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At least 163 records · Page 9

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NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗

NASA NTRS2022

Coupling Carbon Oxidation and Surface Recession in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that are often made out of carbon-based reinforcement and a polymeric matrix. They endure high-temperature oxidation and surface recession when re-entering Earth’s atmosphere. Ablation is the result of many coupled and competing thermal, mechanical, and chemical phenomena, and it is difficult to isolate the role of each on the overall degradation of the TPS. Here we develop an ablation model for material recession coupled explicitly to finite rate carbon oxidation in complex microstructures. In this work, Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al, was adapted to tally surface reactions and other surface data on a per-grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also develop robust algorithms which handle the evolution of the flow cells and solid material regions, including split cells (flow cell divided in two by a solid surface). Finally, we demonstrate our implicit chemistry model for 2D and 3D geometries by producing reaction statistics and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗

NASA NTRS2013

Memory-Efficient Onboard Rock Segmentation

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Burl, Michael C.↗

NASA NTRS2017

Fireballs in the Sky: An Augmented Reality Citizen Science Program

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Day, Brian↗

NASA NTRS2006

Increasing Efficiency at the NTF by Optimizing Model AoA Positioning

The National Transonic Facility (NTF) at NASA Langley Research Center (LaRC) is a national resource for aeronautical research and development. The government, military and private industries rely on the capability of this facility for realistic flight data. Reducing the operation costs and keeping the NTF affordable is essential for aeronautics research. The NTF is undertaking an effort to reduce the time between data points during a pitch polar. This reduction is being driven by the operating costs of a cryogenic facility. If the time per data point can be reduced, a substantial cost savings can be realized from a reduction in liquid nitrogen (LN2) consumption. It is known that angle-of-attack (AoA) positioning is the longest lead-time item between points. In January 2005 a test was conducted at the NTF to determine the cause of the long lead-time so that an effort could be made to improve efficiency. The AoA signal at the NTF originates from onboard instrumentation then travels through a number of different systems including the signal conditioner, digital voltmeter, and the data system where the AoA angle is calculated. It is then fed into a closed loop control system that sets the model position. Each process along this path adds to the time per data point affecting the efficiency of the data taking process. Due to the nature of the closed loop feed back AoA control and the signal path, it takes approximately 18 seconds to take one pitch pause point with a typical AoA increment. Options are being investigated to reduce the time delay between points by modifying the signal path. These options include: reduced signal filtering, using analog channels instead of a digital volt meter (DVM), re-routing the signal directly to the AoA control computer and implementing new control algorithms. Each of these has potential to reduce the positioning time and together the savings could be significant. These timesaving efforts are essential but must be weighed against possible loss of data quality. For example, a reduction in filtering can introduce noise into the signal and using analog channels could result in some loss of accuracy. Data quality assessments need to be performed concurrently with timesaving techniques since data quality parameters are essential in maintaining facility integrity. This paper will highlight time saving efforts being undertaken or studied at the NTF. It will outline the instrumentation and computer systems involved in setting of the model pitch attitude then suggest changes to the process and discuss how these system changes would effect the time between data points. It also discusses the issue of data quality and how the potential efficiency changes in the system could affect it. Lastly, it will discuss the possibility of using an open loop control system and give some pros and cons of this method.

Crawford, Bradley L.↗

NASA NTRS1990

Strategies for concurrent processing of complex algorithms in data driven architectures

The performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Stoughton, John W.↗

NASA NTRS1990

Strategies for concurrent processing of complex algorithms in data driven architectures

Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Som, Sukhamoy↗

NASA NTRS1996

Climate Data Assimilation on a Massively Parallel Supercomputer

We have designed and implemented a set of highly efficient and highly scalable algorithms for an unstructured computational package, the PSAS data assimilation package, as demonstrated by detailed performance analysis of systematic runs on up to 512-nodes of an Intel Paragon. The preconditioned Conjugate Gradient solver achieves a sustained 18 Gflops performance. Consequently, we achieve an unprecedented 100-fold reduction in time to solution on the Intel Paragon over a single head of a Cray C90. This not only exceeds the daily performance requirement of the Data Assimilation Office at NASA's Goddard Space Flight Center, but also makes it possible to explore much larger and challenging data assimilation problems which are unthinkable on a traditional computer platform such as the Cray C90.

supercomputer↗

NASA NTRS2018

Polarization Decomposition and Temperature Bias Resolution for SMAP Passive Soil Moisture Retrieval Using Time Series Brightness Temperature Observations

In passive microwave remote sensing of soil moisture, the tau-omega (τ-ω) model has often been used to provide soil moisture estimates at a spatial scale representative of the satellite footprint dimensions. For modeling simplicity, model parameters such as the single scattering albedo (ω) and vegetation opacity (τ) that go into the geophysical inversion process are often assumed to be independent of polarizations. Although this absence of polarization dependence can often be justified in special cases as in low-frequency remote sensing or under dense vegetation conditions, it is not a robust assumption in general. Additional model parameterization errors arising from this assumption are possible, leading to degradation in soil moisture estimation accuracy. In this paper, we propose a time series approach to try to resolve the polarization dependence of several τ-ω model parameters as well as the temperature bias arising from the ancillary temperature data. The Version 4 of the Soil Moisture Active Passive (SMAP) Level 1B brightness temperature time series observations were used to illustrate the mechanics of this approach, with an emphasis on a comparison between resulting satellite soil moisture retrievals and in situ data collected at several core validation sites. It was found that this time series approach resulted in significant reduction of the dry bias exhibited in the current SMAP passive soil moisture data products, while retaining the same performance in other metrics of the current baseline passive soil moisture retrieval algorithm.

time series↗

NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗

NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations using DOE Analysis

Urban air mobility↗

NASA NTRS2013

Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

TRMM↗

NASA NTRS1986

Antenna pattern correction for the Nimbus-7 SMMR

This paper describes the philosophy and method used to develop the antenna pattern correction (APC) algorithm that was used on the data from the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7. There are limitations on what can be accomplished with such a procedure; these limitations are explored with the aid of Fourier analysis, even though the algorithm used on the SMMR data does not perform any Fourier transforms. The resulting analysis showed that, for the SMMR instrument, no useful improvement could be made in the data in terms of reduction of side lobes, but the quality of the sea surface temperature retrievals could be improved considerably by matching the antenna beamwidths at the different frequencies.

Milman, A. S.↗

NASA NTRS2007

Symbolic LTL Compilation for Model Checking: Extended Abstract

In Linear Temporal Logic (LTL) model checking, we check LTL formulas representing desired behaviors against a formal model of the system designed to exhibit these behaviors. To accomplish this task, the LTL formulas must be translated into automata [21]. We focus on LTL compilation by investigating LTL satisfiability checking via a reduction to model checking. Having shown that symbolic LTL compilation algorithms are superior to explicit automata construction algorithms for this task [16], we concentrate here on seeking a better symbolic algorithm.We present experimental data comparing algorithmic variations such as normal forms, encoding methods, and variable ordering and examine their effects on performance metrics including processing time and scalability. Safety critical systems, such as air traffic control, life support systems, hazardous environment controls, and automotive control systems, pervade our daily lives, yet testing and simulation alone cannot adequately verify their reliability [3]. Model checking is a promising approach to formal verification for safety critical systems which involves creating a formal mathematical model of the system and translating desired safety properties into a formal specification for this model. The complement of the specification is then checked against the system model. When the model does not satisfy the specification, model-checking tools accompany this negative answer with a counterexample, which points to an inconsistency between the system and the desired behaviors and aids debugging efforts.

Rozier, Kristin Y.↗

NASA NTRS1978

Experimental clean combustor program: Phase 3: Turbulence measurement addendum

Airflow turbulence parameters were measured in the high pressure, high temperature flow stream leaving the compressor of an operating gas turbine engine. A water cooled hot film turbulence probe was used to determine the turbulence intensity and length scale in the compressor exit flow stream of the CF6-50 engine. Data were obtained only at idle operating conditions. At engine power levels above idle conditions, durability problems and erratic data readings were encountered with the turbulence measurement probes. Turbulence measurements were made at three radial immersions at a point 15.5 cm downstream of the compressor outlet guide vanes in the compressor exit diffuser. The passage height at this point is 5.54 cm. Data reduction was accomplished with a time-data fast Fourier transform (FFT) system. This system finds the power spectral density distribution (PSD) of a large number of data samples using a direct Fourier transform algorithm and finds the autocorrelation parameter for these data by doing an FFT analysis of the PSD curves for a series of time delay intervals.

Taylor, J. R.↗

NASA NTRS1980

Geophysical and astronomical models applied in the analysis of very long baseline interferometry

Very long baseline interferometry presents an opportunity to measure at the centimeter level such geodetic parameters as baseline length and instantaneous pole position. In order to achieve such precision, the geophysical and astronomical models used in data analysis must be as accurate as possible. The Mark-3 interactive data analysis system includes a number of refinements beyond conventional practice in modeling precession, nutation, diurnal polar motion, UT1, solid Earth tides, relativistic light deflection, and reduction to solar system barycentric coordinates. The algorithms and their effects on the recovered geodetic, geophysical, and astrometric parameters are discussed.

Ma, C.↗

NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗

NASA NTRS1999

Moisture Forecast Bias Correction in GEOS DAS

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

Dee, D.↗