ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Bending mechanics
- All Subjects: stochastic reconstruction
- Creators: Chawla, Nikhilesh
Description
Weevils are among the most diverse and evolutionarily successful animal lineages on Earth. Their success is driven in part by a structure called the rostrum, which gives weevil heads a characteristic "snout-like" appearance. Nut weevils in the genus Curculio use the rostrum to drill holes into developing fruits and nuts, wherein they deposit their eggs. During oviposition this exceedingly slender structure is bent into a straightened configuration - in some species up to 90° - but does not suffer any damage during this process. The performance of the snout is explained in terms of cuticle biomechanics and rostral curvature, as presented in a series of four interconnected studies. First, a micromechanical constitutive model of the cuticle is defined to predict and reconstruct the mechanical behavior of each region in the exoskeleton. Second, the effect of increased endocuticle thickness on the stiffness and fracture strength of the rostrum is assessed using force-controlled tensile testing. In the third chapter, these studies are integrated into finite element models of the snout, demonstrating that the Curculio rostrum is only able to withstand repeated, extreme bending because of
modifications to the composite structure of the cuticle in the rostral apex. Finally, interspecific differences in the differential geometry of the snout are characterized to elucidate the role of biomechanical constraint in the evolution of rostral morphology for both males and females. Together these studies highlight the significance of cuticle biomechanics - heretofore unconsidered by others - as a source of constraint on the evolution of the rostrum and the mechanobiology of the genus Curculio.
modifications to the composite structure of the cuticle in the rostral apex. Finally, interspecific differences in the differential geometry of the snout are characterized to elucidate the role of biomechanical constraint in the evolution of rostral morphology for both males and females. Together these studies highlight the significance of cuticle biomechanics - heretofore unconsidered by others - as a source of constraint on the evolution of the rostrum and the mechanobiology of the genus Curculio.
ContributorsJansen, Michael Andrew (Author) / Franz, Nico M (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Harrison, Jon (Committee member) / Martins, Emilia (Committee member) / Arizona State University (Publisher)
Created2009
Description
An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for quantitative structure-property relations establishment and its performance prediction and optimization. X-ray tomography has provided a non-destructive means for microstructure characterization in both 3D and 4D (i.e., structural evolution over time). Traditional reconstruction algorithms like filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART) require huge number of tomographic projections and segmentation process before conducting microstructural quantification. This can be quite time consuming and computationally intensive.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
ContributorsLi, Hechao (Author) / Jiao, Yang (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Ren, Yi (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2017