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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Lattice Boltzmann Method for Predicting Porous Transport Layer Performance During Electrolysis

Electrolysis, the splitting of water into oxygen and hydrogen using electricity, is a sustainable way to produce green hydrogen for energy storage. In polymer electrolyte membrane (PEM) water electrolysis, water is brought into contact with charged catalyst layers and electrochemically separated into oxygen and hydrogen. The hydrogen product formed at the cathode is carried through the catalyst layer for eventual collection, while the oxygen by-product formed at the anode is removed from the surface via a multiphase interaction with circulating water and a solid porous transport layer (PTL). The design of this PTL aids in the detachment and advection of the oxygen by-product and thereby plays a role in the overall efficacy of the catalyst. In this presentation, we present our initial results modeling this multiphase system using a single-component, multiphase lattice Boltzmann method. We use the Shan-Chen model describing inter-particle forces to capture both the cohesion of the water (liquid) and oxygen (gas) phases and their interaction with the PTL (solid) (Shan and Chen, 1993). We use a Carnahan-Starling equation of state to model the effective density governing these inter-particle interactions which allows us to model this relatively high density ratio system (Carnahan and Starling, 1969). With these simulations, we show that the geometry and heterogeneity of the PTL geometry plays a large role in its ability to move oxygen away from the catalyst layer and the resulting bubble structures that are formed within the PTL. The current work demonstrates these effects using synthesized PTL geometries and 2D physics, which will be extended to experimentally-imaged PTL sections and 3D algorithms in the near future.

Boltzmann↗
DOE OSTI2025

Establishing Models for Digital Twin of Hydropower Systems Using Probability Density Function Shaping

This paper introduces a digital twin modeling method for hydropower systems with Kaplan turbines using probability density function (PDF) shaping. We first use multilayer perceptron (MLP) model to build the discretized openloop Kaplan unit, where the MLP is trained by historical data. Then we use a proportional integral double derivative (PIDD) controller and a lead-lag exciter to test the obtained digital twin model in a closed-loop fashion. Simulation results show that the proposed digital twin modeling method can accurately capture the dynamics of the Kaplan hydropower unit. Finally, we show that the obtained digital twin can help to optimize the PIDD parameters. Compared with the original PIDD controller, the optimized one can achieve an over 90% improvement on the mean square tracking error.

Yin, Zhun [New York University]↗
DOE OSTI2019

Pair Density Wave in the Doped t - J Model with Ring Exchange on a Triangular Lattice

In our previous study, we found a quantum spin liquid phase with a spinon Fermi surface in the two dimensional spin-1/2 Heisenberg model with four-spin ring exchange on a triangular lattice. In this work we dope the spinon Fermi surface phase by studying the $t - J$ model with four-spin ring exchange. We perform density matrix renormalization group calculations on four-leg cylinders of a triangular lattice and find that the dominant pair correlation function is that of a pair density wave; i.e., it is oscillatory while decaying with distance with a power law. The doping dependence of the period is studied. This is the first example where a pair density wave is the dominant pairing in a generic strongly interacting system where the pair density wave cannot be explained as a composite order and no special symmetry is required.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1991

Fluid hydrogen at high density - Pressure dissociation

A model for the Helmholtz free energy of fluid hydrogen at high density and high temperature is developed. This model aims at describing both pressure and temperature dissociation and ionization and bears directly on equations of state of partially ionized plasmas, as encountered in astrophysical situations and high-pressure experiments. This paper focuses on a mixture of hydrogen atoms and molecules and is devoted to the study of the phenomenon of pressure dissociation at finite temperatures. In the present model, the strong interactions are described with realistic potentials and are computed with a modified Weeks-Chandler-Andersen fluid perturbation theory that reproduces Monte Carlo simulations to better than 3 percent. Theoretical Hugoniot curves derived from the model are in excellent agreement with experimental data.

Saumon, Didier↗
DOE OSTI2021

Stripe order enhanced superconductivity in the Hubbard model

Unidirectional (“stripe”) charge density wave order has now been established as a ubiquitous feature in the phase diagram of the cuprate high-temperature superconductors, where it generally competes with superconductivity. Nonetheless, on theoretical grounds it has been conjectured that stripe order (or other forms of “optimal” inhomogeneity) may play an essential positive role in the mechanism of high-temperature superconductivity. Here, we report density matrix renormalization group studies of the Hubbard model on long four- and six-leg cylinders, where the hopping matrix elements transverse to the long direction are periodically modulated—mimicking the effect of putative period 2 stripe order. We find that even modest amplitude modulations can enhance the long-distance superconducting correlations by many orders of magnitude and drive the system into a phase with a substantial spin gap and superconducting quasi–long-range order with a Luttinger exponent, K sc ~ 1.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Chaos on the hypercube

We analyze the spectral properties of a d-dimensional HyperCubic (HC) lattice model originally introduced by Parisi. The U(1) gauge links of this model give rise to a magnetic flux of constant magnitude φ but random orientation through the faces of the hypercube. The HC model, which also can be written as a model of 2d interacting Majorana fermions, has a spectral flow that is reminiscent of Maldacena-Qi (MQ) model, and its spectrum at φ = 0, actually coincides with the coupling term of the MQ model. As was already shown by Parisi, at leading order in 1/d, the spectral density of this model is given by the density function of the Q-Hermite polynomials, which is also the spectral density of the double-scaled Sachdev-Ye-Kitaev model. Parisi demonstrated this by mapping the moments of the HC model to Q-weighted sums on chord diagrams. We point out that the subleading moments of the HC model can also be mapped to weighted sums on chord diagrams, in a manner that descends from the leading moments. The HC model has a magnetic inversion symmetry that depends on both the magnitude and the orientation of the magnetic flux through the faces of the hypercube. The spectrum for fixed quantum number of this symmetry exhibits a transition from regular spectra at φ = 0 to chaotic spectra with spectral statistics given by the Gaussian Unitary Ensembles (GUE) for larger values of φ. For small magnetic flux, the ground state is gapped and is close to a Thermofield Double (TFD) state.

1/N expansion↗
NASA NTRS1928

Tests on Models of Three British Airplanes in the Variable Density Wind Tunnel

This report contains the results of tests made in the National Advisory Committee for Aeronautics variable density wind tunnel on three airplane models supplied by the British Aeronautical Research Committee. These models, the BE-2E with R.A.F. 19 wings, the British Fighter with R.A.F. 15 wings, and the Bristol Fighter with R.A.F. 30 wings, were tested over a wide range in Reynolds numbers in order to supply data desired by the Aeronautical Research Committee for scale effect studies. The maximum lifts obtained in these tests are in excellent agreement with the published results of British tests, both model and full scale. No attempt is made to compare drag data, owing to the emission of tail surfaces, radiator, etc., from the model, but is shown that the scale effect observed on the drag coefficients in these tests is due to a large extent to the parts of the models other than the wings. (author)

Higgins, George J↗
DOE OSTI2021

Recalculation of Soil Bulk Density Used in the Scorpius MCNP6 Model

The soil composition used in the Scorpius MCNP6.2 (Ref. 1) model was recently recalculated. Originally, it was “determined using the United States Geological Survey (USGS) Mercury Core Library and the Nevada National Security Site U.S. Geological Survey Databases (NNSS USGS) and Nevada National Security Site Petrographic, Geochemical, and Geophysical Database (NNSS PGG),” but the details had been lost. Reference 2 documents the updated soil composition determination. Reference 2 estimated the grain density of the soil instead of the bulk density. This report corrects that error. I am indebted to Garrett Euler (EES-17) for reading Ref. 2, pointing out its errors, and guiding me through the correct calculations. This report is organized as follows. For completeness, the composition calculations from Ref. 2 are repeated: Sec. II discusses the data that are reported in the PGG Access database, and Sec. III uses the data in the PGG Access database to compute the composition of the soil. Section IV estimates the bulk density of the soil. Section V evaluates the soil wall thickness in the Scorpius model. Section VI estimates the effect of the soil density change on previously calculated results. Section VII presents a summary and conclusions. Input files and output files are listed in appendices.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1972

Diffusion model for the phase delay between thermospheric density and temperature.

Consideration of a two-dimensional time-dependent model in which the thermosphere dynamics is excited by the UV heat input within the thermosphere, showing that the wind-induced variations in the diurnal component of atomic oxygen dominate over its temperature-induced variations up to 200 km. The assumption of diffusive equilibrium is therefore in general not valid for O within the lower thermosphere. The effect of the diurnal wind circulation is to redistribute O so that the diurnal variations in the forbidden O/forbidden N2 and forbidden O/forbidden O2 ratios are damped by about 20%, thus contributing to the maintenance of the nighttime F2 region, and the maximum in the diurnal variation of O is shifted by one to two hours away from the temperature maximum toward noon, thus contributing significantly to the temperature-density time lag at thermospheric heights above 200 km, where O becomes the major constituent.

Mayr, H. G.↗
DOE OSTI2025

Understanding of Ag Nanocatalysts for Electrocatalytic CO2 Conversion: Effects of Particle Size and Carbon Support

In this talk, we combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate Ag based electrocatalysts for CO2 reduction reaction (CO2RR). Our goal is to understand the critical characteristics governing the activity and selectivity of Ag electrocatalysts. Ag electrocatalysts were grown on highly oriented pyrolytic graphite (HOPG) in the UHV chamber, characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM), and then tested in a custom-built gastight H-cell. Supported by computational modeling based on density functional theory (DFT) calculations and microkinetic modeling (MKM), our studies revealed a strong size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm. Smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR reactivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter. This knowledge is key to understand electrocatalysts performance and to ultimately guide electrocatalyst design

Ag nanoparticles↗
NASA NTRS1992

Thermal plasma in the inner kronian magnetosphere

Since the flybys of the twin Voyager spacecraft through the magnetosphere of Saturn in the early 1980s, conflicting interpretations of the phenomena observed have appeared in the literature. An attempt is made here to constrain the transport rate in the inner magnetosphere by appeal to plasma observations of density and temperature. The conflicting models range from those entailing fast transport, which limits the density, to models in which the ion density is limited by the process of recombination. The coupled differential equations for Coulomb and radiative heat transfer between hot electrons, thermal electrons and thermal heavy ions are solved. It is concluded that diffusive transport is not the dominant factor in determining the plasma state of the inner magnetosphere of Saturn. Support is found for a previously proposed model of a ring source for the cold dense plasma observed by Voyager 2 at the ring plane crossing.

Eviatar, A.↗
DOE OSTI2021

Describing adsorption of benzene, thiophene, and xenon on coinage metals by using the Zaremba–Kohn theory-based model

Semilocal (SL) density functional approximations (DFAs) are widely applied but have limitations due to their inability to incorporate long-range van der Waals (vdW) interaction. Non-local functionals (vdW-DF, VV10, and rVV10) or empirical methods (DFT+D, DFT+vdW, and DFT+MBD) are used with SL-DFAs to account for such missing interaction. The physisorption of a molecule on the surface of the coinage metals (Cu, Ag, and Au) is a typical example of systems where vdW interaction is significant. However, it is difficult to find a general method that reasonably describes both adsorption energy and geometry of even the simple prototypes of cyclic and heterocyclic aromatic molecules such as benzene (C 6 H 6 ) and thiophene (C 4 H 4 S), respectively, with reasonable accuracy. Here, we present an alternative scheme based on Zaremba–Kohn theory, called DFT+vdW-dZK. We show that unlike other popular methods, DFT+vdW-dZK and particularly SCAN+vdW-dZK give an accurate description of the physisorption of a rare-gas atom (xenon) and two small albeit diverse prototype organic molecules on the (111) surfaces of the coinage metals.

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

Solvent Phase Optimizations Improve Correlations with Experimental Stability Constants for Aqueous Lanthanide Complexes

Stability constants provide insight into ion complexation in water. While computational studies have been shown to model the energy of the complexation successfully using a thermodynamic cycle approach, it does not extend to calculating the stability constants for 1:1 lanthanide to ligand complexes in solution. Using B3LYP and 6-31+G* Pople basis with small core effective core potential (ECP) on the lanthanum ion, and a solvent model based on the full solute electron density (SMD) solvation model we computed and compared with previously published stability constants of the ligands: acetate, acetohydroximate, acetylacetonate, methanoate, tropolonate, hydroxide, catecholate, malonate, oxalate, phthalate, and sulfate. The best R 2 values for the thermodynamic cycle can only be determined by separating the mono and divalent ions to achieve an R 2 value of 0.86 and 0.74 for mono and divalent ions, respectively. We show that by optimizing the lanthanide-ligand structures in implicit solvent, we achieve an improved correlation between experimental and computed stability constants of R 2 value of 0.89 for the combined mono and divalent ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Measured acoustic properties of variable and low density bulk absorbers

Experimental data were taken to determine the acoustic absorbing properties of uniform low density and layered variable density samples using a bulk absober with a perforated plate facing to hold the material in place. In the layered variable density case, the bulk absorber was packed such that the lowest density layer began at the surface of the sample and progressed to higher density layers deeper inside. The samples were placed in a rectangular duct and measurements were taken using the two microphone method. The data were used to calculate specific acoustic impedances and normal incidence absorption coefficients. Results showed that for uniform density samples the absorption coefficient at low frequencies decreased with increasing density and resonances occurred in the absorption coefficient curve at lower densities. These results were confirmed by a model for uniform density bulk absorbers. Results from layered variable density samples showed that low frequency absorption was the highest when the lowest density possible was packed in the first layer near the exposed surface. The layers of increasing density within the sample had the effect of damping the resonances.

Dahl, M. D.↗
NASA NTRS1987

A flare event of the long-period RS Canum Venaticorum system IM Pegasi

The characteristics of a flare event detected on the long-period RS CVn system IM Pegasi are reported. The low-resolution spectrum show enhancements of up to a factor of five in some emission lines. All of the ultraviolet emission lines normally visible are enhanced significantly more than the normal 30 rotational modulation. Emission fluxes of both the quiescent and flare event are used to construct models of the density and temperature variation with height. These models reveal a downward shift of the transition region during the flare. Scaled models of the quiet and flaring solar outer atmosphere are used to estimate the filling factor of the flare event at about 30 percent of the stellar surface. The pattern of line enhancements in the flare is the same as a previous event in Lambda Andromeda observed previously.

Buzasi, Derek L.↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS2010

Physical Invariants of Intelligence

A program of research is dedicated to development of a mathematical formalism that could provide, among other things, means by which living systems could be distinguished from non-living ones. A major issue that arises in this research is the following question: What invariants of mathematical models of the physics of systems are (1) characteristic of the behaviors of intelligent living systems and (2) do not depend on specific features of material compositions heretofore considered to be characteristic of life? This research at earlier stages has been reported, albeit from different perspectives, in numerous previous NASA Tech Briefs articles. To recapitulate: One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Mathematical models of motor dynamics are used to simulate the observable physical behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. At the time of reporting the information for this article, the focus of this research was upon the following aspects of the formalism: Intelligence is considered to be a means by which a living system preserves itself and improves its ability to survive and is further considered to manifest itself in feedback from the mental dynamics to the motor dynamics. Because of the feedback from the mental dynamics, the motor dynamics attains quantum-like properties: The trajectory of the physical aspect of the system in the space of dynamical variables splits into a family of different trajectories, and each of those trajectories can be chosen with a probability prescribed by the mental dynamics. From a slightly different perspective, the mechanism of decision-making is feedback from the mental dynamics to the motor dynamics, and this mechanism provides a quantum-like collapse of a random motion into an appropriate deterministic state, such that entropy undergoes a pronounced decrease. The existence of this mechanism is considered to be an invariant of intelligent behavior of living systems, regardless of the origins and material compositions of the systems.

Zak, Michail↗
NASA NTRS2020

Reconstruction of Historical Surface Mass Balance, 1984–2017 from GreenTrACS Multi-offset Ground-penetrating Radar

We present continuous estimates of snow and firn density, layer depth and accumulation from a multi-channel, multi-offset, ground-penetrating radar traverse. Our method uses the electromagnetic velocity, estimated from waveform travel-times measured at common-midpoints between sources and receivers. Previously, common-midpoint radar experiments on ice sheets have been limited to point observations. We completed radar velocity analysis in the upper ~2 m to estimate the surface and average snow density of the Greenland Ice Sheet. We parameterized the Herron and Langway (1980) firn density and age model using the radar-derived snow density, radar-derived surface mass balance (2015–2017) and reanalysis-derived temperature data. We applied structure-oriented filtering to the radar image along constant age horizons and increased the depth at which horizons could be reliably interpreted. We reconstructed the historical instantaneous surface mass balance, which we averaged into annual and multidecadal products along a 78 km traverse for the period 1984–2017. We found good agreement between our physically constrained parameterization and a firn core collected from the dry snow accumulation zone, and gained insights into the spatial correlation of surface snow density.

glacier geophysics↗