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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comparing Emulation Methods for Computer Models with High Dimensional Output

This Master’s Capstone project will present a comparison of statistical models for computer simulation studies. The four models included in this comparison study were chosen for both their proven and diverse methodologies. We will present a case study on hurricane flood data in the Delaware bay which highlights the strengths and weaknesses of each model when applied to a very large spatial field. As computers have gotten faster, we have become interested in modeling increasingly large spatial fields in both size and resolution. Statistical algorithms that are able to efficiently handle these fields have never been more important. We therefore find this comparison to be extremely topical.

42 ENGINEERING↗
DOE OSTI2021

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗
DOE OSTI2024

Sachdev-Ye-Kitaev model on a noisy quantum computer

Here we study the SYK model -- an important toy model for quantum gravity on IBM's superconducting qubit quantum computers. By using a graph-coloring algorithm to minimize the number of commuting clusters of terms in the qubitized Hamiltonian, we find the gate complexity of the time evolution using the first-order product formula for N Majorana fermions is $\mathscr{O}$(N 5 J 2 t 2 /ε) where J is the dimensionful coupling parameter, t is the evolution time, and ε is the desired precision. With this improved resource requirement, we perform the time evolution for N=6,8 with maximum two-qubit circuit depth of 343. We perform different error mitigation schemes on the noisy hardware results and find good agreement with the exact diagonalization results on classical computers and noiseless simulators. In particular, we compute return probability after time t and out-of-time order correlators (OTOC) which is a standard observable of quantifying the chaotic nature of quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Argon equation of state data to 1 TPa: Shock compression experiments and simulations

Argon is the most abundant noble gas on Earth and its noble, atomic fluid nature makes it an excellent candidate for comparison of experiment and theory at extreme conditions. For this study, we performed a combined computational and experimental study on shock compressed cryogenic liquid argon. Using Sandia's Z machine, we shock compressed liquid argon to 600 GPa and reshock states up to 950 GPa. Laser shock experiments at the Omega Laser facility extend the principal Hugoniot to 1000 GPa and provided temperature data along the principal Hugoniot. The plate impact experiments and laser shock experiments used well-characterized impedance matching standards and demonstrate consistent results between the two platforms over a common range. Density functional theory based molecular dynamics simulations provided additional data on the Hugoniot to 600 GPa. The combined experimental data and simulation results provide constraints on the development of new equation of state models at extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Determining the Role of Synthesis and Reaction Conditions on the Exposed Surface and Shape of ..beta..-Mo2C Catalysts

The production of drop-in quality biofuels typically can be achieved through catalytic fast pyrolysis (CFP) of biomass, followed by hydrodeoxygenation (HDO) of the vapor-phase product to reduce the oxygen content and stabilize the bio-oil product. To favor selectivity toward desired deoxygenation products, bifunctional catalysts with both acidic and hydrogenation sites are often employed. Due to both its oxophilicity and its ability to promote hydrogenation reactions, molybdenum carbide catalysts have shown promise for promoting the HDO of CFP vapors. However, the surface structure and composition of carbide catalyst particles are not well understood, precluding the establishment of fundamental structure-function relationships needed for the rational development of molybdedum carbide for HDO, as well as other reactions. For orthorhombic ..beta..-Mo2C, the (100) facet is largely studied for computational surface-reaction analyses, possibly due to its similarities with the close-packed (111) facet of noble-metal catalysts. However, it has previously been postulated through ab initio thermodynamic studies that the (111), (110), and (011) facets are most stable, though there is no consensus. Furthermore, while a majority of previous surface stability analyses of ..beta..-Mo2C focus on bulk terminations, the highly carburizing synthesis conditions and the use of ..beta..-Mo2C in carbon-containing reaction applications could introduce non-stoichiometric coverages of surface carbon. As such, this study uses ab initio thermodynamics calculations to assess the relative surface stability of the low-index facets of ..beta..-Mo2C, including consideration of varying the coverage of surface carbon. From this information, Wulff constructions are utilized to predict the synthesis and reaction condition-dependent shape and surface carbon composition of ..beta..-Mo2C catalyst particles.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2025

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗
DOE OSTI2020

Identifying sequence perturbations to an intrinsically disordered protein that determine its phase-separation behavior

Phase separation of intrinsically disordered proteins (IDPs) commonly underlies the formation of membraneless organelles, which compartmentalize molecules intracellularly in the absence of a lipid membrane. Identifying the protein sequence features responsible for IDP phase separation is critical for understanding physiological roles and pathological consequences of biomolecular condensation, as well as for harnessing phase separation for applications in bioinspired materials design. To expand our knowledge of sequence determinants of IDP phase separation, we characterized variants of the intrinsically disordered RGG domain from LAF-1, a model protein involved in phase separation and a key component of P granules. Based on a predictive coarse-grained IDP model, we identified a region of the RGG domain that has high contact probability and is highly conserved between species; deletion of this region significantly disrupts phase separation in vitro and in vivo. We determined the effects of charge patterning on phase behavior through sequence shuffling. We designed sequences with significantly increased phase separation propensity by shuffling the wild-type sequence, which contains well-mixed charged residues, to increase charge segregation. This result indicates the natural sequence is under negative selection to moderate this mode of interaction. We measured the contributions of tyrosine and arginine residues to phase separation experimentally through mutagenesis studies and computationally through direct interrogation of different modes of interaction using all-atom simulations. Finally, we show that despite these sequence perturbations, the RGG-derived condensates remain liquid-like. Together, these studies advance our fundamental understanding of key biophysical principles and sequence features important to phase separation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data on erosion and hydrogen fuel retention in Beryllium plasma-facing materials

ITER will use beryllium as a plasma-facing material in the main chamber, covering a total surface area of about 620 m 2 . Given the importance of beryllium erosion and co-deposition for tritium retention in ITER, significant efforts have been made to understand the behaviour of beryllium under fusion-relevant conditions with high particle and heat loads. This paper provides a comprehensive report on the state of knowledge of beryllium behaviour under fusion-relevant conditions: the erosion mechanisms and their consequences, beryllium migration in JET, fuel retention and dust generation. The paper reviews basic laboratory studies, advanced computer simulations and experience from laboratory plasma experiments in linear simulators of plasma–wall interactions and in controlled fusion devices using beryllium plasma-facing components. A critical assessment of analytical methods and simulation codes used in beryllium studies is given. The overall objective is to review the existing set of data with a broad literature survey and to identify gaps and research needs to broaden the database for ITER.

Erosion–deposition↗
DOE OSTI2024

Mechanistic Insights into the Origins of Selectivity in a Cu-Catalyzed C–H Amidation Reaction

The catalytic transformation of C-H to C-N bonds offers rapid access to fine chemicals and high-performance materials, but achieving high selectivity from undirected aminations of unactivated C(sp 3 )-H bonds remains an outstanding challenge. Here, we report the origins of the reactivity and selectivity of a Cu-catalyzed C-H amidation of simple alkanes. Using a combination of experimental and computational mechanistic studies and energy decomposition techniques, we uncover a switch in mechanism from inner-sphere to outer-sphere coupling between alkyl radicals and the active Cu(II) catalyst with increasing substitution of the alkyl radical. The combination of computational predictions and detailed experimental validation shows that simultaneous minimization of both Cu-C covalency and alkyl radical size increases the rate of reductive elimination and that both strongly electron-donating and electron-withdrawing substituents on the catalyst accelerate the selectivity-determining C-N bond formation process as a result of a change in mechanism. These findings offer design principles for the development of improved catalyst scaffolds for radical C-H functionalization reactions.

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

Computational investigation of the impact of metal–organic framework topology on hydrogen storage capacity

Metal–organic frameworks (MOFs) are promising, tunable materials for hydrogen storage. For application under cryogenic operating conditions, past work has run into a ceiling on performance due to a trade-off in the volumetric deliverable capacity (VDC) versus the gravimetric deliverable capacity (GDC). In this study, we computationally constructed and screened 105 230 MOF structures based on 529 nets to explore the effect of underlying topology on the hydrogen storage performance of the resulting materials. A machine learning model was developed based on simulated hydrogen uptake to facilitate screening of the entire dataset, and it successfully identified the top 10% of materials with a root-mean-square error of approximately 1 g L −1 as validated by subsequent grand canonical Monte Carlo simulations. We identified a promising structure based on the tsx topology that exhibits both VDC and GDC higher than the current benchmark material, MOF-5. Our data-driven analysis indicates that nets with higher net density yield MOFs with enhanced volumetric and gravimetric surface areas, thereby improving maximum VDC while shifting the capacity trade-off toward higher GDC.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Heat transfer enhancement due to cold cap motion from bubbling in a waste glass melter

In this study, a computational fluid dynamics (CFD) model was developed to model the motion of a solid cold cap in a waste glass melter. Forced convection bubblers at the base of the melter release air into the molten glass, which forms large bubbles that travel upwards to the cold cap and augment heat transfer from the glass to the cold cap. The CFD model employs the Navier- Stokes equations to solve for the fluctuating flowfield using a rigid body motion dynamic fluid body interaction module. This allows for movement of the floating body in response to the bubbling forces calculated at each time step. Further, the heat flux delivered to the cold cap by the convective bubbling is studied as a function of the bubbling rate. Results for the moving cold cap are compared with the computed heat flux trends for a stationary cold cap. The heat flux delivered to the cold cap from the glass is 25% higher for the case with the moving cold cap. The heat flux was found to be proportional to v0.6 as opposed to v0.9 (where v is the normalized bubbling rate) for the stationary cold cap.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Dynamic Undervolting to Improve Energy Efficiency on Multicore X86 CPUs

Chip manufacturers introduce redundancy at various levels of CPU design to guarantee correct operation, even for worst-case combinations of non-idealities in process variation and system operating conditions. This redundancy is implemented partly in the form of voltage margins. However, for a wide range of real-world execution scenarios these margins are excessive and merely translate to increased power consumption, hindering the effort towards higher-energy efficiency in both HPC and general purpose computing. Our study on the x86-64 Haswell and Skylake multicore microarchitectures reveals-wide voltage margins, which vary across different microarchitectures, different chip parts of the same microarchitecture, and across different workloads. We find that it is necessary to quantify-voltage margins using multi-threaded and multi-instance workloads, as characterization with single-threaded and single-instance workloads that do not stress the CPU to its full capacity typically identifies overly optimistic margins that lead to errors when applied in realistic program execution scenarios. In addition, we introduce, deploy and evaluate a run-time governor that dynamically reduces the supply voltage of modern multicore x86-64 CPUs. Our governor employs a model that takes as input a set of performance metrics which are directly measurable via performance monitoring counters and have high predictive value for the minimum tolerable supply voltage (V min ), to predict and apply the appropriate reduction for the workload at hand. Compared with the conventional DVFS governor, our approach in this study achieves up to 42 percent energy savings for the Skylake family and 34 percent for the Haswell family for complex, real-world applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Impact of Circumsolar Diffuse Radiation on the Numerical Computation and Forecasting of DNI

Weather Research and Forecasting model with solar extensions (WRF-Solar) uses the Fast All-sky Radiation Model for Solar applications (FARMS) to predict solar radiation from the forecasted atmospheric gases, aerosols, and clouds. The Beer-Bouguer-Lambert law utilized by FARMS as well as other radiative transfer models assumes Direct Normal Irradiance (DNI) is a narrow beam only covering the sun disk. This assumption is interpreted differently in solar observations by pyrheliometers where the circumsolar diffuse radiation is accounted. This study precisely computes circumsolar diffuse radiation in all-sky conditions using a radiative transfer model based on a parameterization of precomputed cloud transmittance and reflectance. The model is implemented in WRF-Solar to provide day-ahead DNI forecast in the north America. The computation and forecasting of DNI is compared with the Beer-Bouguer-Lambert law to understand the impact of circumsolar diffuse radiation.

aerosols↗
DOE OSTI2021

Characterization of Natural Consolidated Halloysite Nanotube Structures

Halloysite is a unique 1:1 clay mineral frequently appearing with nanotubular morphology, and having surfaces of different polarity with interesting and important technological applications. HNTs can be consolidated naturally in the earth by pressure and thermal flows. In this study of natural consolidated HNTs, the strength and hardness of these materials were found to be dependent on the presence of impurities (gibbsite, alunite, quartz, and other silica minerals), which accounted for the increased stability of such samples. In the absence of impurities, the strength of consolidated HNTs was significantly lower. The first 3D mapping of the pore structure of natural consolidated HNT is provided. The contributions of the porosity within the nanotubes and between the nanotubes were delineated using a combination of non-invasive ultra-small and small-angle X-ray scattering (USAXS/SAXS) analyses, BET/BJH pore size analyses, and computed tomography studies. A total porosity of 40%, as determined by X-ray attenuation and He porosimetry, was found for the natural consolidated HNTs, of which about one-third was due to the inter-HNT porosity. Nano-X-ray computed tomography (nano-XCT) analyses also indicated that 76% of the inter-HNT pores were smaller than 150 nm in diameter. The intra-HNT pore size determined by combined USAXS/SAXS and BET/BJH was about 10 nm. This pore network information is essential for the utilization of natural consolidated HNTs as a model geomaterial to investigate the effects of surface characteristics on confined fluid flow.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Air Exchange Rate Impact on Activity Equilibrium Factors and Inhalation Fractional Equilibrium Factors for Rn, Xe, Kr, Ar, Ne, and Their Progeny in Vapor Intrusion, Risk, and Dose Models

Exposure to the radioactive noble gasses, especially radon, is of high concern and poses a significant risk to humans in an indoor air environment as the second leading cause of lung cancer in the United States. To evaluate and minimize the risks posed by these gasses, it is important to understand their radiological and physical properties. The EPA’s Radon Vapor Intrusion Screening Level (RVISL) calculator calculates indoor air RVISLs based on target working levels (WLs), target excess lifetime cancer risk (ELCR), and annual dose limits for the actinon (Rn-219), thoron (Rn-220), and radon (Rn-222) decay series. The RVISLs are based on inhalation and submersion in gas cloud exposure routes for residential and commercial settings. The RVISLs are analogous to preliminary remediation goals (PRGs) and dose compliance concentrations (DCCs), where the isotope-specific values are in units of activity concentration (activity per unit volume). If the concentration of a parent isotope of radon or its progeny is found to exceed the RVISL, then further action to ensure cleanup of the contaminant may be necessary. In residential and commercial settings, the RVISLs will vary based on the air exchange rate present. The EPA’s Radionuclide PRG and DCC Calculators also assess the risk/dose from noble gases in the air due to household use of water like showering. In this study, a computational method in MATLAB was developed to determine the impact of the air exchange rate on the activity equilibrium factor (A eq ) and the inhalation fractional equilibrium factor (F eq ). Both factors are values that reflect the equilibrium concentrations of progeny to their parent in the air. These factors have a direct impact on the RVISL, PRG, and DCC calculations of WL, ELCR, and annual dose, respectively. This study builds on a previous report that only focused on actinon, thoron, and radon by revisiting the original A eq and F eq calculation methods, as well as including the values for the Rn-207, Rn-209, Rn-210, Rn-211, Rn-215, Rn-216, Rn-217, Rn-218, Rn-223, Ne-24, Ar-42, Ar-43, Ar-44, Kr-74, Kr-75, Kr-76, Kr-77, Kr-88, Kr-89, Xe-120, Xe-121, Xe-122, Xe-123, Xe-135m, and Xe-138 decay chains, which are not currently available in literature. The EPA’s RVISL calculator will be updated to include the new A eq and F eq values for the actinon, thoron, and radon decay chains, while the rest of the calculators will incorporate all the new A eq and F eq values as appropriate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Computational Fluid Dynamics Analysis of the Molten Salt Tritium Transport Experiment Test Section

Tritium, a radionuclide produced through neutron capture by lithium and other elements (beryllium and fluoride) in molten salts, presents unique challenges to radionuclide release. This is true for both fusion energy breeder blankets and molten salt fission reactors. The fundamental understanding of tritium transport is crucial to the safe design and operation of these reactors. The Molten Salt Tritium Transport Experiment (MSTTE), currently under construction at Idaho National Laboratory, aims to investigate tritium transport phenomena using a forced-convection fluoride salt loop. This loop is designed to study various transport mechanisms, such as permeation through metals and gas-liquid interactions, and is intended to support future research on tritium extraction units. A critical aspect of the MSTTE loop design is ensuring a fully developed velocity profile before the fluid reaches the permeation test section where measurements are made. This study employs computational fluid dynamics to model the salt flow behavior within the MSTTE permeation test section. A realizable k-ε turbulent model with enhanced wall treatment is used to simulate the single-phase, vertical upward flow of molten salt FLiNaK under isothermal conditions. The simulation results indicated flow distortion and underdeveloped profiles at all planned flow rates within the test section due to the 85-deg sharp bend. To address this issue, a reduced diameter with a reducer and expander and a flow conditioner are investigated to achieve fully developed flow. The analysis showed that the flow conditioner successfully corrected the flow profile, achieving fully developed behavior at a flow rate of 50 liters per minute (LPM). In conclusion, this research enhances our understanding of flow dynamics in molten salt systems and contributes to optimizing tritium transport control technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Hands-on with OWL: the Oak–Ridge Wang–Landau Monte Carlo software suite

The Oak–Ridge Wang–Landau (OWL) package is an open-source scientific software specialized for large-scale, Monte Carlo simulations for the study of materials properties at finite temperature. In this paper, we discuss the main features and capabilities of OWL, followed by detailed descriptions of building and running the code. The readers will be guided through the usage and functionality of the code with a few hands-on examples. This paper is based on a tutorial on OWL given at the 32nd Center for Simulational Physics Workshop on Recent Developments in Computer Simulation Studies in Condensed Matter Physics.

Li, Ying Wai↗