineering mechanics”, “Electrical machines”. The leading tools of formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects are augmented reality mobile tools (to visualize the objects’ structure and modeling results), mobile computer mathematical systems (universal tools used at all stages of modeling learning), cloud based spreadsheets (as modeling tools) and text editors (to make the program description of model), mobile computer-aided design systems (to create and view the physical properties of models of technical objects) and mobile communication tools (to organize a joint activity in modeling).
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Markova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko, and Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3270.

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Leading research directions are defined on the basis of self-analysis of the study results on the use of cloud technologies in training by employees of joint research laboratory “Сloud technologies in education” of Kryvyi Rih National University and Institute of Information Technology and Learning Aids of the NAES of Ukraine in 2009-2018: cloud learning technologies, cloud technologies of blended learning, cloud-oriented learning environments, cloud-oriented methodological systems of training, the provision of cloud-based educational services. The ways of implementation SaaS, PaaS, IaaS cloud services models which are appropriate to use in the process of studying the academic disciplines of the cycles of mathematical, natural science and professional and practical training of future specialists in information technology are shown, based on the example of software engineering, computer science and computer engineering. The most significant advantages of using cloud technologies in training of future information technology specialists are definite, namely, the possibility of using modern parallel programming tools as the basis of cloud technologies. Conclusions are drawn; the direction of further research is indicated: designing a cloud-oriented learning environment for future specialists in computer engineering, identifying trends in the development of cloud technologies in the professional training and retraining of information technology specialists, developing a methodology for building the research competencies of future software engineering specialists by using cloud technologies.
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.

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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.
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Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev, and Arnold Kiv. Computer Simulation of Neural Networks Using Spreadsheets: Dr. Anderson, Welcome Back. [б. в.], June 2019. http://dx.doi.org/10.31812/123456789/3178.

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The authors of the given article continue the series presented by the 2018 paper “Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot”. This time, they consider mathematical informatics as the basis of higher engineering education fundamentalization. Mathematical informatics deals with smart simulation, information security, long-term data storage and big data management, artificial intelligence systems, etc. The authors suggest studying basic principles of mathematical informatics by applying cloud-oriented means of various levels including those traditionally considered supplementary – spreadsheets. The article considers ways of building neural network models in cloud-oriented spreadsheets, Google Sheets. The model is based on the problem of classifying multi-dimensional data provided in “The Use of Multiple Measurements in Taxonomic Problems” by R. A. Fisher. Edgar Anderson’s role in collecting and preparing the data in the 1920s-1930s is discussed as well as some peculiarities of data selection. There are presented data on the method of multi-dimensional data presentation in the form of an ideograph developed by Anderson and considered one of the first efficient ways of data visualization.
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EFFECT OF RANDOM PRE-STRESSED FRICTION LOSS ON THE PERFORMANCE OF A SUSPEN-DOME STRUCTURE. The Hong Kong Institute of Steel Construction, March 2022. http://dx.doi.org/10.18057/ijasc.2022.18.1.5.

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The key to the high-efficiency performance of the suspen-dome structure is to apply the pre-stressed design value to the structure accurately. However, engineering practice has found that the use of tensioning hoop cables to apply the pre-stress will produce noticeable pre-stressed friction loss (PFL), which significantly affects the safety performance of the structure. In this paper, based on a 1:10 scaled-down experiment model of a suspen-dome structure with rolling cable-strut joint installed, the random PFL (RPFL) effect of the suspen-dome on structure performance was analyzed through a probability statistics theory. First, aiming at the unequal tensioning force at both sides of the tensioned hoop cable during the tensioning process, a pre-stressed force calculation method is proposed that considers the unequal tensioning control force and RPFL at all cable–strut joints, and the reliability of this method is verified through a tension test. Then, based on the cable-joint tension test carried out in the early stage of the research group, a random mathematical model of the friction coefficient (FC) at the rolling cable–strut joint is established. And then, the cable force calculation method is used to establish the random finite element model, and independent and random changes in the FC at each rolling cable–strut joint can be considered. Subsequently, the Monte Carlo method is used to calculate the random mathematical characteristics of the mechanical performance parameters such as the member stress and joint deformation, and the obtained results are verified through a static loading experiment. In addition, to investigate the effect of random defects on structural stability, other random defects, such as the initial curvature and installation deviation, were continuously introduce based on the random finite element model. As such, we could obtain the law of the effect of multi-defect random variation coupling on the structure’s ultimate bearing capacity.

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