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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 127 records · Page 7

Advancing Insights into Electrochemical Pre‐Treatments of Supported Nanoparticle Electrocatalysts by Combining a Design of Experiments Strategy with In Situ Characterization

Activation, break-in, and/or pre-treatment protocols are generally applied to energy conversion devices before regular operation to reach stable performance. There remains much to understand about the relationships among physical properties, performance, and electrochemical pre-treatments. Here, a design-of-experiments (DoE) strategy is employed to address this gap by demonstrating the influence of five pre-treatment parameters for carbon-supported Pt-nanoparticle catalysts on the electrocatalytic oxygen reduction reaction (ORR). A subset of pre-treatments, developed using a central composite design, are tested in a flow cell combined with an inductively-coupled plasma mass spectrometer (on-line ICP-MS). The DoE-based approach facilitates comprehensive insights from two orders of magnitude fewer experiments than a conventional grid search. The coupled on-line ICP-MS setup enables effective catalysis and real-time catalyst dissolution data. Leveraging insights from DoE for on-line ICP-MS and additional characterization, a model is built between the degradation of a multi-dimensional supported Pt surface, its performance, and applied electrochemical parameters. These investigations identify surface modifications, such as oxidation, and subsequent restructuring of Pt during pre-treatment as a primary cause of performance deterioration during ORR. By combining DoE with advanced characterization techniques, a powerful approach is demonstrated to gain a mechanistic understanding of pre-treatment protocols that can be broadly adapted to various reaction chemistries.

Platinum↗

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗

Quasi-periodic structures in the large-scale galaxy distribution and three-dimensional Voronoi tessellation

It has been suggested that the void and wall structure associated with the large-scale galaxy distribution might be qualitatively, or perhaps even physically, modeled by a Voronoi tessellation, and that such structure might account for the surprisingly regular, sharp peaks in the galaxy redshift distributions obtained from 'pencil beam' surveys. Taking cell wall crossings by random line segments to correspond to such redshift peaks, an exact expression is derived for the distribution of spacings of these intersections in a three-dimensional Voronoi tessellation. This result verifies that the spacings are nonrandom and quasi-periodic, qualitatively resembling the observed pattern, even though the cell wall structure is generated from randomly placed seeds. Finally, moments of the spacing distribution are used to show that apparently periodic samples, similar to those recently reported, represent only one to two sigma fluctuations in a Voronoi tesselation.

Ikeuchi, Satoru↗

The Simons Observatory: science goals and forecasts for the enhanced Large Aperture Telescope

We describe updated scientific goals for the wide-field, millimeter-wave survey that will be produced by the Simons Observatory (SO). Significant upgrades to the 6-meter SO Large Aperture Telescope (LAT) are expected to be complete by 2028, and will include a doubled mapping speed with 30,000 new detectors and an automated data reduction pipeline. In addition, a new photovoltaic array will supply most of the observatory's power. The LAT survey will cover about 60% of the sky at a regular observing cadence, with five times the angular resolution and ten times the map depth of the Planck satellite. The science goals are to: (1) determine the physical conditions in the early universe and constrain the existence of new light particles; (2) measure the integrated distribution of mass, electron pressure, and electron momentum in the late-time universe, and, in combination with optical surveys, determine the neutrino mass and the effects of dark energy via tomographic measurements of the growth of structure at redshifts z ≲ 3; (3) measure the distribution of electron density and pressure around galaxy groups and clusters, and calibrate the effects of energy input from galaxy formation on the surrounding environment; (4) produce a sample of more than 30,000 galaxy clusters, and more than 100,000 extragalactic millimeter sources, including regularly sampled AGN light-curves, to study these sources and their emission physics; (5) measure the polarized emission from magnetically aligned dust grains in our Galaxy, to study the properties of dust and the role of magnetic fields in star formation; (6) constrain asteroid regoliths, search for Trans-Neptunian Objects, and either detect or eliminate large portions of the phase space in the search for Planet 9; and (7) provide a powerful new window into the transient universe on time scales of minutes to years, concurrent with observations from the Vera C. Rubin Observatory of overlapping sky.

79 ASTRONOMY AND ASTROPHYSICS↗

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗

HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations

Physics-informed neural networks (PINNs) based machine learning is an emerging framework for solving nonlinear differential equations. However, due to the implicit regularity of neural network structure, PINNs can only find the flattest solution in most cases by minimizing the loss functions. In this paper, we combine PINNs with the homotopy continuation method, a classical numerical method to compute isolated roots of polynomial systems, and propose a new deep learning framework, named homotopy physics-informed neural networks (HomPINNs), for solving multiple solutions of nonlinear elliptic differential equations. The implementation of an HomPINN is a homotopy process that is composed of the training of a fully connected neural network, named the starting neural network, and training processes of several PINNs with different tracking parameters. The starting neural network is to approximate a starting function constructed by the trivial solutions, while other PINNs are to minimize the loss functions defined by boundary condition and homotopy functions, varying with different tracking parameters. These training processes are regraded as different steps of a homotopy process, and a PINN is initialized by the well-trained neural network of the previous step, while the first starting neural network is initialized using the default initialization method. Finally, several numerical examples are presented to show the efficiency of our proposed HomPINNs, including reaction-diffusion equations with a heart-shaped domain.

97 MATHEMATICS AND COMPUTING↗

Charges in the UV completion of neutral electrodynamics

A theory with a non-compact form-symmetry is described by two closed form fields of degrees k and d – k. Effective theory examples are non-linear electrodynamics, a photon field coupled to a neutron field, and a low energy Goldstone boson. We show these models cannot be completed in the UV without breaking the non-compact form-symmetry down to a compact one. This amounts to the existence of electric or magnetic charges. A theory with an unbroken non-compact k-form symmetry is massless and free.

't Hooft and Polyakov loops↗

Solution Irregularity Remediation for Spatial Discretization Error Estimation for S N Transport Solutions

The discrete ordinates linear Boltzmann transport equation is typically solved in its spatially discretized form, incurring spatial discretization error. Quantification of this error for purposes such as adaptive mesh refinement or error analysis requires an a posteriori estimator, which utilizes the numerical solution to the spatially discretized equation to compute an estimate. Because the quality of the numerical solution informs the error estimate, irregularities, present in the true solution for any realistic problem configuration, tend to cause the largest deviation in the error estimate vis-a-vis the true error. In this paper, an analytical partial singular characteristic tracking (pSCT) procedure for reducing the estimator’s error is implemented within our novel residual source estimator for a zeroth-order discontinuous Galerkin scheme, at the additional cost of a single inner iteration. Here, a metric-based evaluation of the pSCT scheme versus the standard residual source estimator is performed over the parameter range of a Method of Manufactured Solutions test suite. The pSCT scheme generates near-ideal accuracy in the estimate in problems where the dominant source of the estimator’s error is the solution irregularity, namely, problems where the true solution is discontinuous and problems where the true solution’s first derivative is discontinuous and the scattering ratio is low. In problems where the scattering ratio is high and the true solution is discontinuous in the first derivative, the error in the scattering source, which is not converged by the pSCT scheme, is greater than the error incurred due to the irregularity. Ultimately, a pSCT scheme is judged to be useful for error estimation in problems where the computational cost of the scheme is justified. In the presence of many irregularities, such a scheme may be intractable for general use, but in benchmarks, as an analytical tool, or in problems that have nondissipative discontinuities, the scheme may prove invaluable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On the psychophysics of workload - Why bother with subjective measures?

Psychophysical functions describe the relationship between variations in the amplitude of a defined physical quantity and the psychological perception of these changes. Examples are brightness, loudness, and pain. The regularities of these relationships have been formulated into psychophysical laws. The measurement methodology of psychophysical scaling has been refined by the Harvard group led by Stevens (1957 and 1966), who proposed a power function as a general form for such laws. It is argued here that a similar scaling approach can be adapted to the measurement of workload and task demands based upon subjective estimates. The rationale is that these estimates, like other psychophysical judgments, reflect the individual's perception of the amount of processing resources that the subject invests to meet the demand imposed by a task. This approach was successfully applied to the assessment of 21 experimental conditions given to a group of 60 subjects. The paper discusses the main results of this effort and their implications to theory and application in human performance.

Gopher, D.↗

Origins of outer-planet satellites

Aspects of satellite origin and evolution which bear on the formation of the solar system are addressed, with emphasis on the chemical evidence contained in satellites concerning the modification of the interstellar material which went to form the solar system. New results on the tidal evolution of outer-planet satellite systems are presented. The gross physical and chemical properties of the satellite systems of the outer planets are outlined. Models for regular satellite formation are reviewed. Attention is given to the evolution of the satellites, with emphasis on tidal evolution, including a discussion of the dynamical origin of Triton. The volatile budgets of Titan, Triton, and Pluto/Charon are discussed, and models are presented for the origin of these budgets which tie them to the larger set of processes associated with solar system formation.

Lunine, Jonathan I.↗

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The GEOS DAS will be used to provide background fields of meteorological quantities to EOS satellite instrument teams for use in their data algorithms as well as providing assimilated data sets for climate studies on decadal time scales. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now embarking on an effort to convert the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). The GEOS DAS consists of two main components, an atmospheric General Circulation Model (GCM) and a Physical-space Statistical Analysis System (PSAS). The GCM operates on data that are stored on a regular grid while PSAS works with observational data that are scattered irregularly throughout the atmosphere. As a result, the two components have different data decompositions. The GCM is decomposed horizontally as a checkerboard with all vertical levels of each box existing on the same processing element(PE). The dynamical core of the GCM can also operate on a rotated grid, which requires communication-intensive grid transformations during GCM integration. PSAS groups observations on PEs in a more irregular and dynamic fashion.

Lucchesi, Rob↗

Mitigating Grazing Flow Impedance Eduction Errors in Additively Manufactured Porous Liners

Additively manufactured porous metamaterials, including triply periodic minimal surface (TPMS) cores, are promising candidates for aeroengine liners but often behave as extended-reacting treatments under grazing flow. Standard impedance eduction procedures assume locally-reacting behavior and can yield physically inconsistent results for such materials. This study evaluates internal partitions (thin solid walls inserted at regular intervals along the liner’s streamwise extent) as a means of suppressing internal streamwise propagation to improve eduction consistency. Six TPMS configurations were tested in the NASA Langley Grazing Flow Impedance Tube (GFIT) at partition spacings of 4′′, 2′′, and 1′′, as well as unpartitioned, and at Mach numbers up to 0.3. For most geometries, 2′′ partition spacing eliminated impedance discontinuities and substantially improved Prony correlation, though effectiveness varied with core topology. Partitions also altered the acoustic response of the liners: resistance increased, resonance frequencies shifted downward, and peak attenuation decreased while bandwidth broadened in some cases. Because partitions modify the liner itself, the educed impedance characterizes the partitioned system rather than the original unpartitioned core. These results establish partitioning as a practical pathway toward liners that are more compatible with standard eduction methods, while demonstrating that the intervention is itself an acoustic design change.

liners↗

Accelerator Physics at NSLS-II: Research Accomplishments in 2024

NSLS-II accelerator physicists advanced the operational performance and scientific capabilities of NSLS-II, providing regular lattice characterization and correction, injec tion optimization, vertical emittance control, and beam dynamics reports with corre lation analysis. We further developed advanced lattice characterization techniques and studies on impedance, beam-induced heating, and higher-harmonic RF cavity effects to support NSLS-II and its high-brightness upgrade. The assessment of free-electron laser options for the NSLS-II upgrade has been completed. We carried out comprehensive studies focused on complex bend magnets and novel efficient injection schemes for next-generation low-emittance synchrotrons. We contributed to the Electron-Ion Collider project, including Electron Storage Ring lattice design, beam diagnostics, and injector studies. The physicists participated in international collaborations, including the development of Python-based Middle Layer software, and participated in key accel erator physics workshops and scientific meetings. The main research accomplishments achieved in 2024 are summarized in this report.

43 PARTICLE ACCELERATORS↗

Physically interpretable approximations of many-body spectral functions

The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the vector fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions. We show that the resulting rational functions are highly efficient in their fitting of sharp features in the spectral functions, and could provide a means to infer physically relevant information from a spectral data set. The position of the peaks in the approximated spectral function are determined by the location of poles in the complex plane. Additionally, we developed a variant of VFIT that incorporates regularization to improve the quality of fits. With this procedure, we demonstrate it is possible to achieve accurate spectral function fits that vary smoothly as a function of physical conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications

Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods is that the resulting model requires significantly less data to train. By incorporating physical rules into the machine learning formulation itself, the predictions are expected to be physically plausible. Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets. In this paper, we investigate the possibility of constraining a GP formulation with monotonicity on three different material datasets, where one experimental and two computational datasets are used. The monotonic GP is compared against the regular GP, where a significant reduction in the posterior variance is observed. The monotonic GP is strictly monotonic in the interpolation regime, but in the extrapolation regime, the monotonic effect starts fading away as one goes beyond the training dataset. Imposing monotonicity on the GP comes at a small accuracy cost, compared to the regular GP. The monotonic GP is perhaps most useful in applications where data are scarce and noisy, and monotonicity is supported by strong physical evidence.

36 MATERIALS SCIENCE↗

CMS Physics Results in the LHC Runs 2,3

The Large hadron Collider at CERN and four scientific collaborations: Alice, ATLAS, CMS, LHCb are in operation since September 2008. The accelerator delivered and the experiments processed trillions of events of proton-proton and heavy ions collisions and provided useful data for thousands of physics analyses and publications. The jewel of the published data is a discovery in 2012 of the long anticipated Higgs boson. During the operation time the regular acquisition of data was interleaved with two periods of maintenance, Long-shutdown-1 (2013-2015) and Long-shutdown-2 (2018-2022), which resulted in several improvements to the machine and the experiments. The CMS collaboration recorded to date two large physics datasets of pp collision data. The first dataset, called Run 2, was recorded between 2015 and 2018 with 140fb-1 of integrated luminosity taken at 13TeV of center of mass energy. The second dataset, called Run 3, has just started in 2022 and it has been recording pp collision data at 13.6 TeV of center of mass energy, with 80 fb-1 of data collected till the end of July 2023.For my presentation I selected the most recent results produced by CMS from Run2 and Run 3 which are covering the topics of Higgs boson properties, searches for new particles and additional scalars, top quark production and properties, and I am discussing other interesting models e.g. using SM particles as portals to the Dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exercise Responses after Inactivity

The exercise response after bed rest inactivity is a reduction in the physical work capacity and is manifested by significant decreases in oxygen uptake. The magnitude of decrease in maximal oxygen intake V(dot)O2max is related to the duration of confinement and the pre-bed-rest level of aerobic fitness; these relationships are relatively independent of age and gender. The reduced exercise performance and V(dot)O2max following bed rest are associated with various physiological adaptations including reductions in blood volume, submaximal and maximal stroke volume, maximal cardiac output, sceletal muscle tone and strength, and aerobic enzyme capacities, as well as increases in venous compliance and submaximal and maximal heart rate. This reduction in physiological capacity can be partially restored by specific countermeasures that provide regular muscular activity or orhtostatic stress or both during the bed rest exposure. The understanding of these physiological and physical responses to exercise following bed rest inactivity has important implications for the solution to safety and health problems that arise in clinical medicine, aerospace medicine, sedentary living, and aging.

Convertino, Victor A.↗

The relation between quasars’ optical spectra and variability

Abstract Brightness variation is an essential feature of quasars, but its mechanism and relationship to other physical quantities are not understood well. We aimed to find the relationship between the optical variability and spectral features to reveal the regularity behind the random variation. It is known that a quasar’s Fe ii/Hβ flux ratio and equivalent width of [O iii]5007 are negatively correlated; this is called Eigenvector 1. In this work, we visualized the relationship between the position on this Eigenvector 1 (EV1) plane and how the brightness of the quasars had changed after ∼10 yr. We conducted three analyses, using a different quasar sample in each. The first analysis showed the relation between the quasars’ distributions on the EV1 plane and how much they had changed brightness, using 13438 Sloan Digital Sky Survey quasars. This result shows how brightness changes later are clearly related to the position on the EV1 plane. In the second analysis, we plotted the sources reported as “changing-look quasars” (or “changing-state quasars”) on the EV1 plane. This result shows that the position on the EV1 plane corresponds to the activity level of each source, and the bright or dim states of them are distributed on the opposite sides divided by the typical quasar distribution. In the third analysis, we examined the transition vectors on the EV1 plane using sources with multiple-epoch spectra. This result shows that the brightening and dimming sources move on a similar path and they reach a position corresponding to the opposite activity level. We also found this trend is opposite to the empirical rule that $R_{\rm {Fe\, \small {II}}}$ positively correlated with the Eddington ratio, which has been proposed based on the trends of a large number of quasars. From all these analyses, it is indicated that quasars tend to oscillate between both sides of the distribution ridge on the EV1 plane; each of them corresponds to a dim state and a bright state. This trend in optical variation suggests that significant brightness changes, such as changing-look quasars, are expected to repeat.

Astronomy & Astrophysics↗