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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Effect of Passive Horizontal Rotations and Vertical Oscillations on Dynamic Visual Acuity

Astronauts experience sensorimotor disturbances after long duration space flight. These crewmembers may need to egress the vehicle within a few minutes for safety and operational reasons in various sea state conditions following a water landing. Exposure to even low frequency motions induced by sea conditions surrounding a vessel can cause significant fine and gross motor control problems affecting critical functions. The objective of this study was to document human motor and visual performance during simulated wave motion in the 0.1 to 2.0 Hz range. We examined in 12 healthy subjects the changes in accuracy when performing a seated visual target acquisition task in which the location of target was offset vertically during horizontal full body rotation at an oscillating frequency of 0.8 Hz (peak velocity of 160 deg/s). The main finding was that the accuracy of performance degraded in 7 of 12 subjects when acquiring vertical targets at perturbing frequencies of 0.8 Hz in the horizontal plane by one step size. We also examined in a separate study on 12 healthy subjects seated dynamic visual acuity (DVA) task performance during vertical full body oscillations at perturbing frequencies of 2 Hz (peak to peak motion of 5 cm). The main finding was that DVA was significantly reduced when acquiring targets at perturbing oscillations at frequencies of 2 Hz in the vertical plane by approximately 1 chart line. Thus low frequencies of perturbations in the horizontal and vertical planes can cause decrement in visual performance.

Mulavara, Ajitkumar↗
DOE OSTI2020

Real Time Effective Impedance Estimation for Power System State Estimation

Here, we introduce two tools-the Effective Impedance State Estimator (EISE), and the Real Time Effective Impedance Estimator (RTEIE). The EISE is novel in that it is an entirely data-driven state estimator, and does not require a network model. Thus, the EISE is well suited for applications in which an accurate network model is not available. Instead of using a network impedance model, the EISE uses an effective impedance network model that is learned online by the RTEIE. The RTEIE recursively estimates the effective impedance network model using phasor measurement unit (PMU) measurements. The mathematical reasoning for using an effective impedance model, rather than a full network impedance model, is given. The recursive estimation framework allows the RTEIE to take the entire history of phasor measurements into account to produce a model estimate, while still adjusting to changes in the network impedance due to external factors such as topology changes and temperature. The merits of the RTEIE and EISE are demonstrated by comparing the accuracy of the EISE with a conventional state estimator on a toy network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1986

Prospects for an orbital determination and capture cell experiment

A dust experiment which combines measurements of the elemental and isotopic composition of individual particles with orbital information would contribute fundamental, new scientific information on the sources contributing to the micrometeoroid population. The general boundary conditions for such a system are: (1) it must be capable of measuring velocities in the range of 10 km/sec to 100 km/sec with several percent accuracy; (2) it must collect particles in such a way that the debris atoms are locally concentrated so that precise isotopic measurements are possible; (3) it should collect particles over a wide range of sizes starting with a lower limit of 10 microns; (4) it should incorporate materials that will not compromise the isotopic measurements; and (5) it should be large enough to obtain statistically meaningful results within a reasonable exposure time. Techniques which may satisfy these conditions are described.

Carey, W. C.↗
NASA NTRS1990

ULTRA-SHARP nonoscillatory convection schemes for high-speed steady multidimensional flow

For convection-dominated flows, classical second-order methods are notoriously oscillatory and often unstable. For this reason, many computational fluid dynamicists have adopted various forms of (inherently stable) first-order upwinding over the past few decades. Although it is now well known that first-order convection schemes suffer from serious inaccuracies attributable to artificial viscosity or numerical diffusion under high convection conditions, these methods continue to enjoy widespread popularity for numerical heat transfer calculations, apparently due to a perceived lack of viable high accuracy alternatives. But alternatives are available. For example, nonoscillatory methods used in gasdynamics, including currently popular TVD schemes, can be easily adapted to multidimensional incompressible flow and convective transport. This, in itself, would be a major advance for numerical convective heat transfer, for example. But, as is shown, second-order TVD schemes form only a small, overly restrictive, subclass of a much more universal, and extremely simple, nonoscillatory flux-limiting strategy which can be applied to convection schemes of arbitrarily high order accuracy, while requiring only a simple tridiagonal ADI line-solver, as used in the majority of general purpose iterative codes for incompressible flow and numerical heat transfer. The new universal limiter and associated solution procedures form the so-called ULTRA-SHARP alternative for high resolution nonoscillatory multidimensional steady state high speed convective modelling.

Leonard, B. P.↗
DOE OSTI2022

Code Verification and Solution Verification framework in pin-resolved neutron transport code MPACT

Program verification in scientific computing encompasses the application of formal and mathematical techniques to a scientific computing code for its credibility, accuracy, and validity. Code Verification identifies bugs and performance issues in the software development stage. Solution Verification assesses the applicability of the code and the accuracy of the solution to problems of interest. Both activities utilize application cases and quantify the error against prescribed acceptance criteria. However, simply executing more application cases does not guarantee stronger or more comprehensive credibility. Here, we establish a verification framework that involves Code Verification and Solution Verification, both of which work together such that the overarching goal of “converge to the correct answer for the intended application” can be reasonably inferred. The application of such a verification framework is demonstrated using the pin-resolved neutron transport code MPACT, where standard unit tests and regression tests are covered, and where the Method of Exact Solutions and the Method of Manufactured Solutions are successfully used. Additionally, the applicability of Method of Manufactured Solutions is extended to the OECD/NEA C5G7 benchmark problems of practical material and geometric configurations. Solution Verification activities are demonstrated on a practical hierarchy of application models of increasing complexity ranging from 2D pin cell problems to 3D assembly problems. The convergence behavior and rate of convergence with respect to each individual variable are studied and provided. This framework can be adapted broadly to other fields involving scientific computing codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development of Explainable Data-Driven Turbulence Models with Application to Liquid Fuel Nuclear Reactors

Liquid fuel nuclear reactors offer innovative possibilities in terms of nuclear reactor designs and passive safety systems. Molten Salts Reactors (MSRs) with a fast spectrum are a particular type of these reactors using liquid fuel. MSFRs often involve large open cavities in their core in which the liquid fuel circulates at a high speed to transport the heat generated by the nuclear reactions into the heat exchangers. This high-speed flow yields a turbulent field with large Reynolds numbers in the reactor core. Since the nuclear power, the neutron precursor’s transport and the thermal exchanges are strongly coupled in the MSFR’s core cavity, having accurate turbulent models for the liquid fuel flow is necessary to avoid introducing significant errors in the numerical simulations of these reactors. Nonetheless, high-accuracy simulations of the turbulent flow field in the reactor cavity of these reactors are usually prohibitively expensive in terms of computational resources, especially when performing multiphysics numerical calculations. Therefore, in this work, we propose a novel method using a modified genetic algorithm to optimize the calculation of the Reynolds Shear Stress Tensor (RST) used for turbulence modeling. The proposed optimization methodology is particularly suitable for advanced liquid fuel reactors such as the MSFRs since it allows the development of high-accuracy but still low-computational-cost turbulence models for the liquid fuel. We demonstrate the applicability of this approach by developing high accuracy Reynolds-Averaged Navier–Stokes (RANS) models (averaged flow error less than 5%) for a low and a large aspect ratio in a Backward-Facing Step (BFS) section particularly challenging for RANS models. The newly developed turbulence models better capture the flow field after the boundary layer tipping, over the extent of the recirculation bubble, and near the boundary layer reattachment region in both BFS configurations. The main reason for these improvements is that the developed models better capture the flow field turbulent anisotropy in the bulk region of the BFS. Then, we illustrate the interest in using this turbulence modeling approach for the case of an MSFR by quantifying the impact of the turbulence modeling on the reactor key parameters.

42 ENGINEERING↗
NASA NTRS1982

Radiation damage

The radiation damage workshop considered a variety of topics among which were the need for equivalent electron fluences in gallium arsenide, the possibility of 15 percent end-of-life efficiencies for silicon, increasing radiation resistance in gallium arsenide, annealing of radiation damage and the need for radiation damage studies in cascade cells. The workshop members agreed that a high priority should be assigned to obtaining equivalent electron fluences for gallium arsenide cells. It was suggested that 1 MeV would be a reasonable electron energy for this purpose. Special care should be given to proton irradiations particularly for energies below 1 MeV. In addition, omnidirectional rather than normal incidence protons should be used. It was also agreed that there was a need for obtaining damage coefficients in gallium arsenide. In silicon, there is a requirement for additional flight data, especially in proton dominated orbits. These data are needed to further check the accuracy of the 1 MeV equivalence fluences.

Weinberg, I.↗
NASA NTRS2001

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Shishir, Pandya↗
NASA NTRS2014

ULSGEN (Uplink Summary Generator)

Uplink is an important part of spacecraft operations. Ensuring the accuracy of uplink content is essential to mission success. Before commands are radiated to the spacecraft, the command and sequence must be reviewed and verified by various teams. In most cases, this process requires collecting the command data, reviewing the data during a command conference meeting, and providing physical signatures by designated members of various teams to signify approval of the data. If commands or sequences are disapproved for some reason, the whole process must be restarted. Recording data and decision history is important for traceability reasons. Given that many steps and people are involved in this process, an easily accessible software tool for managing the process is vital to reducing human error which could result in uplinking incorrect data to the spacecraft. An uplink summary generator called ULSGEN was developed to assist this uplink content approval process. ULSGEN generates a web-based summary of uplink file content and provides an online review process. Spacecraft operations personnel view this summary as a final check before actual radiation of the uplink data. .

Wang, Y.-F.↗
DOE OSTI2026

Applying corrective machine learning in the E3SM atmosphere model in C++ (EAMxx)

The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of earth system models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous computing architectures. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years to a few decades, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3GFS earth system model, this study explores the effects of implementing corrective-ML in EAMxx-SCREAM. We also address the computational challenges of integrating our implementation of corrective-ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as potential reasons why this approach has not proved as effective for EAMxx-SCREAM as for FV3GFS.

Environmental sciences↗
NASA NTRS1972

Current Sheet Magnetic Model for the Solar Corona

A new magnetic model is developed and compared with previous models and the observed solar corona. An attempt is made to more accurately compute the three-dimensional currents flowing in the solar corona. Physical reasons are given that require most of the large scale currents flowing in the solar corona to lie near thin sheets. The current sheets are not constrained into any particular geometry or symmetry as in the previous models of Altschuler and Newkirk (1969) and Schatten et al. (1969). A comparison with the axisymmetric, isothermal MHD solution of Pneuman and Kopp (1970) suggests that the model is able to simulate to high accuracy an isothermal corona. A comparison of the model with the May 30, 1965, solar eclipse and the November 12, 1966, solar eclipse shows the model is capable of computing many features including the polar plume orientations as well as radial and nonradial streamers in the solar corona.

Schatten, K. H.↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗
NASA NTRS1998

GCM Simulations of Cirrus Clouds and Cloud Feedbacks

Cirrus clouds are a particularly uncertain component of general circulation model (GCM simulations of long-term climate change for a variety of reasons: (1) They encompass a wide range of optical thicknesses and altitudes, from thin tropopause cirrus to thick anvil cirrus that descend to the freezing level, and thus can exert both positive and negative forcing and feedback on the climate; (2) The dynamical processes that create them are poorly resolved in climate GCMs and different in the tropics and midlatitudes; (3) Predictions of their formation and microphysical properties depend on the accuracy of dynamical transports of small concentrations of water vapor to and within the upper troposphere; (4) The relative humidity conditions at which they form depends on the nature and concentration of nucleating particles and is poorly understood; (5) They are more difficult to observe than other cloud types, and hence their parameterization is more loosely constrained by available data. We will illustrate the potential sensitivity of the perturbed climate to uncertainties in cirrus cloud formulation. We will also examine the processes that form cirrus in climate models and discuss the accuracy with which climate GCMs represent these processes. We will also discuss ways in which GCM grid-scale parameterizations might be derived from cloud-scale observations. Finally, we will emphasize the types of global observations needed to constrain parameterizations of cirrus in climate GCMs.

DelGenio, Anthony D.↗
NASA NTRS1995

Scan patterns and accuracy of a Radar Wind Sensor (RAWS)

The Radar Wind Sensor (RAWS) was proposed as a complement to laser wind sensors, allowing coverage in cloudy regions excluded from laser coverage. Previous University of Kansas studies showed the feasibility of the wind measurement at various levels in the atmosphere and indicated that RAWS can also measure rain rates and ocean-surface winds. Here we discuss measurement of the wind vector in terms of the scan patterns for a conically scanned antenna. By using many measurements from cells about 66 km square and 132 km square, a least-squares algorithm gives results that are reasonable for insertion into global atmospheric models. For RAWS to be used successfully as a complement to a laser wind sensor, the design of the two sensors should be integrated and radial velocity measurements in a given atmospheric cell should be combined to get the most accurate results.

Song, Shuxian↗
NASA NTRS1993

Solar flux forecasting using mutual information with an optimal delay

Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.

Ashrafi, S.↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗
DOE OSTI2020

Global error analysis of the Chebyshev rational approximation method

The Chebyshev rational approximation method (CRAM) has become a widely adopted method for solving nuclear depletion problems. Therefore, understanding CRAM’s accuracy is important for the safe operation of nuclear power plants. This article performs a global error analysis of CRAM and finds that, as the length of the time step approaches zero, the relative error measured between the exact and CRAM solutions at a fixed end time approaches one and infinity for even and odd orders, respectively; for intermediate time step sizes, a minimum in relative error is observed. Finally, we show that the reason for CRAM’s behavior is that the method is inconsistent. Two best practices for using CRAM, derived from these results, are: (1) use CRAM order 16 or higher, (2) if necessary, increase the CRAM order when multiphysics coupling requires smaller time steps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Spin-free formulation of the multireference driven similarity renormalization group: A benchmark study of first-row diatomic molecules and spin-crossover energetics

We report a spin-free formulation of the multireference (MR) driven similarity renormalization group (DSRG) based on the ensemble normal ordering of Mukherjee and Kutzelnigg (1997). This ensemble averages over all microstates of a given total spin quantum number, and therefore, it is invariant with respect to SU(2) transformations. As such, all equations may be reformulated in terms of spin-free quantities and they closely resemble those of spin-adapted closed-shell coupled cluster (CC) theory. The current implementation is used to assess the accuracy of various truncated MR-DSRG methods (perturbation theory up to third order and iterative methods with single and double excitations) in computing the constants of 33 first-row diatomic molecules. The accuracy trends for these first-row diatomics are consistent with our previous benchmark on a small subset of closed-shell diatomic molecules. We then present the first MR-DSRG application on transition-metal complexes by computing the spin splittings of the [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ molecules. A focal point analysis (FPA) shows that third-order perturbative corrections are essential to achieve reasonably converged energetics. The FPA based on the linearized MR-DSRG theory with one- and two-body operators and up to a quintuple- ζ basis set predicts the spin splittings of [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ to be –35.7 and –17.1 kcal mol –1 , respectively, showing good agreement with the results of local CC theory with singles, doubles, and perturbative triples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗