Littérature scientifique sur le sujet « Reliability (Engineering) Mathematical models »
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Articles de revues sur le sujet "Reliability (Engineering) Mathematical models"
Tharmabala, T., et Andrzej S. Nowak. « Mathematical models for bridge reliability ». Canadian Journal of Civil Engineering 14, no 2 (1 avril 1987) : 155–62. http://dx.doi.org/10.1139/l87-027.
Texte intégralFeinberg, Alec. « Accelerated Reliability Growth Models ». Journal of the IEST 37, no 1 (1 janvier 1994) : 17–23. http://dx.doi.org/10.17764/jiet.2.37.1.f2u73m8022207868.
Texte intégralUrbina, Angel, et Thomas Paez. « Statistical Validation of Structural Dynamics Models ». Journal of the IEST 46, no 1 (14 septembre 2003) : 141–48. http://dx.doi.org/10.17764/jiet.46.1.f430423634885g67.
Texte intégralYi, Ping. « Discussion of Mathematical Models of Probabilistic Constraints Calculation in Reliability-Based Design Optimization ». Advanced Materials Research 243-249 (mai 2011) : 5717–26. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5717.
Texte intégralBelov, Alexander, Dmitry Shaforost et 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.
Texte intégralHeydorn, Richard P. « Reliability Engineering : Probabilistic Models and Maintenance Methods ». Technometrics 48, no 3 (août 2006) : 446. http://dx.doi.org/10.1198/tech.2006.s412.
Texte intégralAbdallah, Wafaa, Jacqueline Saliba, Ziubir-Mehdi Sbartaï, Marwan Sadek, Fadi Hage Chehade et 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.
Texte intégralROMANCHENKO, Ihor S., Oleh SEMENENKO, Maryna SLIUSARENKO, Mykola VASIANOVYCH et Ihor LEVCHENKO. « On the development of mathematical models for the reliability evaluation of aircraft operation in combat conditions ». INCAS BULLETIN 13, S (3 août 2021) : 169–78. http://dx.doi.org/10.13111/2066-8201.2021.13.s.16.
Texte intégralYa-jun, Wang, et Wang Jun. « Generalised Reliability On Hydro-Geo Objects ». Open Civil Engineering Journal 9, no 1 (31 juillet 2015) : 498–503. http://dx.doi.org/10.2174/1874149501509010498.
Texte intégralGuo, R., et E. Love. « Reliability Modelling with Fuzzy Covariates ». International Journal of Reliability, Quality and Safety Engineering 10, no 02 (juin 2003) : 131–57. http://dx.doi.org/10.1142/s0218539303001056.
Texte intégralThèses sur le sujet "Reliability (Engineering) Mathematical models"
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.
Texte intégralThe 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.
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.
Texte intégralHashemolhosseini, Sepehr. « Algorithmic component and system reliability analysis of truss structures ». Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85710.
Texte intégralENGLISH 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.
LEE, SEUNG JOO. « RELIABILITY-BASED OPTIMAL STRUCTURAL AND MECHANICAL DESIGN ». Diss., The University of Arizona, 1987. http://hdl.handle.net/10150/184136.
Texte intégralJiang, Yu, et 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.
Texte intégralKim, 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.
Texte intégralCommittee Co-Chair: Peak, Russell; Committee Co-Chair: Sitaraman, Suresh; Committee Member: Paredis, Christiaan; Committee Member: Pucha, Raghuram; Committee Member: Wong, C.
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.
Texte intégralMalada, Awelani. « Stochastic reliability modelling for complex systems ». Thesis, Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-10182006-170927.
Texte intégralTorng, 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.
Texte intégralYim, Ka-wing, et 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.
Texte intégralLivres sur le sujet "Reliability (Engineering) Mathematical models"
Epstein, Benjamin. Mathematical models for systems reliability. Boca Raton : Taylor & Francis, 2008.
Trouver le texte intégralUshakov, I. A. Probabilistic reliability models. San Diego, CA : Wiley, 2012.
Trouver le texte intégralAven, T. Stochastic models in reliability. New York : Springer, 1999.
Trouver le texte intégralKuo, Way. Optimal Reliability Modeling. New York : John Wiley & Sons, Ltd., 2002.
Trouver le texte intégralNachlas, Joel A. Reliability engineering : Probabilistic models and maintenance methods. Boca Raton : Taylor & Francis, 2005.
Trouver le texte intégralKuo, Way. Optimal reliability modeling : Principles and applications. Hoboken, NJ : John Wiley & Sons, 2003.
Trouver le texte intégralBarlow, Richard E. Mathematical theory of reliability. Philadelphia : SIAM, 1996.
Trouver le texte intégralC, Ionescu D., et Limnios N, dir. Statistical and probabilistic models in reliability. Boston : Birkhäuser, 1999.
Trouver le texte intégralPereguda, A. I. Modeli, pokazateli i metody ikh vychislenii︠a︡ : Nauchnai︠a︡ monografii︠a︡. Obninsk : IATĖ, 2005.
Trouver le texte intégralBeichelt, Frank. Reliability and maintenance : Networks and systems. Boca Raton, FL : CRC Press, 2012.
Trouver le texte intégralChapitres de livres sur le sujet "Reliability (Engineering) Mathematical models"
Vonta, Filia, et Alex Karagrigoriou. « Information Measures in Biostatistics and Reliability Engineering ». Dans 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.
Texte intégralDhillon, B. S. « Mathematical models for engineering systems reliability analysis and usability assurance ». Dans 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.
Texte intégralDhillon, B. S. « Mathematical Models for Performing Human Reliability and Error Analysis in Power Plants ». Dans Springer Series in Reliability Engineering, 151–68. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04019-6_11.
Texte intégralChiodo, Elio, et Giovanni Mazzanti. « Mathematical and Physical Properties of Reliability Models in View of their Application to Modern Power System Components ». Dans Springer Series in Reliability Engineering, 59–140. London : Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-088-5_3.
Texte intégralFalcone, Domenico, Alessandro Silvestri, Gianpaolo Di Bona et Antonio Forcina. « Mathematical Models for Reliability Allocation and Optimization for Complex Systems ». Dans 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.
Texte intégralGreiner-Petter, André, Howard S. Cohl, Abdou Youssef, Moritz Schubotz, Avi Trost, Rajen Dey, Akiko Aizawa et Bela Gipp. « Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra Systems ». Dans 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.
Texte intégralMuir, Paul, et Jack Pew. « An Analysis of the Reliability of Error Control B-Spline Gaussian Collocation PDE Software ». Dans 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.
Texte intégralSantagati, Pietro, et Valeriu Beiu. « A Mathematical Model for the Analysis of the Johnson-Nyquist Thermal Noise on the Reliability in Nano-Communications ». Dans 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.
Texte intégralBirolini, Alessandro. « Basic Mathematical Statistics ». Dans Reliability Engineering, 435–64. Berlin, Heidelberg : Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03792-8_16.
Texte intégralBen-Haim, Yakov. « Reliability of Mathematical Models ». Dans 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.
Texte intégralActes de conférences sur le sujet "Reliability (Engineering) Mathematical models"
Bobalo, Yuriy, Leonid Nedostup, Oxana Lazko et Volodymyr Glemba. « Mathematical models of reliability of components parametrical synthesis ». Dans 2006 International Conference - Modern Problems of Radio Engineering, Telecommunications, and Computer Science. IEEE, 2006. http://dx.doi.org/10.1109/tcset.2006.4404645.
Texte intégralKoltover, Vitaly K. « Mathematical Theory of Reliability and Aging : Teaching Comes from Kiev ». Dans 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.
Texte intégralVikram Kumar Kamboj, Amit Bhardwaj, Harkamaljeet Singh Bhullar, Krishan Arora et Kulraj Kaur. « Mathematical model of reliability assessment for generation system ». Dans 2012 IEEE International Power Engineering and Optimization Conference (PEOCO). IEEE, 2012. http://dx.doi.org/10.1109/peoco.2012.6231118.
Texte intégralKakubava, Revaz, Archil Prangishvili et Grigol Sokhadze. « Closed and Mixed Type Queuing Systems as Mathematical Models of Reliability and Survivability ». Dans 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.
Texte intégralKlymash, Mykhailo, et Roman Pavlyuk. « The Methodology of Determination of SDH-Network Structural Reliability. Mathematical and Imitating Models ». Dans 2006 International Conference - Modern Problems of Radio Engineering, Telecommunications, and Computer Science. IEEE, 2006. http://dx.doi.org/10.1109/tcset.2006.4404641.
Texte intégralHao, Guangbo, et Liyang Xie. « Reliability Mathematical Model of Continuous System Based on Segment-Partition ». Dans ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86857.
Texte intégralJiankang, Dong, Ma Hongyan, Chen Jingjie et Liu Jiaxue. « Mathematical Model of Aircraft Reliability Based on Fault Diagnosis ». Dans 2010 International Conference on Intelligent System Design and Engineering Application (ISDEA). IEEE, 2010. http://dx.doi.org/10.1109/isdea.2010.330.
Texte intégralPandey, Vijitashwa. « Quantum Mechanical Perspectives in Reliability Engineering and System Design ». Dans 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.
Texte intégralBaghdasaryan, Lusine, Wei Chen, Thaweepat Buranathiti et Jian Cao. « Model Validation via Uncertainty Propagation Using Response Surface Models ». Dans 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.
Texte intégralGliklikh, Yuri. « Stochastic Equations and Inclusions with Mean Derivatives and Their Applications to Mathematical Physics ». Dans 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.
Texte intégralRapports d'organisations sur le sujet "Reliability (Engineering) Mathematical models"
Modlo, Yevhenii O., Serhiy O. Semerikov, Stanislav L. Bondarevskyi, Stanislav T. Tolmachev, Oksana M. Markova et 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.], février 2020. http://dx.doi.org/10.31812/123456789/3677.
Texte intégralMarkova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko et Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], septembre 2019. http://dx.doi.org/10.31812/123456789/3270.
Texte intégralTucker-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, juillet 2020. http://dx.doi.org/10.52012/tyob9090.
Texte intégralSemerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev et Arnold Kiv. Computer Simulation of Neural Networks Using Spreadsheets : Dr. Anderson, Welcome Back. [б. в.], juin 2019. http://dx.doi.org/10.31812/123456789/3178.
Texte intégralEFFECT OF RANDOM PRE-STRESSED FRICTION LOSS ON THE PERFORMANCE OF A SUSPEN-DOME STRUCTURE. The Hong Kong Institute of Steel Construction, mars 2022. http://dx.doi.org/10.18057/ijasc.2022.18.1.5.
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