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At least 91 records · Page 5

Flexible User-Defined Domain Decomposition in Kilometer-Scale E3SM Land Model Simulation

The Energy Exascale Earth System Model (E3SM) Land Model (ELM) has been extended to kilometer-scale (km-ELM) resolutions, enabling high-fidelity simulations of terrestrial processes at 1 km x 1 km grid spacing. In ELM, domain decomposition partitions the computational domain across processors, ensuring efficient parallel execution. Currently, round-robin decomposition is applied, providing a straightforward way to distribute computational workload. As ELM continues evolving at the kilometer-scale (km-scale), particularly with integrating lateral flow modeling, decomposition strategies must also account for the increased workload and data movement. This paper introduces a flexible user-defined domain decomposition framework, allowing users to customize domain partitioning based on application requirements. The impact of different decomposition strategies is evaluated across various applications concerning computation, communication, and I/O. Results demonstrate that while 1D partitioning yields superior I/O performance, k-nearest neighbors (KNN) clustering effectively reduces inter-process communication overhead. This study lays the groundwork for scalable partitioning in large-scale land surface simulations, enhancing next-generation Earth system modeling.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗

Enabling kilometer-scale E3SM land model simulation over North America: A new integrated framework solution

This study introduces a novel framework designed to enhance the performance, scalability, and portability of the kilometer-scale E3SM Land Model (km-ELM) within the E3SM modeling infrastructure. By seamlessly integrating cutting-edge data tools, we address existing challenges such as slow performance, limited scalability, and difficulties in software integration in current data-driven ELM simulation over large geographic areas. Our innovative approach leverages the KiloCraft data toolkit to generate unified inputs for simulations ranging from a single-cite case, to a 72,083-cell regional case to a continental configuration encompassing 21.6 million land grid cells at a 1 km × 1 km resolution. We conduct extensive strong- and weak-scaling experiments on three state-of-the-art supercomputers, utilizing up to 100,800 CPU cores across 2400 compute nodes to evaluate end-to-end metrics including wall-clock time, simulation-years-per-day (SYPD), initialization costs, and I/O throughput. Our results reveal the land (LND) component’s efficient scaling, demonstrating near-ideal weak scaling and strong-scaling parallel efficiencies reaching up to 87% at 50,400 cores. We confirm portability and reproducibility through bitwise-equivalent outputs across different machines using identical inputs over supported machines. Notably, at extreme scales, we identify I/O as a critical bottleneck and that leads to effective solution with the SCORPIO/ADIOS stack. Collectively, these findings validate the deployment of km-ELM at a continental scale with high parallel efficiency and provide essential guidance on configuration, decomposition, and I/O settings for optimized kilometer-scale land simulations in E3SM. This work emphasizes the innovative design and practical solutions that enhance the operational capabilities of km-ELM, focusing on software performance and scalability while leaving detailed scientific evaluations of simulated land processes for future investigations.

E3SM land model (ELM), km-ELM, scalability, perfor↗

Validation of Finite Element Crash Test Dummy Models for Predicting Orion Crew Member Injuries During a Simulated Vehicle Landing

A series of crash tests were conducted with dummies during simulated Orion crew module landings at the Wright-Patterson Air Force Base. These tests consisted of several crew configurations with and without astronaut suits. Some test results were collected and are presented. In addition, finite element models of the tests were developed and are presented. The finite element models were validated using the experimental data, and the test responses were compared with the computed results. Occupant crash data, such as forces, moments, and accelerations, were collected from the simulations and compared with injury criteria to assess occupant survivability and injury. Some of the injury criteria published in the literature is summarized for completeness. These criteria were used to determine potential injury during crew impact events.

Tabiei, Al↗

Videopanorama Frame Rate Requirements Derived from Visual Discrimination of Deceleration During Simulated Aircraft Landing

In order to determine the required visual frame rate (FR) for minimizing prediction errors with out-the-window video displays at remote/virtual airport towers, thirteen active air traffic controllers viewed high dynamic fidelity simulations of landing aircraft and decided whether aircraft would stop as if to be able to make a turnoff or whether a runway excursion would be expected. The viewing conditions and simulation dynamics replicated visual rates and environments of transport aircraft landing at small commercial airports. The required frame rate was estimated using Bayes inference on prediction errors by linear FRextrapolation of event probabilities conditional on predictions (stop, no-stop). Furthermore estimates were obtained from exponential model fits to the parametric and non-parametric perceptual discriminabilities d' and A (average area under ROC-curves) as dependent on FR. Decision errors are biased towards preference of overshoot and appear due to illusionary increase in speed at low frames rates. Both Bayes and A - extrapolations yield a framerate requirement of 35 < FRmin < 40 Hz. When comparing with published results [12] on shooter game scores the model based d'(FR)-extrapolation exhibits the best agreement and indicates even higher FRmin > 40 Hz for minimizing decision errors. Definitive recommendations require further experiments with FR > 30 Hz.

deceleration perception↗

Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Altogether, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗

CFD Simulations of Landing and Takeoff CRM High-Lift Configurations

Numerical simulations have been performed for a conventional high-lift version of the Common Research Model (CRM) model corresponding to landing and take- off configurations. Computed values of lift and drag for the landing configuration are compared with the experimental data acquired in the 14- by 22-Foot Subsonic Tunnel (14×22) at the NASA Langley Research Center (LaRC). Simulations replicated the experimentally observed improvements in the lift characteristics in the presence of a nacelle chine. Flow visualization images indicate that vortices generated by the nacelle chine reduce flow separation regions on the upper surface of the wing at higher angles of attack. Based on such observations, the take-off configuration considered is also equipped with a nacelle chine, and testing of this configuration is planned in the 14×22 tunnel in near future. Preliminary solutions are also presented to explore the feasibility of using a localized flap gap blowing (LFGB) active flow control concept for improving the aerodynamic performance at take-off conditions.

aerodynamics↗

CFD Simulations of Landing and Takeoff CRM High-Lift Configurations

Numerical simulations have been performed for a conventional high-lift version of the Common Research Model (CRM) model corresponding to landing and take- off configurations. Computed values of lift and drag for the landing configuration are compared with the experimental data acquired in the 14- by 22-Foot Subsonic Tunnel (14×22) at the NASA Langley Research Center (LaRC). Simulations replicated the experimentally observed improvements in the lift characteristics in the presence of a nacelle chine. Flow visualization images indicate that vortices generated by the nacelle chine reduce flow separation regions on the upper surface of the wing at higher angles of attack. Based on such observations, the take-off configuration considered is also equipped with a nacelle chine, and testing of this configuration is planned in the 14×22 tunnel in near future. Preliminary solutions are also presented to explore the feasibility of using a localized flap gap blowing (LFGB) active flow control concept for improving the aerodynamic performance at take-off conditions.

aerodynamics↗

Prediction of Hydrological Drought: What Can We Learn From Continental-Scale Offline Simulations?

Land surface model experiments are used to quantify, across the coterminous United States, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Forecasted streamflows are compared to naturalized streamflow observations where available and to synthetic (model-generated) streamflow data elsewhere. We find that snow initialization has a major impact on skill in the mountainous western U.S. and in a portion of the northern Great Plains; a mid-winter (January 1) initialization of snow in these areas leads to significant skill in the spring melting season. Soil moisture initialization also contributes to skill, and although the maximum contributions are not as large as those seen for snow initialization, the soil moisture contributions extend across a much broader geographical area. Soil moisture initialization can contribute to skill at long leads (up to 5 or 6 months), particularly for forecasts issued during winter.

Koster, Randal↗

Comparison of Boeing 777 Landing Gear Noise Simulations with Flight Test Data

Acoustic phased microphone array measurements of aircraft flyover noise acquired during the 2005 Quiet Technology Demonstrator II test were used to assess the accuracy of high-fidelity, full-scale simulations of landing gear noise produced by a large civilian aircraft. The simulations, conducted with the lattice Boltzmann solver PowerFLOW®, used a highly accurate digital model of a Boeing 777-300ER aircraft with the nose and main landing gear components replicating the full-scale geometries. The simulations were performed for aircraft parameters that matched those recorded during the flyover test conditions. For benchmarking purposes, several aircraft configurations were simulated: a) nose landing gear deployed with main landing gear and wing high-lift devices stowed, b) nose and main landing gear deployed with wing high-lift devices stowed and c) nose and main landing gear with wing high-lift devices deployed. To facilitate direct comparison with measured data, the simulated data sets were used to generate synthetic pressure records at the same array microphone locations as those used during the flight test. Broadly self-consistent beamforming techniques and procedures were used to process the synthetic pressure records and the measured data. Integration of select regions of the beamform maps containing the nose or main landing gear yielded good agreement between predicted and measured integrated far-field spectra for forward directivity angles where airframe noise is more prominent.

airframe noise↗

Evaluation of air–soil temperature relationships simulated by land surfacemodels during winter across the permafrost region

A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (Δ T ; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C -1 ), and in the relationship between Δ$T$ and snow depth. The observed relationship between Δ$T$ and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km 2 ). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.

58 GEOSCIENCES↗

Daily Precipitation Frequency Distributions Impacts on Land-Surface Simulations of CONUS

Many precipitation-driven data products from land data assimilation systems support assessments of droughts, floods, and other societally-relevant land-surface processes.The accumulated precipitation used as input to these products has a significant impacton water budgets; however, the effects of daily distribution of precipitation on theseproducts are not well known. A comparison of the Integrated Multi-satellite Retrievalsfor GPM (IMERG) and Climate Hazards Group InfraRed Precipitation with Stationsversion 2 (CHIRPS2) rainfall products over the continentalUnited States (CONUS) wasperformed to quantify the impacts of the daily distributionof precipitation on biases anderrors in soil moisture, runoff, and evapotranspiration (ET). Since the total accumulatedprecipitation between the IMERG and CHIRPS product differed, a third precipitationproduct, CHIRPS-to-IMERG (CHtoIM), was produced that usedCHIRPS2 accumulatedprecipitation totals and the daily precipitation frequency distribution of IMERG. Thisnew product supported a controlled analysis of the impact ofprecipitation frequencydistribution on simulated hydrological fields. The CHtoIM had higher occurrences ofprecipitation in the 0–5 mm day−1range, with a lower occurrence of dry days, whichdecreased soil moisture and surface runoff in the land-surface model. The surface soillayer had a tendency to reach saturation more often in the CHIRPS2 simulations, wherethe number of moderate to heavy precipitation days (>5mm day−1) was increased. Usingthe blended CHtoIM product as input reduced errors in surface soil moisture by 5–15%when compared to Soil Moisture Active/Passive (SMAP) data.Similarly, ET errors werealso slightly decreased (∼2%) when compared to SSEBop data. Moderate changes indaily precipitation distributions had a quantifiable impact on soil moisture, runoff, andET. These changes usually improved the model when compared to other modeled andobservational datasets, but the magnitude of the improvements varied by region andtime of year.

Daniel P Sarmiento↗

Lunar Lander Landing Modeling and Simulation in Simscape

The landing gear is a critical subsystem of a lander for a successful landing on the moon or a planet. During a landing event, structural loading, energy absorption and toppling stability are important factors for the landing gear development. These aspects can be studied using simulations. The landing gear comprising the primary struct, secondary structs, footpad, and joints, is easily modeled using Simscape Multibody toolbox. The energy absorption mechanisms in the structs is readily modeled using Simulink and Multibody blocks based on the relative motions of the inner and outer cylinder of the structures. During touchdown, the footpads strike the lunar surface, and the contact forces can be modeled including the soil mechanical properties. Slosh dynamics are included using a mechanical pendulum model. Tip-over controllers are developed using Simulink blocks and toolboxes. This model was intensively tested manually then additionally with Monte Carlo simulation. It offers the opportunity for landing stability study, i.e. the max slope a lander can land without tipping over in 3D realistic landing situations.

Wei Wu↗

Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO 2 observations from a dense tower network and aircraft campaigns over Oregon

Here, the vast forests and natural areas of the Pacific Northwest comprise one of the most productive ecosystems in the northern hemisphere. The heterogeneous landscape of Oregon poses a particular challenge to ecosystem models. We present a framework using a scaling factor Bayesian inversion to improve the modeled atmosphere-biosphere exchange of carbon dioxide. Observations from 5 CO/CO 2 towers, eddy covariance towers, and airborne campaigns were used to constrain the Community Land Model CLM4.5 simulated terrestrial CO 2 exchange at a high spatial and temporal resolution (1/24°, 3-hourly). To balance aggregation errors and the degrees of freedom in the inverse modeling system, we applied an unsupervised clustering approach for the spatial structuring of our model domain. Data from flight campaigns were used to quantify the uncertainty introduced by the Lagrangian particle dispersion model that was applied for the inversions. The average annual statewide net ecosystem productivity (NEP) was increased by 32% to 29.7 TgC per year by assimilating the tropospheric mixing ratio data. The associated uncertainty was decreased by 28.4% to 29%, on average over the entire Oregon model domain with the lowest uncertainties of 11% in western Oregon. The largest differences between posterior and prior CO 2 fluxes were found for the Coast Range ecoregion of Oregon that also exhibits the highest availability of atmospheric observations and associated footprints. In this area, covered by highly productive Douglas-fir forest, the differences between the prior and posterior estimate of NEP averaged 3.84 TgC per year during the study period from 2012 through 2014.

54 ENVIRONMENTAL SCIENCES↗

Managing complexity in simulations of land surface and near-surface processes

Increasing computing power and the growing role of simulation in Earth systems science have led to an increase in the number and complexity of processes in modern simulators. We present a multiphysics framework that specifies interfaces for coupled processes and automates weak and strong coupling strategies to manage this complexity. Process management is enabled by viewing the system of equations as a tree, where individual equations are associated with leaf nodes and coupling strategies with internal nodes. A dynamically generated dependency graph connects a variable to its dependencies, streamlining and automating model evaluation, easing model development, and ensuring models are modular and flexible. Additionally, the dependency graph is used to ensure that data requirements are consistent between all processes in a given simulation. Here we discuss the design and implementation of these concepts within the Arcos framework, and demonstrate their use for verification testing and hypothesis evaluation in numerical experiments.

54 ENVIRONMENTAL SCIENCES↗