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At least 469 records · Page 26

A scalable variational method for estimating the latent infection-rate field of an outbreak

In this paper, we explore whether the infection-rate of a disease can serve as a robust monitoring variable in epidemiological surveillance algorithms. The infection-rate is dependent on population mixing patterns that do not vary erratically day-to-day; in contrast, daily case-counts used in contemporary surveillance algorithms are corrupted by reporting errors. The technical challenge lies in estimating the latent infection-rate from case-counts. Here we devise a Bayesian method to estimate the infection-rate across multiple adjoining areal units, and then use it, via an anomaly detector, to discern a change in epidemiological dynamics. We extend an existing model for estimating the infection-rate in an areal unit by incorporating a Markov random field model, so that we may estimate infection-rates across multiple areal units, while preserving spatial correlations observed in the epidemiological dynamics. To carry out the high-dimensional Bayesian inverse problem, we develop an implementation of mean-field variational inference specific to the infection model and integrate it with the random field model to incorporate correlations across counties. The method is tested on estimating the COVID-19 infection-rates across all 33 counties in New Mexico using data from the summer of 2020, and then employing them to detect the arrival of the Fall 2020 COVID-19 wave. We perform the detection using a temporal algorithm that is applied county-by-county. We also show how the infection-rate field can be used to cluster counties with similar epidemiological dynamics.

60 APPLIED LIFE SCIENCES↗

Evaluation of WSR-88D Level III and MRMS Rainfall Estimates Against Rain Gauge Observations at the Savannah River Site

Rainfall data for the Savannah River Site (SRS) has been historically measured by rain gauges. These instruments serve as ground truth for most climatological and weather applications; however, gauge measurements are prone to errors or biases under certain weather conditions. Rainfall estimates from radar reflectivity values have been developed and improved over the years and serve as an alternative or supplement for gauge measurements. This study compares measurements from tipping bucket rain gauges with rainfall estimates from the NOAA NWS WSR-88D Level III hourly rainfall product and the Multi-Radar Multi-Sensor (MRMS) gauge-corrected precipitation estimate. Results show good agreement between radar derived amounts and ground measurements, with MRMS values showing correlation coefficients of 0.60-0.95 and RMSE values of less than 1.0 cm (0.4 in). The WSR-88D Level III estimates result in correlation coefficients of 0.46-0.86 and RMSE values of less than 1.3 cm (0.5 in). Few outliers are observed for each data pair and are evaluated against precipitation classification products (WSR-88D Hybrid Hydrometeor Classification product and MRMS Precipitation Flag product). The rain gauges used in this study are not part of the Hydrometeorological Automated Data System (HADS) network used to correct the MRMS estimates and therefore, results of this work provide an independent validation of the MRMS gauge correction scheme.

54 ENVIRONMENTAL SCIENCES↗

Qualitative Conditions for Reasonable Estimates of Kerma Using Total and Kerma Cross Section Attenuation of Photons

Performing a full adjoint simulation in the Integrated Tiger Series (ITS) can be time consuming to obtain statistically significant results. The ray-trace capability in ITS allows for rapid scoping calculations of the uncollided kerma from photon sources without needing to run a full adjoint simulation. However, the uncollided estimate will always underestimate the full-physics kerma since it neglects scattered radiation, and under certain conditions, the result from the capability may not provide a sufficiently accurate estimate of the full-physics kerma. To exemplify the conditions in which the capability provides reasonable estimates, two problem geometries with different materials are simulated using the full adjoint capability as well as the ray-trace capability with a total cross section treatment and a new kerma-attenuation cross-section treatment. The results are then compared to show under which conditions the estimates are accurate. Reasonable estimates are provided from the ray-trace feature when there is minimal scattering into a region of interest occurring, such as with low-Z material and when the photons travel through small amounts of material.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Estimates of the Economic Impacts of Long-Duration, Widespread Power Disruptions in Puerto Rico

A typical electricity customer in Puerto Rico experienced nearly 27 hours of power interruptions in 2023–with many customers experiencing extremely long duration outages during a single event (i.e., greater than one month). This project involved conducting state-of-the-art surveying to assess the direct costs of power outages occurring across Puerto Rico, developing customer-specific models to estimate future costs over varying outage durations, and comparing these estimates to FEMA’s Value of Unit Service for Electricity. We estimate that a territory-wide power outage may cost customers $\$1$, $\$5$ and $\$29$ billion during one-, 14-, and 30-day interruptions, respectively. However, these are lower-bound estimates because our study focused on direct economic costs and, by necessity, did not fully incorporate (1) indirect impacts to the economy; (2) costs to repair or replace damaged utility infrastructure; and (3) the broader societal consequences including increased morbidity- and mortality-related costs. The information contained in this study can be used to estimate the direct economic value of past or proposed investments in power system resilience. We conclude with a discussion of this study’s limitations and suggest additional research to improve stakeholder understanding of the impacts of power outages across Puerto Rico.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗

Biases in preconstruction estimates of wind plant annual energy production

Estimating the energy yield of a wind plant during the preconstruction phase is a historically difficult task, even with industry improvements in these estimations. We build on prior research comparing the realized energy production of wind plants and their estimated annual energy production P50 values (median energy production), using owner-provided energy production and losses. We produced similar results to prior studies but with a slightly increasing bias of overestimating median energy production (a bias between realized and estimated energy production of −7.4 % to −6.6 %, depending on the scenario, as opposed to −6.7 % to −5.5 % from earlier studies). In addition to assessing annual energy production P50 bias, we compared both the 1-year and the long-term annual energy production P90 and uncertainty energy yield assessment estimates to the observed long-term-corrected energy production. We found that neither the energy yield assessment uncertainty nor the P90 is conservative enough compared to the observed distribution of prediction errors, suggesting significant room for improvement in the energy yield assessment process.

17 WIND ENERGY↗

The methods of paired comparisons and magnitude estimation in judging the noisiness of aircraft

The point of subjective equality in regard to perceived noisiness for each of 14 pairs of aircraft noises was obtained using both magnitude estimation technique and the method of paired comparisons. Both methods gave approximately the same estimates of the points of subjective equality for the noise pairs, and both showed similar correspondence to predictive physical measures. Nevertheless, the two methods appear to have greater face validity to the listeners. However, the magnitude estimation technique appears to be more efficient; for a given level of reliability it requires approximately 50% of the testing time required by the paired comparison method. The functions relating physical intensity to the estimated magnitude of subjective noisiness had slopes ranging from about .61 to .29 for the aircraft noises employed in this study, indicating a required change of about 5 to 10 db for a doubling in subjective magnitude. Some physical units of noise measurement were found to be very predictive (standard errors of estimate as low as 1.9 db) of the subjective judgements of noisiness.

Clarke, F. R.↗

Bayesian recursive image estimation.

A procedure for recursively estimating images that are characterized statistically by the mean and correlation functions associated with the random process representing the brightness level is proposed for the case where the images are corrupted by additive noise. First, a dynamic model is developed with a response characteristic which matches that of the scanner output (the input of the estimator is the output of a horizontal line scanner) in a statistical sense. Such models have the form of an ordinary differential or difference equation with white noise input. An insignificant approximation is introduced by using a constant-coefficient model. The appropriate model is a vector valued difference equation with the solution representing a vector Markov process. The next step is to obtain the minimum mean square estimate of the image by using a Kalman filter. Since the image estimation is an interpolation problem, two successive runs over the observation are performed in opposite directions and the resultant estimates are averaged. Examples are included for illustration.

Nahi, N. E.↗

Estimating the proportions of objects within a single resolution element of a multispectral scanner.

Description of a procedu*e designed to estimate the proportions of objects and materials contained in the instantaneous field of view (IFOV) of an airborne multispectral device. A mathematical model is derived to relate the signature of a combination of materials in a resolution cell to the signatures of the individual materials considered. Estimation algorithms are generated and digital computer programs are prepared to apply the algorithms in the description of the effects which are observed when several objects are viewed simultaneously. The maximum likelihood estimate of the proportions of various individual materials in an IFOV is discussed. A simulation program is proposed for such estimates. A procedure for analyzing the geometric relations of signatures which affect the accuracy of estimates is set forth.

Horwitz, H. M.↗

Biased estimation for dynamic systems.

Optimization and regulation of static and dynamic systems require good estimates of the states of the system model and the parameters of the model in the presence of input and measurement noise. A biased estimator is proposed as an alternative to the familiar best linear unbiased estimator. Depending on the value of a constant, this biased estimator can be made unbiased and is then identical to the best linear unbiased estimator, thus permitting additional freedom of choice in design and application. The sum of squared errors of this bs tmator can be less than the best linear unbiased case. An existence theorem is established and various properties are discussed.

Chang, J. W.↗

Improvements in estimating proportions of objects from multispectral data

Methods for estimating proportions of objects and materials imaged within the instantaneous field of view of a multispectral sensor were developed further. Improvements in the basic proportion estimation algorithm were devised as well as improved alien object detection procedures. Also, a simplified signature set analysis scheme was introduced for determining the adequacy of signature set geometry for satisfactory proportion estimation. Averaging procedures used in conjunction with the mixtures algorithm were examined theoretically and applied to artificially generated multispectral data. A computationally simpler estimator was considered and found unsatisfactory. Experiments conducted to find a suitable procedure for setting the alien object threshold yielded little definitive result. Mixtures procedures were used on a limited amount of ERTS data to estimate wheat proportion in selected areas. Results were unsatisfactory, partly because of the ill-conditioned nature of the pure signature set.

Horwitz, H. M.↗

Estimation of longitudinal aerodynamic coefficients and comparison with wind-tunnel values

Some recent experience at Ames Research Center in the estimation of aerodynamic coefficients for the Lear-Jet and the Augmentor Wing Jet STOL Research Aircraft is reviewed. The coefficients estimated from flight data are compared with values based on large-scale wind-tunnel tests. The results obtained by the regression and quasilinearization identification techniques are also compared. The regression method generally provides the lower standard deviation in the coefficient estimates and provides the better fit to the wind-tunnel values. The addition of nonlinear terms in the aerodynamic equations decreases the difference between the estimated and measured time histories but also increases the standard deviation in the estimated coefficient values.

Wingrove, R. C.↗

Signature estimation from satellite multispectral scanner data

A method for estimating signatures from satellite multispectral scanner data for areas containing mixtures of specified object classes is presented and evaluated. Each signature is assumed to be a Gaussian distribution. The estimation procedure is simple, and the estimates represent maximum likelihood estimates. Formulae to compute variances for an estimated signature are also given.

Crane, R. B.↗

Attitude estimation of earth orbiting satellites by decomposed linear recursive filters

Attitude estimation of earth orbiting satellites (including Large Space Telescope) subjected to environmental disturbances and noises was investigated. Modern control and estimation theory is used as a tool to design an efficient estimator for attitude estimation. Decomposed linear recursive filters for both continuous-time systems and discrete-time systems are derived. By using this accurate estimation of the attitude of spacecrafts, state variable feedback controller may be designed to achieve (or satisfy) high requirements of system performance.

Kou, S. R.↗

Nonparametric maximum likelihood estimation of probability densities by penalty function methods

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.

Demontricher, G. F.↗

Application of remote sensing in estimating evapotranspiration in the Platte river basin

A 'resistance model' and a mass transport model for estimating evapotranspiration (ET) were tested on large fields of naturally subirrigated alfalfa. Both models make use of crop canopy temperature data. Temperature data were obtained with an IR thermometer and with leaf thermocouples. A Bowen ratio-energy balance (BREB) model, adjusted to account for underestimation of ET during periods of strong sensible heat advection, was used as the standard against which the resistance and mass transport models were compared. Daily estimates by the resistance model were within 10% of estimates made by the BREB model. Daily estimates by the mass transport model did not agree quite as well. Performance was good on clear and cloudy days and also during periods of non-advection and strong advection of sensible heat. The performance of the mass transport and resistance models was less satisfactory for estimation of fluxes of latent heat for short term periods. Both models tended to overestimate at low LE fluxes.

Blad, B. L.↗

Secondary task for full flight simulation incorporating tasks that commonly cause pilot error: Time estimation

The task of time estimation, an activity occasionally performed by pilots during actual flight, was investigated with the objective of providing human factors investigators with an unobtrusive and minimally loading additional task that is sensitive to differences in flying conditions and flight instrumentation associated with the main task of piloting an aircraft simulator. Previous research indicated that the duration and consistency of time estimates is associated with the cognitive, perceptual, and motor loads imposed by concurrent simple tasks. The relationships between the length and variability of time estimates and concurrent task variables under a more complex situation involving simulated flight were clarified. The wrap-around effect with respect to baseline duration, a consequence of mode switching at intermediate levels of concurrent task distraction, should contribute substantially to estimate variability and have a complex effect on the shape of the resulting distribution of estimates.

Rosch, E.↗