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At least 649 records · Page 36

Applications of physics informed neural operators

Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .

97 MATHEMATICS AND COMPUTING↗

Frustrated Magnetism in FeGe 3 O 4 with a Chiral Trillium Network

The discovery of new magnetic ground states in geometrically frustrated lattices remains a central challenge in materials science. Here, we report the synthesis, structural characterization, and frustrated magnetic properties of FeGe 3 O 4 , a newly identified compound that crystallizes in the noncentrosymmetric cubic space group P 2 1 3. In this structure, Fe atoms form an intricate double-trillium lattice with nearest-neighbor Fe−Fe distances of ∼4.2 Å, while Ge 2+ ions mediate magnetic interactions through Fe− Ge−Fe pathways. Field-dependent magnetization at 2 K shows a pronounced nonlinearity, reaching a maximum moment of 2.55(3) μ B /Fe 2+ at 70 kOe without evidence of saturation. Magnetic susceptibility, heat capacity, and neutron scattering collectively reveal the onset of short-range magnetic interactions near 5 K, with no longrange ordering detected down to 0.06 K. Specific heat measurements demonstrate strong frustration: only ∼34% of the expected magnetic entropy is recovered at 2.4 K. Taken together, these results establish FeGe 3 O 4 as a rare example of a geometrically frustrated trillium lattice magnet, offering a promising platform for exploring exotic quantum magnetic phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Asymmetric Aircraft Aerodynamics Due to an Experimental Wing Glove

Aerodynamic computational fluid dynamics analysis of a wing glove attached to one wing of a business jet is presented and discussed. A wing glove placed on only one wing will produce asymmetric aerodynamic effects that will result in overall changes in the forces and moments acting on the aircraft. These changes, referred to as deltas, need to be determined and quantified to ensure that the wing glove does not have a significant effect on the aircraft flight characteristics. TRANAIR (Calmar Research Corporation, Cato, New York), a nonlinear full potential solver, and Star-CCM+ (CD-adapco, Melville, New York), a finite volume full Reynolds-averaged Navier-Stokes computational fluid dynamics solver, are used to analyze a full aircraft with and without the glove at a variety of flight conditions, aircraft configurations, and angles of attack and sideslip. Changes in the aircraft lift, drag, and side force along with roll, pitch, and yaw are presented. Span lift and moment distributions are also presented for a more detailed look at the effects of the glove on the aircraft. Aerodynamic flow phenomena due to the addition of the glove are discussed. Results show that the glove produces only small changes in the aerodynamic forces and moments acting on the aircraft, most of which are insignificant.

Hartshorn, Fletcher↗

Visions of visualization aids: Design philosophy and experimental results

Aids for the visualization of high-dimensional scientific or other data must be designed. Simply casting multidimensional data into a two- or three-dimensional spatial metaphor does not guarantee that the presentation will provide insight or parsimonious description of the phenomena underlying the data. Indeed, the communication of the essential meaning of some multidimensional data may be obscured by presentation in a spatially distributed format. Useful visualization is generally based on pre-existing theoretical beliefs concerning the underlying phenomena which guide selection and formatting of the plotted variables. Two examples from chaotic dynamics are used to illustrate how a visulaization may be an aid to insight. Two examples of displays to aid spatial maneuvering are described. The first, a perspective format for a commercial air traffic display, illustrates how geometric distortion may be introduced to insure that an operator can understand a depicted three-dimensional situation. The second, a display for planning small spacecraft maneuvers, illustrates how the complex counterintuitive character of orbital maneuvering may be made more tractable by removing higher-order nonlinear control dynamics, and allowing independent satisfaction of velocity and plume impingement constraints on orbital changes.

Ellis, Stephen R.↗

de Gennes Narrowing and Relationship between Structure and Dynamics in Self-Organized Ion-Beam Nanopatterning

Investigating the relationship between structure and dynamical processes is a central goal in condensed matter physics. Perhaps the most noted relationship between the two is the phenomenon of de Gennes narrowing, in which relaxation times in liquids are proportional to the scattering structure factor. Here, a similar relationship is discovered during the self-organized ion-beam nanopatterning of silicon using coherent x-ray scattering. However, in contrast to the exponential relaxation of fluctuations in classic de Gennes narrowing, the dynamic surface exhibits a wide range of behaviors as a function of the length scale, with a compressed exponential relaxation at lengths corresponding to the dominant structural motif—self-organized nanoscale ripples. These behaviors are reproduced in simulations of a nonlinear model describing the surface evolution. Our team suggests that the compressed exponential behavior observed here is due to the morphological persistence of the self-organized surface ripple patterns which form and evolve during ion-beam nanopatterning.

36 MATERIALS SCIENCE↗

Dynamic modeling of coronal and interplanetary responses to solar events

Recent progress in the dynamic modeling of responses of the corona and interplanetary medium to solar events (such as surges, eruptive prominences, flares, etc.) is reviewed. In particular, coronal transients and wave phenomena are discussed in some detail including pertinent mathematical requirements. Within the context of hydrodynamics and magnetohydrodynamics, a summary of both one- and two-dimensional time-dependent models is presented. A comparison of theoretical results with ground-based optical, radio, ATM Skylab observations, Pioneer 9 and Pioneer 10 solar wind observations is also presented. It is illustrated that: (1) substantial progress has been made in the theoretical (i.e., numerical) modeling of coronal and interplanetary responses within the last few years; (2) two-dimensional, time-dependent modeling is needed to examine the details of nonlinear wave coupling; and (3) theoretical results of modeling appear to reproduce physical consequences successfully.

Wu, S. T.↗

Control of Mixing and Reactive Flow Processes

The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.

Karagozian, A. R.↗

Investigation of the structure of the electromagnetic field and related phenomena, generated by the Active Satellite

The altitude dependencies of the moduli of the electric field E in the VLF and LF frequency bands (f sub B much less than F less than f sub B) and in the altitude range of the ionosphere Z equals (400 to 2500) km up to Z equals 6000 km (the bottom of the magnetosphere) were calculated by the linear theory. The amplitudes of the field have large maxima in four regions: the axis field (E sub o) close to the direction of the Earth's magnetic field line B sub o, beta approximately 0 degrees, the fields (E sub St), (E sub RevSt) and (E sub Res) in the Storey, Reversed Story and Resonance cones, beta approximately (0 approaches 20) degrees. Their maxima are very pronounced close to the low hybrid frequency F sub L. The nonlinear heating of the magnetoplasma under the action of an electric field Ee (sup iwt) was recently expanded by the macroscopic theory by the author. The velocities, collision frequencies and temperatures of all the constituents of a magnetoplasma - electrons, ions, and neutral particles - are taken into account. Formulae and numerical results are presented for the ionosphere in the frequency band F equals (1 to 10 exp 4) kHz and altitude range Z approximately (100 - 1000) km. Some results of calculations by the self consistent solution of the basis system of equations are also discussed.

Alpert, Yakov L.↗

Higher harmonics in planar Hall effect induced by cluster magnetic multipoles

Antiferromagnetic (AFM) materials are attracting tremendous attention due to their spintronic applications and associated novel topological phenomena. However, detecting and identifying the spin configurations in AFM materials are quite challenging due to the absence of net magnetization. Herein, we report the practicality of utilizing the planar Hall effect (PHE) to detect and distinguish “cluster magnetic multipoles” in AFM Nd 2 Ir 2 O 7 (NIO-227) fully strained films. By imposing compressive strain on the spin structure of NIO-227, we artificially induced cluster magnetic multipoles, namely dipoles and A 2 - and T 1 -octupoles. Importantly, under magnetic field rotation, each magnetic multipole exhibits distinctive harmonics of the PHE oscillation. Moreover, the planar Hall conductivity has a nonlinear magnetic field dependence, which can be attributed to the magnetic response of the cluster magnetic octupoles. Our work provides a strategy for identifying cluster magnetic multipoles in AFM systems and would promote octupole-based AFM spintronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Observed Scaling Behavior of Snow and Soil Moisture Signatures from the CLPX and NAFE Campaigns

Seasonal snow and soil moisture (SM) are important elements of the Earth's water cycle, acting as storage elements and by modulating water and energy exchanges between the land surface and the atmosphere and space. Accurate estimates of snow water equivalent (SWE) and SM also play an important role in weather and climate models over a range of scales. There are many advantages for the retrieval of snow parameters using passive microwave sensors. However, the current scale mismatch between many high-resolution applications and available satellite snow sensor footprints (approx.25km) presents challenges. There is also a scale mismatch for planned L-band soil moisture satellite measurements with their large (50-100 km) passive microwave footprints. Combined radiometer-radar schemes are being explored as possible aids, but this is still an area of ongoing research. Retrieval accuracies are limited in part by complex, and potentially nonlinear relationships between SWE or SM and microwave emission signatures. We will use airborne and satellite observations from two field campaigns to examine the scaling behavior of brightness temperatures and SWE and SM across scales from 100 meters to 10's of kilometers. The results will provide examples of the appropriate spatial sampling scales for new sensors, and guidance for downscaling schemes. The two campaigns are NASA's Cold Land Processes Experiment- 1 (CLPX- 1 : Colorado, 2002 & 2003), and the Australian National Airborne Field Experiment (NAFE, Nov, 2005). The analyses will also illustrate the roles and spatial scales of the underlying phenomena (e.g., vegetation, topography) that control subpixel heterogeneity.

Kim, Edward J.↗

Heat and mass transfer in porous media phase separation at temperatures below the lambda-point of He-4

Newtonian fluid motion, coupled to heat transfer via latent heat of phase transition, is well known from numerous studies of condensation and boiling. Considerably less knowledge is available for vapor-liquid phase separation in the absence of gravity effect on the transport phenomena. The present studies are focused on heat and mass transfer associated with vapor-liquid phase separation required for long-term storage of the cryogen liquid He II in space vessels. Though space conditions are the dominant mode of interest in advanced equipment, e.g. IR telescopes, the systems may be operated in principle during terrestrial conditions. The latter are considered in the present work. It emphasizes the linear regime including an extrapolation based on variable thermophysical properties. Data taken with a phase separation approach show departures from the linear regime prediction. They agree with a transport equation proposed for the nonlinear, turbulent regime.

Yuan, S. W. K.↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical studies of electron dynamics in oblique quasi-perpendicular collisionless shock waves

Linear and nonlinear electron damping of the whistler precursor wave train to low Mach number quasi-perpendicular oblique shocks is studied using a one-dimensional electromagnetic plasma simulation code with particle electrons and ions. In some parameter regimes, electrons are observed to trap along the magnetic field lines in the potential of the whistler precursor wave train. This trapping can lead to significant electron heating in front of the shock for low beta(e). Use of a 64-processor hypercube concurrent computer has enabled long runs using realistic mass ratios in the full particle in-cell code and thus simulate shock parameter regimes and phenomena not previously studied numerically.

Liewer, P. C.↗

Use of GTE, Mozaic, Sonex, and UARS-MLS Data in Understanding Tropospheric Processes Critical to Model Development

During the first year we focused on the analysis of data collected on over 7600 commercial aircraft flights (the MOZAIC program). The aim was to further our understanding of the fundamental dynamical processes that drive mesoscale phenomena in the upper troposphere and lower stratosphere, and their effects on the advection of passive scalars. Through these studies we made the following findings. 2001]: We derived the Kolmogorov equation for the third-order velocity structure function on an f-plane. We showed how the sign of the function yields the direction of the energy cascade. The remarkable linearity of the measured off diagonal third-order structure function was studied. We suggested that the Coriolis term, which appears explicitly in this equation, may be crucial in understanding the observed kinetic energy spectra at scales larger than 100 km, instead of the nonlinear advection term as previously assumed. Also, we showed that decreases with latitude for mid- to high-latitudes, and tabulated the values. Ozone concentration structure functions were calculated by restricting the data points to approximately isentropic pairings. In this way we were able to make comparisons with scalar advection theories. We found that, at even the largest scales, there was no evidence for the simple scaling predicted for smooth advection/diffusion.

Newell, Reginald E.↗

Efficient data-driven regression for reduced-order modeling of spatial pattern formation

We present an efficient data-driven regression approach for constructing reduced-order models (ROMs) of reaction-diffusion systems exhibiting pattern formation. The ROMs are learned non-intrusively from available training data of physically accurate numerical simulations. The method can be applied to general nonlinear systems through the use of polynomial model form, while not requiring knowledge of the underlying physical model, governing equations, or numerical solvers. The process of learning ROMs is posed as a low-cost least-squares problem in a reduced-order subspace identified via Proper Orthogonal Decomposition (POD). Numerical experiments on classical pattern-forming systems–including the Schnakenberg and Mimura–Tsujikawa models–demonstrate that higher-order surrogate models significantly improve prediction accuracy while maintaining low computational cost. The proposed method provides a flexible, non-intrusive model reduction framework, well suited for the analysis of complex spatio-temporal pattern formation phenomena.

Data-driven modeling↗

A Low Order and a High Order Solution for a Converging-Diverging Nozzle Problem

The Computational Aeroacoustics Workshops on Benchmark problems are conducted in order to generate solutions with a variety of methods for problems that are chosen both to be representative of significant and relevant acoustic phenomena. It is generally recognized that CAA applications require the resolution in time and in space of solution details over a significantly broader range of scales than typical computational fluid dynamics applications. These requirements are forcing the development of new methodologies for CAA applications. This paper presents numerical results from a third and a seventh order algorithm for the propagation of an acoustic signal through a converging-diverging nozzle. These two algorithms are members of a new family of high accuracy methods that have the same order accuracy in both space and time, and are an extension of previous work for linearized Euler equations to fully nonlinear time dependent problems. The simulations are all with the fully nonlinear quasi-1D Euler equations for the total solution, which includes both the fluid dynamics and the acoustics. The acoustic solution is obtained from the time dependent nonlinear solution by subtracting the steady solution.

Goodrich, John W.↗

Experimental and Computational Analysis of Unidirectional Flow Through Stirling Engine Heater Head

A high efficiency Stirling Radioisotope Generator (SRG) is being developed for possible use in long-duration space science missions. NASA s advanced technology goals for next generation Stirling convertors include increasing the Carnot efficiency and percent of Carnot efficiency. To help achieve these goals, a multi-dimensional Computational Fluid Dynamics (CFD) code is being developed to numerically model unsteady fluid flow and heat transfer phenomena of the oscillating working gas inside Stirling convertors. In the absence of transient pressure drop data for the zero mean oscillating multi-dimensional flows present in the Technology Demonstration Convertors on test at NASA Glenn Research Center, unidirectional flow pressure drop test data is used to compare against 2D and 3D computational solutions. This study focuses on tracking pressure drop and mass flow rate data for unidirectional flow though a Stirling heater head using a commercial CFD code (CFD-ACE). The commercial CFD code uses a porous-media model which is dependent on permeability and the inertial coefficient present in the linear and nonlinear terms of the Darcy-Forchheimer equation. Permeability and inertial coefficient were calculated from unidirectional flow test data. CFD simulations of the unidirectional flow test were validated using the porous-media model input parameters which increased simulation accuracy by 14 percent on average.

Wilson, Scott D.↗