Naval Surface Warfare Center

About: Naval Surface Warfare Center is a facility organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Radar & Sonar. The organization has 2855 authors who have published 3697 publications receiving 83518 citations. The organization is also known as: NSWC.

Turbulent wall pressure fluctuation measurements on a towed model at high Reynolds numbers

Abstract: Turbulent wall pressure fluctuation measurements were made in water on a towed model of length 129.8 (m) and diameter 3.8 (cm) for steady speeds from 6.2 (m/s) to 15.5 (m/s). The drag on the model was measured with a strut mounted load cell which provided estimates of the momentum thickness and friction velocity. Momentum thickness Reynolds numbers Reθ varied from 4.8 × 105 to 1.1 × 106. The ratio of momentum thickness to viscous length scale is significantly greater than for flat plate cases at comparable Reθ. The effectiveness of inner and outer velocity and length scales for collapsing the pressure spectra are discussed. The wavenumber–frequency spectra show a convective ridge at higher frequencies similar to flat plate boundary layers. At low frequencies, energy broad in wavenumber extends outside the convective ridge and acoustic cone, with no characteristic wave speed. Wall pressure cross-spectral levels scaled with similarity variables are shown to increase with increasing tow speed, and to follow decay constants consistent with flat plate cases. The convection velocities also display features similar to flat plate cases.

Effects of Coolant Density Ratio on Film Cooling Performance on a Vane

Abstract: Film cooling performance was studied on a simulated turbine vane model with an objective of determining how much the coolant density ratio affects this performance. Experiments were conducted using coolant density ratios of 1.8 and 1.2. The purpose of the study was to determine if tests done at small density ratios (which is often more viable in a laboratory) can give reasonable predictions of performance at more realistic large density ratios. Furthermore, appropriate scaling parameters were determined. The mainstream flow was operated with low and high turbulence levels. Adiabatic effectiveness was measured in the showerhead region of the vane, and following the first row of coolant holes on the pressure side. Adiabatic effectiveness performance using small density ratio coolant gave performance trends similar to the large density ratio coolant, but quantitative values differed by varying amount depending on operating conditions.Copyright © 2003 by ASME

Image-Based Automated Change Detection for Synthetic Aperture Sonar by Multistage Coregistration and Canonical Correlation Analysis

Abstract: In this paper, an automated change detection technique is presented that compares new and historical seafloor images created with sidescan synthetic aperture sonar (SAS) for changes occurring over time. The method consists of a four-stage process: a coarse navigational alignment that relates and approximates pixel locations of reference and repeat–pass data sets; fine-scale coregistration using the scale-invariant feature transform (SIFT) algorithm to match features between overlapping data sets; local coregistration that improves phase coherence; and finally, change detection utilizing a canonical correlation analysis (CCA) algorithm to detect changes. The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. Successful results of this multistage change detection method are presented here, and the robustness of the techniques that exploit phase and amplitude levels of the backscattered signals is discussed. It is shown that the coherent nature of the SAS data can be exploited and utilized in this environment over time scales ranging from hours through several days. Robustness of the coregistration methods and analysis of scene coherence over time is characterized by analysis of repeat pass as well as synthetically modified data sets.