A Pragmatic Approach to Greater Integration of Modeling and Simulation Into Certification Activities Related to Advanced Manufacturing
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Douglas N Wells↗
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nPINNs: Nonlocal physics-informed neural networks for a parametrized nonlocal universal Laplacian operator. Algorithms and applications
Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius $\delta$ goes to zero, and to the fractional Laplacian as $\delta$ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We also provide theoretical convergence rates with respect to $\delta$ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, $\delta$ and $\alpha$, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order $\alpha(y)$, which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as $\delta$. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.
97 MATHEMATICS AND COMPUTING↗
Identification of Performance Shaping Factor Lag and Linger Effects for Dynamic Human Reliability Analysis: Application of Experimental Data
Many researchers have emphasized the importance of dynamic probabilistic safety assessment (PSA), which highlights the necessity of studies for dynamic human reliability analysis (HRA). Dynamic HRA concentrates on a dynamic account of human actions or how performance shaping factors (PSFs) can dynamically modify the human error probability (HEP) over time. In contrast, existing static HRA does not consider human actions as changes over time or event progressions. Accordingly, previous research on dynamic HRA conceptually suggested PSF lag and linger effects to treat dependence between operator actions in dynamic HRA versus existing approaches. As follow-up research, this study attempted to identify PSF lag and linger effects for dynamic HRA on the basis of experimental data. Firstly, mathematical models for PSF lag and linger effects were developed based on a literature survey in the field of biology. Secondly, we analyzed experimental scenarios from a control room study to identify operator actions considered in PSA. Lastly, based on the experimental data, the effect of the stress PSF with lag and linger effects was compared to that without PSF lag and linger effects. This paper concludes with an overall discussion of PSF lag and linger effects based on the relation between the stress PSF and error occurrence.
99 GENERAL AND MISCELLANEOUS↗
Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3
Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.
Source record↗
Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NO x emissions over South Korea
This study constrains NO x emissions by utilizing mass balance–based inverse modeling methods and examines the optimization of inverse modeling conditions through a pseudo-observation test for South Korea, which has complex topography. Here, we applied mass balance–based inverse modeling methods such as Basic Mass Balance (BMB), Finite Difference Mass Balance (FDMB), and Iterative Finite Difference Mass Balance (IFDMB). We performed a numerical simulation of air quality using the Community Multi-scale Air Quality (CMAQ) model to calculate the NO 2 column density required for the inverse modeling. The pseudo-observation test was performed according to season, modeling resolution, and regridding methodology of satellite observation data to identify various conditions while applying the inverse modeling for South Korea. Comparing the inverse modeling results from the BMB, FDMB, and IFDMB methods, IFDMB was the most effective method in constraining NO x emissions in the South Korean region since it minimized smearing effects (i.e., transport-induced errors) through iterative calculations. The accuracy of the constrained NO x emissions using mass balance–based inversions in South Korea was the highest in the summer due to the minimized smearing effects, and the 9 km resolution modeling was the most efficient for inverse modeling of the region. In addition, the results of inverse modeling varied depending on the regridding methods, implying the importance of using a suitable regridding method and modeling resolution. This study used pseudo-observations, but the inversions are expected to be applied based on actual satellite data in the future.
54 ENVIRONMENTAL SCIENCES↗
Regional Earthquake Ground Motion Simulations for Southern California With EQSIM: Insights From the 2008 Chino Hills, 2024 Highland Park, and 2021 Carson Earthquakes
This study presents physics-based, 3D simulations using the EQSIM framework for several earthquakes in the Los Angeles region. The primary objective was to assess the ability of deterministic physics-based ground motion simulations to reproduce the observed motions from historical events. The selected events included the mathematical equation M w 5.4 2008 Chino Hills, the mathematical equation M w 4.4 2024 Highland Park, and the mathematical equation M w 4.3 2021 Carson events. The simulated motions were evaluated by comparing the recorded and simulated seismograms, as well as the Fourier amplitude spectra, across multiple seismic stations. The SCEC 3D velocity model, CVM-S4.26.M01, was used to represent the regional geology, and ground motion simulations were carried out with a resolution of up to 5 Hz. The results indicate that the simulated motions captured the recorded motions up to approximately 4 Hz. While careful iterations regarding source parameters and corner frequencies were required, and, for the case of the Highland Park event, some of the near-source stations had relatively low accuracy, the present study established a positive step toward the utilization of physics-based simulations in practical applications. The computational efficiencies exhibited by EQSIM, especially on GPU clusters, further supported this assertion, as wall-clock times of simulations involving more than 10 billion grid points were as low as mathematical equation minutes. This permits ensemble simulations for a considered scenario event so that modeling uncertainties (e.g., source and geology) can be bracketed.
EQSIM↗
Yellowstone Ecological Forecasting: Assessing Change in Aspen Extent in Northern Yellowstone National Park
The removal and reintroduction of the gray wolf (Canis lupus) in Yellowstone National Park have shaped the ecological composition of this distinct landscape, representing a textbook example of trophic dynamics. With particular importance to conservation science, researchers have studied the trophic cascades between wolves and species such as elk (Cervus canadensis) and quaking aspen (Populus tremuloides). In conjunction with the National Park Service, Yellowstone National Park, Utah State University, and the University of Wisconsin–Stevens Point, this project utilized satellite remote sensing to investigate the long-term trends in aspen extent. Through random forest modeling and phenological approaches, Landsat 5 Thematic Mapper (TM; years 1986–2011) and Sentinel-2 Multispectral Instrument (MSI; years 2017–2019) datasets were used to derive color composites, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Tasseled Cap Indices (Brightness, Greenness, Wetness). The International Space System (ISS) Global Ecosystem Dynamics Investigation (GEDI) provided canopy height data. The team consolidated results into maps and time-series which provide an in-depth depiction of aspen stand extent. The National Park Service will use these end products to assist in its management practices and inform wildlife restoration decisions within and beyond Yellowstone National Park.
Kyle Steen↗
Prediction of softening kinetics and recrystallization texture in non-isothermally annealed bulged tubes using CPFEM and CA models
A hierarchically coupled cellular automata (CA) model, crystal plasticity finite element method (CPFEM), and thermal finite element (FE) model is developed to predict the softening kinetics of the bulged steel tube during non-isothermal annealing. Through the developed model, the kinetics of softening mechanisms including static recovery (SRV) and static recrystallization (SRX), as well as the recrystallization texture are predicted. Later, the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model based on the predicted SRX data is developed to interpret the recrystallization behavior of the material. To perform this study, diverse experimental tests including tube hydroforming (THF), annealing, uniaxial tensile test, hardness test, as well as microstructure observations through optical microscopy and Electron Backscatter Diffraction (EBSD) tests on steel tube are performed. The obtained experimental data are utilized to calibrate and verify the implemented CPFEM model for simulation of THF process, thermal FE model for prediction of the local temperature over annealing time, and CA algorithm for modeling of the softening kinetics and texture evolution throughout the annealing process. The study shows that the predicted deformation characteristics, softening kinetics, recrystallization texture and temperature profile during non-isothermal annealing are in good agreement with experimental data. During the annealing process, a total of four stages for the kinetics of softening mechanisms is observed: No softening; SRV only; SRV dominant; and SRX dominant. During the progress of SRX, the behavior of recrystallization is abruptly changed, confirming that two different mechanisms are controlling the kinetics of transformation.
36 MATERIALS SCIENCE↗
The Dynamic Temperate and Boreal Fire and Forest-Ecosystem Simulator (DYNAFFOREST): Development and evaluation
Not Available
54 ENVIRONMENTAL SCIENCES↗
Parallel-in-Time Power System Simulation Using a Differential Transformation Based Adaptive Parareal Method
Not Available
42 ENGINEERING↗
Collisional Excitation and Non-LTE Modeling of Interstellar Chiral Propylene Oxide
Abstract The first set of theoretical rotational cross sections for propylene oxide (CH 3 CHCH 2 O) colliding with cold He atoms has been obtained at the full quantum level using a high-accuracy potential energy surface. By scaling the collision reduced mass, rotational rate coefficients for collisions with para-H 2 are deduced in the temperature range 5–30 K. These collisional coefficients are combined with radiative data in a non-LTE radiative transfer model in order to reproduce observations of propylene oxide made toward the Sagittarius B2(N) molecular cloud with the Green Bank and Parkes radio telescopes. The three detected absorption lines are found to probe the cold (∼10 K) and translucent ( n H ∼ 2000 cm −3 ) gas in the outer edges of the extended Sgr B2(N) envelope. The derived column density for propylene oxide is N tot ∼ 3 × 10 12 cm −2 , corresponding to a fractional abundance relative to total hydrogen of ∼2.5 × 10 −11 . The present results are expected to help our understanding of the chemistry of propylene oxide, including a potential enantiomeric excess, in the cold interstellar medium.
79 ASTRONOMY AND ASTROPHYSICS↗
Quantum speed limit for the out-of-time-ordered correlator from an open-system perspective
Scrambling, the delocalization of initially localized quantum information, is commonly characterized by the out-of-time-ordered correlator (OTOC). Employing the OTOC–Renyi-2 entropy theorem, we derive a quantum speed limit for the OTOC, which sets a lower bound for the rate with which information can be scrambled. This bound becomes particularly tractable by describing the scrambling of information in a closed quantum system as an effective decoherence process of an open system interacting with an environment. We prove that decay of the OTOC can be bounded by the strength of the system-environment coupling and two-point environmental correlation functions. We validate our analytic bound numerically using the nonintegrable transverse field Ising model. Furthermore, our results provide a universal and model-agnostic quantitative framework for understanding the dynamical limits of information spreading across quantum many-body physics, condensed matter systems, and engineered quantum platforms.
Fermions↗
Dynamic modeling of near isothermal compressor for Transcritical carbon dioxide cycle to support efficiency improvement
Compressors are the primary components of energy consumption in vapor compression systems, drawing considerable research effort to reduce carbon emissions and improve energy efficiency. This work presents an isothermal compressor that integrates the compression chamber with the gas cooler to achieve near-isothermal compression, resulting in up to 30% energy reduction compared to traditional isentropic compression, according to the experiment results. A detailed dynamic model for the isothermal compression cycle of carbon dioxide (CO 2 ) is first presented, coupled with a liquid-piston model for chamber design. The model is experimentally validated on a 3.5 kW prototype, yielding a 6.2% relative error in chamber pressure and a 0.5 K deviation in chamber temperature. The liquid piston exhibits reduced frictional heating and geometric adaptability relative to the mechanical piston. Leveraging these attributes, the study further evaluates approaches that enhance the heat transfer to achieve isothermal compression by increasing the effective heat transfer area during compression. As a result, simulations demonstrated up to a 5% improvement in the coefficient of performance over the baseline case through chamber design, providing guidelines for design of isothermal compression cycle.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Feldspathic Meteorites MIL 090034 and 090070: Late Additions to the Lunar Crust
Our studies of the Miller Range lunar meteorites MIL 090034, 090036, and 090070 show them to be a diverse suite of rocks from the lunar highlands hereafter referred to as MIL 34, MIL 36, and MIL 70, resp. MIL34 and MIL70, the focus of this work, are crystalline melt breccias. Plagioclase compositions in both peak sharply around An96-97. Mg numbers of olivine vary from 58-65 with a few higher values. MIL36 is a regolith breccia. MIL 34 and MIL 70 have some of the highest Al2O3 abundances of lunar highland meteorites, indicating that they have among the largest modal abundances of plagioclase for lunar meteorites. They have lower Sc and Cr abundances than nearly all lunar highland meteorites except Dho 081, Dho 489 and Dho 733. MIL34 and MIL70 also have similar cosmic ray exposure (CRE) ages of approximately 1-2 Ma indicating they are launch paired. (MIL36 has a larger CRE age approximately greater than 70 Ma). Park et al. found a variation in Ar-Ar ages among subsamples of MIL 34 and MIL70, but preferred ages of 3500+/-110 Ma for the "Dark" phase of MIL 34 anorthite and 3520+/-30 Ma for the "Light" phase of MIL70. Bouvier et al. reported a Pb-Pb age of 3894+/-39 Ma for a feldspathic clast of MIL 34 and a similar age for a melt lithology. Here we reexamine the Rb-Sr and Sm-Nd isotopic data, which show complexities qualitatively consistent with those of the Ar-Ar and Pb-Pb data. The Sm-Nd data in particular suggest that the feldspathic compositions of MIL 34 and MIL 70 formed during initial lunar geochemical differentiation, and REE modeling suggests a relatively late-stage formation.
Nyquist, L. E.↗
Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0
The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual’s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.
Lazarus, Jessica↗
Towards quantum black hole microstates
Abstract We study the cohomology of local BPS operators in$$ \mathcal{N} $$ N = 4 Yang-Mills theory. The finiteNcohomologies consist of the graviton part (subject to the stringy exclusion principle) and the rest which may describe black hole microstates in quantum AdS/CFT. We construct an infinite tower of non-graviton cohomologies in the SU(2) theory and study to what extent they simulate quantum black holes. We find signals for partial no-hair behaviors by showing that certain gravitons are forbidden to dress these cohomologies. This is in qualitative agreement with the perturbative hairs allowed around black holes, which also leads us to a natural setup to construct hairy BPS black holes. The cohomologies are simpler to study in the BMN matrix model truncation of the classical field theory.
Physics↗
A decade of insights: Delving into calendar aging trends and implications
Lithium-ion batteries remain at rest for extended periods and experience calendar aging. Although lithium-ion batteries are expected to perform for over 10 years at room temperature, long-term calendar aging data are seldom reported over such timescales. We present a dataset from 232 commercial cells across eight cell types and five manufacturers that underwent calendar aging across various temperatures and states of charge (SOCs) for up to 13 years. We analyze calendar aging across these conditions by tracking capacity loss and resistance growth as the cells degrade. This dataset is used to validate simple models, primarily the Arrhenius law and the power law, which explain the temperature and storage time on calendar aging. Certain applications of Arrhenius and power law fail to describe the dependence of capacity loss on temperature and resistance growth on storage time. Through this dataset, we demonstrate the complexity of calendar aging and the challenges in reducing trends into phenomenological models.
25 ENERGY STORAGE↗
Emergence of the isotropic Kitaev honeycomb lattice $α$–RuCl 3 and its magnetic properties
Here, we present a comprehensive investigation of the crystal and magnetic structures of the van der Waals antiferromagnet $α$–RuCl 3 using single crystal x-ray and neutron diffraction. The crystal structure at room temperature is a monoclinic (C2/m). However, with decreasing temperature, a remarkable first-order structural phase transition is observed, leading to the emergence of a rhombohedral ($R\bar3$) structure characterized by three-fold rotational symmetry forming an isotropic honeycomb lattice. On further cooling, a zigzag-type antiferromagnetic order develops below $T_{\textrm{N}} = 6\sim6.6$ K. The critical exponent of the magnetic order parameter was determined to be $\beta = 0.11(1)$, which is close to the two-dimensional Ising model. Additionally, the angular dependence of the magnetic critical field of the zigzag antiferromagnetic order for the polarized ferromagnetic phase reveals a six-fold rotational symmetry within the ab–plane. These findings reflect the symmetry associated with the Ising-like bond-dependent Kitaev spin interactions and underscore the universality of the Kitaev interaction-dominated antiferromagnetic system.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗