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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from quantitative models inform actions ranging from short-term and local decisions, such as those about technology and infrastructure deployment, and global and long-term negotiations and targets. Computational limits require model designers to balance coverage and resolution (i.e., breadth versus depth). Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses with less resolution than models that focus on a single sector's energy use. GCAM balances global supply and demand of all energy carriers projecting prices using internal calculations for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This globally comprehensive model was used to frame the Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050, which the White House released in 2021 and has been used to inform national and global economy-wide climate change mitigation discussions and strategy development for decades. Unlike GCAM, sectoral models focus on a portion of the energy sector and with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects electricity system capacity expansion and operation with high-fidelity representation of emerging technologies for deep decarbonization, such as variable renewable energy and energy storage, and integration of these technologies into the electric grid. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices, with a focus on adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of electrification and energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas mitigation strategies in the United States. The integrated multisector and sector-specific modeling approaches represented by GCAM and these sectoral models are complementary. The integrated multisector approach calculates energy pricing and resource allocation within the model, which is important for consistency when future conditions substantially diverge from current conditions in transformative scenarios. The sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and trade-offs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and it addresses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Updraft and Downdraft Core Size and Intensity as Revealed by Radar Wind Profilers: MCS Observations and Idealized Model Comparisons

This study explores the updraft and downdraft properties of mature stage mesoscale convective systems (MCSs) in terms of draft core width, shape, intensity, and mass flux characteristics. The observations use extended radar wind profiler (RWP) and surveillance radar datasets from the U.S. Department of Energy Atmospheric Radiation Measurement program for midlatitude (Oklahoma, USA) and tropical (Amazon, Brazil) sites. MCS drafts behave qualitatively similar to previous aircraft and RWP cloud summaries. The Oklahoma MCSs indicate larger and more intense convective up- and downdraft cores, and greater mass flux than Amazon MCS counterparts. However, similar size-intensity relationships and draft vertical profile behaviors are observed for both regions. Additional similarities include weak positive correlations between core intensity and core width (correlation coefficient r ~ 0.5), and increases in draft intensity with altitude. A model-observational intercomparison for draft properties (core width, intensity, mass flux) is also performed to illustrate the potential usefulness of statistical observed draft characterizations. Idealized simulations with the Weather Research and Forecasting model aligned with midlatitude MCS conditions are performed at model grid spacings (?x) that range from 4 km to 250 m. It is shown that the simulations performed at ?x = 250 m at similar mature MCS lifecycle stages are those that exhibit draft intensity, width, mass flux, and shape parameter performances best matching with observed properties.

radar, arm, wind profiler, goamazon↗
DOE OSTI2021

The Role of Energy Storage in the Uptake of Renewable Energy: A Model Comparison Approach

The power sector needs to ensure a rapid transition towards a low-carbon energy system to avoid the dangerous consequences of greenhouse gas emissions. Storage technologies are a promising option to provide the power system with the flexibility required when intermittent renewables are present in the electricity generation mix. This paper focuses on the role of electricity storage in energy systems with high shares of renewable sources. The study encompasses a model comparison approach where four models (GENeSYS-MOD, MUSE, NATEM, and urbs - MX) are used to analyse the storage uptake in North America. The analysis addresses the conditions affecting storage uptake in each country and its dependence on resource availability, technology costs, and public policies. Results show that storage may promote emissions reduction at lower costs when renewable mandates are in place whereas in presence of carbon taxes, renewables may compete with other low-carbon options. The study also highlights the main modelling approach shortcomings in the modelling of electricity storage in integrated assessment models.

electricity storage↗
DOE OSTI2024

Subhourly Clipping Correction Model Comparison

This work will compare the Allen method and Walker method of accounting for subhourly inverter clipping power losses in hourly PV performance models. The Allen method uses a matrix lookup based on DNI clearness and clipping potential to assign a clipping correction loss at each simulation timestep. The Walker method models the PV DC power input to the inverter as a distribution over the hourly timestep and uses integration over the timestep to determine the amount of clipping that occurs within the timestep. Both these models have been recently implemented in the System Advisor Model's (SAM) open-source code, and will be applied to hourly SURFRAD datasets to analyze the subhourly clipping loss predicted by each model for different system designs and inverter loading conditions. Both models will be compared to "true" 1-minute SURFRAD data simulations to see their accuracy against more accurate 1-minute clipping correction loss predictions. This model comparisons will be investigated in more detail at the PVSC conference in Seattle, Washington June 2024.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗
DOE OSTI2023

Robust Statistical Approach for Determination of Graphite Nitridation Using Bayesian Model Comparison

A better estimation of surface reaction efficiency of semiconductor-grade graphite with atomic nitrogen, as well as the calibration error are calculated using Bayesian updating based on experimental data. Compared with a conventional deterministic model, the stochastic model approach is a powerful tool in the sense that the model is capable of taking into account underlying error correlations among the data quantities. In this paper, we investigate four different stochastic models (called “stochastic system model classes” herein) corresponding to different descriptions of modeling and measurement error structures, given one deterministic physical model. These stochastic system model classes differ in the covariance matrix structure that is used in the uncertainty model to represent uncertainties associated with the physical model and experimental measurements. For each model class, Bayesian inference is used to estimate the posterior probabilities of the physical model parameters as well as of the stochastic model parameters. Model comparison and selection are then applied based on two measures including Bayesian evidence and Bayesian information criterion, as well as the deviance information criterion. Both measures suggest the stochastic model class, which considers that a correlation between errors in two data quantities among different data points is the most plausible. With the stochastic model class, the range of uncertainty in surface reaction efficiency is estimated to be about two orders of magnitude at [Formula: see text].

Engineering↗
DOE OSTI2022

Transport model comparison studies of intermediate-energy heavy-ion collisions

Transport models are the main method to obtain physics information on the nuclear equation of state and in-medium properties of particles from low to relativistic-energy heavy-ion collisions. The Transport Model Evaluation Project (TMEP) has been pursued to test the robustness of transport model predictions in reaching consistent conclusions from the same type of physical model. To this end, calculations under controlled conditions of physical input and set-up were performed with various participating codes. These included both calculations of nuclear matter in a box with periodic boundary conditions, which test separately selected ingredients of a transport code, and more realistic calculations of heavy-ion collisions. Over the years, six studies have been performed within this project. In this intermediate review, we summarize and discuss the present status of the project. We also provide condensed descriptions of the 26 participating codes, which contributed to some part of the project. These include the major codes in use today. After a compact description of the underlying transport approaches, we review the main results of the studies completed so far. They show, that in box calculations the differences between the codes can be well understood and a convergence of the results can be reached. These studies also highlight the systematic differences between the two families of transport codes, known under the names of Boltzmann–Uehling–Uhlenbeck (BUU) and Quantum Molecular Dynamics (QMD) type codes. However, when the codes were compared in full heavy-ion collisions using different physical models, as recently for pion production, they still yielded substantially different results. This calls for further comparisons of heavy-ion collisions with controlled models and of box comparisons of important ingredients, like momentum-dependent fields, which are currently underway. Furthermore, our evaluation studies often indicate improved strategies in performing transport simulations and thus can provide guidance to code developers. Results of transport simulations of heavy-ion collisions from a given code will have more significance if the code can be validated against benchmark calculations such as the ones summarized in this review.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Antarctic ice sheet model comparison with uncurated geological constraints shows that higher spatial resolution improves deglacial reconstructions

Accurately reconstructing past changes to the shape and volume of the Antarctic ice sheet relies on the use of physically based and thus internally consistent ice sheet modeling, benchmarked against spatially limited geologic data. The challenge in model benchmarking against geologic data is diagnosing whether model-data misfits are the result of an inadequate model, inherently noisy or biased geologic data, and/or incorrect association between modeled quantities and geologic observations. In this work we address this challenge by (i) the development and use of a new model-data evaluation framework applied to an uncurated data set of geologic constraints, and (ii) nested high-spatial-resolution modeling designed to test the hypothesis that model resolution is an important limitation in matching geologic data. While previous approaches to model benchmarking employed highly curated datasets, our approach applies an automated screening and quality control algorithm to an uncurated public dataset of geochronological observations (specifically, cosmogenic-nuclide exposure-age measurements from glacial deposits in ice-free areas). This optimizes data utilization by including more geological constraints, reduces potential interpretive bias, and allows unsupervised assimilation of new data as they are collected. We also incorporate a nested model framework in which high-resolution domains are downscaled from a continent-wide ice sheet model. We highlight the application of this framework by applying these methods to a small ensemble of deglacial ice-sheet model simulations, and demonstrate that the nested approach improves the ability of model simulations to match exposure age data collected from areas of complex topography and ice flow. We develop a range of diagnostic model-data comparison metrics to provide more insight into model performance than possible from a single-valued misfit statistic, showing that different metrics capture different aspects of ice sheet deflation.

Geosciences↗
DOE OSTI2020

Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes

Conservation planners and resource managers seek information about how the availability and locations of cold-water habitats will change in the future and how these predictions vary among models. In this work, we used a physical process-based model to demonstrate the implications of climate change for streamflow and water temperature in two watersheds with distinctive flow regimes: the Snoqualmie watershed (WA) and Siletz watershed (OR), USA. Our model incorporated a downscaled ensemble of global climate model outputs and was calibrated with in situ and remotely sensed water temperatures. Furthermore, we compared predictions from our processed-based model to those from a publicly available and widely used statistical model. The process-based model projected greater changes in summer maximum water temperatures for the mixed-rain-snow Snoqualmie watershed than for the rain-dominated Siletz watershed as a result of the near-complete loss of winter snowpack and significant reduction in summer flow in the Snoqualmie watershed expected by the 2080s. Both models projected generally similar future spatial patterns of maximum water temperature in the two rivers, with cool reaches distributed farther upstream and fewer in number. However, the process-based model projected higher spatial heterogeneity in water temperature due to our spatially explicit simulation of streamflow and because we calibrated the model with spatially continuous remotely sensed water temperature data. We used stream temperature projections to assess the vulnerability of Pacific salmon and trout to changes in the spatial distribution of cold-water habitats during August by the 2080s. Results suggest that salmonids may have fewer summertime cold-water habitats in both watersheds. Projected stream warming may further limit particular species and life stages, especially in the Snoqualmie watershed. Our comparison of models highlights the importance of considering what might be gained by using a process-based model for evaluating and prioritizing management actions that mitigate climate impacts on cold-water habitats for stream fishes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling aerosol bolus inhalations in the human lung with the multiple path particle deposition model: Comparison with experimental data

Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process. Here, in this study, we improved our recently developed alveolar mixing module incorporated in the multiple path particle dosimetry model (MPPD) to account for flow irreversibility and particle trapping in the alveolar spaces, as well as mixing occurring in the tracheobronchial region. This new version of MPPD was coupled with CFPD-based predictions of aerosol bolus dispersion in the oral airway. The model was used to predict the deposition, dispersion, and mode shift of aerosol bolus inhaled at different penetration depths within the lung for breathing patterns and particle size matching those used in a previous experimental study (Darquenne et al., 2016). Even though a quite simplified approach was used, the computations appear to describe subject-specific and test-specific experimental data reasonably well. The proposed combined dispersion-deposition model can be a useful tool for targeted drug delivery and also for exposure health risk assessment.

MPPD↗
DOE OSTI2020

A semblance measure for model comparison

Algorithmic and computational advances have made it possible that geophysical survey and earth model design can be aided by many systematic trial inverse-modelling runs with synthetic data. Such may, for example, come up in machine-learning approaches. Automated image appraisal pertaining to such applications will involve common statistical tests for goodness-of-data fit as a primary evaluation method. However, solution non-uniqueness may render multiple images equivalent in terms of their data fit, requiring secondary categorizers. A logical choice for classifying synthetic-imaging results quantifies the goodness of model fit where a known reference model replaces the observational input. The task of model intercomparison in terms of measuring the resemblance to the reference model poses challenges to common distance-based metrics like root mean square error and mean absolute error. First, distance-based metrics can introduce spurious contributions when smooth models with fuzzy target contours are to be compared against a sharp reference. Second, large differences due to parameter-estimation overshoots can dominate distance metrics. Here, we propose a remedy that is referred to as semblance and is based on the idea of logistic functions, where a binary-dependent variable adds non-zero or zero accumulation terms for the, respectively, passing or failing of preset target thresholds. This classifying approach is amenable to an objective where model feature recognition is primary. Numerical comparisons to distance-based metrics provide evidence for the advantages of the semblance in view of this objective. Geophysical imaging in conjunction with machine-learning is seen as a benefitting upcoming application area.

58 GEOSCIENCES↗
DOE OSTI2021

First attempt to quantify W7-X island divertor plasma by local experiment-model comparison

As a complement to our recent work, which focused on understanding the basic detachment physics and general experimental and numerical trends observed in the W7-X island divertor, this paper compares EMC3-Eirene simulation results with different local diagnostics, including IR cameras, Langmuir probes, H α -cameras, and Thomson scattering. The main purposes are to (1) justify the simulation setup in the previous work, (2) identify the application limitations of the current EMC3-Eirene model, (3) verify the consistency of different diagnostics, and (4) isolate the main geometric and physical effects that need to be prioritized in further developing the EMC3-Eirene code and improving diagnostic capabilities. It turns out that the current version of the EMC3-Eirene code (without drifts) is not yet able to quantitatively reproduce all selected local measurements simultaneously under the current experimental conditions (in particular, the existence of error fields). Nevertheless, it can be shown that within a reasonable range of variation in magnetic configuration, cross-field transport, and SOL plasma state in the modeling, a region of overlap between the numerical results and the local measurements can be established. More accurate model-experiment comparisons will require clarification of error fields, implementation of drifts in EMC3, and improvement of diagnostic capabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Insights on Nuclear Energy from Long-Term System Models: Inter-Model Comparison Results

A variety of US electric power sector capacity expansion models are used by decision makers and analysts to evaluate competition among generation, transmission, and storage technologies to meeting the demands of the system. CEMs use least-cost optimization to identify optimal portfolios of investments capable of satisfying all specified requirements. While CEMs are a useful tool to inform pathways to meet future needs, projections can differ significantly between tools for apparently similar scenario assumptions. Differences in model structure, scope, and input assumption contribute to this issue. This work compares model response with harmonization between four modeling teams on issues significant to the representation and development of nuclear energy.

capacity expansion model↗
DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Statistical (n,$$\gamma $$) cross section model comparison for short-lived nuclei

Abstract Neutron-capture cross sections of neutron-rich nuclei are calculated using a Hauser–Feshbach model when direct experimental cross sections cannot be obtained. A number of codes to perform these calculations exist, and each makes different assumptions about the underlying nuclear physics. We investigated the systematic uncertainty associated with the choice of Hauser-Feshbach code used to calculate the neutron-capture cross section of a short-lived nucleus. The neutron-capture cross section for $$^{73}\hbox {Zn}$$ 73 Zn (n, $$\gamma $$ γ ) $$^{74}\hbox {Zn}$$ 74 Zn was calculated using three Hauser-Feshbach statistical model codes: TALYS, CoH, and EMPIRE. The calculation was first performed without any changes to the default settings in each code. Then an experimentally obtained nuclear level density (NLD) and $$\gamma $$ γ -ray strength function ( $$\gamma \hbox {SF}$$ γ SF ) were included. Finally, the nuclear structure information was made consistent across the codes. The neutron-capture cross sections obtained from the three codes are in good agreement after including the experimentally obtained NLD and $$\gamma \hbox {SF}$$ γ SF , accounting for differences in the underlying nuclear reaction models, and enforcing consistent approximations for unknown nuclear data. It is possible to use consistent inputs and nuclear physics to reduce the differences in the calculated neutron-capture cross section from different Hauser-Feshbach codes. However, ensuring the treatment of the input of experimental data and other nuclear physics are similar across multiple codes requires a careful investigation. For this reason, more complete documentation of the inputs and physics chosen is important.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Climate change impacts on the energy system: a model comparison

Increasing renewable energy use is an essential strategy for mitigating climate change. Nevertheless, the sensitivity of renewable energy to climatic conditions means that the energy system’s vulnerability to climate change can also become larger. In this research, we used two integrated assessment models and data from four climate models to analyse climate change impacts on primary energy use at a global and regional scale under a low-level (RCP2.6) and a medium-level (RCP6.0) climate change scenario. The impacts are analysed on the energy system focusing on four renewable sources (wind, solar, hydropower, and biomass). Globally, small climate impacts on renewable primary energy use are found in both models (5% for RCP2.6 and 6% for RCP6.0). These impacts lead to a decrease in the use of fossil sources for most regions, especially for North America and Europe under the RCP60 scenario. Overall, IMAGE and GCAM provide a similar signal impact response for most regions. E.g. in Asia (excluding China and India), climate change induces an increase in wind and hydropower use under the RCP6.0 scenarios; however, for India, a decrease in solar energy use can be expected under both scenarios and models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗