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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 1,063 records · Page 59

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NASA NTRS1992

Beyond the cockpit: The visual world as a flight instrument

The use of cockpit instruments to guide flight control is not always an option (e.g., low level rotorcraft flight). Under such circumstances the pilot must use out-the-window information for control and navigation. Thus it is important to determine the basis of visually guided flight for several reasons: (1) to guide the design and construction of the visual displays used in training simulators; (2) to allow modeling of visibility restrictions brought about by weather, cockpit constraints, or distortions introduced by sensor systems; and (3) to aid in the development of displays that augment the cockpit window scene and are compatible with the pilot's visual extraction of information from the visual scene. The authors are actively pursuing these questions. We have on-going studies using both low-cost, lower fidelity flight simulators, and state-of-the-art helicopter simulation research facilities. Research results will be presented on: (1) the important visual scene information used in altitude and speed control; (2) the utility of monocular, stereo, and hyperstereo cues for the control of flight; (3) perceptual effects due to the differences between normal unaided daylight vision, and that made available by various night vision devices (e.g., light intensifying goggles and infra-red sensor displays); and (4) the utility of advanced contact displays in which instrument information is made part of the visual scene, as on a 'scene linked' head-up display (e.g., displaying altimeter information on a virtual billboard located on the ground).

Johnson, W. W.↗

NASA NTRS2017

Finding the Needles in the Haystacks: High-Fidelity Models of the Modern and Archean Solar System for Simulating Exoplanet Observations

We present two state-of-the-art models of the solar system, one corresponding to the present day and one to the Archean Eon 3.5 billion years ago. Each model contains spatial and spectral information for the star, the planets, and the interplanetary dust, extending to 50 au from the Sun and covering the wavelength range 0.3-2.5 micron. In addition, we created a spectral image cube representative of the astronomical backgrounds that will be seen behind deep observations of extrasolar planetary systems, including galaxies and Milky Way stars. These models are intended as inputs to high-fidelity simulations of direct observations of exoplanetary systems using telescopes equipped with high-contrast capability. They will help improve the realism of observation and instrument parameters that are required inputs to statistical observatory yield calculations, as well as guide development of post-processing algorithms for telescopes capable of directly imaging Earth-like planets.

extrasolar planetary systems↗

NASA NTRS1999

Improving the Unsteady Aerodynamic Performance of Transonic Turbines using Neural Networks

A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The procedure yielded a modified design that improves the aerodynamic performance through small changes to the reference design geometry. These results demonstrate the capabilities of the neural net-based design procedure, and also show the advantages of including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.

Rai, Man Mohan↗

NASA NTRSDate not supplied

A Computational Study of Plume Modeling For Space Launch System Abort Scenarios

This extended abstract details work on Space Launch System (SLS) core stage drag during abort scenarios that is currently being conducted. In the final paper, viscous computational fluid dynamic simulations will be used to study the axial force coefficient on the SLS core stage as a function of its distance to the upstream crew module and launch abort system, the freestream conditions, and the chemical model used to represent the launch abort system abort motor and attitude control motor plumes. In addition, the computational expense of each method will be studied in order to help determine the appropriate trade-off between fidelity and simulation turn around time.

CFD↗

DOE OSTI2022

Observability of fidelity decay at the Lyapunov rate in few-qubit quantum simulations

In certain regimes, the fidelity of quantum states will decay at a rate set by the classical Lyapunov exponent. This serves both as one of the most important examples of the quantum-classical correspondence principle and as an accurate test for the presence of chaos. While detecting this phenomenon is one of the first useful calculations that noisy quantum computers without error correction can perform, a thorough study of the quantum sawtooth map reveals that observing the Lyapunov regime is just beyond the reach of present-day devices. We prove that there are three bounds on the ability of any device to observe the Lyapunov regime and give the first quantitatively accurate description of these bounds: (1) the Fermi golden rule decay rate must be larger than the Lyapunov rate, (2) the quantum dynamics must be diffusive rather than localized, and (3) the initial decay rate must be slow enough for Lyapunov decay to be observable. This last bound, which has not been recognized previously, places a limit on the maximum amount of noise that can be tolerated. The theory implies that an absolute minimum of 6 qubits is required. Recent experiments on IBM-Q and IonQ imply that some combination of a noise reduction by up to 100x per gate and large increases in connectivity and gate parallelization are also necessary. Finally, scaling arguments are given that quantify the ability of future devices to observe the Lyapunov regime based on trade-offs between hardware architecture and performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗

NASA NTRS2014

Intercomparison and Evaluation of Global Aerosol Microphysical Properties Among Aerocom Models of a Range of Complexity

Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multimodel- mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation an growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.

Cloud physics↗

NASA NTRS1998

Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Performance

A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology (RSM) and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The optimization procedure yields a modified design that improves the aerodynamic performance through small changes to the reference design geometry. The computed results demonstrate the capabilities of the neural net-based design procedure, and also show the tremendous advantages that can be gained by including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.

Madavan, Nateri K.↗

DOE OSTI2026

Modeling Flow in a Microreactor Core: From High-Fidelity CFD to Subchannel Analysis

The accurate prediction of pressure drop in tightly packed, low–Reynolds number (Re) bare rod bundles is essential for the thermal-hydraulic design of the Microreactor Applications Research Validation and EvaLuation (MARVEL) reactor and other microreactor concepts. However, existing friction factor correlations, particularly the upgraded Cheng-Todreas (UCTD) correlation, have limited validation for the small pitch-to-diameter ratios (P/Ds) and transitional flow conditions characteristic of these systems. In this work, we perform high-fidelity large-eddy simulations (LESs) of both an infinite bare rod bundle and a finite bare 37-pin scalloped rod bundle across the range 1000≤ 𝑅𝑒 ≤5500. The simulations reveal strong gap vortex–driven transitional behavior and indicate that the UCTD may underpredict the friction factor by up to 28% at 𝑃/𝐷 = 1.05. Using the LES-calculated pressure drops, we formulate a new friction factor correlation that follows the Cheng-Todreas functional form but is calibrated for low-Re and tightly packed geometries representative of a MARVEL-like reactor. The correlation is implemented in the MOOSE (Multiphysics Object-Oriented Simulation Environment) subchannel module and compared against both the LES and UCTD predictions. Across all subchannel types, the proposed model reduces the streamwise velocity differences from as high as 44% (UCTD) to below 9%, and decreases the pressure gradient differences from 13% to 25% (UCTD) to 0.7% to 7% relative to the LES results. These results suggest that the new correlation has the potential to improve the pressure drop and flow field predictions for such geometries, highlighting the importance of high-fidelity simulations in supporting microreactor thermal-hydraulic model development and motivating future pressure drop experiments for compact rod bundles to further validate these findings.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2017

Evaluation of different inertial control methods for variable-speed wind turbines simulated by fatigue, aerodynamic, structures and turbulence (FAST)

To mitigate the degraded power system inertia and undesirable primary frequency response caused by large-scale wind power integration, the frequency support capabilities of variable-speed wind turbines is studied in this work. This is made possible by controlled inertial response, which is demonstrated on a research turbine - controls advanced research turbine, 3-bladed (CART3). Two distinct inertial control (IC) methods are analysed in terms of their impacts on the grids and the response of the turbine itself. The released kinetic energy in the IC methods are determined by the frequency measurement or shaped active power reference in the turbine speed-power plane. The wind turbine model is based on the high-fidelity turbine simulator fatigue, aerodynamic, structures and turbulence, which constitutes the aggregated wind power plant model with the simplified power converter model. The IC methods are implemented over the baseline CART3 controller, evaluated in the modified 9-bus and 14-bus testing power grids considering different wind speeds and different wind power penetration levels. The simulation results provide various insights on designing such kinds of ICs. The authors calculate the short-term dynamic equivalent loads and give a discussion about the turbine structural loadings related to the inertial response.

17 WIND ENERGY↗

NASA NTRS1963

Integrated Mission Simulation for Long Term Space Flight

The problems of evaluating pilot performance, pilot training, and the integration of the man-machine system for proper functioning become increasingly difficult as the length of projected space flights increases. Further, actual in-flight experience becomes harder to obtain and the major means for training and evaluation becomes simulation. The first major source of difficulty in any simulation stems from a basic requirement of leaning theory: that for increased proficiency of performance to occur within any biologically capable system, the stimuli which are the bases for the expected behavior must be presented in an amenable form to the learner. Further, the sequence of presentation of the pertinent stimuli must be such that the learner can form the appropriate concepts and interactions required for the ultimate use of the learned material. It can then be seen that two basic factors of learning complex skills are: 1) Fidelity of simulation of pertinent stimuli. 2) Appropriate sequencing of stimuli during learning for proper concept formation.

SPACE FLIGHT↗

DOE OSTI2019

Application of deep artificial neural networks to multi-dimensional flamelet libraries and spray flames

The “curse of dimensionality” has limited the applicability and expansion of tabulated combustion models. While the tabulated flamelet model and other multi-dimensional manifold approaches have shown predictive capability, the associated tabulation involves the storage of large lookup tables, requiring large memory as well as multi-dimensional interpolation subroutines, all implemented during runtime. As such, this work investigates the use of deep artificial neural networks to replace lookup tables in order to reduce the memory footprint and increase the computational speed of tabulated flamelets and related approaches. Specifically, different strategic approaches to training the artificial neural network models are explored and a grouped multi-target artificial neural network is introduced, which takes advantage of the ability of artificial neural networks to map an input space to multiple targets by classifying the species based on their correlation to one another. The grouped multi-target artificial neural network approach is validated by applying it to an n-dodecane spray flame using conditions of the Spray A flame from the Engine Combustion Network and comparing global flame characteristics for different ambient conditions using a well-established large-eddy simulation framework. The same framework is then extended to the simulations of methyl decanoate combustion in a compression ignition engine. The validation studies show that the grouped multi-target artificial neural networks are able to accurately capture flame liftoff, autoignition, two-stage heat release and other quantitative trends over a range of conditions. The use of neural networks in conjunction with the grouping mechanism as performed in the grouped multi-target artificial neural network produces a significant reduction in the memory footprint and computational costs for the code and, thus, widens the operating envelope for higher fidelity engine simulations with detailed mechanisms.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1983

Man-vehicle systems research facility: Design and operating characteristics

The Man-Vehicle Systems Research Facility (MVSRF) provides the capability of simulating aircraft (two with full crews), en route and terminal air traffic control and aircrew interactions, and advanced cockpit (1995) display representative of future generations of aircraft, all within the full mission context. The characteristics of this facility derive from research, addressing critical human factors issues that pertain to: (1) information requirements for the utilization and integration of advanced electronic display systems, (2) the interaction and distribution of responsibilities between aircrews and ground controllers, and (3) the automation of aircrew functions. This research has emphasized the need for high fidelity in simulations and for the capability to conduct full mission simulations of relevant aircraft operations. This report briefly describes the MVSRF design and operating characteristics.

Source record↗

DOE OSTI2022

Computational Fluid Dynamics Simulations to Predict Oxidation in Heat Recovery Steam Generator Tubes

Heat Recovery Steam Generators (HRSGs) are widely used across United States in combined cycle power plants to recover waste heat from the gas turbine (GT). HRSGs are used either to generate electricity or to produce process steam for industrial applications. The primary components of HRSG consists of a duct and a heat exchanger (HX). It is known across the power industry that the high temperature oxidation and ensuing exfoliation problem is a major cause for the damage of HX materials of HRSG. Alloys and/or coatings that can prevent or mitigate oxidation are very expensive, therefore they must be used or applied on the select regions of the HX tubes where the tendency of oxide formation is the highest. The main goal of this project is to identify such regions through Computational Fluid Dynamics (CFD) simulations. Therefore, in this work, we developed a CFD framework using commercial code StarCCM+ for the prediction of the fluid flow and heat transfer in a HRSG and associated oxidation inside the tubes of the HX. The developed CFD framework was verified and validated with experimental data before deployment. We also developed an innovative method to model the effect of the fins on the heat transfer and the pressure drop using a porous media model (PMM) approach to keep the mesh size within reasonable limits. After validation, we performed high-fidelity CFD simulations of a real-scale HRSG using the PMM, with High Performance Computing (HPC) resources of ORNL. From the simulation results, we acquired oxide thickness maps for all the tubes of the select HX sections of HRSG prone to oxidation. These oxide maps can inform regions of the HX tubes that requires oxide-resistant coatings, thereby guiding engineers for cost-efficient manufacturing of the HX that can combat oxidation in HRSGs.

36 MATERIALS SCIENCE↗

NASA NTRS2014

Kinematic Modeling of Separation Compression for Paired Approaches to Closely-Spaced Parallel Runways

In a simultaneous paired approach to closely-spaced parallel runways, a pair of aircraft flies in close proximity on parallel approach paths. The longitudinal separation between the aircraft must be maintained within a range that avoids wake encounters and, if one of the aircraft blunders, avoids collision. To increase operational availability, the approach procedure must accommodate a mixture of aircraft sizes and, consequently, approach speeds. In these procedures, the slower aircraft is placed in the lead position. The faster aircraft maintains separation from the slow aircraft in a dependent operation until final approach and flies independently afterward. Due to the higher approach speed of the fast aircraft, longitudinal separation will decrease during final approach. Therefore, the fast aircraft must position itself before the final approach so that it will remain within the safe range of separation as separation decreases. Given the approach geometry and speed schedule for each aircraft, one can use kinematics to estimate the separation loss between a pair of aircraft. A kinematic model can complement fast-time Monte-Carlo simulations of the approach by enabling a tailored reduction in the variation of starting position for the fast aircraft. One could also implement the kinematic model in ground-based or on-board decision support tools to compute the optimal initial separation for a given pair of aircraft. To better match the auto-coupled flight of real aircraft, the paper derives a kinematic model where the speed schedule is flown using equivalent airspeed. The predicted time of flight using the equivalent airspeed kinematic model compares well against a high-fidelity aircraft simulation performing the same approach. This model also demonstrates a modest increase in the predicted loss of separation when contrasted against a kinematic model that assumes the scheduled speed is true airspeed.

Madden, Michael M.↗

DOE OSTI2025

FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment (Final Report)

This report documents the FY25 Theory and Simulation Performance Target (TSPT) of developing an integrated modeling framework for fusion reactor design and assessment (FREDA). Over Q1-Q4, new capabilities were developed across both plasma and engineering domains and demonstrated on an example representation of a Compact Advanced Tokamak with a Dual Cooled Lead Lithium blanket. This represents a first-of-a-kind demonstration of coupled core-to-wall-to-engineering for a reactor. Self-consistent CESOL workflows were applied to provide core, pedestal, and SOL prediction; new modules were developed for energetic particle stability (FAR3D) and transport (TGLF-EP) analysis; and boundary plasma modeling (SOLPS-ITER, BOUT++/Hermes-3) was expanded to evaluate wall and divertor heat fluxes and interface with engineering thermal analysis. A parameterized CAD tool, TRACER, was expanded to generate medium-fidelity divertor, blanket, and coil geometries; OpenFOAM and Diablo workflows were applied for first-wall and divertor thermal analyses with helium cooling; and reduced-order models were created for high-mass-flux divertor cooling. Magnet multiphysics capabilities were verified between Elmer, Diablo, and a new MFEM-based solver, and workflows enable stress, thermal, and neutron-fluence analysis of TF coils with neutronics-driven heating. Nuclear and blanket analysis workflows were demonstrated, including tritium breeding, transport, and CFD-informed thermo-mechanical assessment. Preliminary multi-fidelity uncertainty quantification workflows were applied to boundary modeling codes and shown to achieve variance reductions with fewer high-fidelity boundary simulations. Key findings highlight the challenges of resolving the ITEP gap to find suitable balance between wall and divertor loads, neutron heating, and practical limits of PFC cooling. Next step priorities are to develop automated workflows to check boundary code convergence and detachment, implement tighter physics-engineering CAD provenance tracking, and inclusion of plasma-material interface models for SLAG and tungsten cracking behavior. Collectively, these developments establish sophisticated capabilities for predictive, multi-fidelity, whole-device modeling that integrates plasma physics, materials, magnets, and nuclear engineering to guide pathways to viable Fusion Pilot Plant design points.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

NASA NTRS2009

Survey and Method for Determination of Trajectory Predictor Requirements

A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

Rentas, Tamika L.↗