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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Intrinsic two-dimensional features as textons

We suggest that intrinsic two-dimensional (i2D) features, computationally defined as the outputs of nonlinear operators that model the activity of end-stopped neurons, play a role in preattentive texture discrimination. We first show that for discriminable textures with identical power spectra the predictions of traditional models depend on the type of nonlinearity and fail for energy measures. We then argue that the concept of intrinsic dimensionality, and the existence of end-stopped neurons, can help us to understand the role of the nonlinearities. Furthermore, we show examples in which models without strong i2D selectivity fail to predict the correct ranking order of perceptual segregation. Our arguments regarding the importance of i2D features resemble the arguments of Julesz and co-workers regarding textons such as terminators and crossings. However, we provide a computational framework that identifies textons with the outputs of nonlinear operators that are selective to i2D features.

Discrimination (Psychology)/physiology↗
NASA NTRS2009

Video-Game-Like Engine for Depicting Spacecraft Trajectories

GoView is a video-game-like software engine, written in the C and C++ computing languages, that enables real-time, three-dimensional (3D)-appearing visual representation of spacecraft and trajectories (1) from any perspective; (2) at any spatial scale from spacecraft to Solar-system dimensions; (3) in user-selectable time scales; (4) in the past, present, and/or future; (5) with varying speeds; and (6) forward or backward in time. GoView constructs an interactive 3D world by use of spacecraft-mission data from pre-existing engineering software tools. GoView can also be used to produce distributable application programs for depicting NASA orbital missions on personal computers running the Windows XP, Mac OsX, and Linux operating systems. GoView enables seamless rendering of Cartesian coordinate spaces with programmable graphics hardware, whereas prior programs for depicting spacecraft trajectories variously require non-Cartesian coordinates and/or are not compatible with programmable hardware. GoView incorporates an algorithm for nonlinear interpolation between arbitrary reference frames, whereas the prior programs are restricted to special classes of inertial and non-inertial reference frames. Finally, whereas the prior programs present complex user interfaces requiring hours of training, the GoView interface provides guidance, enabling use without any training.

Upchurch, Paul R.↗
NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗
DOE OSTI2019

Effect of wavefunction delocalization on shift current generation

We derive upper bounds on the magnitude of shift photocurrent generation of materials in two limiting cases: the flat-band limit of almost-isolated systems such as molecular crystals, and the wide-band limit of one-dimensional or quasi-one-dimensional materials such as ferroelectric polymers or other materials with chain-like motifs. These bounds relate the magnitudes of the shift current bulk photovoltaic effect to materials parameters. In both cases, we find that ratio of electron hopping amplitudes to the band gap plays a vital role in maximizing the amount of nonlinear response. Furthermore, by using the Wannier function formalism, we quantify the effect of long-range hopping amplitudes, showing how delocalization of electronic states gives rise to larger photocurrents. Lastly, these results inform the design and selection of new materials for large shift current generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1985

Some properties of n-dimensional triangulations

A number of mathematical results relevant to the problem of constructing a triangulation, i.e., a simplicial tessellation, of the convex hull of an arbitrary finite set of points in n-space are described. The principal results achieved are: (1) a set of n+2 points in n-space may be triangulated in at most 2 different ways; (2) the sphere test defined in this report selects a preferred one of these two triangulations; (3) a set of parameters is defined that permits the characterization and enumeration of all sets of n+2 points in n-space that are significantly different from the point of view of their possible triangulation; (4) the local sphere test induces a global sphere test property for a triangulation; and (5) a triangulation satisfying the global sphere property is dual to the n-dimensional Dirichlet tesselation, i.e., it is a Delaunay triangulation.

Lawson, C. L.↗
DOE OSTI2018

Three dimensional optimization for subsonic axial turbines operating at high unsteady inlet Mach number

In this paper, a three dimensional optimization strategy is presented to improve the performance of a subsonic axial turbine exposed to high Mach number unsteady inflows encountered in pressure gain combustors. The optimization aims at altering the stator hub and shroud end wells. A multi-objective differential evolution optimizer was used to enhance specific work and efficiency. The optimization routine consisted of a multi-step approach where in a first step an optimization was carried out where the turbine was subjected to a steady high Mach inflow. The turbine stage was parametrized via an in-house turbine design tool based on Bezier curves. Seven design parameters were selected to contour the stator end walls and rotor hub end wall. The parametrized turbine stage was meshed and the steady Reynolds-Averaged Navier-Stokes equations were solved via the commercial solver CFD++ and calculation time of each stage was around 10 hours. Results of the steady optimization identified three major design parameters of stator end walls, which were taken as inputs for the next phase unsteady optimization. For the unsteady simulations, a large inlet fluctuation was imposed and the turbine was modeled with the mixing plane approach. Total calculation time of each individual was 48 hours. An efficiency improvement of 10% from the steady optimization and 13% from the unsteady optimization was found compared to the baseline case. Finally, full unsteady simulations with two stator and three rotor passages were performed on selected steady and unsteady optimized configurations.

03 NATURAL GAS↗
DOE OSTI2015

MAGNETOHYDRODYNAMIC SHOCKS IN AND ABOVE POST-FLARE LOOPS: TWO-DIMENSIONAL SIMULATION AND A SIMPLIFIED MODEL

Solar flares are an explosive phenomenon where super-sonic flows and shocks are expected in and above the post-flare loops. To understand the dynamics of post-flare loops, a two-dimensional magnetohydrodynamic (2D MHD) simulation of a solar flare has been carried out. We found new shock structures in and above the post-flare loops, which were not resolved in the previous work by Yokoyama and Shibata. To study the dynamics of flows along the reconnected magnetic field, the kinematics and energetics of the plasma are investigated along selected field lines. It is found that shocks are crucial to determine the thermal and flow structures in the post-flare loops. On the basis of the 2D MHD simulation, we developed a new post-flare loop model, which we defined as the pseudo-2D MHD model. The model is based on the one-dimensional (1D) MHD equations, where all variables depend on one space dimension, and all the three components of the magnetic and velocity fields are considered. Our pseudo-2D model includes many features of the multi-dimensional MHD processes related to magnetic reconnection (particularly MHD shocks), which the previous 1D hydrodynamic models are not able to include. We compared the shock formation and energetics of a specific field line in the 2D calculation with those in our pseudo-2D MHD model, and found that they give similar results. This model will allow us to study the evolution of the post-flare loops in a wide parameter space without expensive computational cost or neglecting important physics associated with magnetic reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Electron-hole pair effects in methane dissociative chemisorption on Ni(111)

The dissociative chemisorption of methane on metal surfaces has attracted much attention in recent years as a prototype of gas-surface reactions in understanding the mode specific and bond selective chemistry. In this work, we systematically investigate the influence of electron-hole pair excitations on the dissociative chemisorption of CH{sub 4}/CH{sub 3}D/CHD{sub 3} on Ni(111). The energy dissipation induced by surface electron-hole pair excitations is modeled as a friction force introduced in the generalized Langevin equation, in which the independent atomic friction coefficients are determined within the local-density friction approximation. Quasi-classical trajectory calculations for CH{sub 4}/CH{sub 3}D/CHD{sub 3} have been carried out on a recently developed twelve-dimensional potential energy surface. Comparing the dissociation probabilities obtained with and without friction, our results clearly indicate that the electron-hole pair effects are generally small, both on absolute reactivity of each vibrational state and on the mode specificity and bond selectivity. Given similar observations in both water and methane dissociation processes, we conclude that electron-hole pair excitations would not play an important role as long as the reaction is direct and the interaction time between the molecule and metal electrons is relatively short.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Structurally Deformed MoS 2 for Electrochemically Stable, Thermally Resistant, and Highly Efficient Hydrogen Evolution Reaction

Abstract The emerging molybdenum disulfide (MoS 2 ) offers intriguing possibilities for realizing a transformative new catalyst for driving the hydrogen evolution reaction (HER). However, the trade‐off between catalytic activity and long‐term stability represents a formidable challenge and has not been extensively addressed. This study reports that metastable and temperature‐sensitive chemically exfoliated MoS 2 (ce‐MoS 2 ) can be made into electrochemically stable (5000 cycles), and thermally robust (300 °C) while maintaining synthetic scalability and excellent catalytic activity through physical‐transformation into 3D structurally deformed nanostructures. The dimensional transition enabled by a high throughput electrohydrodynamic process provides highly accessible, and electrochemically active surface area and facilitates efficient transport across various interfaces. Meanwhile, the hierarchically strained morphology is found to improve electronic coupling between active sites and current collecting substrates without the need for selective engineering the electronically heterogeneous interfaces. Specifically, the synergistic combination of high strain load stemmed from capillarity‐induced‐self‐crumpling and sulfur (S) vacancies intrinsic to chemical exfoliation enables simultaneous modulation of active site density and intrinsic HER activity regardless of continuous operation or elevated temperature. These results provide new insights into how catalytic activity, electrochemical‐, and thermal stability can be concurrently enhanced through the physical transformation that is reminiscent of nature, in which properties of biological materials emerge from evolved dimensional transitions.

Chen, Yen‐Chang↗
DOE OSTI2013

Theoretical formulation of finite-dimensional discrete phase spaces: II. On the uncertainty principle for Schwinger unitary operators

We introduce a self-consistent theoretical framework associated with the Schwinger unitary operators whose basic mathematical rules embrace a new uncertainty principle that generalizes and strengthens the Massar–Spindel inequality. Among other remarkable virtues, this quantum-algebraic approach exhibits a sound connection with the Wiener–Khinchin theorem for signal processing, which permits us to determine an effective tighter bound that not only imposes a new subtle set of restrictions upon the selective process of signals and wavelet bases, but also represents an important complement for property testing of unitary operators. Moreover, we establish a hierarchy of tighter bounds, which interpolates between the tightest bound and the Massar–Spindel inequality, as well as its respective link with the discrete Weyl function and tomographic reconstructions of finite quantum states. We also show how the Harper Hamiltonian and discrete Fourier operators can be combined to construct finite ground states which yield the tightest bound of a given finite-dimensional state vector space. Such results touch on some fundamental questions inherent to quantum mechanics and their implications in quantum information theory. -- Highlights: •Conception of a quantum-algebraic framework embracing a new uncertainty principle for unitary operators. •Determination of new restrictions upon the selective process of signals and wavelet bases. •Demonstration of looser bounds interpolating between the tightest bound and the Massar–Spindel inequality. •Construction of finite ground states properly describing the tightest bound. •Establishment of an important connection with the discrete Weyl function.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Physics-based statistical learning approach to mesoscopic model selection

In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. Here, we apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD “training” data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD “test” data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Three-dimensional inelastic analysis for hot section components, BEST 3D code

The goal is the development of an alternative stress analysis tool, distinct from the finite element method, applicable to the engineering analysis of gas turbine engine structures. The boundary element method was selected for this development effort on the basis of its already demonstrated applicability to a variety of geometries and problem types characteristic of gas turbine engine components. Major features of the BEST3D computer program are described, and some of the significant developments carried out as part of the Inelastic Methods Contract are outlined.

Wilson, Raymond B.↗
NASA NTRS1988

Sensitivity of mixing layers to three-dimensional forcing

It is well known that turbulent mixing layers are dominated by large scale, fairly coherent structures, and that these structures are related to the stability characteristics of the flow. These facts have led researchers to attempt controlling such flows by selectively forcing certain unstable modes, which can in addition have the effect of suppressing other modes. Much of the work on controlling the mixing layer has relied on forcing 2-D instabilities. The results of forcing 3-D instabilities are addressed. The objectives of the work are twofold: to understand how a mixing layer responds to 3-D perturbations, and to test the validity of an amplitude expansion in predicting the mixing layer development. The amplitude expansion could be very useful in understanding and predicting the 3-D response of the flow to a variety of initial conditions.

Riley, J. J.↗
NASA NTRS2018

Digital Image Correlation Data Processing and Analysis Techniques to Enhance Test Data Assessment and Improve Structural Simulations

The NASA Shell Buckling Knockdown Factor Project (SBKF) was established in 2007 by the NASA Engineering and Safety Center (NESC) with the primary goal to develop new analysis-based buckling design factors (a.k.a. knockdown factors) and high-fidelity buckling simulations for selected launch-vehicle-like cylindrical shell structures. A series of tests are being conducted on large-scale metallic and composite cylindrical shells in order to provide validation data for these new factors and simulations. However, the validation of these new factors and simulations is quite demanding and requires test data that is commensurate with their fidelity. Traditional instrumentation, such as linear variable displacement transducers (LVDTs) and electrical-resistance strain gages serve a critical role in providing accurate displacement and strain measurements in these tests, but only allow for data to be recorded at a select number of point locations and are not sufficient to provide all the necessary validation data. Advanced measurement technologies can be used effectively to complement traditional instrumentation and gather additional data required to validate these structural simulations. In particular, three-dimensional digital image correlation (DIC) was implemented during SBKF cylinder testing to characterize the full-field displacement and strain behavior. Commercially available VIC-3DTM software and user-written data processing scripts were used to generate valuable data and insight into the complex buckling response of the cylinders that otherwise would be impossible to gather using traditional instrumentation. In addition, the measured data from DIC was used to verify measured test data obtained from other instrumentation, enhance test and analysis correlation, and help identify the root cause of anomalous test results that may have gone unexplained if only traditional instrumentation was used. Selected test results that demonstrate the use of DIC on the SBKF cylinders are presented and a portion of the data processing methods are described.

Gardner, Nathaniel W.↗
DOE OSTI2016

Ordered Mesoporous Metal Carbides with Enhanced Anisole Hydrodeoxygenation Selectivity

Mesoporous metal carbides are of particular interest as catalysts for a variety of reactions because of their high surface areas, porous networks, nanosized walls, and unique electronic structures. In this work, two ordered mesoporous metal carbides, Mo 2 C and W 2 C, were synthesized using a nanocasting approach coupled with a simultaneous decomposition/carburization process under a continuous methane flow. The as-synthesized mesoporous Mo 2 C and W 2 C have three dimensionally ordered porous structures, large surface areas (70–90 m 2 g –1 ), and crystalline walls. In vapor-phase anisole hydrodeoxygenation (HDO) reactions, they exhibited turnover frequencies of approximately 9 and 2 × 10 –4 mol molCO –1 s –1 , respectively, at relatively low reaction temperatures (423–443 K) and ambient hydrogen pressures. Notably, the ordered mesoporous W 2 C catalyst showed a greater than 96% benzene selectivity in anisole HDO, the highest benzene selectivity reported to date.

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

Anion Binding by Macrocyclic Receptors: Computational Landscape of 1:1 and 2:1 Stoichiometries

Macrocyclic receptors play a crucial role in supramolecular chemistry, enabling the selective binding of guest molecules through non-covalent interactions. This study investigates the anion binding properties of three shape-persistent macrocycles, triazolophane, cyanostar, and tricarb, each featuring preorganized cavities with polarized CH hydrogen bond donors. In the 1:1 binding stoichiometries, the macrocycles preferentially bind anions that fit inside their two-dimensional cavities, with this preference being more pronounced in solution. Specifically, the triazolophane favors smaller anions like chloride and bromide, while the larger cavities offered by cyanostar and tricarb macrocycles preferentially bind the larger iodide. For large, polyatomic anions (SCN − , BF$^{−}_{4}$, ClO$^{−}_{4}$, and PF$^{−}_{6}$), the macrocycles self-assemble to form stable 2:1 sandwich complexes, exhibiting stronger binding. This shift in selectivity highlights the versatility of the macrocycles, making them promising candidates for anion sensing and regulation with various complexation stoichiometries.

Che, Minwei [Indiana University, Bloomington, IN (↗
DOE OSTI2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A natural strategy is to use the Fock basis to encode information in qudits. One can perform quantum operations on the cavity mode qudit by coupling the system to a non-linear ancillary transmon qubit. However, the performance of the cavity-transmon device is limited by the noisy transmons. It is, therefore, important to develop practical benchmarking tools for these qudit systems in an algorithm-agnostic manner. We gauge the performance of these qudit platforms using sampling tests such as the heavy output generation test as well as the linear cross-entropy benchmark, by way of simulations of such a system subject to realistic dominant noise channels. We use selective number-dependent arbitrary phase and unconditional displacement gates as our universal gateset. Our results show that contemporary transmons comfortably enable controlling a few tens of Fock levels of a cavity mode. This framework allows benchmarking even higher dimensional qudits as those become accessible with improved transmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1996

Predicting the stability of a compressible periodic parallel jet flow

It is known that mixing enhancement in compressible free shear layer flows with high convective Mach numbers is difficult. One design strategy to get around this is to use multiple nozzles. Extrapolating this design concept in a one dimensional manner, one arrives at an array of parallel rectangular nozzles where the smaller dimension is omega and the longer dimension, b, is taken to be infinite. In this paper, the feasibility of predicting the stability of this type of compressible periodic parallel jet flow is discussed. The problem is treated using Floquet-Bloch theory. Numerical solutions to this eigenvalue problem are presented. For the case presented, the interjet spacing, s, was selected so that s/omega =2.23. Typical plots of the eigenvalue and stability curves are presented. Results obtained for a range of convective Mach numbers from 3 to 5 show growth rates omega(sub i)=kc(sub i)/2 range from 0.25 to 0.29. These results indicate that coherent two-dimensional structures can occur without difficulty in multiple parallel periodic jet nozzles and that shear layer mixing should occur with this type of nozzle design.

Miles, Jeffrey H.↗