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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

The einstein equivalence principle, intrinsic spin and the invariance of constitutive equations in continuum mechanics

The invariance of constitutive equations in continuum mechanics is examined from a basic theoretical standpoint. It is demonstrated the constitutive equations which are not form invariant under arbitrary translational accelerations of the reference frame are in violation of the Einstein equivalane principle. Furthermore, by making use of an analysis based on statistical mechanics, it is argued that any frame-dependent terms in constitutive equations must arise from the intrinsic spin tensor and are negligible provided that the ratio of microscopic to macroscopic time scales is extremely small. The consistency of these results with existing constitutive theories is discussed in detail along with possible avenues of future research.

Speziale, Charles G.↗
NASA NTRS1988

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

Manohar, M.↗
NASA NTRS1990

Equilibrium Statistical Thermodynamics of a Many-Particle System Coupled to an External Scalar Field

The equilibrium thermodynamics of a many-particle assembly in the presence of an external scalar field is examined. Two types of scalar coupling are considered: an external field coupled to the particle density and an external scalar field coupled to the energy density. It is shown that the broken translational and rotational invariance of the system due to the external field is reflected in the macroscopic physics by loss of the usual extensivity property of the system and by means of anisotropy in the response of the system to changes in the system lengths or to the system shape. In addition, the assumptions used in local equilibrium analyses are shown to be incorrect in principle. Nonlocal effects due to the external field must be included in the determination of the equation of state. Simple model calculations for a system in an external gravitational field and an externally imposed temperature field are presented as illustrations.

Salvino, R. E.↗
NASA NTRS1994

Higher-Order Neural Networks Applied to 2D and 3D Object Recognition

A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.

Spirkovska, Lilly↗
DOE OSTI2023

Permutationally Invariant Networks for Enhanced Sampling (PINES): Discovery of Multimolecular and Solvent-Inclusive Collective Variables

The typically rugged nature of molecular free energy landscapes can frustrate efficient sampling of the thermodynamically relevant phase space due to the presence of high free energy barriers. Enhanced sampling techniques can improve phase space exploration by accelerating sampling along particular collective variables (CVs). A number of techniques exist for data-driven discovery of CVs parameterizing the important large scale motions of the system. A challenge to CV discovery is learning CVs invariant to symmetries of the molecular system, frequently rigid translation, rigid rotation, and permutational relabeling of identical particles. Of these, permutational invariance has proved a persistent challenge in frustrating the data-driven discovery of multi-molecular CVs in systems of self-assembling particles and solvent-inclusive CVs for solvated systems. In this work, we integrate Permutation Invariant Vector (PIV) featurizations with autoencoding neural networks to learn nonlinear CVs invariant to translation, rotation, and permutation, and perform interleaved rounds of CV discovery and enhanced sampling to iteratively expand sampling of configurational phase space and obtain converged CVs and free energy landscapes. Here, we demonstrate the Permutationally Invariant Network for Enhanced Sampling (PINES) approach in applications to the self-assembly of a 13-atom Argon cluster, association/dissociation of a NaCl ion pair in water, and hydrophobic collapse of a C 45 H 92 n-pentatetracontane polymer chain. We make the approach freely available as a new module within the PLUMED2 enhanced sampling libraries.

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

Frame invariant neural network closures for Kraichnan turbulence

Numerical simulations of geophysical and atmospheric flows have to rely on parameterizations of subgrid scale processes due to their limited spatial resolution. Despite substantial progress in developing parameterization (or closure) models for subgrid scale (SGS) processes using physical insights and mathematical approximations, they remain imperfect and can lead to inaccurate predictions. In recent years, machine learning has been successful in extracting complex patterns from high-resolution spatio-temporal data, leading to improved parameterization models, and ultimately better coarse grid prediction. However, the inability to satisfy known physics and poor generalization hinders the application of these models for real-world problems. In this work, we put forth a frame invariant closure approach to improve the accuracy and generalizability of deep learning-based subgrid scale closure models by embedding physical symmetries directly into the structure of the neural network. Specifically, we utilized specialized layers within the convolutional neural network in such a way that desired constraints are theoretically guaranteed without the need for any regularization terms. We demonstrate our framework for a two-dimensional decaying turbulence test case mostly characterized by the forward enstrophy cascade. We show that our frame invariant SGS model (i) accurately predicts the subgrid scale source term, (ii) respects the physical symmetries such as translation, Galilean, and rotation invariance, and (iii) is numerically stable when implemented in coarse-grid simulation with generalization to different initial conditions and Reynolds number. This work opens up a possibility of connecting physics-based theories and data-driven modeling paradigms, and thus represents a promising step towards the development of physically consistent data-driven turbulence closure models.

42 ENGINEERING↗
NASA NTRS1984

Registration of rotated images by invariant moments

A new technique for registration of rotated images using invariant moments as the similarity measure is given. If circular windows with invariant moments are used, then window search can be carried out on rotated images in the same manner cross-correlation with rectangular windows is used on translated images. Normalization of invariant moments for more accurate window similarity measurement is also given. The proposed approach is tested against two images from different satellites that have translational and rotational differences.

Goshtasby, A.↗
NASA NTRS1999

Effects of walking velocity on vertical head and body movements during locomotion

Trunk and head movements were characterized over a wide range of walking speeds to determine the relationship between stride length, stepping frequency, vertical head translation, pitch rotation of the head, and pitch trunk rotation as a function of gait velocity. Subjects (26-44 years old) walked on a linear treadmill at velocities of 0.6-2.2 m/s. The head and trunk were modeled as rigid bodies, and rotation and translation were determined using a video-based motion analysis system. At walking speeds up to 1.2 m/s there was little head pitch movement in space, and the head pitch relative to the trunk was compensatory for trunk pitch. As walking velocity increased, trunk pitch remained approximately invariant, but a significant head translation developed. This head translation induced compensatory head pitch in space, which tended to point the head at a fixed point in front of the subject that remained approximately invariant with regard to walking speed. The predominant frequency of head translation and rotation was restricted to a narrow range from 1.4 Hz at 0.6 m/s to 2.5 Hz at 2.2 m/s. Within the range of 0.8-1.8 m/s, subjects tended to increase their stride length rather than step frequency to walk faster, maintaining the predominant frequency of head movement at close to 2.0 Hz. At walking speeds above 1.2 m/s, head pitch in space was highly coherent with, and compensatory for, vertical head translation. In the range 1.2-1.8 m/s, the power spectrum of vertical head translation was the most highly tuned, and the relationship between walking speed and head and trunk movements was the most linear. We define this as an optimal range of walking velocity with regard to head-trunk coordination. The coordination of head and trunk movement was less coherent at walking velocities below 1.2 m/s and above 1.8 m/s. These results suggest that two mechanisms are utilized to maintain a stable head fixation distance over the optimal range of walking velocities. The relative contribution of each mechanism to head orientation depends on the frequency of head movement and consequently on walking velocity. From consideration of the frequency characteristics of the compensatory head pitch, we infer that compensatory head pitch movements may be produced predominantly by the angular vestibulocollic reflex (aVCR) at low walking speeds and by the linear vestibulocollic reflex (1VCR) at the higher speeds.

NASA Discipline Neuroscience↗
DOE OSTI2020

On decoupling the integrals of cosmological perturbation theory

ABSTRACT Perturbation theory (PT) is often used to model statistical observables capturing the translation and rotation-invariant information in cosmological density fields. PT produces higher order corrections by integration over linear statistics of the density fields weighted by kernels resulting from recursive solution of the fluid equations. These integrals quickly become high dimensional and naively require increasing computational resources the higher the order of the corrections. Here, we show how to decouple the integrands that often produce this issue, enabling PT corrections to be computed as a sum of products of independent 1D integrals. Our approach is related to a commonly used method for calculating multiloop Feynman integrals in quantum field theory, the Gegenbauer Polynomial x-Space Technique. We explicitly reduce the three terms entering the 2-loop power spectrum, formally requiring 9D integrations, to sums over successive 1D radial integrals. These 1D integrals can further be performed as convolutions, rendering the scaling of this method Nglog Ng with Ng the number of grid points used for each fast Fourier transform. This method should be highly enabling for upcoming large-scale structure redshift surveys where model predictions at an enormous number of cosmological parameter combinations will be required by Monte Carlo Markov Chain searches for the best-fitting values.

Slepian, Zachary↗
NASA NTRS1985

Quasi-static evolution of force-free magnetic fields and a model for two-ribbon solar flares

It is shown that a two-dimensional force-free field in the solar corona can evolve in a quasi-static manner toward an open configuration, assuming the coronal field is invariant with respect to translations parallel to the x-axis. The theoretical result is applied to the quantitative theory of the evolution of two-ribbon solar flares of Kopp and Pneuman (1976), and the results are discussed. It is concluded that the two-dimensional force is the principal mechanism for the opening of the coronal magnetic field prior to reconnection during a solar flare.

Aly, J. J.↗
DOE OSTI2022

Magnetic Bloch theorem and reentrant flat bands in twisted bilayer graphene at 2 π flux

Bloch's theorem is the centerpiece of topological band theory, which itself has defined an era of quantum materials research. However, Bloch's theorem is broken by a perpendicular magnetic field, making it difficult to study topological systems in strong flux. For the first time, moiré materials have made this problem experimentally relevant, and its solution is the focus of this paper. We construct gauge-invariant irreps of the magnetic translation group at 2π flux on infinite boundary conditions, allowing us to give analytical expressions in terms of the Siegel theta function for the magnetic Bloch Hamiltonian, non-Abelian Wilson loop, and many-body form factors. We illustrate our formalism using a simple square lattice model and the Bistritzer-MacDonald Hamiltonian of twisted bilayer graphene, obtaining reentrant ground states at 2π flux under the Coulomb interaction.

2-dimensional systems↗
NASA NTRS1979

Optical correlation of surface displacement

A coherent optical correlation technique is used to measure surface displacements. In the event that the surface roughness of the test object is invariant during the object's translation, the correlation intensity peak remains constant. A simple relationship between the displacement of the surface and the displacement of the peak correlation signal is found and experimentally verified.

Owen, R. B.↗
NASA NTRS1987

Some plane curvature approximations

An analytical technique is developed to estimate (with second-order accuracy) the curvature of a sufficiently smooth plane curve defined in finite form. The derivation of the approximations from local information is explained in detail; the continuity and invariance of the estimates under translation and rotation are demonstrated; and examples, error estimates, and a broken-line extension are presented. The suitability of the present technique for computer implementation is indicated.

Mjolsness, R. C.↗
NASA NTRS1986

Dynamic posture analysis of Spacelab-1 crew members

Dynamic posture testing was conducted on the science crew of the Spacelab-1 mission on a single axis linear motion platform. Tests took place in pre- and post-flight sessions lasting approximately 20 min each. The pre-flight tests were widely spaced over the several months prior to the mission while the post-flight tests were conducted over the first, second, fourth, and sixth days after landing. Two of the crew members were also tested on the day of landing. Consistent with previous postural testing conducted on flight crews, these crew members were able to complete simple postural tasks to an acceptable level even in the first few hours after landing. Our tests were designed to induce dynamic postural responses using a variety of stimuli and from these responses, evaluate subtle changes in the postural control system which had occurred over the duration of the flight. Periodic sampling post-flight allowed us to observe the time course of readaptation to terrestrial life. Our observations of hip and shoulder position, when subjected to careful analysis, indicated modification of the postural response from pre- to post-flight and that demonstrable adjustments in the dynamic control of their postural systems were taking place in the first few days after flight. For transient stimuli where the platform on which they were asked to stand quickly moved a few centimeters fore or aft then stopped, ballistic or open loop 'programs' would closely characterize the response. During these responses the desired target position was not always achieved and of equal importance not always properly corrected some 15 seconds after the platform ceased to move. The persistent observation was that the subjects had a much stronger dependence on visual stabilization post-flight than pre-flight. This was best illustrated by a slow or only partial recovery to an upward posture after a transient base-of-support movement with eyes open. Postural responses to persistent wideband pseudorandom base-of-support translation were modeled as time invarient linear systems arrived at by Kalman adaptive filter techniques. Derived model parameters such as damping factor and fundamental frequency of the closed loop system showed significant modification between pre- and post-flight. This phenomenon is best characterized by movement of the poles toward increasing stability. While pre-flight data tended to show shoulders and hips moving in phase with each other, post-flight data showed a more disjoint behavior.(ABSTRACT TRUNCATED AT 400 WORDS).

Non-NASA Center↗
NASA NTRS2013

Hand-Based Biometric Analysis

Hand-based biometric analysis systems and techniques provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an input image. Additionally, the analysis uses re-use of commonly seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

Bebis, George↗
NASA NTRS2015

Hand-Based Biometric Analysis

Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

Bebis, George↗
DOE OSTI2024

Gravitational wave spectrum of chain inflation

Chain inflation is an alternative to slow-roll inflation in which the inflaton tunnels along a large number of consecutive minima in its potential. In this work we perform the first comprehensive calculation of the gravitational wave (GW) spectrum of chain inflation. In contrast to slow-roll inflation the latter does not stem from quantum fluctuations of the gravitational field during inflation, but rather from the bubble collisions during the first-order phase transitions associated with vacuum tunneling. Our calculation is performed within an effective theory of chain inflation which builds on an expansion of the tunneling rate capturing most of the available model space. The effective theory can be seen as chain inflation’s analog of the slow-roll expansion in rolling models of inflation. The near scale-invariance of the scalar power spectrum translates to a quasiperiodic shape of the inflaton potential in chain inflation, with the tunneling rate changing very slowly during the e-folds leading to cosmic microwave background observables. We show that chain inflation produces a very characteristic double-peak GW spectrum: a faint high-frequency peak associated with the gravitational radiation emitted during inflation, and a strong low-frequency peak associated with the graceful exit from chain inflation (marking the transition to the radiation-dominated epoch). There exist very exciting prospects to test the gravitational wave signal from chain inflation at the aLIGO-aVIRGO-KAGRA network, at LISA and /or at pulsar timing array experiments. A particularly intriguing possibility we point out is that chain inflation could be the source of the stochastic gravitational wave background recently detected by NANOGrav, PPTA, EPTA, and CPTA. We also show that the gravitational wave signal of chain inflation is often accompanied by running/ higher running of the scalar spectral index to be tested at future cosmic microwave background experiments. Published by the American Physical Society 2024

Freese, Katherine↗
DOE OSTI2026

Reflections on Noether’s second theorem and the energy-momentum tensor

Through symmetry of the action under global spacetime translations, Noether’s first theorem infamously entails an energy-momentum tensor (EMT) that is neither symmetric nor gauge-invariant. In a prior work [Phys. Rev. D 106, 125012 (2022)], I had obtained a symmetric and gauge-invariant EMT by using Noether’s second theorem instead, with local spacetime translations as the symmetry group. However, the derivation therein was flawed, containing a faulty assumption about the transformation rule for spinor fields. In this work, I revisit the derivation of the previous work, both correcting the faulty step and simplifying the derivation for broader accessibility. The end result is an EMT for quantum chromodynamics that is gauge-invariant, but not symmetric.

Quantum chromodynamics↗