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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Strength Differential Measured in Inconel 718: Effects of Hydrostatic Pressure Studied

Aeropropulsion components, such as disks, blades, and shafts, are commonly subjected to multiaxial stress states at elevated temperatures. Experimental results from loadings as complex as those experienced in service are needed to help guide the development of accurate viscoplastic, multiaxial deformation models that can be used to improve the design of these components. During a recent study on multiaxial deformation (ref. 1) on a common aerospace material, Inconel 718, it was shown that the material in the aged state exhibits a strength differential effect (SDE), whereby the uniaxial compressive yield and subsequent flow behavior are significantly higher than those in uniaxial tension. Thus, this material cannot be described by a standard von Mises yield formulation. There have been other formulations postulated (ref. 2) that involve other combinations of the stress invariants, including the effect of hydrostatic stress. The question remained as to which invariants are necessary in the flow model. To capture the physical mechanisms occurring during deformation and reflect them in the plasticity formulation, researchers examined the flow of Inconel 718 under various amounts of hydrostatic stress to determine whether or not hydrostatic stress is needed in the formulation. Under NASA Grant NCC3-464, monitored by the NASA Glenn Research Center, a series of tensile tests were conducted at Case Western Reserve University on aged (precipitation hardened) Inconel 718 at 650 C and with superimposed hydrostatic pressure. Dogbone shaped tensile specimens (3-mm-diameter gauge by 16-mm gauge length) and cylindrical compression specimens (3-mm-diameter gauge by 6-mm gauge length) were strain gauged and loaded in a high-pressure testing apparatus. Hydrostatic pressures were obtained with argon and ranged from 210 to 630 MPa. The aged Inconel 718 showed a pronounced difference in the tension and compression yield strength (i.e., an SDE), as previously observed. Also, there were no significant effects of hydrostatic pressure on either the tensile and compressive yield strength (see the graph) or on the magnitude of the SDE. This behavior is not consistent with the pressure-dependent theory of the SDE, which postulates that the SDE is associated with pressure-dependent and/or internal friction dependent deformation associated with non-Schmid effects at the crystal level (refs. 3 and 4). Flow in Inconel 718 appears to be independent of hydrostatic pressure, suggesting that this invariant may be removed from the phenomenological constitutive model. As part of an ongoing effort to develop advanced constitutive models, Glenn s Life Prediction Branch coordinated this work with that of research on the multiaxial deformation behavior of Inconel 718 being conducted at Pennsylvania State University under NASA Grant NCC597.

Lewandowski, John J.↗
NASA NTRS2022

Multi-Agent Control Approach to the Stability of Linear Deployable Systems

Collisions and undesired dynamic responses may occur during the expansion phase of deployable elements on a spacecraft. This problem is more pronounced in large and complex deployable elements where characterization of transient dynamics using testing and simulation can be challenging. This paper introduces a multi-agent control theory approach to address the problem of collisions and transient behavior in deployable lattice systems. We introduce the graph theoretic and relative error vector-based state-space structures to represent the geometry of a lattice-based deploy system. We show that under the assumption of almost-strict dissipativity, the closed-loop feedback gains of the relative error dynamics are the spring and damper constants in the structure. Moreover, we introduce the control perspective of shaping transient dynamics using eigenstructure assignment and balanced coordinate transformation.

Pablos, Juan L. de↗
DOE OSTI2026

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying solely on machine learning interatomic potential (MLIP) models. To this end, we first curate a large-scale molecular relaxation dataset comprising 3.5 million molecules and 300 million snapshots. Then MLIP pre-trained models are trained with supervised learning to predict energy and forces given 3D molecular structures. Once trained, we show that the pre-trained models can be used in different ways to obtain geometries either explicitly or implicitly. First, it can be used to obtain approximate low-energy 3D geometries via geometry optimization. While these geometries do not consistently reach DFT-level chemical accuracy or convergence, they can still improve downstream performance compared to non-relaxed structures. To mitigate potential biases and enhance downstream predictions, we introduce geometry fine-tuning based on the relaxed 3D geometries. Second, the pre-trained models can be directly fine-tuned for property prediction when ground truth 3D geometries are available. Our results demonstrate that MLIP pre-trained models trained on relaxation data can learn transferable molecular representations to improve downstream molecular property prediction and can provide practically valuable but approximate molecular geometries that benefit property predictions. Our code is publicly available at: https://github.com/divelab/AIRS/.

Fu, Cong [Texas A & M Univ., College Station, TX (↗
NASA NTRS1972

On the tidal effects in the motion of artificial satellites.

The general perturbations in the elliptic and vectorial elements of a satellite as caused by the tidal deformations of the non-spherical Earth are developed into trigonometric series in the standard ecliptical arguments of Hill-Brown lunar theory and in the equatorial elements of the satellite. The integration of the differential equations for variation of elements of the satellite in this theory is easy because all arguments are linear or nearly linear in time. The trigonometrical expansion permits a judgment about the relative significance of the amplitudes and periods of different tidal 'waves' over a long period of time. Graphs are presented of the tidal perturbations in the elliptic elements of the BE-C satellite which illustrate long term periodic behavior. The tidal effects are clearly noticeable in the observations and their comparison with the theory permits improvement of the 'global' Love numbers for the Earth.

Musen, P.↗
DOE OSTI2025

Cartesian equivariant representations for learning and understanding molecular orbitals

Qualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces.

chemical reactions↗
NASA NTRS1984

Aeroacoustics of turbulent shear flows

Recent analytical, numerical-simulation and experimental studies of sound generation by high-Reynolds-number turbulent shear flows are reviewed, with a focus on the application of linear rapid-distortion theory to the calculation of the unsteady flow field producing the sound. This approach is considered the most important alternative to acoustic-analogy methods. Topics surveyed include the linear theory of solid-surface interactions, the jet-noise problem, extensions to more complex turbulent flows, and supersonic flows. Graphs comparing theoretical and experimental results are shown.

Goldstein, M. E.↗
NASA NTRS1983

Observational Basis for Velocity Fields in Stellar Atmospheres, Workshop, Trieste, Italy, August-September 1982, Proceedings

Solar and stellar winds and mass-loss phenomena are discussed in reviews of recent observations and current theory. Topics examined include mass loss from the sun, the O-type stars, Wolf-Rayet stars, the Parker theory, B stars, T Tauri stars, Balmer line emission from Be stars, novae, symbiotic stars, planetary nebulae, and dwarf novae. Graphs, tables, diagrams, sample spectra, and extensive discussion on each contribution are provided.

Stalio, R.↗
NASA NTRS2021

A Mathematical Analysis of an Example Delay Tolerant Network using the Theory of Sheaves

NASA’s High-Data Rate Architecture (HiDRA) project is working towards a general yet practical toolkit and knowledge base to help usher in the era of new technologies for space systems communications, such as optical links. The High-Rate Delay Tolerant Networking (HDTN) implementation falls under the umbrellas of both the toolkit and the knowledge base, as its advancements illuminate more general areas of Delay Tolerant Networking (DTN) that need growth. The goal of this paper is to explore the usage of particular mathematical machineries, namely temporal flow networks and sheaves, to identify fundamental, underlying structures in DTN for space systems. Satellites, space assets, ground stations, etc. give rise to a disconnected network, and it is the goal of DTN to glue disparate links together into a cohesive system, that is, a network. Depending on a given link, the latencies might be beyond that which the Transmission Control Protocol (TCP) can handle, and contact times might have one-way light times in excess of minute (sometimes significantly longer). Some links might be periodic (say, due to orbital mechanics) or they might not be. This diversity has made it difficult to probe the underlying structure. An immediate consequence is that DTNs in practice today are controlled by globally distributed contact plans (schedules), which are the input to the contact graph routing (CGR) algorithm. While this is effective for smaller networks, it will be very difficult to scale for future networks. Deeper and more rigorous theory is needed to bring DTN to the next evolutionary step. To this end, this paper introduces and suggests a mathematical framework for DTN, and applies it to a space network that is simulated using an orbital analysis toolkit. The tag-line for the structure known as sheaves is that they are the mathematically precise way of gluing local data together into unique, global data. If we consider routing, we see that networking is a “sheafy” science. We then discuss a simplified sheaf model, known as the cellular sheaf. The sheaf-theoretic analysis is presented and discussed, as it is hoped that this and related papers will help form the primordial ooze of DTN theory. Finally there is a section of future work suggesting follow-on research.

Delay Tolerant Networking↗
NASA NTRS1989

Nuclear cross sections for estimating secondary radiations produced in spacecraft

The physical theory underlying calculations of nuclear absorption and fragmentation cross sections and EM dissociation cross sections is reviewed; typical results are presented in graphs; and the adequacy of the experimental data bases for each type of cross section are discussed. The emphasis is on computations applicable to the estimation of secondary radiation in shielded spacecraft.

Townsend, L. W.↗
NASA NTRS1990

On well-partial-order theory and its application to combinatorial problems of VLSI design

We nonconstructively prove the existence of decision algorithms with low-degree polynomial running times for a number of well-studied graph layout, placement, and routing problems. Some were not previously known to be in p at all; others were only known to be in p by way of brute force or dynamic programming formulations with unboundedly high-degree polynomial running times. Our methods include the application of the recent Robertson-Seymour theorems on the well-partial-ordering of graphs under both the minor and immersion orders. We also briefly address the complexity of search versions of these problems.

Fellows, M.↗
DOE OSTI2026

Energy-Screened Many-Body Expansion for Protein–Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven–Body Interactions

Fragment-based quantum chemistry is a powerful strategy for calculating protein−ligand interaction energies using quantum chemistry methods. Rigorous convergence often requires hundreds of atoms in the protein binding-site model, especially if that model is constructed using distance-based criteria to select amino acid residues, while three- and four-body calculations exhibit instability related to combinatorial proliferation in the number of subsystem calculations. Here, we report an energy-based screening protocol for the many-body expansion applied to protein−ligand interactions, implemented in the open-source FRAGME∩T code. Using a combination of aggressive screening based on semiempirical quantum chemistry, with an improved graph-theoretical algorithm to eliminate unimportant subsystems, we are able to perform n-body calculations up to n = 7 using density functional theory in triple-ζ basis sets. Distance cutoffs further reduce the cost without compromising accuracy. Rapid and stable convergence of the many-body expansion is obtained by n = 4, for a pair of metalloenzymes in which a divalent ion coordinates directly to the ligand. As compared to previous results that relied solely on distance cutoffs, oscillations in the n-body corrections are reduced or eliminated, although residual errors remain in one case. This work demonstrates that benchmark-quality protein−ligand interaction energies can be systematically converged using a method with excellent parallel efficiency and scalability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Magnetic reconnection in space and laboratory plasmas; Proceedings of the Chapman Conference on Magnetic Reconnection, Los Alamos, NM, October 3-7, 1983

The physics of magnetic reconnection is discussed in reviews and reports of theoretical and experimental investigations. Topics examined include the theory of magnetic reconnection, reconnection in astronomical objects, reconnection in the earth magnetosphere and magnetotail, computer modeling, and laboratory plasmas. Diagrams, spectra, drawings, graphs, and photographs are provided.

Hones, E. W., Jr.↗
NASA NTRS2021

Identifying Molecules as Biosignatures with Assembly Theory and Mass Spectrometry

The search for evidence of life elsewhere in the universe is hard because it is not obvious what signatures are unique to life. Here we postulate that complex molecules found in high abundance are universal biosignatures as they cannot form by chance. To explore this, we developed the first intrinsic measure of molecular complexity that can be experimentally determined, and this is based upon a new approach called assembly theory which gives the molecular assembly number (MA) of a given molecule. MA allows us to compare the intrinsic complexity of molecules using the minimum number of steps required to construct the molecular graph starting from basic objects, and a probabilistic model shows how the probability of any given molecule forming randomly drops dramatically as its MA increases. To map chemical space, we calculated the MA of ca. 2.5 million compounds, and collected data which showed the complexity of a molecule can be experimentally determined by using three independent techniques including infra-red spectroscopy, nuclear magnetic resonance, and by fragmentation in a mass spectrometer, and this data has an excellent corelation with the values predicted from our assembly theory. We then set out to see if this approach could allow us to identify molecular biosignatures with a set of diverse samples from around the world, outer space, and the laboratory including prebiotic soups. The results show that there is a non-living to living threshold in MA complexity and the higher the MA for a given molecule, the more likely that it had to be produced by a biological process. This work demonstrates it is possible to use this approach to build a life detection instrument that could be deployed on missions to extra-terrestrial locations to detect biosignatures, map the extent of life on Earth, and be used as a molecular complexity scale to quantify the constraints needed to direct prebiotically plausible processes in the laboratory. Such an approach is vital if we are going to find new life elsewhere in the universe or create de-novo life in the lab.

Stuart M Marshall↗
DOE OSTI2025

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Shock development in sound transmitted through a nearly choked flow

A nonlinear quasi-one dimensional theory of sound transmitted through a converging-diverging duct section is extended to the case where the acoustical source is located well downstream of the throat, at a point where the flow Mach number is low. The development and subsequent effects of shocks in the acoustic quantities are of primary consideration. The analysis uses a method of matched asymptotic expansions, yielding a set of inner equations of motion and shock conditions valid in the near-sonic throat region. The analysis leads to a generalization of the 'equal area' relation of weak shock theory. The manner in which nonlinear effects increase with source strength, frequency, and throat Mach number is illustrated by the numerical results and corresponding graphs. The shock waves are shown to cause significant dissipation in acoustic power.

Myers, M. K.↗
NASA NTRS1990

The inviscid stability of supersonic flow past a sharp cone

The effects of lateral curvature on the development of supersonic laminar inviscid boundary-layer flow on a sharp cone with adiabatic wall conditions are investigated analytically, with a focus on the linear temporal inviscid stability properties. The derivation of the governing equations and of a 'triply generalized' inflexion condition is outlined, and numerical results for freestream Mach number 3.8 are presented in extensive graphs and characterized in detail. A third instability mode related to the viscous mode observed by Duck and Hall (1990) using triple-deck theory is detected and shown to be more unstable and to have larger growth rates than the second mode in some cases. It is found that the 'sonic' neutral mode is affected by the lateral curvature and becomes a supersonic neutral mode.

Duck, Peter W.↗
NASA NTRS1994

From conditional oughts to qualitative decision theory

The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., 'You ought to do A, if C') that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound basis for qualitative decision theory, thus providing a framework for qualitative planning under uncertainty. In particular, we show that adding causal relationships (in the form of a single graph) as part of an epistemic state is sufficient to facilitate the analysis of action sequences, their consequences, their interaction with observations, their expected utilities, and the synthesis of plans and strategies under uncertainty.

Pearl, Judea↗