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Advances in Predictive Models and Methodologies for Numerically Efficient Linear and Nonlinear Analysis of Composites

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Cover of 'Advances in Predictive Models and Methodologies for Numerically Efficient Linear and Nonlinear Analysis of Composites'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Variable Kinematic Shell Formulations Accounting for Multi-field Effects for the Analysis of Multi-layered Structures
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    Chapter 3 Bistable Buckled Beam-Like Structures by One-Dimensional Hierarchical Modeling
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    Chapter 4 Multiscale Nonlinear Analysis of Beam Structures by Means of the Carrera Unified Formulation
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    Chapter 5 On the Effectiveness of Higher-Order One-Dimensional Models for Physically Nonlinear Problems
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    Chapter 6 Post-buckling Progressive Failure Analysis of Composite Panels Using a Two-Way Global-Local Coupling Approach Including Intralaminar Failure and Debonding
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    Chapter 7 Mesoscale Hyperelastic Model of a Single Yarn Under High Velocity Transverse Impact
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    Chapter 8 Structural Health Monitoring: Numerical Simulation of Lamb Waves Via Higher-Order Models
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    Chapter 9 Improving the Static Structural Performance of Panels with Spatially Varying Material Properties Using Correlations
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    Chapter 10 Multiscale Identification of Material Properties for Anisotropic Media: A General Inverse Approach
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    Chapter 11 Metamodel-Based Uncertainty Quantification for the Mechanical Behavior of Braided Composites
Attention for Chapter 7: Mesoscale Hyperelastic Model of a Single Yarn Under High Velocity Transverse Impact
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5 Mendeley
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Chapter title
Mesoscale Hyperelastic Model of a Single Yarn Under High Velocity Transverse Impact
Chapter number 7
Book title
Advances in Predictive Models and Methodologies for Numerically Efficient Linear and Nonlinear Analysis of Composites
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-030-11969-0_7
Book ISBNs
978-3-03-011968-3, 978-3-03-011969-0
Authors

P. Del Sorbo, J. Girardot, F. Dau, I. Iordanoff, Del Sorbo, P., Girardot, J., Dau, F., Iordanoff, I.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Professor > Associate Professor 1 20%
Unknown 2 40%
Readers by discipline Count As %
Engineering 2 40%
Computer Science 1 20%
Unknown 2 40%

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