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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model

ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.

17 WIND ENERGY↗
DOE OSTI2023

Large eddy simulation of atmospheric boundary layer flow over complex terrain in comparison with RANS simulation and on-site measurements under neutral stability condition

Large eddy simulation (LES) of the atmospheric boundary layer (ABL) flow over complex terrain is presented with a validation using meteorological tower (met-tower) data through an improved neutral stability sampling approach. The proposed stability sampling procedure includes a condition based on the most-likely occurrence time-periods of the neutral ABL and reduces the variabilities of the conditional wind statistics calculated at the met-towers in comparison to our previous work. The ABL flow simulations are carried out over a potential wind site with a prominent hill based using the OpenFOAM-based simulator for on/off-shore wind farm applications by applying the Lagrangian-averaged scale-invariant dynamic sub-grid scale turbulence model. A low-dissipative scale-selective discretization scheme for the non-linear convection term in the LES governing equation is adopted implicitly to ensure both the second-order accuracy and bounded solution. The LES inflow is generated through a precursor method with a “tiling” approach based on the flow driving parameters obtained from a corresponding Reynolds-averaged Navier–Stokes (RANS) simulation. Overall, the averaged wind velocity profiles predicted by the LES approach at all met-tower locations show a similar tendency as the RANS results, which are also in reasonable agreement with the met-tower data. An obvious difference in wind speed standard deviation profiles is seen between LES and RANS, especially at regions downstream of the hill edge, where the LES shows under-predicted results at the highest measurement levels in comparison to the tower data. The computational costs of the LES are found to be about 20 times higher than the RANS simulations.

Energy & Fuels↗
DOE OSTI2022

The leaf economics spectrum of triploid and tetraploid C 4 grass Miscanthus x giganteus

Abstract The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C 3 species grown under natural ecosystems. However, the specific contribution of C 4 species to the global LES is studied less widely. C 4 species have a CO 2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C 4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M .× giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M .× giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C 4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C 3 species to include C 4 crops, these findings highlight that M .× giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Impacts of stochastic coalescence variability on warm rain initiation using Lagrangian microphysics in box and large-eddy simulations

Various coalescence methods for Lagrangian microphysics schemes are tested in box and large-eddy simulation (LES) models, including the stochastic all-or-nothing super-droplet method (SDM) and a version of SDM (dSDM) that applies a fractional approach similar to the average impact method. In LES, variabilities driven by microphysics and by flow realizations are separated using the “piggybacking” technique. Rain initiation averaged over many realizations of the box model is delayed and rain variability increases as the number of super-drops per collision volume ( N SD ) is decreased using SDM. In contrast, rain initiation time using SDM in LES is insensitive to N SD for 32 ≤ N SD ≤ 512. This is explained through the interaction between LES grid boxes, each acting as a separate collision volume. Variability across the ensemble of LES collision volumes using SDM results in rain quickly initiating in some of the LES grid cells at low N SD and leading to a similar overall timing of rain initiation from the cloud compared to simulations with high N SD . There is a ~20% decrease in the total rain mass and mean rain flux as N SD is increased from 32 to 256, with little additional change as N SD is increased from 256 to 512. The fractional coalescence approach in dSDM leads to reduced microphysical variability and a 15-18 min delay in rain initiation compared to SDM. Finally, an additional LES ensemble with microphysical variability feeding back to the dynamics shows that flow variability dominates the impact of microphysical variability on rain properties. Thus, flow variability must be constrained to isolate impacts of microphysical variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data for The Leaf Economics Spectrum of Triploid and Tetraploid C4 Grass Miscanthus x giganteus

The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C3 species grown under natural ecosystems. However, the specific contribution of C4 species to the global LES is studied less widely. C4 species have a CO2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M. × giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M. × giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C3 species to include C4 crops, these findings highlight that M. × giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

Biomass Analytics↗
NASA NTRS1990

Effectiveness of the Space Shuttle anti-exposure system in a cold water environment

The purpose of this study was to evaluate the NASA Space Shuttle launch entry suit (LES) and raft for 24 h of protection against cold water immersion. Two configurations, the LES and the LES with raft (LES/r) were evaluated for antiexposure protection. Conditions were selected to simulate worst-case water and air temperatures along projected Space Shuttle ground tracks; i.e., water temperatures = 4.4 C, air temperature = 5.6 C, 1-foot waves (chop), and constant spray. Four males 31-44 years of age and one 32-year-old female were studied once in each configuration. Trials with and without a raft were scheduled for up to 24 and 6 h, respectively. Mean LES trial durations were 150 + or - 9 min and final rectal temperature (FRT) = 36.5 + or - 0.3 C. Mean LES/r trial durations were 398 + or - 126 min and FRT = 35.6 + or - 0.4 C. LES and LES/r trials were terminated for reaching FRT = 35.0 C or subject-requested termination due to discomfort. The longest LES and LES/r trials were terminated due to subject discomfort. Although not achieving the desired durations, the LES and LES/r did prove capable of protecting individuals, respectively, for up to 3 and 13.5 h. Since the longest runs were terminated due to subjective tolerance, actual survival times greater than 3 and 13.5 h could be expected.

Bagian, James P.↗
NASA NTRS2001

A Hybrid Numerical Method for Turbulent Mixing Layers

A hybrid method has been developed for simulations of compressible turbulent mixing layers. Such mixing layers dominate the flows in exhaust systems of modern day aircraft and also those of hypersonic vehicles currently under development. The method configurations in which a dominant structural feature provides an unsteady mechanism to drive the turbulent development in the mixing layer. The hybrid method uses a Reynolds-averaged Navier-Stokes (RANS) procedure to calculate wall bounded regions entering a mixing section, and a Large Eddy Simulation (LES) procedure to calculate the mixing dominated regions. A numerical technique was developed to enable the use of the hybrid RANS-LES method on stretched, non-Cartesian grids. Closure for the RANS equations was obtained using the Cebeci-Smith algebraic turbulence model in conjunction with the wall-function approach of Ota and Goldberg. The wall-function approach enabled a continuous computational grid from the RANS regions to the LES region. The LES equations were closed using the Smagorinsky subgrid scale model. The hybrid RANS-LES method is applied to a benchmark compressible mixing layer experiment. Preliminary two dimensional calculations are used to investigate the effects of axial grid density and boundary conditions. Vortex shedding from the base region of a splitter plate separating the upstream flows was observed to eventually transition to turbulence. The location of the transition, however, was much further downstream than indicated by experiments. Actual LES calculations, performed in three spatial directions, also indicated vortex shedding, but the transition to turbulence was found to occur much closer to the beginning of the mixing section. which is in agreement with experimental observations. These calculations demonstrated that LES simulations must be performed in three dimensions. Comparisons of time-averaged axial velocities and turbulence intensities indicated reasonable agreement with experimental data.

Georgiadis, Nicholas J.↗
NASA NTRS2003

On the Computation of Space-Time Correlations by Large-Eddy Simulation

Numerical comparisons in decaying isotropic turbulence suggest that there exist discrepancies in time correlations evaluated by DNS and LES using eddy-viscosity-type SGS models. This is consistent with the previous observations in forced isotropic turbulence. Therefore, forcing is not the main cause of the discrepancies. Comparisons among different SGS models in the LES also indicate that the model choice affects the time correlations in the LES. The multi-scale LES method using the dynamic Smagorinsky model on the small scale equation is the most accurate of the all models, the classic Smagorinsky model is the least accurate and the dynamic Smagorinsky model and spectral eddy viscosity model give intermediate results with small differences. The generalized sweeping hypothesis implies that time correlations in decaying isotropic turbulence are mainly determined by the instantaneous energy spectra and sweeping velocities. The analysis based on the sweeping hypothesis explains the discrepancies in our numerical simulations: the LES overpredicts the decorrelation time scales because the sweeping velocities are smaller than the DNS values, and underpredicts the magnitudes of time correlations because the energy spectrum levels are lower than the DNS ones. Since the sweeping velocity is determined by the energy spectra, one concludes that an accurate prediction of the instantaneous energy spectra guarantees the accuracy of time correlations. An analytical expression of sound power spectra based on Lighthill's theory and the quasi-normal closure assumption suggests that the sound power spectra are sensitive to errors in time correlations. Small errors in time correlations can cause significant errors in the sound power spectra, which exhibit a sizable drop at moderate to high frequencies accompanied by a shift of the peaks to lower frequencies. Based on the above analysis, two possible ways to improve the acoustic power spectrum predictions can be considered. The first is to construct better SGS models to improve the LES accuracy for time correlations. The second is to remedy the temporal statistics of the Lighthill stress tensor in order to "recover" the contribution from the unresolved scales in LES to time correlations.

He, Guo-Wei↗
NASA NTRS2005

Consistent Large-Eddy Simulation of a Temporal Mixing Layer Laden with Evaporating Drops: A Posteriori Modelling - Part 2

Large-eddy simulation (LES) is conducted of a three-dimensional temporal mixing layer whose lower stream is initially laden with liquid drops which may evaporate during the simulation. The gas-phase equations are written in an Eulerian frame for two perfect gas species (carrier gas and vapour emanating from the drops), while the liquid-phase equations are written in a Lagrangian frame. The effect of drop evaporation on the gas phase is considered through mass, species, momentum and energy source terms. The drop evolution is modelled using physical drops, or using computational drops to represent the physical drops. Simulations are performed using various LES models previously assessed on a database obtained from direct numerical simulations (DNS). These LES models are for: (i) the subgrid-scale (SGS) fluxes and (ii) the filtered source terms (FSTs) based on computational drops. The LES, which are compared to filtered-and-coarsened (FC) DNS results at the coarser LES grid, are conducted with 64 times fewer grid points than the DNS, and up to 64 times fewer computational than physical drops. It is found that both constant-coefficient and dynamic Smagorinsky SGS-flux models, though numerically stable, are overly dissipative and damp generated small-resolved-scale (SRS) turbulent structures. Although the global growth and mixing predictions of LES using Smagorinsky models are in good agreement with the FC-DNS, the spatial distributions of the drops differ significantly. In contrast, the constant-coefficient scale-similarity model and the dynamic gradient model perform well in predicting most flow features, with the latter model having the advantage of not requiring a priori calibration of the model coefficient. The ability of the dynamic models to determine the model coefficient during LES is found to be essential since the constant-coefficient gradient model, although more accurate than the Smagorinsky model, is not consistently numerically stable despite using DNS-calibrated coefficients. With accurate SGS-flux models, namely scale-similarity and dynamic gradient, the FST model allows up to a 32-fold reduction in computational drops compared to the number of physical drops, without degradation of accuracy; a 64-fold reduction leads to a slight decrease in accuracy.

two-phase flow↗
NASA NTRS2019

Effect of Spatial Filtering in Implicit Large-Eddy Simulations of Separated Flows

The relatively high Reynolds number of turbulent flows encountered in various applications puts these problems well beyond the reach of direct numerical simulation (DNS) at present. Meanwhile, lower-fidelity Reynolds-averaged Navier-Stokes (RANS) calculations are known to be not accurate enough in complex problems, such as smooth-body flow separation and other flows involving highly-unsteady phenomena. Hence, given the current infeasibility of DNS and the unsatisfactory performance of RANS, intermediate techniques such as large-eddy simulation (LES) and hybrid RANS-LES, whose fidelity lie between RANS and DNS, have received much attention for application to various problems of practical importance. Modeling of the effect of missing scales on resolved scales, also known as subgrid-scale (SGS) modeling, is an important subject for LES. SGS models can be broadly categorized as explicit or implicit approaches. The explicit approach is based on an SGS model that explicitly appears in the governing equations expressed in the form of so-called “filtered Navier-Stokes equations”, which describe the evolution of the turbulence scales resolved by the LES grid. The effect of the scales unresolved by the grid is represented by the SGS model. The implicit modeling approach, on the other hand, does not employ an explicit model but instead treats the intrinsic dissipation of the numerical discretization scheme as an implicit SGS model. An LES without an explicit SGS model is commonly termed as an implicit LES (ILES). The relative merits of one SGS modeling approach over another is a subject of ongoing debate. We have opted to employ an ILES methodology, based on high-order compact finite-difference and spatial filtering schemes, in our recent investigations of separated flow problems [1, 2]. Further discussion of our preference of ILES over explicit LES is provided in Uzun and Malik [2]. The spatial filtering operation, described in the next section, is treated as an implicit SGS model for the ILES. Some observations made during the course of our recent investigations, which pointed out to excessive numerical dissipation in certain parts of the flowfield, prompted us to take a closer look at the potential effect of the spatial filter on ILES predictions. This technical note is therefore devoted to spatial filter effects in the context of a high Reynolds number, transonic shock-induced separated flow.

Ali Uzun↗
NASA NTRS2021

Large-Eddy Simulations of Marine Boundary-Layer Clouds Associated With Cold Air Outbreaks During the Activate Campaign – Part 1: Case Setup and Sensitivities to Large-Scale Forcings

Large-eddy simulation (LES) is able to capture key boundary-layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LES simulations. We derive these quantities from measurements and reanalysis obtained for two cold air outbreak (CAO) events during Phase I of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) in February-March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from the reanalysis data ERA5 agree reasonablywell with those derived fromACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time evolving heat fluxes, wind and advective tendencies profiles from ERA5 reanalysis data to drive the LES.We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 reanalysis data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LES simulations. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path imulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol-cloud-meteorology interactions using LES informed and evaluated by ACTIVATE field measurements.

Large-eddy simulation↗
DOE OSTI2021

Seasonal Cycle of Idealized Polar Clouds: Large Eddy Simulations Driven by a GCM

The uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step toward improved process understanding, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized GCM are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme without water vapor and cloud feedbacks allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes. This enables the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. Furthermore, we show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low-level clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large-scale advection of moisture provides the main source of water vapor for the liquid-containing clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
DOE OSTI2021

Adaptive downstream tensorial eddy viscosity for hybrid large‐eddy simulations‐Reynolds‐averaged‐Navier–Stokes simulations

An adaptive method is developed to improve the accuracy of eddy‐viscosity Reynolds‐averaged‐Navier–Stokes (RANS) model in hybrid large‐eddy simulations (LES)‐RANS simulations by using available upstream LES results. The method first gets the tensorial eddy viscosity from the upstream LES solution at the LES‐RANS interface and then uses that information to improve the downstream RANS model by invoking the weak‐equilibrium assumption. The proposed method was evaluated via two test problems—flow in a channel and over a periodic hill. Results obtained show the proposed approach to increase the accuracy and stability of hybrid LES‐RANS simulations. Since the modification of the downstream RANS model is based on the tensorial eddy viscosity from the upstream LES solution, the method is adaptive to the problem being studied.

Zhang, Wanjia↗
DOE OSTI2023

Reversible and Irreversible Layer Edge Relaxation in Laser–Radiation–Hardened 2D Organic–Inorganic Perovskite Crystals

The layer edge states or low energy state (LES) in 2D hybrid organic–inorganic perovskites demonstrate a prolonged carrier lifetime for better performance of optoelectronic devices. However, the fundamental understanding of LES in 2D perovskites is still inconclusive. Herein, a photoluminescence (PL) study of LES in 2D Ruddlesden–Popper perovskites is presented with n = 2 and n = 3 from their cleaved cross sections that are more stable than the natural edge. The PL measurements clearly observe reversible, and irreversible surface relaxations (case I and case II) in three laser intensity ranges, further supported by a PL excitation cycle from low to high laser intensity, and vice versa. The PL wavelength of LES is tunable with laser intensity and blueshifts with increasing laser intensity during irreversible surface relaxation process (case I). Fluorescence lifetime imaging (FLIM) shows that the LES has a longer lifetime than the band-edge emission in the sample without a photodegradation, while the BE lifetime becomes relatively longer in the area with a photodegradation. Furthermore, the presented laser tunable LES and the related irreversible relaxation process provide a new insight that can help improve the photostability in 2D perovskites and understand roles of LESs in optoelectronic device performance.

2D organic-inorganic perovskite↗
DOE OSTI2021

Coupling Mesoscale Budget Components to Large-Eddy Simulations for Wind-Energy Applications

To simulate the airflow through a wind farm across a wide range of atmospheric conditions, microscale models (e.g., large-eddy simulation, LES, models) have to be coupled with mesoscale models, because microscale models lack the atmospheric physical processes to represent time-varying local forcing. Here we couple mesoscale model outputs to a LES solver by applying mesoscale momentum- and temperature-budget components from the Weather Research and Forecasting model to the governing equations of the Simulator fOr Wind Farm Applications model. We test whether averaging the budget components affects the LES results with regard to quantities of interest to wind energy. Our study focuses on flat terrain during a quiescent diurnal cycle. The simulation results are compared with observations from a 200-m tall meteorological tower and a wind-profiling radar, by analyzing time series, profiles, rotor-averaged quantities, and spectra. However, while results show that averaging reduces the spatio-temporal variability of the mesoscale momentum-budget components, when coupled with the LES model, the mesoscale bias (in comparison with observations of wind speed and direction, and potential temperature) is not reduced. In contrast, the LES technique can correct for shear and veer. In both cases, however, averaging the budget components shows no significant impact on the mean flow quantities in the microscale and is not necessary when coupling mesocale budget components to the LES model.

17 WIND ENERGY↗
DOE OSTI2025

A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials

Most current machine learning interatomic potentials (MLIPs) rely on short-range approximations, without explicit treatment of long-range electrostatics. To address this, we recently developed the Latent Ewald Summation (LES) method, which infers electrostatic interactions, polarization, and Born effective charges (BECs), just by learning from energy and force training data. Here, in this study, we present LES as a standalone library, compatible with any short-range MLIP, and demonstrate its integration with methods such as MACE, NequIP, Allegro, CACE, CHGNet, and UMA. We benchmark LES-enhanced models on distinct systems, including bulk water, polar dipeptides, and gold dimer adsorption on defective substrates, and show that LES not only captures correct electrostatics but also improves accuracy. Additionally, we scale LES to large and chemically diverse data by training MACELES-OFF on the SPICE set containing molecules and clusters, making a universal MLIP with electrostatics for organic systems, including biomolecules. MACELES-OFF is more accurate than its short-range counterpart (MACE-OFF) trained on the same data set, predicts dipoles and BECs reliably, and has better descriptions of bulk liquids. By enabling efficient long-range electrostatics without directly training on electrical properties, LES paves the way for electrostatic foundation MLIPs.

Kim, Dongjin [University of California, Berkeley, ↗
DOE OSTI2024

How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming.

54 ENVIRONMENTAL SCIENCES↗