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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning↗
DOE OSTI2017

Identification of Accretion as Grain Growth Mechanism in Astrophysically Relevant Water–Ice Dusty Plasma Experiment

The grain growth process in the Caltech water–ice dusty plasma experiment has been studied using a high-speed camera and a long-distance microscope lens. It is observed that (i) the ice grain number density decreases fourfold as the average grain major axis increases from 20 to 80 μ m, (ii) the major axis length has a log-normal distribution rather than a power-law dependence, and (iii) no collisions between ice grains are apparent. The grains have a large negative charge resulting in strong mutual repulsion and this, combined with the fractal character of the ice grains, prevents them from agglomerating. In order for the grain kinetic energy to be sufficiently small to prevent collisions between ice grains, the volumetric packing factor (i.e., ratio of the actual volume to the volume of a circumscribing ellipsoid) of the ice grains must be less than ∼0.1 depending on the exact relative velocity of the grains in question. Thus, it is concluded that direct accretion of water molecules is very likely to dominate the observed ice grain growth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining baryon annihilation in the hadronic phase of heavy-ion collisions via event-by-event fluctuations

We point out that the variance of net-baryon distribution normalized by the Skellam distribution baseline, κ 2 [$B-\overline{B}$]/$\langle B+\overline{B} \rangle$, is sensitive to the possible modification of (anti)baryon yields due to $B\overline{B}$ annihilation in the hadronic phase. The corresponding measurements can thus place stringent limits on the magnitude of the $B\overline{B}$ annihilation and its inverse reaction. We perform Monte Carlo simulations of the hadronic phase in Pb-Pb collisions at the LHC via the recently developed subensemble sampler + UrQMD afterburner and show that the effect survives in net-proton fluctuations, which are directly accessible experimentally. The available experimental data of the ALICE Collaboration on net-proton fluctuations disfavors a notable suppression of (anti)baryon yields in $B\overline{B}$ annihilations predicted by the present version of UrQMD if only global baryon conservation is incorporated. On the other hand, the annihilations improve the data description when local baryon conservation is imposed. The two effects can be disentangled by measuring κ 2 [$B-\overline{B}$]/$\langle B+\overline{B} \rangle$, which at the LHC is notably suppressed by annihilations but virtually unaffected by baryon number conservation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantifying the unknown impact of segmentation uncertainty on image-based simulations

Abstract Image-based simulation, the use of 3D images to calculate physical quantities, relies on image segmentation for geometry creation. However, this process introduces image segmentation uncertainty because different segmentation tools (both manual and machine-learning-based) will each produce a unique and valid segmentation. First, we demonstrate that these variations propagate into the physics simulations, compromising the resulting physics quantities. Second, we propose a general framework for rapidly quantifying segmentation uncertainty. Through the creation and sampling of segmentation uncertainty probability maps, we systematically and objectively create uncertainty distributions of the physics quantities. We show that physics quantity uncertainty distributions can follow a Normal distribution, but, in more complicated physics simulations, the resulting uncertainty distribution can be surprisingly nontrivial. We establish that bounding segmentation uncertainty can fail in these nontrivial situations. While our work does not eliminate segmentation uncertainty, it improves simulation credibility by making visible the previously unrecognized segmentation uncertainty plaguing image-based simulation.

42 ENGINEERING↗
DOE OSTI2015

Ion heating, burnout of the high-frequency field, and ion sound generation under the development of a modulation instability of an intense Langmuir wave in a plasma

The development of one-dimensional parametric instabilities of intense long plasma waves is considered in terms of the so-called hybrid models, with electrons being treated as a fluid and ions being regarded as particles. The analysis is performed for both cases when the average plasma field energy is lower (Zakharov's hybrid model—ZHM) or greater (Silin's hybrid model—SHM) than the plasma thermal energy. The efficiency of energy transfer to ions and to ion perturbations under the development of the instability is considered for various values of electron-to-ion mass ratios. The energy of low-frequency oscillations (ion-sound waves) is found to be much lower than the final ion kinetic energy. We also discuss the influence of the changes in the damping rate of the high-frequency (HF) field on the instability development. The decrease of the absorption of the HF field inhibits the HF field burnout within plasma density cavities and gives rise to the broadening of the HF spectrum. At the same time, the ion velocity distribution tends to the normal distribution in both ZHM and SHM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Linewidth broadening and tunneling of excitons bound to N pairs in dilute GaAs:N

The exciton bound to a pair of nitrogen atoms situated at nearby lattice sites in dilute GaAs:N provides an energetically uniform electronic system, spectrally distinct from pairs with larger or smaller separations, and can even be grown with a uniform pair orientation in the crystal. We use photoluminescence excitation spectroscopy on an ensemble of N pairs to study the narrow continuous energy distribution within two of the individual exchange- and symmetry-split exciton states. Inhomogeneous linewidths of 50-60 ueV vary across the crystal on a mesoscopic scale and can be 30 ueV at microscopic locations indicating that the homogeneous linewidth inferred from previous time-domain measurements is still considerably broadened. While excitation and emission linewidths are similar, results show a small energy shift between them indicative of exciton transfer via phonon-assisted tunneling between spatially separated N pairs. We numerically simulate the tunneling in a spatial network of randomly distributed pairs having a normal distribution of bound exciton energies. Comparing the ensemble excitation-emission energy shift with the measured results shows that the transfer probability is higher than expected from the dilute pair concentration and what is known of the exciton wavefunction spatial extent. Both the broadening and the exciton transfer have implications for the goal of pair-bound excitons as a single- or multi-qubit system.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TH-CD-BRA-02: 3D Remote Dosimetry for MRI-Guided Radiation Therapy: A Hybrid Approach

Purpose: To validate the dosimetric accuracy of a commercially available MR-IGRT system using a combination of 3D dosimetry measurements (with PRESAGE(R) radiochromic plastic and optical-CT readout) and an in-house developed GPU-accelerated PENELOPE Monte-Carlo dose calculation system. Methods: {sup 60}Co IMRT subject to a 0.35T lateral magnetic field has recently been commissioned in our institution following AAPM’s TG-119 recommendations. We performed PRESAGE(R) sensitivity studies in 4ml cuvettes to verify linearity, MR-compatibility, and energy-independence. Using 10cm diameter PRESAGE(R), we delivered an open calibration field to examine the percent depth dose and a symmetrical 3-field plan with three adjacent regions of varying dose to determine uniformity within the dosimeter under a magnetic field. After initial testing, TG-119 plans were created in the TPS and then delivered to 14.5cm 2kg PRESAGE(R) dosimeters. Dose readout was performed via optical-CT at a second institution specializing in remote 3D dosimetry. Absolute dose was measured using an IBA CC01 ion chamber and the institution standard patient-specific QA methods were used to validate plan delivery. Calculated TG-119 plans were then compared with an independent Monte Carlo dose calculation (gPENELOPE). Results: PRESAGE(R) responds linearly (R{sup 2}=0.9996) to {sup 60}Co irradiation, in the presence of a 0.35T magnetic field, with a sensitivity of 0.0305(±0.003)cm{sup −1}Gy{sup −1}, within 1% of a 6MV non-MR linac irradiation (R{sup 2}=0.9991) with a sensitivity of 0.0302(±0.003)cm{sup −1}Gy{sup −1}. Analysis of TG-119 clinical plans using 3D-gamma (3%/3mm, 10% threshold) give passing rates of: HN 99.1%, prostate 98.0%, C-shape 90.8%, and multi-target 98.5%. The TPS agreed with gPENELOPE with a mean gamma passing rate of 98.4±1.5% (2%/2mm) with the z-score distributions following a standard normal distribution. Conclusion: We demonstrate for the first time that 3D remote dosimetry using both experimental and computational methods is a feasible and reliable approach to commissioning MR-IMRT, which is particularly useful for less specialized clinics in adopting this new treatment modality.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

NASA Discipline Neuroscience↗
NASA NTRS2012

Monitoring of International Space Station Telemetry Using Shewhart Control Charts

Shewhart control charts have been established as an expedient method for analyzing dynamic, trending data in order to identify anomalous subsystem performance as soon as such performance would exceed a statistically established baseline. Additionally, this leading indicator tool integrates a selection methodology that reduces false positive indications, optimizes true leading indicator events, minimizes computer processor unit duty cycles, and addresses human factor concerns (i.e., the potential for flight-controller data overload). This innovation leverages statistical process control, and provides a relatively simple way to allow flight controllers to focus their attention on subtle system changes that could lead to dramatic off-nominal system performance. Finally, this capability improves response time to potential hardware damage and/or crew injury, thereby improving space flight safety. Shewhart control charts require normalized data. However, the telemetry from the ISS Early External Thermal Control System (EETCS) was not normally distributed. A method for normalizing the data was implemented, as was a means of selecting data windows, the number of standard deviations (Sigma Level), the number of consecutive points out of limits (Sequence), and direction (increasing or decreasing trend data). By varying these options, and treating them like dial settings, the number of nuisance alerts and leading indicators were optimized. The goal was to capture all leading indicators while minimizing the number of nuisances. Lean Six Sigma (L6S) design of experiment methodologies were employed. To optimize the results, Perl programming language was used to automate the massive amounts of telemetry data, control chart plots, and the data analysis.

Fitch, Jeffery T.↗
DOE OSTI2022

Chandra measurements of gas homogeneity and turbulence at intermediate radii in the Perseus Cluster

ABSTRACT We present a Chandra study of surface brightness fluctuations in the diffuse intracluster medium of the Perseus Cluster. Our study utilizes deep, archival imaging of the cluster core as well as a new mosaic of 29 short $\, 5\,$-ks observations extending in eight different directions out to radii of $r_{500} \sim 2.2\, r_{2500}$. Under the assumption that the distribution of densities at a given radius is log-normally distributed, two important quantities can be derived from the width of the log-normal density distribution on a given spatial scale: the density bias, that is equal to the square root of the clumping factor C; and the one-component turbulent velocity, vk,1D. We forward-model all contributions to the measured surface brightness, including astrophysical and particle background components, and account for the Poisson nature of the measured signal. Measuring the distribution of surface brightness fluctuations in 1 arcmin2 regions, spanning the radial range $0.3\rm {-}2.2\, r_{2500}$ ($7.8\rm {-}57.3\,$ arcmin), we find a small to moderate average density bias of around $3{{\ \rm per\ cent}}$ at radii below $1.6\, r_{2500}$. We also infer an average turbulent velocity at these radii of V1D < 400 km s−1. Direct confirmation of our results on turbulent velocities inferred from surface brightness fluctuations should be possible using the X-ray calorimeter spectrometers to be flown aboard the XRISM and Athena observatories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Studies of the 3D surface roughness height

Nowadays nano-coatings occupy more and more significant place in technology. Innovative, functional coatings acquire new aspects from the point of view of modern technologies, considering the aggregate of physical properties that can be achieved manipulating in the production process with the properties of coatings’ surfaces on micro- and nano-level. Nano-coatings are applied on machine parts, friction surfaces, contacting parts, corrosion surfaces, transparent conducting films (TCF), etc. The equipment available at present for the production of transparent conducting oxide (TCO) coatings with highest quality is based on expensive indium tin oxide (ITO) material; therefore cheaper alternatives are being searched for. One such offered alternative is zink oxide (ZnO) nano-coatings. Evaluating the TCF physical and mechanical properties and in view of the new ISO standard (EN ISO 25178) on the introduction of surface texture (3D surface roughness) in the engineering calculations, it is necessary to examine the height of 3D surface roughness, which is one of the most significant roughness parameters. The given paper studies the average values of 3D surface roughness height and the most often applied distribution laws are as follows: the normal distribution and Rayleigh distribution. The 3D surface is simulated by a normal random field.

36 MATERIALS SCIENCE↗
DOE OSTI2014

On bias of kinetic temperature measurements in complex plasmas

The kinetic temperature in complex plasmas is often measured using particle tracking velocimetry. Here, we introduce a criterion which minimizes the probability of faulty tracking of particles with normally distributed random displacements in consecutive frames. Faulty particle tracking results in a measurement bias of the deduced velocity distribution function and hence the deduced kinetic temperature. For particles with a normal velocity distribution function, mistracking biases the obtained velocity distribution function towards small velocities at the expense of large velocities, i.e., the inferred velocity distribution is more peaked and its tail is less pronounced. The kinetic temperature is therefore systematically underestimated in measurements. We give a prescription to mitigate this type of error.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Composited structure of non-precipitating shallow cumulus clouds

The normalized distributions of thermodynamic and dynamical variables both within and outside shallow clouds are investigated through a composite algorithm using large-eddy simulations of oceanic and continental cases. The normalized magnitude is maximum near the cloud centre and decreases outwards. While relative humidity (RH) and cloud liquid water ( q l ) decrease smoothly to match the environment, the vertical velocity, virtual potential temperature (θ v ), and potential temperature (θ) perturbations have more complicated behaviour towards the cloud boundary. Below the inversion layer, θ' v becomes negative before the vertical velocity has turned from an updraft to a subsiding shell outside the cloud, indicating the presence of a transition zone where the updraft is negatively buoyant. Due to the downdraft outside the cloud and enhanced horizontal turbulent mixing across the edge, the normalized turbulent kinetic energy (TKE) and horizontal turbulent kinetic energy (HTKE) decrease more slowly from the cloud centre outwards than the thermodynamic variables. The distributions all present asymmetric structures in response to the vertical wind shear, with more negatively buoyant air, stronger downdrafts, and larger TKE on the downshear side. We discuss several implications of the distributions for theoretical models and parameterizations. Positive buoyancy near the cloud base is mostly due to the virtual effect of water vapour, emphasizing the role of moisture in triggering. The mean vertical velocity is found to be approximately half the maximum vertical velocity within each cloud, providing a constraint to achieve possible power-law distributions for some models. Finally, the normalized distributions for different variables are used to estimate the vertical heat and moisture fluxes within clouds. The results suggest that distributions near the cloud edge and variability of maximum perturbations need careful treatment. The fluxes are underestimated in the inversion layer because cloud-top downdrafts cannot be captured well.

54 ENVIRONMENTAL SCIENCES↗