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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

An evaluative model of system performance in manned teleoperational systems

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Haines, Richard F.↗
NASA NTRS1990

Radial evolution of solar wind thermal electron distributions due to expansion and collisions

ISEE 3 electron observations near 1 AU show that the solar wind thermal electron temperature anisotropy, T(parallel)/T(perpendicular), is typically 1.0 to 1.5, with densest distributions most nearly isotropic, but is sometimes much higher when density is low. For a small observational subset characterized by high density and low bulk speed, T(perpendicular) can exceed T(parallel). Based on these and other observations, a simple model is proposed for radial evolution of thermal electrons in a structureless solar wind under the influence of Coulomb collisions and geometric expansion in a spiral interplanetary magnetic field. The model, which satisfactorily explains the 1 AU observations, shows that the evolution of electron temperature and T(parallel)/T(perpendicular) is controlled by plasma density, flow speed, and initial temperature, with density the most important factor. The model makes predictions for radial distances other than 1 AU and for high solar latitudes.

Phillips, J. L.↗
NASA NTRS1992

A reinforcement learning-based architecture for fuzzy logic control

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Berenji, Hamid R.↗
NASA NTRS1999

A System for Integrated Reliability and Safety Analyses

We present an integrated reliability and aviation safety analysis tool. The reliability models for selected infrastructure components of the air traffic control system are described. The results of this model are used to evaluate the likelihood of seeing outcomes predicted by simulations with failures injected. We discuss the design of the simulation model, and the user interface to the integrated toolset.

Kostiuk, Peter↗
NASA NTRS1997

Comparison of OARE Accelerometer Data with Dopant Distribution in Se-Doped GaAs Crystals Grown During USML-1

Experiments were conducted in the crystal growth furnace (CGF) during the first United States Microgravity Laboratory (USML-1), the STS-50 flight of the Space Shuttle Columbia, to determine the segregation behavior of selenium in bulk GaAs in a microgravity environment. After the flight, the selenium-doped GaAs crystals were sectioned, polished, and analyzed to determine the free carrier concentration as a function of position, One of the two crystals initially exhibited an axial concentration profile indicative of diffusion controlled growth, but this profile then changed to that predicted for a complete mixing type growth. An analytical model, proposed by Naumann [R.J. Naumann, J. Crystal Growth 142 (1994) 253], was utilized to predict the maximum allowable microgravity disturbances transverse to the growth direction during the two different translation rates used for each of the experiments. The predicted allowable acceleration levels were 4.86 microgram for the 2.5 micrometers/s furnace translation rate and 38.9 microgram for the 5.0 micrometers/s rate. These predicted values were compared to the Orbital Acceleration Research Experiment (OARE) accelerometer data recorded during the crystal growth periods for these experiments. Based on the analysis of the OARE acceleration data and utilizing the predictions from the analytical model, it is concluded that the change in segregation behavior was not caused by any acceleration events in the microgravity environment.

Moskowitz, Milton E.↗
NASA NTRS2000

Polydiacetylene Films Prepared in Microgravity

A diffusive/kinetic rate equation was developed for the growth of polydiacetylene films from solution and compared with a microgravity experiment. The model takes into account both the kinetics of thin film growth and the diffusive transport limitations inherent to microgravity. In order to apply this model, measurements of the density and the ultraviolet extinction coefficient of the films, as well as of the diffusion coefficient of the monomer/solvent system, were made. The thin films grown in microgravity were predicted by the model to grow to a thickness of 0.148 micron, versus 0.150 micron for the ground control films. The flight films grew to 0.102 micron.

Carswell, William E.↗
NASA NTRS2001

A Global Optimization Methodology for Rocket Propulsion Applications

While the response surface method is an effective method in engineering optimization, its accuracy is often affected by the use of limited amount of data points for model construction. In this chapter, the issues related to the accuracy of the RS approximations and possible ways of improving the RS model using appropriate treatments, including the iteratively re-weighted least square (IRLS) technique and the radial-basis neural networks, are investigated. A main interest is to identify ways to offer added capabilities for the RS method to be able to at least selectively improve the accuracy in regions of importance. An example is to target the high efficiency region of a fluid machinery design space so that the predictive power of the RS can be maximized when it matters most. Analytical models based on polynomials, with controlled level of noise, are used to assess the performance of these techniques.

Source record↗
NASA NTRS1999

Third and Final Shuttle Mission of the Isothermal Dendritic Growth Experiment Conducted: Highest Supercooling Ever Recorded Achieved

Dendrites describe the treelike crystal morphology commonly assumed in metals and alloys that freeze from supercooled or supersaturated melts. There remains a high level of engineering interest in dendritic solidification because the size, shape, and orientation of the dendrites determine the final microstructure of a material. It is the microstructure that then determines the physical properties of cast or welded products. Although it is well known that dendritic growth is controlled by the transport of latent heat from the moving solid-liquid interface, an accurate and predictive model has not yet been developed. The effects of gravity-induced convection on the transfer of heat from the interface have prevented adequate testing, under terrestrial conditions, of solidification models. The Isothermal Dendritic Growth Experiment (IDGE) constituted a series of three microgravity experiments flown aboard the Space Shuttle Columbia. The apparatus was used to grow and record dendrite solidification in the absence of gravity-induced convective heat transfer, thereby producing a wealth of benchmark-quality data for testing solidification models and theories.

Glicksman, Martin E.↗
NASA NTRS2013

Influence of Persistent Wind Scour on the Surface Mass Balance of Antarctica

Accurate quantification of surface snow accumulation over Antarctica is a key constraint for estimates of the Antarctic mass balance, as well as climatic interpretations of ice-core records. Over Antarctica, near-surface winds accelerate down relatively steep surface slopes, eroding and sublimating the snow. This wind scour results in numerous localized regions (< or = 200 sq km) with reduced surface accumulation. Estimates of Antarctic surface mass balance rely on sparse point measurements or coarse atmospheric models that do not capture these local processes, and overestimate the net mass input in wind-scour zones. Here we combine airborne radar observations of unconformable stratigraphic layers with lidar-derived surface roughness measurements to identify extensive wind-scour zones over Dome A, in the interior of East Antarctica. The scour zones are persistent because they are controlled by bedrock topography. On the basis of our Dome A observations, we develop an empirical model to predict wind-scour zones across the Antarctic continent and find that these zones are predominantly located in East Antarctica. We estimate that approx. 2.7-6.6% of the surface area of Antarctica has persistent negative net accumulation due to wind scour, which suggests that, across the continent, the snow mass input is overestimated by 11-36.5 Gt /yr in present surface-mass-balance calculations.

Antarctica↗
NASA NTRS2017

A Computational Fluid Dynamics Study of Swirling Flow Reduction by Using Anti-Vortex Baffle

OBJECTIVES: To evaluate proposed anti-vortex design in suppressing swirling flow during US burn. APPROACH: Include two major body forces in the analysis a)Vehicle acceleration (all three components); b)Vehicle maneuvers (roll, pitch, and yaw). Perform two drainage analyses of Ares I LOX tank using 6 DOF body forces predicted by GN&C analysis (Guidance Navigation and Control) during vehicle ascent: one with baffle, one without baffle. MODEL: Use Ares I defined geometry. O-Grid for easy fitting of baffle. In this preliminary analysis the holes are sealed. Use whole 360 deg. model with no assumption of symmetry or cyclic boundary conditions. Read in 6DOF data vs time from a file.

Yang, H. Q.↗
NASA NTRS1982

Analytical prediction of the interior noise for cylindrical models of aircraft fuselages for prescribed exterior noise fields. Phase 2: Models for sidewall trim, stiffened structures and cabin acoustics with floor partition

An airplane interior noise prediction model is developed to determine the important parameters associated with sound transmission into the interiors of airplanes, and to identify apropriate noise control methods. Models for stiffened structures, and cabin acoustics with floor partition are developed. Validation studies are undertaken using three test articles: a ring stringer stiffened cylinder, an unstiffened cylinder with floor partition, and ring stringer stiffened cylinder with floor partition and sidewall trim. The noise reductions of the three test articles are computed using the heoretical models and compared to measured values. A statistical analysis of the comparison data indicates that there is no bias in the predictions although a substantial random error exists so that a discrepancy of more than five or six dB can be expected for about one out of three predictions.

Pope, L. D.↗
DOE OSTI2026

Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On-Line Prediction of Resistant Force During Soil–Tool Interaction

For off-road vehicles such as excavators and wheel loaders, a large portion of energy is consumed to overcome the soil resistant force in the digging process. For optimal control of the digging tool, a high-fidelity model of the soil–tool interaction force is important to reduce energy consumption. Here, in this paper, an on-line soil resistant force prediction method is proposed. In this method, a hybrid model, which combines a physical model and a data-driven model, is used for the force prediction. In addition, the parameters of the hybrid model can be updated on-line based on real-time data. Comparisons with experimental data demonstrate that the proposed prediction method has an average error of around 12.7%.

42 ENGINEERING↗
DOE OSTI2023

A localized ensemble of approximate Gaussian processes for fast sequential emulation

More attention has been given to the computational cost associated with the fitting of an emulator. Substantially less attention is given to the computational cost of using that emulator for prediction. This is primarily because the cost of fitting an emulator is usually far greater than that of obtaining a single prediction, and predictions can often be obtained in parallel. In many settings, especially those requiring Markov Chain Monte Carlo, predictions may arrive sequentially and parallelization is not possible. In this case, using an emulator procedure which can produce accurate predictions efficiently can lead to substantial time savings in practice. In this paper, we propose a global model approximate Gaussian process framework via extension of a popular local approximate Gaussian process (laGP) framework. Our proposed emulator can be viewed as a treed Gaussian process where the leaf nodes are laGP models, and the tree structure is learned greedily as a function of the prediction stream. The suggested method (called leapGP) has interpretable tuning parameters which control the time‐memory trade‐off. One reasonable choice of settings leads to an emulator with a training cost and makes predictions rapidly with an asymptotic amortized cost of .

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Forecasting disease risk for increased epidemic preparedness in public health

Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.

Disease Outbreaks↗
NASA NTRS1995

Langley's CSI evolutionary model: Phase 2

Phase 2 testbed is part of a sequence of laboratory models, developed at NASA Langley Research Center, to enhance our understanding on how to model, control, and design structures for space applications. A key problem with structures that must perform in space is the appearance of unwanted vibrations during operations. Instruments, design independently by different scientists, must share the same vehicle causing them to interact with each other. Once in space, these problems are difficult to correct and therefore, prediction via analysis design, and experiments is very important. Phase 2 laboratory model and its predecessors are designed to fill a gap between theory and practice and to aid in understanding important aspects in modeling, sensor and actuator technology, ground testing techniques, and control design issues. This document provides detailed information on the truss structure and its main components, control computer architecture, and structural models generated along with corresponding experimental results.

Horta, Lucas G.↗
DOE OSTI2020

Network-cognizant voltage droop control

The present disclosure provides techniques for network-cognizant droop control in power systems, such as a power distribution system. An example device includes a processor configured to determine, based on (i) a model representing a structure of a power system that includes a plurality of energy resources and (ii) an indication of predicted uncontrollable power injections in the power system, for each controllable energy resource in the plurality of energy resources, a respective value of a first droop coefficient and a respective value of a second droop coefficient. The processor may be further configured to cause at least one controllable energy resource in the plurality of energy resources to modify an output power of the at least one energy resource based on the respective value of the first droop coefficient and the respective value of the second droop coefficient.

24 POWER TRANSMISSION AND DISTRIBUTION↗