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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Accurate small and wide angle x-ray scattering profiles from atomic models of proteins and nucleic acids

A new method is introduced to compute X-ray solution scattering profiles from atomic models of macromolecules. The three-dimensional version of the Reference Interaction Site Model (RISM) from liquid-state statistical mechanics is employed to compute the solvent distribution around the solute, including both water and ions. X-ray scattering profiles are computed from this distribution together with the solute geometry. We describe an efficient procedure for performing this calculation employing a Lebedev grid for the angular averaging. The intensity profiles (which involve no adjustable parameters) match experiment and molecular dynamics simulations up to wide angle for two proteins (lysozyme and myoglobin) in water, as well as the small-angle profiles for a dozen biomolecules taken from the BioIsis.net database. The RISM model is especially well-suited for studies of nucleic acids in salt solution. Use of fiber-diffraction models for the structure of duplex DNA in solution yields close agreement with the observed scattering profiles in both the small and wide angle scattering (SAXS and WAXS) regimes. In addition, computed profiles of anomalous SAXS signals (for Rb{sup +} and Sr{sup 2+}) emphasize the ionic contribution to scattering and are in reasonable agreement with experiment. In cases where an absolute calibration of the experimental data at q = 0 is available, one can extract a count of the excess number of waters and ions; computed values depend on the closure that is assumed in the solution of the Ornstein–Zernike equations, with results from the Kovalenko–Hirata closure being closest to experiment for the cases studied here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Molecular dynamic simulation of Ar-Kr mixture across a rough walled nanochannel: Velocity and temperature profiles

This paper presents the results from a molecular dynamics simulation of mixture of argon and krypton in the Poiseuille flow across a rough walled nanochannel. The roughness effect on liquid nanoflows has recently drawn attention The computational software used for carrying out the molecular dynamics simulations is LAMMPS. The fluid flow takes place between two parallel plates and is bounded by horizontal rough walls in one direction and periodic boundary conditions are imposed in the other two directions. Each fluid atom interacts with other fluid atoms and wall atoms through Leenard-Jones (LJ) potential with a cut off distance of 5.0. To derive the flow a constant force is applied whose value is varied from 0.1 to 0.3 and velocity profiles and temperature profiles are noted for these values of forces. The velocity profile and temperature profiles are also looked at different channel widths of nanochannel and at different densities of mixture. The velocity profile and temperature profile of rough walled nanochannel are compared with that of smooth walled nanochannel and it is concluded that mean velocity increases with increase in channel width, force applied and decrease in density also with introduction of roughness in the walls of nanochannel mean velocity again increases and results also agree with the analytical solution of a Poiseuille flow.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Extension of the flux fit method for estimating power deposition profiles

The flux fit method is used to self-consistently estimate the power deposition profile and heat transport profiles from temperature measurements originating from perturbative experiments with a modulated source. Furthermore, this letter improves on this method by addressing the limitations and assumptions. The most crucial improvement is the additional freedom in the source deposition profile. Allowing for a variable central deposition location and height and including a skewness parameter produces deposition profiles more consistent with the measurement data, but still wider than equilibrium ray tracing in two different DIII-D discharges. Moreover, we show that the quality of the estimated deposition profile is key to the accuracy of diffusivity and connectivity estimates, but inversely, the estimated transport parameters hardly affect the quality of the power deposition estimate. Using this method, we show that the power deposition profile estimate is broadened with respect to ray-tracing by about 1.7-1.8 times in two DIII-D discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Galaxy cluster profiles: a Gaussian mixture model approach to halo miscentering

Measurements of the galaxy density and weak-lensing profiles of galaxy clusters typically rely on an assumed cluster center, which is taken to be the brightest cluster galaxy or other proxies for the true halo center defined as the minimum in the potential well. Departure of the assumed cluster center from the true halo center bias the resultant profile measurements, an effect known as miscentering bias. Currently, miscentering is typically modeled in stacked profiles of clusters with a two parameter model. We use an alternate approach in which the profiles of individual clusters are used with the corresponding likelihood computed using a Gaussian mixture model. We test the approach using halos and the corresponding subhalo profiles from the IllustrisTNG hydrodynamic simulations. We obtain significantly improved estimates of the miscentering parameters for both 3D and projected 2D profiles relevant for imaging surveys. We discuss applications to upcoming cosmological surveys. Our Python package for the Gaussian mixture model is publicly available at https://github.com/KyleMiller1/Halo-Miscentering-Mixture-Model.

Bayesian reasoning↗
DOE OSTI2021

Prediction of electron density and pressure profile shapes on NSTX-U using neural networks

A new model for prediction of electron density and pressure profile shapes on NSTX and NSTX-U has been developed using neural networks. The model has been trained and tested on measured profiles from experimental discharges during the first operational campaign of NSTX-U. By projecting profiles onto empirically derived basis functions, the model is able to efficiently and accurately reproduce profile shapes. In order to project the performance of the model to upcoming NSTX-U operations, a large database of profiles from the operation of NSTX is used to test performance as a function of available data. The rapid execution time of the model is well suited to the planned applications, including optimization during scenario development activities, and real-time plasma control. Finally, a potential application of the model to real-time profile estimation is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction

Burning plasma performance, transport, and the effect of hydrogen isotope (H, D, D-T fuel mix) on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73), were used to predict profiles of T i , T e , and n e while including the effects of alpha heating, auxiliary power (NBI + ECH), collisional energy exchange, and radiation losses inside of $r/a$ = 0.9. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals ($P_\textrm{fusion} = 500$ MW at Q = 10) for the baseline scenario and exhibit energy confinement that is within 1σ of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential resonant magnetic perturbation (RMP) effects on performance with a minimal number of gyrokinetic profile iterations required (3–6). These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that $Q \gt$ 17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in IBS conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.

gyrokinetics↗
DOE OSTI2023

Towards the extraction of the crystal cell parameters from pair distribution function profiles

The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques. The procedure has been validated on a large number of PDF profiles calculated from known crystal structures and on a small number of measured PDF profiles. The lattice determination step has been benchmarked by a comprehensive exploration of different classifiers and different input data. The highest performance is obtained using the k -nearest neighbours classifier applied to whole PDF profiles. Descriptors calculated from the PDF profiles by recurrence quantitative analysis produce results that can be interpreted in terms of PDF properties, and the significance of each descriptor in determining the prediction is evaluated. The cell parameter extraction step depends on the cell metric rather than its type. Monometric, dimetric and trimetric cells have top-1 estimates that are correct 40, 20 and 5% of the time, respectively. Promising results were obtained when analysing real nanocrystals, where unit cells close to the true ones are found within the top-1 ranked solution in the case of monometric cells and within the top-6 ranked solutions in the case of dimetric cells, even in the presence of a crystalline impurity with a weight fraction up to 40%.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Impact of a Faster Thermal Cycling Profile on PV Cell Interconnect Cycles to Failure

The thermal cycling tests used in the photovoltaic industry are slow, requiring over a month for 200 cycles and five months for 800 cycles. A faster alternative would reduce the cost of delay for module qualification. This study investigates the correlation between a baseline thermal cycling profile and profiles that are three and six times faster. Interconnect failure data for each profile was gathered across eight splits of varying material combinations. Models were applied to the failure data and factors which impacted interconnect lifetime were identified. Here, the results show that more cycles were required in the faster profiles for equivalency to the baseline profile. Furthermore, the equivalent number of cycles varied by a factor of two across the splits. Despite these limitations, the faster profiles offer substantial qualification time savings if the underlying failure mechanisms are understood.

14 SOLAR ENERGY↗
DOE OSTI2014

SU-E-J-121: Measuring Prompt Gamma Emission Profiles with a Multi-Stage Compton Camera During Proton Beam Irradiation: Initial Studies

Purpose: Recent studies have suggested that the characteristics of prompt gammas (PG) emitted during proton beam irradiation are advantageous for determining beam range during treatment delivery. The purpose of this work was to determine the feasibility of determining the proton beam range from PG data measured with a prototype Compton camera (CC) during proton beam irradiation. Methods: Using a prototype multi-stage CC the PG emission from a water phantom was measured during irradiation with clinical proton therapy beams. The measured PG emission data was used to reconstruct an image of the PG emission using a backprojection reconstruction algorithm. One dimensional (1D) profiles extracted from the PG images were compared to: 1) PG emission data measured at fixed depths using collimated high purity Germanium and Lanthanum Bromide detectors, and 2) the measured depth dose profiles of the proton beams. Results: Comparisons showed that the PG emission profiles reconstructed from CC measurements agreed very well with the measurements of PG emission as a function of depth made with the collimated detectors. The distal falloff of the measured PG profile was between 1 mm to 4 mm proximal to the distal edge of the Bragg peak for proton beam ranges from 4 cm to 16 cm in water. Doses of at least 5 Gy were needed for the CC to measure sufficient data to image the PG profile and localize the distal PG falloff. Conclusion: Initial tests of a prototype CC for imaging PG emission during proton beam irradiation indicated that measurement and reconstruction of the PG profile was possible. However, due to limitations of the operational parameters (energy range and count rate) of the current CC prototype, doses of greater than a typical treatment dose (∼2 Gy) were needed to measure adequate PG signal to reconstruct viable images. Funding support for this project provided by a grant from DoD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

TH-CD-207B-05: Measurement of CT Bow-Tie Profiles Using a Linear Array Detector

Purpose: To accurately measure CT bow-tie profiles from various manufacturers and to provide non-proprietary information for CT system modeling. Methods: A GOS-based linear detector (0.8 mm per pixel and 51.2 cm in length) with a fast data sampling speed (0.24 ms/sample) was used to measure the relative profiles of bow-tie filters from a collection of eight CT scanners by three different vendors, GE (LS Xtra, LS VCT, Discovery HD750), Siemens (Sensation 64, Edge, Flash, Force), and Philips (iBrilliance 256). The linear detector was first calibrated for its energy response within typical CT beam quality ranges and compared with an ion chamber and analytical modeling (SPECTRA and TASMIP). A geometrical calibration process was developed to determine key parameters including the distance from the focal spot to the linear detector, the angular increment of the gantry at each data sampling, the location of the central x-ray on the linear detector, and the angular response of the detector pixel. Measurements were performed under axial-scan modes for most representative bow-tie filters and kV selections from each scanner. Bow-tie profiles were determined by re-binning the measured rotational data with an angular accuracy of 0.1 degree using the calibrated geometrical parameters. Results: The linear detector demonstrated an energy response as a solid state detector, which is close to the CT imaging detector. The geometrical calibration was proven to be sufficiently accurate (< 1mm in error for distances >550 mm) and the bow-tie profiles measured from rotational mode matched closely to those from the gantry-stationary mode. Accurate profiles were determined for a total of 21 bow-tie filters and 83 filter/kV combinations from the abovementioned scanner models. Conclusion: A new improved approach of CT bow-tie measurement was proposed and accurate bow-tie profiles were provided for a broad list of CT scanner models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Formation of self-consistent pressure profiles in simulation of turbulent convection in tokamak plasmas

The formation of pressure profiles in turbulent tokamak plasmas in ohmic heating regimes and transient regimes induced by turning-on of electron-cyclotron resonance (ECR) heating is investigated. The study is based on self-consistent modeling of low-frequency turbulent plasma convection described by an adiabatically reduced set of hydrodynamic-type equations. The simulations show that, in the ohmic heating stage, turbulence forms and maintains profiles of the total plasma pressure corresponding to turbulent relaxed states. These profiles are close to self-consistent profiles of the total plasma pressure experimentally observed on the T-10 tokamak in ohmic regimes with different values of the safety factor q{sub L} at the limiter. Simulations of nonstationary regimes induced by turning-on of on- and off-axis ECR heating show that the total plasma pressure profiles in the transient regimes remain close to those in the turbulent-relaxed state, as well as to the profiles experimentally observed on T-10.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Prediction of electron density and pressure profile shapes on NSTX-U using neural networks

A new model for prediction of electron density and pressure profile shapes on NSTX and NSTX-U has been developed using neural networks. The model has been trained and tested on measured profiles from experimental discharges during the first operational campaign of NSTX-U. By projecting profiles onto empirically derived basis functions, the model is able to efficiently and accurately reproduce profile shapes. In order to project the performance of the model to upcoming NSTX-U operations, a large database of profiles from the operation of NSTX is used to test performance as a function of available data. The rapid execution time of the model is well suited to the planned applications, including optimization during scenario development activities, and real-time plasma control. A potential application of the model to real-time profile estimation is demonstrated.

Boyer, Mark↗
DOE OSTI2022

A microfluidic system that replicates pharmacokinetic (PK) profiles in vitro improves prediction of in vivo efficacy in preclinical models

Test compounds used on in vitro model systems are conventionally delivered to cell culture wells as fixed concentration bolus doses; however, this poorly replicates the pharmacokinetic (PK) concentration changes seen in vivo and reduces the predictive value of the data. Herein, proof-of-concept experiments were performed using a novel microfluidic device, the Microformulator, which allows in vivo like PK profiles to be applied to cells cultured in microtiter plates and facilitates the investigation of the impact of PK on biological responses. We demonstrate the utility of the device in its ability to reproduce in vivo PK profiles of different oncology compounds over multiweek experiments, both as monotherapy and drug combinations, comparing the effects on tumour cell efficacy in vitro with efficacy seen in in vivo xenograft models. In the first example, an ERK1/2 inhibitor was tested using fixed bolus dosing and Microformulator-replicated PK profiles, in 2 cell lines with different in vivo sensitivities. The Microformulator-replicated PK profiles were able to discriminate between cell line sensitivities, unlike the conventional fixed bolus dosing. In a second study, murine in vivo PK profiles of multiple Poly(ADP-Ribose) Polymerase 1/2 (PARP) and DNA-dependent protein kinase (DNA-PK) inhibitor combinations were replicated in a FaDu cell line resulting in a reduction in cell growth in vitro with similar rank ordering to the in vivo xenograft model. Additional PK/efficacy insight into theoretical changes to drug exposure profiles was gained by using the Microformulator to expose FaDu cells to the DNA-PK inhibitor for different target coverage levels and periods of time. We demonstrate that the Microformulator enables incorporating PK exposures into cellular assays to improve in vitro–in vivo translation understanding for early therapeutic insight.

Singh, Dharaminder (ORCID:0000000346306403)↗
DOE OSTI2021

Energy Sector Position, Navigation, and Time Cybersecurity Profile

The Pacific Northwest National Laboratory has developed this positioning, navigation, and timing (PNT) profile for the Energy Sector at the request of the U.S. Department of Energy. The Department of Energy is the sector-specific agency for the Energy Sector and is responsible for providing guidance in the form of this PNT Profile, per Executive Order 13905, Strengthening National Resilience Through Responsible Use of Positioning, Navigation, and Timing Services (Executive Office of the President 2020) issued February 18, 2020. Executive Order 13905 directed the National Institute of Standards & Technology to develop a PNT Profile that is broadly applicable to all sectors and to serve as a foundation for sector-neutral guidance, NISTIR 8323 Foundational PNT Profile: Applying the Cybersecurity Framework for the Responsible Use of Positioning, Navigation, and Timing (PNT) Services. This document builds on NISTIR 8323 to identify and serve as the required Energy Sector specific guidance. For purposes of this PNT Profile, Energy Sector precise time is 0.5 µs (microseconds) to 1 µs accuracy. Currently, the electricity subsector has systems that use this level of precision time, but the oil and natural gas subsector currently does not. While the electricity subsector uses precision timing, it does not use positioning and/or navigation at this level of accuracy. For this reason, this PNT Profile will focus on only precise time for the electricity subsector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Depth profiling analysis of solar wind helium collected in diamond-like carbon film from Genesis

The distribution of solar-wind ions in Genesis mission collectors, as determined by depth profiling analysis, constrains the physics of ion solid interactions involving the solar wind. Thus, they provide an experimental basis for revealing ancient solar activities represented by solar-wind implants in natural samples. We measured the first depth profile of ⁴He in a collector; the shallow implantation (peaking at <20 nm) required us to use sputtered neutral mass spectrometry with post-photoionization by a strong field. The solar wind He fluence calculated using depth profiling is ~8.5 x 10¹⁴ cm⁻². The shape of the solar wind ⁴He depth profile is consistent with TRIM simulations using the observed ⁴He velocity distribution during the Genesis mission. It is therefore likely that all solar-wind elements heavier than H are completely intact in this Genesis collector and, consequently, the solar particle energy distributions for each element can be calculated from their depth profiles. Ancient solar activities and space weathering of solar system objects could be quantitatively reproduced by solar particle implantation profiles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Multi-frequency radio profiles of PSR B1133+16: Radiation location and particle energy

The pulse profile of PSR B1133+16 is usually regarded as a conal double structure. However, its multi-frequency profiles cannot simply be fitted with two Gaussian functions, and a third component is always needed to fit the bridge region (between two peaks). This would introduce additional, redundant parameters. In this paper, through a comparison of five fitting functions (Gaussian, von Mises, hyperbolic secant, square hyperbolic secant, and Lorentz), it is found that the square hyperbolic secant function can best reproduce the profile, yielding an improved fit. Moreover, a symmetric 2D radiation beam function, instead of a simple 1D Gaussian function, is used to fit the profile. Each profile with either well-resolved or not-so-well-resolved peaks could be fitted adequately using this beam function, and the bridge emission between the two peaks does not need to be a new component. Adopting inclination and impact angles based on polarization measurements, the opening angle (θ{sub μ0}) of the radiation beam in a certain frequency band is derived from beam-function fitting. The corresponding radiation altitudes are then calculated. Based on multi-frequency profiles, we also computed the Lorentz factors of the particles and their dispersion at those locations in both the curvature-radiation and inverse-Compton-scattering models. We found that the Lorentz factors of the particles decrease rapidly as the radiation altitude increases. Besides, the radiation prefers to be generated in an annular region rather than the core region, and this needs further validation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Halo Profiles and the Concentration–Mass Relation for a ΛCDM Universe

Profiles of dark matter-dominated halos at the group and cluster scales play an important role in modern cosmology. Using results from two very large cosmological N-body simulations, which increase the available volume at their mass resolution by roughly two orders of magnitude, we robustly determine the halo concentration-mass (c-M) relation over a wide range of masses, employing multiple methods of concentration measurement. We then characterize individual halo profiles, as well as stacked profiles, relevant for galaxy-galaxy lensing and next-generation cluster surveys; the redshift range covered is 0 ≤ z ≤ 4, with a minimum halo mass of M 200c ~ 2 x 10 11 M ⊙ . Despite the complexity of a proper description of a halo (environmental effects, merger history, nonsphericity, relaxation state), when the mass is scaled by the nonlinear mass scale M * (z), we find that a simple non-power-law form for the c-M/M * relation provides an excellent description of our simulation results across eight decades in M/M * and for 0 ≤ z ≤ 4. Over the mass range covered, the c-M relation has two asymptotic forms: an approximate power law below a mass threshold M/M * ~500-1000, transitioning to a constant value, c 0 ~ 3 at higher masses. The relaxed halo fraction decreases with mass, transitioning to a constant value of ~0.5 above the same mass threshold. We compare Navarro-Frenk-White (NFW) and Einasto fits to stacked profiles in narrow mass bins at different redshifts; as expected, the Einasto profile provides a better description of the simulation results. At cluster scales at low redshift, however, both NFW and Einasto profiles are in very good agreement with the simulation results, consistent with recent weak lensing observations.

79 ASTRONOMY AND ASTROPHYSICS↗