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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Fluid dynamic and thermodynamic analysis of a model pertaining to cryogenic fluid management in low gravity environments for a system with dynamically induced settling

The settling behavior of the liquid and gaseous phases of a fluid in a propellant and in a zero-g environment, when such settling is induced through the use of a dynamic device, in this particular case, a helical screw was studied. Particular emphasis was given to: (1) the description of a fluid mechanics model which seems applicable to the system under consideration, (2) a First Law of Thermodynamics analysis of the system, and (3) a discussion of applicable scaling rules.

Rios, J.↗
NASA NTRS1993

Dynamic subgrid-scale modeling for high-speed transitional boundary layers

The subgrid scales are modeled dynamically in a large-eddy simulation of transitional boundary-layer flow along a hollow cylinder at a Mach number of 4.5. The behavior of the dynamic-model coefficients, which is determined from local information in the resolved field, is investigated through both an a priori test with direct numerical simulation data for the same case and a complete large-eddy simulation. Both contractions proposed by Germano et al. (1991) and Lilly (1992) are used for the unique determination of the coefficients of the dynamic model, and their results are compared and assessed. The behavior, as well as the energy cascade of the subgridscale field structure, is investigated at various stages of the transition process.

El-Hady, Nabil M.↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
NASA NTRS1976

Dynamic modeling for evaluation of solar collector performance

Dynamic modeling is being developed to provide a tool for systematic analysis of performance characteristics in energy systems where time-dependent behavior is important. A dynamic model program designed to aid in the understanding of solar collector behavior over the full range of operating conditions was constructed and tested in the evaluation of a conceptual collector design.

Hamilton, C. L.↗
DOE OSTI2022

A level-of-details framework for representing occupant behavior in agent-based models

We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.

42 ENGINEERING↗
NASA NTRS2019

Cluster Analysis of Spectroscopic Line Profiles and EUV Emission in RMHD Simulations and Observations of the Solar Atmosphere

Spatially-resolved observations from the IRIS, SDO/AIA, and other space mission and ground-based telescopes, coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar atmosphere. To better understand the dynamical and thermodynamic properties in the simulation data and their connection to observations, it is essential to determine similarities in the behaviors of the synthesized and observed emission. However, the complexity of observational data and physical processes makes comparison of observations and modeling results difficult. In this work, we show the initial results of application of K-Means clustering (unsupervised machine learning) algorithm to two different problems: 1) recognition of the typical spectroscopic line profiles observed by IRIS during solar flares and their typical dynamic behavior; 2) recognition of shocks and heating events in synthetic AIA emission data obtained from StellarBox quiet-Sun simulations. The average silhouette width technique for the KMeans algorithm is utilized in different ways to obtain optimal numbers of clusters. We discuss application of the emission clustering to visualizations of the computational volume, understanding its evolutionary trends and behavior patterns, and inversion (reconstruction) of physical properties of the solar atmosphere from synthesizes emission data.

Sadykov, Viacheslav↗
DOE OSTI2020

Linking the Dynamic Response of the Carbon Dioxide-Concentrating Mechanism to Carbon Assimilation Behavior in Fremyella diplosiphon

ABSTRACT Cyanobacteria use a carbon dioxide (CO 2 )-concentrating mechanism (CCM) that enhances their carbon fixation efficiency and is regulated by many environmental factors that impact photosynthesis, including carbon availability, light levels, and nutrient access. Efforts to connect the regulation of the CCM by these factors to functional effects on carbon assimilation rates have been complicated by the aqueous nature of cyanobacteria. Here, we describe the use of cyanobacteria in a semiwet state on glass fiber filtration discs—cyanobacterial discs—to establish dynamic carbon assimilation behavior using gas exchange analysis. In combination with quantitative PCR (qPCR) and transmission electron microscopy (TEM) analyses, we linked the regulation of CCM components to corresponding carbon assimilation behavior in the freshwater, filamentous cyanobacterium Fremyella diplosiphon . Inorganic carbon (C i ) levels, light quantity, and light quality have all been shown to influence carbon assimilation behavior in F. diplosiphon . Our results suggest a biphasic model of cyanobacterial carbon fixation. While behavior at low levels of CO 2 is driven mainly by the C i uptake ability of the cyanobacterium, at higher CO 2 levels, carbon assimilation behavior is multifaceted and depends on C i availability, carboxysome morphology, linear electron flow, and cell shape. Carbon response curves (CRCs) generated via gas exchange analysis enable rapid examination of CO 2 assimilation behavior in cyanobacteria and can be used for cells grown under distinct conditions to provide insight into how CO 2 assimilation correlates with the regulation of critical cellular functions, such as the environmental control of the CCM and downstream photosynthetic capacity. IMPORTANCE Environmental regulation of photosynthesis in cyanobacteria enhances organismal fitness, light capture, and associated carbon fixation under dynamic conditions. Concentration of carbon dioxide (CO 2 ) near the carbon-fixing enzyme RubisCO occurs via the CO 2 -concentrating mechanism (CCM). The CCM is also tuned in response to carbon availability, light quality or levels, or nutrient access—cues that also impact photosynthesis. We adapted dynamic gas exchange methods generally used with plants to investigate environmental regulation of the CCM and carbon fixation capacity using glass fiber-filtered cells of the cyanobacterium Fremyella diplosiphon . We describe a breakthrough in measuring real-time carbon uptake and associated assimilation capacity for cells grown in distinct conditions (i.e., light quality, light quantity, or carbon status). These measurements demonstrate that the CCM modulates carbon uptake and assimilation under low-C i conditions and that light-dependent regulation of pigmentation, cell shape, and downstream stages of carbon fixation are critical for tuning carbon uptake and assimilation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Deformation behavior of annealed Cu64Zr36 metallic glass via molecular dynamics simulations

In the present work, we investigate the isothermal annealing process of Cu 64 Zr 36 metallic glass (MG) by means of molecular dynamics (MD) simulations, and characterize the compression properties under different temperatures and compressive rates. The pair distribution functions, the bond-orientational order, and the cluster-type index method are modeled and analyzed to characterize changes in the structure. Results of the modeling and analysis reveal that the MgZn 2 -type Laves, MgCu 2 -type Laves and five-fold local symmetry structures can be formed during the isothermal holding at 950 K. Study on the compression properties shows that at a fixed strain rate, the yield strength and yield drop all increase with decreasing temperature. At a fixed temperature, however, the increase of the strain rate leads to a noticeable increase in the yield strength at 600 K, but has little effect on yield strength at 10 K. Moreover, the modeling and analysis of the structure at a temperature of 10 K and strain-rate of 5 × 10 7 s -1 demonstrate that the order-disorder transformation initiates the shear band.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MST-8 Colloquium: The Effect of Microstructure on the Spall Strength and Damage of 1045 Steel [Slides]

Three different microstructures of the same steel alloy were investigated to study the influence of microstructure on spall strength and damage. Microstructure influences spall behavior within the explored dynamic regime. Second phase morphology, interphase interface characteristics, and grain boundary character shown to influence spall behavior. Continued understanding of microstructure’s influence on spall and damage needed for targeted material design.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Peculiar Behavior of He II Disturbances due to Sloshing Dynamics Driven by Jitter Accelerations Associated with Slew Motion in Microgravity

The mathematical formulation of Dewar container sloshing dynamics when partially filled with superfluid liquid He 11 driven by the gravity jitter acceleration associated with slew motion in a microgravity environment is studied. Numerical computation of the sloshing dynamics is based on the non-inertia container bound co-ordinate, and solving time-dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. This study discloses the capillary effect of the sloshing dynamics governing the liquid-vapour interface fluctuations driven by the gravity jitter acceleration associated with slew motion, which affects the stability of the fluid system in a microgravity environment. The peculiar behaviour of superfluid helium when reacting to the sloshing dynamics driven by the gravity jitter acceleration associated with slew motion in a microgravity environment is also investigated.

Hung, R. J.↗
NASA NTRS2002

The Stress-strain Behavior of Polymer-Nanotube Composites from Molecular Dynamics Simulations

Stress-strain curves of polymer-carbon nanotube composites are derived from molecular dynamics simulations of a single-walled carbon nanotube embedded in polyethylene. A comparison is made between the response to mechanical loading of a composite with a long, continuous nanotube (replicated via periodic boundary conditions) and the response of a composite with a short, discontinuous nanotube. Both composites are mechanically loaded in the direction of and transverse to the NT axis. The long-nanotube composite shows an increase in the stiffness relative to the polymer and behaves anisotropically under the different loading conditions. The short-nanotube composite shows no enhancement relative to the polymer, most probably because of its low aspect ratio. The stress-strain curves are compared with rule-of-mixtures predictions.

Frankland, S. J. V.↗
DOE OSTI2022

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation: Preprint

As the modern power systems are experiencing exceptional changes with increasing penetration of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system would obtain high system resilience, by not relying on the bulk power system restoration requiring significant human intervention and procedure to restore. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by-phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and start-up behaviors as well as network dynamics. In addition, active involvement of grid-following distributed energy resources (DER) is also studied to facilitate the black start process. It is shown that, by allowing multiple GFM inverters to collectively black start without master-slave coordination, a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗
DOE OSTI2020

Coupling solidification kinetics with phase-behavior computations in hydrodynamic simulations of high-pressure, dynamic-compression processes

In this study, we report a numerical scheme to integrate models for the kinetics of solidification processes together with phase-behavior computations in the context of continuum-scale hydrodynamic simulations. The objective of the phase-behavior computations is to determine the pressure and temperature, given the following three sets of inputs: (1) an appropriate equation of state to describe our system, (2) the phase fraction(s) produced by the kinetic models, (3) and the volume and internal energy obtained by solving the conservation equations that govern the hydrodynamic behavior. The kinetics are assumed to be governed by the Kolmogorov–Johnson–Mehl–Avrami equation, and the nucleation and growth rates that enter into that equation are functions of the pressure and temperature produced by the phase-behavior computations. Our formulation allows for the fluid and solid phases to be at different temperatures (thermal nonequilibrium) and pressures (arising from surface-tension-induced Laplace contributions). The formulation is presented in a fairly general setting that is independent of any particular material, although we demonstrate it in some examples related to high-energy-density science applications where materials are rapidly compressed to pressures exceeding several gigapascals in less than a microsecond. We conclude with a critical evaluation of our approach and provide suggestions for future work to improve the predictive capabilities and generality of the models.

42 ENGINEERING↗
DOE OSTI2026

Iron surface corrosion in supercritical CO2 at atomic scale investigated by molecular dynamics simulations

Understanding the corrosion behavior of steels in supercritical carbon dioxide (S-CO2) is essential for ensuring the safe application of S-CO2 as a heat-transfer fluid in high-temperature energy systems, including advanced nuclear reactors. In this work, molecular dynamics (MD) simulations using ReaxFF potential are performed to explore the atomic-scale corrosion mechanisms of body-centered cubic iron (BCC-Fe) in S-CO2. The results show that CO2 molecules in S-CO2 decompose at the Fe surface, generating free C and O atoms that form Fe-C and Fe-O bonds and subsequently produce oxides and carbides. Concurrently, Fe atoms dissolve from the surface and diffuse into the S-CO2 region, resulting in interdiffusion of Fe, C and O atoms at the interface. The corrosion-layer thickness calculations show that high pressure and temperature induced by S-CO2 have stronger effects than surface orientation on the corrosion process. In addition, surface Fe atoms undergo substantial displacement under S-CO2 exposure, further accelerating corrosion. When a radiation-induced void is introduced near the Fe surface, the corrosion is enhanced. The void-matrix interface expands the reaction surface area and simultaneously induces corrosion reactions inside the bulk, resulting in a deeper penetration of C and O and thicker corrosion layers. All these results indicate that high-temperature, high-pressure and radiation-induced voids can seriously affect the corrosion of Fe in S-CO2, and must be considered to better use S-CO2 in nuclear facilities.

Li, Wenhua↗
DOE OSTI2025

Dynamical dark energy from lattice quantum gravity

We study the behavior of the vacuum in Euclidean dynamical triangulations (EDT). Algorithmic improvements and better lattice spacing determinations allow us to test the properties of the emergent de Sitter geometries of our simulations to higher precision than previously possible. Although the agreement with de Sitter is good, the improved precision reveals deviations that can be interpreted as nontrivial vacuum dynamics, well described by a cosmological constant that runs with scale. The simulations show that the dominant running is quadratic and that the scale can be identified with the Hubble rate. Several key cross-checks support this picture, including consistent results across multiple lattice spacings and the fact that the null energy condition is not violated. The parameters of the running are fully determined by simulations, enabling predictions when extrapolated to the scales relevant for our Universe. This leads to a model for dark energy that is compatible with current observations, but which predicts deviations from the Standard Model of cosmology at the 𝒪⁡(10 −3 ) level in observables that could be tested with future improvements in precision measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Dynamic mechanical analysis of polymeric materials

Polymeric materials exhibit mechanical behavior which is dependent on temperature. Dynamic mechanical analysis measures the mechanical damping and resonant frequency of a material over a temperature range. Values of the dynamic loss modulus, storage modulus, and loss tangent can be calculated from these data. The glass transition temperature and onset temperature are obtained from curves of the dynamic moduli versus temperature.

Kern, Kristen T.↗