Institution
Naval Surface Warfare Center
Facility•Washington D.C., District of Columbia, United States•
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: Sonar & Radar. The organization has 2855 authors who have published 3697 publications receiving 83518 citations. The organization is also known as: NSWC.
Papers published on a yearly basis
Papers
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TL;DR: Comparisons of theory and experiment show that the AP98, on average, is at least as good as the 1995 Aeroprediction Code and, in general, maybe slightly better.
Abstract: The U.S. Naval SurfaceWarfare Center aeroprediction code has been extended to the roll position of 45 deg ( ns in “ £ ” or cross-roll orientation) in addition to the roll position of 0 deg ( ns in “ ” or plus-roll orientation). It has also been extended to compute aerodynamics of nonaxisymmetricbodies based on an equivalent axisymmetric body. In addition, the nonlinear aerodynamic loads have been distributed over the body and lifting surfaces to provideamoreuseful tool forpreliminary structural analysis.Finally,new technologywas developed to improvethe predictionof axialforceat angleof attack.These new technologieshavebeen integrated into the1995Aeroprediction Code (AP95) and will be transitioned to legitimate users as the 1998 Aeroprediction Code (AP98). To make the AP98 more user friendly, an upgraded preand postprocessing, personal-computer interface was also developed. The theoretical methods of the AP98 are summarized, and a sample is shown of the comparisons of the AP98 predictions of static aerodynamics for several missile con gurations to experimental data. Comparisons of theory andexperiment show that theAP98,on average, is at least as goodas theAP95and, in general,maybe slightlybetter.
17 citations
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TL;DR: In this paper, an extensive series of elastomeric polyurethanes based on diphenylmethane-4,4 '-diisocyanate (MDI) prepolymers were prepared and further modified with fluid and powered siloxanes and conventional flame retardant additives.
Abstract: Polyurethanes are the single most versatile family of polymers with a wide range of applications. There is a substantial need for the development of polyurethane materials with low heat release rate and low smoke release rate. In this study, an extensive series of elastomeric polyurethanes based on diphenylmethane-4,4 '-diisocyanate (MDI) prepolymers were prepared and further modified with fluid and powered siloxanes and conventional flame retardant additives. The flame retardant behavior of these polymers was studied using the Cone Calorimeter (ASTM: E-1354), the instrument that has emerged as an important tool for the analytical testing of materials for their fire properties.** All powdered siloxane additives used in this study, even at 5% loading level, gave a 70-80% reduction in peak heat release rates compared to standard materials. The reductions of peak HRR of fluid siloxane-modified materials compared to the base material were in the range of 49-78%. The conventional flame retardant additives used in this study also reduced peak heat release rate dramatically. The synergistic effect of conventional flame retardant additives with siloxane powders is discussed.
17 citations
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01 Jan 2004
TL;DR: A framework and development process is described that allows more “plug ‘n play” integration of new diagnostic and prognostic technologies using evolving Open System Architecture (OSA) standards.
Abstract: Numerous advancements have been made in gas turbine health monitoring technologies focused on detection, classification, and prediction of developing machinery faults and performance degradation. Existing monitoring systems such as ICAS (Integrated Condition Assessment System), which is the Navy’s program of record and is deployed on many US Navy ships, employ alarm thresholds and event detection using rulebased algorithms. Adding the capability to predict the future condition (prognostics) of a machine would add significant benefit to the Navy practice. The current paper describes a framework and development process that allows more “plug ‘n play” integration of new diagnostic and prognostic technologies using evolving Open System Architecture (OSA) standards. Although many modules were developed in the PEDS framework, specific gas turbine modules that focus on compressor and nozzle degradation algorithms are discussed. The modules use statistical prediction algorithms and were developed using seeded fault data generated by the Navy engineering station. The modules are fully automated, interact with the existing monitoring system, process real-time data, and utilize advanced forecasting techniques. Such an advanced prognostic capability can enable a higher level of conditionbased maintenance for optimally managing total Life Cycle Costs (LCC) and readiness of assets.
17 citations
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04 Oct 1999TL;DR: In this article, the authors present algorithms and simulation results for the composite tracking of maneuvering targets through the use of multisensor-multisite integration in the presence of sensor residual bias.
Abstract: The integration of multiple sensors for target tracking is complex but has the potential to provide very accurate state estimates. For most applications, each sensor provides its information to a central location where the integration is performed and the resulting composite track can be very accurate when compared to the individual sensortracks. This composite track has the potential to provide enhanced system decisions and targeting informationnot otherwise available. However, sensor bias can severely degrade composite tracking performance when it is not properly considered. This paper presents algorithms and simulation results for the composite tracking of maneuvering targets through the use of multisensor-multisite integration in the presence of sensor residual bias.Keywords: Composite 'Iacking, Sensor Integration, Sensor Residual Bias 1. INTRODUCTION The integration of multiple sensors located on different platforms for tracking maneuvering targets has beenintensely investigated in recent years. Situational awareness has become very important due to the increasingcomplexity of the battlespace and can be greatly enhanced with effective sensor integration. For most techniques, acentral track is updated with the information (i.e., measurements, estimates, etc.) provided by the sensor suite and
17 citations
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TL;DR: The concomitance of facile fabrication, economic and scalable processing, and high performance-including a reduction in H2O2 decomposition activation energy of 40-50% over conventional material catalysts-paves the way for using these nanostructured microfibers in modern, small-scale underwater vehicle propulsion systems.
Abstract: Micro unmanned underwater vehicles (UUVs) need to house propulsion mechanisms that are small in size but sufficiently powerful to deliver on-demand acceleration for tight radius turns, burst-driven docking maneuvers, and low-speed course corrections. Recently, small-scale hydrogen peroxide (H2O2) propulsion mechanisms have shown great promise in delivering pulsatile thrust for such acceleration needs. However, the need for robust, high surface area nanocatalysts that can be manufactured on a large scale for integration into micro UUV reaction chambers is still needed. In this report, a thermal/electrical insulator, silicon oxide (SiO2) microfibers, is used as a support for platinum nanoparticle (PtNP) catalysts. The mercapto-silanization of the SiO2 microfibers enables strong covalent attachment with PtNPs, and the resultant PtNP–SiO2 fibers act as a robust, high surface area catalyst for H2O2 decomposition. The PtNP–SiO2 catalysts are fitted inside a micro UUV reaction chamber for vehicular propulsion; t...
17 citations
Authors
Showing all 2860 results
Name | H-index | Papers | Citations |
---|---|---|---|
James A. Yorke | 101 | 445 | 44101 |
Edward Ott | 101 | 669 | 44649 |
Sokrates T. Pantelides | 94 | 806 | 37427 |
J. M. D. Coey | 81 | 748 | 36364 |
Celso Grebogi | 76 | 488 | 22450 |
David N. Seidman | 74 | 595 | 23715 |
Mingzhou Ding | 69 | 256 | 17098 |
C. L. Cocke | 51 | 312 | 8185 |
Hairong Qi | 50 | 327 | 9909 |
Kevin J. Hemker | 49 | 231 | 10236 |
William L. Ditto | 43 | 193 | 7991 |
Carey E. Priebe | 43 | 404 | 8499 |
Clifford George | 41 | 235 | 5110 |
Judith L. Flippen-Anderson | 40 | 205 | 6110 |
Mortimer J. Kamlet | 39 | 108 | 12071 |