66 research outputs found
Numerical Techniques for Scattering from Submerged Objects
To represent the final results in terms of matrices, one expands all appropriate physical quantities in terms of partial wave basis states. This includes expansions for the incident and scattered fields and the surface quantities. The method then utilizes the Huygen-Poincare integral representation for both the exterior and interior solutions, leading to the required matrix equations. One thus deals with matrix equations, the complexity of which depends on the nature of the problem. It is shown that in general a transition matrix T can be obtained relating the incident field A with the scattered field f having the form T = PQ(-1), where f = TA. The structure of Q can be quite complicated and can itself be composed of other matrix inversions such as arise from layered objects. Recent improvements in this method appropriate for a variety of physical problems are focused on, and on their implementation. Results are outlined from scattering simulations for very elongated submerged objects and resonance scattering from elastic solids and shells. The final improvement concerns eigenfunction expansions of surface terms, arising from solution of the interior problem, obtained via a preconditioning technique. This effectively reduces the problem to that of obtaining eigenvalues of a Hermitian operator. This formalism is reviewed for scattering from targets that are rigid, sound-soft, acoustic, elastic solids, elastic shells, and elastic layered objects. Two sets of the more interesting results are presented. The first concerns scattering from elongated objects, and the second to thin elastic spheroids
Ultrasonic Characterization of Microspherical Inclusions in Zirconia and Crystallized Glass
In high performance ceramic materials the critical flaw size is ≃ 10 µm. Not all inclusions are equally detrimental to the structural properties. Therefore it is necessary to determine their size and composition.</p
Sound scattering by several zooplankton groups. II. Scattering models
Author Posting. © Acoustical Society of America, 1998. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 103 (1998): 236-253, doi:10.1121/1.421110.Mathematical scattering models are derived and compared with data from zooplankton from several gross anatomical groups—fluidlike, elastic shelled, and gas bearing. The models are based upon the acoustically inferred boundary conditions determined from laboratory backscattering data presented in part I of this series [Stanton et al., J. Acoust. Soc. Am. 103, 225–235 (1998)]. The models use a combination of ray theory, modal-series solution, and distorted wave Born approximation (DWBA). The formulations, which are inherently approximate, are designed to include only the dominant scattering mechanisms as determined from the experiments. The models for the fluidlike animals (euphausiids in this case) ranged from the simplest case involving two rays, which could qualitatively describe the structure of target strength versus frequency for single pings, to the most complex case involving a rough inhomogeneous asymmetrically tapered bent cylinder using the DWBA-based formulation which could predict echo levels over all angles of incidence (including the difficult region of end-on incidence). The model for the elastic shelled body (gastropods in this case) involved development of an analytical model which takes into account irregularities and discontinuities of the shell. The model for gas-bearing animals (siphonophores) is a hybrid model which is composed of the summation of the exact solution to the gas sphere and the approximate DWBA-based formulation for arbitrarily shaped fluidlike bodies. There is also a simplified ray-based model for the siphonophore. The models are applied to data involving single pings, ping-to-ping variability, and echoes averaged over many pings. There is reasonable qualitative agreement between the predictions and single ping data, and reasonable quantitative agreement between the predictions and variability and averages of echo data.This
work was supported by the National Science Foundation
Grant No. OCE-9201264, the U.S. Office of Naval Research
Grant Nos. N00014-89-J-1729, N00014-95-1-0287, and
N00014-94-1-0452, and the MIT/WHOI Joint Graduate Education
Program
Protocols for calibrating multibeam sonar
Author Posting. © Acoustical Society of America, 2005. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 117 (2005): 2013-2027, doi:10.1121/1.1869073.Development of protocols for calibrating multibeam sonar by means of the standard-target method is documented. Particular systems used in the development work included three that provide the water-column signals, namely the SIMRAD SM2000/90- and 200-kHz sonars and RESON SeaBat 8101 sonar, with operating frequency of 240 kHz. Two facilities were instrumented specifically for the work: a sea well at the Woods Hole Oceanographic Institution and a large, indoor freshwater tank at the University of New Hampshire. Methods for measuring the transfer characteristics of each sonar, with transducers attached, are described and illustrated with measurement results. The principal results, however, are the protocols themselves. These are elaborated for positioning the target, choosing the receiver gain function, quantifying the system stability, mapping the directionality in the plane of the receiving array and in the plane normal to the central axis, measuring the directionality of individual beams, and measuring the nearfield response. General preparations for calibrating multibeam sonars and a method for measuring the receiver response electronically are outlined. Advantages of multibeam sonar calibration and outstanding problems, such as that of validation of the performance of multibeam sonars as configured for use, are mentioned.Support by the National Science Foundation through Award
No. OCE-0002664, NOAA through Grant No.
NA97OG0241, and the Cooperative Institute for Climate and
Ocean Research (CICOR) through NOAA Contract No.
NA17RJ1223 is acknowledged
Signal processing of the echo signatures returned by submerged shells insonified by dolphin “clicks:” Active classification
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