NUMERICAL AND ANALYTICAL VERIFICATION OF A MULTISCALE COMPUTATIONAL MODEL FOR IMPACT PROBLEMS IN HETEROGENEOUS VISCOELASTIC MATERIALS WITH EVOLVING DAMAGE

Composites are engineered materials that take advantage of the particular properties of each of its two or more constituents. They are designed to be stronger, lighter and to last longer which can lead to the creation of safer protection gear, more fuel efficient transportation methods and more affordable materials, among other examples. This thesis proposes a numerical and analytical verification of an in-house developed multiscale model for predicting the mechanical behavior of composite materials with various configurations subjected to impact loading. This verification is done by comparing the results obtained with analytical and numerical solutions with the results found when using the model. The model takes into account the heterogeneity of the materials that can only be noticed at smaller length scales, based on the fundamental structural properties of each of the composite’s constituents. This model can potentially reduce or eliminate the need of costly and time consuming experiments that are necessary for material characterization since it relies strictly upon the fundamental structural properties of each of the composite’s constituents. The results from simulations using the multiscale model were compared against results from direct simulations using over-killed meshes, which considered all heterogeneities explicitly in the global scale, indicating that the model is an accurate and fast tool to model composites under impact loads. Advisor: David H. Allen

Mycobacterium bovis–Infected White-Tailed Deer (Odocoileus Virginianus): Detection of Immunoglobulin Specific to Crude Mycobacterial Antigens by ELISA

White-tailed deer (Odocoileus virginianus) have recently emerged as a source of Mycobacterium bovis infection for cattle within North America. The objective of this study was to evaluate the antibody response of M. bovis–infected deer to crude mycobacterial antigens. Deer were experimentally inoculated with M. bovis strain 1315 either by intratonsilar instillation or by exposure to M. bovis–infected (i.e., in contact) deer. To determine the time course of the response, including the effects of antigen administration for comparative cervical skin testing, serum was collected periodically and evaluated by enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (i.e., IgG heavy and light chains) reactivity to mycobacterial antigens. The reactivity to M. bovis purified protein derivative (PPDb) exceeded (P < 0.05) the reactivity to M. avium PPD (PPDa) only after in vivo administration of PPDa and PPDb for comparative cervical testing of the infected deer. The mean immunoglobulin response, as measured by ELISA, of intratonsilar-inoculated deer to a proteinase K–digested whole-cell sonicate (WCS-PK) of M. bovis strain 1315 exceeded (P < 0.05) the mean of the prechallenge responses to this antigen at approximately 1 month after inoculation and throughout the remainder of the study (i.e., ~11 months). This response also exceeded (P < 0.05) that of the uninfected deer. Although this is encouraging, further studies are necessary to validate the use of the proteinase K–digested M. bovis antigens in the antibody-based assays of tuberculosis.

INVESTIGATION INTO CURRENT EFFICIENCY FOR PULSE ELECTROCHEMICAL MACHINING OF NICKEL ALLOY

INVESTIGATION INTO CURRENT EFFICIENCY FOR PULSE ELECTROCHEMICAL MACHINING OF NICKEL ALLOY Yu Zhang, M.S. University of Nebraska, 2010 Adviser: Kamlakar P. Rajurkar Electrochemical machining (ECM) is a nontraditional manufacturing process that can machine difficult-to-cut materials. In ECM, material is removed by controlled electrochemical dissolution of an anodic workpiece in an electrochemical cell. ECM has extensive applications in automotive, petroleum, aerospace, textile, medical, and electronics industries. Improving current efficiency is a challenging task for any electro-physical or electrochemical machining processes. The current efficiency is defined as the ratio of the observed amount of metal dissolved to the theoretical amount predicted from Faraday’s law, for the same specified conditions of electrochemical equivalent, current, etc [1]. In macro ECM, electrolyte conductivity greatly influences the current efficiency of the process. Since there is a certain limit to enhance the conductivity of the electrolyte, a process innovation is needed for further improvement in current efficiency in ECM. Pulse electrochemical machining (PECM) is one such approach in which the electrolyte conductivity is improved by electrolyte flushing in pulse off-time. The aim of this research is to study the influence of major factors on current efficiency in a pulse electrochemical machining process in macro scale and to develop a linear regression model for predicting current efficiency of the process. An in-house designed electrochemical cell was used for machining nickel alloy (ASTM B435) by PECM. The effects of current density, type of electrolyte, and electrolyte flow rate, on current efficiency under different experimental conditions were studied. Results indicated that current efficiency is dependent on electrolyte, electrolyte flow rate, and current density. Linear regression models of current efficiency were compared with twenty new data points graphically and quantitatively. Models developed were close enough to the actual results to be reliable. In addition, an attempt has been made in this work to consider those factors in PECM that have not been investigated in earlier works. This was done by simulating the process by using COMSOL software. However, it was found that the results from this attempt were not substantially different from the earlier reported studies.