Professor Bojan Guzina

Project Title: 
Wave-Based Imaging and Characterization of Heterogeneous Media

These researchers are using MSI for four projects:

  • Developing a noninvasive method for measuring the modulus C of nonlinear tissue elasticity, responsible for coupling the shear and volumetric constitutive responses of a material, with applications to medical diagnosis (differentiation of breast masses). The project proposes an experimental method that utilizes “acoustic radiation force” (ARF) to efficiently estimate tissue nonlinearity locally at the focal region of the ultrasound beam by measuring the amplitude of ARF. Due to experimental limitations, a direct measurement of the ARF in tissue is difficult. To overcome this problem, these researchers deploy 3D elastodynamic finite element (EFE) simulations of the ARF experiment in tissue-mimicking phantoms to estimate the “background” shear modulus from the phase of the induced shear waves; the ARF magnitude from the shear wave amplitude; and the nonlinear modulus C from the knowledge of the ARF. In this way, by interpreting the ARF-generated shear waves through the prism of 3D-EFE simulations, the researchers are able to make a local estimation of the nonlinear C modulus with spatial resolution equaling the size of the focal region. They call this method the C-Elastography (CE).
  • Seismic imaging and characterization of heterogeneous fractures in the subsurface (e.g. hydraulic fractures). The goal of this study is to establish a comprehensive platform for the 2D reconstruction and mechanical characterization of arbitrarily-shaped, distinct fractures in quasi-brittle materials. Over the past decade, research in applied mathematics and engineering has produced a suite of non-iterative approaches to inverse scattering, such as the linear sampling method (LSM). In this work, this goal is accomplished via an extension to the so-called generalized linear sampling method (GLSM) to enable geometric reconstruction of fractures regardless of their interfacial condition. With such results at hand, the proposed inverse solution will entail a three-step hybrid approach where: the fracture surface is reconstructed without the knowledge of interface; given the geometry, the fracture opening displacement (FOD) profile is recovered from an integral transform relating FOD to the observed seismic waveforms; and given FOD, the spatial distribution of specific stiffnesses is resolved from the boundary integral equation for fracture, incorporating its (inhomogeneous) elastic contact condition. This scheme is integrated into a recently developed BEM code. The proposed developments will then be verified in a laboratory setting, making use of the recently acquired Scanning Laser Doppler Vibrometer (SLDV) that is capable of monitoring triaxial waveforms on the specimen's surface.
  • Elastodynamic waveform tomography of spent nuclear fuel casks. At the end of their service life, the nuclear Fuel Assemblies (FAs) consumed by nuclear power plants are cooled down in a spent fuel pool for a certain period and then stored temporarily in dry casks. A spent nuclear fuel cask is a cylindrical structure that encloses a sealed canister where the FAs are arranged vertically via a holding basket. During insertion of the FAs into the canister, the FAs may be damaged or placed improperly with respect to their remaining nuclear capacity. In this setting, this research aims to develop an elastodynamic Non-Destructive Evaluation (NDE) technique that identifies and characterizes the FAs inside the canister in order to evaluate their potential damage and misloading before their transportation and permanent storage. The proposed NDE method is formulated in the form of an inverse problem that models the canister and FAs with their condensed elastodynamic impedance at their point-like contacts. By assuming a parallel arrangement of the latter in response to dynamic excitation applied to the bottom of the canister base plate, the individual FA impedances are extracted by comparing the impedance of the loaded canister and that of the empty canister. In a second stage, the comparison of the reconstructed impedances with their reference “stencils” helps conclude about possible misloading and damage of the FAs without having a direct access to them.
  • Developing a method for detecting foundation pile lengths of High Mast Light Towers (HMLTs). HMLT foundation systems are typically concrete-filled steel pipe piles or steel H-piles, many having no construction documentation (e.g. pile lengths) and soil stratigraphy information. Reviews of designs within current standards suggest that many of these foundations may have insufficient uplift capacity in the event of peak wind loads. The goal of the project is to establish a non-destructive field-testing technique, including machine learning data analysis algorithm, for determining in-place pile lengths by way of seismic waves. Steady-state vibrations, as opposed to deploying an impact response, are chosen for their robust performance in complex/noisy environments. A unique feature of this work is the use of computational modeling to account for the effects of soil profiles, sensor locations, and ground conditions on the sensitivity of the method. The length of each pile supporting an HMLT will be identified through a systematic sensing approach that includes: collection and classification of the pertinent foundation designs and soil conditions; 3D simulation of dynamic soil-foundation interaction; parametric studies of the 3D pile vibration problem; field testing; and analysis-driven machine learning data interpretation.

Project Investigators

Twain Cacek
Professor Bojan Guzina
Daniel Kennedy
Thi Phong Nguyen
Othman Oudghiri-Idrissi
Danial Panahandeh Shahraki
 
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