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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Risk-Based Probabilistic Approach to Aeropropulsion System Assessment

In an era of shrinking development budgets and resources, where there is also an emphasis on reducing the product development cycle, the role of system assessment, performed in the early stages of an engine development program, becomes very critical to the successful development of new aeropropulsion systems. A reliable system assessment not only helps to identify the best propulsion system concept among several candidates, it can also identify which technologies are worth pursuing. This is particularly important for advanced aeropropulsion technology development programs, which require an enormous amount of resources. In the current practice of deterministic, or point-design, approaches, the uncertainties of design variables are either unaccounted for or accounted for by safety factors. This could often result in an assessment with unknown and unquantifiable reliability. Consequently, it would fail to provide additional insight into the risks associated with the new technologies, which are often needed by decision makers to determine the feasibility and return-on-investment of a new aircraft engine. In this work, an alternative approach based on the probabilistic method was described for a comprehensive assessment of an aeropropulsion system. The statistical approach quantifies the design uncertainties inherent in a new aeropropulsion system and their influences on engine performance. Because of this, it enhances the reliability of a system assessment. A technical assessment of a wave-rotor-enhanced gas turbine engine was performed to demonstrate the methodology. The assessment used probability distributions to account for the uncertainties that occur in component efficiencies and flows and in mechanical design variables. The approach taken in this effort was to integrate the thermodynamic cycle analysis embedded in the computer code NEPP (NASA Engine Performance Program) and the engine weight analysis embedded in the computer code WATE (Weight Analysis of Turbine Engines) with the fast probability integration technique (FPI). FPI was developed by Southwest Research Institute under contract with the NASA Glenn Research Center. The results were plotted in the form of cumulative distribution functions and sensitivity analyses and were compared with results from the traditional deterministic approach. The comparison showed that the probabilistic approach provides a more realistic and systematic way to assess an aeropropulsion system. The current work addressed the application of the probabilistic approach to assess specific fuel consumption, engine thrust, and weight. Similarly, the approach can be used to assess other aspects of aeropropulsion system performance, such as cost, acoustic noise, and emissions. Additional information is included in the original extended abstract.

Tong, Michael T.↗
NASA NTRS2021

Development of a Computational Framework for the Design of Resilient Space Structures

Cyber-physical testing provides a unique platform to enable the design of resilient space structures. This hybrid approach requires the development of a structural model that accounts for various hazards (e.g., micrometeorite and debris impact) and interacts with physical tests and other sub-system models (e.g., thermal) of the space habitat. A two-dimensional finite element analysis code was developed in MATLAB to facilitate the evaluation of potential designs under operating and unexpected loads and prepare the computational framework for eventually performing cyber-physical testing. The code’s efficiency was enhanced by using an object-oriented programming approach that reduced data transfer between functions. In this study, the code is implemented to predict the response of a dome-style structure made of regolith concrete to impact loading and identify the force magnitude that will cause the tensile strength to be exceeded in domes with different thicknesses.

Tensile strength↗
DOE OSTI2018

Protection factors for French dwellings - 25573

IRSN's current method of assessment of public exposure from atmospheric releases of radioactivity from nuclear installations assumes an exposed person outside of any building; even though the majority of time is spent inside. A more realistic assessment would take into account the protection from atmospheric contamination and deposits provided by dwellings. Therefore, IRSN carried out a study to estimate protection factors for gamma ray emitting radionuclides. This was done with the MCNP calculation code and assumed several French dwelling types. Air contamination (outside and inside) and deposits on soil (outside and inside) and on a roof are considered. Method and results are set out for a few radionuclides. The results show the influence of dwelling type, and also of room sealing (considering inner contamination or not) in case of radiological emergency. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1994

Installed F/A-18 inlet flow calculations at 30 degrees angle-of-attack: A comparative study

NASA Lewis is currently engaged in a research effort as a team member of the High Alpha Technology Program (HATP) within NASA. This program utilizes a specially equipped F/A-18, the High Alpha Research Vehicle (HARV), in an ambitious effort to improve the maneuverability of high-performance military aircraft at low subsonic speed, high angle of attack conditions. The overall objective of the Lewis effort is to develop inlet technology that will ensure efficient airflow delivery to the engine during these maneuvers. One part of the Lewis approach utilizes computational fluid dynamics codes to predict the installed performance of inlets for these highly maneuverable aircraft. Full Navier-Stokes (FNS) calculations on the installed F/A-18 inlet at 30 degrees angle of attack, 0 degrees yaw, and a freestream Mach number of 0.2 have been obtained in this study using an algebraic turbulence model with two grids (original and revised). Results obtained with the original grid were used to determine where further grid refinements and additional geometry were needed. In order to account properly for the external effects, the forebody, leading edge extension (LEX), ramp, and wing were included with inlet geometry. In the original grid, the diverter, LEX slot, and leading edge flap were not included due to insufficient geometry definition, but were included in a revised grid. In addition, a thin-layer Navier-Stokes (TLNS) code is used with the revised grid and the numerical results are compared to those obtained with the FNS code. The TLNS code was used to evaluate the effects on the solution using a code with more recent CFD developments such as upwinding with TVD schemes versus central differencing with artificial dissipation. The calculations are compared to a limited amount of available experimental data. The predicted forebody/fuselage surface static pressures compared well with data of all solutions. The predicted trajectory of the vortex generated under the LEX was different for each solution. These discrepancies are attributed to differences in the grid resolution and turbulence modeling. All solutions predict that this vortex is ingested by the inlet. The predicted inlet total pressure recoveries are lower than data and the distortions are higher than data. The results obtained with the revised grid were significantly improved from the original grid results. The original grid results indicated the ingested vortex migrated to the engine face and caused additional distortions to those already present due to secondary flow development. The revised grid results indicate that the ingested vortex is dissipated along the inlet duct inboard wall. The TLNS results indicate the flow at the engine face was much more distorted than the FNS results and is attributed to the pole boundary condition introducing numerical distortions into the flow field.

Smith, C. Frederic↗
DOE OSTI2022

Energy deposition model in STREAM with photon transport

Recent efforts have been taken to implement a photon transport module for the neutron transport analysis code STREAM, considering the explicit photon energy distribution in the problem instead of using the locally deposition assumption as employed in previous STREAM versions. The current energy release model in STREAM based on the On-the-fly energy released per fission model is modified accordingly to account for the photon energy deposition computed explicitly by this module. The impacts of the modified energy release model with photon transport in STREAM on the power distribution, fuel temperature and other core parameters during depletion with feedback calculations are studied on several problems from the VERA benchmark suit. Overall, the photon transport provides a better power map for depletion and feedback calculations, especially when strong gamma emitters are present. The fuel temperature, in general, is decreased when the photon transport is employed because fission gammas have been transported out of their birthplace. The new energy deposition model in STREAM with photon transport indicates that gamma energy accounts for about 9.7% of the total energy released in a fresh VERA5 2D core and rises to 10.5% at the End of Cycle. Around 2.5% of the total energy released will be deposited in the coolant in this 2D core. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Graph-Based Prediction of Spatio-Temporal Vaccine Hesitancy From Insurance Claims Data

Growing vaccine hesitancy is contributing to the decline in immunization rates for highly contagious, vaccine-preventable childhood diseases. Therefore, there has been a significant interest in understanding how hesitancy is spreading at higher spatio-temporal resolutions, enabling more targeted interventions. Motivated by this, we study the problem of prediction of vaccine hesitancy at the ZIP Code level, referred to as the VaxHesitancy problem. A significant challenge for this problem is the lack of high-resolution data that indicates hesitancy. Here, we develop a hybrid VaxHesSTL framework that combines a Graph Neural Network (GNN) and a Recurrent Neural Network (RNN) to address the VaxHesitancy problem. The GNN uses a ZIP Code-level network to capture spatial signals from neighboring areas, while the RNN models the temporal dynamics present in the data. We train and evaluate VaxHesSTL using a large dataset, namely the All-Payer Claims Databases (APCD), for Virginia, consisting of insurance claims from over five million individuals for six years. We find that an aggregated contact network or graph, developed from a detailed activity-based population network, plays an important role in the performance of VaxHesSTL, compared to graph models based solely on spatial proximity. Experiments demonstrate that VaxHesSTL outperforms a range of state-of-the-art baselines, which rely solely on historical time series data without accounting for spatial relationships. Since hesitancy data at higher spatial resolution is often unavailable or hard to get, we incorporate an active learning approach with our VaxHesSTL framework to optimize the training set without compromising the prediction performance. We find that hesitancy data for only 18% of ZIP Codes selected by active learning allows us to forecast hesitancy for all the ZIP Codes in the Virginia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2025

Initial validation of ALFRED: A Monte Carlo code built on Geant4 for TREAT energy deposition

Predicting the energy deposited in the specimen during an experiment in the Transient Reactor Test (TREAT) Facility is a complex problem due to the nature of the transients occurring in the reactor. In addition, the many particles contributing to energy deposition have different behavior in time and space. ALFRED, a new Geant4 based code, is developed to transport and simulate each particle generated in the core. This code is verified against OpenMC (Open Monte Carlo) on the Godiva benchmark and a simple TREAT model. Next, the energy deposition in TREAT is calculated: 181.05 ± 0.01 MeV for the “instantaneous” energy deposition (which accounts for the energy deposited within 1 s after neutron emission) in fuel and 189.90 ± 0.01 MeV for the total energy deposition in fuel. We discuss these results in this paper with previous calculations and experimental evaluations. This work demonstrates ALFRED’s potential as a high-fidelity tool for computing the spatial and temporal energy deposition in TREAT paving the way for a better understanding of the energy coupling factors in TREAT.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Atmospheric neutrinos in next-generation xenon and argon dark matter experiments

In this work, we study the sensitivity of future xenon- and argon-based dark matter and neutrino detection experiments to low-energy atmospheric neutrinos. Not accounting for experimental backgrounds, the primary obstacle for identifying nuclear recoils induced by atmospheric neutrinos in xenon is the tail of the electron recoil distribution due to pp solar neutrinos. We use the NEST code to model the solar and atmospheric neutrino signals in a xenon detector and find that an exposure of 700 tonne-years will produce a 5σ detection of atmospheric neutrinos. We explore the effect of different detector properties and find that a sufficiently long electron lifetime is essential to the success of such a measurement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework

Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

An update on the use of the VLA for telemetry reception

An analysis is modified to incorporate the actual structure of the command signal system of the very large array (VLA). In particular, in addition to the 1-ms command signal there is a data invalid signal that is generated. The command signals are transmitted to the antennas during the period in which the data invalid signal is on. This means that the gaps in the received data are really 1.6 ms long rather than 1 ms long. Simulation results with this taken into account show that the VLA will not support (7, 1/2) convolutionally encoded telemetry at acceptable error rates at any of the Voyager telemetry data rates. VLA will support Voyager encounters provided that either concatenated coding is implemented, VLA is arrayed with another receiving site (such as Goldstone), or VLA is reconfigured so that the gaps are rotated.

Deutsch, L. J.↗
NASA NTRS1991

Martian regolith as space radiation shielding

Mars exploration crews will be exposed to such high radiation dosages in route from earth that as to sharply reduce the allowable dose they should receive while on the Martian surface. An account is presently given of the possibility of using Martian regolith as crew shielding to maintain very low short-term dose limits. NASA-Langley's nucleon and heavy-ion transport computer codes are used to predict the propagation and interaction of the free-space nucleons and heavy ions through the Martian atmosphere and then through various thicknesses of regolith. The largest reduction in dose occurs in the first 15-20 cm of regolith material.

Simonsen, L. C.↗
DOE OSTI2023

Charging location selection of an incoming electric vehicle for large EV depot infrastructure

As the use of renewable energy resources increases within charging infrastructures, the risk that charging an additional load within the charging infrastructure will create a violation of the applicable grid code also increases. In an embodiment, a charging location is selected for an incoming load based on a load flow analysis, to thereby mitigate the risk of a violation. This selection process may also account for the charging schedule of the load and the capacity of available charging stations (e.g., fast charging vs. slow charging).

Hafiz, Faeza↗
NASA NTRSDate not supplied

Development of Physics-Based Transition Models for Unstructured-Mesh CFD Codes Using Deep Learning Models

Predicting transition locations over a vehicle surface is of fundamental importance for many engineering applications. With the transition information, the Reynolds-averaged Navier-Stokes (RANS) computations can turn on the turbulence model at the right locations so that drag, lift and other aerodynamic quantities can be accurately predicted. In contrast to the popularity of RANS-based transition modeling in which transition onset is governed by the turbulence equations, physics-based transition models that account for instability waves within the boundary layer, thus more compliant to flow physics, only gained more attention in recent years. This paper describes the development of a new physics-based transition model based on either the linear stability theory (LST) or parabolized stability equations (PSE). The model is designed to communicate with a structured or unstructured-mesh RANS solver back and forth in order to more accurately compute transition fronts over a three-dimensional body. In the developed model, the Python suite of interface codes in conjunction with the LASTRAC software can be executed autonomously to produce transition onset locations for a given laminar or RANS-computed transitional state. In addition, as a proof of concept, the tool set consists of a deep learning neural network model that has been designed and trained to predict instability wave evolutions inside the boundary layer for various instability wave mechanisms across a selected speed range. A machine-learned intelligent profile interpolation model has also been devised to enable reliable instability-wave spectra predictions with just a few points in the mean flow profiles.

Transition Modeling↗
DOE OSTI2022

A correction procedure for self-induced velocity of a finite-sized particle in two-way coupled Euler–Lagrange simulations

The importance of incorporating a correction to undo the self-induced perturbation velocity of a particle, when its size becomes comparable to the Eulerian grid, in a two-way coupled Euler–Lagrange (EL) simulation is now well appreciated. The present work improves upon the prior correction procedures in a few important ways. First, the past correction procedures have been scalar-based with the assumption that the quasi-steady force is the source of self-induced velocity perturbation. Here we generalize to a vector correction procedure and thereby the directions of feedback force and relative velocity can be different. This allows the correction procedure to be used even in the presence of added-mass, history, and lift forces. Second, the effect of a nearby wall has been systematically included in the correction procedure. The correction procedure depends on fundamental Oseen solutions of streamwise and transverse regularized feedback forces. We present a Fourier transform-based analytical approach to obtaining these regularized Oseen solutions. We also present a step-by-step numerical procedure for obtaining the Oseen solutions in any EL code. With the analytical or numerical Oseen functions, the correction procedure can be easily implemented in any EL code. Iterations are required in solving the implicit correction equations and it is demonstrated that the correction procedure converges rapidly within three or four iterations. In conclusion, a simple empirical approach is also presented to account for unsteady effects in the correction procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Nebulin and titin modulate cross-bridge cycling and length-dependent calcium sensitivity

Various mutations in the structural proteins nebulin and titin that are present in human disease are known to affect the contractility of striated muscle. Loss of nebulin is associated with reduced actin filament length and impairment of myosin binding to actin, whereas titin is thought to regulate muscle passive elasticity and is likely involved in length-dependent activation. Here, we sought to assess the modulation of muscle function by these sarcomeric proteins by using the computational platform muscle simulation code (MUSICO) to quantitatively separate the effects of structural changes, kinetics of cross-bridge cycling, and calcium sensitivity of the thin filaments. The simulations show that variation in thin filament length cannot by itself account for experimental observations of the contractility in nebulin-deficient muscle, but instead must be accompanied by a decreased myosin binding rate. Additionally, to match the observed calcium sensitivity, the rate of TnI detachment from actin needed to be increased. Simulations for cardiac muscle provided quantitative estimates of the effects of different titin-based passive elasticities on muscle force and activation in response to changes in sarcomere length and interfilament lattice spacing. Predicted force–pCa relations showed a decrease in both active tension and sensitivity to calcium with a decrease in passive tension and sarcomere length. We conclude that this behavior is caused by partial redistribution of the muscle load between active muscle force and titin-dependent passive force, and also by redistribution of stretch along the thin filament, which together modulate the release of TnI from actin. These data help advance understanding of how nebulin and titin mutations affect muscle function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The role of edge resonant magnetic perturbations in edge-localized-mode suppression and density pump-out in low-collisionality DIII-D plasmas

Two-fluid nonlinear MHD simulations using the TM1 code demonstrate that the formation of magnetic islands at the top and bottom of the H-mode pedestal, together with the strong screening of resonant fields in the gradient region of the pedestal, can account for ELM suppression and density pump-out by n = 2 resonant magnetic perturbations (RMPs) in low-collisionality DIII-D ITER similar shape (ISS) plasmas. Using experimentally relevant transport coefficients, neoclassical resistivity, electron collisionality, and RMP amplitudes, nonlinear MHD simulations reproduce the observed level of density reduction (density pump-out) in DIII-D due to the formation of narrow magnetic islands in the resistive foot of pedestal. For large amplitude RMPs ( B r / B t > 1 × 10 -4 ) simulations predict resonant field penetration and resulting in pressure reduction at the top of the pedestal, consistent with experimental observations at the onset of ELM suppression. The predicted reduction in the height and width of the pedestal by magnetic island enhanced collisional transport provides a quantitative mechanism for the stabilization of the peeling-ballooning mode (PBM). Importantly, these simulations predict strong screening of resonant fields in the steep gradient region of the pedestal due to strong E × B rotation and diamagnetic flows. Yet, if the plasma resistivity is made artificially larger (~ 10X) than neoclassical, the simulations predict magnetic stochasticity throughout the plasma edge and the collapse of the pedestal due to the reduction in the penetration threshold with increasing resistivity. A scaling relation for resonant field penetration at the pedestal top, using several hundred nonlinear simulations, reproduces the density and E × B rotation dependence of the ELM suppression threshold observed in DIII-D. Simulations using ITER model equilibria indicate that the penetration threshold at the top of the ITER pedestal will be lower than in DIII-D due to the anticipated lower perpendicular flow velocities in ITER, resulting in the weaker screening of resonant fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Solid-to-plasma transition of polystyrene induced by a nanosecond laser pulse within the context of inertial confinement fusion

Laser Direct Drive (LDD) Inertial Confinement Fusion (ICF) involves irradiating a spherical target of thermonuclear fuel coated with an ablator, usually made of polystyrene. Laser energy absorption near the target surface leads to matter ablation, hydrodynamic shocks, and ultimately capsule implosion. The conservation of spherical symmetry is crucial for implosion efficiency, yet spatial modulations in laser intensity can induce nonuniformities, causing the laser imprint phenomenon. Understanding laser imprint, especially considering the initial solid state, is essential for advancing LDD ICF. A first microscopic model of solid-to-plasma transition was built in 2019, accounting for laser absorption in the solid state with a band structure based ionization model. This model has been improved to include chemical fragmentation and a more accurate description of electron collision frequency in various matter states. The latest development involves assessing the model reliability by comparing theoretical predictions with experimental observations. Despite the success of this approach, questions remain, leading to further investigations and observations under different irradiation conditions. This work presents an experiment with a nanosecond pulse, taking into account hydrodynamic effects, and measures transmission dynamics over the entire laser beam area to observe two-dimensional effects. As a result, the objective is to adapt the theoretical model, couple it with a hydrodynamic code, and observe additional effects related to the initial solid state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗