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The effect of mechanical vibrations on the ultrafiltration of oily emulsions was studied in the 50–1000 Hz range. A cylindrical vibrating module was assembled and coupled with an electrodynamic exciter, controlled by a computerized system. The ultrafiltration experiments were run with a 20% cutting oil/water emulsion at different working conditions. The experimental data demonstrated that both vibration amplitude and frequency are effective in enhancing membrane performance. The influence of the frequency is more marked. Energy consumption was evaluated, and simple equations were proposed in order to predict both performances and energy requirements.

Complex subsurface structure makes seismo‐acoustic imaging difficult, raising the need for novel detection, classification, and imaging approaches. For the representation of range‐dependent seismo‐acoustic propagation, we employ a hybrid, coupled wavenumber integration approach to range‐dependent seismo‐acoustic modeling based on the OASES environmental modeling framework. In feature identification and classification, time series analysis frequently provides the sought‐after recognition clues. Nevertheless, the geometry and the structure of the subsurface features generate a variety of complexities to the wave field caused by different physical mechanisms, geometric constraints, and intrinsic properties. Based on the time series attributes such as the time of arrival, waveform amplitude, and the frequency content, a set of identification features is extracted and a set of corresponding classes is formed. Using the simulated data scenarios, general rules incorporating the identification features of subsurface structures are deduced. This classification methodology is then applied to the data recorded by an array of seismographs and hydrophones on and off the coast of Japan. The results create a basis for classification and description of the structures of interest such as the presence or absence of very low‐velocity range‐dependent layers below the water‐seabed interface.

It has been suggested that the tomographic approach that feeds the 8–11 kHz ocean acoustic measurements into an ocean model using data from bottom‐mounted hydrophones, suffers from a significant travel‐time variability due to the surface waves. In this work, the influence of the ocean surface motion on the acoustic travel times has been studied using both the experimental data collected at the Pacific missile range facility (PMRF) off Kauai, and an appropriate acoustic model. The ray‐based acoustic model developed is an adaptation of the range‐dependent version of Bellhop with the modified top surface characterizing ocean surface waves. The model‐generated time series suggests a direct relationship between the phase of the top surface wave and the time‐of arrival, which is further confirmed by the experimental data. Furthermore, an approach is developed that automatically decouples the effect of the top surface waves from the environment‐related phenomena, making it possible to assign the travel time variations produced by the physical phenomena independently of the surface geometry, in turn eliminating the surface related error. [Work supported by the ONR.]

With a broader objective of establishing a global solution for systematic assessment and protection of the marine environment, one of the central objectives of this work is to distinguish whale backscattered responses from the ones generated by the environmental clutter in a waveguide. Furthermore, it aims to identify and analyze the target signature features that are necessary for enhanced active sonar detection and classification of marine mammals. Over the years there have been very few documented attempts to capture and analyze the backscattering response of whales using an active sonar system. Nevertheless, whales, mostly owing to their size, their motion, and the aspect dependence of their backscattered field, possess desirable properties that help distinguish their scattered response from clutter and other environment related false alarms. As an initial step, data collected during the Marine Mammal Active Sonar Test (MAST04) is presented, and long‐range gray whale target strength measurements are o...