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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

An Experimental Study of the Flowfield on a Semispan Rectangular Wing with a Simulated Glaze Ice Accretion

Wind tunnel experiments were conducted in order to study the effect of a simulated glaze ice accretion on the flowfield of a semispan, reflection-plane, rectangular wing at Re = 1.5 million and M = 0.12. A laser Doppler velocimeter was used to map the flowfield on the upper surface of the model in both the clean and iced configurations at alpha = 0, 4, and 8 degrees angle of attack. At low angles of attack, the massive separation bubble aft of the leading edge ice horn was found to behave in a manner similar to laminar separation bubbles. At alpha = 0 and 4 degrees, the locations of transition and reattachment, as deduced from momentum thickness distributions, were found to be in good agreement with transition and reattachment locations in laminar separation bubbles. These values at y/b = 0.470, the centerline measurement location, matched well with data obtained on a similar but two dimensional model. The measured velocity profiles on the iced wing compared reasonably with the predicted profiles from Navier-Stokes computations. The iced-induced separation bubble was also found to have features similar to the recirculating region aft of rearward-facing steps. At alpha = 0 degrees and 4 degrees, reverse flow magnitudes and turbulence intensity levels were typical of those found in the recirculating region aft of rearward-facing steps. The calculated separation streamline aft of the ice horn at alpha = 4 degrees, y/b = 0.470 coincided with the locus of the maximum Reynolds normal stress. The maximum Reynolds normal stress peaked at two locations along the separation streamline. The location of the first peak-value coincided with the transition location, as deduced from the momentum thickness distributions. The location of the second peak was just upstream of reattachment, in good agreement with measurements of flows over similar obstacles. The intermittency factor in the vicinity of reattachment at alpha = 4 degrees, y/b = 0.470, revealed the time-dependent nature of the reattachment process. The size and extent of the separation bubble were found to be a function of angle of attack and the spanwise location. Three dimensional effects were found to be strongest at alpha = 8 degrees. The calculated separation and stagnation streamlines were found to vary little with spanwise location at alpha = 0 degrees. The calculated separation streamlines at alpha = 4 degrees revealed that the bubble was largest near the centerline measurement plane, whereas the tip-induced vortex flow and the model root-tunnel wall boundary-layer interaction reduced the size of the bubble. These effects were found to be most dramatic at alpha = 8 degrees.

Khodadoust, Abdollah↗
NASA NTRS2002

The footprints of visual attention in the Posner cueing paradigm revealed by classification images

In the Posner cueing paradigm, observers' performance in detecting a target is typically better in trials in which the target is present at the cued location than in trials in which the target appears at the uncued location. This effect can be explained in terms of a Bayesian observer where visual attention simply weights the information differently at the cued (attended) and uncued (unattended) locations without a change in the quality of processing at each location. Alternatively, it could also be explained in terms of visual attention changing the shape of the perceptual filter at the cued location. In this study, we use the classification image technique to compare the human perceptual filters at the cued and uncued locations in a contrast discrimination task. We did not find statistically significant differences between the shapes of the inferred perceptual filters across the two locations, nor did the observed differences account for the measured cueing effects in human observers. Instead, we found a difference in the magnitude of the classification images, supporting the idea that visual attention changes the weighting of information at the cued and uncued location, but does not change the quality of processing at each individual location.

Non-NASA Center↗
NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗
NASA NTRS2008

Simulation of Ground Winds Time Series for the NASA Crew Launch Vehicle (CLV)

Simulation of wind time series based on power spectrum density (PSD) and spectral coherence models for ground wind turbulence is described. The wind models, originally developed for the Shuttle program, are based on wind measurements at the NASA 150-m meteorological tower at Cape Canaveral, FL. The current application is for the design and/or protection of the CLV from wind effects during on-pad exposure during periods from as long as days prior to launch, to seconds or minutes just prior to launch and seconds after launch. The evaluation of vehicle response to wind will influence the design and operation of constraint systems for support of the on-pad vehicle. Longitudinal and lateral wind component time series are simulated at critical vehicle locations. The PSD model for wind turbulence is a function of mean wind speed, elevation and temporal frequency. Integration of the PSD equation over a selected frequency range yields the variance of the time series to be simulated. The square root of the PSD defines a low-pass filter that is applied to adjust the components of the Fast Fourier Transform (FFT) of Gaussian white noise. The first simulated time series near the top of the launch vehicle is the inverse transform of the adjusted FFT. Simulation of the wind component time series at the nearest adjacent location (and all other succeeding next nearest locations) is based on a model for the coherence between winds at two locations as a function of frequency and separation distance, where the adjacent locations are separated vertically and/or horizontally. The coherence function is used to calculate a coherence weighted FFT of the wind at the next nearest location, given the FFT of the simulated time series at the previous location and the essentially incoherent FFT of the wind at the selected location derived a priori from the PSD model. The simulated time series at each adjacent location is the inverse Fourier transform of the coherence weighted FFT. For a selected design case, the equations, the process and the simulated time series at multiple vehicle stations are presented.

Adelfang, Stanley I.↗
NASA NTRS2020

A Summary of Airframe Results from a Fokker F28 Full-Scale Crash Test

On June 20, 2019, a full-scale crash test was conducted on a Fokker F28 MK1000 aircraft as a part of a joint NASA / Federal Aviation Administration (FAA) research effort to investigate the crashworthiness characteristics of a Transport Category Aircraft (TCA), as defined by 14 Code of Federal Regulations, Part 25. The test was conducted at NASA Langley Research Center’s Landing and Impact Research Facility and was the third in a test series to further understand TCA crashworthiness characteristics. The test article featured 24 Anthropomorphic Test Devices (ATDs, a.k.a. crash test dummies), and over 700 channels of instrumentation covering major aircraft structures such as the wings, tail, nose, cockpit and cabin, along with recording seat, overhead bin and ATD accelerations. Five different U.S. Government agencies collaborated on the test including: NASA, the FAA, the U.S. Army Research Laboratory, the National Transportation Safety Board (NTSB) and the National Highway Traffic Safety Administration (NHTSA). This report will covertest article build up, which includes weight and balance measurements and pre-test laser scans. It will also cover the events of the test, which includes the test sequence of events and post-test damage inspections. Finally, it will show airframe level accelerations at all positions measured, with discussion on correlation to the airframe damage witnessed. The test build up consisted of outfitting the main cabin section of the aircraft with 24 ATDs seated in 12 rows of seats, overhead mass and the under floor cargo area with foam representing the luggage. The main cabin also included all of the onboard data system pallets, which recorded711 channels of data from the test. All major portions of the aircraft were instrumented, including locations at the floor / frame junction locations in the cabin where the ATDs were located along with other major exterior components such as the nose, the tail, each engine cowling, and at overhead hat rack ballast locations. The aircraft impacted a soil surface at65.3 ft/s horizontal and 31.8 ft/s vertical velocities. The aircraft plowed through the soil and slid a distance of 32.5 feet from the initial impact location. There was a secondary impact occurring 0.9 s due to the “slap down” of the nose during the post-impact response. The duration of the event from impact to rest was1.62 seconds. There was major structural damage in the lower fuselage areas around the Wingbox and Aft Fuselage sections. The Aft Fuselage section deformation caused some cabin intrusion from the keel beams pushing the aft cabin floor into the cabin. Other structural deformations occurred around the tail and at transition regions in the aircraft structure; mainly in locations of differing overall stiffness. The data obtained showed average vertical accelerations between 12 and 16 g with spikes reaching almost 40 g at certain floor locations. Average horizontal accelerations were approximately 10 g for all floor locations measured with spikes reaching approximately 25 g in some locations. The report includes a full set of results on aircraft deformation and accelerations along with discussions as to the effect on the aircraft structure.

Justin D Littell↗
NASA NTRS2010

Quantification of Juniperus Ashei Pollen Production for the Development of Forecasting Models

Juniperus ashei pollen is considered one of the most allergenic species of Cupressaceae in North America. Juniperus ashei is distributed throughout central Texas, Northern Mexico, the Arbuckle Mountains of south central Oklahoma, and the Ozark Mountains of northern Arkansas and southwestern Missouri. The large amount of airborne pollen that J. ashei produces affects inhabitants of cities and towns adjacent to juniper woodland areas and because juniper pollen can be transported over long distances, it affects populations that are far away. In order to create a dynamic forecast system for allergy and asthma sufferers, pollen production must be estimated. Estimation of pollen production requires the estimation of male cone production. Two locations in the Arbuckle Mountains of Oklahoma and 4 locations in the Edwards Plateau region of Texas were chosen as sampling sites. Trees were measured to determine approximate size. Male to female ratio was determined and pollen cone production was estimated using a qualitative scale from 0 to 2. Cones were counted from harvested 1/8 sections of representative trees. The representative trees were measured and approximate surface area of the tree was calculated. Using the representative tree data, the number of cones per square meter was calculated for medium production (1) and high production (2) trees. These numbers were extrapolated to calculate cone production in other trees sampled. Calibration was achieved within each location's sub-plot by counting cones on 5 branches collected from 5 sides of both high production and medium production trees. The total area sampled in each location was 0.06 hectare and total cone production varied greatly from location to location. The highest production area produced 5.8 million cones while the lowest production area produced 72,000 cones. A single representative high production tree in the Arbuckle Mountains produced 1.38 million cones. The number of trees per location was relatively uniform, but the number of high cone production trees varied greatly. Although there is great diversity in the locations making it difficult to determine which factors are most important, cone production was well correlated with certain stand characteristics including trunk diameter.

Bunderson, L. D.↗
NASA NTRS2023

X-57 Cockpit Interface Control Document (ICD-CEPT-006)

The Cockpit Interface Control Document defines the hardware interfaces between the X-57 cockpit and subsystems. It provides locational and operational information in support of ground and flight operations with details on controls and displays that include Modes of Operation, Start-Up and Shut- Down Sequence diagrams and captures the current state of the MOD II Avionics Power Architecture. There is also preliminary information of the MOD III and MOD IV configurations. Microsoft PowerPoint was chosen for the document as early development required frequent meetings with multiple customers including aircraft operators (pilots), ground operations, support contractors and power, instrumentation, and human systems integration engineers and PowerPoint enabled presentations that could be quickly modified based on customer and developer interaction. One of the driving requirements for the cockpit design was to keep the left side panel as close the stock Tecnam panel as possible to reduce the failure risk of flight critical indicators. The original annunciator panel in the left side panel was modified to alert the pilot to failures in critical X-57 subsystems and an operator audio alert capability was added for these subsystems. Power-Up switches for the aircraft low voltage 13.8 VDC systems are located at the bottom of the left side panel and center panel, the same location as the stock Tecnam 13.8 VDC switches. The switches for energizing the high voltage system were located in the overhead panel to reduce the risk of inadvertently energizing the high voltage system during the low voltage power-up sequence. The Cruise Motor ARM switches were also located in the overhead panel and correspond to the same location as the stock Tecnam ignition switches. The stock Tecnam throttle levers and prop pitch levers were retained for the X-57. The throttle levers were renamed torque levers since they controlled the commanded torque to the cruise motors. The prop pitch levers provide a commanded RPM signal to an electronic prop pitch controller. X-57 specific displays, located in the right-side panel, are driven by dedicated sensors that monitor right and left side cruise motor RPM, right and left high voltage “Traction Bus” A and B (voltage, current and power) and the Avionics Bus DC converters (A and B) voltage and current. An X-57 Multi-Function Display (MFD) located in the center panel displays CAN Bus parameters. CAN Bus architecture is not certified for flight so these displays could not be used for safety critical information but were designed to be used for test point information only.

Laura Kushner↗
NASA NTRS1983

Analytical model of rotor wake aerodynamics in ground effect

The model and the computer program developed provides the velocity, location, and circulation of the tip vortices of a two-blade helicopter in and out of the ground effect. Comparison of the theoretical results with some experimental measurements for the location of the wake indicate that there is excellent accuracy in the vicinity of the rotor and fair amount of accuracy far from it. Having the location of the wake at all times enables us to compute the history of the velocity and the location of any point in the flow. The main goal of out study, induced velocity at the rotor, can also be calculated in addition to stream lines and streak lines. Since the wake location close to the rotor is known more accurately than at other places, the calculated induced velocity over the disc should be a good estimate of the real induced velocity, with the exception of the blade location, because each blade was replaced only by a vortex line. Because no experimental measurements of the wake close to the ground were available to us, quantitative evaluation of the theoretical wake was not possible. But qualitatively we have been able to show excellent agreement. Comparison of flow visualization with out results has indicated the location of the ground vortex is estimated excellently. Also the flow field in hover is well represented.

Saberi, H. A.↗
NASA NTRS1989

Control surface spanwise placement in active flutter suppression systems

All flutter suppression systems require sensors to detect the movement of the lifting surface and to activate a control surface according to a synthesized control law. Most of the work performed to date relates to the development of control laws based on predetermined locations of sensors and control surfaces. These locations of sensors and control surfaces are determined either arbitrarily, or by means of a trial and error procedure. The aerodynamic energy concept indicates that the sensors should be located within the activated strip. Furthermore, the best chordwise location of a sensor activating a T.E. control surface is around the 65 percent chord location. The best chordwise location for a sensor activating a L.E. surface is shown to lie upstream of the wing (around 20 percent upstream of the leading edge), or alternatively, two sensors located along the same chord should be used.

Nissim, E.↗
NASA NTRS1992

Spectral infrared hemispherical reflectance measurements for LDEF tray clamps

This paper describes infrared hemispherical reflectance measurements (2-15 microns) that were made on 58 chromic acid anodized tray clamps retrieved from the LDEF spacecraft. These clamps were used for maintaining the experiments in place and were located at various locations about the spacecraft. Changes in reflectance of the tray clamps at these locations were compared with atomic oxygen fluxes at the same locations. A decrease in absorption band depth was seen for the surfaces exposed to space indicating that there was some surface layer erosion. In all of the surfaces measured, little evidence of contamination was observed and none of the samples showed evidence of the brown nicotine stain that was so prominent in other experiments. Total emissivity values were calculated for both exposed and unexposed tray clamp surfaces. Only small differences, usually less than 1 percent, were observed. The spectral reflectances were measured using a hemi-ellipsoidal mirror reflectometer matched with an interferometer spectrometer. The rapid scanning capability of the interferometer allowed the reflectance measurements to be made in a timely fashion. The ellipsoidal mirror has its two foci separated by 2 inches and located on the major axis. A blackbody source was located at one focus while the tray clamp samples were located at the conjugate focus. The blackbody radiation was modulated and then focused by the ellipsoid onto the tray clamps. Radiation reflected from the tray clamp was sampled by the interferometer by viewing through a hole in the ellipsoid. A gold mirror (reflectance approximately 98 percent) was used as the reference surface.

Wood, Bobby E.↗
NASA NTRS1993

Yana ring structure, North-Eastern Siberia: A possible counterpart of coronae on Venus

An arch of Verkhoyansky Range in NE Siberia, Russia is considered as W and S parts of the rim of the large ring structure, referred hereafter as Yana Ring Structure (YRS). It has general appearance similar to coronae on Venus and could be considered as the terrestrial counter part of coronae. The structure is located between 63 and 70 deg N, 125 and 140 deg E. The outer diameter of YRS (between the rim feet) is 680-700 km. The rim crest diameter is 500-520 km. The inner diameters (between the inner feet of the rim) is 320-350 km. The rim of YRS consist of the following topographic features: W segment is Orulgan Range (N part of Verkhoyansky Range), SW and S segments consist of S part of Verkhoyansky Range, SE segment is Elginskoye Ploskogorye (Tableland), E segment is Chersky Range (its part W of Indigirka River), NE segment is Selennyakhsky Range, and NW segment is Kular Range. Inside this ring of mountains Yanskoye Ploskogorye (Tableland) is located. The circular outlines of YRS are marked with the large river valleys located outside: Lena River (lower of Aldan River mouth) is located W from YRS, Aldan River (lower of Amga River mouth) is from S, Indigirka River (between 64 and 67 deg N lat) is from E, and Selennyakh River (the part running N to S) is from NE. The ring patterns inside the mountaineous rim of YRS are marked with the tributaries of Yana River. The largest ring here, 300 km in diameter, consists of Bytangay (with Bellyakh) River at W, Nelgese and Derbeke Rivers at S/SE, and Tuostakh River at E. The typical altitudes of YRS mountain rim are 1000-2000 m. The maximal ones are: 2400 m in W part of the rim, 2300 m in S, 1600 m in SE, 2200-2500 m in E, and 1300-1500 m in N. The central part of YRS have typical altitudes of 400-600 m. There are lowlands with altitudes 50-200 m to the S, W, N, and NW outside YRS Oymyakonskoye Nagorye (Highland) is located SE of YRS at 500-1500 m altitudes. It should be recognized from this description YRS have a general appearance of circular highland with its central plateau located 1000-2000 m lower than surrounding mountain rim, but 300-400 m higher than plains of lowlands located outside the rim. Such topographic patterns are typical for coronae on Venus. The diameter of YRS is equal to the largest coronae on Venus. There are only 3 or 4 structures of such or larger size on the whole Venus. This calls to compare morphology and geologic evolution of YRS with morphology and models of coronae evolutions especially the largest ones, to search the similarities and/or differences in geologic histories of the structures on the Earth and Venus.

Burba, G. A.↗
NASA NTRS1995

The magnetic evolution of AR 6555 which lead to two impulsive, readily compact, X-type flares

We study the evolution of the vector magnetic field and the sunspot motions observed in AR 6555 during 23-26 Mar. 1991. This region displays two locations of large magnetic shear that were also sites of flare activity. The first location produced two large (X-class) flares during the period covered by our observations. The second location had larger magnetic shear than the first, but produced only small (M- and C-class) flares during our observations. We study the evolution of the photospheric magnetic field in relation to the large flares in the first location. These flares occurred around the same included polarity, and have very similar characteristics (soft X-ray light curves, energies, etc.). However, the whole active region has changed substantially in the period between them. We found several characteristics of the region that appear related to the occurrence of these flares. (1) The flares occurred near regions of large magnetic 'shear,' but not at the locations of maximum shear or maximum field. (2) Potential field extrapolations of the observed field suggest that the topology changed, prior to the first of the two flares, in such a way that a null appeared in the coarse magnetic field. (3) This null was located close to both X-class flares, and remained in that location for a few days while the two flares were observed. (4) The flaring region has a pattern of vector field and sunspot motions in which material is 'squeezed' along the polarity inversion line. This pattern is very different from that usually associated with shearing arcades, but it is similar to that suggested previously by Fontenla and Davis. The vertical electric currents, inferred from the transverse field, are consistent with this pattern. (5) A major reconfiguration of the longitudinal field and the vertical electric currents occurred just prior to the first of the two flares. Both changes imply substantial variations of the magnetic structure of the region. On the basis of the available data we suggest that these changes made the flaring possible, and we develop a scenario that can explain the origin of the magnetic free energy that was released in these flares.

Ambastha, A.↗
NASA NTRS1995

Optical fiber sensors for damage analysis in aerospace materials

Under this grant, fiber optic sensors were investigated for use in the nondestructive evaluation of aging aircraft. Specifically, optical fiber sensors for detection and location of impacts on a surface, and for detection of corrosion in metals were developed. The use of neural networks was investigated for determining impact location by processing the output of a network of fiberoptic strain sensors distributed on a surface. This approach employs triangulation to determine location by comparing the arrival times at several sensors, of the acoustic signal generated by the impact. For this study, a neural network simulator running on a personal computer was used to train a network using a back-propagation algorithm. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors are attached to or embedded in the surface, so that stress waves emanating from an impact can be detected. The ability of the network to determine impact location by time-or-arrival of acoustic signals was assessed by comparing network outputs with actual experimental results using impacts on a panel instrumented with optical fiber sensors. Using the neural network to process the sensor outputs, the impact location can be inferred to centimeter range accuracy directly from the arrival time data. In addition, the network can be trained to determine impact location, regardless of material anisotropy. Results demonstrate that a back-propagation network identifies impact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate. Two different approaches were investigated for the development of fiber optic sensors for corrosion detection in metals, both utilizing optical fiber sensors with metal coatings. In the first approach, an extrinsic Fabry-Perot interferometric fiber optic strain sensor was placed under tensile stress, and while in the resulting strained position, a thick coating of metal was applied. Due to an increase in the quantity of material, the sensor does not return to its original position upon removal of the applied stress, and some residual strain is maintained within the sensor element. As the metal thickness decreases due to corrosion, this strain is released, providing the sensing mechanism for corrosion detection. In the second approach, photosensitive optical fibers with long period Bragg gratings in the core were coated with metal. The Bragg gratings serve to couple core modes at discrete wavelengths to cladding modes. Since cladding modes interact with the metal coating surrounding the fiber cladding, the specific wavelengths coupled from core to cladding depend on the refractive index of the metal coating. Therefore, as the metal corrodes, the resulting change in index of the coating may be measured by measuring the change in wavelength of the coupled mode. Results demonstrate that both approaches can be successfully used to track the loss in metal coating on the optical fiber sensors due to corrosion.

Schindler, Paul↗
NASA NTRS1995

The Magnetic Evolution of AR 6555 which led to Two Impulsive, Relatively Compact, X-Type Flares

We study the evolution of the vector magnetic field and the sunspot motions observed in AR 6555 during 1991 March 23-26. This region displays two locations of large magnetic shear that were also sites of flare activity. The first location produced two large (X-class) flares during the period covered by our observations. The second location had larger magnetic shear than the first but produced only small (M- and C-class) flares during our observations. We study the evolution of the photospheric magnetic field in relation to the large flares in the first location. These flares occurred around the same included polarity and have very similar characteristics (soft X-ray light curves, energies, etc,). However, the whole active region has changed substantially in the period between them. We found several characteristics of the region that appear related to the occurrence of these flares: (1) The flares occurred near regions of large magnetic 'shear' but not at the locations of maximum shear or maximum field. (2) Potential field extrapolations of the observed field suggest that the topology changed, prior to the first of the two flares, in such a way that a null appeared in the coarse magnetic field. (3) This null was located close to both X-class flares and remained in that location for a few days while the two flares were observed. (4) The flaring region has a pattern of vector field and sunspot motions in which material is 'squeezed' along the polarity inversion line. This pattern is very different from that usually associated with shearing arcades, but it is similar to that suggested previously by Fontenia and Davis. The vertical electric currents, inferred from the transverse field, are consistent with this pattern. (5) A major reconfiguration of the longitudinal field and the vertical electric currents occurred just prior to the first of the two flares. Both changes imply substantial variations of the magnetic structure of the region. On the basis of the available data we suggest that these changes made the flaring possible, and we develop a scenario that can explain the origin of the magnetic free-energy that was released in these flares.

Fontenla, J. M.↗
NASA NTRS1999

Lunar Meteorites and Implications for Compositional Remote Sensing of the Lunar Surface

Lunar meteorites (LMs) are rocks found on Earth that were ejected from the Moon by impact of an asteroidal meteoroid. Three factors make the LMs important to remote-sensing studies: (1) Most are breccias composed of regolith or fragmental material; (2) all are rocks that resided (or breccias composed of material that resided) in the upper few meters of the Moon prior to launch and (3) most apparently come from areas distant from the Apollo sites. How Many Lunar Locations? At this writing (June 1999), there are 18 known lunar meteorite specimens. When unambiguous cases of terrestrial pairing are considered, the number of actual LMs reduces to 13. (Terrestrial pairing is when a single piece of lunar rock entered Earth's atmosphere, but multiple fragments were produced because the meteoroid broke apart on entry, upon hitting the ground or ice, or while being transported through the ice.) We have no reason to believe that LMs preferentially derive from any specific region(s) of the Moon; i.e., we believe that they are samples from random locations. However, we do not know how many different locations are represented by the LMs; mathematically, it could be as few as 1 or as many as 13. The actual maximum is < 13 because in some cases a single impact appears to have yielded more than one LM. Yamato 793169 and Asuka 881757 are considered "source-crater paired" or "launch paired" because they are compositionally and petrographically similar to each other and distinct from the others, and both have similar cosmic-ray exposure (CRE) histories. The same can be said of QUE 94281 and Y 793274. Thus the 13 meteorites probably represent a maximum of 11 locations on the Moon. The minimum number of likely source craters is debated and in flux as new data for different isotopic systems are obtained. Conservatively, considering CRE data only, a minimum of about 5 impacts is required. Compositional and petrographic data offer only probabilistic constraints. An extreme, but not unreasonable viewpoint, is that such data offer no constraint. For example, if one were to cut up the Apollo 17 landing site (which was selected for its diversity) into softball-sized pieces, some of those pieces (e.g., sample 70135) would be crystalline mare basalts like Y 793169 whereas others (e.g., sample 73131 would be feldspathic regolith breccias like MAC 88104/ 88105. However, nature is not so devious. Warren argues that LMs come from craters of only a few kilometers in diameter. If so, even though CRE data allow, for example, that ALHA 81005 and Y 791197) were launched simultaneously from the same crater, the probability is nevertheless low because the two meteorites are compositionally and mineralogically distinct. Thus, within the allowed range (5-11) for the number of locations represented by the LMs, values at the high end of the range are probably more likely. Mare Meteorites: Three LMs consist almost entirely of mare basalt. Two, Y 793169 and Asuka 881757, are unbrecciated, low-Ti, crystalline rocks that are compositionally and mineralogically similar (but not identical) to each other; they probably derive from a single lunar-mare location. The third, EET 87521/96008, is a fragmental breccia consisting predominantly of VLT mare basalt. Thus, these LMs probably represent only two lunar mare locations. The basaltic LMs have mineral and bulk compositions distinct from Apollo mare basalts. The petrography of Calcalong Creek has not been described in detail, but compositionally it is unique in that it corresponds to a mixture (breccia) of about one-half feldspathic material (i.e., the mean composition of the feldspathic lunar meteorites, below), one-fourth KREEP norite, one-fourth VLT mare basalt (like EET 87521), and 1% CI chondrite. With 4 micro g/g Th and correspondingly high concentrations of other incompatible elements, it is the only lunar meteorite that is likely to have come from within the Procellarum KREEP Terrane (PKT). Yamato 793274 and QUE 94281 are together distinct in being fragmental breccias containing subequal parts of feldspathic highland material and VLT mare basalt. Jolliff et al. estimate a mare to highland ratio of 54:46 for QUE 94281 and 62:38 for Y 793274; this difference is well within the range observed for soils collected only centimeters apart (in cores) at interface site like Apollo 15 and 17 [11]. Although the two meteorites were found on opposite sides of Antarctica, they are probably launch-paired. The strongest evidence is that the pyroclastic glass spherules that occur in both are of two compositional groups and the two groups are essentially the same in both meteorites. Yamato 791197 is nominally a feldspathic lunar meteorite (below), but among FLMs, it probably contains the highest abundance of clasts and glasses of mare derivation. As a consequence, its composition is at the high-Fe, low-Mg end of the range for FLMs and is not included in the FLM average of Table 1. Its composition is consistent with about 10% mare-derived material. Similarly, the two small (Y 82) pieces of Y 82192/82193186032 are more mafic than the large (Y 86) piece, probably as a result of about 7% mare-derived material. All Apollo missions went to areas in or near the PKT, and, consequently, all Apollo regolith samples are contaminated with Th-rich material from the PKT. At the nominally "typical" highland site, Apollo 16, about 30% of the regolith (<1-mm fines) is Th-rich ejecta from the Imbrium impact and about 6% is mare material probably derived from mare basins. Thus Apollo 16 regolith is not typical of the highlands. Among Apollo rocks, the compositions of the FLMs correspond most closely to the feldspathic granulitic breccias of Apollo 16 and 17. (Additional information is contained in original)

Korotev, R. L.↗
NASA NTRS2007

Advanced Systems for Monitoring Underwater Sounds

The term "Passive Acoustic Monitoring System" (PAMS) describes a developmental sensing-and-data-acquisition system for recording underwater sounds. The sounds (more precisely, digitized and preprocessed versions from acoustic transducers) are subsequently analyzed by a combination of data processing and interpretation to identify and/or, in some cases, to locate the sources of those sounds. PAMS was originally designed to locate the sources such as fish of species that one knows or seeks to identify. The PAMS unit could also be used to locate other sources, for example, marine life, human divers, and/or vessels. The underlying principles of passive acoustic sensing and analyzing acoustic-signal data in conjunction with temperature and salinity data are not new and not unique to PAMS. Part of the uniqueness of the PAMS design is that it is the first deep-sea instrumentation design to provide a capability for studying soniferous marine animals (especially fish) over the wide depth range described below. The uniqueness of PAMS also lies partly in a synergistic combination of advanced sensing, packaging, and data-processing design features with features adapted from proven marine instrumentation systems. This combination affords a versatility that enables adaptation to a variety of undersea missions using a variety of sensors. The interpretation of acoustic data can include visual inspection of power-spectrum plots for identification of spectral signatures of known biological species or artificial sources. Alternatively or in addition, data analysis could include determination of relative times of arrival of signals at different acoustic sensors arrayed at known locations. From these times of arrival, locations of acoustic sources (and errors in those locations) can be estimated. Estimates of relative locations of sources and sensors can be refined through analysis of the attenuation of sound in the intervening water in combination with water-temperature and salinity data acquired by instrumentation systems other than PAMS. A PAMS is packaged as a battery-powered unit, mated with external sensors, that can operate in the ocean at any depth from 2 m to 1 km. A PAMS includes a pressure housing, a deep-sea battery, a hydrophone (which is one of the mating external sensors), and an external monitor and keyboard box. In addition to acoustic transducers, external sensors can include temperature probes and, potentially, underwater cameras. The pressure housing contains a computer that includes a hard drive, DC-to- DC power converters, a post-amplifier board, a sound card, and a universal serial bus (USB) 4-port hub.

Lane, Michael↗
NASA NTRS2009

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Schwabacher, Mark A.↗
NASA NTRS2013

An Update on Phased Array Results Obtained on the GE Counter-Rotating Open Rotor Model

Beamform maps have been generated from 1) simulated data generated by the LINPROP code and 2) actual experimental phased array data obtained on the GE Counter-rotating open rotor model. The beamform maps show that many of the tones in the experimental data come from their corresponding Mach radius. If the phased array points to the Mach radius associated with a tone then it is likely that the tone is a result of the loading and thickness noise on the blades. In this case, the phased array correctly points to where the noise is coming from and indicates the axial location of the loudest source in the image but not necessarily the correct vertical location. If the phased array does not point to the Mach radius associated with a tone then some mechanism other than loading and thickness noise may control the amplitude of the tone. In this case, the phased array may or may not point to the actual source. If the source is not rotating it is likely that the phased array points to the source. If the source is rotating it is likely that the phased array indicates the axial location of the loudest source but not necessarily the correct vertical location. These results indicate that you have to be careful in how you interpret phased array data obtained on an open rotor since they may show the tones coming from a location other than the source location. With a subsonic tip speed open rotor the tones can come form locations outboard of the blade tips. This has implications regarding noise shielding.

Podboy, Gary↗