Whole assembled shear panel

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Table of contents

Introduction 
1.1 Context
1.2 Objectives
1.3 Strategy
1.4 Positioning
1.5 Structure of the document
2 Vibroacoustic problem 
2.1 Introduction
2.2 Definition of the vibroacoustic system
2.3 Boundary value problem for the vibroacoustic system
2.3.1 Structure
2.3.2 Internal dissipative acoustic fluid
2.3.3 Poroelastic medium
2.4 Computational model for the vibroacoustic problem
2.4.1 Finite element implementation
2.4.2 Computational model
2.5 Alternative computational model with limp frame poroelastic medium modeled as an equivalent fluid
2.6 Conclusion
3 Overview of lightweight structural materials and identification from experimental measurements
3.1 Introduction
3.2 System parameters identification problem
3.2.1 Definition of the admissible set for the structural system parameters
3.2.2 Definition of the optimisation problem
3.3 Validation of the computational model and identification of the elastic parameters for typical lightweight building elements
3.3.1 Wooden beams
3.3.2 Lightweight boards
3.4 Conclusion
4 Flexible connection model and experimental identification 
4.1 Introduction
4.2 Computational model for flexible mounting
4.3 Experimental identification of mounting parameters
4.3.1 Assembly of beam elements
4.3.2 Assembly of one oriented strand board and beam elements
4.4 Whole assembled shear panel
4.5 Conclusion
5 Reduced order computational model for the vibroacoustic problem 
5.1 Introduction
5.2 Reduced order model for the structure
5.2.1 Construction of the truncated projection basis
5.2.2 Generalized matrices for the reduced order model
5.3 Reduced order model for the internal acoustic fluid
5.3.1 Construction of the truncated projection basis
5.3.2 Generalized matrices for the reduced order model
5.4 Reduced order model for the poroelastic medium modeled as coupled solid and fluid phases with displacements as primary variables
5.4.1 Construction of the truncated projection basis
5.4.2 Generalized matrices for the reduced order model
5.4.3 Comparison of dierent reduction strategies for a poroelastic medium coupled with an acoustic cavity
5.5 Reduced order model for the poroelastic medium modeled as an equivalent fluid with pressure as the primary variable
5.5.1 Construction of the truncated projection basis
5.5.2 Generalized matrices for the reduced order model
5.6 Assembled reduced order computational models
5.7 Conclusion
6 Probabilistic approach of uncertainties for the computational model and identification 
6.1 Introduction
6.2 Stochastic computational model and uncertainty quantification
6.2.1 Stochastic reduced order computational model
6.2.2 Convergence of the random solution
6.2.3 Confidence regions for the observables
6.3 Generalized probabilistic approach of uncertainties
6.4 Probabilistic approach of system parameters uncertainties
6.4.1 Prior probabilistic model of uncertainties for the structure parameters
6.4.2 Strategies for the identification of the prior probabilistic model hyperparameters from experimental measurement 6.4.3 Identification of the prior probabilistic model hyperparameters for typical structural lightweight components
6.5 Uncertainty quantification for a shear panel and comparison with experimental measurements
6.5.1 Mean model taking into account flexible connections
6.5.2 Mean model including modeling errors induced by perfectly rigid connections .
6.6 Conclusion
7 Airborne sound insulation 
7.1 Introduction
7.2 Model for the evaluation of airborne sound insulation
7.2.1 Parallelepiped room model
7.2.2 Analytical modal expansion of the pressure field in the rooms
7.2.3 Decoupled approach for the evaluation of the sound reduction index
7.2.4 Concluding remarks about the approach
7.3 Application to double parting wall separative systems
7.3.1 Nominal systems
7.3.2 Mean computational models
7.3.3 Definition of the external excitation for the computational model
7.3.4 Evaluation of the sound reduction indices
7.3.5 Uncertainty quantification
7.4 Conclusion
8 Impact sound insulation 
8.1 Introduction
8.2 Model for the evaluation of impact noise level
8.3 Model for the tapping machine excitation force
8.3.1 Probabilistic model for the external excitation resulting from the tapping machine 101
8.3.2 Concluding remarks about the approach
8.4 Validation of the computational model for the impact problem and uncertainty quantification
8.4.1 Experimental validation of the computational model for a simple lightweight system
8.4.2 Uncertainty quantification
8.4.3 Concluding remarks about impact forces modeling
8.5 Application to a full scale lightweight floor system
8.5.1 Nominal system
8.5.2 Mean steady-state computational model
8.5.3 Stochastic steady-state computational model
8.5.4 Comparison with experimental measurements: velocity levels
8.5.5 Comparison with experimental measurements: impact sound level
8.6 Conclusion
9 Optimisation 
9.1 Introduction
9.2 Optimisation algorithm
9.2.1 Definition of the fitness functions
9.2.2 Genetic algorithm
9.3 Robust optimisation problems
9.3.1 Lightweight double parting wall systems
9.3.2 Lightweigth floor system
9.4 Conclusion
Conclusions and perspectives
Appendices
A Validation of the finite element implementation with respect to the Biot displacement formulation
A.1 Analytical solutions for the sound propagation in a unidimensional poroelastic
medium
A.2 Unidimensional reference problems
B Limp frame poroelastic medium equivalent fluid model
References