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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Statistical Models of Areal Distribution of Fragmented Land Cover Types

Imagery of coarse resolution, such weather satellite imagery with 1 square kilometer pixels, is increasingly used to monitor dynamic and fragmented types of land surface types, such as scars from recent fires and ponds in wetlands. Accurate estimates of these land cover types at regional to global scales are required to assess the roles of fires and wetlands in global warming, yet difficult to compute when much of the area is accounted for by fragments about the same size as the pixels. In previous research, we found that size distribution of the fragments in several example scenes fit simple two-parameter models and related effects of coarse resolution to errors in area estimates based on pixel counts. We summarize our model based approach to improved area estimations and report on progress to develop accurate areas estimates based on modeling the size distribution of the fragments, including analysis of size distributions on an expanded set of maps developed from digital imagery.

Hlavka, C.↗
NASA NTRS1998

Fragmented Land Cover Types and Estimation of Area with Course Spatial Resolution Imagery

Imagery of coarse resolution, such weather satellite imagery with 1 sq km pixels, is increasingly used to monitor dynamic and fragmented types of land surface types, such as scars from recent fires and ponds in wetlands. Accurate estimates of these land cover types at regional to global scales are required to assess the roles of fires and wetlands in global warming, yet difficult to compute when much of the area is accounted for by fragments about the same size as the pixels. In previous research, we found that size distribution of the fragments in several example scenes fit simple two-parameter models and related effects of coarse resolution to errors in area estimates based on pixel counts. We report on progress to develop accurate area estimates based on modelling the size distribution of the fragments, including analysis of size distributions on an expanded set of maps developed from digital imagery and a test of a procedure to correct for effects of coarse spatial resolution.

Hlavka, Chris↗
NASA NTRS1999

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

Morris, A. Terry↗
NASA NTRS1980

The estimation of the propagation delay through the troposphere from microwave radiometer data

The uncertainity in propagation delay estimates is due primarily to tropospheric water, the total amount and vertical distribution of which is variable. Because water vapor both delays and attenuates microwave signals, the propagation delay, or wet path length, can be estimated from the microwave brightness temperature near the 22.235 GHz transition of water vapor. The data from a total of 240 radiosonde launches taken simultaneously were analyzed. Estimates of brightness temperature at 19 and 22 GHz and wet path length were made from these data. The wet path length in the zenith direction could be estimated from the surface water vapor density to an accuracy of 5 cm for the summer data and 2 cm for winter data. Using the brightness temperatures, the wet path could be estimated to an accuracy of 0.3 cm. Two dual frequency radiometers were refurbished in order to test these techniques. These radiometers were capable of measuring the difference in the brightness temperature at 30 deg elevation angle and at the zenith to an accuracy of about 1 K. In August 1975, 45 radiosondes were launched over an 11 day period. Brightness temperature measurements were made simultaneously at 19 and 22 GHz with the radiometers. The rms error for the estimation of wet path length from surface meteorological parameters was 3.2 cm, and from the radiometer brightness temperatures, 1.5 cm.

Moran, J. M.↗
NASA NTRS2012

Can Selforganizing Maps Accurately Predict Photometric Redshifts?

We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

Way, Michael J.↗
NASA NTRS2013

Validation of Forested Inundation Extent Revealed by L-Band Polarimetric and Interferometric SAR Data

UAVSAR, NASA's airborne Synthetic Aperture Radar (SAR), conducted an extended observational campaign in Central and South America in March 2013, primarily related to volcanic deformations along the Andean Mountain Range but also including a large number of flights studying other scientific phenomena. During this campaign, the L-Band SAR collected data over the Napo River in Ecuador. The objectives of this experiment were to acquire polarimetric and interferometric L-Band SAR data over an inundated tropical forest in Ecuador simultaneously with on-the-ground field work ascertaining the extent of inundation, and to then derive from this data a quantitative estimate for the error in the SAR-derived inundation extent. In this paper, we will first describe the processing and preliminary analysis of the SAR data. The polarimetric SAR data will be classified by land cover and inundation state. The interferometric SAR data will be used to identify those areas where change in inundation extent occurred, and to measure the change in water level between two observations separated by a week. Second, we will describe the collection of the field estimates of inundation, and have preliminary comparisons of inundation extent measured in the field field versus that estimated from the SAR data.

Synthetic Aperture Radar (SAR),↗
NASA NTRS1995

Ground-based measurements of water vapor in the middle atmosphere

We present measurements of the middle atmospheric water vapor mixing ratio profile obtained using the ground-based Naval Research Laboratory (NRL) water vapor millimeter-wave spectrometer (WVMS) instrument at the Jet Propulsion Laboratory (JPL) Table Mountain Observatory. The measurements cover a period of 262 days from January 23, 1992, to October 13, 1992. During this campaign it was possible to retrieve useful daily mixing ratio profiles for 186 days. We thus have a nearly continuous record of water vapor mixing ratios for altitudes from approximately equals 35 to 75 km. The retrievals are obtained using the optimal estimation method. Details of the error analysis are presented, and a technique is introduced that reduces baseline effects and helps to estimate the baseline error. The high-altitude (greater than or approx. equal to 65 km) data show a sharp rise prior to the expected maximum near the summer solstice and a gradual decline in the following months. The mixing ratios generally peak between 55 and 65 km, at which point the mixing ratios are 6 - 7 parts per million by volume. The highest peaks occur in January, May, and October.

Nedoluha, Gerald E.↗
NASA NTRS2001

Assessment of the time constant of relaxation: insights from simulations and hemodynamic measurements

The objective of this study was to use high-fidelity animal data and numerical simulations to gain more insight into the reliability of the estimated relaxation constant derived from left ventricular pressure decays, assuming a monoexponential model with either a fixed zero or free moving pressure asymptote. Comparison of the experimental data with the results of the simulations demonstrated a trade off between the fixed zero and the free moving asymptote approach. The latter method more closely fits the pressure curves and has the advantage of producing an extra coefficient with potential diagnostic information. On the other hand, this method suffers from larger standard errors on the estimated coefficients. The method with fixed zero asymptote produces values of the time constant of isovolumetric relaxation (tau) within a narrow confidence interval. However, if the pressure curve is actually decaying to a nonzero pressure asymptote, this method results in an inferior fit of the pressure curve and a biased estimation of tau.

NASA Discipline Cardiopulmonary↗
DOE OSTI2023

Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules

Abstract Materials simulations involving strongly correlated electrons pose fundamental challenges to state‐of‐the‐art electronic structure methods but are hypothesized to be the ideal use case for quantum computing algorithms. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real‐world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near‐term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using the VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies using it have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near‐term feasibility of modeling a molecule with d‐orbitals on real quantum hardware. We demonstrate that the inclusion of d‐orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE + UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Maximum likelihood estimation of label imperfection probabilities and its use in the identification of mislabeled patterns

Estimating label imperfections and the use of estimations in the identification of mislabeled patterns are discussed. Expressions are presented for the asymptotic variances of the probability of correct classification and proportion, and for the maximum likelihood estimates of classification errors and a priori probabilities. Models are developed for imperfections in the labels and classification errors, and expressions are derived for the probability of imperfect label identification schemes resulting in wrong decisions. The expressions are used in computing thresholds and the techniques are given practical applications. The imperfect label identification scheme in the multiclass case is found to amount to establishing a region around each decision surface, and decisions of the label correction scheme are found in close agreement with the analyst-interpreter interpretations of the imagery films. As an example, the application of the maximum likelihood estimation to the processing of Landsat MSS data is discussed.

Chittineni, C. B.↗
DOE OSTI2023

tih_vqe [SWR-23-32]

This software supports the paper, "Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules," published in the International Journal of Quantum Chemistry, whose abstract is as follows: Materials simulations involving strongly correlated electrons pose fundamental challenges to state-of-the-art electronic structure methods but are hypothesized to be the ideal use case for quantum computing. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real-world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately-sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near-term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near-term feasibility of modeling a molecule with d-orbitals on real quantum hardware. We demonstrate that the inclusion of d-orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE+UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

Graf, Peter↗
NASA NTRS1993

The use of polar-orbiting satellite sounding data to estimate rural maximum and minimum temperatures

Atmospheric sounding products from NOAA's polar-orbiting satellites were used to derive and test predictive equations of rural shelter-level maximum and minimum temperatures. Sounding data from both winter and summer months were combined with surface data from over 5300 cooperative weather stations in the continental United States to develop multiple linear regression equations. Separate equations were developed for both maximum and minimum temperature, using the three types of sounding retrievals (clear, partly cloudy, and cloudy). Clear retrieval models outperformed others, and maximum temperatures were more accurately predicted than minimums. Average standard deviations of observed rural shelter temperatures within sounding search areas were of similar magnitude to root-mean-square errors from satellite estimates for most clear and partly cloudy cases, but were significantly less for cloudy retrieval cases. Model validation for surrogate polar and tropical climatic regions showed success in application of the four clear retrieval models (maximum and minimum temperature, for both winter and summer). This indicates the potential adaptability of these models to estimates of rural shelter temperature in areas outside of the United States.

Johnson, Gregory L.↗
NASA NTRS1997

The Application of New Software Technology to the Architecture of the National Cycle Program

As part of the Numerical Propulsion System Simulation (NPSS) effort of NASA Lewis in conjunction with the United States aeropropulsion industry, a new system simulation framework, the National Cycle Program (NCP), capable of combining existing empirical engine models with new detailed component-based computational models is being developed. The software architecture of the NCP program involves a generalized object- oriented framework and a base-set of engine component models along with supporting tool kits which will support engine simulation in a distributed environment. As the models are extended to contain two and three dimensions the computing load increases rapidly and it is intended that this load be distributed across multiple work stations executing concurrently in order to get acceptably fast results. The research carried out was directed toward performance analysis of the distributed object system. More specifically, the performance of the actor-based distributed object design I created earlier was desired. To this end, the research was directed toward the design and implementation of suitable performance-analysis techniques and software to demonstrate those techniques. There were three specific results which are reported in two separate reports submitted separately as NASA Technical Memoranda. The results are: (1) Design, implementation, and testing of a performance analysis program for a set of active objects (actor based objects) which allowed the individual actors to be assigned to arbitrary processes on an arbitrary set of machines. (2) The global-balance-equation approach has the fundamental limitation that the number of equations increases exponentially with the number of actors. Hence, unlike many approximate approaches to this problem, the nearest-neighbor approach allows checking of the solution and an estimate of the error. The technique was demonstrated in a prototype analysis program as part of this research. The results of the program were checked against the global-balance solution discussed above. Late during the grant, a much better approximation was developed and this is discussed in result below. As a consequence, a proposal was submitted to continue the research by developing the new approximation including development of a complete program from the prototype. (3) The source of approximation in the nearest-neighbor algorithm is the requirement for estimating some joint probabilities from some marginal distributions. A completely ad hoc estimate was used in the prototype.

Schoeffler, James D.↗
NASA NTRS2012

Design and Performance Evaluation on Ultra-Wideband Time-Of-Arrival 3D Tracking System

A three-dimensional (3D) Ultra-Wideband (UWB) Time--of-Arrival (TOA) tracking system has been studied at NASA Johnson Space Center (JSC) to provide the tracking capability inside the International Space Station (ISS) modules for various applications. One of applications is to locate and report the location where crew experienced possible high level of carbon-dioxide and felt upset. In order to accurately locate those places in a multipath intensive environment like ISS modules, it requires a robust real-time location system (RTLS) which can provide the required accuracy and update rate. A 3D UWB TOA tracking system with two-way ranging has been proposed and studied. The designed system will be tested in the Wireless Habitat Testbed which simulates the ISS module environment. In this presentation, we discuss the 3D TOA tracking algorithm and the performance evaluation based on different tracking baseline configurations. The simulation results show that two configurations of the tracking baseline are feasible. With 100 picoseconds standard deviation (STD) of TOA estimates, the average tracking error 0.2392 feet (about 7 centimeters) can be achieved for configuration Twisted Rectangle while the average tracking error 0.9183 feet (about 28 centimeters) can be achieved for configuration Slightly-Twisted Top Rectangle . The tracking accuracy can be further improved with the improvement of the STD of TOA estimates. With 10 picoseconds STD of TOA estimates, the average tracking error 0.0239 feet (less than 1 centimeter) can be achieved for configuration "Twisted Rectangle".

Ni, Jianjun↗
NASA NTRS2003

Validation and Error Characterization for the Global Precipitation Measurement

The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration, assumption, or algorithm. The instrumentation and techniques of the Supersites will be discussed. The GPM core satellite, with its dual-frequency radar and conically scanning radiometer, will provide insight into precipitation drop-size distributions and potentially increased measurement capabilities of light rain and snowfall. The ground validation program will include instrumentation and techniques commensurate with these new measurement capabilities.

Bidwell, Steven W.↗
DOE OSTI2026

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗
NASA NTRS2000

Modeling Oceanic Primary Production: Photoacclimation and Nutrient Effects on Light-saturated Photosynthesis

In this report, we describe a new model (the 'PhotoAcc' model) for estimating changes in the light-saturated rate of chlorophyll-normalized phytoplankton carbon fixation (Pbmax). The model is based on measurements conducted during the Atlantic Meridional Transect studies and the Bermuda Time Series program. The PhotoAcc model explained 64% to 82% of the observed variability in Pbmax for our data set, whereas none of the previously published Pbmax models described over the past 44 years explained any of the variance. The significance of this result is that a primary limiting factor for extracting ocean carbon fixation rates from satellite measurements of near surface chlorophyll has been errors in the estimate of Pbmax. Our new model should thus result in much improved calculations of oceanic photosynthesis and thus the role of the oceans in the global carbon cycle.

Behrenfeld, Michael J.↗