Stochastic Elasticity

Stochastic Elasticity
Author :
Publisher : Springer Nature
Total Pages : 283
Release :
ISBN-10 : 9783031066924
ISBN-13 : 3031066928
Rating : 4/5 (928 Downloads)

Book Synopsis Stochastic Elasticity by : L. Angela Mihai

Download or read book Stochastic Elasticity written by L. Angela Mihai and published by Springer Nature. This book was released on 2022-09-01 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic elasticity is a fast developing field that combines nonlinear elasticity and stochastic theories in order to significantly improve model predictions by accounting for uncertainties in the mechanical responses of materials. However, in contrast to the tremendous development of computational methods for large-scale problems, which have been proposed and implemented extensively in recent years, at the fundamental level, there is very little understanding of the uncertainties in the behaviour of elastic materials under large strains. Based on the idea that every large-scale problem starts as a small-scale data problem, this book combines fundamental aspects of finite (large-strain) elasticity and probability theories, which are prerequisites for the quantification of uncertainties in the elastic responses of soft materials. The problems treated in this book are drawn from the analytical continuum mechanics literature and incorporate random variables as basic concepts along with mechanical stresses and strains. Such problems are interesting in their own right but they are also meant to inspire further thinking about how stochastic extensions can be formulated before they can be applied to more complex physical systems.


Stochastic Elasticity Related Books

Stochastic Elasticity
Language: en
Pages: 283
Authors: L. Angela Mihai
Categories: Mathematics
Type: BOOK - Published: 2022-09-01 - Publisher: Springer Nature

DOWNLOAD EBOOK

Stochastic elasticity is a fast developing field that combines nonlinear elasticity and stochastic theories in order to significantly improve model predictions
Parameter Estimation in Stochastic Volatility Models
Language: en
Pages: 634
Authors: Jaya P. N. Bishwal
Categories: Mathematics
Type: BOOK - Published: 2022-08-06 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While
Finite Element Methods for Structures with Large Stochastic Variations
Language: en
Pages: 282
Authors: Isaac Elishakoff
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2003 - Publisher: Oxford University Press, USA

DOWNLOAD EBOOK

The finite element method (FEM) can be successfully applied to various field problems in solid mechanics, fluid mechanics and electrical engineering. This text
Data-driven Modelling of Structured Populations
Language: en
Pages: 329
Authors: Stephen P. Ellner
Categories: Mathematics
Type: BOOK - Published: 2016-05-13 - Publisher: Springer

DOWNLOAD EBOOK

This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a l
Uncertainty Quantification
Language: en
Pages: 329
Authors: Christian Soize
Categories: Computers
Type: BOOK - Published: 2017-04-24 - Publisher: Springer

DOWNLOAD EBOOK

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale