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At least 1,513 records · Page 84

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗

The electroweak phase transition in the Inert Doublet Model

We study the strength of a first-order electroweak phase transition in the Inert Doublet Model (IDM), where particle dark matter (DM) is comprised of the lightest neutral inert Higgs boson. We improve over previous studies in the description and treatment of the finite-temperature effective potential and of the electroweak phase transition. We focus on a set of benchmark models inspired by the key mechanisms in the IDM leading to a viable dark matter particle candidate, and illustrate how to enhance the strength of the electroweak phase transition by adjusting the masses of the yet undiscovered IDM Higgs states. We argue that across a variety of DM masses, obtaining a strong enough first-order phase transition is a generic possibility in the IDM. We find that due to direct dark matter searches and collider constraints, a sufficiently strong transition and a thermal relic density matching the universal DM abundance is possible only in the Higgs funnel regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Use of a Reduced Order Model (ROM) to Simulate SOFC Performance in System Models

Numerical models for design and optimization of fuel cell-based power generation systems require an accurate representation of the SOFC stack performance over a wide range of operating conditions. Response surface techniques were used with detailed SOFC stack model results to create a computationally efficient reduced order model (ROM) of the stack that retains desirable information about its internal state, which can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall reliability. A tool was developed to randomly sample selected input parameters, obtain stack solutions for these sampled cases, perform regression to obtain response surfaces for stack performance and other metrics of interest, and export the response surfaces as a ROM. The ROM was then successfully implemented in an Aspen Plus® system model for a natural gas fuel cell (NGFC) power system. Additional work to characterize the ROM’s approximation error is ongoing.

Modeling & Simulation↗

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗

System Advisor Model: Flat Plate Photovoltaic Performance Modeling Validation Report

The System Advisor Model (SAM) is a free software tool that performs detailed analysis of both system performance and system financing for a variety of renewable energy technologies. This report provides detailed validation of the SAM flat plate photovoltaic performance model by comparing SAM-modeled PV system generation data to actual measured production data for nine PV systems ranging from 75 kW to greater than 25 MW in size. The results show strong agreement between SAM predictions and field data, with annualized prediction error below 3% for all fixed tilt cases and below 8% for all one axis tracked cases. The analysis concludes that snow cover and system outages are the primary sources of disagreement, and other deviations resulting from seasonal biases in the irradiation models and one axis tracking issues are discussed in detail.

14 SOLAR ENERGY↗

Predicting the severity of spurious “double ITCZ” problem in CMIP5 coupled models from AMIP simulations [Tropical versus extratropical origins of the spurious 'double ITCZ' in coupled climate models]

The severity of the double Intertropical Convergence Zone (DI) problem in climate models can be measured by a tropical precipitation asymmetry index (PAI), indicating whether tropical precipitation favors the Northern Hemisphere or the Southern Hemisphere. Examination of 19 Coupled Model Intercomparison Project phase 5 models reveals that the PAI is tightly linked to the tropical sea surface temperature (SST) bias. As one of the factors determining the SST bias, the asymmetry of tropical net surface heat flux in Atmospheric Model Intercomparison Project (AMIP) simulations is identified as a skillful predictor of the PAI change from an AMIP to a coupled simulation, with an intermodel correlation of 0.90. Using tropical top-of-atmosphere (TOA) fluxes, the correlations are lower but still strong. However, the extratropical asymmetries of surface and TOA fluxes in AMIP simulations cannot serve as useful predictors of the PAI change. Furthermore, this study suggests that the largest source of the DI bias is from the tropics and from atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

Interface and embedded joint methods for modeling dynamic fracture opening by explosive products [Two methods for modeling dynamic fracture opening by explosive products]

Two computational approaches are proposed in the paper to model dynamic fracture opening by explosive products. The first method assumes that the fractures may be modeled using flow elements embedded along the mesh lines. This method models crack opening in a straightforward way by splitting the nodes of the computational grid. It can account for crack branching; however, the crack directions are constrained by existing mesh faces, which may lead to mesh dependence. Also, the stress in flow elements is calculated explicitly separate from the surrounding solid elements that can impose additional limits on the time step stability condition for explicit integration. The second approach uses embedded flow elements to model the cracks. Typical thickness of the cracks is much smaller than the element size. Therefore, gas pressure in the cracks is assumed to be in stress equilibrium with the element stress. To achieve this, the crack thickness and the state of the gas is updated simultaneously with the state of the solid element which contains the crack. Therefore, the time step is controlled by the explicit solver applied for the solid and does not depend on the thickness of the crack. In conclusion, the main disadvantage of the second approach is due to the complexity of modeling multiple intersecting cracks, which go through the same element. We discuss the areas of possible applications of these 2 methods and the ways to improve and enhance them for future practical applications.

58 GEOSCIENCES↗

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗

Constraints on mediator-based dark matter and scalar dark energy models using $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS detector

Constraints on selected mediator-based dark matter models and a scalar dark energy model using up to 37 fb ₋1 $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS detector at the LHC during 2015-2016 are summarised in this paper. The conclusions of experimental searches in a variety of final states are interpreted in terms of a set of spin-1 and spin-0 single-mediator dark matter simplified models and a second set of models involving an extended Higgs sector plus an additional vector or pseudo-scalar mediator. The searches considered in this paper constrain spin-1 leptophobic and leptophilic mediators, spin-0 colour-neutral and colour-charged mediators and vector or pseudo-scalar mediators embedded in extended Higgs sector models. In this case, also $\sqrt{s}$ = 8 TeV pp collision data are used for the interpretation of the results. The results are also interpreted for the first time in terms of light scalar particles that could contribute to the accelerating expansion of the universe (dark energy).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental determination of lead carbonate solubility at high ionic strengths: A Pitzer model description

In this article, solubility measurements of lead carbonate, PbCO 3 (cr), cerussite, as a function of total ionic strengths are conducted in the mixtures of NaCl and NaHCO 3 up to I = 1.2 mol•kg –1 and in the mixtures of NaHCO 3 and Na 2 CO 3 up to I = 5.2 mol•kg –1 , at room temperature (22.5 ± 0.5 °C). The solubility constant (log K sp ) for cerussite, PbCO 3 (cr) = Pb 2+ + CO 3 2- was determined as –13.76 ± 0.15 (2σ) with a set of Pitzer parameters describing the specific interactions of PbCO 3 (aq), Pb(CO 3 ) 2 2- , and Pb(CO 3 )Cl – with the bulk-supporting electrolytes, based on the Pitzer model. The model developed in this work can reproduce the experimental results including model-independent solubility values from the literature over a wide range of ionic strengths with satisfactory accuracy. The model is expected to find applications in numerous fields, including the accurate description of chemical behavior of lead in geological repositories, the modeling of formation of oxidized Pb–Zn ore deposits, and the environmental remediation of lead contamination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Balancing global water availability and use at basin scale in an integrated assessment model

Water is essential for the world’s food supply, for energy production, including bioenergy and hydroelectric power, and for power system cooling. Water is already scarce in many regions of the world and could present a critical constraint as society attempts simultaneously to mitigate climate forcing and adapt to climate change, and to provide for a larger and more prosperous human population. Numerous studies have pointed to growing pressures on the world’s scarce fresh water resources from population and economic growth, and climate change. This study goes further. We use the Global Change Assessment Model to analyze interactions between population, economic growth, energy, land and water resources simultaneously in a dynamically evolving system where competing claims on water resources from all claimants—energy, land, and economy—are reconciled with water resource availability—from renewable water, non-renewable groundwater sources and desalinated water—across 14 geopolitical regions, 151 agriculture-ecological zones, and 235 major river basins. We find that previous estimates of global water withdrawal projections are overestimated. Model simulations show that it is more economical in some basins to alter agricultural and energy activities rather than utilize non-renewable groundwater or desalinated water. This study highlights the importance of accounting for water as a binding factor in agriculture, energy and land use decisions in IAMs and implications for global responses to water scarcity, particularly in the trade of agricultural commodities and land-use decisions.

basin↗

Multiphase Resistivity Model for Magnetic Nanocomposites Developed for High Frequency, High Power Transformation

New power conversion systems that offer promise to transform electricity grids into unified interactive supply networks require high-resistivity soft-magnetic materials to allow for switching of magnetic materials at frequencies approaching 100 kHz for power transformation in the megawatt range. Amorphous and nanocomposite soft-magnetic materials, which represent the state of the art in terms of high power densities and low losses at high frequencies, have resistivities that depend on the structures and spatial distributions of multiple phases in thin ribbons. We present a multiphase resistivity model applicable to nanocomposite materials by considering an equivalent circuit approach considering paths through an amorphous, crystalline, and growth inhibitor shell phase. We detail: (a) identification of amorphous, crystalline, and shell phases; (b) consideration of the role of the morphology of each phase in an equivalent circuit model for the resistance; (c) a two-band model for the Fe/Co composition dependence of the resistivity in crystalline and amorphous phases; (d) a virtual bound state model for resistivity to explain increased resistivity due to early transition-metal growth inhibitors in the shell surrounding the nanocrystalline phase; and (e) disorder effects on amorphous phase resistivity. Experimental design and results for systems of interest in high-frequency power transformation are discussed in the context of our model including: (a) techniques for measurements of cross-section and density, (b) four-point probe and surface resistivity measurements, and (c) measurements in Fe- and Co-rich systems comparing amorphous and nanocomposite materials.

DeGeorge, V↗

Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation

This paper provides projections of water withdrawals and consumption for electricity generation in India through 2050. Based on the results from five energy-economic modeling teams, the paper explores the implications of economic growth, power plant cooling policies, and electricity CO2 emissions reductions on water withdrawals and consumption. To isolate modeling differences, the five teams used harmonized assumptions regarding economic and population growth, the distribution of power plants by cooling technologies, and withdrawals and consumption intensities. The results demonstrate the different but potentially complementary implications of cooling technology policies and efforts to reduce CO2 emissions. The application of closed-loop cooling technologies substantially reduces water withdrawals but increases consumption. The water implications of CO2 emissions reductions, depend critically on the approach to these reductions. Focusing on wind and solar power reduces consumption and withdrawals; a focus on nuclear power increases both; and a focus on hydroelectric power could increase consumptive losses through evaporation.

electricity generation↗