Results for “Multi-mode data analysis”

NASA NTRS2011

Gravitational-Wave Data Analysis with Spinning Merger-Ringdown Waveforms

The recent availability of high-quality, gravitational merger-ringdown waveforms from spinning black-hole systems has made possible the development of multi-mode GW templates for use in data-analysis studies of current and proposed interferometric GW detectors. We report on recent work at NASA Goddard, analyzing the most significant modes from aligned-spin black-hole-binary mergers. From these, we have developed time-domain merger-ringdown GW templates covering the aligned-spin portion of parameter space. We also discuss how using the full information content of aligned-spin mergers can significantly reduce uncertainties in some parameters, emphasizing the significant gains possible in the last stages of merger, inaccessible to inspiral-only post-Newtonian templates.

Kelly Bernard J.↗

NASA NTRS1992

Multi-Mode Excitation and Data Reduction for Fatigue Crack Characterization in Conducting Plates

Advances in the technique of fatigue crack characterization by resonant modal analysis have been achieved through a new excitation mechanism and data reduction of multiple resonance modes. A non-contacting electromagnetic device is used to apply a time varying Lorentz force to thin conducting sheets. The frequency and direction of the Lorentz force are such that resonance modes are generated in the test sample. By comparing the change in frequency between distinct resonant modes of a sample, detecting and sizing of fatigue cracks are achieved and frequency shifts caused by boundary condition changes can be discriminated against. Finite element modeling has been performed to verify experimental results.

Wincheski, B.↗

NASA NTRS2010

Ares Launch Vehicle Transonic Buffet Testing and Analysis Techniques

It is necessary to define the launch vehicle buffet loads to ensure that structural components and vehicle subsystems possess adequate strength, stress, and fatigue margins when the vehicle structural dynamic response to buffet forcing functions are considered. In order to obtain these forcing functions, the accepted method is to perform wind-tunnel testing of a rigid model instrumented with hundreds of unsteady pressure transducers designed to measure the buffet environment across the desired frequency range. The buffet wind-tunnel test program for the Ares Crew Launch Vehicle employed 3.5 percent scale rigid models of the Ares I and Ares I-X launch vehicles instrumented with 256 unsteady pressure transducers each. These models were tested at transonic conditions at the Transonic Dynamics Tunnel at NASA Langley Research Center. The ultimate deliverable of the Ares buffet test program are buffet forcing functions (BFFs) derived from integrating the measured fluctuating pressures on the rigid wind-tunnel models. These BFFs are then used as input to a multi-mode structural analysis to determine the vehicle response to buffet and the resulting buffet loads and accelerations. This paper discusses the development of the Ares I and I-X rigid buffet model test programs from the standpoint of model design, instrumentation system design, test implementation, data analysis techniques to yield final products, and presents normalized sectional buffet forcing function root-mean-squared levels.

Piatak, David J.↗

NASA NTRS1989

Spectral calibration analysis of the airborne oceanographic lidar

Efforts were concentrated on the spectral resolution of the Airborne Oceanographic Lidar (AOL). This year's work was targeted towards the analysis of calibration techniques to enable the AOL to measure absolute radiances of both passive and active modes of operation. Absolute spectral calibration of the AOL is necessary in order to fully understand and monitor the sensitivity and stability of the total system. Calibration is also needed to obtain valid surface truth data, with which to improve the accuracy of satellite-borne oceanic color scanners. In particular, accurate measurements of oceanic chlorophyll concentrations rests upon reliable irradiance calibrations of both laser induced and solar induced chlorophyll fluoresence. An analysis was performed on the spectral calibration methods used by the AOL. The optical path of the instrumentation was examined to study how the radiance from a calibration sphere was influenced. Ray tracing analysis was performed, including the Cassegrain-telescope optics. It was determined that the calibration radiance was significantly effected by optical-defocusing, due to close positioning of the calibration sphere with respect to the telescope. Since the multi-mode usages of the AOL require varying altitudes and trajectories, a computational algorithm was developed to compensate for image distortions of the telescope optics. Secondary mirror blockage, secondary vignetting, and beam divergence was determined, in order to account for the actual amount of calibrated flux received at the spectral sensors.

Rousey, Carlton E.↗

NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗