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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 1,171 records · Page 65
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NASA NTRS1987

Digital robust active control law synthesis for large order systems using constrained optimization

This paper presents a direct digital control law synthesis procedure for a large order, sampled data, linear feedback system using constrained optimization techniques to meet multiple design requirements. A linear quadratic Gaussian type cost function is minimized while satisfying a set of constraints on the design loads and responses. General expressions for gradients of the cost function and constraints, with respect to the digital control law design variables are derived analytically and computed by solving a set of discrete Liapunov equations. The designer can choose the structure of the control law and the design variables, hence a stable classical control law as well as an estimator-based full or reduced order control law can be used as an initial starting point. Selected design responses can be treated as constraints instead of lumping them into the cost function. This feature can be used to modify a control law, to meet individual root mean square response limitations as well as minimum single value restrictions. Low order, robust digital control laws were synthesized for gust load alleviation of a flexible remotely piloted drone aircraft.

Mukhopadhyay, Vivek↗
NASA NTRS2018

Multidecadal Changes in Lower Stratospheric Ozone: Variability Vs. Trends

As upper stratospheric ozone appears to be recovering as a result of decreasing chlorine loading following the implementation of the Montreal Protocol and its amendments and in agreement with model projections, several recent studies report an apparent decline of ozone concentrations in the lower stratosphere in the last two decades, particularly in the extratropics. Our previous work as well as at least two other studies provide evidence that this decline results from transport changes rather than an intensification of chemical depletion. It remains unclear whether these changes represent long-term internal variability or are a consequence of a climate forcing. Here we perform free-running ensembles of the recent past (1980-2016) using the Goddard Earth Observing System Model (GEOS) at the cubed sphere C180 (approximately half degree) resolution. Two suites of 10-member ensembles are performed, one in which observed sea surface temperature (SSTs) are fully prescribed, and the other in which the linear SST trend over the recent past is removed so as to only retain internal variability. We evaluate the trends in both ozone as well as two idealized tracers with prescribed uniform loss that are used to isolate the role of transport from chemistry and emissions. Probability-distribution-functions of the trends in both ozone and idealized tracers are compared among ensemble members and with observed trends in order to evaluate the likelihood of recent observed declines in lower stratospheric ozone, relative to large internal variability. Moreover, comparisons among simulations with and without imposed SST trends indicate the extent to which dynamically-driven ozone trends reflect forced trends or internal variability in lower stratospheric dynamics.

Wargan, Krzysztof↗
DOE OSTI2024

Hutchinson Trace Estimation for high-dimensional and high-order Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data and physics. However, extending PINNs to high-dimensional and even high-order PDEs encounters significant challenges due to the computational cost associated with automatic differentiation in the residual loss function calculation. Herein, we address the limitations of PINNs in handling high-dimensional and high-order PDEs by introducing the Hutchinson Trace Estimation (HTE) method. Starting with the second-order high-dimensional PDEs, which are ubiquitous in scientific computing, HTE is applied to transform the calculation of the entire Hessian matrix into a Hessian vector product (HVP). This approach not only alleviates the computational bottleneck via Taylor-mode automatic differentiation but also significantly reduces memory consumption from the Hessian matrix to an HVP’s scalar output. We further showcase HTE’s convergence to the original PINN loss and its unbiased behavior under specific conditions. Comparisons with the Stochastic Dimension Gradient Descent (SDGD) highlight the distinct advantages of HTE, particularly in scenarios with significant variability and variance among dimensions. We further extend the application of HTE to higher-order and higher-dimensional PDEs, specifically addressing the biharmonic equation. By employing tensor-vector products (TVP), HTE efficiently computes the colossal tensor associated with the fourth-order high-dimensional biharmonic equation, saving memory and enabling rapid computation. The effectiveness of HTE is illustrated through experimental setups, demonstrating comparable convergence rates with SDGD under memory and speed constraints. Additionally, HTE proves valuable in accelerating the Gradient-Enhanced PINN (gPINN) version as well as the Biharmonic equation. Overall, HTE opens up a new capability in scientific machine learning for tackling high-order and high-dimensional PDEs.

Curse of dimensionality↗
DOE OSTI2019

The modeling of the turbulent reaction rate under high-pressure conditions: A priori evaluation of the Conditional Source-term Estimation concept

With the goal of obtaining an accurate model of the turbulent reaction rate for Large Eddy Simulations (LESs), the modeling of turbulence-chemistry-thermodynamic interaction is addressed through an a priori study of a Direct Numerical Simulation (DNS) database representing high-pressure turbulent combustion. The DNS database consists of simulations of a temporal mixing layer in which a single-step chemical reaction occurs. The potential of the single-conditioned Conditional Source-term Estimation (CSE) approach to model the filtered turbulent reaction rate needed for conducting LES is examined. Evaluations conducted with the mixture fraction as a conditioning variable at two filter widths and with the probability density function (PDF) extracted from the DNS database that represents the mixture fraction, show that the deviation between the model and template is large and substantially increases with filter width. To address this deviation, the Double-conditioned CSE (DCSE) approach is explored with two different second conditioning variables, the first conditioning variable still being the mixture fraction; four filter widths are considered. The first choice of the second conditioning variable is a normalized progress variable based on the CO 2 mass fraction and the second choice of the second conditioning variable is a normalized temperature. With each second conditional variable, the DCSE results represent a substantial improvement over CSE, by as much as an order of magnitude when measured by the relative error from the DNS-extracted filtered reaction rate. A quantitative test based on a root mean square identifies the reason for the DCSE success compared to CSE: unlike in CSE, the DCSE is able to substantially reduce the fluctuations of the modeled reaction rate from the filtered reaction rate over the entire range of the filtered reaction rate values, and particularly at the larger reaction rate values for which the DCSE model has higher fidelity. The results are shown to be equally favorable for the two conditioning variables. Consideration of DNS realizations at higher free-stream pressure or larger Reynolds number shows that the results are essentially equally successful at other pressure or Reynolds number values.

42 ENGINEERING↗
NASA NTRS1992

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

Cook, A. B.↗
NASA NTRS2003

Compositional Grading in an Impact-produced Spherule Bed, Barberton Greenstone Belt, South Africa: A Key to Condensation History of Rock Vapor Clouds

The chemical and physical processes by which spherules form during the condensation of impact-produced rock vapor clouds are poorly understood. Although efforts have been made to model the processes of spherule formation, there is presently a paucity of field data to constrain the resulting theoretical models. The present study examines the vertical compositional variability in a single early Archean spherule bed in the Barberton Greenstone Belt (BGB), South Africa, in order to better identify the process by which impact vapor clouds condense and spherules form and accumulate. The BGB spherule beds are suitable for this type of study because of their great thickness, often exceeding 25cm of pure spherules, due to the massive sizes of the impactors. Two main problems complicate analysis of vertical compositional variability of graded spherule beds: (1) differential settling of particles in both the vapor and water column due to density and size differences and (2) turbulence within the vapor cloud. The present study compares sections of spherule bed S3 from four different depositional environments in the Barberton Greenstone Belt: (1) The Sheba Mine section (SAF-381) was deposited under fairly low energy conditions in deep water, providing a nice fallout sequence, and also has abundant Ni-rich spinels; (2) Jay's Chert section (SAF-380) was deposited in subaerial to shallow-water conditions with extensive post-depositional reworking by currents. The spherules also have preserved spinels; (3) the Loop Road section (loc. SAF-295; samp. KSA-7) was moderately reworked and has only rare preservation of spinels; and (4) the shallow-water Barite Syncline section (loc. SAF-206; samp KSA-1) has few to no spinels preserved and is not reworked. Although all of the spherule beds have been altered by silica diagenesis and K-metasomatism, most of the compositional differences between these sections appear to reflect their diagenetic histories, possibly related to their differing depositional environments. Sulfate diagenesis in the Barite Syncline and Loop road sections may account for the loss of spinels.

Krull, A. E.↗
NASA NTRS1992

Maxwell's second- and third-order equations of transfer for non-Maxwellian gases

Condensed algebraic forms for Maxwell's second- and third-order equations of transfer are developed for the case of molecules described by either elastic hard spheres, inverse-power potentials, or by Bird's variable hard-sphere model. These hardly reduced, yet exact, equations provide a new point of origin, when using the moment method, in seeking approximate solutions in the kinetic theory of gases for molecular models that are physically more realistic than that provided by the Maxwell model. An important by-product of the analysis when using these second- and third-order relations is that a clear mathematical connection develops between Bird's variable hard-sphere model and that for the inverse-power potential.

Baganoff, D.↗
DOE OSTI2021

The Value of Watching How Materials Grow: A Multimodal Case Study on Halide Perovskites

Material synthesis is one of the most important aspects in humankinds’ endeavor to discover and create new materials for energy applications. One strategy to tailor materials with desired functions in a rational way is by knowing how functions relate to structure, synthetic variables, arrangement of atoms and molecules, and how functions evolve during synthesis. In order to accelerate materials synthesis, discovery, and optimization by 10 times it is the right time now to integrate computational tools, synthesis, and characterization. One particular barrier to realizing this concept is the understanding of when and how phases form in real time during synthesis, which is challenging to asses by existing theoretical frameworks. In addition, transient or metastable phases with positive free energy above the lowest-free energy ground state can be revealed by such real time (in situ) measurements. Metastable materials are ubiquitous in condensed matter and can show superior properties compared to their equilibrium form. This work discusses the value of emerging multimodal in situ characterizations exemplified on hybrid halide perovskites. Finally, the ways in which the implementation of in situ measurements can advance the materials science synthesis field as well as their role to enable close-loop feedback control and autonomous synthesis are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurements of inclusive and differential cross-sections of combined $ t\overline{t}\gamma$ and tWγ production in the eμ channel at 13 TeV with the ATLAS detector

Inclusive and differential cross-sections for the production of top quarks in association with a photon are measured with proton-proton collision data corresponding to an integrated luminosity of 139 fb - 1 . The data were collected by the ATLAS detector at the LHC during Run 2 between 2015 and 2018 at a centre-of-mass energy of 13 TeV. The measurements are performed in a fiducial volume defined at parton level. Events with exactly one photon, one electron and one muon of opposite sign, and at least two jets, of which at least one is b -tagged, are selected. The fiducial cross-section is measured to be $ {39.6}_{-2.3}^{+2.7} $ fb. Differential cross-sections as functions of several observables are compared with state-of-the-art Monte Carlo simulations and next-to-leading-order theoretical calculations. These include cross-sections as functions of photon kinematic variables, angular variables related to the photon and the leptons, and angular separations between the two leptons in the event. All measurements are in agreement with the predictions from the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Opinion Dynamics on Networks under Correlated Disordered External Perturbations

We study an influence network of voters subjected to correlated disordered external perturbations, and solve the dynamical equations exactly for fully connected networks. The model has a critical phase transition between disordered unimodal and ordered bimodal distribution states, characterized by an increase in the vote-share variability of the equilibrium distributions. The fluctuations (variance and correlations) in the external perturbations are shown to reduce the impact of the external influence by increasing the critical threshold needed for the bimodal distribution of opinions to appear. The external fluctuations also have the surprising effect of driving voters towards biased opinions. Furthermore, the first and second moments of the external perturbations are shown to affect the first and second moments of the vote-share distribution. This is shown analytically in the mean field limit, and confirmed numerically for fully connected networks and other network topologies. Studying the dynamic response of complex systems to disordered external perturbations could help us understand the dynamics of a wide variety of networked systems, from social networks and financial markets to amorphous magnetic spins and population genetics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Generalized logarithmic equation of state in classical and loop quantum cosmology dark energy–dark matter coupled systems

In this paper we shall study the phase space of a coupled dark energy–dark matter fluids system, in which the dark energy has a generalized logarithmic corrected equation of state. Particularly, the equation of state for the dark energy will contain a logarithmic function of the dark energy density ρ{sub d} and will also have quadratic and Chaplygin gas-like terms, expressed in terms of ρ{sub d}. We shall use the dynamical system approach in order to study the cosmological dynamics, and by appropriately choosing the dynamical system variables, we shall construct an autonomous dynamical system. The study will be performed in the context of classical and loop quantum cosmology, and the focus is on finding stable de Sitter attractors. As we demonstrate, in both the classical and loop quantum cosmology cases, there exist stable de Sitter attractors in the phase space, with the loop quantum cosmology case though having a wider range of the free parameter values for which the stable de Sitter attractors may occur. It is emphasized that the use of a generalized dark energy equation of state makes possible the existence of de Sitter attractors, which were absent in the case that a simple logarithmic term constitutes the dark energy equation of state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics

Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Polyakov loop modeling for hot QCD

Here, we review theoretical aspects of quantum chromodynamics (QCD) at finite temperature. The most important physical variable to characterize hot QCD is the Polyakov loop, which is an approximate order parameter for quark deconfinement in a hot gluonic medium. Additionally to its role as an order parameter, the Polyakov loop has rich physical contents in both perturbative and non-perturbative sectors. This review covers a wide range of subjects associated with the Polyakov loop from topological defects in hot QCD to model building with coupling to the Polyakov loop.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

The Influence of Microstructure on Deuterium Retention in Polycrystalline Tungsten

The retention of hydrogen isotopes in the plasma-facing materials of a fusion reactor is dependent on the density of trapping sites in the material. One factor that can influence the trapping defects is the surface state of the material before exposure. Mechanically polished, electropolished, and recrystallized tungsten samples were compared by exposing them to 350 eV D + beams with peak fluences of ~1 × 10 24 D + /m 2 at 500 and 740 K at the Multicharged Ion Research Facility (MIRF). At the exposure temperature of 740 K, no significant retention was detected. For material exposed at 500 K, significant differences in retention were observed, and the order of increasing retention was recrystallized, electropolished, and mechanically polished. Lastly, the other variable besides surface treatment was the time delay between ion exposure and thermal desorption spectroscopy which also may have impacted the retention measurements if there was out-gassing of the D while samples were in storage before thermal desorption spectroscopy (TDS).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Helical magnetism in Sr-doped CaM n 7 O 12 films

Noncollinear magnetism can play an important role in multiferroic materials but is relatively understudied in oxide heterostructures compared to their bulk counterparts. Using variable temperature magnetometry and neutron diffraction, we demonstrate the presence of helical magnetic ordering in CaMn 7 O 12 and Ca 1-x Sr x Mn 7 O 12 (for x up to 0.51) thin films. Consistent with bulk Ca 1-x Sr x Mn 7 O 12 , the net magnetization increases with Sr doping. Neutron diffraction confirms that the helical magnetic structure remains incommensurate at all values of x, while the fundamental magnetic wavevector increases upon Sr substitution. Lastly, this result demonstrates a chemical-based approach for tuning helical magnetism in quadruple perovskite films and enables future studies of strain and interfacial effects on helimagnetism in oxide heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Perturbations of Gibbons-Maeda black holes in Einstein-Maxwell-dilaton theories

The study of perturbations around black hole backgrounds in general relativity and Einstein-Maxwell theory has a long history, going back to the work of Regge and Wheeler in the 1950s. As part of a broader investigation of perturbations around black holes in supergravity, we describe here our results for the perturbations around the Gibbons-Maeda static charged black holes in a class of Einstein-Maxwell-Dilaton theories. Our analysis follows the general strategy developed by Chandrasekhar and Xanthopoulos for the perturbations of the Reissner-Nordström black hole. Here, the analysis is considerably more involved, because of the presence of the dilaton field, which couples to the other polar modes. We nonetheless find that the problem is completely solvable, in the sense that one can separate variables and eventually describe all the perturbations in terms of diagonalised second-order radial equations. We are able to prove the mode stability of all the Gibbons-Maeda black hole solutions. Published by the American Physical Society 2024

Pope, C. N. (ORCID:0000000284012564)↗
DOE OSTI2019

Parallel-In-Time Multigrid with Adaptive Spatial Coarsening for The Linear Advection and Inviscid Burgers Equations

We apply a multigrid reduction-in-time (MGRIT) algorithm to hyperbolic partial differential equations in one spatial dimension. This study is motivated by the observation that sequential time-stepping is a computational bottleneck when attempting to implement highly concurrent algorithms; thus parallel-in-time methods are desirable. MGRIT adds parallelism by using a hierarchy of successively coarser temporal levels to accelerate the solution on the finest level. In the case of explicit time-stepping, spatial coarsening is a suitable approach to ensure that stability conditions are satisfied on all levels, and it may be useful for implicit time-stepping by producing cheaper multigrid cycles. Unfortunately, uniform spatial coarsening results in extremely slow convergence when the wave speed is near zero, even if only locally. We present an adaptive spatial coarsening strategy that addresses this issue for the variable coefficient linear advection equation and the inviscid Burgers equation using first-order explicit or implicit time-stepping methods. Serial numerical results show this method offers significant improvements over uniform coarsening and is convergent for the inviscid Burgers equation with and without shocks. Parallel scaling tests on up to 128K cores indicate that run-time improvements over serial time-stepping strategies are possible when spatial parallelism alone saturates, and that scalability is robust for oscillatory solutions which change on the scale of the grid spacing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Partons as unique ground states of quantum Hall parent Hamiltonians: The case of Fibonacci anyons

We present microscopic, multiple Landau level, (frustration-free and positive semi-definite) parent Hamiltonians whose ground states, realizing different quantum Hall fluids, are parton-like and whose excitations display either Abelian or non-Abelian braiding statistics. We prove ground state energy monotonicity theorems for systems with different particle numbers in multiple Landau levels, demonstrate S-duality in the case of toroidal geometry, and establish complete sets of zero modes of special Hamiltonians stabilizing parton-like states, specifically at filling factor \nu=2/3 ν = 2 / 3 . The emergent Entangled Pauli Principle (EPP), introduced in [Phys. Rev. B 98, 161118(R) (2018)] and which defines the “DNA” of the quantum Hall fluid, is behind the exact determination of the topological characteristics of the fluid, including charge and braiding statistics of excitations, and effective edge theory descriptions. When the closed-shell condition is satisfied, the densest (i.e., the highest density and lowest total angular momentum) zero-energy mode is a unique parton state. We conjecture that parton-like states generally span the subspace of many-body wave functions with the two-body M M -clustering property within any given number of Landau levels, that is, wave functions with M M th-order coincidence plane zeroes and both holomorphic and anti-holomorphic dependence on variables. General arguments are supplemented by rigorous considerations for the M=3 M = 3 case of fermions in four Landau levels. For this case, we establish that the zero mode counting can be done by enumerating certain patterns consistent with an underlying EPP. We apply the coherent state approach of [Phys. Rev. X 1, 021015 (2011)] to show that the elementary (localized) bulk excitations are Fibonacci anyons. This demonstrates that the DNA associated with fractional quantum Hall states encodes all universal properties. Specifically, for parton-like states, we establish a link with tensor network structures of finite bond dimension that emerge via root level entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗