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At least 685 records · Page 38

Excitation dynamics in galvanically coupled fluxonium circuits

We propose a near-term quantum simulator based on the fluxonium qubits galvanically coupled to form a chain. This system provides long coherence time, large anharmonicity, and strong coupling, making it suitable to study strongly interacting Ising spin models. At half-flux quantum sweet spot, the system is described by the transverse field Ising model (TFIM). We evaluate the propagation of qubit excitations through the system. As disorder increases, the excitations become localized. A single qubit measurement using the circuit QED methods is sufficient to identify localization transition without introducing tunable couplers. We argue that galvanically coupled fluxoniums provide opportunities to study localization and many-body effects in highly coherent quantum systems.

Ozguler, A. Baris↗

On a simplified solution of climate-carbon dynamics in idealized flat10MIP simulations

Abstract. Idealized experiments with coupled climate-carbon Earth system models (ESMs) provide a basis for understanding the response of the carbon cycle to external forcing and for quantifying climate-carbon feedbacks. Here, we analyze globally-averaged results from idealized esm-flat10 experiments and show that most models exhibit a quasi-linear relationship between cumulative carbon uptake on land and in the ocean during a period of constant fossil fuel emissions of 10 Pg C yr−1. We hypothesize that this relationship does not depend on emission pathways. Further, as a simplification, we quantify the relationship between cumulative ocean carbon uptake and changes in ocean heat content using a linear approximation. In this way, changes in oceanic heat content and atmospheric CO2 concentration become interdependent variables, reducing the coupled temperature-CO2 system to just one differential equation. The equation can be solved analytically or numerically for the atmospheric CO2 concentration as a function of fossil fuel emissions. This approach leads to a simplified description of global carbon and climate dynamics, which could be used for applications beyond existing analytical frameworks.

Brovkin, Victor↗

Excitation dynamics in inductively coupled fluxonium circuits

We propose a near-term quantum simulator based on the fluxonium qubits inductively coupled to form a chain. This system provides long coherence time, large anharmonicity, and strong coupling, making it suitable to study Ising spin models. At the half-flux quantum sweet spot, the system is described by the transverse field Ising model (TFIM). We evaluate the propagation of qubit excitations through the system. As disorder increases, the excitations become localized. A single qubit measurement using the circuit QED methods is sufficient to identify localization transition without introducing tunable couplers. We argue that inductively coupled fluxoniums provide opportunities to study localization and many-body effects in highly coherent quantum systems.

Barış Özgüler, A.↗

A conservative discontinuous-Galerkin-in-time (DGiT) multirate time integration framework for interface-coupled problems with applications to solid–solid interaction and air–sea models

In this paper we extend the DGiT multirate framework, developed in Connors and Sockwell (2022) for scalar transmission problems, to a solid–solid interaction (SSI) problem involving two coupled elastic solids and a coupled air–sea model with the rotating, thermal shallow water equations. In so doing we aim to demonstrate the broad applicability of the mathematical theory and governing principles established in Connors and Sockwell (2022) to coupled problems characterized by subproblems evolving at different temporal scales. Further, multirate time integration algorithms employing different time steps, optimized for the dynamics of each subproblem, can significantly improve simulation efficiency for such coupled problems. However, development of multirate algorithms is a highly non-trivial task due to the coupling, which can impact accuracy, stability or other desired properties such as preservation of system invariants. DGiT provides a general template for multirate time integration that can achieve these properties. To elucidate the manner in which DGiT accomplishes this task, we fully detail each step in the application of the framework to the SSI and air–sea coupled problems. Numerical examples illustrate key properties of the resulting multirate schemes for both problems.

42 ENGINEERING↗

Leveraging on-shell interference to search for FCNCs of the top quark and the Z boson

Abstract Flavour-changing-neutral currents (FCNCs) involving the top quark are highly suppressed within the Standard Model (SM). Hence, any signal in current or planned future collider experiments would constitute a clear manifestation of physics beyond the SM. We propose a novel, interference-based strategy to search for top-quark FCNCs involving the Z boson that has the potential to complement traditional search strategies due to a more favourable luminosity scaling. The strategy leverages on-shell interference between the FCNC and SM decay of the top quark into hadronic final states. We estimate the feasibility of the most promising case of anomalous tZc couplings using Monte Carlo simulations and a simplified detector simulation. We consider the main background processes and discriminate the signal from the background with a deep neural network that is parametrised in the value of the anomalous tZc coupling. We present sensitivity projections for the HL-LHC and the FCC-hh. We find an expected 95% CL upper limit of $${\mathcal {B}}_{\textrm{excl}}(t\rightarrow Zc) = 6.4 \times 10^{-5}$$ B excl ( t → Z c ) = 6.4 × 10 - 5 for the HL-LHC. In general, we conclude that the interference-based approach has the potential to provide both competitive and complementary constraints to traditional multi-lepton searches and other strategies that have been proposed to search for tZc FCNCs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Coupling turbulent flow with blade aeroelastics and control modules in large-eddy simulation of utility-scale wind turbines

We present a large-eddy simulation framework capable of control co-design of large wind turbines, coupling the turbulent flow environment with blade aeroelastics and turbine controllers. The geometry and aerodynamics of the rotor blades and the turbine nacelle are parameterized using an actuator surface model. The baseline collective pitch control and individual pitch control (IPC) algorithms, consisting of a single-input, single-output proportional–integral controller and two integral controllers, respectively, are incorporated into the simulation framework. Furthermore, a second-order model based on the Euler–Bernoulli beam theory is implemented to describe the blade deformation. Simulations are carried out to investigate the impact of collective and individual pitch control strategies on the deflection of turbine blades. Our results show that the IPC reduces the blade tip deflection fluctuations in the out-of-plane direction, while the fluctuations of the blade tip deflection along the in-plane direction are barely affected by the IPC. Furthermore, the blade out-of-plane deformation fluctuation is underestimated by the one-way coupling approach compared to the two-way coupling approach. Furthermore, the findings of this study reveal the importance of advanced control systems in reducing the dynamic loads on wind turbine blades and underscore the potential of control co-design to reduce the levelized cost of wind energy.

42 ENGINEERING↗

Initial steady-state core simulation capability or thermal and pool-type molten salt reactors, coupling reactor physics, thermal-hydraulics, and evolving chemistry

This report presents the development and validation of an initial steady-state multiphysics capability for molten salt reactors (MSRs) under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in Fiscal Year 2025. The framework integrates neutronics, thermal-hydraulics, species transport, and thermochemistry to capture the coupled dynamics of liquid-fueled systems. Implementation and testing were performed on two representative designs: the Molten Salt Reactor Experiment (MSRE), a thermal-spectrum, channeled-flow reactor, and the Lotus Molten Salt Reactor (L-MSR), a fast-spectrum, pool-type reactor. The modeling suite employs Griffin for reactor physics and depletion, Pronghorn and SAM for thermal-hydraulics, Thermochimica for chemistry, and Saline for thermophysical properties, with benchmarking and validation carried out against historical MSRE data, experimental flow-loop measurements, and reference depletion calculations from Monte Carlo codes. The framework demonstrated the ability to reproduce key reactor behaviors including temperature feedback, reactivity losses, delayed neutron precursor transport, xenon poisoning, and redox potential evolution. The results confirm the feasibility and accuracy of the coupled models in predicting steady-state and selected transient MSR behaviors. This latter ones are used in this report as a proxy indicating that the steady-state models from which the transient starts are accurate. For MSRE, validation showed good agreement with pump start-up and natural circulation tests, while for the L-MSR, benchmarking confirmed hydraulic calibration and consistency of neutronics–thermal coupling. The tools also provided new insights into species transport, noble metal deposition, and salt solidification dynamics. On the Xenon transport front, the code is validated against the steady state Xenon poisoining measurement and showed good agreement with the experimental value. Identified areas for future work include advanced void transport modeling, three-dimensional simulations, improved alloy corrosion models, and tighter integration with high-fidelity Monte Carlo codes. These developments provide a foundation for high-fidelity MSR simulations that can support reactor design optimization, safety assessments, and long-term operational strategies.

42 - ENGINEERING↗

Complex-Valued Intermolecular Coupling Enables Directional Exciton Transport in Excitonic Circuits

Molecular systems capable of directing the flow of excitons are key to the development and optimization of optoelectronic materials. The transport of excitons across multiple molecules is governed by an intermolecular electronic coupling network. In this article, we consider the effects of complex-valued intermolecular electronic coupling on exciton transport. Here, we present a molecular motif capable of generating complex-valued coupling under excitation with circularly polarized light. We use theoretical modeling and simulation to illustrate how complex coupling can be leveraged to drive the rotational flux of excitons in cyclic molecular networks and direct the exciton population in branched molecular networks.

chromophores↗

Immersion Freezing in Particle-Based Aerosol-Cloud Microphysics: A Probabilistic Perspective on Singular and Time-Dependent Models

Cloud droplets containing immersed ice-nucleating particles (INPs) may freeze at temperatures above the homogeneous freezing threshold temperature in a process referred to as immersion freezing. In modeling studies, immersion freezing is often described using either so-called “singular” or “time-dependent” parameterizations. Here, we compare both approaches and discuss them in the context of probabilistic particle-based (super-droplet) cloud microphysics modeling. First, using a box model, we contrast how both parameterizations respond to idealized ambient cooling rate profiles and quantify the impact of the polydispersity of the immersed surface spectrum on the frozen fraction evolution. Presented simulations highlight that the singular approach, constituting a time-integrated form of a more general time-dependent approach, is only accurate under a limited range of ambient cooling rates. The time-dependent approach is free from this limitation. Second, using a prescribed-flow two-dimensional cloud model, we illustrate the macroscopic differences in the evolution in time of ice particle concentrations in simulations with flow regimes relevant to ambient cloud conditions. The flow-coupled aerosol-budget-resolving simulations highlight the benefits and challenges of modeling cloud condensation nuclei activation and immersion freezing on insoluble ice nuclei with super-particle methods. The challenges stem, on the one hand, from heterogeneous ice nucleation being contingent on the presence of relatively sparse immersed INPs, and on the other hand, from the need to represent a vast population of particles with relatively few so-called super particles (each representing a multiplicity of real particles). We discuss the critical role of the sampling strategy for particle attributes, including the INP size, the freezing temperature (for singular scheme) and the multiplicity.

54 ENVIRONMENTAL SCIENCES↗

SOWFA Large-Eddy Simulation of a Diurnal Cycle at the SWiFT Site

These are large-eddy simulation (LES) data output from the Simulator for Wind Farm Applications (SOWFA) with internal mesoscale-to-microscale coupling. A diurnal cycle was simulated over the Scaled Wind Farm Technology (SWIFT) facility near Lubbock, Texas, from 2013-11-08 12:00:00 UTC to 2013-11-09 12:00:00 UTC. Indirect profile assimilation was used to enforce nonstationary mesoscale conditions. Mesoscale forcing data were extracted from WRF numerical weather prediction outputs or derived from observations at SWiFT.

17 WIND ENERGY↗

Convergence Criteria for Multiphysics Simulations

The behavior of engineered systems is often influenced by multiple physical phenomena, such as mechanical deformation, heat transfer, and chemical species transport and reactions. There are often strong interactions between these phenomena, and there is increasing interest in applying coupled-physics models to improve understanding of physical behavior under complex environmental conditions. Multiple simulation frameworks that facilitate coupled-physics simulations are in widespread use, and these employ a variety of techniques to account for interactions between those physics. Many frameworks solve the physics models independently and transfer results between them. Alternatively, a single monolithic system of equations for every physics model can be formed and solved. Each of these approaches has its benefits and drawbacks, and the optimal approach varies depending on the nature of the problem. The open-source MOOSE framework was developed targeting solution of large-scale multiphysics problems. Although it provides options for all these coupling approaches, its standard approach for multiphysics solutions is to form and solve a single monolithic system of equations containing the unknowns for all physics models. MOOSE provides a streamlined approach for users to define the solution variables, the terms in the partial differential equations pertaining to each variable, and interactions between solution variables. One aspect of the monolithic solution approach that can be problematic, however, is defining appropriate convergence criteria for the nonlinear system. A standard approach is to determine convergence is to simply take a norm of the residual vector corresponding to the full vector of unknowns. However, if the residual vector contains variables for multiple physics models, the magnitudes of those variables can differ significantly, and the variables can converge at significantly different rates from each other. It is important to ensure that the variables for each of the physics are converged, and also ensure that the convergence criteria are not excessively stringent in cases when there is little change in the solution. This talk presents representative multiphysics problems to highlight these issues, and shows strategies for convergence criteria in MOOSE that are robust for multiphysics models under a variety of conditions.

97 - MATHEMATICS AND COMPUTING↗

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to MLexperts because of lack of training data and relevant, easy-to-use workflows. Wepresent ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res2) and code(https://leap-stc.github.io/ClimSim)arereleasedopenlytosupport the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.

artificial intelligence, machine learning↗

Multiphysics Coupling of PROTEUS-NODAL and SAM for Molten Salt Reactor Simulation

The purpose of this report is to document the new features and capabilities that have been implemented in the PROTEUS-NODAL code and the coupling procedure of PROTEUS-NODAL with SAM to analyze MSRs. This report is organized as follows. Section 2 presents the variational nodal P 1 solver for cylindrical geometries and its verification test results. Section 3 discusses the transient analysis capability implemented in the P 1 solvers of PROTEUS-NODAL. The solution methods for the coupled system of TFSP and precursor drift equations, the coarse mesh finite difference (CMFD) acceleration, the kinetics parameter evaluation method, and the thermal feedback are discussed. The verification test results against the SP 3 solutions are also discussed. Section 4 describes the coupling scheme of PROTEUS-NODAL and SAM under the MOOSE framework for MSR applications. The developed MOOSE applications named “TreeFrog” and “TreeKangaroo” are discussed. Verification test results for the coupled system are also discussed by comparing the MSFR steady state solution with that obtained from a manually coupled PROTEUS-NODAL and ANSYS CFX computational fluid dynamics (CFD) calculations and the MSFR transient analysis results with the open literature solutions and the PROTEUS-NODAL solutions obtained with the standalone thermal-hydraulics solver. Section 5 provides conclusions and future works.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗

A coupled hydrodynamic (HEC-RAS 2D) and water quality model (WASP) for simulating flood-induced soil, sediment, and contaminant transport

Increased intensity and frequency of floods raise concerns about the release and transport of contaminated soil and sediment to and from rivers and streams. To model these processes during flooding events, we developed an External Coupler in Python to link the Hydrologic Engineering Center-River Analysis System (HEC-RAS) 2D hydrodynamic model to the Water Quality Analysis Simulation Program (WASP). Accurate data transfer from a hydrodynamic model to a water quality model is critical. Our test results showed the External Coupler successfully linked HEC-RAS and WASP and addressed technical challenges in aggregating flow data and conserving mass during the flood event. We ran the coupled models for a 100-year flood event to calculate flood-induced transport of sediment-associated arsenic in Woodbridge Creek, NJ. Change in surface sediment and arsenic at the end of 48-h flood simulation ranged from a net loss of 13.5 cm to a net gain of 11.6 cm, and 16.2 to 2.9 mg/kg, respectively, per model segment, which demonstrates the capability of the coupled model for simulating sediment and contaminant transport in flood.

54 ENVIRONMENTAL SCIENCES↗

Coupling coarse-mesh CFD with fine-mesh CFD for modeling molten-salt reactors in the Virtual Test Bed (VTB)

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims at developing a simulation tool kit to accelerate the development and deployment of nuclear power technologies. NEAMS multiphysics tools have been designed to provide numerical simulation support for the design and licensing of GEN IV reactors. Pronghorn is NEAMS's coarse-mesh computational fluid dynamics (CFD) tool, which is designed to run 3D core transients in GEN IV reactors at a reduced computational cost. To increase their accuracy, coarse-mesh CFD simulations require calibrated closure coefficients. One way of computing these coefficients is via the Nek5000, NEAMS's high-fidelity CFD tool. This article discusses our current research lines in informing Pronghorn closure coefficients via Nek5000 to enable multiphysics simulations of the core cavity of the molten-salt fast reactor. We present an application in which Pronghorn mixing length turbulent viscosity has been calibrated from Nek5000 simulations. The resulting Pronghorn thermal-hydraulics model is then coupled to Griffin, the NEAMS neutron transport solver, to solve for the steady-state configuration of the molten-salt fast reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Impacts of Sea‐Level Rise on Coastal Groundwater Table Simulated by an Earth System Model With a Land‐Ocean Coupling Scheme

Abstract Sea‐level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land‐ocean interface. To address this gap, we developed a novel land‐ocean hydrologic coupling scheme in a state‐of‐the‐science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR‐induced inundation. Simulations were performed with the updated E3SMv2 for the global land‐ocean interface to assess the impacts of SLR on coastal groundwater under a high CO 2 emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land‐ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR‐induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land‐ocean interface, which needs to be considered in ESMs.

54 ENVIRONMENTAL SCIENCES↗