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.

Polynitroaliphatic explosives containing the pentafluorosulfanyl (SF5) group: The selection and study of a model compound

Abstract: An investigation concerning the effect of the pentafluoro-sulfanyl (SF5) group on the properties of explosive nitro compounds is described. The investigation includes: (a) the preparation of severa...

Combining random and data-driven coverage planning for underwater mine detection

Abstract: Unmanned autonomous vehicles are proving themselves to be effective means for conducting underwater mine hunting missions. The resulting efficiency, reduced search time, and covert search possibilities will facilitate larger mission areas requiring many agents searching for significant lengths of time (e.g., many weeks or months). In search areas of this scale, complete area coverage may not always be feasible. Therefore, this research investigates a path planning scheme for incomplete coverage. This scheme divides the search area into cells and surveys each cell using a conventional line-sweep pattern with a row spacing that is larger than the sensor footprint. The rows of the line-sweep pattern are randomly spaced near the boundaries of each cell to decrease the probability of missing a line of evenly spaced mines. The spacing of the rows near the center of each cell are specifically determined from estimated possible mine locations. Bounds placed on the row spacing limits the amount of uncovered area to maintain an acceptable probability of detection. This method results in a probability of missing a mine that is less than the percent of unsearched area.

Estimation method of the capsizing probability in irregular beam seas using non-Gaussian probability density function

Abstract: This paper aims to describe a probabilistic assessment technique for ship roll behavior in beam sea conditions. Here, following the work of Kimura and its previous application by the author, probability density function (pdf) of roll response is calculated by combining the moment method with equivalent linearization technique. Results produced using this method are shown to be in good agreement with Monte Carlo simulation results. Moreover, this procedure is extended to the estimation of the capsizing probability. The final results concerning capsizing probability for the linear damping coefficient case are well correlated to the Monte Carlo simulation results. The advantage of this method is that it does not require a significant amount of computation and it enables the direct assessment of capsizing probability for ships with strongly nonlinear restoring terms.

An initial assessment of discriminant surface complexity for power law features

Abstract: The detection of man-made objects in natural terrain is important in both the targeting and terminal homing phase of modern warfare. The presence of man-made objects in gray-scale images has been successfully detected using a new class of density estimation neural networks to analyze power law signatures. The complex nature of the discriminant surface relating these features has been elucidated using these adaptive mixture networks.

Application of time-frequency analysis to machinery condition assessment

Abstract: Machinery condition has traditionally been assessed by analysis of the spectral energy density of the machine's vibration signal. Examination of time-frequency representations (TFRs) of constant-speed machinery data reveals vibration features that demonstrate variation in frequency over a short time period and thus cannot be adequately characterized by the power spectrum. These features may be used as supplemental information to assess the condition of the machine. Although the spectrogram provides a general indication of the time-varying spectrum, new representations such as the "cone-kernel" TFR reveal the existence of fine structural details inherent to the signal. >