One key element of underwater transducer design is the acoustic baffle. Acoustic baffles isolate a structure, such as a submarine hull, from noise and vibration produced by the active elements of the transducer and vice versa. Baffle materials must meet many conflicting requirements such as the need to be lightweight while providing high acoustic isolation. Currently Syntactic Acoustic Damping Material (SADM) is widely used as the primary acoustic baffle material. However, SADM baffles have many undesirable characteristics such as high density, poor machinability, high lead content and depth dependent acoustical behavior. The study of baffle materials is an under-represented area of sonar design. Most sonar transducer research focuses on the electrically active materials and their response to a variety of conditions. Relatively fewer studies have been devoted to understanding the effects of the supporting and baffle materials. This work considers the effects of the entire hydrophone system on the response while developing a method for aiding in proper system material selection. This was accomplished by first developing a model for a transducer's response in a variety of conditions. The response was validated with numerical finite-element models and experiments. Next, a generic model was developed that allows any number of layers with any material to be analyzed. This generic model is applied in concert with a material optimization method to aid in the selection of materials that will improve the transducer's response. The tools are finally applied to a simple real world problem to illustrate its strengths and weaknesses. / text

Predicting tenderness in today's beef supply could be advantageous to packers and consumers. In this study (n = 1,137 carcasses), visible-near-infrared, electrical impedance, pH and Minolta CIE L*, a*, and b* color space values were examined as predictors of beef 1, 7, and 14 d Warner-Bratzler (N) or Slice Shear (N) force values as estimators of beef tenderness. Visible-NIR at 350 to 1830 nm, electrical impedance, and color space values were taken at the beef packing plant, along with carcass data. Strip loins were transported to Texas A & M University where pH was taken. Six steaks were taken from the anterior end of the strip loin and randomly assigned to either Warner-Bratzler shear force (WBSF) after 1, 7, or 14 days, or Slice shear force (SSF) after 1, 7, and 14 days of post-harvest aging at 2 degrees C. Shears were taken on assigned days. Shear force values were highly correlated with each other (r = 0.37 to 0.56 for WBSF and r = 0.75 to 0.78 for SSF) (P < 0.05). Within the independent variables, reflectance values for mid-range wavelengths (562nm-1193nm) were found to be most highly correlated with the dependent variables (P < 0.05). pH and color spaces values were more highly correlated (P < 0.05) to slice shears values then to Warner-Bratzler shears force values. Electrical impedance was the least significant with r values of 0.00 to 0.14. When Visble-NIR reflectance values were used in stepwise regression equations to predict 1, 7, or 14 d WBSF or 1, 7, or 14 d SSF, prediction equations for 14 d WBSF and SSF had the highest R^2 (0.14 and 0.36, respectively). Stepwise regression equations that included pH and color space values had the highest R^2 for 7 d WBSF and 1 d SSF (0.22 and 0.28, respectively). Electrical impedance alone in a stepwise regression equation had the highest R^2 for 1 and 14 d WBSF and 1 and 7 d SSF (0.02 and 0.03, respectively). Stepwise regression equations that included pH, color space values, and electrical impedance had the highest R^2 for 7 d WBSF and 14 d SSF (0.25 and 0.24, respectively). When pH, color space values, electrical impedance, and Visible-NIR were used, 7 d WBSF and 1 d SSF had the highest R^2 (0.38 and 0.34, respectively). Stepwise regression equations that included pH, color space values, and Visible-NIR had the highest R^2 for 7 d WBSF and 14 d SSF (0.30 and 0.44, respectively). For predicting 14 d Warner-Bratzler shear force, a R^2 of 0.20 was found using Visible-NIR, pH and color space values. When used, the partial least squares equation predicted tenderness with an 85 percent success rate. For predicting 14 d Slice shear forces, a R^2 of 0.40 was found. When used, the partial least squares equation had a 100 percent success rate of predicting those steaks found tender to be tender for Slice shear force. There was an 85 percent success rate for predicting 14 d Warner-Bratzler shear forces. Both equations still had little to no success in predicting tough steaks. The Visible-NIR can successfully predict tenderness

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Thesis (Ph. D.)--University of Washington, 1990. / Vita. Includes bibliographical references (leaves [174]-182).

Thesis (Ph.D.)-- University of Adelaide, Dept. of Mechanical Engineering, 2000. / Bibliography: leaves 182-190. Also available electronically.

Thesis (Ph.D.)--University of Adelaide, Dept. of Mechanical Engineering, 2000? / Bibliography: leaves 182-190. Also available in print form.