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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

HIGH-RESOLUTION CALCULATION OF THE SOLAR GLOBAL CONVECTION WITH THE REDUCED SPEED OF SOUND TECHNIQUE. II. NEAR SURFACE SHEAR LAYER WITH THE ROTATION

We present a high-resolution, highly stratified numerical simulation of rotating thermal convection in a spherical shell. Our aim is to study in detail the processes that can maintain a near surface shear layer (NSSL) as inferred from helioseismology. Using the reduced speed of sound technique, we can extend our global convection simulation to 0.99 R {sub ☉} and include, near the top of our domain, small-scale convection with short timescales that is only weakly influenced by rotation. We find the formation of an NSSL preferentially in high latitudes in the depth range of r = 0.95-0.975 R {sub ☉}. The maintenance mechanisms are summarized as follows. Convection under the weak influence of rotation leads to Reynolds stresses that transport angular momentum radially inward in all latitudes. This leads to the formation of a strong poleward-directed meridional flow and an NSSL, which is balanced in the meridional plane by forces resulting from the 〈v{sub r}{sup ′}v{sub θ}{sup ′}〉 correlation of turbulent velocities. The origin of the required correlations depends to some degree on latitude. In high latitudes, a positive correlation 〈v{sub r}{sup ′}v{sub θ}{sup ′}〉 is induced in the NSSL by the poleward meridional flow whose amplitude increases with the radius, while a negative correlation is generated by the Coriolis force in bulk of the convection zone. In low latitudes, a positive correlation 〈v{sub r}{sup ′}v{sub θ}{sup ′}〉 results from rotationally aligned convection cells ({sup b}anana cells{sup )}. The force caused by these Reynolds stresses is in balance with the Coriolis force in the NSSL.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Assessment of metal artifact reduction methods in pelvic CT

Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Polarimetry in the hard X-ray domain with INTEGRAL SPI

We present recent improvements in polarization analysis with the INTEGRAL SPI data. The SPI detector plane consists of 19 independent Ge crystals and can operate as a polarimeter. The anisotropy characteristics of Compton diffusions can provide information on the polarization parameters of the incident flux. By including the physics of the polarized Compton process in the instrument simulation, we are able to determine the instrument response for a linearly polarized emission at any position angle. We compare the observed data with the simulation sets by a minimum χ{sup 2} technique to determine the polarization parameters of the source (angle and fraction). We have tested our analysis procedure with Crab Nebula observations and find a position angle similar to those previously reported in the literature, with a comfortable significance. Since the instrument response depends on the incident angle, each exposure in the SPI data requires its own set of simulations, calculated for 18 polarization angles (from 0° to 170° in steps of 10°) and unpolarized emission. The analysis of a large number of observations for a given source, required to obtain statistically significant results, represents a large amount of computing time, but it is the only way to access this complementary information in the hard X-ray regime. Indeed, major scientific advances are expected from such studies since the observational results will help to discriminate between the different models proposed for the high energy emission of compact objects like X-ray binaries and active galactic nuclei or gamma-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-Fidelity Accelerated Design of High-performance Electrochemical Systems

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical materials will be critical, but their development currently relies heavily on human-time-intensive experimental trial and error and computationally expensive first-principles, meso-scale and continuum simulations. To accelerate this process, our team has developed the AutoMat platform. AutoMat can accelerate development of new electrochemical materials along two avenues: first, automated input generation and management of simulations at multiple lengthscales as well as “handoff” of outputs from one lengthscale as inputs to the next; and second, replacement of the most computationally intensive simulation processes with machine-learned surrogate models. The crux of our team’s effort was not “reinventing the wheel” by developing entirely new techniques, but rather building a “superhighway” that allows existing state-of-the-art techniques to run faster and more smoothly than before. AutoMat can utilize tools spanning from first-principles quantum chemistry computations to automated robotic experimentation, and is driven by design space search techniques to reduce the number of iterations through the full simulation loop by rapidly targeting promising regions of design spaces such as single-atom alloy catalysts or blends of liquid electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2025

Modeling laser-wakefield accelerators using the time-averaged ponderomotive approximation in a Lorentz boosted frame

Future, high-fidelity simulations of multi-GeV-class laser Wakefield accelerators (LWFAs) will need to model the propagation of high-intensity laser drivers over meter-scale plasmas with high spatial and temporal resolutions, thus requiring high amounts of computational resources. Various techniques have been devised over the years to reduce the computational cost of such simulations, including the time-averaged ponderomotive approximation, and the use of the Lorentz boosted frame technique. In this paper we discuss the combination of these two computational techniques, highlighting the resulting significant reduction in the computational cost of LWFA simulations and the limitations of this approach. The combination of the two techniques can potentially become essential for the modeling of a multi-TeV, LWFA-based collider.

Laser Wakefield Acceleration↗
DOE OSTI2021

Various facets of magnetic charge correlation: Micromagnetic and distorted-wave Born approximation simulations study

The emergent concept of the magnetic charge quasiparticle provides a new realm to study the evolution of magnetic properties in two-dimensional artificially frustrated magnets. Here we report on the exploration of magnetic phases due to various magnetic charge correlation using the complementary numerical techniques of micromagnetic and distorted-wave Born approximation simulations in artificial permalloy honeycomb lattice. The honeycomb element length varies between 10 nm and 100 nm, while the width and thickness are kept within the single domain limit. In addition to the charge ordered loop state, we observe disordered charge arrangement, characterized by the random distribution of ±Q charges, in single domain size honeycomb lattice. As the length of the honeycomb element increases, low multiplicity magnetic charges tend to form contiguous bands in thinner lattice. Thin honeycomb lattice with 100 nm element length exhibits a perfect spin ice pattern, which remains unaffected by the modest increase in the width of element size. We simulate scattering profiles under the pretext of distorted-wave Born approximation formalism for the micromagnetic phases. The results are expected to provide useful guidance in the experimental investigation of magnetic phases in an artificial honeycomb magnet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model

In spite of the importance of land ecosystems in offsetting carbon dioxide emissions released by anthropogenic activities into the atmosphere, the spatiotemporal dynamics of terrestrial carbon fluxes remain largely uncertain at regional to global scales. Over the past decade, data assimilation (DA) techniques have grown in importance for improving these fluxes simulated by terrestrial biosphere models (TBMs), by optimizing model parameter values while also pinpointing possible parameterization deficiencies. Although the joint assimilation of multiple data streams is expected to constrain a wider range of model processes, their actual benefits in terms of reduction in model uncertainty are still under-researched, also given the technical challenges. In this study, we investigated with a consistent DA framework and the ORCHIDEE-LMDz TBM–atmosphere model how the assimilation of different combinations of data streams may result in different regional to global carbon budgets. To do so, we performed comprehensive DA experiments where three datasets (in situ measurements of net carbon exchange and latent heat fluxes, spaceborne estimates of the normalized difference vegetation index, and atmospheric CO 2 concentration data measured at stations) were assimilated alone or simultaneously. We thus evaluated their complementarity and usefulness to constrain net and gross C land fluxes. We found that a major challenge in improving the spatial distribution of the land C sinks and sources with atmospheric CO 2 data relates to the correction of the soil carbon imbalance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Here, large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO 2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO 2 , using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO 2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO 2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr -1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.

58 GEOSCIENCES↗
DOE OSTI2014

Benchmarking all-atom simulations using hydrogen exchange

Molecular dynamics simulations have recently become capable of observing multiple protein unfolding and refolding events in a single-millisecond–long trajectory. This major advance produces atomic-level information with nanosecond resolution, a feat unmatched by experimental methods. Such simulations are being extensively analyzed to assess their description of protein folding, yet the results remain difficult to validate experimentally. We apply a combination of hydrogen exchange, NMR, and other techniques to test the simulations with a resolution of single H-bonds. Several significant discrepancies between the simulations and experimental data were uncovered for regions of the energy surface outside of the native basin. This comparison yields suggestions for improving the force fields and provides a general method for experimentally validating folding simulations.

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

SU-E-T-427: Feasibility Study for Evaluation of IMRT Dose Distribution Using Geant4-Based Automated Algorithms

Purpose: For intensity-modulated radiation therapy (IMRT) treatment planning validation using Monte Carlo (MC) simulations, a precise and automated procedure is necessary to evaluate the patient dose distribution. The aim of this study is to develop an automated algorithm for IMRT simulations using DICOM files and to evaluate the patient dose based on 4D simulation using the Geant4 MC toolkit. Methods: The head of a clinical linac (Varian Clinac 2300 IX) was modeled in Geant4 along with particular components such as the flattening filter and the multi-leaf collimator (MLC). Patient information and the position of the MLC were imported from the DICOM-RT interface. For each position of the MLC, a step- and-shoot technique was adopted. PDDs and lateral profiles were simulated in a water phantom (50×50×40 cm{sup 3}) and compared to measurement data. We used a lung phantom and MC-dose calculations were compared to the clinical treatment planning used at the Seoul National University Hospital. Results: In order to reproduce the measurement data, we tuned three free parameters: mean and standard deviation of the primary electron beam energy and the beam spot size. These parameters for 6 MV were found to be 5.6 MeV, 0.2378 MeV and 1 mm FWHM respectively. The average dose difference between measurements and simulations was less than 2% for PDDs and radial profiles. The lung phantom study showed fairly good agreement between MC and planning dose despite some unavoidable statistical fluctuation. Conclusion: The current feasibility study using the lung phantom shows the potential for IMRT dose validation using 4D MC simulations using Geant4 tool kits. This research was supported by Korea Institute of Nuclear safety and Development of Measurement Standards for Medical Radiation funded by Korea research Institute of Standards and Science. (KRISS-2015-15011032)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Experimental and computing strategies in advanced material characterization problems

The mechanical characterization of materials relies more and more often on sophisticated experimental methods that permit to acquire a large amount of data and, contemporarily, to reduce the invasiveness of the tests. This evolution accompanies the growing demand of non-destructive diagnostic tools that assess the safety level of components in use in structures and infrastructures, for instance in the strategic energy sector. Advanced material systems and properties that are not amenable to traditional techniques, for instance thin layered structures and their adhesion on the relevant substrates, can be also characterized by means of combined experimental-numerical tools elaborating data acquired by full-field measurement techniques. In this context, parameter identification procedures involve the repeated simulation of the laboratory or in situ tests by sophisticated and usually expensive non-linear analyses while, in some situation, reliable and accurate results would be required in real time. The effectiveness and the filtering capabilities of reduced models based on decomposition and interpolation techniques can be profitably used to meet these conflicting requirements. This communication intends to summarize some results recently achieved in this field by the author and her co-workers. The aim is to foster further interaction between engineering and mathematical communities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Reconstruction and Measurement of $\mathcal{O}$(100) MeV Energy Electromagnetic Activity from $\pi^0 \rightarrow \gamma\gamma$ Decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of &calO;(100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of kerogen nanopores using 2D NMR relaxation and MD simulations

The characterization of kerogen nanopores is crucial for predicting the geostorage capacity and recoverability of natural gas in unconventional gas shale reservoirs. Towards this end, a powerful technique is presented which integrates 2D NMR T 1 -T 2 relaxation measurements with molecular dynamics (MD) simulations of hydrocarbons confined in the nanopores of kerogen. The integrated NMR-MD technique is demonstrated using T 1 -T 2 measurements of kerogen isolates and organic-rich chalks saturated with heptane, together with MD simulations of heptane completely dissolved in a realistic kerogen model. The NMR-MD results are used to extract the swelling ratio and nanopore size distribution of kerogen as a function of depth in the reservoir. The effects of organic nanoconfinement on the T 1 relaxation dispersion and T 2 residual dipolar coupling of heptane are investigated, as well as the effect of downhole effective stress on the kerogen nanopore size as a function of depth and compaction. Potential applications in partially depleted gas shale reservoirs are discussed, including CO 2 utilization/geostorage, geostorage of green H 2 , and integration of the NMR-MD technique with thermodynamic models for predicting the competitive sorption of gas mixtures in kerogen.

Compaction↗
DOE OSTI2022

Revealing hidden defects through stored energy measurements of radiation damage

With full knowledge of a material’s atomistic structure, it is possible to predict any macroscopic property of interest. In practice, this is hindered by limitations of the chosen characterization techniques. For example, electron microscopy is unable to detect the smallest and most numerous defects in irradiated materials. Instead of spatial characterization, we propose to detect and quantify defects through their excess energy. Differential scanning calorimetry of irradiated Ti measures defect densities five times greater than those determined using transmission electron microscopy. Our experiments also reveal two energetically distinct processes where the established annealing model predicts one. Molecular dynamics simulations discover the defects responsible and inform a new mechanism for the recovery of irradiation-induced defects. The combination of annealing experiments and simulations can reveal defects hidden to other characterization techniques and has the potential to uncover new mechanisms behind the evolution of defects in materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT

Purpose : A method is presented for generating simulated low-dose cone-beam CT (CBCT) preview images from which patient- and task-specific minimum-dose protocols can be confidently selected prospectively in clinical scenarios involving repeat scans. Methods : In clinical scenarios involving a series of CBCT images, the low-dose preview (LDP) method operates upon the first scan to create a projection dataset that accurately simulates the effects of dose reduction in subsequent scans by injecting noise of proper magnitude and correlation, including both quantum and electronic readout noise as important components of image noise in flat-panel detector CBCT. Experiments were conducted to validate the LDP method in both a head phantom and a cadaveric torso by performing CBCT acquisitions spanning a wide dose range (head: 0.8–13.2 mGy, body: 0.8–12.4 mGy) with a prototype mobile C-arm system. After injecting correlated noise to simulate dose reduction, the projections were reconstructed using both conventional filtered backprojection (FBP) and an iterative, model-based image reconstruction method (MBIR). The LDP images were then compared to real CBCT images in terms of noise magnitude, noise-power spectrum (NPS), spatial resolution, contrast, and artifacts. Results : For both FBP and MBIR, the LDP images exhibited accurate levels of spatial resolution and contrast that were unaffected by the correlated noise injection, as expected. Furthermore, the LDP image noise magnitude and NPS were in strong agreement with real CBCT images acquired at the corresponding, reduced dose level across the entire dose range considered. The noise magnitude agreed within 7% for both the head phantom and cadaveric torso, and the NPS showed a similar level of agreement up to the Nyquist frequency. Therefore, the LDP images were highly representative of real image quality across a broad range of dose and reconstruction methods. On the other hand, naïve injection ofuncorrelated noise resulted in strong underestimation of the true noise, which would lead to overly optimistic predictions of dose reduction. Conclusions : Correlated noise injection is essential to accurate simulation of CBCT image quality at reduced dose. With the proposed LDP method, the user can prospectively select patient-specific, minimum-dose protocols (viz., acquisition technique and reconstruction method) suitable to a particular imaging task and to the user's own observer preferences for CBCT scans following the first acquisition. The method could provide dose reduction in common clinical scenarios involving multiple CBCT scans, such as image-guided surgery and radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Structural Basis for Binding of Allosteric Drug Leads in the Adenosine A 1 Receptor

Despite intense interest in designing positive allosteric modulators (PAMs) as selective drugs of the adenosine A 1 receptor (A 1 AR), structural binding modes of the receptor PAMs remain unknown. Using the first X-ray structure of the A 1 AR, we have performed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) technique to determine binding modes of the A 1 AR allosteric drug leads. Two prototypical PAMs, PD81723 and VCP171, were selected. Each PAM was initially placed at least 20 Å away from the receptor. Extensive GaMD simulations using the AMBER and NAMD simulation packages at different acceleration levels captured spontaneous binding of PAMs to the A 1 AR. The simulations allowed us to identify low-energy binding modes of the PAMs at an allosteric site formed by the receptor extracellular loop 2 (ECL2), which are highly consistent with mutagenesis experimental data. Furthermore, the PAMs stabilized agonist binding in the receptor. In the absence of PAMs at the ECL2 allosteric site, the agonist sampled a significantly larger conformational space and even dissociated from the A 1 AR alone. In summary, the GaMD simulations elucidated structural binding modes of the PAMs and provided important insights into allostery in the A 1 AR, which will greatly facilitate the receptor structure-based drug design.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Locust: C++ software for simulation of RF detection

The Locust simulation package is the new C++ software tool developed to simulate the measurement of time-varying electromagnetic fields using RF detection techniques. Modularity and flexibility allow for arbitrary input signals, while concurrently supporting tight integration with physics-based simulations as input. External signals driven by the Kassiopeia particle tracking package are discussed, demonstrating conditional feedback between Locust and Kassiopeia during software execution. An application of the simulation to the Project 8 experiment is described. Locust is publicly available at https://github.com/project8/locust_mc

97 MATHEMATICS AND COMPUTING↗