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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SITCOMTN-161: PSF assessment in the field of Abell 360 and shapeHSM shear profile using LSSTComCam data

The Rubin LSSTComCam on-sky campaign performed at the end of 2024 provided observations of the Abell 360 galaxy cluster; these data allow a preliminary study of cluster weak lensing analysis using Rubin Data Preview 1 (DP1) data. Among all the steps required for such analyses, accurate modeling of the PSF is essential. This work uses several diagnostics, mostly based on the residuals between the second moments of stars and the PSF model, to characterize the accuracy of the PSF modeling in the A360 field. We find the level of the residuals to be sufficiently low not to hinder the measurement of the tangential shear profile around A360. With a simple source selection process, we demonstrate that outputs of the LSST Science Pipelines can be used to detect the tangential shear profile in Abell 360 at the 3.6σ level, and our analysis indicates that contamination from PSF modeling systematics is negligible.

Dell'Antonio, Ian [Brown University]↗
DOE OSTI2014

OpenStudio - Fault Modeling

This software record documents the OpenStudio fault model development portion of the Fault Detection and Diagnostics LDRD project.The software provides a suite of OpenStudio measures (scripts) for modeling typical HVAC system faults in commercial buildings and also included supporting materials: example projects and OpenStudio measures for reporting fault costs and energy impacts.

Frank, Stephen↗
NASA NTRS1994

Analytic Lyman-alpha wing diagnostics and the chromospheric excitation balance in cool dwarfs

I show that the Lyman alpha wings of cool dwarfs can be understood in terms of a very simple model, based on a simplified representation of the chromospheric hydrogen excitation balance and approximate analytic wing diagnostics in partial redistribution. Much of the complexity of the radiation transfer in the partially coherent and steeply temperature-sensitive Lyman alpha line is circumvented by this technique. The result is an expedient scheme for inverting the Lyman alpha wing profile to determine the characteristic free electron density and its gradient in the middle chromosphere. This represents an important new diagnostic for constraining chromospheric models and their radiative losses. I apply this diagnostic to the Lyman alpha wing profiles of the Sun and AU Mic and show that current instrumentation, most notably the Goddard High Resolution Spectrograph (GHRS) on the Hubble Space Telescope, is capable of providing the necessary data.

Gayley, K. G.↗
DOE OSTI2021

Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols

Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y −1 or +1.8%) than on land evaporation (+0.18 W m −2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.

Chakraborty, TC↗
DOE OSTI2016

CALIBRATED ULTRA FAST IMAGE SIMULATIONS FOR THE DARK ENERGY SURVEY

Image simulations are becoming increasingly important in understanding the measurement process of the shapes of galaxies for weak lensing and the associated systematic effects. For this purpose we present the first implementation of the Monte Carlo Control Loops (MCCL), a coherent framework for studying systematic effects in weak lensing. It allows us to model and calibrate the shear measurement process using image simulations from the Ultra Fast Image Generator (UFig) and the image analysis software SExtractor. We apply this framework to a subset of the data taken during the Science Verification period (SV) of the Dark Energy Survey (DES). We calibrate the UFig simulations to be statistically consistent with one of the SV images, which covers ∼0.5 square degrees. We then perform tolerance analyses by perturbing six simulation parameters and study their impact on the shear measurement at the one-point level. This allows us to determine the relative importance of different parameters. For spatially constant systematic errors and point-spread function, the calibration of the simulation reaches the weak lensing precision needed for the DES SV survey area. Furthermore, we find a sensitivity of the shear measurement to the intrinsic ellipticity distribution, and an interplay between the magnitude-size and the pixel value diagnostics in constraining the noise model. This work is the first application of the MCCL framework to data and shows how it can be used to methodically study the impact of systematics on the cosmic shear measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

An ultra-fast method for generating synthetic down-scattered neutron data for inertial confinement fusion implosions

In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.

Deuterium↗
DOE OSTI2021

Measurements of the time-dependent cosmic-ray Sun shadow with seven years of IceCube data: Comparison with the Solar cycle and magnetic field models

Observations of the time-dependent cosmic-ray Sun shadow have been proven as a valuable diagnostic for the assessment of solar magnetic field models. Here, seven years of IceCube data are compared to solar activity and solar magnetic field models. A quantitative comparison of solar magnetic field models with IceCube data on the event rate level is performed for the first time. Additionally, a first energy-dependent analysis is presented and compared to recent predictions. We use seven years of IceCube data for the moon and the Sun and compare them to simulations on data rate level. The simulations are performed for the geometrical shadow hypothesis for the moon and the Sun and for a cosmic-ray propagation model governed by the solar magnetic field for the case of the Sun. We find that a linearly decreasing relationship between Sun shadow strength and solar activity is preferred over a constant relationship at the 6.4σ level. We test two commonly used models of the coronal magnetic field, both combined with a Parker spiral, by modeling cosmic-ray propagation in the solar magnetic field. Both models predict a weakening of the shadow in times of high solar activity as it is also visible in the data. We find tensions with the data on the order of 3σ for both models, assuming only statistical uncertainties. The magnetic field model CSSS fits the data slightly better than the PFSS model. This is generally consistent with what is found previously by the Tibet AS-γ Experiment; a deviation of the data from the two models is, however, not significant at this point. Regarding the energy dependence of the Sun shadow, we find indications that the shadowing effect increases with energy during times of high solar activity, in agreement with theoretical predictions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Use of FUV auroral emissions as diagnostic indicators

In an earlier study we modeled selected Far Ultraviolet (FUV) auroral emissions (O I(1356 A), N2 Lyman-Birge-Hopfield (LBH) (1464 A), and LBH (1838 A)) to examine the sensitivity of these emissions and their ratios to likely changes in the neutral atmosphere. In this paper we extend that study to examine the dependence of these same emissions and their ratios on the shape of the energy distribution of the auroral electrons. In particular, we wish to determine whether changes in energy spectra might interfere with our determination of the characteristic energy. Modeled column-integrated emissions show relatively small (less than 30%) dependences on the shape and width of the incident energy spectrum, provided the average energy and total energy flux of the energy distribution are held constant. Long-wavelength FUV emissions, which are relatively unaffected by O2 absorption losses, exhibit virtually no dependence on the shape of the incident energy distribution. Changes in ratios of FUV short- to long-wavelength emissions as a function of characteristic energy are much larger than those due to changes in energy distribution. As a result, the determination of characteristic energy using these emission ratios is relatively unambiguous. We also examine the relative intensities of the aurora and the dayglow for various conditions. The intensities of modeled FUV auroral emissions relative to the dayglow emissions are presented as a function of solar zenith angle and incident energy flux. Under certain conditions (energy flux less than or equal 1 erg/sq cm/s and solar zenith angle less than or equal 50 deg) the dayglow will be limiting factor in the detection of weak auroras.

Germany, G. A.↗
NASA NTRS2000

Characteristics of three-dimensional quasi-geostrophic transient eddy propagation in the vicinity of a simulated Gulf Stream

Output of an eddy-resolving model of the North Atlantic is diagnosed in the vicinity of the Gulf Stream (GS), using the three-dimensional quasi-geostrophic transient wave activity flux diagnostic developed by Plumb [1986]. The model North Atlantic shows large transient wave activity along the model GS and along the edge of the Mediterranean Outflow. The fluxes show advection of wave activity by the GS from the separation point and radiation of wave activity from the GS in the top 1000 m.

boundary↗
DOE OSTI2022

Development of Short-Term Forecasting Models Using Plant Asset Data and Feature Selection

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This paper focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 +- 0.014, 0.0026 +- 0, and 0.063 +- 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Multi-fidelity physics-informed machine learning for probabilistic damage diagnosis

Machine learning (ML) models are gaining popularity in structural health monitoring (SHM) because of their ability to learn the complex relationship between damage and sensor data. However, the lack of sufficient experimental data for structures with different degrees of damage is a key problem in training ML models for SHM. This problem can be alleviated by using physics-based models to generate the required training data to build physics-informed ML (PIML) models for SHM. However, it takes significant computational effort to perform enough high-fidelity simulations of the diagnostic test. It is thus desirable to know whether the available computational resource budget should be expended on numerous low-fidelity physics simulations, or a small number of high-fidelity simulations, or their combination. In this paper, we investigate this aspect of generating adequate training data for PIML, by constructing multi-fidelity PIML models. We evaluate the performance of several PIML models, trained with different amounts of low-fidelity and high-fidelity data, in locating hidden cracks in concrete structures using a nonlinear dynamics-based diagnosis technique. Here, we find that high-fidelity physics simulations that do not cover the (test and damage) parameter space do not improve the performance of diagnostic PIML models built using data from many low-fidelity physics simulations.

42 ENGINEERING↗
NASA NTRS2002

Rocket Engine Oscillation Diagnostics

Rocket engine oscillating data can reveal many physical phenomena ranging from unsteady flow and acoustics to rotordynamics and structural dynamics. Because of this, engine diagnostics based on oscillation data should employ both signal analysis and physical modeling. This paper describes an approach to rocket engine oscillation diagnostics, types of problems encountered, and example problems solved. Determination of design guidelines and environments (or loads) from oscillating phenomena is required during initial stages of rocket engine design, while the additional tasks of health monitoring, incipient failure detection, and anomaly diagnostics occur during engine development and operation. Oscillations in rocket engines are typically related to flow driven acoustics, flow excited structures, or rotational forces. Additional sources of oscillatory energy are combustion and cavitation. Included in the example problems is a sampling of signal analysis tools employed in diagnostics. The rocket engine hardware includes combustion devices, valves, turbopumps, and ducts. Simple models of an oscillating fluid system or structure can be constructed to estimate pertinent dynamic parameters governing the unsteady behavior of engine systems or components. In the example problems it is shown that simple physical modeling when combined with signal analysis can be successfully employed to diagnose complex rocket engine oscillatory phenomena.

Nesman, Tom↗
NASA NTRS1981

Global and local fluctuations of winter and summer simulations with the GLAS climate model

Winter and summer simulations were carried out with an improved version of the GLAS general circulation model. An improved method of computing the boundary layer fluxes, and a more realistic specification of the albedo of snow and ice covered surfaces were used. Each particular diagnostic quantity was computed from the model data and each of the 15 years of observations in precisely the same way, wherever possible. The reported observational results are averaged over the 15 winters or summers, as appropriate.

Straus, D. M.↗
NASA NTRS2007

Supersonic Combustion Research at NASA

This paper discusses the progress of work to model high-speed supersonic reacting flow. The purpose of the work is to improve the state of the art of CFD capabilities for predicting the flow in high-speed propulsion systems, particularly combustor flowpaths. The program has several components including the development of advanced algorithms and models for simulating engine flowpaths as well as a fundamental experimental and diagnostic development effort to support the formulation and validation of the mathematical models. The paper will provide details of current work on experiments that will provide data for the modeling efforts along with the associated nonintrusive diagnostics used to collect the data from the experimental flowfield. Simulation of a recent experiment to partially validate the accuracy of a combustion code is also described.

Drummond, J. P.↗
DOE OSTI2015

Evaluation of thermal helium beam and line-ratio fast diagnostic on the National Spherical Torus Experiment-Upgrade

A 1-D kinetic collisional radiative model (CRM) with state-of-the-art atomic data is developed and employed to simulate line emission to evaluate the Thermal Helium Beam (THB) diagnostic on NSTX-U. This diagnostic is currently in operation on RFX-mod, and it is proposed to be installed on NSTX-U. The THB system uses the intensity ratios of neutral helium lines 667.8, 706.5, and 728.1 nm to derive electron temperature (eV ) and density (cm –3 ) profiles. The purpose of the present analysis is to evaluate the applications of this diagnostic for determining fast (~4 μs) electron temperature and density radial profiles on the scrape-off layer (SOL) and edge regions of NSTX-U that are needed in turbulence studies. The diagnostic is limited by the level of detection of the 728.1 nm line, which is the weakest of the three. In conclusion, this study will also aid in future design of a similar 2-D diagnostic systems on the divertor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Experimental and modeling studies of the plasma chemistry in a humid Ar radiofrequency atmospheric pressure plasma jet

Abstract While humid atmospheric pressure plasmas are extensively modeled, reaction set validation for these conditions remains limited. We present a detailed comparison of a modelling and experimental study with a goal to elucidate the plasma chemistry in a humid Ar radiofrequency-driven atmospheric pressure plasma jet. A large group of species including radicals (H, OH, O, HO 2 ) and long-lived species (H 2 , O 2 and H 2 O 2 ) in the jet effluent was experimentally quantified by molecular beam mass spectroscopy (MBMS). MBMS measurements of H 2 O 2 , OH and H were validated by direct comparison with a liquid phase colorimetric measurement, laser-induced fluorescence (LIF) and two-photon absorption LIF respectively. While an excellent agreement was found for OH and H 2 O 2 by both techniques, a significant difference was found for H and shown to be due to boundary layer effects at the MBMS sampling substrate. The measured O, OH, HO 2 and H 2 are in good agreement with the plug model while H and O 2 were underestimated and H 2 O 2 was overestimated by the model. The accuracy of both the used reaction set and the diagnostics, as well as the observed discrepancies between the modeling and experimental results, are critically assessed. The results presented in this work enable us to identify further data needs for describing H 2 O vapor chemistry in low-temperature plasmas.

Physics↗
NASA NTRS1994

Energy transport and dynamics

We report findings concerning energy transport and dynamics in flares during the impulsive and gradual phases based on new ground-based and space observations (notably from Yohkoh). A preheating sometimes occurs during the impulsive phase. Ca XIX line shifts are confirmed to be good tracers of bulk plasma motions, although strong blue shifts are not as frequent as previously claimed. They often appear correlated with hard X-rays but, for some events, the concept that electron beams provide the whole energy input to the thermal component seems not to apply. Theory now yields: new diagnostics of low-energy proton and electric beams; accurate hydrodynamical modeling of pulse beam heating of the atmosphere; possible diagnostics of microflares (based on X-ray line ratio or on loop variability); and simulated images of chromospheric evaporation fronts. For the gradual phase, the continual reorganization of magnetic field lines over active regions determines where and when magnetic reconnection, the mechanism favored for energy release, will occur. Spatial and temporal fragmentation of the energy release, observed at different wavelengths, is considered to be a factor as well in energy transport and plasma dynamics.

Schmieder, Brigitte↗
NASA NTRS2008

An Efficient Reachability Analysis Algorithm

A document discusses a new algorithm for generating higher-order dependencies for diagnostic and sensor placement analysis when a system is described with a causal modeling framework. This innovation will be used in diagnostic and sensor optimization and analysis tools. Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in-situ platforms. This algorithm will serve as a power tool for technologies that satisfy a key requirement of autonomous spacecraft, including science instruments and in-situ missions.

Vatan, Farrokh↗