SEARCH · Search NASA

Results for “profiles”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Sensitivities of time-dependent temperature profile predictions for NSTX with the multi-mode model

The Multi-Mode Model (MMM) for turbulent transport was applied to a large set of well-analyzed discharges from the National Spherical Torus Experiment (NSTX) in order to evaluate its sensitivities to a wide range of plasma conditions. MMM calculations were performed for hundreds of milliseconds in each discharge by performing time-dependent predictive simulations with the 1.5D tokamak integrated modeling code TRANSP. A closely related study (Lestz et al 2025 Plasma Phys. Control. Fusion 67 105029) concluded that MMM predicted electron and ion temperature profiles that were in reasonable agreement with NSTX observations, generally outperforming a different reduced transport model, TGLF. This finding motivates the more thorough investigation of the characteristics of the MMM predictions conducted in this work. The simulations with MMM have electron energy transport dominated by electron temperature gradient modes in the examined discharges with relatively low plasma β (ratio of kinetic plasma pressure to magnetic field pressure) and high collisionality, transitioning to a mixture of different modes for higher β and lower collisionality. The thermal ion diffusivity predicted by MMM is much smaller than the neoclassical contribution, in line with previous experimental analysis of NSTX. Nonetheless, the electron and ion temperature profiles are coupled via collisional energy exchange and thus sensitive to which transport channels are predicted. The time-dependent simulations with MMM are robust to the simulation start time, converging to remarkably similar temperature profiles later during the discharge. MMM typically overpredicts confinement relative to NSTX observations, leading to the prediction of overly steep temperature profiles. Plasmas with spatially broader temperature profiles, higher plasma β, and longer energy confinement times tend to be predicted by MMM with better agreement with the experiment. As a result, these findings provide useful context for understanding the regime-dependent tendencies of MMM in anticipation of self-consistent, time-dependent predictive simulations of NSTX-U discharges with these same modeling tools.

MMM↗

DOE OSTI2024

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗

DOE OSTI2024

The mass profiles of dwarf galaxies from Dark Energy Survey lensing

We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterize their stellar mass and redshift distributions with a spectroscopic calibration sample. By combining the ${\sim} 5000\,\mathrm{deg}^2$ multiband photometry from the Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs Survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z\lt 0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log _{10}(M_*/\text{M}_\odot)=\left[8.52\substack{+0.57 -0.76},\, 9.02\substack{+0.50 -0.64},\, 9.49\substack{+0.50 -0.58}\right]$ . We measure the stacked excess surface mass density profiles, $\Delta \Sigma (R)$, of these galaxies using galaxy–galaxy lensing with a signal-to-noise ratio of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log _{10}(M_{\rm halo}/\text{M}_\odot)$ = [$10.67\substack{+0.2 -0.4}$, $11.01\substack{+0.14 -0.27}$, $11.40\substack{+0.08 -0.15}$]. The cold dark matter profiles are consistent with NFW (Navarro, Frenk, and White) profiles over scales ${\lesssim} 0.15 \, {h}^{-1}$ Mpc. We find that ${\sim} 20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.

dark matter↗

DOE OSTI2026

Using strong lensing to detect subhaloes with steep inner density profiles

ABSTRACT The inner region of a subhalo’s density distribution is particularly sensitive to dark matter microphysics, with alternative dark matter models leading to both cored and steeply-rising inner density profiles. This work investigates how the lensing signature and detectability of dark matter subhaloes in mock HST-, Euclid-, and JWST-like strong lensing observations depend on the subhalo’s radial density profile, especially with regards to the inner power-law slope, $\beta$. We demonstrate that the minimum subhalo mass detectable along the Einstein ring of a system is strongly dependent on $\beta$. In particular, we show that subhaloes with $\beta = 2.2$ can be detected down to masses over an order-of-magnitude lower than their Navarro–Frenk–White (NFW) counterparts with $\beta = 1$. Importantly, we find that the detectability of subhaloes with steep inner profiles is minimally affected by increasing the complexity of the main lens galaxy’s mass model. This is a notable characteristic of these subhaloes, as those with NFW or shallower profiles become essentially undetectable when multipole perturbations are added to the lens model. The results of this work highlight how the underlying dark matter physics can significantly impact the expected number of subhalo detections from strong gravitational lensing observations. This is important for testing Cold Dark Matter against alternative models, such as Self-Interacting Dark Matter, that predict a diverse range of subhalo inner density profiles.

dark matter↗

DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗

DOE OSTI2025

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-The-Meter Solar

The ever-growing integration of distributed energy resources (DERs), especially behind-the-meter (BTM) solar generations, poses imperative operational challenges to system operators such as regional transmission organizations (RTOs). It is important for RTOs to effectively and accurately extract actual load profiles at the transmission level for a single node with significant BTM solar injection. This paper first illustrates the necessity of disaggregating the daily actual load profile of a single node. Furthermore, by segmenting nodes with selected timeseries features, nodes with significant BTM solar generation are identified. Lastly, a bi-level framework is proposed, comprising reference node disaggregation and DeepFM nodal disaggregation, aimed at disaggregating the nodal load profiles from which system operators require more information. By adopting a hybrid Deep Factorization Machine (DeepFM) model, the model achieve accurate results by extracting both linear and nonlinear relations between nodes in the same region and the zonal load and nodal load profile. To overcome the lack of ground truth, this paper segments the load profile into daytime, nighttime, and zero-crossing points and utilizes the latter two for evaluation purposes. The proposed disaggregation procedure is validated using real world, minute-level, normalized, and anonymized nodal data in the PJM service territory.

42 ENGINEERING↗

DOE OSTI2025

Measurement techniques using the electron beam profile scanner at the Fermilab Main Injector

This work presents techniques for non-invasive transverse profile measurements of high-intensity proton beams using an Electron Beam Profile Scanner (EBPS). The EBPS utilizes low-energy electrons as a probe to analyze the transverse size of proton beams, allowing for potential analysis on a single-bunch basis. Recent upgrades to the Fermilab Main Injector have enhanced beam power on target to 1 MW, with future developments targeting 2 MW. The higher beam power has increased the demand for non-invasive diagnostics, as invasive methods can disrupt operations.The techniques presented include 1) the slow scan technique, which serves as a proof of concept for the probe beam, 2) the one-shot scan technique for measuring horizontal beam profiles, and 3) the raster scan technique for analyzing horizontal beam profiles as a function of the longitudinal distribution of the beam. The profiles obtained will be crucial for studying and understanding instabilities in high-power, high-intensity proton beams. This will contribute to optimizing the operation of high-power proton accelerators by minimizing beam loss, activation, and damage to both the diagnostics and the accelerator components.

Mwaniki, Matilda [IIT, Chicago]↗

DOE OSTI2024

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the above-mentioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1972

Speed-dependent collisional width and shift parameters in spectral profiles.

Derivation of an expression for the spectral profile, termed a speed-dependent Voigt profile (SDVP), taking into account speed-dependent shift and width parameters which are calculated on the basis of an active atom-perturber interaction. It is shown that an analysis of line shapes in terms of simple Voigt profiles (rather than the SDVP) may lead to considerable errors in the determination of characteristic atomic parameters, especially in systems where the perturber to active atom mass ratio is large. It is also noted that the speed-dependent shift leads to an asymmetrical profile, and such a profile is displayed.

Berman, P. R.↗

NASA NTRS1972

A study of the properties of beryllium doped silicon with particular emphasis on diffusion mechanisms: Profiles of depth dependent conductivity as determined by electrical surface probes

Very large diffusion coefficients were encountered and required the determination of impurity profiles for samples approximately 1 cm thick. Since conductivity values are readily converted into concentrations of electrically active impurities, the major problem became that of accurately determining the conductivity profiles of beryllium diffused silicon samples. Four-point probe measurements on samples having depth conductivities are interpreted in terms of conductivity profiles, based on an exact solution of the problem of exponentially depth dependent conductivity. Applications include surface conductivity determination where the form of the conductivity profile is known, and conductivity profile determination from probe measurements taken as the sample surface is progressively lapped away. The application is limited to samples having conductivity monotonically decreasing with depth from the probed surface.

Franks, R. K.↗

NASA NTRS1973

Boundary-layer electron profiles for entry of a blunts slender body at high altitude

New calculations of boundary-layer electron concentration profiles for entry of a blunt-nosed slender body into the earth's atmosphere are compared with previous calculations in which ambipolar diffusion was neglected. The old and new results agree in those flight regimes where ambipolar diffusion is unimportant, but large differences are noted in both peak electron concentration and profile shape at the higher altitudes, where diffusion effects are greatest. The new results are also compared with flight-measured profiles and with calculated profiles for a viscous-shock-layer theory which was recently reported in the literature. The boundary-layer results and the data agree in most respects. Differences which occur between predicted results and the data in the outer parts of the profile are discussed in terms of the effects of aerodynamic heating of the probes.

Evans, J. S.↗

NASA NTRS1975

Theoretical and experimental study of a new method for prediction of profile drag of airfoil sections

Theoretical and experimental studies are described which were conducted for the purpose of developing a new generalized method for the prediction of profile drag of single component airfoil sections with sharp trailing edges. This method aims at solution for the flow in the wake from the airfoil trailing edge to the large distance in the downstream direction; the profile drag of the given airfoil section can then easily be obtained from the momentum balance once the shape of velocity profile at a large distance from the airfoil trailing edge has been computed. Computer program subroutines have been developed for the computation of the profile drag and flow in the airfoil wake on CDC6600 computer. The required inputs to the computer program consist of free stream conditions and the characteristics of the boundary layers at the airfoil trailing edge or at the point of incipient separation in the neighborhood of airfoil trailing edge. The method described is quite generalized and hence can be extended to the solution of the profile drag for multi-component airfoil sections.

Goradia, S. H.↗

NASA NTRS1976

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

Hodges, D. B.↗

NASA NTRS1977

Galatry profile convolved with the Fabry-Perot instrument function

The physical conditions in laboratory gases and in the upper atmosphere of the planets, including earth, can be deduced from a measurement of the intensity and line profile of different radiating molecules. Because of the low pressures in the upper atmospheres, many molecular lines with small pressure-broadening coefficients are collisionally narrowed. These lines are resolvable with a Fabry-Perot interferometer. Analytical expressions are given relating the measured line intensity and profile to the true line intensity and profile. A deconvolution of the measured profile gives the parameters A, beta, and K characterizing the collisionally narrowed Galatry profile. General expressions for the nonideal interferometer are discussed, and, specifically, mirror defects and a limited detector aperture are treated.

Goorvitch, D.↗

NASA NTRS1977

Backus-Gilbert theory and its application to retrieval of ozone and temperature profiles

The inversion method provides a quantitative evaluation of the trade-off between vertical resolution of a retrieved profile and formal root-mean-square (rms) error due to measurement noise propagation. The problem of retrieving the top-side ozone profile from backscattered ultraviolet (BUV) measurements is considered. For measurements of the type currently being obtained with the Nimbus 4 and AE-E BUV experiments, it is found that a vertical resolution of approximately 0.75 scale height can be achieved for a formal volume mixing ratio profile error of 10%. Other examples include treatments of the retrieval of temperature profiles from measurements in the 15 micron CO2 absorption band for both the terrestrial and Martian atmospheres. Finally, the method is applied to the problem of retrieving temperature profiles of the Jovian planets from measurements in the far infrared pressure induced H2 lines to be obtained from the Mariner Jupiter/Saturn fly-by missions.

Conrath, B. J.↗

NASA NTRS1979

Modified power law equations for vertical wind profiles

In an investigation of windpower plant siting, equations are presented and evaluated for a wind profile model which incorporates both roughness and wind speed effects, while retaining the basic simplicity of the Hellman power law. These equations recognize the statistical nature of wind profiles and are compatible with existing analytical models and recent wind profile data. Predictions of energy output based on the proposed profile equations are 10% to 20% higher than those made with the 1/7 power law. In addition, correlation between calculated and observed blade loads is significantly better at higher wind speeds when the proposed wind profile model is used than when a constant power model is used.

Spera, D. A.↗

NASA NTRS1981

The supercritical profile of the supercritical wing

The profile wing design for supercritical structures is discussed. Emphasis is placed on the flow of air surrounding the wing and variations in flow fields are examined. Modifications to the profile for flight below transonic level are presented that increase the uplift pressure and permit the achievement of critical Mach numbers on the order of 0.85. The uplift pressure along the upper side of the profile is compared for a classical and a Peaky profile. A comparison of classical and supercritical wing cross sections indicates a flatter upper side, a large nose radius, and a thicker profile to the supercritical wing.

Wagner, O.↗