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DOE OSTI2025

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Attribution of Snowpack Errors to Simulated Temperature and Precipitation in E3SMv1 Over the Contiguous United States

Abstract Snow water equivalent (SWE), temperature, and precipitation biases and trends are evaluated in the atmosphere‐land simulations of the Energy Exascale Earth System Model version 1 (E3SMv1) in comparison to the Community Earth System Model version 2 (CESM2) and two other models using the ground measurement‐based University of Arizona (UA) snow product. SWE, temperature, and precipitation biases are highest in magnitude in the Western contiguous United States (CONUS). SWE errors are attributed to temperature and precipitation through multiple linear regressions of normalized errors, the coefficients of which represent the sensitivities to temperature and precipitation errors. SWE errors are more sensitive to temperature errors throughout the CONUS. Model SWE and temperature trends are generally opposite from UA product trends in the Western CONUS. SWE trend errors are also attributed to temperature and precipitation trend errors using multiple linear regressions of normalized trend errors. SWE trend errors are more sensitive to those of precipitation at higher elevations (>1,500 m) in the Western CONUS in these simulations. Thus, the sensitivity to temperature and precipitation differ for SWE errors and its trend errors. Furthermore, the SWE trend errors are more sensitive to temperature and precipitation in the atmosphere‐ocean coupled simulations in which the atmosphere‐land is coupled to an active ocean model. These results suggest that both errors in simulated temperature and precipitation contribute to SWE errors.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Extending TOUGH + HYDRATE with a parallel particle transport simulator: numerical investigation of sand production during gas production from hydrate deposits

A new parallel code for simulating particle transport in porous media is integrated with the TOUGH + HYDRATE simulator to investigate sand production associated with gas production from unconsolidated gas hydrate-bearing sediments (HBS). Here, the parallel coupled simulator is named THMPT and uses the integral finite difference method to describe the Darcian and non-Darcian flow of fluids and heat transport, the finite element method to describe the associated geomechanical changes, and the discrete element method to track the trajectory of individual sand particles within the HBS. The THMPT simulator is written in Fortran, incorporates multiple optimized algorithms, and can comprehensively address the coupled flow, thermal, chemical, geomechanical, and particle transport processes that characterize the system behaviors during gas production from HBS. The simulator can capture all processes involved in sand particle transport in porous media, including sand detachment, collision, clogging (i.e., bridging), and migration. A benchmark case study of sand production in the course of depressurization-induced gas production from a representative HBS reveals various distinct microscopic particle migration mechanisms and the adverse impact of sand particle detachment, transport, and clogging. The numerical investigation also examines the effect of bottomhole pressure on mitigating sand production. The simulation results indicate that sand clogging near the wellbore significantly reduces permeability, decreasing gas production by at least 50%. Lastly, the efficiency of gravel packing in mitigating sand production is numerically evaluated, revealing that the structure of the porous media appears to profoundly influence the macroscopic motion behavior of sand particles and sand clogging characteristics.

discrete element method↗

DOE OSTI2024

Mechanistic definition and prediction of the mass exchange coefficient between rivers and hyporheic zones: The $α$ of two $Ω$s

Solute transport in interconnected rivers and hyporheic zones is typically modeled through dual-domain models where first-order solute mass transfer between the two domains, Ω R and Ω HZ , is represented by a coefficient α. The transient storage model (TSM) is an example of such an approach. In practice, α is determined by fitting the tails of solute tracer breakthrough curves using a TSM. This approach has led to ambiguity regarding α’s physical meaning and transferability. Here, in this work, we investigated the physical basis for α and tested it with virtual experiments through the fully coupled multiphysics model hyporheicFoam for the Ω R – Ω HZ system. hyporheicFoam explicitly simulated coupled flow and solute transport over a kilometer with centimeter-scale resolution. Model results were analyzed to calculate α following its theoretical definition directly. Using the determined α within a TSM enables accurate reproduction of solute transport, underscoring α’s physical relevance and precision.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Lifting the Garage Door on Spawn, An Open-Source BEM-Controls Engine

Spawn is the latest whole-building energy simulation engine developed by the US Department of Energy, National Labs and industry. Whereas EnergyPlus was designed as a successor to DOE-2, Spawn is not a direct successor of–nor is it intended as an imminent replacement for– EnergyPlus. Instead, Spawn reuses parts of EnergyPlus while supporting new use cases in HVAC and controls. Spawn is intended to provide several capabilities that significantly advance beyond EnergyPlus. It is intended to support the evaluation of novel HVAC and district energy systems in a more physically realistic way. Critically, it can model control in a physically realistic way, using portable specifications that can be compiled for execution on control platforms. Spawn is also intended to support co-simulation in an intrinsic way to enable integration with third-party models. This paper describes the software architecture of Spawn from model authoring to compilation and simulation. It explains how Spawn reuses the envelope and daylighting modules of EnergyPlus and couples them to HVAC and control models from the Modelica Buildings Library using the Functional Mockup Interface (FMI) standard. It presents a number of examples that: i) validate Spawn’s coupled simulation approach by comparing its results to those of EnergyPlus, ii) illustrate the Spawn methodology for modeling and simulating HVAC systems, and iii) evaluate the performance of Spawn’s Quantized State System (QSS) time integration algorithms

Wetter, Michael↗

DOE OSTI2021

Multi-scale Coupled Processes Modeling of Fractures as Porous, Interfacial and Granular Systems from Rock Images with the Numerical Manifold Method

Abstract The greatest challenges of rigorously modeling coupled hydro-mechanical processes in fractured rocks at different scales are associated with computational geometry. In addition, selections of continuous or discontinuous models, physical laws, and coupling priorities at different scales based on different geometric features determine the applicability of a numerical model for a certain type of problem. In this study, we present our multi-scale modeling capabilities that have been developed based on the numerical manifold method for analyzing coupled hydro-mechanical processes in fractured rocks. Based on their geometric features, the fractures are modeled as continua—finite-thickness porous zones, and discontinua—discontinuous interfaces and microscale asperities and granular systems. Different governing equations, physical laws, coupling priorities, and approaches for addressing fracture intersections and shearing are then applied to describe these. We applied these models to simulate coupled processes in fractured rocks using realistic geometry obtained from rock images at different scales. We first calculated shearing of a single fracture with different models and demonstrated the impacts of asperities on shearing. We then applied the continuous and discontinuous models to simulate a network of rough fractures, demonstrating that contact dynamics contribute significantly to the geometric, multi-physical evolution of systems where rough fractures are not mineral filled. For a discrete fracture network, our coupled processes modeling demonstrates that shearing of the discrete fractures can have a major impact on stress and pore pressure distribution. Lastly, we applied the discontinuous granular model to simulate evolution of a complex granular system with a deformation band, demonstrating that the deformation band can dominate contact dynamics, the structural and the stress evolution of the granular system.

58 GEOSCIENCES↗

DOE OSTI2022

components for the MuMMI software release

The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.

Neale, Christopher↗

DOE OSTI2024

Portable, heterogeneous ensemble workflows at scale using libEnsemble

libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator–allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a simulator or generator should be called. The generator steers the ensemble based on simulation results. Generators may, for example, apply methods for numerical optimization, machine learning, or statistical calibration. libEnsemble communicates between a manager and workers. Flexibility is provided through multiple manager–worker communication substrates each of which has different benefits. These include Python’s multiprocessing, mpi4py, and TCP. Multisite ensembles are supported using Balsam or Globus Compute. We overview the unique characteristics of libEnsemble as well as current and potential interoperability with other packages in the workflow ecosystem. We highlight libEnsemble’s dynamic resource features: libEnsemble can detect system resources, such as available nodes, cores, and GPUs, and assign these in a portable way. These features allow users to specify the number of processors and GPUs required for each simulation; and resources will be automatically assigned on a wide range of systems, including Frontier, Aurora, and Perlmutter. Such ensembles can include multiple simulation types, some using GPUs and others using only CPUs, sharing nodes for maximum efficiency. We also describe the benefits of libEnsemble’s generator–simulator coupling, which easily exposes to the user the ability to cancel, and portably kill, running simulations based on models that are updated with intermediate simulation output. We demonstrate libEnsemble’s capabilities, scalability, and scientific impact via a Gaussian process surrogate training problem for the longitudinal density profile at the exit of a plasma accelerator stage. In conclusion, the study uses gpCAM for the surrogate model and employs either Wake-T or WarpX simulations, highlighting efficient use of resources that can easily extend to exascale.

Dynamic ensembles↗

DOE OSTI2025

Improved Representations of Land‐Atmosphere Interactions Over the Continental U.S. Through Dynamic Root Modeling

Previous studies have identified the oversimplified root system representation as a key factor leading to inaccuracies in vegetation‐atmosphere feedbacks. In this study, a dynamic root water uptake scheme in the Noah‐MP land surface model has been coupled to the Weather Research and Forecasting (WRF) model to investigate its impact on the surface hydroclimate variables and land‐atmosphere interactions. To evaluate the impact of the dynamic root, two coupled simulations were conducted, one with the dynamic root water uptake scheme (DynRt) and one with the static root water uptake scheme (StcRt), which is based on the default root representation in Noah‐MP, with slight modifications, primarily in vegetation‐related parameters. Both DynRt and StcRt simulations were conducted with a small ensemble of three members to account for variations in physical parameterizations, initial and boundary forcing and model setup. When compared with reference data sets, the DynRt simulations show improved results than the StcRt simulations, reducing biases in the simulated leaf area index, surface energy fluxes, soil moisture and precipitation. Two different mechanisms through which roots affect land‐atmosphere coupling have been identified. Over the transitional climate zone between the dry and wet climate, the dynamic root scheme affects surface climate and land‐atmosphere coupling mainly through changes in soil moisture through hydraulic redistribution by plant root system. Over the energy‐limited mesic zone, the dynamic root affects regional land‐atmosphere coupling mainly through changes in carbon allocation. This work highlights the importance of dynamic root representation in improving vegetation‐atmosphere simulations by enhancing predictions of water, energy, and carbon fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The discrete Green's function paradigm for two-way coupled Euler–Lagrange simulation

We outline a methodology for the simulation of two-way coupled particle-laden flows. The drag force that couples fluid and particle momentum depends on the undisturbed fluid velocity at the particle location, and this latter quantity requires modelling. We demonstrate that the undisturbed fluid velocity, in the low particle Reynolds number limit, can be related exactly to the discrete Green's function of the discrete Stokes equations. In addition to hydrodynamics, the method can be extended to other physics present in particle-laden flows such as heat transfer and electromagnetism. The discrete Green's functions for the Navier–Stokes equations are obtained at low particle Reynolds number in a two-plane channel geometry. We perform verification at different Reynolds numbers for a particle settling under gravity parallel to a plane wall, for different wall-normal separations. Compared with other point-particle schemes, the Stokesian discrete Green's function approach is the most robust at low particle Reynolds number, accurate at all wall-normal separations. To account for degradation in accuracy away from the wall at finite Reynolds number, we extend the present methodology to an Oseen-like discrete Green's function. The extended discrete Green's function method is found to be accurate within 6% at all wall-normal separations for particle Reynolds numbers up to 24. Furthermore, the discrete Green's function approach is well suited to dilute systems with significant mass loading and this is highlighted by comparison against other Euler–Lagrange as well as particle-resolved simulations of gas–solid turbulent channel flow. Strong particle–turbulence coupling is observed in the form of turbulence modification and turbophoresis suppression, and these observations are placed in context of the different methods.

42 ENGINEERING↗

DOE OSTI2024

A protocol for model intercomparison of impacts of marine cloud brightening climate intervention

A modeling protocol (defined by a series of climate model simulations with specified model output) is introduced. Studies using these simulations are designed to improve the understanding of climate impacts using a strategy for climate intervention (CI) known as marine cloud brightening (MCB) in specific regions; therefore, the protocol is called MCB-REG (where REG stands for region). The model simulations are not intended to assess consequences of a realistic MCB deployment intended to achieve specific climate targets but instead to expose responses to interventions in six regions with pervasive cloud systems that are often considered candidates for such a deployment. A calibration step involving simulations with fixed sea surface temperatures (SSTs) is first used to identify a common forcing, and then coupled simulations with forcing in individual regions and combinations of regions are used to examine climate impacts. Synthetic estimates constructed by superposing responses from simulations with forcing in individual regions are considered a means of approximating the climate impacts produced when MCB interventions are introduced in multiple regions. A few results comparing simulations from three modern climate models (CESM2, E3SMv2, and UKESM1) are used to illustrate the similarities and differences between model behavior and the utility of estimates of MCB climate responses that were synthesized by summing responses introduced in individual regions. Cloud responses to aerosol injections differ substantially between models (CESM2 clouds appear much more susceptible to aerosol emissions than the other models), but patterns in precipitation and surface temperature responses were similar when forcing is imposed with similar amplitudes in the same regions. A previously identified La Niña-like response to forcing introduced in the Southeast Pacific is evident in this study, but the amplitude of the response was shown to markedly differ across the three models. Other common response patterns were also found and are discussed. Forcing in the Southeast Atlantic consistently (across all three models) produces weaker global cooling than that in other regions, and the Southeast Pacific and South Pacific show the strongest cooling. This indicates that the efficiency of a given intervention depends on not only the susceptibility of the clouds to aerosol perturbations, but also the strength of the underlying radiative feedbacks and ocean responses operating within each region. These responses were generally robust across models, but more studies and an examination of responses with ensembles would be beneficial.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

City-Scale Building Anthropogenic Heating during Heat Waves

More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban environment, and hence it is critical to understand the interactive effects of urban microclimate and building heat emissions in terms of the urban energy balance. Here we developed a coupled-simulation approach to quantify these effects, mapping urban environmental data generated by the mesoscale Weather Research and Forecasting (WRF) coupled to Urban Canopy Model (UCM) to urban building energy models (UBEM). We conducted a case study in the city of Los Angeles, California, during a five-day heat wave event in September 2009. We analyzed the surge in city-scale building heat emission and energy use during the extreme heat event. We first simulated the urban microclimate at a high resolution (500 m by 500 m) using WRF-UCM. We then generated grid-level building heat emission profiles and aggregated them using prototype building energy models informed by spatially disaggregated urban land use and urban building density data. The spatial patterns of anthropogenic heat discharge from the building sector were analyzed, and the quantitative relationship with weather conditions and urban land-use dynamics were assessed at the grid level. The simulation results indicate that the dispersion of anthropogenic heat from urban buildings to the urban environment increases by up to 20% on average and varies significantly, both in time and space, during the heat wave event. The heat dispersion from the air-conditioning heat rejection contributes most (86.5%) of the total waste heat from the buildings to the urban environment. We also found that the waste heat discharge in inland, dense urban districts is more sensitive to extreme events than it is in coastal or suburban areas. The generated anthropogenic heat profiles can be used in urban microclimate models to provide a more accurate estimation of urban air temperature rises during heat waves.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗

DOE OSTI2023

Mapping the performance of a versatile water-based condensation particle counter (vWCPC) with numerical simulation and experimental study

Accurate airborne aerosol instrumentation is required to determine the spatial distribution of ambient aerosol particles, particularly when dealing with the complex vertical profiles and horizontal variations of atmospheric aerosols. A versatile water-based condensation particle counter (vWCPC) has been developed to provide aerosol concentration measurements under various environments with the advantage of reducing the health and safety concerns associated with using butanol or other chemicals as the working fluid. However, the airborne deployment of vWCPCs is relatively limited due to the lack of characterization of vWCPC performance at reduced pressures. Given the complex combinations of operating parameters in vWCPCs, modeling studies have advantages in mapping vWCPC performance. In this work, we thoroughly investigated the performance of a laminar-flow vWCPC using COMSOL Multiphysics® simulation coupled with MATLAB™. We compared it against a modified vWCPC (vWCPC model 3789, TSI, Shoreview, MN, USA). Our simulation determined the performance of particle activation and droplet growth in the vWCPC growth tube, including the supersaturation, $D$ p,kel,0 (smallest size of particle that can be activated), $D$ p,kel,50 (particle size activated with 50 % efficiency) profile, and final growth particle size D d under wide operating temperatures, inlet pressures $P$ (30–101 kPa), and growth tube geometry (diameter $D$ and initiator length $L$ ini ). The effect of inlet pressure and conditioner temperature on vWCPC 3789 performance was also examined and compared with laboratory experiments. The COMSOL simulation result showed that increasing the temperature difference (Δ$T$) between conditioner temperature $T$ con and initiator $T$ ini will reduce $D$ p,kel,0 and the cut-off size $D$ p,kel,50 of the vWCPC. In addition, lowering the temperature midpoint ($T$ mid = $\frac{T_{con}+T_{ini}}{2}$ increases the supersaturation and slightly decreases the $D$ p,kel . The droplet size at the end of the growth tube is not significantly dependent on raising or lowering the temperature midpoint but significantly decreases at reduced inlet pressure, which indirectly alters the vWCPC empirical cut-off size. Our study shows that the current simulated growth tube geometry ($D$=6.3 mm and $L$ ini =30 mm) is an optimized choice for current vWCPC flow and temperature settings. The current simulation can more realistically represent the $D$ p,kel for 7 nm vWCPC and also achieved good agreement with the 2 nm setting. Using the new simulation approach, we provide an optimized operation setting for the 7 nm setting. This study will guide further vWCPC performance optimization for applications requiring precise particle detection and atmospheric aerosol monitoring.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

First coupled GENE–XGC microturbulence simulations

Covering the core and the edge region of a tokamak, respectively, the two gyrokinetic turbulence codes Gyrokinetic Electromagnetic Numerical Experiment (GENE) and X-point Gyrokinetic Code (XGC) have been successfully coupled by exchanging three-dimensional charge density data needed to solve the gyrokinetic Poisson equation over the entire spatial domain. Certain challenges for the coupling procedure arise from the fact that the two codes employ completely different numerical methods. This includes, in particular, the necessity to introduce mapping procedures for the transfer of data between the unstructured triangular mesh of XGC and the logically rectangular grid (in a combination of real and Fourier space) used by GENE. Constraints on the coupling scheme are also imposed by the use of different time integrators. First, coupled simulations are presented. We have considered collisionless ion temperature gradient turbulence, in both circular and fully shaped plasmas. Coupled simulations successfully reproduce both GENE and XGC reference results, confirming the validity of the code coupling approach toward a whole device model. Here, many lessons learned in the present context, in particular, the need for a coupling procedure as flexible as possible, should be valuable to our and other efforts to couple different kinds of codes in pursuit of a more comprehensive description of complex real-world systems and will drive our further developments of a whole device model for fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Probing circular polarization and magnetic field structure in active galactic nuclei

The composition and magnetic field morphology of relativistic jets can be studied using circular polarization (CP) measurement. Recent three-dimensional relativistic magnetohydrodynamic (3D RMHD) simulations coupled with radiative transfer (RT) calculations make strong predictions about the level (and morphology) of the jet’s CP emission. These simulations show that the sign of CP and the electric vector position angle (EVPA) are both sensitive to the jet’s magnetic field morphology within the radio core. We probe this theory by exploring whether the jet’s radio core EVPA orientation is consistent with the observed sign of the core CP in deep full-track polarimetric observations. Based on a selection of sources from earlier MOJAVE observations, we aim to probe the nature of linear polarization (LP) and CP in the innermost regions of jets from a small sample of nine blazars. This sample includes sources that have exhibited: (i) positive CP; (ii) negative CP; or (iii) positive and negative CP simultaneously in the radio core region. By coupling deep polarimetric observations of a carefully selected sample of blazars with state-of-the-art RMHD and RT calculations, we hope to gain a deeper understanding of the physics of blazar jets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Time-Domain Vortex Induced Vibration Modeling of Reference Dynamic Power Cable for the Gulf of Maine

Vortex-induced vibration (VIV) is a phenomenon known to decrease the fatigue life of dynamic power cables used in floating offshore wind systems through increased bending loading cycles. A variety of modeling solutions have been proposed to study this, but none enable fully-coupled simulations leveraging open-source tools. To address this, a time-domain VIV model has been successfully implemented into the open-source mooring dynamics model MoorDyn. The semi-empirical VIV model describes a lift force acting on segments of a flexible cylinder, making it well suited for implementation into MoorDyn. The new capability successfully predicted the frequencies and magnitudes of strain in both steady and oscillating flows when compared to the original validation results and matched peak spectral response when compared to experimental results, verifying successful implementation. MoorDyn with VIV was then leveraged to simulate a 15 MW floating turbine with a dynamic power cable in the Gulf of Maine using OpenFAST for six return periods of combined wind, wave, and current conditions. Increased curvature and tension fluctuations in higher flow speeds were observed when simulating VIV. Maximum tensions and curvatures also increased, with the 500 year conditions violating the curvature factor of safety of 2.0. These results highlight the importance of considering VIV when designing dynamic power cables for the Gulf of Maine, and indicate that cost effective mitigation strategies should be explored for the area. They also demonstrate the utility of this new modeling capability, which provides the first open-source tool for fully coupled time-domain floating offshore wind simulations with dynamic power cable VIV.

17 WIND ENERGY↗

DOE OSTI2023

Latest developments in the MOOSE fluid properties module

The fluid properties module in MOOSE serves a variety of fluid simulation applications based on MOOSE, including the MOOSE Navier Stokes module~\cite{moose_ns}, Pronghorn~\cite{pgh}, SAM~\cite{sam}, the MOOSE thermal hydraulics module, RELAP-7~\cite{relap7} and subchannel~\cite{subchannel}. It is used for coarse mesh multi-dimensional thermal-hydraulics~\cite{pgh}, 1D systems analysis~\cite{sam,relap7} in nuclear reactor analysis, and porous flow simulations~\cite{porous} for underground gas storage and water seepage. The use of consistent fluid properties across fluid flow applications facilitates coupled simulations~\cite{anl_sam_pgh}. The module offers a consistent set of interfaces to implement to create a new fluid property. There are numerous fluid properties of interest in the entirety of all fields of fluid flow simulations, and this is exacerbated by the use of different variable sets depending on the compressibility of the fluid. For single-phase fluids, the following variable sets may be used to compute fluid properties: (pressure, temperature) and (specific volume, specific internal energy). Some properties may also be computed using the (pressure, density) or the (specific volume, specific enthalpy) variable sets. In order to reduce the challenge of adding a new fluid property, properties may be implemented partially.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗