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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Microfabricated Devices and Ion Trapping Capabilities

Next generation ion traps will likely need to support tens if not hundreds of ions in order to achieve several logical qubits. As we scale to those sizes, the same problems we face now – rf dissipation, control I/O, and optical access – will only grow and become more complicated. While many of these challenges can potentially be solved with technology integration, independently researching the feasibility of that integration and other solutions may help reduce the time and risk in scaling up to larger traps, by testing on smaller less complex devices. We should also consider other fabrication techniques that may help scale to larger devices, such as: through-substrate-vias (TSVs), different metal coatings, exotic rf routing, on chip laser sources, or even a secondary macroscopic trap to reload ions from. To have these technologies ready for full scale integration when we need them, ion traps with some of these capabilities need to be produced now. Developing the rigorous fabrication methods for producing reliable traps takes time and experimentation. We propose developing larger ion traps and reliable integrated technology in conjunction to make both available faster.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Contribution of Lobe Power to Experiment Heating in the Advanced Test Reactor

In order to ease the computational burden associated with designing irradiation experiments in the Advanced Test Reactor (ATR), scaling factors are often used to estimate design parameters at different lobe powers. Here, this paper examines the validity of long-standing assumptions about the contribution of lobe power to total experiment heating in the ATR. For each of the ATR’s 77 different experiment positions, the fractional contribution of each of the ATR’s five lobes to the total heating in that position is calculated and compared to traditional assumptions. The updated fractional contributions are then used to scale heating rates in a sample problem, and the results are compared to traditional scaling methods as well as explicit MC21 heating calculations. It is concluded that for experiment locations in close proximity to the ATR driver fuel (i.e. flux traps and the A, H, and B positions), heating rates scaled with the updated fractional contributions generally agree better with explicit MC21 calculations than do heating rates scaled using the traditionally assumed contributions. For the I positions, which are located on the very periphery of the ATR core, both scaling methods led to poor results when compared against explicit calculations due to the effect that movement of the outer shim control cylinders has on the experiment heating in those positions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Towards quantifying the impact of triaxiality on optical signatures of galaxy clusters: weak lensing and galaxy distributions

ABSTRACT We present observational evidence of the impact of triaxiality on radial profiles that extend to 40 Mpc from galaxy cluster centres in optical measurements. We perform a stacked profile analysis from a sample of thousands of nearly relaxed galaxy clusters from public data releases of the Dark Energy Survey and the Dark Energy Camera Legacy Survey. Using the central galaxy elliptical orientation angle as a proxy for galaxy cluster orientation, we measure cluster weak lensing and excess galaxy density axis-aligned profiles, extracted along the central galaxy’s major or minor axes on the plane of the sky. Our measurements show a ≳ 2σ–3σ difference per radial bin between the normalized axis-aligned profiles. The profile difference between each axis-aligned profile and the azimuthally averaged profile ($\sim \pm 10\,\rm per\ cent-20~{{\ \rm per\ cent}}$ along major/minor axis) appears inside the clusters (∼0.4 Mpc) and extends to the large-scale structure regime (∼10–20 Mpc). The magnitude of the difference appears to be relatively insensitive to cluster richness and redshift, and extends further out in the weak lensing surface mass density than in the galaxy overdensity. Looking forward, this measurement can easily be applied to other observational or simulation data sets and can inform the systematics in cluster mass modelling related to triaxiality. We expect imminent upcoming wide-area deep surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, to improve our quantification of optical signatures of cluster triaxiality.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Radiance-based NIR v as a proxy for GPP of corn and soybean

Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIR v,Rad ), defined as the product of observed NIR radiance and normalized difference vegetation index (NDVI), can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIR v,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIR v,Ref ), enhanced vegetation index (EVI), and far-red solar-induced fluorescence (SIF760). The strong linear relationship between NIR v,Rad and absorbed photosynthetically active radiation by green leaves (APAR green ), and that between APAR green and GPP, explain the good NIR v,Rad -GPP relationship. The NIR v,Rad -GPP relationship is robust and consistent across sites. The scalability and simplicity of NIR v,Rad indicate a great potential to estimate daily or sub-daily GPP from high-resolution and/or long-term satellite remote sensing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Explosive Yield Estimation Using Regional Seismic Moment Tensors

Here, we use the Pasyanos and Chiang (2022) data set to calculate the seismic moment M 0 for each explosion and use the measured explosive yield W to validate the W~M 0 relationship in Denny and Johnson (1991; hereafter, DJ91). The M 0 is corrected by transforming to a potency tensor and applying more appropriate near-source geophysical parameter values in the moment estimate. The mean residual between observed and predicted yield is near zero; however, the standard deviation of the residuals results in an F-value (a 95% confidence factor) of about 5. We re-estimate the coefficients in the DJ91 model and find similar values and only a slight improvement in the F-value. Next, we embark on a similar model selection process as DJ91, allowing for non-cube-root yield scaling and other plausible near-source elastic moduli. As was found by DJ91, the yield dependence is not significantly different from unity, and a cube root assumption is valid. Therefore, we yield scale the seismic moment and test the significance of all plausible explanatory variables. Isotropic moment performs better in the response variable than total moment. The preference for isotropic moment could be due to its relationship to volume change, which would be more directly affected by explosive yield. Surprisingly, we find that the overburden pressure, which is a function of depth, is not a significant parameter in the model. We hypothesize that this is due to the competing depth effects on source asymmetry and the incorporation of depth in the Green’s functions used to calculate the seismic moment tensors. Importantly, this emphasizes that only seismic moment tensor-derived moments should be used in these models. After removing insignificant model parameters, we are left with a simple model to predict explosive yield $\widehat{W}$ in kt from isotropic moment M I in N·m, $\widehat{W}$=κ –1.4132 10 0.035626GP M I , in which κ and GP are the near-source bulk modulus and gas porosity in Pa and %, respectively. The F-value for this model is approximately 3.

58 GEOSCIENCES↗
DOE OSTI2020

Fine structure of the isovector giant dipole resonance in Nd 142 – 150 and Sm 152

Inelastic proton scattering at energies of a few hundred MeV and very-forward scattering angles including 0° has been established as a tool for the study of electric-dipole strength distributions in nuclei. The present work reports a systematic investigation of the chain of stable even-mass Nd isotopes representing a transition from spherical to quadrupole-deformed nuclei. Extraction of the equivalent photo-absorption cross sections and analysis of their fine structure in the energy region of the isovector giant dipole resonance (IVGDR). Method: Proton inelastic scattering reactions of 200 MeV protons were measured at the iThemba Laboratory for Accelerator Based Sciences in Cape Town, South Africa. The scattering products were momentum-analyzed by the K600 magnetic spectrometer positioned at θ Lab = 0°. Using dispersion-matching techniques, energy resolutions of ΔE ≈ 40–50 keV (full width at half maximum) were obtained. After subtraction of background and contributions from other multipoles, the spectra were converted to photoabsorption cross sections using the equivalent virtual-photon method. Wavelet-analysis techniques are used to extract characteristic energy scales of the fine structure of the IVGDR from the experimental data. Fine structure of the IVGDR is observed even for the most deformed nuclei studied. Comparisons between the extracted experimental energy scales and those energy scales obtained from the quasiparticle-phonon model (QPM) and Skyrme separable random phase approximation (SSRPA) predictions provide insight into the role of different giant-resonance damping mechanisms. It can be seen that the scales in the spherical and most likely also in the deformed nuclei mainly result from the fragmentation of the one-particle-one-hole (1p1h) strength into several dominant transitions serving as doorway states. In cases where calculations beyond the 1p1h level are available, some impact of the spreading due to coupling of the two-particle-two-hole (2p2h) states to the 1p1h doorway states is observed. New virtual-photon absorption data for the chain of stable Nd isotopes and 152 Sm are presented, with a focus on the phenomenon of nonstatistical cross-section fluctuations, referred to as fine structure, in the energy region of the IVGDR. The wavelet-analysis techniques used allowed for the features of the fine structure to be quantified in the form of characteristic scales. Finally, comparisons between experimental results and model predictions indicate that Landau damping seems to be the main source of the fine structure in both the spherical and deformed nuclei, but calculations including 2p2h degrees of freedom would be beneficial to confirm this for the deformed cases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Electronic structure prediction of multi-million atom systems through uncertainty quantification enabled transfer learning

The ground state electron density — obtainable using Kohn-Sham Density Functional Theory (KS-DFT) simulations — contains a wealth of material information, making its prediction via machine learning (ML) models attractive. However, the computational expense of KS-DFT scales cubically with system size which tends to stymie training data generation, making it difficult to develop quantifiably accurate ML models that are applicable across many scales and system configurations. Here, we address this fundamental challenge by employing transfer learning to leverage the multi-scale nature of the training data, while comprehensively sampling system configurations using thermalization. Our ML models are less reliant on heuristics, and being based on Bayesian neural networks, enable uncertainty quantification. We show that our models incur significantly lower data generation costs while allowing confident — and when verifiable, accurate — predictions for a wide variety of bulk systems well beyond training, including systems with defects, different alloy compositions, and at multi-million-atom scales. Moreover, such predictions can be carried out using only modest computational resources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Integrating AI with physics-based hydrological models and observations for insightinto changing climate and anthropogenic impacts

Focal Areas: Advanced computational methods that integrate AI, physics, and observations to provide predictive landscape hydrological modeling over large areas (regional, continental, worldwide) while incorporating increasingly available high-resolution data from drones, lidar and satellite. Science Challenge: Landscape data is available at finer scales than can be used in physics-based hydrological (PBH) models for regional or continental terrestrial water modeling. Thus, we throw away observable detail to achieve computability. We argue that integration of AI with PBH models and observed data can be used to provide upscaling for predictive models that are computable, retain physical conservation properties, and represent the fine-scale features that affect complex flow physics through both natural and urban environments. Developing such next-generation capabilities requires outside-the-box thinking that melds the different approaches of AI modeling, PBH modeling, and observation across multiple scales from local drones to satellites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Translating dosimetry of Dibenzo[ def,p ]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling

We report that Dibenzo[def,p]chrysene (DBC) is an environmental polycyclic aromatic hydrocarbon (PAH) that causes tumors in mice and has been classified as a probable human carcinogen by the International Agency for Research on Cancer. Animal toxicity studies often utilize higher doses than are found in relevant human exposures. Additionally, like many PAHs, DBC requires metabolic bioactivation to form the ultimate toxicant, and species differences in DBC and DBC metabolite metabolism have been observed. To understand the implications of dose and species differences, a physiologically based pharmacokinetic model (PBPK) for DBC and major metabolites was developed in mice and humans. Metabolism parameters used in the model were obtained from experimental in vitro metabolism assays using mice and human hepatic microsomes. PBPK model simulations were evaluated against mice dosed with 15 mg/kg DBC by oral gavage and human volunteers orally microdosed with 29 ng of DBC. DBC and its primary metabolite DBC-11,12-diol were measured in blood of mice and humans, while in urine, the majority of DBC metabolites were obeserved as conjugated DBC-11,12-diol, conjugated DBC tetrols, and unconjugated DBC tetrols. The PBPK model was able to predict the time course concentrations of DBC, DBC-11,12-diol, and other DBC metabolites in blood and urine of human volunteers and mice with reasonable accuracy. Agreement between model simulations and measured pharmacokinetic data in mice and human studies demonstrate the success and versatility of our model for interspecies extrapolation and applicability for different doses. Furthermore, our simulations show that internal dose metrics used for risk assessment do not necessarily scale allometrically, and that PBPK modeling provides a reliable approach to appropriately account for interspecies differences in metabolism and physiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

On the cogent formulation of an elastomeric silicone ink material for direct ink write ( DIW ) 3D printing

Abstract Adhesives and sealants show fine rheology with good physical and mechanical properties as viscous pastes, a possible starting point for developing direct ink writing (DIW) 3D printing ink. However, many commercial adhesives and sealants take days or weeks to cure fully. DIW 3D‐printed parts made directly from these sealants are not designed for a scalable manufacturing process and high‐volume production. Moreover, most of these adhesives and sealants have volume shrinkage during cure. A systematic understanding of formulation methods and design principles for an elastomeric silicone DIW ink can overcome these issues. This study presents the cogent formulation development of a 3D printable thermoset elastomer silicone that gels and cures isotropically in minutes, reducing cycle time for rapid ink development with no shrinkage during cure. More specifically, we outline the principles of raw material selection of a formulation to achieve excellent rheology, printability, synchronized working, and gel time fitting requirements closer to scalable manufacturing. The reaction kinetics and their corresponding 3D‐printed structural properties are also described. Interest in future work is toward a rational DIW 3D printing ink material development protocol and use of machine learning (ML). Highlights Formulation method flexibility and design principle of DIW ink. Raw material selection principle to achieve optimal rheology for DIW printing. Ink gel kinetics for large‐scale DIW manufacturing. Hydrosilylation conversion over time at different ambient temperatures. Structural properties of DIW 3D printed parts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Continuous and discrete modeling of HIV-1 decline on therapy

Mathematical models have shed light on the dynamics of HIV- 1 infection in vivo. In this paper, we generalize continuous mathematical models of drug therapy for HIV-1 by Perelson et al. (Science 271:1582–1586, 1996) and Perelson and Nelson (SIAM Rev 41:3–44, 1999) on time scales, i.e., a nonempty closed subset of real numbers in order to derive new discrete models that predict the total concentration of plasma virus as a function of time. Here, one of our main goals is to compare discrete mathematical models with the continuous model in Perelson et al. (1996) where HIV infected patients were given protease inhibitors and sampled frequently thereafter. For the comparison, we use experimental data collected in Perelson et al. (1996) and estimate the parameters such as the virion clearance rate and the rate of loss of infected cells by fitting the total concentration of plasma virus to this data set. Our results show that discrete systems describe the best fit. In the previous models of this study, the efficacy of protease inhibitor is assumed to be perfect. Motivated by Perelson and Nelson (1999), we end the paper with a mathematical model of imperfect protease inhibitor and reverse transcriptase (RT) inhibitor combination therapy of HIV-1 infection on time scales with its stability analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO 2 ) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO 2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO 2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO 2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Experiments and CFD simulation of mass transfer and hydrodynamics in a cylindrical bubble column

Flow visualization, Particle Image Velocimetry (PIV) and dissolved oxygen charging experiments are carried out in a small-scale cylindrical air-water bubble column at different superficial gas velocities. Void fraction profile, total gas holdup, liquid phase velocity field and volumetric mass transfer coefficient are obtained. Details of each experiment are given, with a new procedure for obtaining a 2D void fraction profile from flow visualization by image processing and time averaging which could provide useful information for CFD model validation. The experimental results are analyzed and compared with simulations where good agreement is found for both local and global flow patterns. The averaged governing equations and constitutive relations used in the simulation are discussed briefly, with emphasis on the proper comparison between simulations and experiments based on the derivation of the two-fluid model. Finally, by conducting three sets of experiments related to phase distribution, velocity field and mass transfer in the same apparatus, a validated CFD model for multiphase mass transfer is established and can be used in the future design of a multi-phase reactor.

42 ENGINEERING↗
DOE OSTI2023

On the role of methyl groups in the molecular architectures of mesophase pitches

The role of methyl groups on the liquid–crystal structure of mesophase pitches was investigated by combining experimental characterizations and atomic-scale computational modeling, using three pitches synthesized from different precursors. Of the three pitches, C-9 alkyl benzene and naphthalene-based pitches have 13 and 7 methyl groups per average polyaromatic hydrocarbon, respectively. By contrast, mesophase produced from a coal-tar pitch has about one methyl group. The coal tar–based mesophase pitch is hydrogen deficient or more aromatic compared with C-9 alkyl benzene- and naphthalene-based pitches. Additionally, X-ray diffraction data showed that average coherent domain sizes of C-9 alkyl benzene (3.7 nm) and naphthalene-based (3.6 nm) pitches with more methyl groups are larger than that of coal tar–based mesophase (2.4 nm). Based on the identified features, the influence of the methyl group on the layering structures was investigated via molecular dynamics simulations. The results revealed that methyl groups are critical in mesophase layering in C-9 alkyl benzene- and naphthalene-based pitches, by reducing CH-π interaction. However, similar alignment could be achieved without the same degree of methyl substitutions for the coal tar-based pitch because of stronger π-π interaction than the other precursors. The insights from this study contribute to our understanding of the formation of conventional mesophase pitch and have implications for the processing of coal-derived materials. In conclusion, this knowledge is vital to produce valuable products like carbon fiber and graphite from pitches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effects of surface runoff and infiltration partition methods on hydrological modeling: A comparison of four schemes in two watersheds in the Northeastern US

The ratio according to which the precipitation/snowmelt is divided into surface and subsurface water is of primary importance to watershed scale hydrological modeling. The present study compared four different surface runoff and infiltration partition methods in the Richards-equation-based SWAT model (RSWAT), i.e., daily curve number method (DC-RSWAT), hourly curve number method (HC-RSWAT), Green-Ampt method (GA-RSWAT), and effective infiltration capacity method (EIC-RSWAT). These four versions of RSWAT and a daily-curve-number-based SWAT (DC-SWAT) were used to simulate daily flow rate (from 2001 to 2015) at the outlets of the Tuckahoe Creek Watershed (TCW) and Greensboro Watershed (GW) of the Chesapeake Bay in Maryland. Parameter sensitivity analysis, calibration, and prediction uncertainty analysis were conducted. The results indicate that surface runoff and infiltration partition methods have pronounced impacts on model performance. Comparative analysis showed that DC-RSWAT outperformed other versions of RSWAT for both calibration (from 2001 to2007) and validation (from 2008 to 2015) periods in the two test watersheds. In general, DC-RSWAT achieved more accurate deterministic flow simulation and reliable uncertainty estimation than other versions. As such, daily-curve-number method is recommended for surface runoff and infiltration partition in RSWAT for simulating stream flow.

hydrology, modeling, streamflow↗
DOE OSTI2023

More is definitely different: the zebrafish as witness: Comment on ”Structure and function in artificial, zebrafish and human neural networks” by Peng Ji et al.

We report half a century ago, in his foundation paper More is different, Anderson stated the relevance of including multiple scales of interaction, instead of trying to reduce everything to fundamental principles. By doing so, one may witness phenomena that were not expected by looking at each individual components separately. This idea finds indeed numerous realizations such as the synchronization phenomenon, where a multitude of dynamical systems suddenly start to behave coherently together, or the spreading of diseases over entire populations, to name only two examples. But if one would have to give a single example of a system where the multiplicity of interaction scales is of utmost importance, it would probably be the brain. In their review, Ji et al. give a comprehensive overview of the multiple scales of science required in the investigation of structural and functional brain networks, as well as their interplay.

59 BASIC BIOLOGICAL SCIENCES↗