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Advances in peridynamics

Madenci, Erdogan.

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Advances in peridynamics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in peridynamics/ by Erdogan Madenci, Pranesh Roy, Deepak Behera.
Author:	Madenci, Erdogan.
other author:	Roy, Pranesh.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xvi, 422 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Continuum mechanics. -
Online resource:	https://doi.org/10.1007/978-3-030-97858-7
ISBN:	9783030978587

Advances in peridynamics
Madenci, Erdogan.

Advances in peridynamics[electronic resource] /by Erdogan Madenci, Pranesh Roy, Deepak Behera. - Cham :Springer International Publishing :2022. - xvi, 422 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9783030978587

Standard No.: 10.1007/978-3-030-97858-7doiSubjects--Topical Terms:

535472
Continuum mechanics.

LC Class. No.: TA352 / .M33 2022

Dewey Class. No.: 620.1123

Advances in peridynamics
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100 1 $a Madenci, Erdogan. $3 2055823
245 1 0 $a Advances in peridynamics $h [electronic resource] / $c by Erdogan Madenci, Pranesh Roy, Deepak Behera.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xvi, 422 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Continuum mechanics. $3 535472
650 0 $a Dynamics. $3 519830
650 1 4 $a Mathematical Physics. $3 1542352
650 2 4 $a Engineering Mechanics. $3 3538834
650 2 4 $a Engineering Mathematics. $3 3301900
650 2 4 $a Applied Dynamical Systems. $3 3538870
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Roy, Pranesh. $3 3599775
700 1 $a Behera, Deepak. $3 3599776
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-97858-7
950 $a Physics and Astronomy (SpringerNature-11651)