Дисертації з теми "Spectral stochastic finite element"
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Fink, Sebastian [Verfasser]. "Simulation of elastic-plastic material behaviour with uncertain material parameters : a spectral stochastic finite element method approach / Sebastian Fink." Hannover : Technische Informationsbibliothek (TIB), 2015. http://d-nb.info/1095501860/34.
Повний текст джерелаAdam, Alexandros. "Finite element, adaptive spectral wave modelling." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/45307.
Повний текст джерелаBakhtiari, Siamak. "Stochastic finite element slope stability analysis." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/stochastic-finite-element-slope-stability-analysis(c1b451d9-8bf6-43ff-9c10-7b5209fb45c1).html.
Повний текст джерелаUllmann, Elisabeth. "Solution strategies for stochastic finite element discretizations." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2009. http://nbn-resolving.de/urn:nbn:de:bsz:105-8042820.
Повний текст джерелаSavvides, Abraham. "Application of two-dimensional spectral/finite-difference and spectral/hp finite-element methods to cylinder flows." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264204.
Повний текст джерелаXiao, Dong Wen. "Efficiency analysis on element decomposition method for stochastic finite element analysis." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1636334.
Повний текст джерелаStarkloff, Hans-Jörg. "Stochastic finite element method with simple random elements." Universitätsbibliothek Chemnitz, 2008. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200800596.
Повний текст джерелаParvini, Mehdi. "Pavement deflection analysis using stochastic finite element method." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0014/NQ42757.pdf.
Повний текст джерелаZheng, Yuquan. "Stochastic finite element analysis of continuous elastic systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0002/MQ42231.pdf.
Повний текст джерелаParvini, Mehdi. "Pavement deflection analysis using stochastic finite element method /." *McMaster only, 1997.
Знайти повний текст джерелаSachdeva, Sachin K. "Subspace projection schemes for stochastic finite element analysis." Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/72061/.
Повний текст джерелаLi, Chenfeng. "Stochastic finite element modelling of elementary random media." Thesis, Swansea University, 2006. https://cronfa.swan.ac.uk/Record/cronfa42770.
Повний текст джерелаAntypas, Dionyssios. "Structural response modelling using the stochastic finite element method." Thesis, Imperial College London, 2002. http://hdl.handle.net/10044/1/8314.
Повний текст джерелаMahadevan, Sankaran. "Stochastic finite element-based structural reliability analysis and optimization." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/19517.
Повний текст джерелаValenciano, Rubio Jose L. "Adaptive spectral element methods for swirling Newtonian flows." Thesis, Edinburgh Napier University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285227.
Повний текст джерелаKhodaparast, Hamed Haddad. "Stochastic finite element model updating and its application in aeroelasticity." Thesis, University of Liverpool, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548785.
Повний текст джерелаNešpůrek, Lukáš. "STOCHASTIC CRACK PROPAGATION MODELLING USING THE EXTENDED FINITE ELEMENT METHOD." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-233900.
Повний текст джерелаWeber, Marc Anton. "Stochastic structural analysis of engineering components using the finite element method." Doctoral thesis, University of Cape Town, 1993. http://hdl.handle.net/11427/8476.
Повний текст джерелаThis thesis investigates probabilistic and stochastic methods for structural analysis which can be integrated into existing, commercially available finite element programs. It develops general probabilistic finite element routines which can be implemented within deterministic finite element programs without requiring major code development. These routines are implemented in the general purpose finite element program ABAQUS through its user element subroutine facility and two probabilistic finite elements are developed: a three-dimensional beam element limited to linear material behaviour and a two-dimensional plane element involving elastic-plastic material behaviour. The plane element incorporates plane strain, plane stress and axisymmetric formulations. The numerical accuracy and robustness of the routines are verified and application of the probabilistic finite element method is illustrated in two case studies, one involving a four-story, two-bay frame structure, the other a reactor pressure vessel nozzle. The probabilistic finite element routines developed in this thesis integrate point estimate methods and mean value first order methods within the same program. Both methods require a systematic sequence involving the perturbation of the random parameters to be evaluated, although the perturbation sequence of the methods differ. It is shown that computer-time saving techniques such as Taylor series and iterative perturbation schemes, developed for mean value based methods, can also be used to solve point estimate method problems. These efficient techniques are limited to linear problems; nonlinear problems must use full perturbation schemes. Finally, it is shown that all these probabilistic methods and perturbation schemes can be integrated within one program and can follow many of the existing deterministic program structures and subroutines. An overall strategy for converting deterministic finite element programs to probabilistic finite element programs is outlined.
Breakah, Tamer M. "Stochastic finite element analysis of moisture damage in hot mix asphalt." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3389089.
Повний текст джерелаOliver, Robin. "A stochastic finite element model for the dynamics of globular proteins." Thesis, University of Leeds, 2013. http://etheses.whiterose.ac.uk/5555/.
Повний текст джерелаHuh, Jungwon. "Dynamic reliability analysis for nonlinear structures using stochastic finite element method." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/289087.
Повний текст джерелаCitrain, Aurélien. "Hybrid finite element methods for seismic wave simulation : coupling of discontinuous Galerkin and spectral element discretizations." Thesis, Normandie, 2019. http://www.theses.fr/2019NORMIR28.
Повний текст джерелаTo solve wave equations in heterogeneous media with finite elements with a reasonable numerical cost, we couple the Discontinuous Galerkin method (DGm) with Spectral Elements method (SEm). We use hybrid meshes composed of tetrahedra and structured hexahedra. The coupling is carried out starting from a mixed-primal DG formulation applied on a hybrid mesh composed of a hexahedral macro-element and a sub-mesh composed of tetrahedra. The SEm is applied in the macro-element paved with structured hexahedrons and the coupling is ensured by the DGm numerical fluxes applied on the internal faces of the macro-element common with the tetrahedral mesh. The stability of the coupled method is demonstrated when time integration is performed with a Leap-Frog scheme. The performance of the coupled method is studied numerically and it is shown that the coupling reduces numerical costs while keeping a high level of accuracy. It is also shown that the coupled formulation can stabilize the DGm applied in areas that include Perfectly Matched Layers
Klenow, Bradley. "Finite and Spectral Element Methods for Modeling Far-Field Underwater Explosion Effects on Ships." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/37648.
Повний текст джерелаPh. D.
Guo, Xiu Xiu. "Finite element analysis of nonlinear stochastic oscillators with Poisson white noise excitation." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2182943.
Повний текст джерелаKundu, Abhishek. "Efficient uncertainty propagation schemes for dynamical systems with stochastic finite element analysis." Thesis, Swansea University, 2014. https://cronfa.swan.ac.uk/Record/cronfa42292.
Повний текст джерелаLee, Jangwoon. "Analysis and finite element approximations of stochastic optimal control problems constrained by stochastic elliptic partial differential equations." [Ames, Iowa : Iowa State University], 2008.
Знайти повний текст джерелаNizamiev, Kamil. "Stochastic Galerkin Model Updating of Randomly Distributed Parameters." University of Akron / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=akron1302884328.
Повний текст джерелаMousavi, Nezhad Mohaddeseh. "Stochastic finite element modelling of flow and solute transport in dual domain system." Thesis, University of Exeter, 2010. http://hdl.handle.net/10036/111704.
Повний текст джерелаZhang, Wu. "Adaptive stochastic finite element procedure of electronic packaging problems using disturbed state concept." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282373.
Повний текст джерелаZhou, Yiguang. "Efficient stochastic finite element method for the reliability analysis of nonlinear frame structures." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185746.
Повний текст джерелаWang, Donghai. "Gaussian Finite Element Closure of Steady State Unsaturated Flow in Randomly Heterogeneous Soils." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1331%5F1%5Fm.pdf&type=application/pdf.
Повний текст джерелаCarella, Alfredo Raúl. "Spectral Finite Element Methods for solving Fractional Differential Equations with applications in Anomalous Transport." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-17656.
Повний текст джерелаMardyanto, Mas Agus. "A solution to an inverse problem of groundwater flow using stochastic finite element method." Thesis, University of Ottawa (Canada), 2004. http://hdl.handle.net/10393/29139.
Повний текст джерелаGao, Liwei. "Stochastic finite element method for the reliability analysis of nonlinear frames with PR connections." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186898.
Повний текст джерелаJeisman, Joseph Ian. "Estimation of the parameters of stochastic differential equations." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16205/1/Joseph_Jesiman_Thesis.pdf.
Повний текст джерелаJeisman, Joseph Ian. "Estimation of the parameters of stochastic differential equations." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16205/.
Повний текст джерелаFitzgerald, Anthony P. "A general variational principle for random and fields in elastic solid mechanics." Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/21462.
Повний текст джерелаBanz, Lothar [Verfasser]. "hp-finite element and boundary element methods for elliptic, elliptic stochastic, parabolic and hyperbolic obstacle and contact problems / Lothar Banz." Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2012. http://d-nb.info/1022752340/34.
Повний текст джерелаBaingo, Darek. "A Framework for Stochastic Finite Element Analysis of Reinforced Concrete Beams Affected by Reinforcement Corrosion." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23063.
Повний текст джерелаScinocca, Francisco. "Uncertainty quantification of aircraft modal analysis using perturbation technique in the stochastic finite element method." Instituto Tecnológico de Aeronáutica, 2012. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=2062.
Повний текст джерелаJeong, Gi Young. "Tensile Properties of Loblolly Pine Strands Using Digital Image Correlation and Stochastic Finite Element Method." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/29563.
Повний текст джерелаPh. D.
Dechamps, Xavier. "Numerical simulation of incompressible magnetohydrodynamic duct and channel flows by a hybrid spectral, finite element solver." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209203.
Повний текст джерелаDoctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Zeng, Wei. "Advanced Development of Smoothed Finite Element Method (S-FEM) and Its Applications." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309306.
Повний текст джерелаBirgersson, Fredrik. "Prediction of random vibration using spectral methods." Doctoral thesis, KTH, Aeronautical and Vehicle Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3694.
Повний текст джерелаMuch of the vibration in fast moving vehicles is caused bydistributed random excitation, such as turbulent flow and roadroughness. Piping systems transporting fast flowing fluid isanother example, where distributed random excitation will causeunwanted vibration. In order to reduce these vibrations andalso the noise they cause, it is important to have accurate andcomputationally efficient prediction methods available.
The aim of this thesis is to present such a method. Thefirst step towards this end was to extend an existing spectralfinite element method (SFEM) to handle excitation of planetravelling pressure waves. Once the elementary response tothese waves is known, the response to arbitrary homogeneousrandom excitation can be found.
One example of random excitation is turbulent boundary layer(TBL) excitation. From measurements a new modified Chase modelwas developed that allowed for a satisfactory prediction ofboth the measured wall pressure field and the vibrationresponse of a turbulence excited plate. In order to model morecomplicated structures, a new spectral super element method(SSEM) was formulated. It is based on a waveguide formulation,handles all kinds of boundaries and its elements are easily putinto an assembly with conventional finite elements.
Finally, the work to model fluid-structure interaction withanother wave based method is presented. Similar to the previousmethods it seems to be computationally more efficient thanconventional finite elements.
Khokhar, Zahid R. "Finite-element analysis of delamination in CFRP laminates : effect of material randomness." Thesis, Loughborough University, 2010. https://dspace.lboro.ac.uk/2134/6125.
Повний текст джерелаLocatelli, Marco. "Order reduction strategies for stochastic Galerkin matrix equations." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15881/.
Повний текст джерелаLan, Shuang Wen. "Stochastic finite element analysis of structures with elementary stiffness matrix decomposition method and exponential polynomial moment method." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148241.
Повний текст джерелаHaque, Md Zakiul. "A combined experimental and stochastic finite element analysis methodology for the probabilistic fracture behavior of composite laminates." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0017/MQ47836.pdf.
Повний текст джерелаTraverso, Luca. "Mixed finite element and stochastic Galerkin methods for groundwater flow modelling : efficiency analysis and real-life application." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55531/.
Повний текст джерелаKaravelić, Emir. "Stochastic Galerkin finite element method in application to identification problems for failure models parameters in heterogeneous materials." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2501.
Повний текст джерелаThis thesis deals with the localized failure for structures built of heterogeneous composite material, such as concrete, at two different scale. These two scale are latter connected through the stochastic upscaling, where any information obtained at meso-scale are used as prior knowledge at macro-scale. At meso scale, lattice model is used to represent the multi-phase structure of concrete, namely cement and aggregates. The beam element represented by 3D Timoshenko beam embedded with strong discontinuities ensures complete mesh independency of crack propagation. Geometry of aggregate size is taken in agreement with EMPA and Fuller curve while Poisson distribution is used for spatial distribution. Material properties of each phase is obtained with Gaussian distribution which takes into account the Interface Transition Zone (ITZ) through the weakening of concrete. At macro scale multisurface plasticity model is chosen that takes into account both the contribution of a strain hardening with non-associative flow rule as well as a strain softening model components for full set of different 3D failure modes. The plasticity model is represented with Drucker-Prager yield criterion, with similar plastic potential function governing hardening behavior while strain softening behavior is represented with St. Venant criterion. The identification procedure for macro-scale model is perfomed in sequential way. Due to the fact that all ingredients of macro-scale model have physical interpretation we made calibration of material parameters relevant to particular stage. This approach is latter used for model reduction from meso-scale model to macro-scale model where all scales are considered as uncertain and probability computation is performed. When we are modeling homogeneous material each unknown parameter of reduced model is modeled as a random variable while for heterogeneous material, these material parameters are described as random fields. In order to make appropriate discretizations we choose p-method mesh refinement over probability domain and h-method over spatial domain. The forward model outputs are constructed by using Stochastic Galerkin method providing outputs more quickly the the full forward model. The probabilistic procedure of identification is performed with two different methods based on Bayes’s theorem that allows incorporating new observation generated in a particular loading program. The first method Markov Chain Monte Carlo (MCMC) is identified as updating the measure, whereas the second method Polynomial Chaos Kalman Filter (PceKF) is updating the measurable function. The implementation aspects of presented models are given in full detail as well as their validation throughthe numerical examples against the experimental results or against the benchmarks available from literature