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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermal interfaces in dynamic compression experiments

Temperature is a difficult thermodynamic variable to measure in dynamic compression experiments. Optical pyrometry is a general-purpose technique for measuring temperature from a radiant surface, but that surface is often the interface between distinct materials with temperatures that vary spatially along the loading direction. This leads to a fundamental problem: how does the measured interface temperature relate to this temperature profile along the compression axis? Numerical analysis of loading history and thermal diffusion at these interfaces shows that seemingly subtle changes in experiment geometry can lead to very different temperature profiles. We compare these results to laboratory temperature measurements of shock-compressed tin.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part I: Flux and Eigenvalue Solutions

Computing in the energy dimension is one of the greatest challenges confronting present-day deterministic neutron transport solvers. Accurately resolving the neutron flux as neutrons downscatter across resonances in the nuclear cross sections currently requires considerable computing power and suffers from approximation errors. Flux uncertainty resulting from the uncertainty of the resonance structure is the single-largest cause of reactivity uncertainty. Any additional reference solution for the critical neutron downscattering problem with resonance phenomena would be a boon to verification and validation of neutronics codes. This paper establishes a benchmark to verify the accuracy of neutron transport criticality solvers along the energy dimension. For the first time, the analytic solution of the flux amplitude is derived in the particular case of an infinite homogeneous medium with isotropic scattering in the center of mass and an arbitrary number of no-threshold, neutral particle reaction resonances (e.g., radiative capture, fission, and resonance scattering). Furthermore, original analytic expressions are established to quantify the discrepancy between the ψ k (E) and ψ α (E) flux amplitudes, respective solutions of the multiplication factor k, or the exponential time-evolution frequency α eigenproblems. The physical study of these relations led to analysis of their first-order relative difference near the criticality condition α=0. Finally, numerical solutions are provided to a benchmark problem constituted of the first resonance of 239 Pu, the 6.67-eV resonance of 238 U, and a scattering isotope with a flat cross section, allowing for the computational verification of the energy resolution of current neutron transport criticality codes. Through these novel results, this analytic benchmark can serve as a reference to verify the energy resolution and sensitivity analysis of neutron transport criticality calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Synergy of coupled kink and tearing modes in fast ion transport

One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the 'kick' model has been developed to compute the evolution of the fast ion distribution from neutral beam injection using instabilities as phase-space resonance sources. Overall, the goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft x-ray diagnostics are used to identify the mode parameters in the National Spherical Torus Experiment. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows that the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Hybrid quantum simulations with qubits and qumodes on trapped-ion platforms

We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms. Trapped-ion systems have demonstrated record one- and two-qubit gate fidelities and long qubit coherence times, while qumodes, which can be represented by the collective vibrational modes of the ion chain, have remained relatively unex- plored for their use in computing. Using numerical simulations, we show that high-fidelity hybrid gates and measurement operations can be achieved for existing trapped-ion quantum platforms. As an exemplary application, we consider quantum simulations of the Jaynes-Cummings-Hubbard model, which is given by a one-dimensional chain of interacting spin and boson degrees of free- dom. Using classical simulations, we study its real-time evolution and develop a suitable variational quantum algorithm for ground state preparation. Furthermore, our results motivate further studies of hybrid quantum computing in this context, which may lead to direct applications in condensed matter and fundamental particle and nuclear physics.

Lower-dimensional field theories↗
DOE OSTI2022

Using kernel-based statistical distance to study the dynamics of charged particle beams in particle-based simulation codes

Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as numerical diagnostics for simulations involving charged-particle beams. Related measures of statistical dependence are also described. The resulting diagnostics provide sensitive measures of dynamical processes important for beams in nonlinear or high-intensity systems, which are otherwise difficult to characterize. Here, the focus is on kernel-based methods such as maximum mean discrepancy, which have a well-developed mathematical foundation and reasonable computational complexity. Several benchmark problems and examples involving intense beams are discussed. While the focus is on charged-particle beams, these methods may also be applied to other many-body systems such as plasmas or gravitational systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Constructing Neural Network Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, and chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in applying data-driven modeling techniques to solve a wide range of problems in physics and engineering. Here this article provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Synergy of Coupled Kink and Tearing Modes in Fast Ion Transport

One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the ''kick" model has been developed to compute the evolution of the fast ion distribution from the neutral beam injection using instabilities as phase space resonance sources. The goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft X-ray diagnostics are used to identify the mode parameters in NSTX. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transpor

Energetic Particles↗
DOE OSTI2024

Chromosome-level genome assemblies and genetic maps reveal heterochiasmy and macrosynteny in endangered Atlantic Acropora

Abstract Background Over their evolutionary history, corals have adapted to sea level rise and increasing ocean temperatures, however, it is unclear how quickly they may respond to rapid change. Genome structure and genetic diversity contained within may highlight their adaptive potential. Results We present chromosome-scale genome assemblies and linkage maps of the critically endangered Atlantic acroporids,Acropora palmataandA. cervicornis. Both assemblies and linkage maps were resolved into 14 chromosomes with their gene content and colinearity. Repeats and chromosome arrangements were largely preserved between the species. The family Acroporidae and the genusAcroporaexhibited many phylogenetically significant gene family expansions. Macrosynteny decreased with phylogenetic distance. Nevertheless, scleractinians shared six of the 21 cnidarian ancestral linkage groups as well as numerous fission and fusion events compared to other distantly related cnidarians. Genetic linkage maps were constructed from oneA. palmatafamily and 16A. cervicornisfamilies using a genotyping array. The consensus maps span 1,013.42 cM and 927.36 cM forA. palmataandA. cervicornis, respectively. Both species exhibited high genome-wide recombination rates (3.04 to 3.53 cM/Mb) and pronounced sex-based differences, known as heterochiasmy, with 2 to 2.5X higher recombination rates estimated in the female maps. Conclusions Together, the chromosome-scale assemblies and genetic maps we present here are the first detailed look at the genomic landscapes of the critically endangered Atlantic acroporids. These data sets revealed that adaptive capacity of Atlantic acroporids is not limited by their recombination rates. The sister species maintain macrosynteny with few genes with high sequence divergence that may act as reproductive barriers between them. In the AtlanticAcropora, hybridization between the two sister species yields an F1 hybrid with limited fertility despite the high levels of macrosynteny and gene colinearity of their genomes. Together, these resources now enable genome-wide association studies and discovery of quantitative trait loci, two tools that can aid in the conservation of these species.

Biotechnology & Applied Microbiology↗
DOE OSTI2021

Evolution of Pore Structure and Permeability of Rocks Under Hydrothermal Conditions (Final Report)

The physical and transport properties of porous rocks can be altered by a variety of diagenetic, metamorphic, and tectonic processes, and the changes that result are of critical importance to such industrial applications as resource recovery, carbon dioxide sequestration, and waste isolation in geologic formations. The associated interrelationships between rocks, pore fluids and deformation are also key to understanding many natural processes, including dynamic metamorphism, fault mechanics, fault stability and pressure solution creep. In this project, we investigated the changes of permeability and pore geometry owing to inelastic deformation by solution-transfer, brittle fracturing and dislocation creep. In particular, we studied the coupling between pore fluids and deformation in fluid-filled quartz, calcite, mudstones and ultramafic rocks and examine the effects of coupled mechanical and chemical processes on the evolution of porosity and permeability under hydrothermal conditions. The investigations used a combination of techniques, that included triaxial laboratory experiments; uniaxial compressive loading with in situ observations of microstructure; permeability under hydrostatic compression; observations of microstructure using optical and electron microscopes, and micro-CT imaging; and numerical calculations. Laboratory experiments were designed to provide mechanical and transport data under conditions that isolate the particular mechanisms responsible for the changes. The data obtained were used to quantify changes in surface roughness, porosity, pore dimensions and their spatial fluctuations. The results of the experiments and data from image analyses were compared to the results of network, finite-difference and other numerical models to verify the validity of experimentally established relations between permeability and other rock properties. A bibliography for the period from 2015-2019 is appended below. New results obtained in the final year and the unfunded extension period are detailed below.

58 GEOSCIENCES↗
DOE OSTI2021

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Optimization of the artificial viscosity in Lagrangian staggered discretization codes. Modeling 1D stand-alone shock - case study

We have developed new measures of errors for numerical shock. The new approach is based on analysis of the structure function, and separation of the errors related to oscillations and shock width, which also include error in the position of the ”center” of the numerical shock. We have demonstrated that those measures correctly characterize the numerical solution. We introduced an objective function in, which both types of errors are weighted, and presented optimal values of the coefficients of the linear and quadratic viscosity for different weights and different Mach numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Diversified Therapeutic Phage Cocktails from Close Relatives of the Target Bacterium

This project tackles the antibiotic resistance crisis, developing a new method for discovering numerous efficacious bacteriophages for therapeutic cocktails against bacterial pathogens. The phage therapy approach to infectious disease, recently rekindled in U.S. medicine, requires numerous phages for each bacterial pathogen. Our approach 1) uses Sandia-unique software to identify dormant phages (prophages) integrated into bacterial chromosomes, 2) identifies prophage-laden bacteria that are close relatives of the target pathogenic strain to be killed, and 3) engineers away properties of these phages that are undesirable for therapy. We have perfected our phage-finding software, implemented our phage therapy strategy by targeting the pathogen Pseudomonas aeruginosa, and prepared new software to assist the phage engineering. We then turned toward Burkholderia pathogens, aiming to overcome the difficulty to transform these bacteria with a novel phage conjugation approach. Our work demonstrates the validity of a new approach to phage therapy for killing antibiotic resistant pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dynamic Pressure Drag on Rising Buoyant Thermals in a Neutrally Stable Environment

Abstract This study examines dynamic pressure drag on rising dry buoyant thermals. A theoretical expression for drag coefficient C d as a function of several other nondimensional parameters governing thermal dynamics is derived based on combining the thermal momentum budget with the similarity theory of Scorer. Using values for these nondimensional parameters from previous studies, the theory suggests drag on thermals is small relative to that on solid spheres in laminar or turbulent flow. Two sets of numerical simulations of thermals in an unstratified, neutrally stable environment using an LES configuration of the Cloud Model 1 (CM1) are analyzed. One set has a relatively low effective Reynolds number R e and the other has an order-of-magnitude-higher R e ; these produce laminar and turbulent resolved-scale flows, respectively. Consistent with the theoretical C d , the magnitude of drag is small in all simulations. However, whereas the laminar thermals have C d ≈ 0.01, the turbulent thermals have weakly negative drag ( C d ≈ −0.1). This difference is explained by the laminar thermals having near vertical symmetry but the turbulent thermals exhibiting considerable vertical asymmetry of their azimuthally averaged flows. In the laminar thermals, buoyancy rapidly becomes concentrated around the main centers of rotation located along the horizontal central axis, leading to expansion of thermals via baroclinic vorticity generation but doing little to break vertical symmetry of the flow. Vertical asymmetry of the azimuthally averaged flow of turbulent thermals is attributed mainly to small-scale resolved eddies that are concentrated in the upper part of the thermals.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

The Relative Contribution to Heavy Metals Production from Binary Neutron Star Mergers and Neutron Star–Black Hole Mergers

The origin of the heavy elements in the universe is not fully determined. Neutron star–black hole (NSBH) and binary neutron star (BNS) mergers may both produce heavy elements via rapid neutron-capture (r-process). We use the recent detection of gravitational waves from NSBHs, improved measurements of the neutron star equation of state (EoS), and the most modern numerical simulations of ejected material from binary collisions to measure the relative contribution of NSBHs and BNSs to the production of heavy elements. As the amount of r-process ejecta depends on the mass and spin distribution of the compact objects, as well as on the EoS of the neutron stars, we consider various models for these quantities, informed by gravitational-wave and pulsar data. We find that in most scenarios, BNSs have produced more r-process elements than NSBHs over the past 2.5 billion years. If black holes have preferentially small spins, BNSs can produce at least twice the amount of r-process elements than NSBHs. If black hole spins are small and there is a dearth of low-mass (<5M ⊙ ) black holes within NSBH binaries, BNSs can account for the near totality of the r-process elements from binaries. For NSBH to produce a large fraction of r-process elements, black holes in NSBHs must have small masses and large aligned spins, which is disfavored by current data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Characterizing Mesoscale Cellular Convection in Marine Cold Air Outbreaks With a Machine Learning Approach

Abstract During marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

On the combustion of n-butyl acetate droplets

This paper presents an experimental and numerical study of the combustion of isolated n‑butyl acetate droplets in the standard atmosphere. Numerical simulations are reported using a model that incorporates unsteady gas and liquid transport, variable properties, and radiation. Three skeletal mechanisms of n‑butyl acetate, derived from a large detailed mechanism comprised of 819 species and 52,698 reactions, were used in the numerical simulations to evaluate the influence of the kinetic mechanism on burning. The reduced mechanisms comprised 212 species and 5413 reactions, 157 species and 3089 reactions, and 105 species and 1035 reactions. The numerical model did not include soot formation, though qualitatively mild sooting was noted only for droplets larger than 0.7 mm. The numerical predictions were in good agreement with experimental measurements of droplet and flame diameters. Flame extinction was numerically predicted which was attributed to a decrease of the characteristic diffusion time relative to the chemical time as droplet burned. Effects of initial droplet diameter on the evolution of maximum gas temperature (Tmax) and peak mole fractions of CO2 and CO are also examined numerically.

09 BIOMASS FUELS↗
DOE OSTI2021

Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon

Abstract In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion , defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content ( ) to the adiabatic liquid water content ( ), while no strong correlation between and is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases , explaining the inverse relationship between and in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on . The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform within polluted clouds. These findings can be useful for parameterizing the shape parameter ( ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.

54 ENVIRONMENTAL SCIENCES↗