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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exciton-vibrational dynamics induces efficient self-trapping in a substituted nanoring

Cycloparaphenylenes, being the smallest segments of carbon nanotubes, have emerged as prototypes of the simplest carbon nanohoops. Their unique structure–dynamics–optical properties relationships have motivated a wide variety of synthesis of new related nanohoop species. Studies of how chemical changes, introduced in these new materials, lead to systems with new structural, dynamics and optical properties, expand their functionalities for optoelectronics applications. Herein, we study the effect that conjugation extension of a cycloparaphenylene through the introduction of a satellite tetraphenyl substitution has on its structural and dynamical properties. Our non-adiabatic excited state molecular dynamics simulations suggest that this substitution accelerates the electronic relaxation from the high-energy band to the lowest excited state. This is partially due to efficient conjugation achieved between specific phenyl units as introduced by the tetraphenyl substitution. We observe a particular exciton redistribution during relaxation, in which the tetraphenyl substitution plays a significant role. As a result, an efficient inter-band energy transfer takes place. Besides, the observed phonon-exciton interplay induces a significant exciton self-trapping. Finally, our results encourage and guide the future studies of new phenyl substitutions in carbon nanorings with desired optoelectronic properties.

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

First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis

Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Stochastic simulation of reaction-diffusion systems: A fluctuating-hydrodynamics approach

Here, we develop numerical methods for stochastic reaction-diffusion systems based on approaches used for fluctuating hydrodynamics (FHD). For hydrodynamic systems, the FHD formulation is formally described by stochastic partial differential equations (SPDEs). In the reaction-diffusion systems we consider, our model becomes similar to the reaction-diffusion master equation (RDME) description when our SPDEs are spatially discretized and reactions are modeled as a source term having Poisson fluctuations. However, unlike the RDME, which becomes prohibitively expensive for an increasing number of molecules, our FHD-based description naturally extends from the regime where fluctuations are strong, i.e., each mesoscopic cell has few (reactive) molecules, to regimes with moderate or weak fluctuations, and ultimately to the deterministic limit. By treating diffusion implicitly, we avoid the severe restriction on time step size that limits all methods based on explicit treatments of diffusion and construct numerical methods that are more efficient than RDME methods, without compromising accuracy. Guided by an analysis of the accuracy of the distribution of steady-state fluctuations for the linearized reaction-diffusion model, we construct several two-stage (predictor-corrector) schemes, where diffusion is treated using a stochastic Crank-Nicolson method, and reactions are handled by the stochastic simulation algorithm of Gillespie or a weakly second-order tau leaping method. We find that an implicit midpoint tau leaping scheme attains second-order weak accuracy in the linearized setting and gives an accurate and stable structure factor for a time step size of an order of magnitude larger than the hopping time scale of diffusing molecules. We study the numerical accuracy of our methods for the Schlögl reaction-diffusion model both in and out of thermodynamic equilibrium. We demonstrate and quantify the importance of thermodynamic fluctuations to the formation of a two-dimensional Turing-like pattern and examine the effect of fluctuations on three-dimensional chemical front propagation. Furthermore, by comparing stochastic simulations to deterministic reaction-diffusion simulations, we show that fluctuations accelerate pattern formation in spatially homogeneous systems and lead to a qualitatively different disordered pattern behind a traveling wave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On-the-fly machine learned force fields for the study of warm dense matter: Application to diffusion and viscosity of CH

We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme based on the kernel method and Bayesian linear regression, with the training data generated from the Kohn–Sham density functional theory (DFT) using the Gauss spectral quadrature method, within which we calculate energies, atomic forces, and stresses. We verify the accuracy of the formalism by comparing the predicted properties of warm dense carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that ab initio MD simulations of WDM can be accelerated by up to three orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the diffusion coefficients and shear viscosity of CH at a density of 1 g/cm3 and temperatures in the range of 75 000–750 000 K. We find that the self- and inter-diffusion coefficients and the viscosity obey a power law with temperature, and that the diffusion coefficient results suggest a weak coupling between C and H in CH. In addition, we find agreement within standard deviation with previous results for C and CH but disagreement for H, demonstrating the need for ab initio calculations as presented here.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Joint ptycho-tomography with deep generative priors

Abstract Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is common in conventional phase retrieval. We use an augmented Lagrangian scheme for formulating the constrained optimization problem and employ an alternating direction method of multipliers (ADMM) for the joint solution. ADMM allows the problem to be split into smaller and computationally more efficient subproblems: ptychographic phase retrieval, tomographic reconstruction, and regularization of the solution. We extend our ADMM framework with plug-and-play (PnP) denoisers by replacing the regularization subproblem with a general denoising operator based on machine learning. While the PnP framework enables integrating such learned priors as denoising operators, tuning of the denoiser prior remains challenging. To overcome this challenge, we propose a denoiser parameter to control the effect of the denoiser and to accelerate the solution. In our simulations, we demonstrate that our proposed framework with parameter tuning and learned priors generates high-quality reconstructions under limited and noisy measurement data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Two self-similar Reynolds-stress transport models with anisotropic eddy viscosity

Two Reynolds-averaged Navier-Stokes models with full Reynolds-stress transport (RST) and tensor eddy viscosity are presented. These new models represent RST extensions of the $k−2L−a−\mathscr{C}$ and $k−ϕ−L−a−\mathscr{C}$ models by Morgan. Self-similarity analysis is used to derive constraints on model coefficients required to reproduce expected growth parameters for a variety of canonical flows, including Rayleigh-Taylor (RT) and Kelvin-Helmholtz (KH) mixing layers. Both models are then applied in one-dimensional simulation of RT and KH mixing layers, and the expected self-similar growth rates and anisotropy are obtained. Next, models are applied in two-dimensional simulation of the so-called “tilted rocket rig” inclined RT experiment and in simulation of a shock-accelerated localized patch of turbulence. Here it is found that RST is required to capture the qualitative growth of the shock-accelerated patch, and an anisotropic eddy viscosity provides substantial improvement over a Boussinesq treatment for the tilted rocket rig problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling the inner part of the jet in M87: Confronting jet morphology with theory

The formation of jets in black hole accretion systems is a long-standing problem. It has been proposed that a jet can be formed by extracting the rotation energy of the black hole (“BZ-jet”) or the accretion flow (“disk-jet”). While both models can produce collimated relativistic outflows, neither has successfully explained the observed jet morphology. By using general relativistic magnetohydrodynamic simulations and considering nonthermal electrons accelerated by magnetic reconnection that is likely driven by magnetic eruption in the underlying accretion flow, we obtain images by radiative transfer calculations and compared them to millimeter observations of the jet in M87. We find that the BZ-jet originating from a magnetically arrested disk around a high-spin black hole can well reproduce the jet morphology, including its width and limb-brightening feature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Investigating the Particle Growth in Bimodal Pt/C Catalysts by In-Situ Small-Angle X-ray Scattering: Challenges in the Evaluation of Stress Test Protocol-Dependent Degradation Mechanisms

The influence of different combinations of accelerated stress test (AST) protocols simulating load-cycle and start/stop conditions of a proton exchange membrane fuel cell (PEMFC) vehicle is investigated on a bimodal Pt/C catalyst. The bimodal Pt/C catalyst, prepared by mixing two commercial catalysts, serves as a model system and consists of two distinguishable size populations. The change in mean particle size was investigated by in situ small-angle X-ray scattering (SAXS). The comparison to the reference catalysts, i.e., the two single-size population catalysts, uncovers the presence of electrochemical Ostwald ripening as a degradation mechanism in the bimodal catalyst. Increasing the harshness of the applied AST protocol combinations by faster changing between load-cycle or start/stop conditions, the particle size of the larger population of the bimodal catalyst increases faster than expected. Surprisingly, the change in mean particle size of the smaller size population indicates a smaller increase for harsher AST protocols, which might be explained by a substantial electrochemical Ostwald ripening.

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

Blunt Impact Brain Injury using Cellular Injury Criterion

The Advanced Combat Helmet (\ACH") military specification (\mil-spec") requires a helmeted magnesium (\Mg") Department of Transportation (\DOT") headform be dropped vertically, with an impact speed of 3.1 m/s (10 ft/s), onto a steel hemispherical target. The pass/fail criteria are based on translational acceleration (150 G) alone, absent of any rotational component. Without a rotational component, the specification's injury risk application is limited to skull fracture and peripheral hematomas (subdural, subarachnoid), since this translational acceleration injury risk assessment is based on the Wayne State Tolerance Curve (\WSTC"). To provide a more comprehensive view of injury for the entire brain, an alternative approach is needed. To meet this need, we worked with a larger group called PANTHER, a collaboration between national laboratories, industry, and academia. Collaborations specific to research and results presented here come from efforts led by Mr. Ron Szalkowski and Mr. Sushant Malave, Ms. Alice Fawzi, and Dr. Christian Franck. We have developed a prototypical injury risk criterion based on the neuronal response to abrupt changes in general motion (translation, rotation, or both). The cellular-based mild traumatic brain injury (\cbmTBI") criterion utilizes both the strain and strain rate of brain tissue to account for the stretch and rate of stretch that occurs throughout the brain as a result of blunt impact to the head. We conducted physical experiments of an ACH-fitted magnesium headform, which produced repeatable headform peak accelerations. Then, we developed a simulation of the experiment, and validated the simulation output with the experimental data. We then substituted the magnesium headform with a human headform, consisting of skin, muscle, bone, gray matter, white matter, cerebral-spinal fluid, membranes, vasculature, intravertebral discs, airway and sinus. We quantified brain injury risk using the cbmTBI criterion, using the current mil-spec test and a modified test. The modified mil-spec test used an inclined anvil target that was located posterior to the crown of the helmet in the axial plane. While the current mil-spec test produced brain deformation from head translation alone, the modified test produced brain deformation from head translation and rotation, which is closer to most real world and combat theater impacts (e.g., such as occur in tertiary blast exposure). Compared to the current mil-spec test, the modified test produced elevated strains in the human digital twin. These data, mapped to the cbmTBI criterion, suggest increased injury risk for blunt impacts that cause rotation and translation, rather than just translation alone. Moreover, these data may lead to a rotational performance metric, which is rooted in the biology and pathology of the brain's response to impact and blast, and which should be used to improve next-generation helmet designs.

42 ENGINEERING↗
DOE OSTI2020

Re-Additization of Commercial Biodiesel Blends During Long-Term Storage

Commercial biodiesel blends representative of the U.S. market were aged following procedure ASTM D4625, Standard Test Method for Middle Distillate Fuel Storage Stability at 43°C (110°F), with periodic monitoring of fuel properties indicative of oxidation. The oxidation stability—or oxidation reserve expressed as Rancimat induction period (IP)—gradually decreased from its initial value, as expected. At a predetermined IP threshold, an antioxidant was used to restore IP to the ASTM D7467 specification minimum of 6 six hours, referred to as re-additization. At lower IP values, the amount of antioxidant required increased significantly, and the effectiveness tended to be reduced. Once IP fell to essentially zero, the acid content increased to above the allowable limit. Insoluble material was detectable after the acid number increased out of specification. Storage life was increased with re-additization relative to the as-received fuels, as evidenced by longer time to produce acids. Experience in the field may vary based on storage conditions; however, these results indicate re-additization can significantly increase the storage life of biodiesel blends when used with regular monitoring of IP and acid number. An assessment of property changes during long-term storage showed the initial IP did not predict storage behavior, although fuels above the specification minimum remained stable for greater than 12 weeks of D4625 accelerated aging (1 one year simulated).

09 BIOMASS FUELS↗
DOE OSTI2023

Hybrid physics-based and machine learning tools for materials assessment

In this work, we develop novel physics-based and machine learning computational techniques to predict fundamental properties of metallic systems that affect radiation damage behavior in reactor structural materials. Oftentimes, atomistic predictions of engineering alloys simplify chemical compositions to a single element to reduce computational cost and complexity, introducing large sources of uncertainty and potentially missing important behavior. In addition, engineering alloys such as SS 316 are particularly challenging to simulate with first principles methods because of the additional degrees of freedom introduced by magnetic natures of the constituent elements, and very little data of this type exists within the literature. These novel methods aim to improve the qualitative prediction of radiation damage in engineering alloys by more accurately simulating their compositions, both by accelerating the computations and by developing novel analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

NEAMS Burnup Extension Accomplishments and Remaining Modeling Gaps

The economic viability of light-water reactors (LWRs) in the United States is declining in heavily subsidized markets, and as a result, the nuclear industry is looking for opportunities to enhance the economic competitiveness of nuclear power. This is not a foreign concept to the nuclear industry: in the mid-2000s, the nuclear industry set out to achieve zero fuel failures by 2010. The goal in this effort was to drive down the cost of reactor shut down by replacing a pin or bundle in response to fuel rod failure. 2010 brought about the initiative to deliver the nuclear promise to reduce operating cost by 30% to improve nuclear energy’s economic competitiveness before 2020. The emergence of accident-tolerant fuel also offers the nuclear industry an opportunity to build on these past successes and deliver affordable, clean energy. Accident-tolerant fuel has been shown to provide superior performance compared to traditional Zircaloy/UO2 fuel concepts, offering the unique ability to remove operational limitations that inhibit the economic viability of nuclear power. This has led the industry to begin building a technical case to extend the peak rod average burnup beyond 62 GWd/tU to extend pressurized water reactor cycle lengths to 24 months and to develop more efficient boiling water reactor core designs. The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program mission is to develop advanced modeling and simulation tools and capabilities to accelerate the deployment of advanced nuclear energy technologies. The primary safety concern inhibiting the nuclear industry from extending burnup is related to high-burnup fuel fragmentation, relocation, and dispersal. Therefore, the NEAMS program developed a targeted 5-year plan to support the industry’s efforts to extend burnup. This milestone report summarizes the 5-year plan that was enacted in FY20, followed by a discussion of the ongoing activates required to fulfill the 5-year plan, as well as the approach to address the current modeling gaps. Additionally, an LWR stakeholder meeting was held to communicate work performed in the NEAMS program over the past three years, to assess the LWR community’s perspective on the impact of the program, and to identify remaining significant gaps in the NEAMS suite of capabilities. This engagement will be documented by the Electric Power Research Institute and used by NEAMS to redirect current LWR scope as needed and to develop the next phase for LWR research and development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

PIP-II Beam Current Monitor Fault Case & Beam Position Monitor Linearity Studies in CST Studio

The use of non-invasive sensors & systems to measure particle beam characteristics is a crucial part of modern accelerator control systems. As such, simulations predicting the behavior of these sensors are essential for guiding beamline control system design. This poster details the results returned by two beam sensor models created using CST Studio software: the signal linearity of an elliptical beam position monitor (BPM), and the fault cases of an AC current transformer (ACCT) beam current monitor (BCM).

Rouzky, Adam↗
DOE OSTI2025

Beam Non-Uniformity Characterization at the SpinQuest and DarkQuest Experiments

The SpinQuest experiment, including upgrades to SpinQuest designed to increase sensitivity to dark sector searches (commonly known as DarkQuest), utilizes the high-intensity 120 GeV proton beam delivered by the Fermilab Accelerator Complex to probe the inner structure of nucleons and search for new physics beyond the Standard Model. The SpinQuest beam is extracted from the Main Injector synchrotron at Fermilab in what is known as a slow spill . The slow spill involves a complex non-linear half-integer extraction method, which results in non-uniform beam behavior. SpinQuest observes spikes of very high intensity beam which can saturate detectors and reduce trigger efficiency, significantly impacting the experiment's sensitivity. In this project we address this challenge by developing an analysis framework to characterize the beam delivered to SpinQuest. By discovering trends within each spill and by comparing thousands of spills, we can better inform the Accelerator Division and improve the slow spill extraction. We have also begun a collaboration with the Accelerator Division in order to simulate the slow spill and improve the magnet ramp process controls which will improve the uniformity of the beam. These improvements will directly enhance the physics reach of SpinQuest/DarkQuest, increasing their sensitivity to key measurements such as the Sivers function and searches for new physics.

Dolen, James William [Purdue U., Calumet] (ORCID:0↗
DOE OSTI2021

Assessing climate-change-induced flood risk in the Conasauga River watershed: an application of ensemble hydrodynamic inundation modeling

Abstract. This study evaluates the impact of potential future climate change on flood regimes, floodplain protection, and electricity infrastructures across the Conasauga River watershed in the southeastern United States through ensemble hydrodynamic inundation modeling. The ensemble streamflow scenarios were simulated by the Distributed Hydrology Soil Vegetation Model (DHSVM) driven by (1) 1981–2012 Daymet meteorological observations and (2) 11 sets of downscaled global climate models (GCMs) during the 1966–2005 historical and 2011–2050 future periods. Surface inundation was simulated using a GPU-accelerated Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON) hydrodynamic model. A total of 9 out of the 11 GCMs exhibit an increase in the mean ensemble flood inundation areas. Moreover, at the 1 % annual exceedance probability level, the flood inundation frequency curves indicate a ∼ 16 km2 increase in floodplain area. The assessment also shows that even after flood-proofing, four of the substations could still be affected in the projected future period. The increase in floodplain area and substation vulnerability highlights the need to account for climate change in floodplain management. Overall, this study provides a proof-of-concept demonstration of how the computationally intensive hydrodynamic inundation modeling can be used to enhance flood frequency maps and vulnerability assessment under the changing climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Strain effects on oxygen transport in tetragonal zirconium dioxide

Temperature accelerated dynamics and molecular dynamics simulations are used to investigate the strain effects on oxygen interstitial and vacancy migration in tetragonal zirconium dioxide. At zero external strain, the anisotropic migration mechanisms of oxygen defects are characterized. At non-zero strains, both the crystal structure and defect migration barriers are modified by strain. Under compressive strains, the defect migration barrier increases with the increasing strain for both interstitials and vacancies. The crystal structure transforms from a tetragonal to a nearly cubic fluorite structure. Accordingly, the defect migration becomes nearly isotropic. Under dilative strains, the migration barrier first decreases then increases with increasing strain for both types of defects. The tetragonal phase transforms to a lower symmetry structure that is close to the orthorhombic phase. In turn, the defect migration becomes highly anisotropic. Under both compressive and dilative strains, interstitials respond to strain more strongly than vacancies. At small dilative strains, an oxygen interstitial has comparable diffusivity to a vacancy, suggesting that both types of defects can contribute to oxygen transport, if they are present. Although currently no previous result is available to validate oxygen interstitial diffusion behavior, the trend of strain effects on oxygen vacancy diffusion is in good agreement with available experimental and theoretical studies in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Atomistic Studies of Cation Transport in Tetragonal ZrO2 During Zirconium Corrosion

Zirconium alloys are the major fuel cladding materials in current reactors. The water-side corrosion is one of the major degradation mechanisms of these alloys. During corrosion the transport of oxidizing species in zirconium dioxide (ZrO2) determines the corrosion kinetics. Previously it has been argued that the outward diffusion of cation ions is important for forming protective oxides. In this work, the migration of Zr defects in tetragonal ZrO2 is studied with temperature accelerated dynamics and molecular dynamics simulations. The results show that Zr interstitials have anisotropic diffusion and migrate preferentially along the [001] or c direction in tetragonal ZrO2. The compressive stresses can increase the Zr interstitial migration barrier significantly. The migration barriers of some defect clusters can be much lower than those of point defects. The migration of Zr interstitials at some special grain boundaries is much slower than in a bulk oxide. The implications of these atomistic simulation results in the Zr corrosion are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Connected and automated vehicles, driving systems, and control logic for info-rich eco-autonomous driving

A method for controlling automated driving operations of a vehicle includes determining vehicle origin and destination data, and generating a graphical representation of a road network with multiple candidate routes between the vehicle's origin and destination. Road-level data, including speed, turn angle, and/or gradient data, is received for each candidate route, and respective total energy uses are estimated for the vehicle to traverse across the candidate routes. Multiple candidate driving strategies, each having respective speed and acceleration profiles, are determined for the candidate route with the lowest estimated total energy use. An optimal candidate driving strategy is selected through a cost evaluation of the associated speed and acceleration profiles and forward movement simulations of the vehicle over a prediction horizon. Command signals are transmitted to the vehicle's steering and/or powertrain systems to execute control operations based on the optimal driving strategy and the candidate route with the lowest energy use.

Zhao, Junfeng↗