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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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NASA NTRS1985

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗
NASA NTRS2017

Filter Tuning Using the Chi-Squared Statistic

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

Covariance Analysis↗
DOE OSTI2019

Rapid estimation of earthquake locations using waveform traveltimes

SUMMARY We introduce a new approach for locating earthquakes using arrival times derived from waveforms. The most costly computational step of the algorithm scales as the number of stations in the active seismographic network. In this approach, a variation on existing grid search methods, a series of full waveform simulations are conducted for all receiver locations, with sources positioned successively at each station. The traveltime field over the region of interest is calculated by applying a phase picking algorithm to the numerical wavefields produced from each simulation. An event is located by subtracting the stored traveltime field from the arrival time at each station. This provides a shifted and time-reversed traveltime field for each station. The shifted and time-reversed fields all approach the origin time of the event at the source location. The mean or median value at the source location thus approximates the event origin time. Measures of dispersion about this mean or median time at each grid point, such as the sample standard error and the average deviation, are minimized at the correct source position. Uncertainty in the event position is provided by the contours of standard error defined over the grid. An application of this technique to a synthetic data set indicates that the approach provides stable locations even when the traveltimes are contaminated by additive random noise containing a significant number of outliers and velocity model errors. It is found that the waveform-based method out-performs one based upon the eikonal equation for a velocity model with rapid spatial variations in properties due to layering. A comparison with conventional location algorithms in both a laboratory and field setting demonstrates that the technique performs at least as well as existing techniques.

58 GEOSCIENCES↗
DOE OSTI2026

A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions

In this paper, we propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governing physics into the score function of a diffusion model using simulation data and incorporate observational information via a likelihood-based correction in a reverse-time stochastic differential equation. This enables adaptive learning through iterative refinement of the solution as new data becomes available. To improve computational efficiency in high-dimensional settings, we introduce the ensemble score filter, a training-free approximation of the score function designed for real-time inference. Numerical experiments on benchmark SPDEs demonstrate the accuracy and robustness of the proposed method under sparse and noisy observations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

GSFC OSTM, Jason-l and TOPEX POD Update

The OSTM (Jason-2) has been in orbit for three years (since June 2008), and the full suite of altimeter data from TOPEX/Poseidon, Jason-I and Jason-2 now span nearly twenty years since the launch of TOPEX in 1992. Issues that affect the stability of the orbits through time and the orbit accuracy include the reference frame, the radiation pressure models for the altimeter satellites and the fidelity of the dynamic force model, including time-variable gravity, as well as the performance of the individual tracking systems. We have conducted detailed analyses of the new ITRF2008 reference frame and find only a small effect on global mean sea level compared to ITRF2005, although we note an improvement in POD quality over the most recent time periods for Jason-2. In the past year we have developed a new time series of orbits for TOPEX/Poseidon, Jason-I, and Jason-2 based on the ITRF2008 reference frame using SLR and DORIS data and for Jason-2 using GPS data. In addition, we have continued to experiment with improvements to the radiation pressure model for the altimeter satellites in particular the Jason satellites since these nonconservative force model errors now rank as the most outstanding source of error on altimeter satellite POD. In the previous (ITRF2005-based) and current (ITRF2008-based) orbits we have relied on a simplified time-variable gravity (TVG) model, derived from GRACE solutions. We have recently experimented with improvements using higher fidelity TVG models (both temporally and spatially) and report on the results. We have computed a time series of GPS-only reduced-dynamic orbits at GSFC, and used these in conjunction with the SLR-DORIS dynamic and reduced-dynamic orbits to assess reference fiame stability with respect to the different tracking systems for both ITRF2005 and ITRF2008. We show through internal (GSFConly) and external comparisons (with other analysis centers) that the radial orbit accuracy for Jason-2 remains at I cm.

Lemoine, Frank G.↗
NASA NTRS2009

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗
DOE OSTI2022

Analysis of Integrated Vapor Transport Biases

Abstract High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.

Reynolds, Carolyn A.↗
NASA NTRS1984

Error detection process - Model, design, and its impact on computer performance

An analytical model is developed for computer error detection processes and applied to estimate their influence on system performance. Faults in the hardware, not in the design, are assumed to be the potential cause of transition to erroneous states during normal operations. The classification properties and associated recovery methods of error detection are discussed. The probability of obtaining an unreliable result is evaluated, along with the resulting computational loss. Error detection during design is considered and a feasible design space is outlined. Extension of the methods to account for the effects of extant multiple faults is indicated.

Shin, K. G.↗
NASA NTRS1995

Extension to the dynamic modeling of the large angle magnetic suspension test fixture

The Large Angle Magnetic Suspension Test Fixture (LAMSTF) is a laboratory scale proof-of-concept system. The configuration is unique in that the electromagnets are mounted in a circular planar array. A mathematical model of the system had previously been developed, but was shown to have inaccuracies. These inaccuracies showed up in the step responses. Eddy currents were found to be the major cause of the modeling errors. In the original system, eddy currents existed in the aluminum baseplate, iron cores, and the sensor support frame. An attempt to include the eddy current dynamics in the system model is presented. The dynamics of a dummy sensor ring were added to the system. Adding the eddy current dynamics to the simulation improves the way it compares to the actual experiment. Also presented is a new method of determining the yaw angle of the suspended element. From the coil currents the yaw angle can be determined and the controller can be updated to suspend at the new current. This method has been used to demonstrate a 360 degree yaw angle rotation.

Foster, Lucas E.↗
DOE OSTI2016

Robust verification analysis

We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification. Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Machine Learning Prediction of H Adsorption Energies on Ag Alloys

Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. This has prompted a significant amount of work towards efficiently predicting adsorption energies without performing expensive quantum chemical calculations, based on semi-empirical or data scientific models. Here, we develop machine learning models to predict H adsorption energies on stepped Ag surface alloys using a database of energies obtained from first-principles electronic structure calculations based on density functional theory. Starting with a simple model and iteratively refining the features extracted from the calculations, we determine the key characteristics of successful models, and reduce the number of features required for accurate prediction of the adsorption energy. We find that nonlinear models are essential for accurate predictions. Moreover, detailed comparison of model predictions and calculations reveal a counterintuitive "selfpassivation" induced by some alloying elements, as well as unexpected discontinuous electronic structure effects. These findings are rationalized using tight-binding model hamiltonians and by analyzing the electronic density of states. Lastly, we show that we can estimate the reliability of a particular prediction, mitigating the effects of errors in the small fraction of cases where these errors are significant.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluation of methods to assess the uncertainty in estimated energy savings

In this work we present a methodology to evaluate the accuracy of methods used to quantify the uncertainty in estimated total energy savings. We focus on savings measurement and verification (M&V) approaches that use a baseline model to characterize energy use, and that forward-project the model for a counterfactual to determine avoided energy use. These approaches are common to the International Performance Measurement and Verification Protocol's (IPMVP's) Option C and Option B. This methodology can be used to evaluate the uncertainty in savings estimates that are due to model error. It has been applied to evaluate two uncertainty estimation methods, including the industry standard ASHRAE Guideline 14 approach. The evaluation used data from 69 commercial buildings and four different baseline models that span daily and hourly granularity, as well as linear and non-linear/non-parametric forms. The findings of this work indicate that the standard methods that are widely used by the M&V community for estimating the total savings uncertainty over the post-installation period tend to underestimate the uncertainty. The tendency to underestimate the uncertainty is stronger for hourly models than for daily models, due to stronger autocorrelation in model residuals at the hourly time scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Bias-Adjustment Methods for Future Subdaily Precipitation Extremes Consistent Across Durations

Model output from climate projections often requires bias-adjustment to compensate for systematic model errors. A bias-adjustment method for extreme precipitation intensity is proposed that preserves the scaling equation for different accumulation levels from hourly to daily, using intensity-duration-frequency (IDF) modeling. A validation is performed within a pseudo-reality setting, based on hourly precipitation from 28 regional climate model projections of the EURO-CORDEX ensemble over Belgium. The scaling-based adjustment methods improve upon previous methods, an optimal method is identified, and, analytical quantile mapping methods must be avoided due to three identified problems. The ensemble mean of the adjusted extreme precipitation intensity obeys the above-mentioned scale-invariance property, which is consistent with observed extreme intensities. We thus show that IDF modeling provides added value in the context of bias-adjustment, and, that the particular IDF model proposed balances well between accuracy and the preservation of desired properties such as scale invariance and consistency among rainfall durations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

TH-CD-202-06: A Method for Characterizing and Validating Dynamic Lung Density Change During Quiet Respiration

Purpose: To obtain a functional relationship that calibrates the lung tissue density change under free breathing conditions through correlating Jacobian values to the Hounsfield units. Methods: Free-breathing lung computed tomography images were acquired using a fast helical CT protocol, where 25 scans were acquired per patient. Using a state-of-the-art deformable registration algorithm, a set of the deformation vector fields (DVF) was generated to provide spatial mapping from the reference image geometry to the other free-breathing scans. These DVFs were used to generate Jacobian maps, which estimate voxelwise volume change. Subsequently, the set of 25 corresponding Jacobian and voxel intensity in Hounsfield units (HU) were collected and linear regression was performed based on the mass conservation relationship to correlate the volume change to density change. Based on the resulting fitting coefficients, the tissues were classified into parenchymal (Type I), vascular (Type II), and soft tissue (Type III) types. These coefficients modeled the voxelwise density variation during quiet breathing. The accuracy of the proposed method was assessed using mean absolute difference in HU between the CT scan intensities and the model predicted values. In addition, validation experiments employing a leave-five-out method were performed to evaluate the model accuracy. Results: The computed mean model errors were 23.30±9.54 HU, 29.31±10.67 HU, and 35.56±20.56 HU, respectively, for regions I, II, and III, respectively. The cross validation experiments averaged over 100 trials had mean errors of 30.02 ± 1.67 HU over the entire lung. These mean values were comparable with the estimated CT image background noise. Conclusion: The reported validation experiment statistics confirmed the lung density modeling during free breathing. The proposed technique was general and could be applied to a wide range of problem scenarios where accurate dynamic lung density information is needed. This work was supported in part by NIH R01 CA0096679.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

ON THE RETRIEVAL OF MESOSPHERIC WINDS ON MARS AND VENUS FROM GROUND-BASED OBSERVATIONS AT 10 μm

A detailed analysis is presented of ground-based observations of atmospheric emissions on Mars and Venus under non-local thermodynamic equilibrium (non-LTE) conditions at high spectral resolution. Our first goal is to comprehend the difficulties behind the derivation of wind speeds from ground-based observations. A second goal is to set a framework to permit comparisons with other observations and with atmospheric models. A forward model including non-LTE radiative transfer is used to evaluate the information content within the telescopic beam, and is later convolved with the beam function and a typical wind field to discern the major contributions to the measured radiance, including limb and nadir views. The emission mostly arises from the non-LTE limb around altitudes of 75 km on Mars and 110 km on Venus. We propose a parameterization of the limb emission using few geophysical parameters which can be extended to other hypothetical CO{sub 2} planetary atmospheres. The tropospheric or LTE component of the emission varies with the temperature and is important at low solar illumination but only for the emerging radiance, not for the wind determinations since these are derived from the Doppler shift at the non-LTE line cores. We evaluated the sources of uncertainty and found that the forward model errors amount to approximately 12% of the measured winds, which is normally smaller than the instrumental errors. We applied this study to revise a set of measurements extending for three Martian years and confirmed previous results suggesting winds that are too large simulated by current Martian circulation models at equatorial latitudes during solstice. We encourage new observational campaigns, particularly for the strong jet at mid–high latitudes on Mars, and propose general guidelines and recommendations for future observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Tracking and orbit determination of near earth orbiting satellites using earth synchronous relay satellites

A Tracking Data Relay Satellite System (TDRSS) made up of two earth synchronous data relay satellites is proposed for the late 1970s to aid in the tracking, or take the place of ground tracking, or near-earth orbiters. Theoretical error analysis studies were conducted to evaluate the TDRSS concept of tracking user satellites. All major factors affecting orbit determination accuracy were considered in the analysis, including tracking system and dynamic modeling errors.

Bryant, W. C., Jr.↗
NASA NTRS1991

A walk through the planned CS building

Using the architectural plan views of our future computer science building as test objects, we have completed the first stage of a Building walkthrough system. The inputs to our system are AutoCAD files. An AutoCAD converter translates the geometrical information in these files into a format suitable for 3D rendering. Major model errors, such as incorrect polygon intersections and random face orientations, are detected and fixed automatically. Interactive viewing and editing tools are provided to view the results, to modify and clean the model and to change surface attributes. Our display system provides a simple-to-use user interface for interactive exploration of buildings. Using only the mouse buttons, the user can move inside and outside the building and change floors. Several viewing and rendering options are provided, such as restricting the viewing frustum, avoiding wall collisions, and selecting different rendering algorithms. A plan view of the current floor, with the position of the eye point and viewing direction on it, is displayed at all times. The scene illumination can be manipulated, by interactively controlling intensity values for 5 light sources.

Khorramabadi, Delnaz↗
NASA NTRS1995

Sensitivity of planetary cruise navigation to earth orientation calibration errors

A detailed analysis was conducted to determine the sensitivity of spacecraft navigation errors to the accuracy and timeliness of Earth orientation calibrations. Analyses based on simulated X-band (8.4-GHz) Doppler and ranging measurements acquired during the interplanetary cruise segment of the Mars Pathfinder heliocentric trajectory were completed for the nominal trajectory design and for an alternative trajectory with a longer transit time. Several error models were developed to characterize the effect of Earth orientation on navigational accuracy based on current and anticipated Deep Space Network calibration strategies. The navigational sensitivity of Mars Pathfinder to calibration errors in Earth orientation was computed for each candidate calibration strategy with the Earth orientation parameters included as estimated parameters in the navigation solution. In these cases, the calibration errors contributed 23 to 58% of the total navigation error budget, depending on the calibration strategy being assessed. Navigation sensitivity calculations were also performed for cases in which Earth orientation calibration errors were not adjusted in the navigation solution. In these cases, Earth orientation calibration errors contributed from 26 to as much as 227% of the total navigation error budget. The final analysis suggests that, not only is the method used to calibrate Earth orientation vitally important for precision navigation of Mars Pathfinder, but perhaps equally important is the method for inclusion of the calibration errors in the navigation solutions.

Estefan, J. A.↗