Indirect acoustic impedance computations involving fixed free‐space attenuation or fixed boundary loss factors: Experimental model validation studies

1992 ◽  
Vol 92 (4) ◽  
pp. 2431-2432
Author(s):  
A. A. Oni ◽  
J. T. Kalb ◽  
G. Garinther
Keyword(s):  
Experimental Model ◽  
Model Validation ◽  
Acoustic Impedance ◽  
Validation Studies ◽  
Free Space ◽  
Fixed Boundary ◽  
Loss Factors

Reconstruction of Acoustic Radiation of a Vibrating Structure Located in a Half-Space Bounded by a Passive Surface with Finite Acoustic Impedance

2020 ◽  
Vol 28 (04) ◽  
pp. 2050019
Author(s):  
Daren Zhou ◽  
Huancai Lu ◽  
D. Michael McFarland ◽  
Yongxiong Xiao
Keyword(s):  
Half Space ◽  
Acoustic Impedance ◽  
Free Space ◽  
Plane Surface ◽  
Spherical Wave ◽  
Boundary Surface ◽  
Sound Field ◽  
Wave Functions ◽  
Reconstruction Method ◽  
Direct Radiation

Vibrating structures are often mounted on or located near a passive plane surface with finite acoustic impedance, and hence the acoustic pressures measured in a half-space bounded by the surface consist of both the direct radiation from the structure and the reflection from the boundary surface. In order to visualize the direct radiation from the source into free space, a reconstruction method based on expansion in half-space spherical wave functions is proposed. First, the series of half-space spherical wave functions is derived based on the analytical solution of the sound field due to a multipole source located near an impedance plane. Then the sound field in the half-space is approximated by the superposition of a finite number of half-space expansion terms. The expansion coefficients are determined by solving an overdetermined linear system of equations obtained by matching this assumed solution to the total acoustic pressures in the half-space. The free-space radiation can finally be reconstructed via multiplying the free-space spherical wave functions by the corresponding coefficients. Numerical simulation examples of a vibrating sphere and a vibrating baffled plate are demonstrated. The effects of specific acoustic impedance of the boundary and the locations of the measurement points on the accuracy of reconstruction are examined.

Experimental Model Validation for a Flexible Robot With a Prismatic Joint

1990 ◽  
Vol 112 (3) ◽  
pp. 315-323 ◽  
Author(s):  
Ye-Chen Pan ◽  
A. Galip Ulsoy ◽  
R. A. Scott
Keyword(s):  
Rigid Body ◽  
Numerical Simulations ◽  
Dynamic Model ◽  
Experimental Model ◽  
Model Validation ◽  
Solution Method ◽  
Flexible Robot ◽  
Spherical Coordinate ◽  
Prismatic Joints ◽  
Rigid Body Motions

In [1] a dynamic model for flexible manipulators with prismatic joints and the solution method were presented. In this paper experiments on a spherical coordinate robot are performed to further validate the proposed dynamic model. Using the validated model, numerical simulations are performed to illustrate the coupling effects between the rigid body motions and the flexible motions, the effects of the flexible motion on a rigid body controller, and the effects of axial shortening.

Validation of Microsimulation Models Used for Population Health Policy

2020 ◽  
pp. 227-240
Author(s):  
Fernando Alarid-Escudero ◽  
Roman Gulati ◽  
Carolyn M. Rutter
Keyword(s):  
Health Policy ◽  
Population Health ◽  
Model Validation ◽  
Validation Studies ◽  
Simulation Models ◽  
Systematic Evaluation ◽  
Fitness For Purpose ◽  
Empirical Results ◽  
Model Predictions ◽  
Microsimulation Models

This chapter discusses validation of simulation models used to inform health policy. Confidence in a model’s validity can be weaker or stronger depending on several factors. These factors include verifying whether model specifications were implemented correctly, evaluating the extent to which model-predicted results are consistent with empirical results, and examining whether model predictions are robust to alternative structural assumptions. Systematic evaluation of these factors can be used to gauge the extent to which a model is validated for a given application. It reviews types of validation, discusses the related concepts of calibration and nonidentifiability, takes a deeper dive into cancer model validation studies, and concludes with questions that consumers of models should ask (and modelers should answer) to inform judgment about a model’s fitness for purpose. Final judgments about when model results can be trusted ultimately rely on the evolving understanding of the disease and intervention effects, available data relevant to the application, and access to reporting of model validation exercises.

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