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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

A walk through the planned CS building

Using the architectural plan views of our future computer science building as test objects, we have completed the first stage of a Building walkthrough system. The inputs to our system are AutoCAD files. An AutoCAD converter translates the geometrical information in these files into a format suitable for 3D rendering. Major model errors, such as incorrect polygon intersections and random face orientations, are detected and fixed automatically. Interactive viewing and editing tools are provided to view the results, to modify and clean the model and to change surface attributes. Our display system provides a simple-to-use user interface for interactive exploration of buildings. Using only the mouse buttons, the user can move inside and outside the building and change floors. Several viewing and rendering options are provided, such as restricting the viewing frustum, avoiding wall collisions, and selecting different rendering algorithms. A plan view of the current floor, with the position of the eye point and viewing direction on it, is displayed at all times. The scene illumination can be manipulated, by interactively controlling intensity values for 5 light sources.

Khorramabadi, Delnaz↗
NASA NTRS2009

Transonic Tones and Excess Broadband Noise in Overexpanded Supersonic Jets

Noise characteristics of convergent-divergent (C-D) nozzles in the overexpanded regime are the focus of this paper. The flow regime is encountered during takeoff and landing of certain airplanes and also with rocket nozzles in launch-pad environment. Experimental results from laboratory-scale single nozzles are discussed. The flow often undergoes a resonance accompanied by emission of tones (referred to as transonic tones). The phenomenon is different from the well-known screech tones. Unlike screech, the frequency increases with increasing supply pressure. There is a staging behavior odd harmonic stages occur at lower pressures while the fundamental occurs in a range of relatively higher pressures. A striking feature is that tripping of the nozzle s internal boundary layer tends to suppress the resonance. However, even in the absence of tones the broadband levels are found to be high. That is, relative to a convergent case and at same pressure ratio, the C-D nozzles are found to be noisier, often by more than 10dB. This excess broadband noise (referred to as EBBN) is further explored. Its characteristics are found to be different from the well-known broadband shockassociated noise ( BBSN ). For example, while the frequency of the BBSN peak varies with observation angle no such variation is noted with EBBN. The mechanisms of the transonic tone and the EBBN are not completely understood yet. They appear to be due to unsteady shock motion inside the nozzle. The shock drives the flow downstream like a vibrating diaphragm, and resonance takes place similarly as with acoustic resonance of a conical section having one end closed and the other end open. When the boundary layer is tripped, apparently a breakdown of azimuthal coherence suppresses the resonance. However, there is still unsteady shock motion albeit with superimposed randomness. Such random motion of the internal shock and its interaction with the separated boundary layer produces the EBBN.

Zaman, Khairul B. M. Q.↗
DOE OSTI2020

Equilibrium Thermodynamic Properties of Aqueous Solutions of Ionic Liquid 1-Ethyl-3-Methylimidazolium Methanesulfonate [EMIM][MeSO3]

Abstract The ionic liquid 1-ethyl-3-methylimidazolium methanesulfonate ([EMIM][MeSO 3 ]) has been considered as a promising alternative desiccant to triethylene glycol and lithium bromide commonly used in the industry. In this paper, the water activity coefficient of this binary system was measured from 303 K to 363 K with water concentration from 18% to 92%. The interaction energies between the ionic liquid molecules ( $${g}_{22}$$ g 22 ) and between the ionic liquid and water molecules ( $${g}_{12}$$ g 12 ) for the [EMIM][MeSO 3 ]/water binary system were determined from the water activity coefficient data using the Non-Random Two-Liquid (NRTL) model. The magnitude of the interaction energy between the [EMIM][MeSO 3 ] and water molecules ( $${g}_{12}$$ g 12 ) was found to be in the range of 45~49 kJ/mol, which was about 20% larger than that between the water molecules ( $${g}_{11}$$ g 11 ) in the [EMIM][MeSO 3 ]/water system. The large ( $${g}_{12}$$ g 12 ) can explain many observed macroscopic thermodynamic properties such as strong hygroscopicity in the ionic liquid [EMIM][MeSO 3 ]. These interaction energies were used to determine the heat of desorption of the [EMIM][MeSO 3 ]/water system, and the obtained heat of desorption was in good agreement with that calculated from the conventional Clausius-Clapeyron Equation.

42 ENGINEERING↗
NASA NTRS1975

Wave theory of turbulence in compressible media (acoustic theory of turbulence)

The generation and the transmission of sound in turbulent flows are treated as one of the several aspects of wave propagation in turbulence. Fluid fluctuations are decomposed into orthogonal Fourier components, with five interacting modes of wave propagation: two vorticity modes, one entropy mode, and two acoustic modes. Wave interactions, governed by the inhomogeneous and nonlinear terms of the perturbed Navier-Stokes equations, are modeled by random functions which give the rates of change of wave amplitudes equal to the averaged interaction terms. The statistical framework adopted is a quantum-like formulation in terms of complex distribution functions. The spatial probability distributions are given by the squares of the absolute values of the complex characteristic functions. This formulation results in nonlinear diffusion-type transport equations for the probability densities of the five modes of wave propagation.

Kentzer, C. P.↗
DOE OSTI2022

Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories

In this work, we present an efficient energy-based method for structural optimization with stochastic electronic structure theories, such as diffusion quantum Monte Carlo (DMC). This method is based on robust line-search energy minimization in reduced parameter space, exploiting approximate but accurate Hessian information from a surrogate theory, such as density functional theory. The surrogate theory is also used to characterize the potential energy surface, allowing for simple but reliable ways to maximize statistical efficiency while retaining controllable accuracy. We demonstrate the method by finding the minimum DMC energy structures of the selected flake-like aromatic molecules, such as benzene, coronene, and ovalene, represented by 2, 6, and 19 structural parameters, respectively. In each case, the energy minimum is found within two parallel line-search iterations. The method is near-optimal for a line-search technique and suitable for a broad range of applications. It is easily generalized to any electronic structure method where forces and stresses are still under active development and implementation, such as diffusion Monte Carlo, auxiliary-field Monte Carlo, and stochastic configuration interaction, as well as deterministic approaches such as the random-phase approximation. Accurate and efficient means of geometry optimization could shed light on a broad class of materials and molecules, showing high sensitivity of induced properties to structural variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Revisiting superconductivity in the extended one-band Hubbard model: Pairing via spin and charge fluctuations

The leading superconducting instabilities of the two-dimensional extended repulsive one-band Hubbard model within spin-fluctuation pairing theory depend sensitively on electron density, band, and interaction parameters. We map out the phase diagrams within a random-phase-approximation spin- and charge-fluctuation approach, and find that while B 1g (d x 2 –y 2 ) and B 2g (d xy ) pairing dominates in the absence of repulsive longer-range Coulomb interactions V NN , the latter induces pairing in other symmetry channels, including, e.g., A 2g (g-wave), nodal A 1g (extended s-wave), or nodal E u (p-wave) spin-triplet superconductivity. At the lowest temperatures, transition boundaries in the phase diagrams between symmetry-distinct spin-singlet orders generate complex time-reversal symmetry broken superpositions. By contrast, we find that boundaries between singlet and triplet regions are characterized by first-order transitions. Finally, motivated by recent photoemission experiments, we have determined the influence of an additional explicitly attractive nearest-neighbor interaction, V NN < 0, on the superconducting gap structure. Furthermore, depending on the electronic filling, such an attraction boosts E u (p-wave) spin-triplet or B 1g (d x 2 –y 2 ) spin-singlet ordering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

SERTA Domain Containing Protein 1 (SERTAD1) Interacts with Classical Swine Fever Virus Structural Glycoprotein E2, Which Is Involved in Virus Virulence in Swine

E2 is the major structural glycoprotein of the classical swine fever virus (CSFV). E2 has been shown to be involved in important virus functions such as replication and virulence in swine. Using the yeast two-hybrid system, we previously identified several host proteins specifically interacting with CSFV E2. Here, we analyze the protein interaction of E2 with SERTA domain containing protein 1 (SERTAD1), a factor involved in the stimulation of the transcriptional activities of different host genes. We have confirmed that the interaction between these two proteins occurs in CSFV-infected swine cells by using a proximity ligation assay and confocal microscopy. Amino acid residues in the CSFV E2 protein that are responsible for mediating the interaction with SERTAD1 were mapped by a yeast two-hybrid approach using a randomly mutated E2 library. Using that information, a recombinant CSFV mutant (E2ΔSERTAD1v) that harbors substitutions in those residues mediating the protein-interaction with SERTAD1 was developed and used to study the role of the E2-SERTAD1 interaction in viral replication and virulence in swine. CSFV E2ΔSERTAD1v, when compared to the parental BICv, showed a clearly decreased ability to replicate in the SK6 swine cell line and a more severe replication defect in primary swine macrophage cultures. Importantly, 80% of animals infected with E2ΔSERTAD1v survived infection, remaining clinically normal during the 21-day observational period. This result would indicate that the ability of CSFV E2 to bind host SERTAD1 protein during infection plays a critical role in virus virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A minimal motif for sequence recognition by mitochondrial transcription factor A (TFAM)

Abstract Mitochondrial transcription factor A (TFAM) plays a critical role in mitochondrial transcription initiation and mitochondrial DNA (mtDNA) packaging. Both functions require DNA binding, but in one case TFAM must recognize a specific promoter sequence, while packaging requires coating of mtDNA by association with non sequence-specific regions. The mechanisms by which TFAM achieves both sequence-specific and non sequence-specific recognition have not yet been determined. Existing crystal structures of TFAM bound to DNA allowed us to identify two guanine-specific interactions that are established between TFAM and the bound DNA. These interactions are observed when TFAM is bound to both specific promoter sequences and non-sequence specific DNA. These interactions are established with two guanine bases separated by 10 random nucleotides (GN10G). Our biochemical results demonstrate that the GN10G consensus is essential for transcriptional initiation and contributes to facilitating TFAM binding to DNA substrates. Furthermore, we report a crystal structure of TFAM in complex with a non sequence-specific sequence containing a GN10G consensus. The structure reveals a unique arrangement in which TFAM bridges two DNA substrates while maintaining the GN10G interactions. We propose that the GN10G consensus is key to facilitate the interaction of TFAM with DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization of quantum chaos by two-point correlation functions

In this work, we propose a characterization of quantum many-body chaos: given a collection of simple operators, the set of all possible pair correlations between these operators can be organized into a matrix with a random-matrix-like spectrum. This approach is particularly useful for locally interacting systems, which do not generically show exponential Lyapunov growth of out-of-time-ordered correlators. We demonstrate the validity of this characterization by numerically studying the Sachdev-Ye-Kitaev model and a one-dimensional spin chain with random magnetic field (XXZ model).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of the Anions on the Interaction Energy between Water and Ionic Liquids

It is essential to understand the interaction energy between water and ionic liquids (ILs) in search of ILs for dehumidification applications. In this paper, the intermolecular interaction energy between water and 1-ethyl-3-methylimidazolium ([EMIM])-based ILs was investigated. The vapor-liquid equilibrium data were first measured for solutions of [EMIM][BF 4 ], [EMIM][N(CN) 2 ], [EMIM][CF 3 SO 3 ], and [EMIM][CH 3 SO 3 ] with water molar fractions of 8–95 % at temperatures of 303–343 K. The IL-IL and water-IL intermolecular interaction energies were determined by using the correlated non-random two-liquid model. The results revealed that fluorine atoms in anions reduce the attraction energy between IL and water, and thus, decrease the water affinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

Simulation of Liquid Rocket Engine Failure Propagation Using Self-Evolving Scenarios

Traditional probabilistic risk assessment approaches often require failure scenarios to be explicitly defined through event sequences that are then quantified as part of the integrated analysis. This approach becomes difficult when failure propagation paths change as a function of the system operation. Additionally, if the propagation paths represent interactions among even a modest number of components, the scenario count becomes combinatorially intractable. This paper presents an alternate approach for quantifying the probability of failure propagation in such a case. Rather than explicitly defining scenario sequences, simple physical models are created for each of the components. In this way, only the physical states and rules of component interactions must be defined, rather than event sequences for each individual scenario. Initiating failures are introduced into the system, either randomly or as defined by relative likelihood, and the failures cascade through the system via the interaction rules. This process is repeated using Monte Carlo methods and, as a result, the most probable scenarios “self-evolve” in terms of both sequence path and frequency. This approach was applied to failures occurring in the engine compartment of a space launch vehicle with four liquid rocket engines and four high-pressure helium tanks. Each engine was modeled with key components, such as turbomachinery, combustion chamber, propellant lines, and additional support systems. Three test cases were conducted with different high-energy engine failures. End results of interest included an additional engine-out failure and tank burst, which represent the loss-of-mission (LOM) and loss-of-crew (LOC) failure environments, respectively. Observations show that almost every scenario outcome is unique and that many scenarios involve complex chain reactions that are difficult to predict. This validates the usefulness of the modeling approach in assessing the overall risks to the crew during a launch vehicle abort.

Rocket Engine↗
DOE OSTI2021

A crystal plasticity model with an atomistically informed description of grain boundary sliding for improved predictions of deformation fields

Crystal plasticity (CP) is a powerful meso-scale technique for deformation modeling in polycrystalline materials. Crystal plasticity models typically do not include an explicit description of grain boundary (GB) sliding, which could lead to inaccurate predictions of strain distributions, especially in the vicinity of GBs. In the present study, a CP model is developed that includes GB sliding as an additional deformation mechanism and models the interaction between slip and GB sliding. Atomistic simulations are used to formulate the constitutive model for GB sliding and its interaction with incident slip. The deformation fields and structure of the GBs are obtained directly from experimental characterization and are faithfully reproduced as bicrystal systems for molecular dynamics simulations. The GBs are modeled as random-type (non-coincidence, asymmetrical) boundaries as observed from experimental data. The underlying atomistic-scale mechanism for pure sliding of random GBs was found to be analogous to fluid-flow. The interaction between incident slip and a sliding GB caused local increases in stress concentration, which further led to a momentary increase in the local sliding rate. The displacement profiles at the sliding GBs computed from the CP model with sliding accommodation are 38% more accurate than the baseline CP model as quantified by the mean squared error between the simulations and experiment. Here these results help improve the sophistication and accuracy of deformation modeling by including physics-based descriptions for GB sliding and its interaction with slip, eventually leading to more reliable predictions of micromechanical quantities.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Entanglement-fidelity limits of photonically networked atomic qubits from recoil and timing

The remote entanglement of two atomic quantum memories through photonic interactions is accompanied by atomic momentum recoil. When the interactions occur at different times, such as from the random emission over the lifetime of the atomic excited state, the difference in recoil timing can expose “which-path” information and ultimately lead to decoherence. Time-bin encoded photonic qubits can be particularly sensitive to asynchronous recoil timing. In this paper we study the limits of entanglement fidelity in atomic systems due to recoil and other timing imbalances and show how these effects can be suppressed or even eliminated through proper experimental design.

Quantum communication↗
DOE OSTI2022

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly

Switchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO 3 – , Ca 2+ , PO 4 3– , and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

plant biomass↗
DOE OSTI2020

Uncertainty Quantification in Scientific ML

The intricate interactions between data sampling, model selection and the inherent randomness in complex systems strongly emphasize the need for a rigorous characterization of ML algorithms. In conventional statistics, uncertainty quantification (UQ) provides this characterization by measuring how accurately a model reflects the physical reality and by studying the impact of different error sources on the prediction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Small-scale transition in a plane mixing layer

An experimental study was conducted to investigate the generation process of random small-scale turbulence in an originally laminar mixing layer. The evolutions of the two types of deterministic structures, the spanwise and streamwise vortices, were first clarified in order to determine their roles in the transition process. A scaling rule for the streamwise distance from the trailing edge of the splitter plate to the vortex merging position was found for various velocity ratios. After this stremwise lengthscale was determined, it became clear that the spanwise wavelength of the streamwise vortices doubled after the merging of the spanwise structures which nominally doubled streamwise wavelengths. The most interesting finding was that the random small-scale eddies were produced by the interactions between the merging spanwise structures and the streamwise vortices.

Huang, Lein-Saing↗