A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection
Abstract not provided.
Wahl, Daniel E.↗
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Results for “estimation”
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.
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Hydrogen Station Cost Estimates: Comparing Hydrogen Station Cost Calculator Results with other Recent Estimates
This report compares hydrogen station cost estimates conveyed by expert stakeholders through the Hydrogen Station Cost Calculation (HSCC) to a select number of other cost estimates. These other cost estimates include projections based upon cost models and costs associated with recently funded stations.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Evaluation of mineral reactive surface area estimates for prediction of reactivity of a multi-mineral sediment
Our limited understanding of mineral reactive surface area contributes to significant uncertainties in quantitative simulations of reactive chemical transport in subsurface processes. Continuum formulations for reactive transport typically use a number of different approximations for reactive surface area, including geometric, specific, and effective surface area. In this work, reactive surface area estimates are developed and evaluated for their ability to predict dissolution rates in a well-stirred flow-through reactor experiment using disaggregated samples from the Nagaoka pilot CO 2 injection site (Japan). The disaggregated samples are reacted with CO 2 acidified synthetic brine under conditions approximating the field conditions and the evolution of solute concentrations in the reactor effluent is tracked over time. The experiments, carried out in fluid-dominated conditions at a pH of 3.2 for 650 h, resulted in substantial dissolution of the sample and release of a disproportionately large fraction of the divalent cations. Traditional reactive surface area estimation methods, including an adjusted geometric surface area and a BET-based surface area, are compared to a newly developed image-based method. Continuum reactive transport modeling is used to determine which of the reactive surface area models provides the best match with the effluent chemistry from the well-stirred reactor. The modeling incorporates laboratory derived mineral dissolution rates reported in the literature and the initial modal mineralogy of the Nagaoka sediment was determined from scanning electron microscopy (SEM) characterization. The closest match with the observed steady-state effluent concentrations was obtained using specific surface area estimates from the image-based approach supplemented by literature-derived BET measurements. To capture the evolving effluent chemistry, particularly over the first 300 h of the experiment, it was also necessary to account for the grain size distribution in the sediment and the presence of a highly reactive volcanic glass phase that shows preferential cation leaching.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
An image-based equation for estimating the prospective CO2 storage resource of organic-rich shale formations
Not Available
Azenkeng, Alexander↗
Band gap estimation from temperature dependent Seebeck measurement—Deviations from the 2e|S|maxTmax relation
Not Available
Gibbs, Zachary M.↗
Bayesian Parameter Estimation of the k-ω Shear Stress Transport Model for Accurate Simulations of Impinging-Jet Heat Transfer
Given the lack of fusion-relevant component test facilities, current estimates of the thermo-fluid performance of plasma-facing components are based for the most part on numerical simulations. A major source of uncertainty in these simulations is the semiempirical turbulence (closure) models for the Reynolds stresses appearing in the governing Reynolds-averaged Navier-Stokes equations, which involve a set of constants that depend upon the flow. The objective of this study is to evaluate Bayesian parameter estimation of turbulence closure constants in ANSYS Fluent to model heat transfer in impinging jets. The Bayesian statistical calibration produces a probability distribution for these constants from experimental data; the maximum a posteriori estimates are then taken to be the calibrated constants, or parameters. The turbulence model constants are calibrated using an experimental study of a submerged jet of air impinging on a flat heated surface at Reynolds numbers Re = O(10 4 ) and impingement distance in jet diameters H/d = 2. Numerical predictions using the calibrated model parameters are then compared with those generated using the default constants. Predictions obtained with model parameters calibrated on datasets of two different sizes are compared to evaluate the effect of the number of calibration samples. Lastly, the extrapolative ability of the calibrated model is examined by predictions at a Re beyond the calibration values.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
On the estimation of statistical uncertainties on powder diffraction and small-angle scattering data from two-dimensional X-ray detectors
Optimal methods are explored for obtaining one-dimensional powder pattern intensities from two-dimensional planar detectors with good estimates of their standard deviations. Methods are described to estimate uncertainties when the same image is measured in multiple frames as well as from a single frame. The importance of considering the correlation of diffraction points during the integration and the resampling process of data analysis is shown. It is found that correlations between adjacent pixels in the image can lead to seriously overestimated uncertainties if such correlations are neglected in the integration process. Off-diagonal entries in the variance–covariance (VC) matrix are problematic as virtually all data processing and modeling programs cannot handle the full VC matrix. It is shown that the off-diagonal terms come mainly from the pixel-splitting algorithm used as the default integration algorithm in many popular two-dimensional integration programs, as well as from rebinning and resampling steps later in the processing. When the full VC matrix can be propagated during the data reduction, it is possible to get accurate refined parameters and their uncertainties at the cost of increasing computational complexity. However, as this is not normally possible, the best approximate methods for data processing in order to estimate uncertainties on refined parameters with the greatest accuracy from just the diagonal variance terms in the VC matrix is explored.
Yang, X.↗
Dynamic Programming Approach to Estimate the Capacity Value of Energy Storage
Abstract not provided
14 SOLAR ENERGY↗
Attenuation-based estimation of patient size for the purpose of size specific dose estimation in CT. Part II. Implementation on abdomen and thorax phantoms using cross sectional CT images and scanned projection radiograph images
Purpose: To estimate attenuation using cross sectional CT images and scanned projection radiograph (SPR) images in a series of thorax and abdomen phantoms. Methods: Attenuation was quantified in terms of a water cylinder with cross sectional area of A{sub w} from both the CT and SPR images of abdomen and thorax phantoms, where A{sub w} is the area of a water cylinder that would absorb the same dose as the specified phantom. SPR and axial CT images were acquired using a dual-source CT scanner operated at 120 kV in single-source mode. To use the SPR image for estimating A{sub w}, the pixel values of a SPR image were calibrated to physical water attenuation using a series of water phantoms. A{sub w} and the corresponding diameter D{sub w} were calculated using the derived attenuation-based methods (from either CT or SPR image). A{sub w} was also calculated using only geometrical dimensions of the phantoms (anterior-posterior and lateral dimensions or cross sectional area). Results: For abdomen phantoms, the geometry-based and attenuation-based methods gave similar results for D{sub w}. Using only geometric parameters, an overestimation of D{sub w} ranging from 4.3% to 21.5% was found for thorax phantoms. Results for D{sub w} using the CT image and SPR based methods agreed with each other within 4% on average in both thorax and abdomen phantoms. Conclusions: Either the cross sectional CT or SPR images can be used to estimate patient attenuation in CT. Both are more accurate than use of only geometrical information for the task of quantifying patient attenuation. The SPR based method requires calibration of SPR pixel values to physical water attenuation and this calibration would be best performed by the scanner manufacturer.
60 APPLIED LIFE SCIENCES↗
Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign
This study presents radar-based precipitation estimates collected during the two-month DOE ARM - NASA Midlatitude Continental Convective Clouds Experiment (MC3E). Emphasis is on the usefulness of radar observations from the C-band and X-band scanning ARM precipitation radars (CSAPR, XSAPR) for rainfall estimation products to distances within 100 km of the Oklahoma SGP facility. A dense collection of collocated ARM, NASA GPM and nearby surface Oklahoma Mesonet gauge records are consulted to evaluate potential ARM radar-based hourly rainfall products and campaign optimized methods over individual gauge and areal characterizations. Rainfall products are evaluated against the performance of the regional operational NWS NEXRAD S-band radar polarimetric product. Results indicate that the ARM C-band system may achieve similar point and areal-gauge bias and root mean square (rms) error performance to the NEXRAD standard for the variety of MC3E deep convective events sampled when capitalizing on differential phase measurements. The best campaign rainfall performance was achieved when applying radar relations capitalizing on estimates of the specific attenuation from the CSAPR system. The ARM X-band systems only demonstrate solid capabilities as compared to NEXRAD standards for hourly point and areal rainfall accumulations under 10 mm. Here, all methods exhibit a factor of 1.5 to 2.5 reduction in rms errors for areal accumulations over a 15 km2 NASA dense network housing 16 sites having collocated bucket gauges, with the higher error reductions best associated with polarimetric methods.
54 ENVIRONMENTAL SCIENCES↗
New machine learning techniques for simulation-based inference: InferoStatic nets, kernel score estimation, and kernel likelihood ratio estimation
We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential \varphi φ . In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.
Kong, Kyoungchul↗
PR100: Estimated Medium- and Heavy-Duty Electric Vehicle Adoption and Load Estimation in Puerto Rico through 2050
The 2-year Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study analyzed stakeholder-driven pathways to Puerto Rico’s clean energy future. Outputs relating to electricity demand modeling were partially informed by estimates of electric vehicle adoption across all classes of medium- and heavy-duty vehicles (MHDVs), and the ensuing charging loads. To create these estimates, the team developed a transportation model for MHDVs in Puerto Rico to estimate the amount and geospatial distribution of energy used. Charging schedules for the different end uses of MHDVs were then used to construct electric load shapes assuming a portion of those vehicles would be replaced by battery electric counterparts. Study results showed that, by 2050, electric vehicles may constitute roughly 50% of the MHDV population in Puerto Rico. The resulting electrical demand curve attributable to MHDV charging showed that, for solar energy-based electrical systems with limited energy storage, this demand may create challenges unless appropriately managed either on the demand or supply side.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Estimating Jupiter’s Gravity Field Using Juno Measurements, Trajectory Estimation Analysis, and a Flow Model Optimization
The upcoming Juno spacecraft measurements have the potential of improving our knowledge of Jupiter’s gravity field. The analysis of the Juno Doppler data will provide a very accurate reconstruction of spatial gravity variations, but these measurements will be very accurate only over a limited latitudinal range. In order to deduce the full gravity field of Jupiter, additional information needs to be incorporated into the analysis, especially regarding the Jovian flow structure and its depth, which can influence the measured gravity field. In this study we propose a new iterative method for the estimation of the Jupiter gravity field, using a simulated Juno trajectory, a trajectory estimation model, and an adjoint-based inverse model for the flow dynamics. We test this method both for zonal harmonics only and with a full gravity field including tesseral harmonics. The results show that this method can fit some of the gravitational harmonics better to the “measured” harmonics, mainly because of the added information from the dynamical model, which includes the flow structure. Thus, it is suggested that the method presented here has the potential of improving the accuracy of the expected gravity harmonics estimated from the Juno and Cassini radio science experiments.
79 ASTRONOMY AND ASTROPHYSICS↗
Quantiles, parametric-select density estimation, and bi-information parameter estimators
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
Parzen, E.↗
Space shuttle propulsion parameter estimation using optimal estimation techniques
The first twelve system state variables are presented with the necessary mathematical developments for incorporating them into the filter/smoother algorithm. Other state variables, i.e., aerodynamic coefficients can be easily incorporated into the estimation algorithm, representing uncertain parameters, but for initial checkout purposes are treated as known quantities. An approach for incorporating the NASA propulsion predictive model results into the optimal estimation algorithm was identified. This approach utilizes numerical derivatives and nominal predictions within the algorithm with global iterations of the algorithm. The iterative process is terminated when the quality of the estimates provided no longer significantly improves.
Source record↗
Space shuttle propulsion parameter estimation using optional estimation techniques
A regression analyses on tabular aerodynamic data provided. A representative aerodynamic model for coefficient estimation. It also reduced the storage requirements for the "normal' model used to check out the estimation algorithms. The results of the regression analyses are presented. The computer routines for the filter portion of the estimation algorithm and the :"bringing-up' of the SRB predictive program on the computer was developed. For the filter program, approximately 54 routines were developed. The routines were highly subsegmented to facilitate overlaying program segments within the partitioned storage space on the computer.
Source record↗
Inversion of vegetation canopy reflectance models for estimating agronomic variables. III - Estimation using only canopy reflectance data as illustrated by the suits model. IV - Total inversion of the SAIL model
The possibility of estimating agronomic and spectral parameters for a vegetation canopy from the canopy reflectance (CR) data in the infrared region is investigated for a set of solar/view directions. It is shown that such an estimation is possible, in principle, for the Suits (1972) model for a homogeneous canopy. The technique is then applied to a more complex model, the SAIL (scattering by arbitrarily inclined leaves) model which explicitly includes the leaf angle distribution in the computation of the canopy reflectance. It is concluded that, given the expected accuracy of CR measurements and the accuracy of the SAIL model in representing CR in the infrared region, the agronomic parameters, leaf area index, and leaf angle distribution can be estimated fairly accurately using ancillary data on spectral parameters.
Goel, N. S.↗
Model-based estimation of wind fields over the ocean from wind scatterometer measurements. I - Development of the wind field model. II - Model parameter estimation
Techniques for the determination of near-surface mesoscale ocean wind fields on the basis of satellite scatterometer data are developed and demonstrated. The derivation of normal-boundary and parameterized-boundary-condition (PBC) wind-field models is outlined, and results from a simulation performed to estimate the model errors are presented in tables. It is shown that the PBC model provides accurate results while minimizing the number of unknowns. After a review of the principles of scatterometry and an analysis of scatterometer measurement noise, an objective function for the measurement parameters is developed and optimized on the basis of gradient search with initial values computed from pointwise wind estimates. The model is then applied to data from a simulation of the NASA Scatterometer (Li et al., 1984), and the results are presented in extensive graphs. The feasibility of model-based wind-field estimation and the appropriateness of the PBC model are demonstrated.
Long, David G.↗