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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dynamic Tensile Characterization of Thin-Sheet Brittle Metallic Materials

Refractory metals are favorable materials in applications where high strength and ductility are needed at elevated temperatures. In some cases, operating temperatures may be near the melting point of the material. However, as temperature drops, refractory metals typically undergo a significant mechanical response change - ductile-to-brittle transition. These materials may be subjected to high strain rate loading at an ambient temperature state, such as an impact or crash. Knowledge of the high rate material properties are essential for design as well as simulation of impact events. The high rate stress-strain behavior of brittle metallic materials at ambient temperature is rarely studied because of experimental challenges, particularly when failure is involved. Failure typically occurs within the non-gage section of the material, which invalidates any collected stress-strain information. Here, a method to determine a specimen geometry which will produce failures in the gage section is presented. Pure tungsten in thin-sheet form was used as a trial material to select a specimen geometry for high rate Kolsky tension bar experiments. A finite element simulation was conducted to derive a strain correction for more accurate results. The room temperature stress-strain behavior of pure tungsten at a strain rate of 24 s –1 is presented. The outcome of this experimental technique can be applied to other brittle materials for dynamic tensile characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Field-tailoring quantum materials via magneto-synthesis: metastable metallic and magnetically suppressed phases in a trimer iridate

We demonstrate that applying modest magnetic fields (< 0.1 T) during high-temperature crystal growth can profoundly alter the structure and ground state of a spin-orbit-coupled, antiferromagnetic trimer lattice. Using BaIrO₃ as a model system, whose ground state is intricately dictated by the trimer lattice, we show that magneto-synthesis , a field-assisted synthesis approach, stabilizes a structurally compressed, metastable metallic and magnetically suppressed phases inaccessible via conventional methods. These effects include a 0.85% reduction in unit cell, 4-order-of-magnitude decrease in resistivity, a 10-fold enhancement of the Sommerfeld coefficient, and the collapse of long-range magnetic order -- all intrinsic and bulk in origin. First-principles calculations confirm that the field-stabilized structure lies substantially above the ground state in energy, highlighting its metastable character. These large, coherent and correlated changes across multiple bulk properties, unlike those caused by dilute impurities, defects or off-stoichiometry, point to an intrinsic field-induced mechanism. The findings establish magneto-synthesis as a powerful new pathway for accessing non-equilibrium quantum phases in strongly correlated materials.

magneto-synthesis↗
DOE OSTI2024

Low-temperature formation of pyridine and (iso)quinoline via neutral–neutral reactions

Aromatic molecules represent fundamental building blocks in prebiotic chemistry and are contemplated as vital precursors to DNA and RNA nitrogen bases. However, despite the identification of some 300 molecules in extraterrestrial environments, the pathways to pyridine (C 5 H 5 N), pyridinyl (C 5 H 4 N•), and (iso)quinoline (C 9 H 7 N) – the simplest represen-tative of mono and bicyclic aromatic molecule carrying nitrogen – are elusive. Here, we afford compelling evidence on the gas-phase formation of methylene amidogen (H 2 CN•) and cyanomethyl (H 2 CCN•) radicals via molecular beam studies and electronic structure calcula-tions. The modeling of the chemistries of Taurus Molecular Cloud (TMC-1) and Titan’s atmosphere contemplates a complex chain of reactions synthesizing pyridine, pyridinyl, and (iso)quinoline from H 2 CN• and H 2 CCN• at levels of up to 75%. Furthermore, this study affords unique entry points to precursors of DNA and RNA nitrogen bases in hydrocarbon-rich extraterrestrial environments thus changing the way we think about the origin of prebiotic molecules in our Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Combining different 3-D global and regional seismic wave propagation solvers towards box tomography in the deep Earth

SUMMARY In previous publications, we presented a general framework, which we called ‘box tomography’, that allows the coupling of any two different numerical seismic wave propagation solvers, respectively outside and inside a target region, or ‘box’. The goal of such hybrid wavefield computations is to reduce the cost of computations in the context of full-waveform inversion for structure within the target region, when sources and/or receivers are located at large distances from the box. Previously, we had demonstrated this approach with sources and receivers outside the target region in a 2-D acoustic spherical earth model, and demonstrated and applied this methodology in the 3-D spherical elastic Earth in a continental scale inversion in which all stations were inside the target region. Here we extend the implementation of the approach to the case of a 3-D global elastic earth model in the case where both sources and stations are outside the box. We couple a global 3-D solver, SPECFEM3D_GLOBE, for the computation of the wavefield and Green’s functions in a reference 3-D model, with a regional 3-D solver, RegSEM, for the computation of the wavefield within the box, by means of time-reversal mirrors. We briefly review key theoretical aspects, showing in particular how only the displacement is needed to be stored at the boundary of the box. We provide details of the practical implementation, including the geometrical design of the mirrors, how we deal with different sizes of meshes in the two solvers, and how we address memory-saving through the use of B-spline compression of the recorded wavefield on the mirror. The proposed approach is numerically efficient but also versatile, since adapting it to other solvers is straightforward and does not require any changes in the solver codes themselves, as long as the displacement can be recovered at any point in time and space. We present benchmarks of the hybrid computations against direct computations of the wavefield between a source and an array of stations in a realistic geometry centred in the Yellowstone region, with and without a hypothetical plume within the ‘box’, and with a 1-D or a 3-D background model, down to a period of 20 s. The ultimate goal of this development is for applications in the context of imaging of remote target regions in the deep mantle, such as, for example, Ultra Low Velocity Zones.

Geochemistry & Geophysics↗
DOE OSTI2024

Operation of Grid Forming Converters as Self Excited Induction Generators Under Non-Ideal Loading Conditions

Self-excited induction generators offer a robust solution for power production for standalone as well as grid-connected systems. In general, self-excited induction generators require excitation capacitors which make use of the machine magnetization characteristics for voltage build up process as well as operation at a specific frequency. In this paper, a self-excited induction machine is modeled with both the electrical and mechanical dynamics. This modeled virtual machine's dynamics are utilized for voltage build up process for a standalone photovoltaic converter connected to a local load for a microgrid application. The modeled machine's parameters are used from the name plate rating from the manufacturer. However, in a microgrid the accommodation of unbalanced and/or nonlinear harmonic rich load is a necessity, therefore, in this work the virtual self-excitation capacitors of the modeled machine are varied based on the machine characteristics. With the objective of ensuring harmonic free point of common coupling voltage, the modeled virtual self-excitation capacitors are varied to accomplish change in terminal frequency and the virtual load torque is varied to obtain voltage magnitude change. To verify the efficacy, the overall system is modeled in MATLAB/Simulink and PLECS domain and most important case studies are presented.

grid forming converters (GFM)↗
DOE OSTI2020

Continuum Description of the Role of Negative Transference Numbers on Ion Motion in Polymer Electrolytes

New experimental techniques such as electrophoretic NMR (eNMR) are emerging as powerful methods for directly measuring ion velocities in electrolytes under applied electric fields. The aim of this theoretical study is to predict the spatial- and temporal-dependence of these velocities of ions as a function of the magnitude of the applied field and salt concentration. It has recently been shown that mixtures of poly(ethylene oxide)-based (PEO) and lithium bis(trifluoromethanesulfonyl) imide (LiTFSI) electrolytes exhibit negative cation transference numbers in a certain salt concentration range. In this range, the cation motion at early times is directed to the positive electrode at all locations in the cell; ion migration dominates in this regime. As time progresses, the cation velocity in finite zones near both the electrodes changes sign. These zones grow rapidly with time, reflecting the increasing importance of diffusion, and a point in time is reached beyond which the cation velocity in the entire cell is directed toward the negative electrode. Overall, our work reveals the limited time window over which the results of eNMR can be used to determine the transference number. More importantly, it shows how to account for the effect of diffusional flux in such experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development of in situ thickness sensor for vapor diffused Nb3Sn films

Fermilab is one of the leaders in development of vapor diffused Nb3Sn films inside niobium cavities. This material has a higher critical temperature (Tc) than niobium, enabling cavity operation at 4.2 K. This higher operational temperature significantly reduces the infrastructure required for cooling compared to 2 K systems, making superconducting radio-frequency (SRF) technology more accessible. Current deposition methods have relied on iterative testing to determine nominal film thickness, a process that can be time-consuming and imprecise. To address this, we are developing a sensor to measure the thickness of Nb3Sn thin film in situ during vapor diffusion. Our design involves a four-point resistance measurement of a thin film of niobium, inside the coating region. During coating, the change in resistance reflects the conversion of the film from Nb to Nb3Sn, which allows simple integration with the current furnace infrastructure. This sensor would allow real time measurement of the Nb3Sn film thickness, allowing for increased precision in future depositions for cavity applications.

Howard, K. [Chicago U.] (ORCID:0000000325613308)↗
DOE OSTI2022

Flux Eruption Events Drive Angular Momentum Transport in Magnetically Arrested Accretion Flows

We evolve two high-resolution general relativistic magnetohydrodynamic simulations of advection-dominated accretion flows around nonspinning black holes (BHs), each over a duration ~3 × 10 5 GM BH /c 3 . One model captures the evolution of a weakly magnetized (SANE) disk and the other that of a magnetically arrested disk (MAD). Magnetic flux eruptions in the MAD model push out gas from the disk and launch strong winds with outflow efficiencies at times reaching 10% of the incoming accretion power. Despite the substantial power in these winds, average mass outflow rates remain low out to a radius ~100GM BH /c 2 , only reaching ~60%–80% of the horizon accretion rate. The average outward angular momentum transport is primarily radial in both modes of accretion, but with a clear distinction: magnetic flux eruption–driven disk winds cause a strong vertical flow of angular momentum in the MAD model, while for the SANE model, the magnetorotational instability (MRI) moves angular momentum mostly equatorially through the disk. Further, we find that the MAD state is highly transitory and nonaxisymmetric, with the accretion mode often changing to a SANE-like state following an eruption before reattaining magnetic flux saturation with time. The Reynolds stress changes directions during such transitions, with the MAD (SANE) state showing an inward (outward) stress, possibly pointing to intermittent MRI-driven accretion in MADs. Pinning down the nature of flux eruptions using next-generation telescopes will be crucial in understanding the flow of mass, magnetic flux, and angular momentum in sub-Eddington accreting BHs like M87* and Sagittarius A*.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Adaptive Data-Driven Model Predictive Control for Heat Pipe Microreactors

To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Adaptable Data Driven Model Predictive Control for Heat Pipe Microreactors

To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

How can an ecosystem approach support integrated management of marine renewable energy? An initial assessment from an environmental point of view

With the increasing installation of marine renewable energy (MRE) devices in areas already subject to multiple anthropogenic activities and environmental changes, it is necessary to develop tools and methods for the integrated management of marine ecosystems. The ecosystem approach is a holistic environmental management method that considers all components of an ecosystem. The ecosystem approach has demonstrated utility in the application to various anthropogenic activities and is relevant for consideration within the context of MRE. Indeed, many of the effects observed on marine ecosystems from those other activities are also applicable to MRE development. This review is an initial assessment where we summarize the potential effects of MRE development on marine ecosystems and propose schematic frameworks for applying the ecosystem approach to MRE. We also provide a non-exhaustive list of commonly used models pertinent to the ecosystem approach and associated with several reference studies. An outline of core questions that can currently be answered using available modeling tools central to the ecosystem approach is provided, along with recommendations for the application of this approach to the MRE context. Further, we identify key knowledge gaps and areas that require additional investigation for meaningful application of the ecosystem approach to MRE development. Our recommendations mainly concern the current limitations of applying the ecosystem approach to concrete cases, such as consolidating knowledge of the effects of MRE on the local environment, the need to obtain fine-scale data, considering effects at different spatiotemporal scales, and, finally, the need for an interdisciplinary vision.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Reliability-based hull geometry optimisation of a point-absorber wave energy converter with power take-off structural reliability objectives

Recent studies have focused on optimising wave energy converter (WEC) designs, maximising their power performance and techno-economic feasibility. Reliability has yet to be fully considered in these formulations, despite its impact on cost and performance. In this study, this gap is addressed by developing a reliability-based design optimisation framework for WEC hull geometries to explore the trade-off between power performance and power take-off (PTO) system damage equivalent loading (DEL). Optimised hull geometries for two sites are considered (from the centre of the North Sea and off the west coast of Norway), and two directions of motions (heave and surge). Results indicate that site characteristics affect the potential power production and DEL for an optimal WEC design. These are also affected by the direction of motion for power extraction, which also significantly changes optimal hull shape characteristics. Optimal surging WEC designs have edges facing oncoming wave directions, while heaving WECs have pointed bottoms, both to streamline movement. Larger, more convex WECs result in greater power production and DEL, while smaller, more concave WECs result in lesser power production and DEL. These findings underline the importance of considering WEC hull geometry in early design processes to optimise cost, power production, and reliability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Temporal variation in skin microbiota of cohabitating amphibians

Temporal changes and transmission patterns in host-associated microbial communities have important implications for host health. The diversity of amphibian skin microbial communities is associated with disease outcome in amphibians exposed to the fungal pathogen Batrachochytrium dendrobatidis (Bd). To successfully develop conservation strategies against Bd, we need a comprehensive understanding of how skin microbes are maintained and transmitted over time within populations. Here we used 16S rRNA sequence analysis to compare Epipedobates anthonyi frogs housed with one conspecific to frogs housed singly at four time points over the course of 1 year. We found that both α and β diversity of frog skin bacterial communities changed significantly over the course of the experiment. Specifically, we found that bacterial communities of cohabitating frogs became more similar over time. We also observed that some bacterial taxa were differentially abundant between frogs housed singly and frogs housed with a conspecific. These results suggest that conspecific contact may play a role in mediating amphibian skin microbial diversity and that turnover of skin microbial communities can occur across time. Our findings provide rationale for future studies exploring horizontal transmission as a potential mechanism of host-associated microbial maintenance in amphibians.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A kinetic model for simulating non-equilibrium mass transport in oxides applied to hematite growth under irradiation

We propose an approach to simulating the dynamic evolution and transport of charged point defects within and through the oxide scales that form during corrosion. The method follows the cluster dynamics formalism widely adopted for radiation damage in solids, which can apply in both quasi-static and far from equilibrium conditions, such as in radiation environments. By treating each charged defect as a cluster of an atomic defect and associated unit charges, the proposed model flexibly allows charge state transitions and shifts in the Fermi level by absorption and emission of charge carriers from point defects in a reaction network with rates constrained by local equilibrium. Applying this model to hematite predicts changes in self-diffusion and oxidation kinetics in irradiation environments, surprisingly showing reduced oxidation rates in many conditions, despite enhanced self-diffusion. In conclusion, the origin of this effect lies in a change in Fermi level induced by excess vacancies formed under irradiation, which in turn suppresses the transport of cation interstitials which facilitate hematite growth.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of controlled magnetic island bifurcation on electron diffusion

Magnetic islands strongly influence cross-field electron transport in magnetized plasmas. In particular, bifurcations of the island topology modify the number and location of O-points, X-points, and separatrix boundaries, thereby altering diffusion pathways. In recent DIII-D experiments, external magnetic perturbations were used to rotate and periodically bifurcate the island on the q = 2 surface, causing a switchback between a q = 2/1-dominated structure and a narrower q = 4/2-dominated structure. To investigate how this topological change affects electron transport, we employ the field line tracing code TRIP3D with an implemented collisional operator. Thermal, tracer electrons launched from O-points, X-points, and outside separatrix boundaries reveal distinct diffusion regimes, including classical, subdiffusive, and superdiffusive behavior, depending on both the dominant island mode and launch location. These results suggest that island bifurcation can alter electron diffusion across rational surfaces, with direct implications for particle confinement. While the present work emphasizes diffusion as a general framework, the findings provide insight into the conditions under which electron trapping into an island or stochastization of the island's separatrix can enable additional mechanisms, such as the generation of energetic electrons.

DIII-D↗
DOE OSTI2021

Energy Exascale Earth System Model v2.0

First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.

E3SM Project, DOE↗