Transient implicit wave propagation dynamics with overlapping finite elements

2018 ◽  
Vol 199 ◽  
pp. 18-33 ◽  
Author(s):  
Ki-Tae Kim ◽  
Lingbo Zhang ◽  
Klaus-Jürgen Bathe
Keyword(s):  
Wave Propagation ◽  
Finite Elements ◽  
Propagation Dynamics

Wave Propagation Using Wavelet-Based Finite Elements

2009 ◽  
Author(s):  
Rodrigo Bird Burgos ◽  
Felipe Prado Loureiro ◽  
Marco Antonio Cetale Santos ◽  
Raul Rosas E Silva
Keyword(s):  
Wave Propagation ◽  
Finite Elements

Fundamental Understanding of Wave Propagation in a Beam Using PZT Actuators and Sensors

2013 ◽  
Author(s):  
Vishnu Prasad Venugopal ◽  
Gang Wang
Keyword(s):  
Finite Element ◽  
Wave Propagation ◽  
Finite Elements ◽  
Timoshenko Beam ◽  
High Frequency ◽  
Beam Structure ◽  
Frequency Wave ◽  
Coupled Equations ◽  
High Frequency Wave ◽  
Spectral Finite Element

Embedded smart actuators/sensors, such as piezoelectric types, have been used to conduct wave transmission and reception, pulse-echo, pitch-catch, and phased array functions in order to achieve in-situ nondestructive evaluation for different structures. By comparing to baseline signatures, the damage location, amount, and type can be determined. Typically, this methodology does not require analytical structural models and interrogation algorithm is carefully designed with little wave propagation knowledge of the structure. However, the wave excitation frequency, waveform, and other signal characteristics must be comprehensively considered to effectively conduct diagnosis of incipient forms of damage. Accurate prediction of high frequency wave response requires a prohibitively large number of conventional finite elements in the structural model. A new high fidelity approach is needed to capture high frequency wave propagations in a structure. In this paper, a spectral finite element method (SFEM) is proposed to characterize wave propagations in a beam structure under piezoelectric material (i.e., PZT) actuation/sensing. Mathematical models are developed to account for both Uni-morph and bi-morph configurations, in which PZT layers are modeled as either an actuator or a sensor. The Timoshenko beam theory is adopted to accommodate high frequency wave propagations, i.e., 20–200 KHz. The PZT layer is modeled as a Timoshenko beam as well. Corresponding displacement compatibility conditions are applied at interfaces. Finally, a set of fully coupled governing equations and associated boundary conditions are obtained when applying the Hamilton’s principle. These electro-mechanical coupled equations are solved in the frequency domain. Then, analytical solutions are used to formulate the spectral finite element model. Very few spectral finite elements are required to accurately capture the wave propagation in the beam because the shape functions are duplicated from exact solutions. Both symmetric and antisymmetric mode of lamb waves can be generated using bimorph or uni-morph actuation. Comprehensive simulations are conducted to determine the beam wave propagation responses. It is shown that the PZT sensor can pick up the reflected waves from beam boundaries and damages. Parametric studies are conducted as well to determine the optimal actuation frequency and sensor sensitivity. Such information helps us to fundamentally understand wave propagations in a beam structure under PZT actuation and sensing. Our SFEM predictions are validated by the results in the literature.

Blind Identification of 2-Channel IIR Wave Propagation Systems for Central Cardiovascular Monitoring

2008 ◽  
Author(s):  
Jin-Oh Hahn ◽  
Andrew T. Reisner ◽  
H. Harry Asada
Keyword(s):  
Blood Pressure ◽  
Wave Propagation ◽  
Infinite Impulse Response ◽  
Identification Algorithm ◽  
Blind Identification ◽  
Pressure Measurements ◽  
Cardiovascular Monitoring ◽  
Channel Dynamics ◽  
Identification Approach ◽  
Propagation Dynamics

This paper presents a new approach to blind identification of a class of 2-channel infinite impulse response (IIR) systems describing the wave propagation dynamics. For these systems, this paper derives a blind identifiability condition and develops a blind identification algorithm, which is capable of uniquely determining both the numerator and denominator polynomials of the channel dynamics. The efficacy of the method is illustrated by a 2-sensor central cardiovascular monitoring application as an example, where the cardiovascular blood pressure wave propagation dynamics is identified and the aortic signals are reconstructed from blood pressure measurements at two distinct extremity locations. Experimental results using a swine subject illustrate how the new blind identification approach effectively identifies cardiovascular dynamics and reconstructs the aortic blood pressure and flow signals very accurately from two distinct peripheral blood pressure measurements under diverse physiologic conditions.

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