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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Large-scale 3D geoelectromagnetic modeling using parallel adaptive high-order finite element method

Here, we have investigated the use of the adaptive high-order finite-element method (FEM) for geoelectromagnetic modeling. Because high-order FEM is challenging from the numerical and computational points of view, most published finite-element studies in geoelectromagnetics use the lowest order formulation. Solution of the resulting large system of linear equations poses the main practical challenge. We have developed a fully parallel and distributed robust and scalable linear solver based on the optimal block-diagonal and auxiliary space preconditioners. The solver was found to be efficient for high finite element orders, unstructured and nonconforming locally refined meshes, a wide range of frequencies, large conductivity contrasts, and number of degrees of freedom (DoFs). Furthermore, the presented linear solver is in essence algebraic; i.e., it acts on the matrix-vector level and thus requires no information about the discretization, boundary conditions, or physical source used, making it readily efficient for a wide range of electromagnetic modeling problems. To get accurate solutions at reduced computational cost, we have also implemented goal-oriented adaptive mesh refinement. The numerical tests indicated that if highly accurate modeling results were required, the high-order FEM in combination with the goal-oriented local mesh refinement required less computational time and DoFs than the lowest order adaptive FEM.

58 GEOSCIENCES↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2016

DRSPALL: Impact of the Modification of the Numerical Spallings Model on Waste Isolation Pilot Plant Performance Assessment.

The numerical code DRSPALL (from direct release spallings) is written to calculate the volume of Waste Isolation Pilot Plant (WIPP) solid waste subject to material failure and transport to the surface as a result of a hypothetical future inadvertent drilling intrusion. An error in the implementation of the DRSPALL finite difference equations was discovered as documented in Software Problem Report (SPR) 13-001. The modifications to DRSPALL to correct the finite difference equations are detailed, and verification and validation testing has been completed for the modified DRSPALL code. The complementary cumulative distribution function (CCDF) of spallings releases obtained using the modified DRSPALL is higher compared to that found in previous WIPP performance assessment (PA) calculations. Compared to previous PAs, there was an increase in the number of vectors that result in a nonzero spallings volume, which generally translates to an increase in spallings releases. The overall mean CCDFs for total releases using the modified DRSPALL are virtually unchanged, thus the modification to DRSPALL did not impact WIPP PA calculation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1989

Improving the low temperature ductility of NiAl

As part of a study aimed at developing a ductile NiAl-based alloy, ingots of Ni-Fe-Al alloys were cast and hot extruded to rods. The purpose of the iron additions was two-fold viz; to produce a change in the slip vector from 001 to 111 line and, in one alloy, to add a L1(2)-structured ductile second phase. Extruded Ni-20Al-30Fe was two-phase, containing a pro-eutectic B2 phase in a fine lamellar structure of B2+L1(2) phases. Room temperature tensile testing of both single extruded and double extruded alloys resulted in 8-percent and 22-percent plastic elongation and yield stresses of 850 and 760 MPa, respectively. Fracture in both cases occurred by ductile tearing of the eutectic and transgranular cleavage of the proeutectic phase at 1350 MPa. The ductility in double extruded condition is higher than that reported earlier in rapidly solidified wires by Inoue et al. (1984). By comparison, extruded single-phase B2-structured Ni-30Al-20Fe exhibited a fracture strength of 780 MPa, no plasticity, and a mixture of intergranular fracture and transgranular cleavage. This is contrast to earlier work by Inoue et al. where a yield stress of 400 MPa, 5 percent plastic strain, and a mixture of dimple and intergranular fracture was reported.

Guha, Sumit↗
NASA NTRS1992

Ultrasonic Dynamic Vector Stress Sensor

Stress inferred from measurements in specimens rather than in bonded gauges. Ultrasonic dynamic vector stress sensor (UDVSS) measures changes in dynamic directional stress occurring in material or structure at location touched by device when material or structure put under cyclic load. Includes phase-locked loop, synchronous amplifier, and contact probe. Useful among manufacturers of aerospace and automotive structures for stress testing and evaluation of designs.

Heyman, Joseph S.↗
NASA NTRS1993

Some practical turbulence modeling options for Reynolds-averaged full Navier-Stokes calculations of three-dimensional flows

New turbulence modeling options recently implemented for the 3D version of Proteus, a Reynolds-averaged compressible Navier-Stokes code, are described. The implemented turbulence models include: the Baldwin-Lomax algebraic model, the Baldwin-Barth one-equation model, the Chien k-epsilon model, and the Launder-Sharma k-epsilon model. Features of this turbulence modeling package include: well documented and easy to use turbulence modeling options, uniform integration of turbulence models from different classes, automatic initialization of turbulence variables for calculations using one- or two-equation turbulence models, multiple solid boundaries treatment, and fully vectorized L-U solver for one- and two-equation models. Good agreements are obtained between the computational results and experimental data. Sensitivity of the compressible turbulent solutions with the method of y(+) computation, the turbulent length scale correction, and some compressibility corrections are examined in detail. Test cases show that the highly optimized one- and two-equation turbulence models can be used in routine 3D Navier-Stokes computations with no significant increase in CPU time as compared with the Baldwin-Lomax algebraic model.

Bui, Trong T.↗
NASA NTRS1999

Improved Modeling in a Matlab-Based Navigation System

An innovative approach to autonomous navigation is available for low earth orbit satellites. The system is developed in Matlab and utilizes an Extended Kalman Filter (EKF) to estimate the attitude and trajectory based on spacecraft magnetometer and gyro data. Preliminary tests of the system with real spacecraft data from the Rossi X-Ray Timing Explorer Satellite (RXTE) indicate the existence of unmodeled errors in the magnetometer data. Incorporating into the EKF a statistical model that describes the colored component of the effective measurement of the magnetic field vector could improve the accuracy of the trajectory and attitude estimates and also improve the convergence time. This model is identified as a first order Markov process. With the addition of the model, the EKF attempts to identify the non-white components of the noise allowing for more accurate estimation of the original state vector, i.e. the orbital elements and the attitude. Working in Matlab allows for easy incorporation of new models into the EKF and the resulting navigation system is generic and can easily be applied to future missions resulting in an alternative in onboard or ground-based navigation.

Deutschmann, Julie↗
NASA NTRS2003

Finite Element Simulation of a Space Shuttle Solid Rocket Booster Aft Skirt Splashdown Using an Arbitrary Lagrangian-eulerian Approach

Explicit finite element techniques employing an Arbitrary Lagrangian-Eulerian (ALE) methodology, within the transient dynamic code LS-DYNA, are used to predict splashdown loads on a proposed replacement/upgrade of the hydrazine tanks on the thrust vector control system housed within the aft skirt of a Space Shuttle Solid Rocket Booster. Two preliminary studies are performed prior to the full aft skirt analysis: An analysis of the proposed tank impacting water without supporting aft skirt structure, and an analysis of space capsule water drop tests conducted at NASA's Langley Research Center. Results from the preliminary studies provide confidence that useful predictions can be made by applying the ALE methodology to a detailed analysis of a 26-degree section of the skirt with proposed tank attached. Results for all three studies are presented and compared to limited experimental data. The challenges of using the LS-DYNA ALE capability for this type of analysis are discussed.

Melis, Matthew E.↗
NASA NTRS2010

Performance Evaluation of the T6 Ion Engine

The T6 ion engine is a 22-cm diameter, 4.5-kW Kaufman-type ion thruster produced by QinetiQ, Ltd., and is baselined for the European Space Agency BepiColombo mission to Mercury and is being qualified under ESA sponsorship for the extended range AlphaBus communications satellite platform. The heritage of the T6 includes the T5 ion thruster now successfully operating on the ESA GOCE spacecraft. As a part of the T6 development program, an engineering model thruster was subjected to a suite of performance tests and plume diagnostics at the Jet Propulsion Laboratory. The engine was mounted on a thrust stand and operated over its nominal throttle range of 2.5 to 4.5 kW. In addition to the typical electrical and flow measurements, an E x B mass analyzer, scanning Faraday probe, thrust vector probe, and several near-field probes were utilized. Thrust, beam divergence, double ion content, and thrust vector movement were all measured at four separate throttle points. The engine performance agreed well with published data on this thruster. At full power the T6 produced 143 mN of thrust at a specific impulse of 4120 seconds and an efficiency of 64%; optimization of the neutralizer for lower flow rates increased the specific impulse to 4300 seconds and the efficiency to nearly 66%. Measured beam divergence was less than, and double ion content was greater than, the ring-cusp-design NSTAR thruster that has flown on NASA missions. The measured thrust vector offset depended slightly on throttle level and was found to increase with time as the thruster approached thermal equilibrium.

Snyder, John Steven↗
DOE OSTI2014

Indirect and direct signatures of Higgs portal decaying vector dark matter for positron excess in cosmic rays

We investigate the indirect signatures of the Higgs portal U(1){sub X} vector dark matter (VDM) X{sub μ} from both its pair annihilation and decay. The VDM is stable at renormalizable level by Z{sub 2} symmetry, and thermalized by Higgs-portal interactions. It can also decay by some nonrenormalizable operators with very long lifetime at cosmological time scale. If dim-6 operators for VDM decays are suppressed by 10{sup 16} GeV scale, the lifetime of VDM with mass ∼ 2 TeV is just right for explaining the positron excess in cosmic ray observed by PAMELA and AMS02 Collaborations. The VDM decaying into μ{sup +}μ{sup −} can fit the data, evading various constraints on cosmic rays. We give one UV-complete model as an example. This scenario for Higgs portal decaying VDM with mass around ∼ 2 TeV can be tested by DM direct search at XENON1T, and also at the future colliders by measuring the Higgs self-couplings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Multi-Mode Cavity Accelerator Structure

This project aimed to develop a prototype for a novel accelerator structure comprising coupled cavities that are tuned to support modes with harmonically-related eigenfrequencies, with the goal of reaching an acceleration gradient >200 MeV/m and a breakdown rate <10 -7 /pulse/meter. Phase I involved computations, design, and preliminary engineering of a prototype multi-harmonic cavity accelerator structure; plus tests of a bimodal cavity. A computational procedure was used to design an optimized profile for a bimodal cavity with high shunt impedance and low surface fields to maximize the reduction in temperature rise ΔT. This cavity supports the TM010 mode and its 2nd harmonic TM011 mode. Its fundamental frequency is at 12 GHz, to benchmark against the empirical criteria proposed within the worldwide High Gradient collaboration for X-band copper structures; namely, a surface electric field E sur max < 260 MV/m and pulsed surface heating ΔT max < 56 °K. With optimized geometry, amplitude and relative phase of the two modes, reductions are found in surface pulsed heating, modified Poynting vector, and total RF power—as compared with operation at the same acceleration gradient using only the fundamental mode.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

TEST OF THE HEMISPHERIC RULE OF MAGNETIC HELICITY IN THE SUN USING THE HELIOSEISMIC AND MAGNETIC IMAGER (HMI) DATA

Magnetic twist in solar active regions (ARs) has been found to have a hemispheric preference in sign (hemisphere rule): negative in the northern hemisphere and positive in the southern. The preference reported in previous studies ranges greatly, from ∼ 58% to 82%. In this study, we examine this hemispheric preference using vector magnetic field data taken by Helioseismic and Magnetic Imager and find that 75% ± 7% of 151 ARs studied obey the hemisphere rule, well within the preference range in previous studies. If the sample is divided into two groups—ARs having magnetic twist and writhe of the same sign and having opposite signs—the strength of the hemispheric preference differs substantially: 64% ± 11% for the former group and 87% ± 8% for the latter. This difference becomes even more significant in a sub-sample of 82 ARs having a simple bipole magnetic configuration: 56% ± 16% for the ARs having the same signs of twist and writhe, and 93% with lower and upper confidence bounds of 80% and 98% for the ARs having the opposite signs. The error reported here is a 95% confidence interval. This may suggest that, prior to emergence of magnetic tubes, either the sign of twist does not have a hemispheric preference or the twist is relatively weak.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

PythonFOAM: In-situ data analyses with OpenFOAM and Python

Here, we outline the development of a general-purpose Python-based data analysis tool for OpenFOAM. Our implementation relies on the construction of OpenFOAM applications that have bindings to data analysis libraries in Python. Double precision data in OpenFOAM is cast to a NumPy array using the NumPy C-API and Python modules may then be used for arbitrary data analysis and manipulation on flow-field information. We highlight how the proposed wrapper may be used for an in-situ online singular value decomposition (SVD) implemented in Python and accessed from the OpenFOAM solver PimpleFOAM. Here, 'in-situ' refers to a programming paradigm that allows for a concurrent computation of the data analysis on the same computational resources utilized for the partial differential equation solver. In addition, to demonstrate parallel deployments, we deploy a distributed SVD, which collects snapshot data across the ranks of a distributed simulation to compute the global left singular vectors. Crucially, both OpenFOAM and Python share the same message passing interface (MPI) communicator for this deployment which allows Python objects and functions to exchange NumPy arrays across ranks. Subsequently, we provide scaling assessments of this distributed SVD on multiple nodes of Intel Broadwell and KNL architectures for canonical test cases such as the large eddy simulations of a backward facing step and a channel flow at friction Reynolds number of 395. Finally, we demonstrate the deployment of a deep neural network for compressing the flow-field information using an autoencoder to demonstrate an ability to use state-of-the-art machine learning tools in the Python ecosystem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Machine-Learning Identification of the Sensing Descriptors Relevant in Molecular Interactions with Metal Nanoparticle-Decorated Nanotube Field-Effect Transistors

We report that carbon nanotube-based field-effect transistors (NTFETs) are ideal sensor devices as they provide rich information regarding carbon nanotube interactions with target analytes and have potential for miniaturization in diverse applications in medical, safety, environmental, and energy sectors. Herein, we investigate chemical detection with cross-sensitive NTFETs sensor arrays comprised of metal nanoparticle-decorated single-walled carbon nanotubes (SWCNTs). By combining analysis of NTFET device characteristics with supervised machine-learning algorithms, we have successfully discriminated among five selected purine compounds, adenine, guanine, xanthine, uric acid, and caffeine. Interactions of purine compounds with metal nanoparticle-decorated SWCNTs were corroborated by density functional theory calculations. Furthermore, by testing a variety of prepared as well as commercial solutions with and without caffeine, our approach accurately discerns the presence of caffeine in 95% of the samples with 48 features using a linear discriminant analysis and in 93.4% of the samples with only 11 features when using a support vector machine analysis. Lastly, we also performed recursive feature elimination and identified three NTFET parameters, transconductance, threshold voltage, and minimum conductance, as the most crucial features to analyte prediction accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A New High-Order Spectral Difference Method for Simulating Viscous Flows on Unstructured Grids with Mixed Elements

In the present study, a new spectral difference (SD) method is developed for viscous flows on meshes with a mixture of triangular and quadrilateral elements. The standard SD method for triangular elements, which employs Lagrangian interpolating functions for fluxes, is not stable when the designed accuracy of spatial discretization is third-order or higher. Unlike the standard SD method, the method examined here uses vector interpolating functions in the Raviart-Thomas (RT) spaces to construct continuous flux functions on reference elements. Studies have been performed for 2D wave equation and Euler equa- tions. Our present results demonstrated that the SDRT method is stable and high-order accurate for a number of test problems by using triangular-, quadrilateral-, and mixed- element meshes.

17 WIND ENERGY↗
NASA NTRS1984

Objective scatterometer wind ambiguity removal using smoothness and dynamical constraints

In the present investigation, a variational analysis method (VAM) is used to remove the ambiguity of the Seasat-A Satellite Scatterometer (SASS) winds. At each SASS data point, two, three, or four wind vectors (termed ambiguities) are retrieved. It is pointed out that the VAM is basically a least squares method for fitting data. The problem may be nonlinear. The best fit to the data and constraints is obtained on the basis of a minimization of the objective function. The VAM was tested and tuned at 12 h GMT Sept. 10, 1978. Attention is given to a case study involving an intense cyclone centered south of Japan at 138 deg E.

Hoffman, R. N.↗
NASA NTRS1986

Full potential methods for analysis/design of complex aerospace configurations

The steady form of the full potential equation, in conservative form, is employed to analyze and design a wide variety of complex aerodynamic shapes. The nonlinear method is based on the theory of characteristic signal propagation coupled with novel flux biasing concepts and body-fitted mapping procedures. The resulting codes are vectorized for the CRAY XMP and the VPS-32 supercomputers. Use of the full potential nonlinear theory is demonstrated for a single-point supersonic wing design and a multipoint design for transonic maneuver/supersonic cruise/maneuver conditions. Achievement of high aerodynamic efficiency through numerical design is verified by wind tunnel tests. Other studies reported include analyses of a canard/wing/nacelle fighter geometry.

Shankar, Vijaya↗
NASA NTRS1994

Improvements to TOVS retrievals over sea ice and applications to estimating Arctic energy fluxes

Modeling studies suggest that polar regions play a major role in modulating the Earth's climate and that they may be more sensitive than lower latitudes to climate change. Until recently, however, data from meteorological stations poleward of 70 degs have been sparse, and consequently, our understanding of air-sea-ice interaction processes is relatively poor. Satellite-borne sensors now offer a promising opportunity to observe polar regions and ultimately to improve parameterizations of energy transfer processes in climate models. This study focuses on the application of the TIROS-N operational vertical sounder (TOVS) to sea-ice-covered regions in the nonmelt season. TOVS radiances are processed with the improved initialization inversion ('3I') algorithm, providng estimates of layer-average temperature and moisture, cloud conditions, and surface characteristics at a horizontal resolution of approximately 100 km x 100 km. Although TOVS has flown continuously on polar-orbiting satellites since 1978, its potential has not been realized in high latitudes because the quality of retrievals is often significantly lower over sea ice and snow than over the surfaces. The recent availability of three Arctic data sets has provided an opportunity to validate TOVS retrievals: the first from the Coordinated Eastern Arctic Experiment (CEAREX) in winter 1988/1989, the second from the LeadEx field program in spring 1992, and the third from Russian drifting ice stations. Comparisons with these data reveal deficiencies in TOVS retrievals over sea ice during the cold season; e.g., ice surface temperature is often 5 to 15 K too warm, microwave emissivity is approximately 15% too low at large view angles, clear/cloudy scenes are sometimes misidentified, and low-level inversions are often not captured. In this study, methods to reduce these errors are investigated. Improvements to the ice surface temperature retrieval have reduced rms errors from approximately 7 K to 3 K; correction of microwaves (50 GHz) brightness temperatures for view angle dependence now allows the surface type (open water versus sea ice) to be determined; modifications to the clear/cloud tests have improved cloud detection over sea ice, especially where it is inhomogeneous; and improved surface temperature estimates have resulted in more successful diagnoses of low-level stratification. Applications of improved retrievals to studies of the Arctic energy budget are encouraging. Preliminary calculations of air-ice stress vectors, 10-m wind speed, and horizontal advection of heat and moisture are presented.

Francis, Jennifer A.↗