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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗
NASA NTRS2015

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid

The development of a wholly superconducting turboelectric distributed propulsion system presents unique opportunities for the aerospace industry. However, this transition from normally conducting systems to superconducting systems significantly increases the equipment complexity necessary to manage the electrical power systems. Due to the low technology readiness level (TRL) nature of all components and systems, current Turboelectric Distributed Propulsion (TeDP) technology developments are driven by an ambiguous set of system-level electrical integration standards for an airborne microgrid system (Figure 1). While multiple decades' worth of advancements are still required for concept realization, current system-level studies are necessary to focus the technology development, target specific technological shortcomings, and enable accurate prediction of concept feasibility and viability. An understanding of the performance sensitivity to operating voltages and an early definition of advantageous voltage regulation standards for unconventional airborne microgrids will allow for more accurate targeting of technology development. Propulsive power-rated microgrid systems necessitate the introduction of new aircraft distribution system voltage standards. All protection, distribution, control, power conversion, generation, and cryocooling equipment are affected by voltage regulation standards. Information on the desired operating voltage and voltage regulation is required to determine nominal and maximum currents for sizing distribution and fault isolation equipment, developing machine topologies and machine controls, and the physical attributes of all component shielding and insulation. Voltage impacts many components and system performance.

electric faults↗
DOE OSTI2017

Same Precursor, Two Different Products: Comparing the Structural Evolution of In–Ga–O “Gel-Derived” Powders and Solution-Cast Films Using Pair Distribution Function Analysis

Amorphous metal oxides are central to a variety of technological applications. In particular, indium gallium oxide has garnered attention as a thin-film transistor channel layer material. In this work we examine the structural evolution of indium gallium oxide gel-derived powders and thin films using infrared vibrational spectroscopy, X-ray diffraction, and pair distribution function (PDF) analysis of X-ray total scattering from standard and normal incidence thin-film geometries (tfPDF). We find that the gel-derived powders and films from the same aqueous precursor evolve differently with temperature, forming mixtures of Ga-substituted In2O3 and In-substituted β-Ga2O3 with different degrees of substitution. X-ray total scattering and PDF analysis indicate that the majority phase for both the powders and films is an amorphous/nanocrystalline β-Ga2O3 phase, with a minor constituent of In2O3 with significantly larger coherence lengths. This amorphous β-Ga2O3 phase could not be identified using the conventional Bragg diffraction techniques traditionally used to study crystalline metal oxide thin films. The combination of Bragg diffraction and tfPDF provides a much more complete description of film composition and structure, which can be used to detail the effect of processing conditions and structure–property relationships. This study also demonstrates how structural features of amorphous materials, traditionally difficult to characterize by standard diffraction, can be elucidated using tfPDF.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Wasserstein normalized autoencoder for anomaly detection

A novel anomaly detection algorithm is presented. The Wasserstein normalized autoencoder (WNAE) is a normalized probabilistic model that minimizes the Wasserstein distance between the learned probability distribution—a Boltzmann distribution where the energy is the reconstruction error of the autoencoder (AE)—and the distribution of the training data. This algorithm has been developed and applied to the identification of semivisible jets—conical sprays of visible standard model (SM) particles and invisible dark matter states—with the CMS experiment at the CERN LHC. Trained on jets of particles from simulated SM processes, the WNAE is shown to learn the probability distribution of the input data in a fully unsupervised fashion, such that it effectively identifies new physics jets as anomalies. The model exhibits stable, convergent training and recovers strong classification performance for a wide range of signals against the selected background process, for which a standard AE fails because of outlier reconstruction. In addition, the model improves upon standard normalized autoencoders while remaining fully agnostic to the signal. The WNAE directly tackles the problem of outlier reconstruction, a common failure mode of autoencoders in anomaly detection tasks.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
NASA NTRS2015

Preferrential Concentration of Particles in Protoplanetary Nebula Turbulence

Preferential concentration in turbulence is a process that causes inertial particles to cluster in regions of high strain (in-between high vorticity regions), with specifics depending on their stopping time or Stokes number. This process is thought to be of importance in various problems including cloud droplet formation and aerosol transport in the atmosphere, sprays, and also in the formation of asteroids and comets in protoplanetary nebulae. In protoplanetary nebulae, the initial accretion of primitive bodies from freely-floating particles remains a problematic subject. Traditional growth-by-sticking models encounter a formidable "meter-size barrier" [1] in turbulent nebulae. One scenario that can lead directly from independent nebula particulates to large objects, avoiding the problematic m-km size range, involves formation of dense clumps of aerodynamically selected, typically mm-size particles in protoplanetary turbulence. There is evidence that at least the ordinary chondrite parent bodies were initially composed entirely of a homogeneous mix of such particles generally known as "chondrules" [2]. Thus, while it is arcane, turbulent preferential concentration acting directly on chondrule size particles are worthy of deeper study. Here, we present the statistical determination of particle multiplier distributions from numerical simulations of particle-laden isotopic turbulence, and a cascade model for modeling turbulent concentration at lengthscales and Reynolds numbers not accessible by numerical simulations. We find that the multiplier distributions are scale dependent at the very largest scales but have scale-invariant properties under a particular variable normalization at smaller scales.

protoplanetary nebulae↗
DOE OSTI2025

Factors controlling injection-induced rupture of intersecting faults during geological sequestration of CO 2

This study addresses coupled multiphase fluid flow and geomechanics effects on potential fault activation associated with subsurface CO 2 injection around intersecting faults. An enhanced fault-representation model is used to capture geomechanical responses of two intersecting faults with finite length during CO 2 injection. The faults are embedded in a strike-slip stress regime of a caprock-reservoir-basement system with the faults represented by zero-thickness interfaces with adjacent finite-thickness damage zones. A sensitivity analysis is conducted to study the effect of fault permeability, slip-weakening behavior, well location relative to the orientation of faults, and well placement (the number and location of injection wells). Five metrics (pressure, CO 2 plume, shear state on the fault, as well as shear displacement and stress path at selected fault monitoring points) are selected to assess CO 2 migration and reactivation of intersecting faults. The results show that induced ruptures are favored by low permeability faults due to high pressure buildup and by slip-weakening behavior resulting from fault strength reduction. The location of one injection well relative to fault orientation determines the magnitude of changes in effective normal stress and shear stress, affecting the location of induced ruptures. Well placement (two injection wells used in the paper) dominates pressure diffusion around the intersection and tips of faults. This redistributes changes in effective normal stress caused by each injection well, influencing the spatial distribution of ruptures along faults. A larger injection volume induces far-field ruptures that are controlled by stress transfer within the injection layer. The findings presented here can provide valuable insights into engineering operations for a long-term, safe, and reliable geologic CO 2 storage.

Fault permeability↗
DOE OSTI2018

Scaling laws for the additive manufacturing

The evaluation of simple thermal model of selective laser melting (SLM) process shows that the temperature distribution in the sample is characterized by two dimensionless parameters: normalized enthalpy and the ratio of dwell time to the thermal diffusion time. Here we demonstrated that the melt depth data taken for different machines for different materials collapsed in one curve, making possible to rescale the optimal processing parameters between the different materials and machines. The melt pool depth, width and the length are the universal function of these two parameters. Within the operational range of parameters for SLM these functions can be interpolated by the simple algebraic expressions given the possibility to reduce the calculation of the melt pool characteristic to spreadsheet model.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Predicting properties of gas and solid streams by intrinsic kinetics of fast pyrolysis of wood

Pyrolysis has the potential to create a biocrude oil from biomass sources that can be used as fuel or as feedstock for subsequent upgrading to hydrocarbon fuels or other chemicals. The product distribution/composition, however, is linked to the biomass source. This work investigates the products formed from pyrolysis of woody biomass with a previously developed chemical kinetics model. Different woody feedstocks reported in prior literature are placed on a common basis (moisture, ash, fixed carbon free) and normalized by initial elemental composition through ultimate analysis. Observed product distributions over the full devolatilization range are explored, reconstructed by the model, and verified with independent experimental data collected with a microwave-assisted pyrolysis system. These trends include production of permanent gas (CO, CO 2 ), char, and condensable (oil, water) species. Elementary compositions of these streams are also investigated. As a result, close agreement between literature data, model predictions, and independent experimental data indicate that the proposed model/method is able to predict the ideal distribution from fast pyrolysis given reaction temperature, residence time, and feedstock composition.

09 BIOMASS FUELS↗
DOE OSTI2022

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Theoretical analysis of the background intensity distribution in X-ray Birefringence Imaging using synchrotron bending-magnet radiation

In the recently developed technique of X-ray Birefringence Imaging, molecular orientational order in anisotropic materials is studied by exploiting the birefringence of linearly polarized X-rays with energy close to an absorption edge of an element in the material. In the experimental setup, a vertically deflecting high-resolution double-crystal monochromator is used upstream from the sample to select the appropriate photon energy, and a horizontally deflecting X-ray polarization analyzer, consisting of a perfect single crystal with a Bragg reflection at Bragg angle of approximately 45°, is placed downstream from the sample to measure the resulting rotation of the X-ray polarization. However, if the experiment is performed on a synchrotron bending-magnet beamline, then the elliptical polarization of the X-rays out of the electron orbit plane affects the shape of the output beam. Also, because the monochromator introduces a correlation between vertical position and photon energy to the X-ray beam, the polarization analyzer does not select the entire beam, but instead selects a diagonal stripe, the slope of which depends on the Bragg angles of the monochromator and the polarization analyzer. In the present work, the final background intensity distribution is calculated analytically because the phase space sampling methods normally used in ray traces are too inefficient for this setup. X-ray Birefringence Imaging data measured at the Diamond Light Source beamline B16 agree well with the theory developed here.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A forward modeling approach to analyzing galaxy clustering with S IM BIG

We present cosmological constraints from a simulation-based inference (SBI) analysis of galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the predictive power of high-fidelity simulations and provides an inference framework that can extract cosmological information on small nonlinear scales. In this work, we apply SimBIG to the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample and analyze the power spectrum, P ℓ (k), to k max = 0.5 h/Mpc. We construct 20,000 simulated galaxy samples using our forward model, which is based on 2,000 high-resolution Quijote N -body simulations and includes detailed survey realism for a more complete treatment of observational systematics. We then conduct SBI by training normalizing flows using the simulated samples and infer the posterior distribution of ΛCDM cosmological parameters: Ω m , Ω b , h, n s , σ 8 . We derive significant constraints on Ω m and σ 8 , which are consistent with previous works. Our constraint on σ 8 is 27% more precise than standard P ℓ analyses because we exploit additional cosmological information on nonlinear scales beyond the limit of current analytic models, k > 0.25 h/Mpc. This improvement is equivalent to the statistical gain expected from a standard P ℓ analysis of galaxy sample ~ 60% larger than CMASS. While we focus on P ℓ in this work for validation and comparison to the literature, SimBIG provides a framework for analyzing galaxy clustering using any summary statistic. We expect further improvements on cosmological constraints from subsequent SimBIG analyses of summary statistics beyond P ℓ .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Characteristics of He ii proximity profiles

The proximity profile in the spectra of z≈3 quasars, where fluxes extend blueward of the He ii Lyα wavelength 304 (1+z) Å, is one of the most important spectral features in the study of the intergalactic medium (IGM). Based on the Hubble Space Telescope spectra of 24 He ii quasars, we find that the majority of them display a proximity profile, corresponding to an ionization radius as large as 20 Mpc in the source's rest frame. In comparison with those in the H i spectra of the quasars at z ≈ 6, the He ii proximity effect is more prominent and is observed over a considerably longer period of reionization. The He ii proximity zone sizes decrease at higher redshifts, particularly at z>3.3. This trend is similar to that for H i, signaling an onset of He ii reionization at z≳4. For quasar SDSS1253+6817 (z = 3.48), the He ii absorption trough displays a gradual decline and serves as a good case for modeling the He ii reionization. To model such a broad profile requires a quasar radiation field whose energy distribution between 4 and 1 Rydberg is considerably harder than normally assumed. The UV continuum of this quasar is indeed exceptionally steep, and the He ii ionization level in the quasar vicinity is higher than the average level in the IGM. These results are evidence that a very hard EUV continuum from this quasar produces a large ionized zone around it. Distinct exceptions are the two brightest He ii quasars at z ≈ 2.8, for which no significant proximity profile is present, probably implying that they are very young.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Plasma-arc lamp high heat flux cycling exposure of neutron irradiated tungsten materials

Thick plate, unalloyed W was neutron irradiated in the High Flux Isotope Reactor (HFIR) at 550 °C to a fast fluence of 1.24 × 10 25 n m -2 E > 0.1 MeV (~0.24 dpa). Unirradiated and irradiated specimens of the material were high heat flux (HHF) tested in the Plasma Arc Lamp (PAL) facility. The PAL uses a high-power photon source to provide a broad and even heat distribution on the sample surface. To simulate on/off cycling of normal operating plasma, the samples were exposed to approximately 800 cycles at 4.73 MW m -2 absorbed heat flux (incident heat fluxes of 10.95 MW m -2 ). Additionally, after PAL exposure, slight changes were observed on the surfaces of the samples with SEM. The samples showed some annealing in the near surface polished region, but they were all below the damage threshold for cracking or other destructive features. The PAL has a large parameter space for future testing. The use of the HFIR and PAL to sequentially expose neutron irradiated samples to HHF will be a powerful tool for understanding materials behavior in a fusion-like environment.

36 MATERIALS SCIENCE↗
DOE OSTI2015

γ decay from the quasicontinuum of 197,198 Au

Here, the average electromagnetic dipole response of levels in the quasicontinuum of 197,198 Au has been measured using ( 3 He, 3 He') and (d,p) reactions. The extracted γ-ray strength functions have been normalized according to three model assumptions for the nuclear spin distribution. An enhancement in the energy region E γ = 3.0–6.5 MeV is observed for both isotopes. The E1 component of such excess of strength is studied in detail for 198 Au and is interpreted as the pygmy dipole resonance with an energy centroid of 5.9(1) MeV and exhausts about 1% of the total integrated strength. The pygmy dipole resonance is shown to have a significant impact on the calculated 197 Au(n,γ) 198 Au cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Constraints on dark photon dark matter from Lyman- α forest simulations and an ultrahigh signal-to-noise quasar spectrum

The ultralight dark photon is a well-motivated, hypothetical dark matter candidate. In a dilute plasma, they can resonantly convert into photons, and heat up the intergalactic medium between galaxies. In this work, we explore the dark photon dark matter parameter space by comparing synthetic Lyman- α forest data from cosmological hydrodynamical simulations to observational data from VLT/UVES of the quasar HE0940-1050 ( z em = 3.09 ). We use a novel flux normalization technique that targets underdense gas, reshaping the flux probability distribution. Not only do we place robust constraints on the kinetic mixing parameter of dark photon dark matter, but notably our findings suggest that this model can still reconcile simulated and observed Doppler parameter distributions of z ∼ 0 Lyman- α lines, as seen by HST/COS. This work opens new pathways for the use of the Lyman- α forest to explore new physics, and can be extended to other scenarios such as primordial black hole evaporation, dark matter decay, and annihilation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Wake loss and energy spread factor of the LEReC Booster cavity caused by short range wake field

LEReC project uses a DC photoemission gun with multi-alkali (CsK 2 Sb or NaK 2 Sb) cathode [1]. To get 24 mm “flat-top” distribution, 32 Gaussian laser bunches with 0.6 mm rms length are stacked together with 0.75 mm distance [2]. In this case one cannot simply use a 1 cm rms length Gaussian/step/delta bunch for short range wake field simulation since a 0.6 mm bunch contains frequency much higher than the 1 cm bunch. A short range wake field simulation was done using CST Particle Studio™ with 0.6 mm rms Gaussian bunch at the speed of light, and this result was compared with the result for 1 cm rms Gaussian bunch in Figure 1, from where one notice that the wake potential for the 0.6 mm bunch is ~10 times higher than that of the 1 cm bunch. The wake potential of the 0.6 mm bunch, as well as the charge distribution, was then “shift and stack” every 0.75 mm, the normalized results are shown in Figure 2. The wake loss factor (WLF) is the integration of the product of wake potential and normalized bunch charge, and the energy spread factor (ESF) is the rms deviation from the average energy loss. It is calculated by summing the weighted squares of the differences and taking the square root of the sum. These two factors were then divided by β 2 for 1.6 MV beam energy. The wake loss factor is at 0.86 V/pC and energy spread factor is at 0.54 V/pC rms. With 100 pC electron bunch, the energy spread inter-bunch is 54 V rms.

43 PARTICLE ACCELERATORS↗