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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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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Efficient Calibration of Expensive Computational Models

Accounting for uncertainty when calibrating expensive computational models is a common challenge faced by scientists and engineers. Often Bayesian techniques are adopted to estimate a probability density function over the model parameters given noisy empirical data. The methods used to perform this type of probabilistic calibration are computationally prohibitive in that they require a large number of evaluations of the expensive model. In these cases, surrogate modeling -- that is, using a fast-to-evaluate, lower fidelity stand-in for the original computational model -- may be the only option to alleviate this computational burden. However, the upfront cost of generating training data to build a surrogate model can itself be expensive. As such, it is important to be judicious when selecting training points at which the full-fidelity model is evaluated. Here, an active learning approach is proposed that enables efficient selection of training points using approximate samples of the calibrated parameter probability density function. In this way, the training points can be concentrated in regions where the calibration algorithm requires high model accuracy.

active learning↗
NASA NTRS1998

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

Smith, T. D.↗
DOE OSTI2025

Analytical and EZmock covariance validation for the DESI 2024 results

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on an ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full-Shape analyses, which motivates the use of a corrected mock covariance for DESI's 2024 Full Shape analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Neutrino-nucleus cross section impacts on neutrino oscillation measurements

The challenges in neutrino-nucleus cross section modeling and its impact on neutrino oscillation experiments are widely recognized. However, a comprehensive and theoretically robust estimation of cross section uncertainties has been lacking, and few studies have quantitatively examined their impact on oscillation measurements. In this work, we evaluate the effect of cross section uncertainties on oscillation parameters using setups inspired by NOvA and DUNE. To characterize these uncertainties, we adopt multiple neutrino-nucleus event generators and simulate a realistic experimental procedure that incorporates near-detector data and near-to-far-detector extrapolation. Our results confirm that cross section uncertainties cannot significantly bias oscillation results in current statistics-dominated experiments like NOvA. However, they could lead to substantial bias for future systematics-dominated experiments like DUNE, even when near-detector data are employed to mitigate uncertainties. These findings underscore the need for further studies on the quantitative impacts of cross section modeling, improved strategies to utilize near-detector data and the PRISM concept, and more robust cross section models to optimize the success of future experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Prices in Frequency Regulation Markets: Impacts of Natural Gas Prices and Variable Renewable Energy

Increasing wind and solar penetration and low natural gas prices have reduced electricity prices in competitive power markets in recent years, while also increasing the relative importance of ancillary services in balancing short-term net load variability. As a result, ancillary service markets are providing a valuable alternative revenue stream for many market participants. Yet the price dynamics in these markets are still not very well understood. In this work, we incorporate unit-level ancillary service offer prices and quantities into a production cost model and examine how prices for frequency regulation are impacted by relatively extreme perturbations of several system parameters. Initial offers are first estimated on the basis of limited available public data and are then iteratively calibrated against historic market outcomes. Through a case study of the PJM Interconnection, we find that doubling the natural gas price increases the average annual regulation price by 36%, while replacing all coal generation with natural gas decreases the average price by 42%. Increasing the wind penetration from 2% to 30% in isolation increases the average regulation price by 32%, while further doubling the regulation requirement results in an 84% increase. These price increases can be mitigated by introducing additional battery storage capacity or by increasing offer quantities from hydro and thermal units. Finally, we discuss a number of modeling challenges that are faced when incorporating ancillary services into traditional production cost models. These include poor data availability, inconsistent product definitions across markets, and complex market rules.

02 PETROLEUM↗
NASA NTRS1990

Systems Engineering and Integration (SE and I)

The issue of technology advancement and future space transportation vehicles is addressed. The challenge is to develop systems which can be evolved and improved in small incremental steps where each increment reduces present cost, improves, reliability, or does neither but sets the stage for a second incremental upgrade that does. Future requirements are interface standards for commercial off the shelf products to aid in the development of integrated facilities; enhanced automated code generation system slightly coupled to specification and design documentation; modeling tools that support data flow analysis; and shared project data bases consisting of technical characteristics cast information, measurement parameters, and reusable software programs. Topics addressed include: advanced avionics development strategy; risk analysis and management; tool quality management; low cost avionics; cost estimation and benefits; computer aided software engineering; computer systems and software safety; system testability; and advanced avionics laboratories - and rapid prototyping. This presentation is represented by viewgraphs only.

Chevers, ED↗
NASA NTRS1999

Heat Transfer Issues in Thin-Film Thermal Radiation Detectors

The Thermal Radiation Group at Virginia Polytechnic Institute and State University has been working closely with scientists and engineers at NASA's Langley Research Center to develop accurate analytical and numerical models suitable for designing next generation thin-film thermal radiation detectors for earth radiation budget measurement applications. The current study provides an analytical model of the notional thermal radiation detector that takes into account thermal transport phenomena, such as the contact resistance between the layers of the detector, and is suitable for use in parameter estimation. It was found that the responsivity of the detector can increase significantly due to the presence of contact resistance between the layers of the detector. Also presented is the effect of doping the thermal impedance layer of the detector with conducting particles in order to electrically link the two junctions of the detector. It was found that the responsivity and the time response of the doped detector decrease significantly in this case. The corresponding decrease of the electrical resistance of the doped thermal impedance layer is not sufficient to significantly improve the electrical performance of the detector. Finally, the "roughness effect" is shown to be unable to explain the decrease in the thermal conductivity often reported for thin-film layers.

Barry, Mamadou Y.↗
NASA NTRS2011

Evaluating the Performance of Single and Double Moment Microphysics Schemes During a Synoptic-Scale Snowfall Event

Increases in computing resources have allowed for the utilization of high-resolution weather forecast models capable of resolving cloud microphysical and precipitation processes among varying numbers of hydrometeor categories. Several microphysics schemes are currently available within the Weather Research and Forecasting (WRF) model, ranging from single-moment predictions of precipitation content to double-moment predictions that include a prediction of particle number concentrations. Each scheme incorporates several assumptions related to the size distribution, shape, and fall speed relationships of ice crystals in order to simulate cold-cloud processes and resulting precipitation. Field campaign data offer a means of evaluating the assumptions present within each scheme. The Canadian CloudSat/CALIPSO Validation Project (C3VP) represented collaboration among the CloudSat, CALIPSO, and NASA Global Precipitation Measurement mission communities, to observe cold season precipitation processes relevant to forecast model evaluation and the eventual development of satellite retrievals of cloud properties and precipitation rates. During the C3VP campaign, widespread snowfall occurred on 22 January 2007, sampled by aircraft and surface instrumentation that provided particle size distributions, ice water content, and fall speed estimations along with traditional surface measurements of temperature and precipitation. In this study, four single-moment and two double-moment microphysics schemes were utilized to generate hypothetical WRF forecasts of the event, with C3VP data used in evaluation of their varying assumptions. Schemes that incorporate flexibility in size distribution parameters and density assumptions are shown to be preferable to fixed constants, and that a double-moment representation of the snow category may be beneficial when representing the effects of aggregation. These results may guide forecast centers in optimal configurations of their forecast models for winter weather and identify best practices present within these various schemes.

Molthan, Andrew L.↗
NASA NTRS1987

Baseline estimation from simultaneous satellite laser tracking

Simultaneous Range Differences (SRDs) to Lageos are obtained by dividing the observing stations into pairs with quasi-simultaneous observations. For each of those pairs the station with the least number of observations is identified, and at its observing epochs interpolated ranges for the alternate station are generated. The SRD observables are obtained by subtracting the actually observed laser range of the station having the least number of observations from the interpolated ranges of the alternate station. On the basis of these observables semidynamic single baseline solutions were performed. The aim of these solutions is to further develop and implement the SRD method in the real data environment, to assess its accuracy, its advantages and disadvantages as related to the range dynamic mode methods, when the baselines are the only parameters of interest. Baselines, using simultaneous laser range observations to Lageos, were also estimated through the purely geometric method. These baselines formed the standards the standards of comparison in the accuracy assessment of the SRD method when compared to that of the range dynamic mode methods. On the basis of this comparison it was concluded that for baselines of regional extent the SRD method is very effective, efficient, and at least as accurate as the range dynamic mode methods, and that on the basis of a simple orbital modeling and a limited orbit adjustment. The SRD method is insensitive to the inconsistencies affecting the terrestrial reference frame and simultaneous adjustment of the Earth Rotation Parameters (ERPs) is not necessary.

Dedes, George C.↗
NASA NTRS1981

Equivalent source modeling of the main field using Magsat data

Magsat dipole solution models were obtained with both 32 deg and 21 deg resolution based on a data set extending over 4 months. Time dependence was modeled using first time derivatives for the dipole magnetization vector components. This doubles the n total number of parameters in the solution. The solutions displayed a very slow convergence in time derivatives although at each iteration the conversion of the dipole parameters to spherical harmonic coefficients showed close agreement with the MGST (12/80) spherical harmonic model to degree 13 in the constant terms and 8 in the secular variation terms. The program error in the option to simultaneously estimate observatory anomaly biases was found and corrected. A 32 deg resolution dipole model was generated using the selected magnetic observatory data from 1960-1977 used in the GSFC (9/80) spherical harmonic model.

Source record↗
NASA NTRS1986

Bearing Thermal Performance Prediction

Parameter called lubricant percent volume or cavity factor (XCAV) used primarily in calculation of ball or roller drag and, therefore, significantly affects calculated bearing-heat generation and temperature distribution. New equation accounts for sensitivity of XCAV to shaft speed, lubricant flow rate, and bearing size, and provides significant improvement over previous estimation methods.

Parker, R. J.↗
NASA NTRS1992

Maximum likelihood techniques applied to quasi-elastic light scattering

There is a necessity of having an automatic procedure for reliable estimation of the quality of the measurement of particle size from QELS (Quasi-Elastic Light Scattering). Getting the measurement itself, before any error estimates can be made, is a problem because it is obtained by a very indirect measurement of a signal derived from the motion of particles in the system and requires the solution of an inverse problem. The eigenvalue structure of the transform that generates the signal is such that an arbitrarily small amount of noise can obliterate parts of any practical inversion spectrum. This project uses the Maximum Likelihood Estimation (MLE) as a framework to generate a theory and a functioning set of software to oversee the measurement process and extract the particle size information, while at the same time providing error estimates for those measurements. The theory involved verifying a correct form of the covariance matrix for the noise on the measurement and then estimating particle size parameters using a modified histogram approach.

Edwards, Robert V.↗
NASA NTRS2002

Broadband Observations and Modeling of the Shell-Type Supernova Remnant G347.3-0.5

The supernova remnant G347.3-0.5 emits a featureless power law in X-rays, thought to indicate shock acceleration of electrons to high energies. We here produce a broadband spectrum of the bright northwest limb of this source by combining radio observations from the Australia Telescope Compact Array (ATCA), X-ray observations from the Advanced Satellite for Cosmology and Astrophysics (ASCA), and TeV gamma-ray observations from the CANGAROO imaging Cerenkov telescope. We assume that this emission is produced by an electron population generated by diffusive shock acceleration at the remnant forward shock. The nonlinear aspects of the particle acceleration force a connection between the widely different wavelength bands and between the electrons and the unseen ions, presumably accelerated simultaneously with the electrons. This allows us to infer the relativistic proton spectrum and estimate ambient parameters such as the supernova explosion energy, magnetic field, matter density in the emission region, and efficiency of the shock acceleration process. We find convincing evidence that the shock acceleration is efficient, placing greater than 25% of the shock kinetic energy flux into relativistic ions. Despite this high efficiency, the maximum electron and proton energies, while depending somewhat on assumptions for the compression of the magnetic field in the shock, are well below the observed 'knee' at 10(exp 15) eV in the Galactic cosmic-ray spectrum.

Ellison, Donald C.↗
NASA NTRS2018

Physics-Based Approach to Predict the Solar Activity Cycles

Observations of the complex highly non-linear dynamics of global turbulent flows and magnetic fields are currently available only from Earth-side observations. Recent progress in helioseismology has provided us some additional information about the subsurface dynamics, but its relation to the magnetic field evolution is not yet understood. These limitations cause uncertainties that are difficult take into account, and perform proper calibration of dynamo models. The current dynamo models have also uncertainties due to the complicated turbulent physics of magnetic field generation, transport and dissipation. Because of the uncertainties in both observations and theory, the data assimilation approach is natural way for the solar cycle prediction and estimating uncertainties of this prediction. I will discuss the prediction results for the upcoming Solar Cycle 25 and their uncertainties and affect of Ensemble Kalman Filter parameters to resulting predictions.

Physics-Based↗
NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗
NASA NTRS2003

Market Assessment of Forward-Looking Turbulence Sensing Systems

This viewgraph presentation provides a cost benefit analysis of three next-generation forward-looking turbulence sensing systems: X band turbulence radar system for convective turbulence, LIDAR based turbulence systems to sense clear air turbulence and a combined hybrid system. Parameters for the cost benefit analysis were established using a business model which considered injury rates, cost of injuries, indirect costs, market penetration rate estimates and product success characteristics. Topics covered include: study approach, business case equations, data acquisition, benchmark analysis. Data interpretation from the cost benefit analysis is presented. The researchers conclude that the market potential for these products is based primarily on injury cost reduction and that X band radar systems have the greatest chance for commercial success.

Kauffmann, Paul↗
DOE OSTI2019

Search for an Exotic S=-2, Q=-2 Baryon Resonance in Proton-Proton Interactions at $\sqrt{s_{NN}}$ = 17.3 GeV

Searches and analyses of strong gravitational lenses are challenging due to the rarity and image complexity of these astronomical objects. Next-generation surveys (both ground- and space-based) will provide more opportunities to derive science from these objects, but only if they can be analyzed on realistic time-scales. Currently, these analyses are expensive. In this work, we present a regression analysis with uncertainty estimates using deep learning models to measure four parameters of strong gravitational lenses in simulated Dark Energy Survey data. Using only $gri$-band images, we predict Einstein Radius, lens velocity dispersion, lens redshift to within $10-15\%$ of truth values and source redshift to $30\%$ of truth values, along with predictive uncertainties. This work helps to take a step along the path of faster analyses of strong lenses with deep learning frameworks.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Controls for space structures

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control. A theory for disturbance accommodating controllers based on reduced order models of structures was developed, and stability results for these controllers in closed-loop with large-scale finite element models of structures were obtained.

Balas, Mark↗