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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Separation of Hydrogen Using Pd/Ag Membranes: Experimental and Modeling Results with Potential Application to Direct Internal Recycle

Implementation of fusion energy requires processing the deuterium-tritium (D-T) mixture used to fuel the reaction, and separation of hydrogen isotopes from other gases is imperative. Specifically, the separation of hydrogen isotopes from helium is a matter of importance to the fusion fuel cycle community. Initial testing with a palladium-silver (Pd-Ag) membrane indicates that even moderate vacuum (~100 torr permeate pressure) can provide a high degree of separation (>90%) at a high ratio of H 2 to He. Given the presence of He in many fusion systems, a high technology readiness level (TRL) for Q 2 /He (where Q represents any isotope of hydrogen) separations is needed. This study demonstrates the efficacy of H 2 removal from He via permeation and potential applications for direct internal recycle. Modeling will accompany the experimental campaign to generate a predictive capability and quantify the separation performance. Modeling from previous hydrogen permeation studies has demonstrated that the typical Sieverts’ law fails to predict the measured permeation rates at high hydrogen fluxes. Existing models are being refined to integrate the effects of surface phenomena into permeation predictions, which have been expanded to account for mixtures with large ranges of Q 2 concentrations. These data will improve the TRL of permeators as a separation technology for the fusion fuel cycle.

08 HYDROGEN↗
DOE OSTI2020

WRF Modelling of Deep Convection and Hail for Wind Power Applications

Deep convection and the related occurrence of hail, intense precipitation and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the United States Southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modelling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates and precipitation totals show good agreement with observations. Here, the occurrence of precipitation during power producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modelled with a mean proportion correct of 0.77 and an odds ratio 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry and there is evidence for positive model bias in cloud reflectivity.

17 WIND ENERGY↗
DOE OSTI2024

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Knowledge Distillation for Anomaly Detection

Unsupervised deep learning techniques are widely used to identify anomalous behaviour. The performance of such methods is a product of the amount of training data and the model size. However, the size is often a limiting factor for the deployment on resource-constrained devices. Here, we present a novel procedure based on knowledge distillation for compressing an unsupervised anomaly detection model into a supervised deployable one and we suggest a set of techniques to improve the detection sensitivity. Compressed models perform comparably to their larger counterparts while significantly reducing the size and memory footprint.

Pol, Adrian Alan↗
DOE OSTI2023

Flash Diffusivity Measurement of Semi-Porous Insulation Material Intended for Radioisotope Thermoelectric Generators

This research involves the analysis of flash-heating data pursuant to find the thermal diffusivity of a semi-porous insulation material (Min-K) that is being considered for use in a radioisotope thermoelectric generator (RTG). An RTG uses radioactive nuclear fuel to produce electricity through a temperature difference imposed on a bimetallic thermocouple. Insulation is required to protect sensitive equipment from high temperatures and to conserve heat in the fuel. Using flash diffusivity temperature data, various simulations were fitted in order to find the most appropriate heat transfer model for the experiments. Four models were allowed to compete and the standard deviation of the residuals were compared for each model in evaluating model performance. The residuals are simply the difference in temperatures between the measurements and the mathematical models at each measurement point.

McMasters, Robert L.↗
DOE OSTI2026

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
NASA NTRS1979

Progress on Variable Cycle Engines

Progress in the development and future requirements of the Variable Stream Control Engine (VSCE) are presented. The two most critical components of this advanced system for future supersonic transports, the high performance duct burner for thrust augmentation, and the low jet coannular nozzle were studied. Nozzle model tests substantiated the jet noise benefit associated with the unique velocity profile possible with a coannular nozzle system on a VSCE. Additional nozzle model performance tests have established high thrust efficiency levels only at takeoff and supersonic cruise for this nozzle system. An experimental program involving both isolated component and complete engine tests has been conducted for the high performance, low emissions duct burner with good results and large scale testing of these two components is being conducted using a F100 engine as the testbed for simulating the VSCE. Future work includes application of computer programs for supersonic flow fields to coannular nozzle geometries, further experimental testing with the duct burner segment rig, and the use of the Variable Cycle Engine (VCE) Testbed Program for evaluating the VSCE duct burner and coannular nozzle technologies.

Westmoreland, J. S.↗
NASA NTRS1985

Separated transonic airfoil flow calculations with a nonequilibrium turbulence model

Navier-Stokes transonic airfoil calculations based on a recently developed nonequilibrium, turbulence closure model are presented for a supercritical airfoil section at transonic cruise conditions and for a conventional airfoil section at shock-induced stall conditions. Comparisons with experimental data are presented which show that this nonequilibrium closure model performs significantly better than the popular Baldwin-Lomax and Cebeci-Smith equilibrium algebraic models when there is boundary-layer separation that results from the inviscid-viscous interactions.

King, L. S.↗
NASA NTRS1987

Relations between two-point correlations and pressure strain terms

The structure of the two-point spatial correlations (velocity-velocity, velocity-scalar, and scalar-scalar) were studied with a view to improve turbulence closure models. The linear model for the two-point correlations proposed by Naot provides a method of including the information about the turbulence structure in the turbulence models. The assumptions and adequacy of this model were tested against the homogeneous shear flow simulation data base. The model performs poorly in some details and it is suggested how it may be improved. The models were also tested for rapid pressure-strain terms in a variety of flows including axisymmetric expansion and contraction flows, homogeneous shear flow, channel flow, and boundary layer.

Wolfshtein, Micha↗
NASA NTRS1990

Modeling of near-wall turbulence

An improved k-epsilon model and a second order closure model is presented for low Reynolds number turbulence near a wall. For the k-epsilon model, a modified form of the eddy viscosity having correct asymptotic near wall behavior is suggested, and a model for the pressure diffusion term in the turbulent kinetic energy equation is proposed. For the second order closure model, the existing models are modified for the Reynolds stress equations to have proper near wall behavior. A dissipation rate equation for the turbulent kinetic energy is also reformulated. The proposed models satisfy realizability and will not produce unphysical behavior. Fully developed channel flows are used for model testing. The calculations are compared with direct numerical simulations. It is shown that the present models, both the k-epsilon model and the second order closure model, perform well in predicting the behavior of the near wall turbulence. Significant improvements over previous models are obtained.

Shih, T. H.↗
NASA NTRS1999

Estimated Benefits of Variable-Geometry Wing Camber Control for Transport Aircraft

Analytical benefits of variable-camber capability on subsonic transport aircraft are explored. Using aerodynamic performance models, including drag as a function of deflection angle for control surfaces of interest, optimal performance benefits of variable camber are calculated. Results demonstrate that if all wing trailing-edge surfaces are available for optimization, drag can be significantly reduced at most points within the flight envelope. The optimization approach developed and illustrated for flight uses variable camber for optimization of aerodynamic efficiency (maximizing the lift-to-drag ratio). Most transport aircraft have significant latent capability in this area. Wing camber control that can affect performance optimization for transport aircraft includes symmetric use of ailerons and flaps. In this paper, drag characteristics for aileron and flap deflections are computed based on analytical and wind-tunnel data. All calculations based on predictions for the subject aircraft and the optimal surface deflection are obtained by simple interpolation for given conditions. An algorithm is also presented for computation of optimal surface deflection for given conditions. Benefits of variable camber for a transport configuration using a simple trailing-edge control surface system can approach more than 10 percent, especially for nonstandard flight conditions. In the cruise regime, the benefit is 1-3 percent.

Bolonkin, Alexander↗
NASA NTRS2004

Local Scale Radiobrightness Modelling during Intensive Observing Period-4 of the Cold Land Processes Experiment-1

The NASA Cold Land Processes Field Experiment (CLPX-1) was designed to provide microwave remote sensing observations and ground truth for studies of snow and frozen ground remote sensing, particularly issues related to scaling. CLPX-1 was conducted in the spring of 2003 in Colorado, USA. Initial forward model validation work is concentrating on the Local-Scale Observation Site (LSOS), a 0.8 ha study site consisting of open meadows separated by trees where the most detailed measurements were made of snow depth and temperature, density, and grain size profiles. This paper will focus on the ability of forward Dense Medium Radiative Transfer (DMRT) modelling, combined with snowpack measurements to reproduce the radiobrightness signatures observed by the University of Michigan s Truck-Mounted Radiometer System at 19 and 37 GHz during the 4th Intensive Observing Period (IOP4) in March, 2003. Unlike the earlier IOP3, conditions during IOP4 include both wet and dry periods, providing a valuable test of DMRT model performance. Observations of upwelling and downwelling tree radiobrightness will be used to formulate a simple model for the effect of trees within the field of view. In addition, a comparison will be made for the one day of coincident observations by the University of Tokyo s Ground- Based Microwave Radiometer-7 (GBMR-7). These analyses will help guide the choice of future snow retrieval algorithms and the design of future Cold Lands observing systems.

Kim, Edward J.↗
NASA NTRS2009

Transitioning Models and Model Output to Space Weather Operations: Challenges and Opportunities

The transition of space weather models or of information derived from space weather models to space weather forecasting is the last step of the chain from model development to model deployment in forecasting operations. As such, it is an extremely important element of the quest to increase our national capability to forecast and mitigate space weather hazards. It involves establishing customer requirements, and analyses of available models, which are, in principle, capable of delivering the required product. Models will have to be verified and validated prior to a selection of the best performing model. Further considerations include operational hardware, and the availability of data streams to drive the model. The final steps include the education of forecasters, and the implementation on gateway hardware prior to operational use. This presentation will provide a discussion of opportunities for rapid progress from the viewpoint of the Community Coordinated Modeling Center.

Hesse, Michael↗
DOE OSTI2024

Thermal Management of Wide-Bandgap Semiconductor Amplifiers Used for Plasma Heating and Control

Princeton Fusion Systems (PFS) has designed, built, and tested a Load Switch printed circuit board (PCB) to demonstrate the capabilities of 2 kV silicon carbide (SiC) cascodes in development by Qorvo towards plasma heating and control applications. Initial tests have been conducted at low power (~100 W) for validation with thermal finite element analysis (FEA) modeling performed by the National Renewable Energy Laboratory (NREL). Comparisons of experimental data with the thermal modeling results, along with considerations for operating in plasma systems, will be discussed.

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗
NASA NTRS1979

Millimeter wave satellite concepts. Volume 1: Executive summary

The objectives of the program were: (1) development of methodology based on the technical requirements of potential services that might be assigned to millimeter wave bands for identifying the viable and appropriate technologies for future NASA millimeter research and development programs, and (2) testing of this methodology with user applications and services. The scope of the program included the entire communications network, both ground and space subsystems. The reports include: (1) cost, weight, and performance models for the subsystems, (2) conceptual design for point-to-point and broadcast communications satellites, (3) analytic relationships between subsystem parameters and an overall link performance, (4) baseline conceptual systems, (5) sensitivity studies, (6) model adjustment analyses, (7) identification of critical technologies and their risks, (8) brief R&D program scenarios for the technologies judged to be moderate or extensive risks.

Hilsen, N. B.↗
NASA NTRS1977

Millimeter wave satellite concepts, volume 1

The identification of technologies necessary for development of millimeter spectrum communication satellites was examined from a system point of view. Development of methodology based on the technical requirements of potential services that might be assigned to millimeter wave bands for identifying the viable and appropriate technologies for future NASA millimeter research and development programs, and testing of this methodology with selected user applications and services were the goals of the program. The entire communications network, both ground and space subsystems was studied. Cost, weight, and performance models for the subsystems, conceptual design for point-to-point and broadcast communications satellites, and analytic relationships between subsystem parameters and an overall link performance are discussed along with baseline conceptual systems, sensitivity studies, model adjustment analyses, identification of critical technologies and their risks, and brief research and development program scenarios for the technologies judged to be moderate or extensive risks. Identification of technologies for millimeter satellite communication systems, and assessment of the relative risks of these technologies, was accomplished through subsystem modeling and link optimization for both point-to-point and broadcast applications.

Hilsen, N. B.↗