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In this paper, we present error sources and predicted performance of the Wide-Swath Ocean altimeter, an instrument which has been proposed as an experiment for the NASA/CNES Ocean Surface Topography Mission. The data obtained by this instrument will allow the detailed study of ocean mesoscale phenomena, with a space-time resolution which cannot be achieved by a single conventional nadir altimeter.
Recent NASA initiatives for space exploration have reinvigorated research on Apollo-like capsule vehicles. Aerothermodynamic characteristics of these capsule configurations during reentry play a crucial role in the performance and safety of the planetary entry probes and the crew exploration vehicles. At issue are the forebody thermal shield protection and afterbody aeroheating predictions. Due to the lack of flight or wind tunnel measurements at hypersonic speed, design decisions on such vehicles would rely heavily on computational results. Validation of current computational tools against experimental measurement thus becomes one of the most important tasks for general hypersonic research. This paper is focused on time-accurate numerical computations of hypersonic flows over a set of capsule configurations, which employ a counterflow jet to offset the detached bow shock. The accompanying increased shock stand-off distance and modified heat transfer characteristics associated with the counterflow jet may provide guidance for future design of hypersonic reentry capsules. The newly emerged space-time conservation element solution element (CESE) method is used to perform time-accurate, unstructured mesh Navier-Stokes computations for all cases investigated. The results show good agreement between experimental and numerical Schlieren pictures. Surface heat flux and aerodynamic force predictions of the capsule configurations are discussed in detail.
Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.
Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).
The primary focus of my presentation is the development of the jet noise prediction code JeNo with most examples coming from the experimental work that drove the theoretical development and validation. JeNo is a statistical jet noise prediction code, based upon the Lilley acoustic analogy. Our approach uses time-average 2-D or 3-D mean and turbulent statistics of the flow as input. The output is source distributions and spectral directivity. NASA has been investing in development of statistical jet noise prediction tools because these seem to fit the middle ground that allows enough flexibility and fidelity for jet noise source diagnostics while having reasonable computational requirements. These tools rely on Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solutions as input for computing far-field spectral directivity using an acoustic analogy. There are many ways acoustic analogies can be created, each with a series of assumptions and models, many often taken unknowingly. And the resulting prediction can be easily reverse-engineered by altering the models contained within. However, only an approach which is mathematically sound, with assumptions validated and modeled quantities checked against direct measurement will give consistently correct answers. Many quantities are modeled in acoustic analogies precisely because they have been impossible to measure or calculate, making this requirement a difficult task. The NASA team has spent considerable effort identifying all the assumptions and models used to take the Navier-Stokes equations to the point of a statistical calculation via an acoustic analogy very similar to that proposed by Lilley. Assumptions have been identified and experiments have been developed to test these assumptions. In some cases this has resulted in assumptions being changed. Beginning with the CFD used as input to the acoustic analogy, models for turbulence closure used in RANS CFD codes have been explored and compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.
A method for using non-resonant Raman lidar during daytime hours is presented. A dual (or quadruple) arrangement of electro-optical channels is set up in the lidar receiver. Each channel contains its own optical spectral response as determined by an appropriate set of interference filters. The incoming signal is split and fed into two channels, filtered (simultaneously) and then inserted into the input terminals of an operational amplifier. The difference signal is selected and amplified whereas the common portion of the signal is highly attenuated (Common Mode Re.jection Ratio = 75-80db). For the present hardware, daylight intensities 10(exp 2)-10(exp 3) times Raman signals are received simultaneously. Mean values of intensities of daylight signals which give rise to a constant differences merely shift the value of the measured variable at the ground. These mean value signals have their common part highly attenuated. The differences of the fluctuation portions of the daylight signal represents a noise signal. Identical (space-time) optical paths for each component of the daylight signal produce the same fluctuational spectra in each channel. Hence noise levels, much less than signal levels, are anticipated. First a N2-H2 ) signal pair is differenced. Then an N2-O2 pair is differenced and used for instrumental normalization purposes. Signal levels to be encountered are quite well known as a result of prior field work. Improved optical design of laser system can reduce mean value of daylight intensities by 10(exp 2). Thus the mean daylight intensity can be set equal to the expected signal levels by more advanced optical design. Performance characteristics of photomultiplier pairs are discussed in this connection.
The objective of the Space Telescope Project is to orbit a high quality optical 2.4-meter telescope system by the Space Shuttle for use by the astronomical community in conjunction with NASA. The scientific objectives of the Space Telescope are to determine the constitution, physical characteristics, and dynamics of celestial bodies; the nature of processes which occur in the extreme physical conditions existing in stellar objects; the history and evolution of the universe; and whether the laws of nature are universal in the space-time continuum. Like ground-based telescopes, the Space Telescope was designed as a general-purpose instrument, capable of utilizing a wide variety of scientific instruments at its focal plane. This multi-purpose characteristic will allow the Space Telescope to be effectively used as a national facility, capable of supporting the astronomical needs for an international user community and hence making contributions to man's needs. By using the Space Shuttle to provide scientific instrument upgrading and subsystems maintenance, the useful and effective operational lifetime of the Space Telescope will be extended to a decade or more.
The 2003 Fundamental Physics workshop included presentations ranging from forces acting on RNA, to properties of clouds of degenerate Fermi atoms, to techniques to probe for added space-time dimensions, and to flight hardware for low temperature experiments, among others.
This paper indicates that topography, Rossby wave dynamics, and eddy/stream interactions, all appear to have a significant role in determining the space-time scales and propagation properties of the long-period response of sea level in the Gulf Stream.
Evaluation of general physical condition of Gemini IV flight crew with increasing time under space flight conditions - response of cardiovascular system to calibrated workload
Quantitative description of climatic element field by orthogonal functions
Euclidean nature of relativistic rotating disk in conclusions of Eddington and Lorentz
Retarded observer time as coordinate in relativistic spherical hydrodynamic equations prevents Schwarzschild surface formation
Elliptic Kruskal-Schwarzschild space, discussing identification of points which limit Kruskal space into Minkowski space
Correlation properties of quantities depending on space and time
Kruskal space in general relativity and uniform accelerated rigid rod in special relativity show striking formal similarities
Static axisymmetric interior solution of Einstein field equations which matches smoothly to one of Weyl exterior solutions
Parametrization of reduced problem of stationary axially symmetric gravity fields