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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Field-Aligned Poynting Flux Observations in the High-Latitude Ionosphere

We have used data from Dynamics Explorer 2 to investigate the rate of conversion of electromagnetic energy into both thermal and bulk flow particle kinetic energy in the high-latitude ionosphere. The flux tube integrated conversion rate E(dot)J can be determined from spacecraft measurements of the electric and magnetic field vectors by deriving the field-aligned Poynting flux, S(parallel) = S(dot)B(sub 0), where B(sub 0) is in the direction of the geomagnetic field. Determination of the Poynting flux from satellite observations is critically dependent upon the establishment of accurate values of the fields and is especially sensitive to errors in the baseline (unperturbed) geomagnetic field. We discuss our treatment of the data in some detail, particularly in regard to systematically correcting the measured magnetic field to account for attitude changes and model deficiencies. S(parallel) can be used to identify the relative strengths of the magnetosphere and thermospheric winds as energy drivers and we present observations demonstrating the dominance of each of these. Dominance of the magnetospheric driver is indicated by S(parallel) directed into the ionosphere. Electromagnetic energy is delivered to and dissipated within the region. Dominance of the neutral wind requires that the conductivity weighted neutral wind speed in the direction of the ion drift be larger than the ion drift, resulting in observations of an upward directed Poynting flux. Electromagnetic energy is generated within the ionospheric region in this case. We also present observations of a case where the neutral atmosphere motion may be reaching a state of sustained bulk flow velocity as evidenced by very small Poynting flux in the presence of large electric fields.

Slavin, J. A.↗
DOE OSTI2016

TU-AB-202-07: A Novel Method for Registration of Mid-Treatment PET/CT Images Under Conditions of Tumor Regression for Patients with Locally Advanced Lung Cancers

Purpose: In PET-guided adaptive radiotherapy (RT), changes in the metabolic activity at individual voxels cannot be derived until the duringtreatment CT images are appropriately registered to pre-treatment CT images. However, deformable image registration (DIR) usually does not preserve tumor volume. This may induce errors when comparing to the target. The aim of this study was to develop a DIR-integrated mechanical modeling technique to track radiation-induced metabolic changes on PET images. Methods: Three patients with non-small cell lung cancer (NSCLC) were treated with adaptive radiotherapy under RTOG 1106. Two PET/CT image sets were acquired 2 weeks before RT and 18 fractions after the start of treatment. DIR was performed to register the during-RT CT to the pre-RT CT using a B-spline algorithm and the resultant displacements in the region of tumor were remodeled using a hybrid finite element method (FEM). Gross tumor volume (GTV) was delineated on the during-RT PET/CT image sets and deformed using the 3D deformation vector fields generated by the CT-based registrations. Metabolic tumor volume (MTV) was calculated using the pre- and during–RT image set. The quality of the PET mapping was evaluated based on the constancy of the mapped MTV and landmark comparison. Results: The B-spline-based registrations changed MTVs by 7.3%, 4.6% and −5.9% for the 3 patients and the correspondent changes for the hybrid FEM method −2.9%, 1% and 6.3%, respectively. Landmark comparisons were used to evaluate the Rigid, B-Spline, and hybrid FEM registrations with the mean errors of 10.1 ± 1.6 mm, 4.4 ± 0.4 mm, and 3.6 ± 0.4 mm for three patients. The hybrid FEM method outperforms the B-Spline-only registration for patients with tumor regression Conclusion: The hybrid FEM modeling technique improves the B-Spline registrations in tumor regions. This technique may help compare metabolic activities between two PET/CT images with regressing tumors. The author gratefully acknowledges the financial support from the National Institutes of Health Grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Computation of the Biot–Savart line integral with higher-order convergence using straight segments

One common approach to computing the magnetic field produced by a filamentary current-carrying coil is to approximate the coil as a series of straight segments. The Biot–Savart field from each straight segment is analytically known. However, if the endpoints of the straight segments are chosen to lie on the coil, then the accuracy of the Biot–Savart computation is generally only the second order in the number of endpoints. In this work, we propose a simple modification: shift each end point of the coil in the outward normal direction by an amount proportional to the local curvature. With this modification, the Biot–Savart accuracy increases to the fourth order and the numerical error is dramatically reduced for a given number of discretization points.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1974

Optimal design of an unsupervised adaptive classifier with unknown priors

An adaptive detection scheme for M hypotheses was analyzed. It was assumed that the probability density function under each hypothesis was known, and that the prior probabilities of the M hypotheses were unknown and sequentially estimated. Each observation vector was classified using the current estimate of the prior probabilities. Using a set of nonlinear transformations, and applying stochastic approximation theory, an optimally converging adaptive detection and estimation scheme was designed. The optimality of the scheme lies in the fact that convergence to the true prior probabilities is ensured, and that the asymptotic error variance is minimum, for the class of nonlinear transformations considered. An expression for the asymptotic mean square error variance of the scheme was also obtained.

Kazakos, D.↗
NASA NTRS1984

Research in computer science

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.

Ortega, J. M.↗
NASA NTRS1991

A scheme for reducing the effect of selective availability on precise geodetic measurements from the Global Positioning System

From March to August 1990, the signals transmitted by the Block II satellites of the GPS were dithered under a policy of 'Selective Availability' (SA). The dithering appears as an about 10 to the -10th deviation of the satellite oscillator frequency, which, when accumulated over several minutes, can produce an error of about 100 cycles in the model for carrier beat phase. Differencing between simultaneously sampling receivers minimizes the error. If, however, the receivers do not sample simultaneously, it is necessary to model the frequency deviation. Such a model is here applied to data collected in March 1990 by TI4100 and Minimac receivers sampling at times separated by 0.92 s. Applying the algorithm significantly improves the rms scatter of the estimated relative position vectors. The rms scatter from a data set including dithered satellites is similar for both simultaneously and nonsimultaneously sampling receivers, a result which indicates that SA can be adequately modeled.

Feigl, Kurt L.↗
DOE OSTI2018

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ), which is not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for online estimation and control of MIQ indices. First, to completely capture the nonlinear dynamics of the BF process, the nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multi-output problem, the multi- task transfer learning is proposed to design a novel multi-output LS-SVR (M-LS-SVR) for learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS- SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can be properly distinguished, thus a robust modeling result can be achieved. Finally, a novel multi- objective evaluation index on modeling performance is developed by comprehensively considering the root mean square error of modeling and the correlation coefficient on trend fitting, based on which the NSGA-II algorithm is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently, which indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.

blast cavities, Control↗
NASA NTRS1984

A SEASAT SASS simulation experiment to quantify the errors related to a + or - 3 hour intermittent assimilation technique

A series of SEASAT repeat orbits over a sequence of best Low center positions is simulated by using the Seatrak satellite calculator. These Low centers are, upon appropriate interpolation to hourly positions, Located at various times during the + or - 3 hour assimilation cycle. Error analysis for a sample of best cyclone center positions taken from the Atlantic and Pacific oceans reveals a minimum average error of 1.1 deg of Longitude and a standard deviation of 0.9 deg of Longitude. The magnitude of the average error seems to suggest that by utilizing the + or - 3 hour window in the assimilation cycle, the quality of the SASS data is degraded to the Level of the background. A further consequence of this assimilation scheme is the effect which is manifested as a result of the blending of two or more more juxtaposed vector winds, generally possessing different properties (vector quantity and time). The outcome of this is to reduce gradients in the wind field and to deform isobaric and frontal patterns of the intial field.

Sylvester, W. B.↗
NASA NTRS1994

Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude

Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.

Sedlak, J.↗
NASA NTRS2004

The Wind and Temperature Spectrometer (WTS) in the Atmospheric Neutral Density Experiment (ANDE) Satellite

Miniaturization efforts in new spectrometers for ionosphere/thermosphere investigations of the ion-drifts and neutral winds and corresponding temperatures make possible very light (about 250 g) packages consuming less than 0.4 W. Previously described, our approach measures the angular and energy distributions of neutral atoms and molecules (or ions) in two perpendicular planes; using those distributions to determine the full wind vector, the temperature and the relative densities of O and N2, as required for the ANDE mission. The measurements require two separate electron impact ion sources each with its own electron beam cathode. We have developed a low-temperature thermionic emission cathode that delivers 1 mA electron current at 80 mW power, making it possible to operate neutral wind-temperature experiments for the first time with powers less than 0.5 W. Advances in the ion optics of the energy-angle spectrometer enhance the energy resolution-aperture product more than a factor of 3 to enable energy resolutions of a few percent with large apertures. With these technology improvements it is now possible to obtain the full neutral wind vector, temperature and O/N2, density ratio once per second in a 250g/0.4W package with sensitivity up to about 500 km altitude in the thermosphere. We will describe the WTS as deployed in ANDE and show simulated data with the non-linear least squares analysis to illustrate expected performance of the WTS in the estimated errors in the three components of the wind, the temperature, and the relative densities.

Herrero, F. A.↗
NASA NTRS2009

Bounded-Angle Iterative Decoding of LDPC Codes

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Dolinar, Samuel↗
DOE OSTI2011

QCD sum rule determination of the charm-quark mass

QCD sum rules involving mixed inverse moment integration kernels are used in order to determine the running charm-quark mass in the MS scheme. Both the high and the low energy expansion of the vector current correlator are involved in this determination. The optimal integration kernel turns out to be of the form p(s)=1-(s{sub 0}/s){sup 2}, where s{sub 0} is the onset of perturbative QCD. This kernel enhances the contribution of the well known narrow resonances, and reduces the impact of the data in the range s{approx_equal}20-25 GeV{sup 2}. This feature leads to a substantial reduction in the sensitivity of the results to changes in s{sub 0}, as well as to a much reduced impact of the experimental uncertainties in the higher resonance region. The value obtained for the charm-quark mass in the MS scheme at a scale of 3 GeV is m{sub c}(3 GeV)=987{+-}9 MeV, where the error includes all sources of uncertainties added in quadrature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗
DOE OSTI2024

Structure Sensitive Reaction Kinetics of Chiral Molecules on Intrinsically Chiral Surfaces

Enantiospecific heterogeneous catalysis utilizes chiral surfaces to resolve enantiomers via structure sensitive surface chemistry. The catalyst design challenge is the identification of chiral surface structures that maximize enantiospecificity. Herein, we develop data driven models for the enantiospecificity of tartaric acid reactions on chiral Cu(hkl) R&S surfaces. Measurements of enantiospecific rate constants were obtained by using curved Cu(hkl) R&S surfaces that enable kinetic measurements on hundreds of chiral surface orientations. One model uses feature vectors derived from generalized coordination numbers to capture the local structure around Cu atoms exposed by the Cu(hkl) R&S surfaces. The second model introduces the use of chiral cubic harmonic functions to capture the symmetry constraints of the face-centered cubic Cu structure. The model using 58 generalized coordination numbers has a fitting error similar to that of the model using only 5 cubic harmonic functions. The two models predict maxima in the enantiospecificity on surfaces with very similar surface orientations. The models developed in this work are applicable for any enantiospecific reaction happening on any chiral material with a cubic lattice structure, opening the way to understanding the surface structure sensitivity of the enantiospecific reaction kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Sample variance in weak lensing: How many simulations are required?

Constraining cosmology using weak gravitational lensing consists of comparing a measured feature vector of dimension N b with its simulated counterpart. An accurate estimate of the N b × N b feature covariance matrix C is essential to obtain accurate parameter confidence intervals. When C is measured from a set of simulations, an important question is how large this set should be. To answer this question, we construct different ensembles of N r realizations of the shear field, using a common randomization procedure that recycles the outputs from a smaller number N s ≤ N r of independent ray-tracing N-body simulations. We study parameter confidence intervals as a function of (N s , N r ) in the range 1 ≤ N s ≤ 200 and 1 ≤ N r ≲ 105. Previous work [S. Dodelson and M. D. Schneider, Phys. Rev. D 88, 063537 (2013)] has shown that Gaussian noise in the feature vectors (from which the covariance is estimated) lead, at quadratic order, to an O(1/N r ) degradation of the parameter confidence intervals. Using a variety of lensing features measured in our simulations, including shear-shear power spectra and peak counts, we show that cubic and quartic covariance fluctuations lead to additional O(1/N 2 r ) error degradation that is not negligible when N r is only a factor of few larger than N b . We study the large N r limit, and find that a single, 240 Mpc/h sized 512 3 -particle N-body simulation (N s = 1) can be repeatedly recycled to produce as many as N r = few × 10 4 shear maps whose power spectra and high-significance peak counts can be treated as statistically independent. Lastly, a small number of simulations (N s = 1 or 2) is sufficient to forecast parameter confidence intervals at percent accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Characterizing Sub-Cohorts via Data Normalization and Representation Learning

The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipeline for refining the process of cohort selection based on medical concepts recorded in the electronic health records (EHRs). The pipeline extracts EHR data for a given cohort and normalizes this data using standard vocabularies. Then a stacked denoising autoencoder is used to embed the normalized patient vectors in a low dimensional space, where the patients are subsequently clustered into sub-cohorts. The goal is to represent the cohort in a standard format and abstract variants of sub-populations. As a use-case, we applied the pipeline to 1.8 million Veterans diagnosed with major depressive disorder (MDD), and identified four meaningful sub-cohorts using the features learned by the autoencoder. Then, each sub-cohort was explored using a set of keywords for interpretation.

Rush III, Everett↗
DOE OSTI2019

Modelling Curvilinear Beamline Effects on Beam- and Spin-Dynamics in the Fermilab Muon g-2 Storage Ring.

A model of the Fermilab Muon g-2 Experiment storage ring is developed with the BMAD simulation library for beam- and spin-dynamics studies. Particular focus is given to the electrostatic quadrupoles, the plates of which follow the curvature of the particle design trajectory of the magnetically uniform storage ring. To model these, standard electric multipoles and a novel method based on cylindrical harmonics are investigated and found to accurately match the electric field maps produced for the bulk and fringe regions of the curved quadrupoles respectively, despite these methods being specifically for straight beamlines. The toroidal multipole description is then developed, to include curvature and longitudinal field variations (to model the fringe field regions). Various combinations of the different descriptions (including use of the field maps) are used for the bulk and fringe fields of the quadrupoles, and the toroidal multipoles are found to provide the best agreement with the measured tunes of the storage ring. Two integrators are also developed, based on the method of Wu, Forest and Robin. The first of these describes motion in a uniform magnetic dipole field with arbitrary electric field, and produces results comparable to those of the adaptive-step fourth-order Runge–Kutta integrator implemented in BMAD, suitable for tracking over thousands of turns. The second is a generalisation of the first to arbitrary magnetic vector potentials superimposed on that of the uniform dipole, with arbitrary electric fields, and was also found to agree with the Runge–Kutta integrator. Simulations of antimuon storage for 2000 turns of the storage ring were performed, where losses were studied along with the evolution of beam polarisation. The storage losses, important for reducing the systematic error in the measurement of the muon g-2, were found to be largely due to collimator shape. The correlation between momentum and spin precession frequency reflect the effects expected from the electric field correction in the T-BMT equation, on the order of 10 -6 . Particle injection was also studied, for various injection angles, quadrupole strengths and strengths of injection kick, and in the cases where experimental data was provided, the model was found to be consistent with the experiment.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Projecting the Thermal Response in a HTGR-Type System during Conduction Cooldown Using Graph-Laplacian Based Machine Learning

Accurate prediction of an off-normal event in a nuclear reactor is dependent upon the availability of sensory data, reactor core physical condition, and understanding of the underlying phenomenon. This work presents a method to project the data from some discrete sensory locations to the overall reactor domain during conduction cooldown scenarios similar to High Temperature Gas-cooled Reactors (HTGRs). The existing models for conductive cooldown in a heterogeneous multi-body system, such as an assembly of prismatic blocks or pebble beds relies on knowledge of the thermal contact conductance, requiring significant knowledge of local thermal contacts and heat transport possibilities across those contacts. With a priori knowledge of bulk geometry features and some discrete sensors, a machine learning approach was devised. The presented work uses an experimental facility to mimic conduction cooldown with an assembly of 68 cylindrical rods initially heated to 1200 K. High-fidelity temperature data were collected using an infrared (IR) camera to provide training data to the model and validate the predicted temperature data. The machine learning approach used here first converts the macroscopic bulk geometry information into Graph-Laplacian, and then uses the eigenvectors of the Graph-Laplacian to develop Kernel functions. Support vector regression (SVR) was implemented on the obtained Kernels and used to predict the thermal response in a packed rod assembly during a conduction cooldown experiment. The usage of SVR modeling differs from most models today because of its representation of thermal coupling between rods in the core. When trained with thermographic data, the average normalized error is less than 2% over 400 s, during which temperatures of the assembly have dropped by more than 500 K. The rod temperature prediction performance was significantly better for rods in the interior of the assembly compared to those near the exterior, likely due to the model simplification of the surroundings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗