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The hydrogen- and self-broadened line widths of 116 (sup 14)NH(sub 3) ground state transitions with J,K = 1,0 to 10,10 have been measured at 0.0006 cm(sup -1) resolution using a Bruker spectrometer between 40 to 210 cm(sup -1). These experimental widths have been reproduced to 2.4% and 11% respectively using an heuristically derived expression of the form....
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The steady rise in demand for air transportation over the years has put much emphasis on the need for sophisticated air traffic flow management (TFM) within the National Airspace System (NAS). The NAS refers to hardware, software and people, including runways, radars, networks, FAA, airlines, etc., involved in air traffic management (ATM) in the US. One of the metrics that has been used to assess the performance of NAS is the actual delays provided through FAA's Air Traffic Operations Network (OPSNET). The OPSNET delay data includes those reportable delays, i.e. delays of 15 minutes or more experienced by Instrument Flight Rule (IFR) flights, submitted by the FAA facilities. These OPSNET delays are caused by the application of TFM initiatives in response to, for instance, weather conditions, increased traffic volume, equipment outages, airline operations, and runway conditions. TFM initiatives such as, ground stops, ground delay programs, rerouting, airborne holding, and miles-in-trail restrictions, are actions which are needed to control the air traffic demand to mitigate the demand-capacity imbalance due to the reduction in capacity. Consequently, TFM initiatives result in NAS delays. Of all the causes, weather has been identified as the most important causal factor for NAS delays. Therefore, in order to accurately assess the NAS performance, it has become necessary to create a baseline for NAS performance and establish a model which characterizes the relation between weather and NAS delays.
This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.
This document includes a viewgraph presentation plus the full paper presented at the conference. The Living With a Star Ion Flux Model (IFM) is a radiation environment risk mitigation tool that provides magnetospheric ion flux values for varying geomagnetic disturbance levels in the geospace environment. IFM incorporates flux observations from the Polar and Geotail spacecraft in a single statistical flux model. IFM is an engineering environment model which predicts the proton flux not only in the magnetosphere, but also in the solar wind and magnetosheath phenomenological regions. This paper describes the ion flux databases that allows for IFM output to be correlated with the geomagnetic activity level, as represented by the Kp index.
Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.
Two data sets of experimental field observations with a range of meteorological conditions are used to investigate the possibility of modeling near-surface soil temperature profiles in a bare soil. It is shown that commonly used heat flow methods that assume a constant ground heat flux can not be used to model the extreme variations in temperature that occur near the surface. This paper proposes a simple approach for modeling the surface soil temperature profiles from a single depth observation. This approach consists of two parts: 1) modeling an instantaneous ground flux profile based on net radiation and the ground heat flux at 5cm depth; 2) using this ground heat flux profile to extrapolate a single temperature observation to a continuous near surface temperature profile. The new model is validated with an independent data set from a different soil and under a range of meteorological conditions.
The goal of this LWS tools effort is the development of a new data-based F-region TOpside and PLAsmasphere (TOPLA) model for the electron density (Ne) and temperature (Te) for inclusion in the International Reference Ionosphere (IRI) model using newly available satellite data and models for these regions. The IRI model is the de facto international standard for specification of ionospheric parameters and is currently being considered as an ISO Technical Specification for the ionosphere. Our effort is directed towards improving the topside part of the model and extending it into the plasmasphere. Specifically we are planning to overcome the following shortcomings of the current IRI topside model: (I) overestimation of densities above 700 km by a factor of 2 and more, (3) unrealistically steep density profiles at high latitudes during very high solar activities, (4) no solar cycle variations and no semi-annual variations for the electron temperature, (5) discontinuities or unphysical gradients when merging with plasmaspheric models. We will report on first accomplishments and on the current status of the project.
We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.
By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.
Damage tolerance consists of analysis and experimentation working together. Impact damage is usually of most concern for laminated composites. Once impacted, the residual compression strength is usually of most interest. Other properties may be of more interest than compression (application dependent). A damage tolerance program is application specific (not everyone is building aircraft). The "Building Block Approach" is suggested for damage tolerance. Advantage can be taken of the excellent fatigue resistance of damaged laminates to save time and costs.
This slide presentation reviews the damage tolerance for composite laminates. It includes information surrounding observations on impact testing, laminate damage threshold, and fatigue.
This slide presentation reviews the concept of using Orthogonal Defect Classification (ODC) to identify pre-launch anomalies in software. The goals of this work are: (1) To characterize pre-launch software anomalies, using data from multiple spacecraft projects, by means of a defect-analysis technology, Orthogonal Defect Classification (ODC). (2) To support transfer of ODC to NASA projects through applications and demonstrations. Approach: Analyzed anomaly data using adaptation of Orthogonal Defect Classification (ODC) method. This project has adapted ODC for NASA use and applied to NASA projects.
A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.
One of the major technical problems associated with cryogenic liquid propellant systems used to supply rocket engines and their subassemblies and components is the phenomenon of propellant tank pressurant and ullage gas collapse. This collapse is mainly caused by heat transfer from ullage gas to tank walls and interfacing propellant, which are both at temperatures well below those of this gas. Mass transfer between ullage gas and cryogenic propellant can also occur and have minor to significant secondary effects that can increase or decrease ullage gas collapse. Pressurant gas is supplied into cryogenic propellant tanks in order to initially pressurize these tanks and then maintain required pressures as propellant is expelled from these tanks. The net effect of pressurant and ullage gas collapse is increased total mass and mass flow rate requirements of pressurant gases. For flight vehicles this leads to significant and undesirable weight penalties. For rocket engine component and subassembly ground test facilities this results in significantly increased facility hardware, construction, and operational costs. "Collapse Factor" is a parameter used to quantify the pressurant and ullage gas collapse. Accurate prediction of collapse factors, through analytical methods and modeling tools, and collection and evaluation of collapse factor data has evolved over the years since the start of space exploration programs in the 1950 s. Through the years, numerous documents have been published to preserve results of studies associated with the collapse factor phenomenon. This paper presents a summary and selected details of prior literature that document the aforementioned studies. Additionally other literature that present studies and results of heat and mass transfer processes, related to or providing important insights or analytical methods for the studies of collapse factor, are presented.
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When launching or landing a space craft on the regolith of a terrestrial surface, special attention needs to be paid to the rocket exhaust cratering effects. If the effects are not controlled, the rocket cratering could damage the spacecraft or other surrounding hardware. The cratering effects of a rocket landing on a planet's surface are not understood well, especially for the lunar case with the plume expanding in vacuum. As a result, the blast effects cannot be estimated sufficiently using analytical theories. It is necessary to develop physics-based simulation tools in order to calculate mission-essential parameters. In this work we test out the scaling laws of the physics in regard to growth rate of the crater depth. This will provide the physical insight necessary to begin the physics-based modeling.
A new model for Blade-Vortex Interaction noise generation during maneuvering flight is developed in this paper. Acoustic and performance data from both flight and wind tunnels are used to derive a non-dimensional and analytical performance/acoustic model that describes BVI noise in steady flight. The model is extended to transient maneuvering flight (pure pitch and roll transients) by using quasisteady assumptions throughout the prescribed maneuvers. Ground noise measurements, taken during maneuvering flight of a Bell 206B helicopter, show that many of the noise radiation details are captured. The result is a computationally efficient Blade-Vortex Interaction noise model with sufficient accuracy to account for transient maneuvering flight. The code can be run in real time to predict transient maneuver noise and is suitable for use in an acoustic mission-planning tool.