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Advances in peridynamics / Erdogan Madenci, Pranesh Roy, Deepak Behera.

Madenci, Erdogan, author.; Roy, Pranesh, author.; Behera, Deepak, author.
2022
TA352
Available Online
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Title
Advances in peridynamics / Erdogan Madenci, Pranesh Roy, Deepak Behera.
Author
Madenci, Erdogan, author.
ISBN
9783030978587 (electronic bk.)
3030978583 (electronic bk.)
9783030978570
DOI
https://doi.org/10.1007/978-3-030-97858-7
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (xvi, 422 pages) : illustrations (some color)
Item Number
10.1007/978-3-030-97858-7 doi
Call Number
TA352
Dewey Decimal Classification
620.1/123
Summary
This book presents recent improvements in peridynamic modeling of structures. It provides sufficient theory and numerical implementation helpful to both new and existing researchers in the field. The main focus of the book is on the non-ordinary state-based (NOSB) peridynamics (PD) and its applications for performing finite deformation. It presents the framework for modeling high stretch polymers, viscoelastic materials, thermoelasticity, plasticity, and creep. It provides a systematic derivation for dimensionally reduced structures such as axisymmetric structures and beams. Also, it presents a novel approach to impose boundary conditions without suffering from displacement kinks near the boundary. Furthermore, it presents refinements to bond-based PD model by including rotation kinematics for modeling isotropic and composite materials. Moreover, it presents a PD - FEM coupling framework in ANSYS based on principle for virtual work. Lastly, it presents an application of neural networks in the peridynamic (PINN) framework. Sample codes are provided for readers to develop hands-on experience on peridynamic modeling. Describes new developments in peridynamics and their applications in the presence of material and geometric nonlinearity; Describes an approach to seamlessly couple PD with FE; Introduces the use of the neural network in the PD framework to solve engineering problems; Provides theory and numerical examples for researchers and students to self-study and apply in their research (Codes are provided as supplementary material); Provides theoretical development and numerical examples suitable for graduate courses.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 26, 2022).
Added Author
Roy, Pranesh, author.
Behera, Deepak, author.
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Introduction
Peridynamic Differential Operator
Refinements In Bond-Based Peridynamics
Refinements In Ordinary State-Based Peridynamics
Weak Form Of Peridynamics
Bond-Associated State-Based Peridynamics (Ba-Sb Pd)
Ba-Sb Pd For Thermoelastic Deformation
Ba-Sb Pd For Elastic- Plastic Deformation
Ba-Sb Pd For Viscoleastic And Creep Deformation
Ba-Sb Pd For Hyperelastic Deformation
Ba-Sb Pd For Visco-Hyperelastic Deformation
Ba-Sb Pd Modeling For Damage In Quasi-Brittle Materials
Ba-Sb Pd Modeling For Impact Analysis
Ba-Sb Pd Modeling Of Plates And Shells
Ba-Sb Pd Modeling Under Axisymmetric Idealization
Peridynamics For Multi-Scale Modeling
Peridynamics For Machine Learning
Peridynamics Coupled With Fem In Ansys Framework.

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