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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Space Shuttle Environmental Effects: The First 5 Flights

Environmental effects associated with the first five Space Shuttle flights were monitored by the National Aeronautics and Space Administration (NASA) and the U.S. Air Force (USAF). Results and interpretations from this effort were reported at the December 1982 joint NASA-USAF conference. The conference proceedings are presented in this document. Most of the monitoring activity was focused on the launch cloud, emphasizing surface effects on the biota and air quality, model prediction of surface concentrations of HCl gas and Al2O3 dust, and airborne measurements of cloud composition. In general, assessments and predictions made in the April 1978 Final Environmental Impact Statement for the Space Shuttle Program were verified. Fallout of acidic mist and dust within 3 mi to 5 mi of the launch pad was the only unexpected effect of the launch. Atomization of deluge water in the Shuttle exhaust is considered to be the most probable cause of this effect. Sonic booms were monitored for several landings at Edwards Air Force Base, California; results agreed well with model predictions.

Potter, A.↗
DOE OSTI2025

Data Placement Optimization for ATLAS in a Multi-Tiered Storage System within a Data Center

Scientific experiments and computations, especially in High Energy Physics, are generating and accumulating data at an unprecedented rate. Effectively managing this vast volume of data while ensuring efficient data analysis poses a significant challenge for data centers, which must integrate various storage technologies. This paper proposes addressing this challenge by designing and developing a precise data popularity prediction model utilizing state-of-theart AI/ML techniques. This model is crafted from the analysis of ATLAS data and access patterns. It enables us to migrate infrequently accessed data to more economical storage media, such as tape drives, while storing frequently accessed data on faster yet costlier storage media like HDD or SSD. This strategic approach ensures data is placed optimally into the appropriate storage classes, thereby maximizing storage capacity while minimizing data access latency for end-users. Furthermore, the paper includes a performance evaluation of the prediction model using various key metrics such as F1 score, accuracy, precision and recall. Finally, we present a prototype use case, leveraging real-world file access data to assess the model’s impact on performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Elastic Changepoint Detection for Globally-indexed Functional Time Series Data with Climate Applications

Changepoint detection is a vital tool in the application of climate data analysis. Numerous types of climate observation data are most properly represented by functional time series, implying a need for accurate changepoint detection methods applicable to functional time series data. Such data taken at a global scale often contain both spatial heterogeneity and dependence as well as phase (time) misalignment. In this report, we present methods which can detect spatially-dependent changepoints while allowing different estimates of change time and change strength depending on location. Additionally, we provide extensions to this spatially-predicted model which controls for phase variability among observations. Our methods provide the ability to detect a single change, or control for epidemic changes (where a “return-to-normal” change is more likely to be detected than the initial change). We showcase results analyzing the June 1991 eruption of Mt. Pinatubo, where our methods demonstrate the ability to accurately detect both single and epidemic changepoints even in the presence of strong seasonal variability. We find that our spatially-predicted model improves the detection of relevant changepoints versus methods which do not take spatial information into account, and we find that controlling for phase variability helps to control the false discovery rate during the detection process.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Synergism of active and passive microwave data for estimating bare surface soil moisture

Active and passive microwave sensors were applied effectively to the problem of estimating the surface soil moisture in a variety of environmental conditions. Research to date has shown that both types of sensors are also sensitive to the surface roughness and the vegetation cover. In estimating the soil moisture, the effect of the vegetation and roughness are often corrected either by acquiring multi-configuration (frequency and polarization) data or by adjusting the surface parameters in order to match the model predictions to the measured data. Due to the limitations on multi-configuration spaceborne data and the lack of a priori knowledge of the surface characteristics for parameter adjustments, it was suggested that the synergistic use of the sensors may improve the estimation of the soil moisture over the extreme range of naturally occurring soil and vegetation conditions. To investigate this problem, the backscattering and emission from a bare soil surface using the classical rough surface scattering theory were modeled. The model combines the small perturbation and the Kirchhoff approximations in conjunction with the Peak formulation to cover a wide range of surface roughness parameters with respect to frequency for both active and passive measurements. In this approach, the same analytical method was used to calculate the backscattering and emissivity. Therefore, the active and passive simulations can be combined at various polarizations and frequencies in order to estimate the soil moisture more actively. As a result, it is shown that (1) the emissivity is less dependent on the surface correlation length, (2) the ratio of the backscattering coefficient (HH) over the surface reflectivity (H) is almost independent of the soil moisture for a wide range of surface roughness, and (3) this ratio can be approximated as a linear function of the surface rms height. The results were compared with the data obtained by a multi-frequency radiometer-scatterometer system working at frequencies between 3.0 GHz to 11.0 GHz. The data were acquired over bare soil surfaces with moisture variations due to freezing and thawing and roughness changes due to rain and erosion. The model predictions are shown to be in reasonable agreement with the data. In addition, it was shown that the same ratio when calculated from the data shows almost no dependence on the soil moisture. Finally, a simple technique which combines the backscattering coefficient at HH polarization (active sensing) with the emissivity at H polarization (passive sensing) is suggested for retrieving the soil moisture from bare soil surfaces.

Saatchi, Sasan S.↗
NASA NTRS1988

Chlorine-hydrocarbon photochemistry in the marine troposphere and lower stratosphere

The role of chlorine atoms in the oxidation of methane and nonmethane hydrocarbons (NMHCs) in the marine troposphere and lower stratosphere was investigated using a one-dimensional photochemical model that incorporated the chemistry of CH4, NMHCs, NO(x), O(x), and HO(x), as well as organic and inorganic halogens in the troposphere and lower stratosphere. The model predicted that chlorine atoms are present in the marine troposphere at the concentrations of about 1000/cu cm, mostly as a product of the reaction between OH and HCl released from sea spray. The results indicate that Cl atoms cause 20 to 40 percent of NMHC oxidation in the troposphere and 40 to 90 percent in the lower stratosphere. At 15 km, the NMHC-Cl reactions account for nearly 80 percent of the PAN produced. Where available, experimental data confirmed the model predictions.

Singh, H. B.↗
NASA NTRS2010

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗
NASA NTRS2010

Data-Based Predictive Control with Multirate Prediction Step

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Barlow, Jonathan S.↗
NASA NTRS1972

Study of induced load and stress, volume 3

An analytical and experimental investigation into the effects of blade tip clearance on inducer performance and of leading edge sweepback on both blade pressure loading and performance was performed. Tip clearance flow was represented with a vortex flow model and measured data from previous inducer tests at three clearances were correlated with model predictions. A leading edge model was added to an existing inducer internal flow analysis, tests with two sweepbacks were conducted, and blade pressure and performance predictions were correlated with measured data.

Coons, L. L.↗
DOE OSTI2025

Characterization and Quantification of Radiation-Induced Clusters/Precipitates in RPV Steels Using STEM-EDS and Machine Learning

Over the operational lifespan of a nuclear reactor, reactor pressure vessel (RPV) steels are subjected to significant neutron irradiation, resulting in complex microstructural changes and the consequent degradation of mechanical properties. Various physically motivated correlation models have been developed to predict neutron irradiation-induced embrittlement of RPVs under different irradiation conditions. However, the efficient and accurate characterizations and quantification of radiation-induced clusters in RPVs are still challenging, which will affect the precision of the predictive models for embrittlement of RPV components. In the DOE Visiting Faculty Program (VFP) research work at Oak Ridge National Lab (ORNL), I integrate machine learning to aid Scanning Transmission Electron Microscopy – Energy Dispersive X-ray Spectroscopy (STEM-EDS) analyses, which improve the characterization and quantification of radiation-induced clusters in RPV steels, thereby enabling more accurate predictions of material behavior under irradiation. The surveillance base- and welded- RPV steels were annealed at various temperatures of 340 °C, 450 °C and 500 °C for up to 168 hours, respectively. Afterwards, I have characterized radiation-induced clusters using advanced STEM-EDS techniques and subsequently applying machine learning algorithms to analyze and refine STEM-EDS datasets, enhancing the quantification of clusters compositions and distributions. In the end, an efficient workflow for integrating STEM-EDS data analysis with machine learning to address challenges including noise reduction has been developed. The completion of this VFP work will support bridge critical gaps in the accurate quantification of radiation-induced clusters in RPV steels using STEM-EDS and support the development of more precise models for predicting RPV embrittlement in the Light Water Reactor Sustainability program supported by Department of Energy and enhancing the collaboration between ORNL and Alred University. The outcome of the VFP project will leverage a few research papers submission to peer-reviewed journals in the relevant scientific field and a few oral presentations at national and international conferences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗
DOE OSTI2025

IBPSA Project 2 BOPTEST: An update on the test cases available in the framework for testing advanced control strategies in buildings

Project 2 develops software infrastructure, test cases, and extensions for the Building Optimization Testing Framework (BOPTEST) to address the expanding needs of building and urban energy system controls through open international collaboration. This paper provides an overview of the new test cases available as of BOPTEST version 0.7.1. Each test case is developed using open-source Modelica libraries and Spawn of EnergyPlus, enabling the creation of high-fidelity building models that incorporate envelope dynamics, Heating Ventilation and Air Conditioning (HVAC) systems, and explicit control representations. Currently, eight test cases are available, with five additional cases under development. These test cases cover a wide range of climates, building types, and HVAC systems. This paper compiles and summarizes test case descriptions, cites original manuscripts that developed them for a more detailed description, and reports baseline control performance metrics. Furthermore, two example applications are presented: one illustrating different levels of control, from supervisory to low-level, and another demonstrating how Model Predictive Control (MPC) solutions must be adapted from continuous to integer to control some building actuators.

Zanetti, Ettore↗
NASA NTRS1985

X-ray emission from cataclysmic variables with accretion disks. I - Hard X-rays. II - EUV/soft X-ray radiation

Theoretical models explaining the hard-X-ray, soft-X-ray, and EUV emission of accretion-disk cataclysmic variables in terms of the disk boundary layer (DBL) are developed on the basis of a survey of the published observational data. The data are compared with model predictions in graphs for systems with high or low (greater than or less than 10-Pg/s) accretion rates. Good agreement is obtained both at low accretion rates, where an optically thin rarefied hot (Te = 10 to the 8th K) DBL radiates most of its energy as hard X-rays, and at high accretion rates, where an optically thick 100,000-K DBL radiates most of its energy in the EUV and as soft X-rays. Detailed analysis of the old nova V603 Aql suggests that previous models predicting more detections of soft-X-ray/EUV emissions from thick-DBL objects (Ferland et al., 1982) used inappropriate dwarf masses, interstellar column densities, or classical-nova space densities.

Patterson, J.↗
NASA NTRS2001

Traveling-Wave Tube Amplifier Model to Predict High-Order Modulation Intersymbol Interference

Demands for increased data rates in satellite communications necessitate higher order modulation schemes, larger system bandwidth, and minimum distortion of the modulated signal as it is passed through the traveling wave tube amplifier (TWTA). One type of distortion that the TWTA contributes to is intersymbol interference (ISI), and this becomes particularly disruptive with wide-band, complex modulation schemes. It is suspected that in addition to the dispersion of the TWT, frequency dependent reflections due to mismatches within the TWT are a significant contributor to ISI. To experimentally investigate the effect of these mismatches within the physical TWT on ISI would be prohibitively expensive, as it would require manufacturing numerous amplifiers in addition to the acquisition of the required digital hardware. In an attempt to develop a more accurate model to correlate IS1 with the TWTA and the operational signal, a fully three-dimensional (3D), time-dependent, TWT interaction model has been developed using the electromagnetic particle-in-cell (PIC) code MAFIA (solution of Maxwell's equations by the Finite-Integration-Algorithm). The model includes a user defined slow-wave circuit with a spatially tapered region of loss to implement a sever, and spatially varied geometry (such as helical pitch) to implement a phase velocity taper. The model also includes user defined input/output coupling and an electron beam contained by solenoidal, electrostatic, or periodic permanent magnet (PPM) focusing allowing standard or novel TWTs to be investigated. This model comprehensively takes into account the effects of frequency dependent nonlinear distortions (MAM and AMPM); gain ripple due to frequency dependent reflections at the input/output coupling, severs, and mismatches from dynamic pitch variations; drive induced oscillations; harmonic generation; intermodulation products; and backward waves.

Kory, Carol L.↗
DOE OSTI2025

Differential cross-section measurements of Higgs boson production in the H → τ + τ - decay channel in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

Differential measurements of Higgs boson production in the τ-lepton-pair decay channel are presented in the gluon fusion, vector-boson fusion (VBF), VH and $t\overline{t}H$ associated production modes, with particular focus on the VBF production mode. The data used to perform the measurements correspond to 140 fb -1 of proton-proton collisions collected by the ATLAS experiment at the LHC. Two methods are used to perform the measurements: the Simplified Template Cross-Section (STXS) approach and an Unfolded Fiducial Differential measurement considering only the VBF phase space. For the STXS measurement, events are categorized by their production mode and kinematic properties such as the Higgs boson’s transverse momentum (${p}_{\textrm{T}}^{\textrm{H}}$ ), the number of jets produced in association with the Higgs boson, or the invariant mass of the two leading jets (mjj). For the VBF production mode, the ratio of the measured cross-section to the Standard Model prediction for m jj > 1.5 TeV and ${p}_{\textrm{T}}^{\textrm{H}}$ > 200 GeV (${p}_{\textrm{T}}^{\textrm{H}}$ < 200 GeV) is ${1.29}_{-0.34}^{+0.39}$ (${0.12}_{-0.33}^{+0.34}$ ). This is the first VBF measurement for the higher-${p}_{\textrm{T}}^{\textrm{H}}$ criteria, and the most precise for the lower-${p}_{\textrm{T}}^{\textrm{H}}$ criteria. The fiducial cross-section measurements, which only consider the kinematic properties of the event, are performed as functions of variables characterizing the VBF topology, such as the signed ΔΦ jj between the two leading jets. The measurements have a precision of 30%–50% and agree well with the Standard Model predictions. These results are interpreted in the SMEFT framework, and place the strongest constraints to date on the CP-odd Wilson coefficient ${c}_{H\overset{\sim }{W}}$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2012

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Yildiz, Yildiray↗
NASA NTRSDate not supplied

A Model for Ice Accretion Roughness Evolution and Spatial Variations

Over the past decade, multiple investigations of ice accretion roughness and spatial variations have been performed in the Icing Research Tunnel (IRT) at the NASA Glenn Research Center. The early investigations used models of NACA 0012 airfoils with different chord sizes and focused on temporal scaling and primary cloud scaling parameters such as stagnation point collection efficiency. Subsequent investigations included the effects of model sweep, airfoil shape, airfoil lifting condition, and freestream static temperature. To develop a predictive model for roughness evolution in generalized icing situations, the maximum roughness values for the airfoils and conditions used in the angle of attack and freestream temperature investigations were scaled to eliminate the temporal variations. LEWICE simulations were employed to identify the local collection efficiency at the locations of maximum roughness, and a two-dimensional panel-method code was used to identify the local static pressure at the location of the maximum roughness. Because of the stochastic nature of ice accretion roughness, a physics-directed approach was employed to develop a multi-dimensional correlation based on the local pressure coefficient, the local total temperature, the cloud properties, and the cloud exposure time. The resulting correlation predictions are compared to ice shapes measured in the IRT for both a 21-in. NACA 0012 airfoil model and a 60-in. HAARP-II model. The resulting predictions indicate that the local freezing fraction must be included in the roughness predictive model. Implications regarding icing heat transfer predictions using the resulting roughness model are also discussed.

Icing↗
NASA NTRS2011

Track Structure and the Biological Effectiveness of Accelerated Particles for the Induction of Chromosome Damage

Track structure models predict that at a fixed value of LET, particles with lower charge number, Z will have a higher biological effectiveness compared to particles with a higher Z. In this report we investigated how track structure effects induction of chromosomal aberration in human cells. Human lymphocytes were irradiated in vitro with various energies of accelerated iron, silicon, neon, or titanium ions and chromosome damage was assessed in using three color FISH chromosome painting in chemically induced PCC samples collected a first cell division post irradiation. The LET values for these ions ranged from 30 to195 keV/micron. Of the particles studied, Neon ions have the highest biological effectiveness for induction of total chromosome damage, which is consistent with track structure model predictions. For complex-type exchanges 64 MeV/ u Neon and 450 MeV/u Iron were equally effective and induced the most complex damage. In addition we present data on chromosomes exchanges induced by six different energies of protons (5 MeV/u to 2.5 GeV/u). The linear dose response term was similar for all energies of protons suggesting that the effect of the higher LET at low proton energies is balanced by the production of nuclear secondaries from the high energy protons.

George, K.↗
NASA NTRS2012

The Biological Effectiveness of Accelerated Particles for the Induction of Chromosome Damage: Track Structure Effects and Cytogenetic Signatures of High-LET Exposure

Track structure models predict that at a fixed value of LET, particles with lower charge number, Z will have a higher biological effectiveness compared to particles with a higher Z. In this report we investigated how track structure effects induction of chromosomal aberration in human cells. Human lymphocytes were irradiated in vitro with various energies of accelerated iron, silicon, neon, or titanium ions and chromosome damage was assessed in using three color FISH chromosome painting in chemically induced PCC samples collected a first cell division post irradiation. The LET values for these ions ranged from 30 to 195 keV/micrometers. Of the particles studied, Neon ions have the highest biological effectiveness for induction of total chromosome damage, which is consistent with track structure model predictions. For complex-type exchanges 64 MeV/ u Neon and 450 MeV/u Iron were equally effective and induced the most complex damage. In addition we present data on chromosomes exchanges induced by six different energies of protons (5 MeV/u to 2.5 GeV/u). The linear dose response term was similar for all energies of protons suggesting that the effect of the higher LET at low proton energies is balanced by the production of nuclear secondaries from the high energy protons. All energies of protons have a much higher percentage of complex-type chromosome exchanges than gamma rays, signifying a cytogenetic signature for proton exposures.

George, K.↗