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At least 91 records · Page 5

Changes in high-latitude surface energy balance driven by snowpack and vegetation dynamics under warmer climate

With rapid climate warming, expected changes in snowpack and vegetation will alter the seasonal surface albedo of high-latitude ecosystems. The extent to which these albedo changes may affect surface energy balances and thus soil temperatures is uncertain, but represents a potentially important component of ecosystem feedbacks to climate change. Here, we apply a well-tested process-rich ecosystem model, ecosys , to examine changes in seasonal surface albedo and soil temperature driven by climate-induced snowpack and vegetation changes across Alaska under a warmer twenty-first century climate. Under the Representative Concentration Pathway 8.5 climate change scenario, the modeled changes in surface albedo exhibited large seasonal and spatial variations. We found spring albedo decreases driven by increases in snow-free periods (>20 d) and an extended growing season length that resulted in greater gains in leaf area index (LAI) in most parts of Alaska. In contrast, we modeled increases in summer and winter albedo (despite modeled increases in LAI) across much of the boreal forest due to an increased proportion of aspen, which has a higher leaf albedo than the currently dominant black spruce. Modeled latent heat fluxes generally increase across the twenty-first century, particularly during the spring and summer. Overall, climate warming and changes in surface energy fluxes resulted in a 3.5 ± 0.50 °C increase in spatial- and annual-averaged top 10 cm surface soil temperatures across Alaskan ecosystems by the year 2100, with larger increases in tundra than boreal forest regions. We conclude that under warmer climates, seasonal variations in albedo and surface energy fluxes are particularly pronounced during the spring and summer, driven by changes in snowpack and vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗

Evolutionary Game Dynamics between Distributed Energy Resources and Microgrid Operator: Balancing Act for Power Factor Improvement

This article investigates the intricate dynamics between Distributed Energy Resources (DERs) and the Microgrid Operator (MGO) within a microgrid interconnected with the main grid. Employing an evolutionary game framework, the study scrutinizes the strategic evolution of DERs’ decision-making processes in their interactions with the MGO. Modeled as an evolutionary game, these interactions encapsulate the strategies adopted by DERs, resulting in stable equilibrium strategies over time. Motivated by direct benefits linked to increased active power production, DERs strive to sell all available power, while the MGO focuses on optimizing the microgrid’s overall performance. The study assesses the microgrid’s performance in terms of its power factor, emphasizing the strategic balance DERs must achieve in their active power generation to avoid penalization. This penalization results in decreased individual utility for DERs due to the overall power factor decrease resulting from their prioritization of active power generation. Additionally, the diminished overall power factor implies a decrease in MGO utility. The individual utility of each DER is further influenced by the strategies adopted by other DERs, impacting the penalization factor. Leveraging a modified IEEE 13-node distribution microgrid consisting of three DERs, the study presents case studies encompassing both cooperative and non-cooperative evolutionary game scenarios. These case studies illuminate the intricacies of interactions and the resulting equilibrium outcomes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Zonal magnetic fields regulate nonlinear edge-localized-mode dynamics via self-consistent force balance

Edge-localized modes (ELMs) eject intense bursts of heat and particles that threaten plasma-facing components in fusion reactors. Nonlinear full-torus BOUT++ simulations show that turbulence-driven zonal magnetic fields (ZMFs) play an essential role in nonlinear ELM evolution by maintaining self-consistent force balance. Zonal flows mitigate the initial crash through shear but do not prevent continued radial transport. When ZMFs are self-consistently included, turbulence-driven zonal currents modify the parallel current distribution and magnetic tension and are associated with a reduction of the axisymmetric (𝑛 = 0) perturbed radial force imbalance. This coincides with a transition from convective, bursty propagation to more localized, diffusive transport. Similar behavior is observed across the regimes considered, including both resistive-ballooning and peeling-ballooning cases. Finally, associated signatures, including radial electric field shear and parallel current redistribution, provide experimentally accessible diagnostics for present devices and ITER-relevant conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗

Microgrid Modeling for Stability Analysis

Here this document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid (MG) Dynamic Modeling, IEEE Power and Energy Society, Tech. Rep. PES-TR106, 2023. In this paper, the major issues and challenges in microgrid modeling for stability analysis are discussed, and a review of state-of-the-art modeling approaches and trends is presented. In the context of the IEEE 1547 standard, the document covers issues associated with component models for MG dynamic studies and simulations, including generator and grid modeling, full and average converter models, unbalanced and balanced system conditions, dynamic and static loads, protection requirements, and detailed and simplified controls considering communications delays, packet losses, and security issues. Considering the future integration of grids and MGs to form broad integrated networks, a discussion is presented of the use of phasor vis-à-vis electromagnetic transient simulation tools for MG dynamic stability studies, as well as modeling scale-up issues and MG equivalent models. Specifically white-, grey-, and black-box models, are presented. This TF paper and companion report constitute a modeling guide for R&D groups working on developments and standards of MGs with a focus on stability issues.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Well-balanced treatment of gravity in astrophysical fluid dynamics simulations at low Mach numbers

We report accurate simulations of flows in stellar interiors are crucial to improving our understanding of stellar structure and evolution. Because the typically slow flows are merely tiny perturbations on top of a close balance between gravity and the pressure gradient, such simulations place heavy demands on numerical hydrodynamics schemes. We demonstrate how discretization errors on grids of reasonable size can lead to spurious flows orders of magnitude faster than the physical flow. Well-balanced numerical schemes can deal with this problem. Three such schemes were applied in the implicit, finite-volume SEVEN-LEAGUE HYDRO code in combination with a low-Mach-number numerical flux function. We compare how the schemes perform in four numerical experiments addressing some of the challenges imposed by typical problems in stellar hydrodynamics. We find that the α-β and deviation well-balancing methods can accurately maintain hydrostatic solutions provided that gravitational potential energy is included in the total energy balance. They accurately conserve minuscule entropy fluctuations advected in an isentropic stratification, which enables the methods to reproduce the expected scaling of convective flow speed with the heating rate. The deviation method also substantially increases accuracy of maintaining stationary orbital motions in a Keplerian disk on long timescales. The Cargo–LeRoux method fares substantially worse in our tests, although its simplicity may still offer some merits in certain situations. Overall, we find the well-balanced treatment of gravity in combination with low Mach number flux functions essential to reproducing correct physical solutions to challenging stellar slow-flow problems on affordable collocated grids.

79 ASTRONOMY AND ASTROPHYSICS↗

Hidden Killing fields, geometric symmetries and black hole mergers

Highlights: • Construction of geometric models with a variable degree of symmetry. • Formulation of Energy and Momentum Balance Laws. • Description of backreactions on spacetime geometries caused by dissipative effects. • Analytic description of accretion and/or merger processes in GR. • Exact model for the merger of two extremal Reissner–Nordström black holes. In the present work, using the recently introduced framework of local geometric deformations, special types of vector fields – so-called hidden Killing vector fields – are constructed, which solve the Killing equation not globally, but only locally, i.e. in local subregions of spacetime. Taking advantage of the fact that the vector fields coincide locally with Killing fields and therefore allow the consideration of integral laws that convert into exact physical conservation laws on local scales, balance laws in dynamical systems without global Killing symmetries are derived that mimic as closely as possible the conservation laws for energy and angular momentum of highly symmetric models. The utility of said balance laws is demonstrated by a concrete geometric example, namely a toy model for the binary merger of two extremal Reissner–Nordström black holes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗

Mathematical Modeling of Multi-Phenomena Anisotropic Systems: Ejection of Primary Aerosols during the Fast Pyrolysis of Biomass

This study introduces a novel particle model for biomass fast pyrolysis, incorporating an anisotropic cylindrical particle to address mass and energy transport coupled with aerosol ejection, which previous models have overlooked. The main contribution lies in developing a model that considers aerosol generation in anisotropic cylindrical particles for the first time, addressing bubbling dynamics and bursting within the liquid phase. The population balance equation describes bubble dynamics and aerosol formation, capturing phenomena like nucleation, growth, coalescence, and bursting. The model employs the method of moments with bubble volume as an internal variable, substantially reducing computational costs by eliminating dependence on this variable. Results highlight the significant impact of anisotropy and particle size on aerosol ejection: smaller, less elongated particles experience faster heating, quicker conversion, and the increased accumulation of the liquid intermediate phase. Specifically, 1 mm diameter particles yield higher concentrations of metaplast and bio-oil aerosols, exceeding 15%, compared to concentrations below 11% for 3 mm particles. This model provides insights into aerosol structure (volume, surface area), aiding in understanding aerosol reactivity at the reactor scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Turbulent Regimes in Collisions of 3D Alfvén-wave Packets

Using three-dimensional gyrofluid simulations, we revisit the problem of Alfvén-wave (AW) collisions as building blocks of the Alfvénic turbulent cascade and their interplay with magnetic reconnection at magnetohydrodynamic (MHD) scales. Depending on the large-scale value of the nonlinearity parameter χ 0 (the ratio between the AW linear propagation time and nonlinear turnover time), different regimes are observed. For strong nonlinearities (χ 0 ~ 1), turbulence is consistent with a dynamically aligned, critically balanced cascade—fluctuations exhibit a scale-dependent alignment $\sin {\theta }_{{k}_{\perp }}\propto {k}_{\perp }^{-1/4}$, resulting in a ${k}_{\perp }^{-3/2}$ spectrum and ${k}_{\parallel }\propto {k}_{\perp }^{1/2}$ spectral anisotropy. At weaker nonlinearities (small χ 0 ), a spectral break marking the transition between a large-scale weak regime and a small-scale ${k}_{\perp }^{-11/5}$ tearing-mediated range emerges, implying that dynamic alignment occurs also for weak nonlinearities. At χ 0 < 1 the alignment angle ${\theta }_{{k}_{\perp }}$ shows a stronger scale dependence than in the χ 0 ~ 1 regime, namely $\sin {\theta }_{{k}_{\perp }}\propto {k}_{\perp }^{-1/2}$ at χ 0 ~ 0.5, and $\sin {\theta }_{{k}_{\perp }}\propto {k}_{\perp }^{-1}$ at χ 0 ~ 0.1. Dynamic alignment in the weak regime also modifies the large-scale spectrum, scaling approximately as ${k}_{\perp }^{-3/2}$ for χ 0 ~ 0.5 and as ${k}_{\perp }^{-1}$ for χ 0 ~ 0.1. A phenomenological theory of dynamically aligned turbulence at weak nonlinearities that can explain these spectra and the transition to the tearing-mediated regime is provided; at small χ 0 , the strong scale dependence of the alignment angle combines with the increased lifetime of turbulent eddies to allow tearing to onset and mediate the cascade at scales that can be larger than those predicted for a critically balanced cascade by several orders of magnitude. Such a transition to tearing-mediated turbulence may even supplant the usual weak-to-strong transition.

79 ASTRONOMY AND ASTROPHYSICS↗

Time propagation of electronic wavefunctions using nonorthogonal determinant expansions

The use of truncated configuration interaction in real-time time-dependent simulations of electron dynamics provides a balance of computational cost and accuracy, while avoiding some of the failures associated with real-time time-dependent density functional theory. However, low-order truncated configuration interaction also has limitations, such as overestimation of polarizability in configuration interaction singles, even when perturbative doubles are included. Increasing the size of the determinant expansion may not be computationally feasible, and so, in this work, we investigate the use of nonorthogonality in the determinant expansion to establish the extent to which higher-order substitutions can be recovered, providing an improved description of electron dynamics. Model systems are investigated to quantify the extent to which different methods accurately reproduce the (hyper)polarizability, including the high-harmonic generation spectrum of H 2 , water, and butadiene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ecological Assembly Processes Are Coordinated between Bacterial and Viral Communities in Fractured Shale Ecosystems

The ecological drivers that concurrently act upon both a virus and its host and that drive community assembly are poorly understood despite known interactions between viral populations and their microbial hosts. Hydraulically fractured shale environments provide access to a closed ecosystem in the deep subsurface where constrained microbial and viral community assembly processes can be examined. Here, we used metagenomic analyses of time-resolved-produced fluid samples from two wells in the Appalachian Basin to track viral and host dynamics and to investigate community assembly processes. Hypersaline conditions within these ecosystems should drive microbial community structure to a similar configuration through time in response to common osmotic stress. However, viral predation appears to counterbalance this potentially strong homogeneous selection and pushes the microbial community toward undominated assembly. In comparison, while the viral community was also influenced by substantial undominated processes, it assembled, in part, due to homogeneous selection. When the overall assembly processes acting upon both these communities were directly compared with each other, a significant relationship was revealed, suggesting an association between microbial and viral community development despite differing selective pressures. These results reveal a potentially important balance of ecological dynamics that must be in maintained within this deep subsurface ecosystem in order for the microbial community to persist over extended time periods. More broadly, this relationship begins to provide knowledge underlying metacommunity development across trophic levels.

54 ENVIRONMENTAL SCIENCES↗

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An adaptive scalable fully implicit algorithm based on stabilized finite element for reduced visco-resistive MHD

The magnetohydrodynamics (MHD) equations are continuum models used in the study of a wide range of plasma physics systems, including the evolution of complex plasma dynamics in tokamak disruptions. However, efficient numerical solution methods for MHD are extremely challenging due to disparate time and length scales, strong hyperbolic phenomena, and nonlinearity. Additionally, therefore the development of scalable, implicit MHD algorithms and high-resolution adaptive mesh refinement strategies is of considerable importance. In this work, we develop a high-order stabilized finite-element algorithm for the reduced visco-resistive MHD equations based on the MFEM finite element library (mfem.org). The scheme is fully implicit, solved with the Jacobian-free Newton-Krylov (JFNK) method with a physics-based preconditioning strategy. Our preconditioning strategy is a generalization of the physics-based preconditioning methods in Chacón et al. (2002) to adaptive, stabilized finite elements. Algebraic multigrid methods are used to invert sub-block operators to achieve scalability. A parallel adaptive mesh refinement scheme with dynamic load-balancing is implemented to efficiently resolve the multi-scale spatial features of the system. Our implementation uses the MFEM framework, which provides arbitrary-order polynomials and flexible adaptive conforming and non-conforming meshes capabilities. Results demonstrate the accuracy, efficiency, and scalability of the implicit scheme in the presence of large scale disparity. The potential of the AMR approach is demonstrated on an island coalescence problem in the high Lundquist-number regime (≥ 10 7 ) with the successful resolution of plasmoid instabilities and thin current sheets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fractal Model for Drag Reduction on Multiscale Nonwetting Rough Surfaces

Rough surfaces in contact with a flow of fluid exhibit alternating no-slip and free shear boundary conditions at the solid–liquid and air–liquid interfaces, respectively, thereby potentially offering drag reduction benefits. The balance between the dynamic pressure in the flow and the restoring capillary pressure in the interasperity spaces determines the stability of the Cassie state of wettability and is a function of the relative extent of no-slip and free shear regions per unit surface area. In the present study, using a fractal representation of rough surface topography, an analytical model is developed to quantify the stability of the Cassie state of wettability as well as drag reduction and the friction factor for laminar flow in a rectangular channel between nonwetting multiscale rough surfaces. A systematic study is conducted to quantify the effects of fractal parameters of the surfaces and the flow Reynolds number on drag reduction and the friction factor. The studies are used to develop friction factor curves extending the classical Moody diagram to hydrophobic and superhydrophobic surfaces. On the basis of the studies, regime maps are derived for estimating the extent of drag reduction offered by hydrophobic and superhydrophobic surfaces, revealing that superhydrophobic surfaces do not always offer the best drag reduction performance. The application of the fractal model to practical topographies of nonwetting surfaces of copper, aluminum, and zinc oxide fabricated via electrodeposition and etching is also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Episodes of Early Pleistocene West Antarctic Ice Sheet Retreat Recorded by Iceberg Alley Sediments

Abstract Ice loss in the Southern Hemisphere has been greatest over the past 30 years in West Antarctica. The high sensitivity of this region to climate change has motivated geologists to examine marine sedimentary records for evidence of past episodes of West Antarctic Ice Sheet (WAIS) instability. Sediments accumulating in the Scotia Sea are useful to examine for this purpose because they receive iceberg‐rafted debris (IBRD) sourced from the Pacific‐ and Atlantic‐facing sectors of West Antarctica. Here we report on the sedimentology and provenance of the oldest of three cm‐scale coarse‐grained layers recovered from this sea at International Ocean Discovery Program Site U1538. These layers are preserved in opal‐rich sediments deposited ∼1.2 Ma during a relatively warm regional climate. Our microCT‐based analysis of the layer's in‐situ fabric confirms its ice‐rafted origin. We further infer that it is the product of an intense but short‐lived episode of IBRD deposition. Based on the petrography of its sand fraction and the Phanerozoic 40 Ar/ 39 Ar ages of hornblende and mica it contains, we conclude that the IBRD it contains was likely sourced from the Weddell Sea and/or Amundsen Sea embayment(s) of West Antarctica. We attribute the high concentrations of IBRD in these layers to “dirty” icebergs calved from the WAIS following its retreat inland from its modern grounding line. These layers also sit at the top of a ∼366‐m thick Pliocene and early Pleistocene sequence that is much more dropstone‐rich than its overlying sediments. We speculate this fact may reflect that WAIS mass‐balance was highly dynamic during the ∼41‐kyr (inter)glacial world.

Bailey, Ian↗

Molecular origin of negative lithium transference in electrolytes with star-shaped multivalent anions

Large-scale molecular dynamics simulations illustrate that highly correlated cation–anion motion leads to negative t 0+ on the order of 1 in lithium electrolytes with star-shaped multivalent anions. Large multivalent anions have gained increasing attention for their potential to improve lithium transference in electrolytes. We employ large-scale molecular dynamics simulations based on the Onsager transport framework to investigate ion transport in a lithium electrolyte with star-shaped multivalent anions. The simulations show that t 0+, the cation transference number with respect to solvent velocity, is negative over a wide range of concentration. This is consistent with experimental data reported previously. The simulation-based Onsager transport coefficients reveal that the magnitudes of the cation–cation, anion–anion, and cation–anion correlations are comparable, a signature of highly correlated motion in the electrolyte. Examination of the cation solvation environment indicates the presence of strong cation–anion association across the entire concentration range, which leads to negative t 0+ on the order of −1. Both simulation and experiment also show that the maximum value of t 0+ reaches 0 when the cation concentration is c + = 0.4 M. This is the concentration at which the anions begin to spatially overlap, and lithium ions serve as dynamic linkers to balance cation–cation and cation–anion correlations. Our results provide molecular-level insights into the origin of transference in multivalent electrolytes.

Fang, Chao↗