Estimating fibres’ material parameter distributions from limited data with the help of Bayesian inference
暂无分享,去创建一个
[1] Tshilidzi Marwala,et al. Finite Element Model Updating Using Bayesian Framework and Modal Properties , 2005 .
[2] Constantinos Soutis,et al. Generation of Micro-scale Finite Element Models from Synchrotron X-ray CT Images for Multidirectional Carbon Fibre Reinforced Composites , 2016 .
[4] K. Ip,et al. Parameter estimation of orthotropic plates by Bayesian sensitivity analysis , 1996 .
[5] Cwj Cees Oomens,et al. Multi-scale mechanical characterization of scaffolds for heart valve tissue engineering. , 2012, Journal of biomechanics.
[6] Laurent Orgéas,et al. Towards the 3D in situ characterisation of deformation micro-mechanisms within a compressed bundle of fibres , 2011 .
[7] R. C. Picu. Mechanics of random fiber networks—a review , 2011 .
[8] Andrew Gelman,et al. Handbook of Markov Chain Monte Carlo , 2011 .
[9] Francesco Ubertini,et al. Estimation of elastic constants of thick laminated plates within a Bayesian framework , 2007 .
[10] P. S. Koutsourelakis,et al. A novel Bayesian strategy for the identification of spatially varying material properties and model validation: an application to static elastography , 2012, 1512.05913.
[11] Tetsu Uesaka,et al. Direct simulations of fiber network deformation and failure , 2012 .
[12] K. D. Murphy,et al. A Bayesian Approach to Identifying Structural Nonlinearity using Free-Decay Response: Application to Damage Detection in Composites , 2010 .
[13] R. C. Picu,et al. Size effect on mechanical behavior of random fiber networks , 2013 .
[14] Christopher M. Bishop,et al. Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .
[15] Oriol Roch,et al. Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market , 2006, Comput. Stat. Data Anal..
[16] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[17] Patrick Ienny,et al. Mechanical properties and non-homogeneous deformation of open-cell nickel foams: application of the mechanics of cellular solids and of porous materials , 2000 .
[18] F. Delannay,et al. Elastic anisotropy of a transversely isotropic random network of interconnected fibres: non-triangulated network model , 2004 .
[19] X. Cheng,et al. Mechanics of Stochastic Fibrous Networks , 1998 .
[20] A. Vautrin,et al. Bayesian Identification of Elastic Constants in Multi-Directional Laminate from Moiré Interferometry Displacement Fields , 2012, Experimental Mechanics.
[21] Werner Hürlimann,et al. Fitting Bivariate Cumulative Returns with Copulas , 2002, Comput. Stat. Data Anal..
[22] James L. Beck,et al. Bayesian Updating and Model Class Selection for Hysteretic Structural Models Using Stochastic Simulation , 2008 .
[23] Raphael T. Haftka,et al. Introduction to the Bayesian Approach Applied to Elastic Constants Identification , 2010 .
[24] Mgd Marc Geers,et al. A multiscale quasicontinuum method for lattice models with bond failure and fiber sliding , 2014 .
[25] Pascal Bouvry,et al. Management of an academic HPC cluster: The UL experience , 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).
[26] Mgd Marc Geers,et al. Predicting hygro-elastic properties of paper sheets based on an idealized model of the underlying fibrous network , 2015 .
[27] Laurent Orgéas,et al. X-ray phase contrast microtomography for the analysis of the fibrous microstructure of SMC composites , 2008 .
[28] J. Beck. Bayesian system identification based on probability logic , 2010 .
[29] M. Shephard,et al. Effect of Fiber Crimp on the Elasticity of Random Fiber Networks With and Without Embedding Matrices. , 2016, Journal of applied mechanics.
[30] Stéphane Bordas,et al. Bayesian inference to identify parameters in viscoelasticity , 2018 .
[31] C. Genest,et al. A semiparametric estimation procedure of dependence parameters in multivariate families of distributions , 1995 .
[32] M. Koblischka,et al. Microstructural Analysis of Electrochemical Coated Open‐Cell Metal Foams by EBSD and Nanoindentation , 2014 .
[33] Hedibert Freitas Lopes,et al. Copula, marginal distributions and model selection: a Bayesian note , 2008, Stat. Comput..
[34] R. Nelsen. An Introduction to Copulas , 1998 .
[35] J. Beck,et al. Updating Models and Their Uncertainties. I: Bayesian Statistical Framework , 1998 .
[36] Carlos González,et al. Damage micromechanisms and notch sensitivity of glass-fiber non-woven felts: An experimental and numerical study , 2010 .
[37] Chia-Wei Wang,et al. Structure, Mechanics and Failure of Stochastic Fibrous Networks: Part I—Microscale Considerations , 2000 .
[38] S. Bordas,et al. Open-cell aluminium foams with graded coatings as passively controllable energy absorbers , 2015 .
[39] Heikki Haario,et al. Adaptive proposal distribution for random walk Metropolis algorithm , 1999, Comput. Stat..
[40] Thomas Most,et al. Identification of the parameters of complex constitutive models: Least squares minimization vs. Bayesian updating , 2010 .
[41] Curt A. Bronkhorst,et al. Modelling paper as a two-dimensional elastic-plastic stochastic network , 2003 .
[42] Laa Lars Beex,et al. The mechanical reliability of an electronic textile investigated using the virtual-power-based quasicontinuum method , 2015 .
[43] Emmanuelle Vidal-Sallé,et al. Development of a new 3D beam element with section changes , 2015 .
[44] Jean-François Ganghoffer,et al. Discrete woven structure model: yarn-on-yarn friction , 2007 .
[45] R. C. Picu,et al. Scaling of nonaffine deformation in random semiflexible fiber networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.
[46] P. X. Song,et al. Multivariate Dispersion Models Generated From Gaussian Copula , 2000 .
[47] Martine Pithioux,et al. Numerical damage models using a structural approach: application in bones and ligaments , 2002 .
[49] K. F. Alvin,et al. Finite Element Model Update via Bayesian Estimation and Minimization of Dynamic Residuals , 1996 .
[50] H. Rappel,et al. Identifying elastoplastic parameters with Bayes’ theorem considering output error, input error and model uncertainty , 2019, Probabilistic Engineering Mechanics.
[51] Kyung K. Choi,et al. Identification of marginal and joint CDFs using Bayesian method for RBDO , 2009 .
[52] Siu-Kui Au,et al. Bayesian parameter identification of hysteretic behavior of composite walls , 2013 .
[53] M. Sklar. Fonctions de repartition a n dimensions et leurs marges , 1959 .
[54] Laa Lars Beex,et al. A discrete network model for bond failure and frictional sliding in fibrous materials , 2013 .