A comparison of clustering algorithms for use in large scale gene expression analysis using synthetic microarray data
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Characterization of Potential Springs in the Lower Colorado Desert of Southern California using Satellite Radar and Landsat Time Series Analysis
Renewable energy development in southern California is receiving increasing attention due to potential impacts on wildlife habitats and water sources. This study was designed to quantify and map, for the first time, sub-surface water sources from springs in the Lower Colorado Desert area of southern California using satellite radar data and 30 years of Landsat satellite image data. Synthetic Aperture Radar (SAR) data was used to identify sub-surface water sources not already documented as springs or seeps in the National Hydrography Database. Landsat imagery starting in 1985 was used to characterize vegetation growth patterns at these suspected spring locations detected from SAR analysis. Results showed a total of 104 potential spring locations across the Lower Colorado Desert study area, 19 of which were detected within Solar Energy Zone (SEZ) development boundaries, roughly evenly split between Riverside East and Imperial East, and 13 of which (both inside and outside SEZs) showed relatively high green vegetation index values over the period of 1985 to 2015 that would depend on non-precipitation water sources associated with active springs.
DRECP↗
Planetary Probe Entry Atmosphere Estimation Using Synthetic Air Data System
This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with an assumed vehicle aerodynamic model. The approach utilizes the full navigation state of the vehicle (position, velocity, and attitude) to recast the vehicle aerodynamic model to be a function solely of the atmospheric state (density, pressure, and winds). Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman-Schmidt filter to estimate the atmospheric conditions. The new method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the new estimation algorithm are compared with results from a Flush Air Data Sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the new proposed estimation method provides estimates consistent with the air data measurements, without the use of pressure measurements. Implications for future missions such as the Mars 2020 entry capsule are described.
Karlgaard, Chris↗
Planetary Probe Entry Atmosphere Estimation Using Synthetic Air Data System
This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with a vehicle aerodynamic model. The approach uses the navigation state of the vehicle to recast the vehicle aerodynamic model to be a function solely of the atmospheric state. Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman–Schmidt filter to estimate the atmospheric conditions. The method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the estimation algorithm are compared with results from a flush air data sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the proposed method provides estimates consistent with the air data measurements, without the use of pressure transducers. Implications for future missions such as the Mars 2020 entry capsule are described.
Karlgaard, Chris↗
Future Orbiting and In-Situ Exploration of Venus: Mount Etna as Terrestrial Analog
The exploration of Venus will soon experience a new golden era thanks to the recently selected NASA Deep Atmosphere of Venus Investigation of Noble gases, Chemistry and Imaging (DAVINCI) mission, NASA Venus Emissivity, Radio Science, InSAR, Topography & Spectroscopy (VERITAS) mission, and ESA EnVision mission. The DAVINCI mission will focus on the analysis of the the atmospheric vertical structure and composition of Earth’s twin planet and on the geologic structure of a tesserae terrain. The VERITAS mission will investigate the geologic features of its surface as well as geodynamic characteristics of the subsurface, providing high-resolution emissivity data, a global radar map at an approximate resolution of 30 meters/pixel, and estimation of the gravity anomaly of the shallow crust of the planet. The ESA EnVision mission will be complementary to the two NASA missions, providing high resolution 0.8-2.5 micron emissivity data, Synthetic Aperture Radar (SAR) data, and Subsurface Radar Sounder (SRS) data. Beyond those, the proposed Roscosmos-NASA Venera-D mission will also be equipped with an orbiter that will investigate the atmospheric composition and circulation, as well as a lander that will analize the in-situ chemical composition and the surface-atmosphere interactions.
P. D’Incecco↗
Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation
A hybrid flush/synthetic air data sensing filter for entry vehicle atmosphere estimation is developed. The approach makes use of a Kalman-Schmidt and Rauch-Tung-Streibel smoother. The filter/smoother blends information from pressure sensors distributed on the heatshield with pseudo-measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars 2020 entry, descent, and landing at Jezero crater on February 18th, 2021. The final paper will also include results from the Mars Science Laboratory entry, descent, and landing.
Chris D. Karlgaard↗
Improving Sim-to-Real Transfer in Vision-Based Robot Navigation Via Instance-Level GAN-Based Data Augmentation
Achieving robust vision-based robotic tasks requires large amounts of data, which are often difficult to obtain in real-world scenarios. Simulators and synthetic data offer a cost-effective alternative, but the visual gap between simulation and reality hinders the performance of models when deployed in real-world environments. In this paper, we present a data augmentation pipeline that integrates a foundation model (Segment Anything Model) with an unsupervised image-to-image translation model (CycleGAN) for instance-level domain transfer from simulation to reality. This pipeline enables the generation of realistic labeled data from synthetic images for training supervised machine learning models in vision-based navigation tasks. We evaluate our approach on real-world data for ego-vehicle pose estimation, a critical autonomous navigation task involving the prediction of cross-track position and heading angle relative to road center line markings. The results of our tests show that our GAN-based data augmentation pipeline significantly outperforms models trained solely on simulation data or on data processed with standard image augmentation methods for sim-to-real transfer, enhancing model robustness and generalizability in real-world scenarios. Our method provides a scalable and flexible data augmentation tool for leveraging large synthetic datasets to enhance vision-based robotic navigation tasks.
artificial intelligence↗
Analysis of urban area land cover using SEASAT Synthetic Aperture Radar data
Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.
Henderson, F. M.↗
Potentials for change detection using Seasat synthetic aperture radar data
The use of synthetic aperture radar (SAR) images for detecting change on the earth's surface is highly dependent on target orientation, azimuth angle, and sensor depression angle. SAR data can be used for change detection when consistency is maintained in radar wavelength, polarization, azimuth directions, and off-nadir depression angle. The interaction of these parameters and the imaged surface for change detection are shown in examples drawn from (1) Los Angeles, CA, (2) southern Florida, (3) Imperial Valley, CA, (4) a desert region west of Tucson, AZ, and (5) western Kansas. SAR imagery is used to emphasize the geometric form, and roughness, of the earth's surface. As changes in the roughness of the surface occur over time, temporal SAR images will indicate those differences. Several guidelines for change detection studies using imaging radar are derived from the examples.
Bryan, M. L.↗
Computational Characterization and Model Verification for 3D Microstructure Reconstruction of Additively-Manufactured Materials
The goal of this study is to characterize and validate the texture and grain topology of additively-manufactured anisotropic three-dimensional (3D) polycrystalline microstructures. The special focus is on developing methodologies to compare the grain shapes and orientations of two-dimensional (2D) and 3D microstructure representations using the same metric. To generate statistical data, synthetic microstructures are reconstructed from experimental data using Markov random field (MRF). The statistical similarity between the experimental and synthetic microstructures is verified by comparing their grain topologies. A universal measure to compare 2D and 3D grains is portrayed through the concept of image moments that are invariant to shape transformations. The graphical plots developed based on moment invariants to compare the 2D and 3D grains are used to verify the synthetic model
Materials Characterization↗
A modified objective mapping technique for scatterometer wind data
A method for generating high-resolution wind maps from scatterometer data was developed and tested on synthetic data for the northeast Pacific Ocean. It is shown that, unlike the wind fields generated by current GCMs, the wind maps constructed by this method retain the high spatial resolution of the scatterometer wherever adequate measurements exist. For the NASA scatterometer, this method would produce every 12 hours a wind map with spatial resolution that preserves the small-scale features of the original data over about half the mapped region. Over the rest of the region, maps with somewhat lower resolution and accuracy will be obtained.
Kelly, Kathryn A.↗
On the Isothermality of Solar Plasmas
Recent measurements have shown that the quiet unstructured solar corona observed at the solar limb is close to isothermal, at a temperature that does not appear to change over wide areas or with time. Some in dividual active loop structures have also been found to be nearly iso thermal both along their axis and across their cross-section. Even a complex active region observed at the solar limb has been found to be composed of three distinct isothermal plasmas. If confirmed, these r esults would pose formidable challenges to the current theoretical understanding of the thermal structure and heating of the solar corona. For example, no current theoretical model can explain the excess dens ities and lifetimes of many observed loops if the loops are in fact i sothermal. All of these measurements are based on the so-called emiss ion measure (EM) diagnostic technique that is applied to a set of opt ically thin lines under the assumption of isothermal plasma. It provi des simultaneous measurement of both the temperature and EM. However, no study has ever been carried out to quantify the uncertainties in the technique and to rigorously assess its ability to discriminate bet ween isothermal and multithermal plasmas. Such a study is the topic o f the present work. We define a formal measure of the uncertainty in the EM diagnostic technique that can easily be applied to real data. We here apply it to synthetic data based on a variety of assumed plas ma thermal distributions, and develop a method to quantitatively asse ss the degree of multithermality of a plasma.
Landi, E.↗
Comparison of Computational and Experimental Microphone Array Results for an 18%-Scale Aircraft Model
An 18%-scale, semi-span model is used as a platform for examining the efficacy of microphone array processing using synthetic data from numerical simulations. Two hybrid RANS/LES codes coupled with Ffowcs Williams-Hawkings solvers are used to calculate 97 microphone signals at the locations of an array employed in the NASA LaRC 14x22 tunnel. Conventional, DAMAS, and CLEAN-SC array processing is applied in an identical fashion to the experimental and computational results for three different configurations involving deploying and retracting the main landing gear and a part span flap. Despite the short time records of the numerical signals, the beamform maps are able to isolate the noise sources, and the appearance of the DAMAS synthetic array maps is generally better than those from the experimental data. The experimental CLEAN-SC maps are similar in quality to those from the simulations indicating that CLEAN-SC may have less sensitivity to background noise. The spectrum obtained from DAMAS processing of synthetic array data is nearly identical to the spectrum of the center microphone of the array, indicating that for this problem array processing of synthetic data does not improve spectral comparisons with experiment. However, the beamform maps do provide an additional means of comparison that can reveal differences that cannot be ascertained from spectra alone.
Lockard, David P.↗
Feasibility of microwave holography for imaging the sea surface
The possibility of imaging the sea surface in three dimensions by means of microwave holography from a low-flying aircraft is considered. Data cover a brief feasibility study and a review of some computer experiments in which it was demonstrated that it is possible to compute three-dimensional images of objects from raw holographic data recorded on magnetic tape. These experiments used synthetic data.
Wells, W.↗
Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors
The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments, conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules, which are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flow field carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.
Drozda, Tomasz G.↗
Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors
The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.
PLIF↗
Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors
The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flushwall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. Both schlieren and PLIF techniques are applied to obtain mixing flowfield flow visualizations. The experimental PLIF is obtained by using a UV laser sheet to interrogate a plane of the flow by exciting fluorescence from the NO molecules that are present in the AHSTF air. Consequently, the absence of signal in the resulting PLIF images is an indication of pure helium (fuel). The computational PLIF is obtained by applying a fluorescence model for NO to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield carried out using the VULCAN-CFD solver. This approach is required because the PLIF signal is a nonlinear function of not only NO concentration, but also pressure, temperature, and the flow velocity. This complexity allows additional flow features to be identified and compared with those obtained from the computational fluid dynamics (CFD) simulations, however, such comparisons are only semiquantitative. Three-dimensional image reconstruction, similar to that used in magnetic resonance imaging, is also used to obtain images in the streamwise and spanwise planes from select cross-stream PLIF plane data. Synthetic schlieren is also computed from the RAS data. Good agreement between the experimental and computational results provides increased confidence in the CFD simulations for investigations of injector performance.
PLIF↗
Fresnel zone processing of synthetic aperture radar data
Fresnel zone processing of synthetic aperture radar
FRESNEL REGION↗