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Topics in Experimental Dynamics Substructuring and Wind Turbine Dynamics, Volume 2

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Cover of 'Topics in Experimental Dynamics Substructuring and Wind Turbine Dynamics, Volume 2'

Table of Contents

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    Book Overview
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    Chapter 1 Tutorial on Experimental Dynamic Substructuring Using the Transmission Simulator Method
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    Chapter 2 Experimental–Analytical Substructure Model Sensitivity Analysis for Cutting Machine Chatter Prediction
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    Chapter 3 Eliminating Indefinite Mass Matrices with the Transmission Simulator Method of Substructuring
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    Chapter 4 Using Substructuring to Predict the Human Hand Influence on a Mechanical Structure
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    Chapter 5 Simple Experiments to Validate Modal Substructure Models
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    Chapter 6 Experimental Realization of System-Level Vibration by Use of Single Component Based on Virtual Boundary Condition Concept
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    Chapter 7 An Introduction to the SEM Substructures Focus Group Test Bed – The Ampair 600 Wind Turbine
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    Chapter 8 Modal Assessment of Wind Turbine Blade in Preparation of Experimental Substructuring
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    Chapter 9 Comparison of Some Wind Turbine Blade Tests in Various Configurations
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    Chapter 10 Consideration of Interface Damping in Dynamic Substructuring
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    Chapter 11 Direct Hybrid Formulation for Substructure Decoupling
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    Chapter 12 Substructuring with Nonlinear Subcomponents: A Nonlinear Normal Mode Perspective
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    Chapter 13 An Effective Method for Assembling Impulse Response Functions to Linear and Non-linear Finite Element Models
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    Chapter 14 Truncating the Impulse Responses of Substructures to Speed Up the Impulse-Based Substructuring
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    Chapter 15 Application of Residual Vectors to Superelement Modeling of an Offshore Wind Turbine Foundation
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    Chapter 16 Demonstrating Predictive Capability of Validated Wind Turbine Blade Models
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    Chapter 17 Towards the Experimental Assessment of NLBeam for Modeling Large Deformation Structural Dynamics
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    Chapter 18 Wind Turbine Experimental Dynamic Substructure Development
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    Chapter 19 Validation of a Finite Element Model Used for Dynamic Stress–Strain Prediction
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    Chapter 20 Dynamic Stress–Strain on Turbine Blade Using Digital Image Correlation Techniques Part 1: Static Load and Calibration
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    Chapter 21 Dynamic Stress–Strain on Turbine Blades Using Digital Image Correlation Techniques Part 2: Dynamic Measurements
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    Chapter 22 Structural Health Monitoring of Wind Turbine Blades Under Fatigue Loads
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    Chapter 23 Dynamic Characterization of Whisper 500 Turbine Blade
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    Chapter 24 Developing a Finite Element Model in Conjunction with Modal Test for Wind Turbine Blade Models
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    Chapter 25 Dynamic Stress-Strain Prediction from Limited Measurements in the Presence of Structural Defects
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    Chapter 26 On the Mode Based Simulation of Dry Friction inside Lap Joints
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    Chapter 27 Efficient Updating of Static Modes in the Craig-Bampton Reduction Basis
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    Chapter 28 Comparison of CMS, Krylov and Balanced Truncation Based Model Reduction from a Mechanical Application Engineer’s Perspective
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    Chapter 29 Vertical Axis Wind Turbine Operational Modal Analysis in Sheared Wind Flow
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    Chapter 30 Output-Only Estimation of Wind Induced Stresses in Structures
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    Chapter 31 Modal Testing of 9 m CX-100 Turbine Blades
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Title
Topics in Experimental Dynamics Substructuring and Wind Turbine Dynamics, Volume 2
Published by
Springer New York, April 2012
DOI 10.1007/978-1-4614-2422-2
ISBNs
978-1-4614-2421-5, 978-1-4614-2422-2
Editors

Mayes, R., Rixen, D., Griffith, D.T., De Klerk, D., Chauhan, S., Voormeeren, S.N., Allen, M.S.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Italy 1 2%
Singapore 1 2%
Unknown 53 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 41%
Student > Master 10 17%
Researcher 7 12%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Other 5 9%
Unknown 6 10%
Readers by discipline Count As %
Engineering 44 76%
Computer Science 2 3%
Energy 2 3%
Physics and Astronomy 1 2%
Materials Science 1 2%
Other 1 2%
Unknown 7 12%