Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CAPTURE EFFECT”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

NMACFoam (Numerical-model for Membrane-spacer Assemblies and Configurations in OpenFOAM) [SWR-23-57]

NMACFoam is a computational fluid dynamics tool for simulating flow and solids transport in membrane-spacer channels pertaining to reverse osmosis or nanofiltration applications. It is developed on the OpenFOAM framework and allows for simulating spacers with complex geometries. It includes porous wall boundary conditions for membranes and can accurately capture concentration polarization effects. One can perform large calculations at module-scale domain sizes using high performance computing resources with NMACFoam, which scales to 1000s of processors for problems with 1-10 million cells.

Sitaraman, Hariswaran↗
DOE OSTI2023

Justice 40 Tool (J40 Tool) v1.0

The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract. Instead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.

Heleno, Miguel↗
DOE OSTI2017

The Changing Character of Twenty-First-Century Precipitation over the Western United States in the Variable-Resolution CESM

Abstract The changing characters of precipitation frequency and intensity have been comprehensively investigated from the recent historical period to the end of the twenty-first century over the western United States. Variable-resolution Community Earth System Model (VR-CESM) ensemble simulations are applied with a fine grid resolution of ~0.25° over the study area. Simulations are forced with prescribed sea surface temperatures, sea ice extent, and greenhouse gas concentrations from the representative concentration pathway 8.5 (RCP8.5) scenario. VR-CESM is shown to be effective at accurately capturing the spatial patterns of the historical precipitation climatology. The results of VR-CESM output provide significantly regional details with crucial enhancement of precipitation representations over complex terrain. In the Intermountain West and U.S. Southwest, a statistically significant increase in mean precipitation and rainy days through midcentury is observed, although this trend is tempered by the end of the century in response to a decrease in relative humidity. Over the Pacific Northwest, extreme precipitation events are observed to increase significantly as a result of increased cool season integrated vapor transport associated with a moistening of the cool seasons and drying through the warm seasons. In particular, extreme precipitation in this region appears to increase more rapidly than would be predicted by the Clausius–Clapeyron relationship. No clear climate signal emerges in mean precipitation or extreme events in the majority of California, where the precipitation climatology is attributed to large interannual variabilities that are tied closely to ENSO patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Ultrabroadband infrared near-field spectroscopy and imaging of local resonators in percolative gold films

Percolation processes are ubiquitous in nature and are responsible for many critical phenomena such as first-order phase transitions and infectious epidemic networks. The optical properties of a percolative medium can generally be captured by the effective medium approximation (EMA) when the degree of percolation and the properties of the constituent materials are properly addressed. However, the important local collective responses of nanoclusters in the deep subwavelength regime are often only phenomenologically addressed in the standard EMA formalism. Additionally, a comprehensive method that measures local light–matter interactions and registers how the local responses influence global optical properties has yet to be established on a firm basis. In this paper, we use infrared nanoimaging/spectroscopy to investigate percolative gold films in the vicinity of the critical percolation threshold. We demonstrate experimentally and theoretically that the near-field spectra yield quantitative information of the characteristic length scale of the local gold clusters and their relative oscillator strengths. As a result, EMA analysis can be augmented with near-field nano-spectroscopy to yield better predictability of the far-field reflection spectrum at the corresponding spectral range.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Mesoscale Benchmark Demonstration, Problem 1: Mesoscale Simulations of Intra-granular Fission Gas Bubbles in UO 2 under Post-irradiation Thermal Annealing

A study was conducted to evaluate the capabilities of different numerical methods used to represent microstructure behavior at the mesoscale for irradiated material using an idealized benchmark problem. The purpose of the mesoscale benchmark problem was to provide a common basis to assess several mesoscale methods with the objective of identifying the strengths and areas of improvement in the predictive modeling of microstructure evolution. In this work, mesoscale models (phase-field, Potts, and kinetic Monte Carlo) developed by PNNL, INL, SNL, and ORNL were used to calculate the evolution kinetics of intra-granular fission gas bubbles in UO 2 fuel under post-irradiation thermal annealing conditions. The benchmark problem was constructed to include important microstructural evolution mechanisms on the kinetics of intra-granular fission gas bubble behavior such as the atomic diffusion of Xe atoms, U vacancies, and O vacancies, the effect of vacancy capture and emission from defects, and the elastic interaction of non-equilibrium gas bubbles. An idealized set of assumptions was imposed on the benchmark problem to simplify the mechanisms considered. The capability and numerical efficiency of different models are compared against selected experimental and simulation results. These comparisons find that the phase-field methods, by the nature of the free energy formulation, are able to represent a larger subset of the mechanisms influencing the intra-granular bubble growth and coarsening mechanisms in the idealized benchmark problem as compared to the Potts and kinetic Monte Carlo methods. It is recognized that the mesoscale benchmark problem as formulated does not specifically highlight the strengths of the discrete particle modeling used in the Potts and kinetic Monte Carlo methods. Future efforts are recommended to construct increasingly more complex mesoscale benchmark problems to further verify and validate the predictive capabilities of the mesoscale modeling methods used in this study.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Low-temperature Stirling Engine for Geothermal Electricity Generation

Up to 2700 terawatt-hours per year of geothermal electricity generation capacity has been shown to be available within North America, typically with wells drilled into geologically active regions of the earth's crust where this energy is concentrated (Huttrer, 2001). Of this potential, about half is considered to have temperatures high enough for conventional (steam-based) power production, while the other half requires unconventional power conversion approaches, such as organic Rankine cycle systems or Stirling engines. If captured and converted effectively, geothermal power generation could replace up to 100GW of fossil fuel electric power generation, leading to a significant reduction of US power sector emissions. In addition, with the rapid growth of hydro-fracking in oil and gas production, there are smaller-scale distributed power generation opportunities in heated liquids that are co-produced with the main products. Since 2006, Cool Energy, Inc. (CEI) has designed, fabricated and tested four generations of low-temperature (100°C to 300°C) Stirling engine power conversion equipment. The electric power output of these engines has been demonstrated at over 2kWe and over 16% thermal conversion efficiency for an input temperature of 215°C and a rejection temperature of 15°C. Initial pilot units have been shipped to development partners for further testing and validation, and significantly larger engines (20+ kWe) have been shown to be feasible and conceptually designed. Originally intended for waste heat recovery (WHR) applications, these engines are easily adaptable to geothermal heat sources, as the heat supply temperatures are similar. Both the current and the 20+ kWe designs use novel approaches of self-lubricating, low-wear-rate bearing surfaces, non-metallic regenerators, and high-effectiveness heat exchangers. By extending CEI's current 3 kWe SolarHeart® Engine into the tens of kWe range, many additional applications are possible, as one 20 kWe design produces nearly seven times the power output of the 3 kWe unit but at only 2.5 times the estimated fabrication cost. Phase I of the proposed SBIR program will therefore study the feasibility of generating electricity with one or more 20 kWe or larger Stirling engines, powered by geothermal heat produced by current and possibly some forward-looking borehole extraction methods, and from producing oil and gas wells. The feasibility study will include full analysis of the thermodynamic and heat transfer processes within the engine (necessary to produce optimum theoretical designs and performance maps), the cost of pumping the geothermal heat recovery fluid, and how the system tradeoffs impact the overall system economics. The goal is a geothermal system design that could be demonstrated during a Phase II follow-on program at a field test site.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Advanced Numerical Model for Irradiated Concrete

In this report, we establish a numerical model for concrete exposed to irradiation to address these three critical points. The model accounts for creep in the cement paste and its coupling with damage, temperature and relative humidity. The shift in failure mode with the loading rate is also properly represented. The numerical model for creep has been validated and calibrated against different experiments in the literature [Wittmann, 1970, Le Roy, 1995]. Results from a simplified model are shown to showcase the ability of numerical homogenization to simulate irradiation effects in concrete. In future works, the complete model will be applied to the analysis of the irradiation experiments of Elleuch et al. [1972] and Kelly et al. [1969]. This requires a careful examination of the experimental environmental conditions as in both cases certain critical information are missing, including the relative humidity history. A sensitivity analysis will be conducted to provide lower and upper bounds of the concrete expansion under irradiation, and check if the scatter in the simulated results matches the one found in experiments. The numerical and experimental results will be compared in terms of expansion and loss of mechanical stiffness and strength. Both effects should be captured accordingly by the model to validate it. Once the model has been validated on these two experiments, it can be applied to simulate concrete from nuclear power plants. To do so, the materials used in these concrete must be as well characterized as possible. The main parameters required are the mechanical properties of each constituent in the concrete (aggregates, cement paste), namely the elastic modulus, the creep properties, the tensile and compressive strength, the thermal expansion coefficient, and the drying shrinkage. These can be either measured experimentally, estimated from the initial composition in the case of cement paste, or back-calculated from mechanical tests on concrete. If some are unknown, a sensitivity analysis must be carried out to provide lower and upper bounds of the material behaviour. Finally, the model can be used as a basis to formulate a macroscopic material model for concrete subject to irradiation, which later can be used in structural analyses to estimate the structural impact of irradiation on nuclear power plants.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synergistic Computational and Microstructural Design of Next- Generation High-Temperature Austenitic Stainless Steels

The purpose of this project was to: 1) study deformation twinning, its evolution, thermal stability, and the contribution on mechanical response of the new advanced stainless steels, especially at elevated temperatures; 2) study alumina-scale formation on the surface, as an alternative for conventional chromium oxide, that shows better oxidation resistance, through alloy design; and 3) design new generation of high temperature stainless steels that form alumina scale and have thermally stable nano-twins. The work involved few baseline alloys for investigating the twin formation under tensile loading, thermal stability of these twins, and the role of deformation twins on the mechanical response of the alloys. These baseline alloys included Hadfield Steel (Fe-13Mn-1C), 316, 316L and 316N stainless steels. Another baseline alloy was studied for alumina-scale formation investigations. Hadfield steel showed twinning but undesired second phases formed at higher temperatures. 316N stainless steel did not show signs of deformation twinning. Conventional 316 stainless steel demonstrated extensive deformation twinning at room temperature. Investigations on this alloy, both in single crystalline and polycrystalline forms, showed that deformation twins evolve in a hierarchical manner, consisting of micron–sized bundles of nano-twins. The width of nano-twins stays almost constant as the extent of strain increases, but the width and number of the bundles increase with increasing strain. A systematic thermomechanical cycling study showed that the twins were stable at temperatures as high as 900°C, after the dislocations are annealed out. Using such cycles, volume fraction of the thermally stable deformation twins were increased up to 40% in 316 stainless steel. Using computational thermodynamics and kinetics calculations, we designed two generations of advanced austenitic stainless steels. In the first generation, Alloy 1, which had been proposed as an alumina-forming austenitic stainless steel, is fully austenitic, but possesses carbides that were not dissolvable and could not be controlled. This alloy also did not show deformation twinning. Alloy 2 was designed based on alloy 1, but was not fully austenitic and had significant traces of uncontrollable precipitates as well. Alloy 3, also designed based on alloy 1, was mainly austenitic with evolution of a second phase along the grain boundaries, but also had precipitates that were not controllable. Based on the knowledge gained from the first generation of the designed steels, two more steels, called PGAA1 and PGAA2, were proposed using genetic algorithms that, based on the modelling, were supposed to exhibit alumina-scale formation. PGAA1, however, did not demonstrate a fully austenitic structure. PGAA2 could achieve a mostly austenitic structure through thermo-mechanical processing, and was then used for oxidation tests. The oxidation tests of PGAA2, with and without nitrogen impurities, along with alloy 1, suggested that PGAA2 can form alumina-scale similar to alloy 1, but N impurity will prevent formation of such a scale, probably through formation of aluminum nitrides. For the above mentioned genetic algorithm framework of alloy design, separate models were developed for specific design criteria. For prediction of alumina formation in stainless steels, a model was constructed based off of two criteria – effective valence and third element effect. These criteria capture the thermodynamics and kinetics of alumina formation in steels. To test the efficacy and robustness of this model, they were tested against alloys in the literature which had been experimentally verified to exhibit alumina formation and the predictions were in excellent agreement with the experiments. Another meta-model for prediction of twinning in unknown steel compositions was developed by an informatics based machine learning/data mining approach. Stacking Fault Energy data was captured from the literature for a large number of steel compositions and then this data was used to build a classifier to predict deformation mechanisms. Here a training set-test set based analysis was performed to test performance. The above genetic algorithm based optimization framework for alloy design was exhibited to be a successful methodology for accelerated materials discovery in the context of alloy design.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Preparation of NO 2 -Aged Silver-Functionalized Silica-Aerogel and Silver Mordenite Samples

Reprocessing used nuclear fuel can result in the volatilization of radioactive gaseous species, including 129 I, into the various process off-gas streams. In order to comply with US regulatory requirements, plant off-gas streams must be treated to remove the iodine prior to discharging the off-gas into the environment. The performance of available gas removal methods depends not only on the concentration of the volatile radioisotope of interest, but also on other constituents that could be present in the reprocessing off-gas streams. Some of the constituents, such as NOx produced during fuel dissolution, are known to have deleterious effects on the capture performance of silver-based sorbents used for iodine removal. Commercially available reduced silver mordenite (AgZ) has an iodine saturation concentration of 7.0-9.0 wt%, and its iodine sorption capacity is reduced by 20-50% as a result of NO2 aging. Silverfunctionalized silica aerogel (AgAerogel), an alternative for iodine capture, has an initial iodine saturation of 29.0 wt% and its iodine capacity is only reduced by 15% from NO2 aging. Understanding the differences in aging behavior between AgZ and AgAerogel is critical to determining the behavior of these sorbents under realistic off-gas conditions. To assist in future technical studies on this topic, samples of both AgZ and AgAerogel were aged with NO2. In the experiment, 10.2190 g of AgZ and 10.1771 g of AgAerogel were exposed to a static 0.75% NO 2 /dry air blend for a period of 28 days. The samples were then removed and stored under argon until needed for future experiments.=

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Geometric pre-patterning based tuning of the period doubling onset strain during thin film wrinkling

Wrinkling of supported thin films is an easy-to-implement and low-cost fabrication technique for generation of stretch-tunable periodic micro and nano-scale structures. However, the tunability of such structures is often limited by the emergence of an undesirable period doubled mode at high strains. Predictively tuning the onset strain for period doubling via existing techniques requires one to have extensive knowledge about the nonlinear pattern formation behavior. Herein, a geometric pre-patterning based technique is introduced to delay the onset of period doubling that can be implemented to predictively tune the onset strain even with limited system knowledge. The technique comprises pre-patterning the film/base bilayer with a sinusoidal pattern that has the same period as the natural wrinkle period of the system. The effectiveness of this technique has been verified via physical and computational experiments on the polydimethylsiloxane/glass bilayer system. It is observed that the period doubling onset strain can be increased from the typical value of 20% for flat films to greater than 30% with a modest pre-pattern aspect ratio (2∙amplitude/period) of 0.15. In addition, finite element simulations reveal that (i) the onset strain can be increased up to a limit by increasing the amplitude of the pre-patterns and (ii) the delaying effect can be captured entirely by the pre-pattern geometry. As a result, one can implement this technique even with limited system knowledge, such as material properties or film thickness, by simply replicating pre-existing wrinkled patterns to generate prepatterned bilayers. Thus, geometric pre-patterning is a practical scheme to suppress period doubling that can increase the operating range of stretch-tunable wrinkle-based devices by at least 50%.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development and Validation of SAM Multi-dimensional Flow Model for Thermal Mixing and Stratification Modeling

Thermal mixing and stratification in large pools or enclosures are very important phenomena that are critical to nuclear reactor safety. Because of the wide ranges of time and length scales associated with such phenomena, accurate modeling and simulation of thermal mixing and stratification remain as the key unresolved, challenging problems for reactor transient analyses. In traditional system analysis codes, simplified zero-dimensional (0-D) models are widely used for their high numerical efficiency, but they generally suffer from very limited prediction accuracies or range of applicability. Like traditional system analysis codes, the current version of the SAM code has implemented such simplified 0-D and one-dimensional mixing models. On the other hand, high-resolution Computational Fluid Dynamics (CFD) tools are often used to model complex thermal mixing and stratification phenomena. They are, however, generally numerically expensive, and they require large amounts of computational resources. It is therefore desirable to implement advanced and efficient thermal mixing and stratification modeling capabilities embedded in a system analysis code. This approach will improve the accuracy of reactor safety analyses when thermal mixing and stratification are involved, and also avoid using the large computational resources needed for high-resolution CFD analysis. Currently, with the support of the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation program, an effort has been launched to develop and implement a multi-dimensional flow model in the system analysis code SAM, and demonstrate its applications to model thermal mixing and stratification phenomena in large enclosures. The main outcomes of this research and development activity are summarized in this report, which presents an attempt to include a built-in advanced multi-dimensional flow model in a system analysis code with the focus on overcoming the simulation challenges of thermal mixing and stratification phenomena. In this report, we start with the introduction of existing SAM code capabilities to simulate thermal mixing and stratification phenomena, which is followed by a short summary of the multi-dimensional model implemented in the SAM code, including both the physical model and the Finite Element Method code implementation. In this study, two options were implemented in the SAM code to model turbulent flows: a relatively simple built-in turbulence model and an interface to accept externally computed turbulent viscosities (e.g., from a high- resolution CFD simulation). Code validation studies on this newly added capability were then carried out to compare SAM simulation results with experimental data from the SUPERCAVNA facility, which was designed to study the complex flow recirculation and thermal stratification phenomena relevant to sodium fast reactor designs. In this study, one transient and two steady-state test cases were used for code validation. Different approaches have been used to model the complex turbulence flow fields in the SUPERCAVNA facility. A highly simplified zero-equation turbulence model was first used, but it was determined that it is too simple to capture the complex turbulence flow fields in these test cases. Subsequently, the code validation continued with the use of turbulent viscosity data from high-resolution STAR-CCM+ CFD simulations to improve the accuracy of the results. Using this approach, the SAM simulation results showed very good agreement with both the SUPERCAVNA experimental data and STAR-CCM+ simulation results. In this report, we demonstrate the development, implementation, and successful validation of a multi-dimensional flow model in the SAM code, which aims to improve the simulation accuracy for complex thermal mixing and stratification phenomena. Lessons have also been learned, including that in cases where the flow fields are not well predicted by the zero-equation model, the iinput of turbulent viscosities from an external source can enhance the overall predictive capabilities needed to accurately capture complex thermal-hydraulic phenomena. Therefore, future research will be needed to further improve the code’s capabilities, such as by developing a more efficient and robust approach to capture the turbulence effects in the SAM code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Estimation of the Attenuation Caused by Power Line Towers on an E1-HEMP Induced Excitation

In a transmission line, the coupling between a line and a tower above ground is evaluated when the excitation is an E1 high-altitude electromagnetic pulse (HEMP). The model focuses on capturing correctly the effect of the coupling on the peak of the HEMP induced current that propagates along the line. This assessment is necessary to accurately estimate the effect of the excitation on the systems and components of the power grid. This analysis is a step towards a quantitative evaluation of HEMP excitation on the power grid. The results obtained indicate that the effect can be significant, especially for lines heights of 20 meters or more.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Cost and Performance Baseline for Fossil Energy Plants, Volume 3 – Low Rank Coal and Natural Gas to Electricity

Presentation by the National Energy Technology Laboratory (NETL) on performance and cost results of utilizing low rank coals and natural gas to produce electricity, including the effects of carbon capture. The coal plants are located in elevated terrain, and the natural gas plants are sited in the same conditions to allow comparability of elevation impacts. The study reports on overall performance of both fuel types, without and with carbon capture, and gives comparisons of the levelized cost of electricity for each unit. This presentation was given at the 2022 Pittsburgh Coal Conference.

James, III, Robert E.↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Aeroelastic Modelling of Large Wind Turbines: Towards a Unified OpenFAST-SEAHOWL Approach

In recent years, the scale of wind turbines has significantly increased to maximize energy capture for a given site (particularly offshore), presenting new challenges in terms of structural design and dynamics. As towers grow taller and blades grow longer, flexion and torsion of the latter have a non-negligible impact on the behavior and performance of the turbine in terms of overall loads, power production, and control. When representing large-scale wind turbines numerically to capture these important effects, particular attention must therefore be given to the level of fidelity for representing each structural component, as well as the coupling scheme used between them to keep simulations accurate, stable, and efficient. To address this issue, we combine here the two following tools: (1) OpenFAST, the reference whole-turbine simulation tool from NREL with standalone modules covering each physics and the choice between loose coupling and a new tight coupling scheme for structural dynamics, and (2) SEAHOWL, the whole-turbine simulation tool from TotalEnergies with monolithic coupling of structural dynamics through Project Chrono and partitioned coupling for multiphysics interactions.

17 WIND ENERGY↗
DOE OSTI2026

FullWave — A Full Wave Parallel Code for Modeling RF Fields in Hot Tokamak Plasma

FullWave is a computer code that simulates how radio-frequency (RF) waves travel and deposit energy in the hot plasma inside a fusion reactor. RF waves are used to heat the plasma and drive electrical current, which is essential for sustaining fusion reactions. The code uses a new algorithm that can handle much finer spatial detail than previous codes — more than 100 times finer — while running efficiently on national supercomputers. It incorporates a detailed physics model that captures subtle kinetic effects important for accurate prediction of wave behavior. Under this project, FullWave was extended to cover multiple RF frequency ranges relevant to present and future tokamaks, and validated against experimental parameters from the DIII-D tokamak at General Atomics. Results were published in peer-reviewed journal articles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A seamless approach for evaluating climate models across spatial scales

In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗