SEARCH · Engineering Papers

Results for “.NET”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

All sources NASA NTRS DOE OSTI

NASA NTRS1998

The Net Exchange Between Terrestrial Ecosystems and the Atmosphere as a Result of Changes in Land Use

The general purpose of this research was to improve and update (to 1990) estimates of the net flux of carbon between the world's terrestrial ecosystems and the atmosphere from changes in land use (e.g., deforestation and reforestation). The estimates are important for understanding the global carbon cycle, and for predicting future concentrations of atmospheric CO2 that will result from emissions. The emphasis of the first year's research was on the northern temperate zone and boreal forests, where the greatest discrepancy exists between estimates of flux. Forest inventories suggest net sinks of 0.6 PgC/yr; inversion analyses based on atmospheric data and models suggest much larger sinks 2-3.6 PgC/yr (e.g., Tans et al. 1990, Ciais et al. 1995). The work carried out with this grant calculated the flux attributable to changes in land use. The estimated flux was somewhat smaller than the flux calculated from inventory data suggesting that environmental changes have led to a small accumulation of carbon in forests that exceeds the accumulation expected from past rates of harvest. Two publications have described these results (Houghton 1996, 1998). The large difference between these estimates and those obtained with atmospheric data and models remains unexplained. The recent estimate of a 1.7 PgC/yr sink in North America, alone (Fan et al. 1998), is particularly difficult to explain. That part of the sink attributable to land-use change, however, is defined as a result of this grant.

Houghton, R. A.↗

NASA NTRS1998

Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Performance

A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology (RSM) and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The optimization procedure yields a modified design that improves the aerodynamic performance through small changes to the reference design geometry. The computed results demonstrate the capabilities of the neural net-based design procedure, and also show the tremendous advantages that can be gained by including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.

Madavan, Nateri K.↗

NASA NTRS1997

Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather

Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.

Frolking, Steve↗

NASA NTRS1998

Net Carbon Balance for the Brazilian Amazon

The general purpose of this research was to use recent satellite-based estimates of deforestation in Brazilian Amazonia to calculate the net flux of carbon associated with deforestation and subsequent regrowth of secondary forests. We have made such a calculation, in the process comparing two estimates of deforestation and two estimates of biomass for the region. Both estimates were based on the RADAMBRASIL survey. They differed in the equations used to convert wood-volumes to total biomass. The net flux of carbon from changes in land use seems to vary from year to year, perhaps by as much as a factor of 4.

Houghton, R. A.↗

NASA NTRS2001

Near-Net Shape Powder Metallurgy Rhenium Thruster

This paper describes the development of a method to produce a near-net shape (NNS) powder metallurgy (PM) rhenium combustion chamber of the size 445 N (100 lbf) used in a high performance liquid apogee engine. These engines are used in low earth Orbit and geostationary orbit for satellite positioning systems. The developments in near-net shape powder metallurgy rhenium combustion chambers reported in this paper will reduce manufacturing cost of the rhenium chambers by 25 percent, and reduce the manufacturing time by 30 to 40 percent. The quantity of rhenium metal powder used to produce a rhenium chamber is reduced by approximately 70 percent and the subsequent reduction in machining schedule and costs is nearly 50 percent.

Leonhardt, Todd↗

NASA NTRS2001

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Decker, Arthur J.↗

NASA NTRS1992

NASA's Software Bank (NETS)

NETS (A Neural Network Development Tool) is a software system for mimicking the human brain. It is used in a University of Arkansas project in pattern matching of chemical systems. If successful, chemists would be able to identify mixtures of compounds without long and costly separation procedures. Using NETS, the group has trained the computer to recognize pattern relationships in a known compound and associate the results to an unknown compound. The research appears to be promising.

Source record↗

NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗

NASA NTRS2004

Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

Decker, Arthur J.↗

NASA NTRS2006

Near Net Manufacturing Using Thin Gage Friction Stir Welding

Friction Stir Welding (FSW) and near net spin forming of FSW aluminumn blanks were investigated for large-scale pressure vessel applications. With a specific focus on very thin gage 2xxx and 7xxx aluminum alloys, the program concentrated on the following: the criteria used for material selection, a potential manufacturing flow, and the effectiveness and associated risks of near net spin forming. Discussion will include the mechanical properties of the friction stir welds and the parent material from before and after the spin forming process. This effort was performed under a NASA Space Exploration initiative focused on increasing the affordability, reliability and performance of pressure vessels larger than 10 ft. diameter.

Takeshita, Jennifer↗

NASA NTRS2007

Neural Net Safety Monitor Design

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a floating limiter (FL) concept1 that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly floating and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually hit the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗

NASA NTRS2007

Recent Advances in Near-Net-Shape Fabrication of Al-Li Alloy 2195 for Launch Vehicles

Recent applications in launch vehicles use 2195 processed to Super Lightweight Tank specifications. Potential benefits exist by tailoring heat treatment and other processing parameters to the application. Assess the potential benefits and advocate application of Al-Li near-net-shape technologies for other launch vehicle structural components. Work with manufacturing and material producers to optimize Al-Li ingot shape and size for enhanced near-net-shape processing. Examine time dependent properties of 2195 critical for reusable applications.

Wagner, John↗

NASA NTRS2006

Revisiting a Hydrological Analysis Framework with International Satellite Land Surface Climatology Project Initiative 2 Rainfall, Net Radiation, and Runoff Fields

The International Satellite Land Surface Climatology Project Initiative 2 (ISLSCP-2) data set provides the data needed to characterize the surface water budget across much of the globe in terms of energy availability (net radiation) and water availability (precipitation) controls. The data, on average, are shown to be consistent with Budyko s decades-old framework, thereby demonstrating the continuing relevance of Budyko s semiempirical relationships. This consistency, however, appears only when a small subset of the data with hydrologically suspicious behavior is removed from the analysis. In general, the precipitation, net radiation, and runoff data also appear consistent in their interannual variability and in the phasing of their seasonal cycles.

Koster, Randal D.↗

NASA NTRS2009

Processing Ocean Images to Detect Large Drift Nets

A computer program processes the digitized outputs of a set of downward-looking video cameras aboard an aircraft flying over the ocean. The purpose served by this software is to facilitate the detection of large drift nets that have been lost, abandoned, or jettisoned. The development of this software and of the associated imaging hardware is part of a larger effort to develop means of detecting and removing large drift nets before they cause further environmental damage to the ocean and to shores on which they sometimes impinge. The software is capable of near-realtime processing of as many as three video feeds at a rate of 30 frames per second. After a user sets the parameters of an adjustable algorithm, the software analyzes each video stream, detects any anomaly, issues a command to point a high-resolution camera toward the location of the anomaly, and, once the camera has been so aimed, issues a command to trigger the camera shutter. The resulting high-resolution image is digitized, and the resulting data are automatically uploaded to the operator s computer for analysis.

Veenstra, Tim↗

NASA NTRS2011

On INM's Use of Corrected Net Thrust for the Prediction of Jet Aircraft Noise

The Federal Aviation Administration s (FAA) Integrated Noise Model (INM) employs a prediction methodology that relies on corrected net thrust as the sole correlating parameter between aircraft and engine operating states and aircraft noise. Thus aircraft noise measured for one set of atmospheric and aircraft operating conditions is assumed to be applicable to all other conditions as long as the corrected net thrust remains constant. This hypothesis is investigated under two primary assumptions: (1) the sound field generated by the aircraft is dominated by jet noise, and (2) the sound field generated by the jet flow is adequately described by Lighthill s theory of noise generated by turbulence.

McAninch, Gerry L.↗

NASA NTRS2010

The Net Climate Impact of Coal-Fired Power Plant Emissions

Coal-fired power plants influence climate via both the emission of long-lived carbon dioxide (CO2) and short-lived ozone and aerosol precursors. Using a climate model, we perform the first study of the spatial and temporal pattern of radiative forcing specifically for coal plant emissions. Without substantial pollution controls, we find that near-term net global mean climate forcing is negative due to the well-known aerosol masking of the effects of CO2. Imposition of pollution controls on sulfur dioxide and nitrogen oxides leads to a rapid realization of the full positive forcing from CO2, however. Long-term global mean forcing from stable (constant) emissions is positive regardless of pollution controls. Emissions from coal-fired power plants until 1970, including roughly 1/3 of total anthropogenic CO2 emissions, likely contributed little net global mean climate forcing during that period though they may have induce weak Northern Hemisphere mid-latitude (NHml) cooling. After that time many areas imposed pollution controls or switched to low sulfur coal. Hence forcing due to emissions from 1970 to 2000 and CO2 emitted previously was strongly positive and contributed to rapid global and especially NHml warming. Most recently, new construction in China and India has increased rapidly with minimal application of pollution controls. Continuation of this trend would add negative near-term global mean climate forcing but severely degrade air quality. Conversely, following the Western and Japanese pattern of imposing air quality pollution controls at a later time could accelerate future warming rates, especially at NHmls. More broadly, our results indicate that due to spatial and temporal inhomogeneities in forcing, climate impacts of multi-pollutant emissions can vary strongly from region to region and can include substantial effects on maximum rate-of-change, neither of which are captured by commonly used global metrics. The method we introduce here to estimate regional temperature responses may provide additional insight.

Shindell, D.↗

NASA NTRS2016

Drought Rapidly Diminishes the Large Net CO2 Uptake in 2011 Over Semi-Arid Australia

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010-11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010-11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010-11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011-12, and was nearly eliminated in 2012-13 (0.08 Pg). We further report evidence of an earlier 2000-01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.

fluorescence↗

NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗