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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Structure and thermodynamics of core-softened models for alcohols

The phase behavior and the fluid structure of coarse-grain models for alcohols are studied by means of reference interaction site model (RISM) theory and Monte Carlo simulations. Specifically, we model ethanol and 1-propanol as linear rigid chains constituted by three (trimers) and four (tetramers) partially fused spheres, respectively. Thermodynamic properties of these models are examined in the RISM context, by employing closed formulæ for the calculation of free energy and pressure. Gas-liquid coexistence curves for trimers and tetramers are reported and compared with already existing data for a dimer model of methanol. Critical temperatures slightly increase with the number of CH{sub 2} groups in the chain, while critical pressures and densities decrease. Such a behavior qualitatively reproduces the trend observed in experiments on methanol, ethanol, and 1-propanol and suggests that our coarse-grain models, despite their simplicity, can reproduce the essential features of the phase behavior of such alcohols. The fluid structure of these models is investigated by computing radial distribution function g{sub ij}(r) and static structure factor S{sub ij}(k); the latter shows the presence of a low−k peak at intermediate-high packing fractions and low temperatures, suggesting the presence of aggregates for both trimers and tetramers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2024

ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]

ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.

Horsey, Henry↗
DOE OSTI2017

Transitioning NWChem to the Next Generation of Manycore Machines

The NorthWest chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers [1-3]. It contains an umbrella of modules that today includes self-consistent eld (SCF), second order Møller-Plesset perturbation theory (MP2), coupled cluster (CC), multiconguration self-consistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real-time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics (AIMD), Car-Parrinello molecular dynamics (MD), classical MD, hybrid quantum mechanics molecular mechanics (QM/MM), hybrid ab initio molecular dynamics molecular mechanics (AIMD/MM), gauge independent atomic orbital nuclear magnetic resonance (GIAO NMR), conductor like screening solvation model (COSMO), conductor-like screening solvation model based on density (COSMO-SMD), and reference interaction site model (RISM) solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities [4]. Moreover, new capabilities continue to be added with each new release.

Bylaska, Eric J.↗
NASA NTRS1985

The Venus ionosphere

Physical properties of the Venus ionosphere obtained by experiments on the US Pioneer Venus and the Soviet Venera missions are presented in the form of models suitable for inclusion in the Venus International Reference Atmosphere. The models comprise electron density (from 120 km), electron and ion temperatures, and relative ion abundance in the altitude range from 150 km to 1000 km for solar zenith angles from 0 to 180 deg. In addition, information on ion transport velocities, ionopause altitudes, and magnetic field characteristics of the Venus ionosphere, are presented in tabular or graphical form. Also discussed is the solar control of the physical properties of the Venus ionosphere.

Bauer, S. J.↗
NASA NTRS1950

Investigation of the Model ME 210 in the Spin Wind Tunnel of the DVL: Model with Long Fuselage and with a VEE Tail - Report 4

After conclusion of the spin investigation of the model Me 210 with elongated fuselage and central vertical tail surfaces (model condition III; reference 3), tests were performed on the same model with a vee tail (model condition IV). Here the entire tail surfaces consist of only one surface with pronounced dihedral. Since the blanketing of the vertical tail surfaces by the horizontal tail surfaces, which may occur in case of standard tail surfaces, does not occur here, one could expect for this type of tail surface favorable spin characteristics, particularly with respect to rudder effectiveness for spin recovery. However, the test results did not confirm these expectations. The steady spin was shown to be very irregular; regarding rudder effectiveness the vee tail surfaces proved to be inferior even to standard tail surfaces, thus they represent the most unfavorable of the four fuselage and tail-surface combinations investigated so far.

Huffschmid, A↗
NASA NTRS2000

Application of Energy Integration Techniques to the Design of Advanced Life Support Systems

Exchanging heat between hot and cold streams within an advanced life support system can save energy. This savings will reduce the equivalent system mass (ESM) of the system. Different system configurations are examined under steady-state conditions for various percentages of food growth and waste treatment. The scenarios investigated represent possible design options for a Mars reference mission. Reference mission definitions are drawn from the ALSS Modeling and Analysis Reference Missions Document, which includes definitions for space station evolution, Mars landers, and a Mars base. For each scenario, streams requiring heating or cooling are identified and characterized by mass flow, supply and target temperatures and heat capacities. The Pinch Technique is applied to identify good matches for energy exchange between the hot and cold streams and to calculate the minimum external heating and cooling requirements for the system. For each pair of hot and cold streams that are matched, there will be a reduction in the amount of external heating and cooling required, and the original heating and cooling equipment will be replaced with a heat exchanger. The net cost savings can be either positive or negative for each stream pairing, and the priority for implementing each pairing can be ranked according to its potential cost savings. Using the Pinch technique, a complete system heat exchange network is developed and heat exchangers are sized to allow for calculation of ESM. The energy-integrated design typically has a lower total ESM than the original design with no energy integration. A comparison of ESM savings in each of the scenarios is made to direct future Pinch Analysis efforts.

Levri, Julie↗
DOE OSTI2016

Reference aquaplanet climate in the Community Atmosphere Model, Version 5

In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, including an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Evaluation of CASL boiling model for DNB performance in full scale 5x5 fuel bundle with spacer grids

As one of main tasks for FY17 CASL-THM activity, Evaluation study on applicability of the CASL baseline boiling model for 5x5 DNB application is conducted and the predictive capability of the DNB analysis is reported here. While the baseline CASL-boiling model (GEN- 1A) approach has been successfully implemented and validated with a single pipe application in the previous year’s task, the extended DNB validation for realistic sub-channels with detailed spacer grid configurations are tasked in FY17. The focus area of the current study is to demonstrate the robustness and feasibility of the CASL baseline boiling model for DNB performance in a full 5x5 fuel bundle application. A quantitative evaluation of the DNB predictive capability is performed by comparing with corresponding experimental measurements (i.e. reference for the model validation). The reference data are provided from the Westinghouse Electricity Company (WEC). Two different grid configurations tested here include Non-Mixing Vane Grid (NMVG), and Mixing Vane Grid (MVG). Thorough validation studies with two sub-channel configurations are performed at a wide range of realistic PWR operational conditions.

42 ENGINEERING↗
DOE OSTI2021

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Abstract Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade‐off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade‐off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rooftop unit comparison calculator: a framework for comparing performance of rooftop units with building energy simulation

The applications of building energy simulation (BES) in designing heating, ventilation, and air conditioning (HVAC) systems are limited by the high costs of developing simulation models and the lack of references for determining the model parameters. This paper presents a software framework for selecting designs for rooftop unit HVAC (RTU) systems with BES. Specifically, this framework reduces the cost of using BES by automating the generation of EnergyPlus models. It also employs a systematic method for determining model parameters based on well-accepted datasets. We applied this framework in a comprehensive assessment of an advanced design of RTU systems in which 478 EnergyPlus models were developed without human involvement. The assessment reveals that replacing a constant-speed fan/coil with a multiple-speed fan/coil may not guarantee better overall performance. In conclusion, it also suggests the benefits of replacing furnace coils with heat pumps are subject to utility cost, weather conditions, and heating load profiles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2012

Global 3-D Ionospheric Electron Density Reanalysis Based on Multisource Data Assimilation

We report preliminary results of a global 3-D ionospheric electron density reanalysis demonstration study during 2002-2011 based on multisource data assimilation. The monthly global ionospheric electron density reanalysis has been done by assimilating the quiet days ionospheric data into a data assimilation model constructed using the International Reference Ionosphere (IRI) 2007 model and a Kalman filter technique. These data include global navigation satellite system (GNSS) observations of ionospheric total electron content (TEC) from ground-based stations, ionospheric radio occultations by CHAMP, GRACE, COSMIC, SAC-C, Metop-A, and the TerraSAR-X satellites, and Jason-1 and 2 altimeter TEC measurements. The output of the reanalysis are 3-D gridded ionospheric electron densities with temporal and spatial resolutions of 1 h in universal time, 5deg in latitude, 10deg in longitude, and approx.30 km in altitude. The climatological features of the reanalysis results, such as solar activity dependence, seasonal variations, and the global morphology of the ionosphere, agree well with those in the empirical models and observations. The global electron content derived from the international GNSS service global ionospheric maps, the observed electron density profiles from the Poker Flat Incoherent Scatter Radar during 2007-2010, and foF2 observed by the global ionosonde network during 2002-2011 are used to validate the reanalysis method. All comparisons show that the reanalysis have smaller deviations and biases than the IRI-2007 predictions. Especially after April 2006 when the six COSMIC satellites were launched, the reanalysis shows significant improvement over the IRI predictions. The obvious overestimation of the low-latitude ionospheric F region densities by the IRI model during the 23/24 solar minimum is corrected well by the reanalysis. The potential application and improvements of the reanalysis are also discussed.

Xinan Yue↗
NASA NTRSDate not supplied

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗
NASA NTRS2011

Development of Head Injury Assessment Reference Values Based on NASA Injury Modeling

NASA is developing a new capsule-based, crewed vehicle that will land in the ocean, and the space agency desires to reduce the risk of injury from impact during these landings. Because landing impact occurs for each flight and the crew might need to perform egress tasks, current injury assessment reference values (IARV) were deemed insufficient. Because NASCAR occupant restraint systems are more effective than the systems used to determine the current IARVs and are similar to NASA s proposed restraint system, an analysis of NASCAR impacts was performed to develop new IARVs that may be more relevant to NASA s context of vehicle landing operations. Head IARVs associated with race car impacts were investigated by completing a detailed analysis of all of the 2002-2008 NASCAR impact data. Specific inclusion and exclusion criteria were used to select 4071 impacts from the 4015 recorder files provided (each file could contain multiple impact events). Of the 4071 accepted impacts, 274 were selected for numerical simulation using a custom NASCAR restraint system and Humanetics Hybrid-III 50th percentile numerical dummy model in LS-DYNA. Injury had occurred in 32 of the 274 selected impacts, and 27 of those injuries involved the head. A majority of the head injuries were mild concussions with or without brief loss of consciousness. The 242 non-injury impacts were randomly selected and representative of the range of crash dynamics present in the total set of 4071 impacts. Head dynamics data (head translational acceleration, translational change in velocity, rotational acceleration, rotational velocity, HIC-15, HIC-36, and the Head 3ms clip) were filtered according to SAE J211 specifications and then transformed to a log scale. The probability of head injury was estimated using a separate logistic regression analysis for each log-transformed predictor candidate. Using the log transformation constrains the estimated probability of injury to become negligible as IARVs approach zero. For the parameters head translational acceleration, head translational velocity change, head rotational acceleration, HIC-15, and HIC-36, conservative values (in the lower 95% confidence interval) that gave rise to a 5% risk of any injury occurring were estimated as 40.0 G, 7.9 m/s, 2200 rad/s2, 98.4, and 77.4 respectively. Because NASA is interested in the consequence of any particular injury on the ability of the crew to perform egress tasks, the head injuries that occurred in the NASCAR dataset were classified according to a NASA-developed scale (Classes I - III) for operationally relevant injuries, which classifies injuries on the basis of their operational significance. Additional analysis of the data was performed to determine the probability of each injury class occurring, and this was estimated using an ordered probit model. For head translational acceleration, head translational velocity change, head rotational acceleration, head rotational velocity, HIC-36, and head 3ms clip, conservative values of IARVs that produced a 5% risk of Class II injury were estimated as 50.7 G, 9.5 m/s, 2863 rad/s2, 11.0 rad/s, 30.3, and 46.4 G respectively. The results indicate that head IARVs developed from the NASCAR dataset may be useful to protect crews during landing impact.

Somers, Jeffrey T.↗
DOE OSTI2011

Quantum magnetism with polar alkali-metal dimers

We show that dipolar interactions between ultracold polar alkali-metal dimers in optical lattices can be used to realize a highly tunable generalization of the t-J model, which we refer to as the t-J-V-W model. The model features long-range spin-spin interactions J{sub z} and J{sub perpendicular} of XXZ type, long-range density-density interaction V, and long-range density-spin interaction W, all of which can be controlled in both magnitude and sign independently of each other and of the tunneling t. The spin's is encoded in the rotational degree of freedom of the molecules, while the interactions are controlled by applied static electric and continuous-wave microwave fields. Furthermore, we show that nuclear spins of the molecules can be used to implement an additional (orbital) degree of freedom that is coupled to the original rotational degree of freedom in a tunable way. The presented system is expected to exhibit exotic physics and to provide insights into strongly correlated phenomena in condensed-matter systems. Realistic experimental imperfections are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Study of ionospheric models for satellite orbit determination

Means of improving the accuracy of the ionospheric correction of two empirical ionospheric models, the Bent (Schmid et al. 1973) and international reference ionosphere (IRI) models, have been evaluated. An improved IRI topside formula is found to minimize the tendency for the electron density profile to decrease too sharply with increasing altitude, and is shown to produce results which compare well with satellite data and ground-based incoherent scatter measurements. A model for the effective parabolic thickness is proposed for the bottomside. Comparison with results from a Meteosat tracking exercise demonstrates that the present changes improve the overall accuracy of ionospheric delays calculated using the two models.

Bilitza, D.↗
NASA NTRS2019

initMIP-Antarctica: an Ice Sheet Model Initialization Experiment of ISMIP6

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

ice sheet model↗