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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗
DOE OSTI2024

Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulated wildfire burned area over the CONUS during 2001-2020

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM). A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

Liu, Ye↗
DOE OSTI2023

Wave climate and energy resources in the Mariana Islands from a 42-year high-resolution hindcast

We report a high-resolution wave hindcast from 1979 to 2020 was developed for Guam and the Commonwealth of the Northern Mariana Islands, which are influenced by mesoscale and synoptic weather systems from the western Pacific Rim to the Central Pacific. The spectral wave modeling utilized structured global and unstructured regional grids with improved resolution in nearshore waters, where wave resources development is most feasible. The hindcast demonstrates its capability in capturing multi-modal seas through reproduction of bulk and partitioned wave parameters derived from altimetry and buoy measurements. The local wave climate is influenced by the year-round trade winds and tropical cyclones as well as seasonal monsoons, frontal systems, and mid-latitude high- and low-pressure systems. The strong intra-annual variation of the significant wave height and power flux reflects transitions between local and distant weather systems, which account for the diverse wave conditions comprised of short-period wind waves, intermediate-period seas, and long-period swells around the islands. Among the Pacific island regions, spectral partitioning is particularly important for describing the dominant wave components by period and direction with pertinent information conducive to energy resources characterization and coastal zone management in the Mariana Islands.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Molten‐Salt‐Mediated Chemical Looping Oxidative Dehydrogenation of Ethane with In‐Situ Carbon Capture and Utilization

Abstract The molten‐salt‐mediated oxidative dehydrogenation (MM‐ODH) of ethane (C 2 H 6 ) via a chemical looping scheme represents an effective carbon capture and utilization (CCU) method for the valorization of ethane‐rich shale gas and concurrent mitigation of carbon dioxide (CO 2 ) emissions. Here, stepwise experimentation with Li 2 CO 3 ‐Na 2 CO 3 ‐K 2 CO 3 (LNK) ternary salts (i) assessed how each component of the LNK mixture impacted ethane MM‐ODH performance and (ii) explored physicochemical and thermodynamic mechanisms behind melt‐induced changes to ethylene (C 2 H 4 ) and carbon monoxide (CO) yields. Of fifteen screened LNK compositions, nine exhibited ethylene yields greater than 50 % at 800 °C while maintaining C 2 H 4 selectivities of 85 % or higher. LNK salts rich in Li 2 CO 3 content yielded more ethylene and CO on average than their counterparts, and net CO 2 capture per cycle reached a maximum of ~75 %. Extended MM‐ODH cycling also demonstrated long‐term stability of a high‐performing LNK medium. Density functional theory (DFT) calculations andab initiomolecular dynamics (AIMD) simulations suggested that the molten salt does not directly activate C 2 H 6 . Meanwhile, an empirical model informed by experimental data and reaction thermodynamics adequately predicted overall MM‐ODH performance from LNK composition and provided insights into the system′s primary drivers.

Chemistry↗
DOE OSTI2025

Sandwiching of MOF nanoparticles between graphene oxide nanosheets among ice grains

Current strategies to tailor the formation of nanoparticle clusters require specificity and directionality built into the surface functionalization of the nanoparticles by involved chemistries that can alter their properties. Here, we describe a non-disruptive approach to place nanomaterials of different shapes between nanosheets, i.e., nano-sandwiches, absent any pre-modification of the components. We demonstrate this with metal-organic frameworks (MOFs) and silicon oxide (SiO 2 ) nanoparticles sandwiched between graphene oxide (GO) nanosheets, MOF-GO and SiO 2 -GO, respectively. For the MOF-GO, the MOF shows significantly enhanced conductivity and retains its original crystallinity, even after one-year exposure to aqueous acid/base solutions, where the GO effectively encapsulates the MOF, shielding it from polar molecules and ions. The MOF-GOs are shown to effectively capture CO 2 from a high-humidity flue gas while fully maintaining their crystallinities and porosities. Similar behavior is found for other MOFs, including water-sensitive HKUST-1 and MOF-5, promoting the use of MOFs in practical applications. The nanoparticle sandwich strategy provides opportunities for materials science in the design of nanoparticle clusters consisting of different materials and shapes with predetermined spatial arrangements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Influence of cellular redox reactions on the structure and function of light harvesting and photosystems

Photosynthesis enables the conversion of one of the most abundant and free forms of energy, sunlight, into chemical bonds through the utilization of highly tailored protein complexes. These enzymes work in unison to absorb, convert, and transform light into high-energy electrons which are used for various functions important to metabolism and cellular protection. Over the last ∼50 years, photosynthetic organisms, such as cyanobacteria, have been adapted and engineered to produce valuable compounds like hydrogen and ethylene, among others. Often this is performed by removing native and/or adding in exogenous energy utilization pathways so that light energy is re-directed towards the synthesis of desired compounds. However, the interplay between primary light capture, conversion reactions, and the downstream electron utilization sinks is not fully understood. Further complicating these strategies are the plethora of compensatory mechanisms that facilitate steady electron flow and the maintenance of photosynthesis under dynamic conditions. This manifests as structural and functional plasticity of the photosynthetic machinery, often seen in modulations of oligomeric compositions or changes in protein-protein interactions and coupling with redox enzymes. Understanding these mechanisms is crucial to biotechnology applications because re-engineering electron utilization sinks has profoundly different effects on the light capture and conversion reactions of photosynthesis. Optimization requires a molecular-level understanding of the functional interrelationships between electron sinks and photosynthetic components that influence photosynthetic efficiencies to realize potential improvements in product yields. Here, we aim to highlight how perturbation of reductive reactions is revealing the functional plasticity in key components of the photosynthetic energy transduction pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Probing Condensed-Phase Structure and Dynamics in Hierarchical Zeolites and Nanosheets for Catalytic Upgradation of Biomass (Final Report)

Understanding complex reaction pathways in systems governed by multi-scale collective interactions across time and length scales remains a central scientific challenge. This project was guided by the hypothesis that the interplay among oligomers, solvents, and active sites can be tuned by a suitable choice of solvation environment and pore architecture in solid-acid catalysts to direct chemical transformations relevant to biomass conversion. Zeolites and zeolite nanosheets were used as model platforms, allowing for the interaction of macromolecules with the surface of the zeolite nanosheets and with smaller pores that host catalytically active sites. To investigate these coupled phenomena, we employ a multi-scale computational framework that integrates molecular-level descriptions with advanced sampling approaches to capture key physical and chemical interactions. Our work through this project improved fundamental understanding of how reactants and solid-acid catalysts interact in solvent-rich environments, thereby enabling the rational design of catalytic systems that upgrade biomass with enhanced selectivity and energy efficiency. In addition, the project developed advanced sampling methodologies critical for disentangling complex, reactive processes in multi-component catalytic environments.

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

Design and Experimental Demonstration of an Additive Manufactured Smart Oxy-Methane Burner for High Pressure and Supercritical Combustion

Pressurized oxy combustion-based systems can improve efficiency by recovering latent heat of the steam in the Flue Gas and achieving 90% CO2 capture. In addition, the novel Directly Heated Supercritical Carbon Dioxide (DH-SCO2) power cycles can achieve high thermal efficiencies and provide nearly full carbon capture. Additionally, due to the reduction of flue gas at higher pressure, smaller system size and capital cost reductions are also possible. Recent thermodynamic analysis of the DH-SCO2 cycle performed by the UTEP research team shows that combustion conditions in the vicinity of 300 bar pressure and 1000-1400 K temperature allow for relatively high system efficiencies while operating within the limit of available combustor materials. However, the realization of a directly heated supercritical power cycle requires combustion systems to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K). The thermodynamic properties along with the combustion properties and kinetics are unexplored at such conditions. Additionally, the interaction of the supercritical environment with energy components is also unknown. High-pressure combustion tests are performed using a smart burner at some intermediate pressure ranges (<20 bar) to help minimize these knowledge gaps. The knowledge obtained from the high-pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. The obtained data will act as a systematic first step in testing at higher pressures of 100 and 300 bar pressures.The primary purpose of this Dissertation is to demonstrate the operability of a low NOx smart burner for oxy-methane combustion at high pressure (< 20 bar) and scalable up to supercritical conditions. A shear co-axial smart burner is designed with a real-time temperature monitoring capability to understand the burner face interaction at high-pressure conditions. In addition, the burner has four independent injection ports to allow the independent injection of fuel and dilution gases in the combustor. The maximum operating capability of the burner is 575 kWth. The burner was fabricated using a Laser Powder Bed Fusion process with Nickel Alloy 718. A powder removal technology was invented comprising ultrasonic vibration, liquid nitrogen exposure and media blasting to remove powders from internal channels of the burner. The burner operability tests are performed in the high-pressure combustor and the swirl combustor. The high-pressure combustor was used to investigate the burner operability and thermal soak back at different pressurized conditions. The experimental tests in high-pressure combustor up to 275 kWth input resulted in 16.5 bar chamber pressure and 198°C thermal soaks back to the burner. The burner was capable of providing the required thermal input within a 3% deviation range. In addition, soot formation occurred at high-pressure tests. The swirl combustor was used to observe the flame stability of the burner. Flame lift-off was observed for jet velocities above 450 m/s. Additionally, lift-off decreased for low co-flow velocities. CO2 dilution experiments showed increased flame instabilities for all conditions above 50% dilution ratios. At lower thermal inputs, partial flame blow-offs occurred for dilution ratios above 50%. All conditions significantly reduced the flame temperature and increased the flame lift-off height. Finally, a 2nd generation AM smart burner was designed using the knowledge from the 1st generation burner experiments. The 2nd generation burner incorporated two sets of swirlers with 0.9 swirl no. A cooling system was also designed for long-duration tests at higher pressures. The thermal input and division of the burner's power are kept the same as the 1st generation burner. The burner is to be fabricated using nickel-alloy 718 for high-pressure handling capability. The design can sustain at high-pressure conditions up to 100 bar.

Islam, Md Nawshad Arslan↗
DOE OSTI2024

Light Water Reactor Sustainability Program: Technical and Economic Considerations for Uprate of Existing Nuclear Reactors with Cogeneration

The United States nuclear reactor fleet consists of 63 pressurized water reactors and 31 boiling water reactors and is a pivotal component in the nation's energy infrastructure, supplying approximately 97 GW e of clean power. With the country's commitment to decarbonization by 2050, these reactors are not only instrumental in decarbonizing the electricity grid but also play a critical role in decarbonizing industrial processes, producing clean fuels, and scaling up CO 2 removal. This report delves into the potential for power uprates in the existing fleet to contribute to these decarbonization efforts, focusing on the expansion of capacity for applications such as hydrogen production and carbon capture and sequestration. Building on previous research, the report explores regional market demands for hydrogen, oxygen, and carbon dioxide, financial implications of oxygen and CO 2 sales from high-temperature steam electrolysis systems, and the potential for direct air capture systems paired with uprated nuclear plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗
DOE OSTI2024

Topological Data Analysis for Particulate Gels

Soft gels, formed via the self-assembly of particulate materials, exhibit intricate multiscale structures that provide them with flexibility and resilience when subjected to external stresses. Here, this work combines particle simulations and topological data analysis (TDA) to characterize the complex multiscale structure of soft gels. Our TDA analysis focuses on the use of the Euler characteristic, which is an interpretable and computationally scalable topological descriptor that is combined with filtration operations to obtain information on the geometric (local) and topological (global) structure of soft gels. We reduce the topological information obtained with TDA using principal component analysis (PCA) and show that this provides an informative low-dimensional representation of the gel structure. We use the proposed computational framework to investigate the influence of gel preparation (e.g., quench rate, volume fraction) on soft gel structure and to explore dynamic deformations that emerge under oscillatory shear in various response regimes (linear, nonlinear, and flow). Our analysis provides evidence of the existence of hierarchical structures in soft gels, which are not easily identifiable otherwise. Moreover, our analysis reveals direct correlations between topological changes of the gel structure under deformation and mechanical phenomena distinctive of gel materials, such as stiffening and yielding. In summary, we show that TDA facilitates the mathematical representation, quantification, and analysis of soft gel structures, extending traditional network analysis methods to capture both local and global organization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fullerene-like defects in high-temperature neutron-irradiated nuclear graphite

Irradiation-induced defect evolution in graphite is particularly important for its application in graphite-moderated nuclear reactors. The evolution of defects directly influences macroscopically observed property changes in irradiated nuclear graphite which, in turn, can govern the lifetime of graphite components. This article reports novel defect structures and the irradiation response of microstructural features occurring in high-temperature irradiated nuclear graphite IG-110. High resolution transmission electron microscopy (HRTEM) was used to characterize specimens neutron-irradiated at a high temperature (≥ 800°C) at doses of 1.73 and 3.56 atomic displacements per atom (dpa). Concentric shelled and fullerene-like defects were found to result in swelling along the c-axis and contraction along the a/b-axis of crystallites. Furthermore, such defects are shown to occur within, and partially fill, Mrozowski cracks prior to turnaround dose. In addition, in situ TEM under similar irradiation conditions was used to capture the real-time dynamic evolution of defects, providing unambiguous analysis of the evolution of the graphite structures during irradiation. Here, the results suggest the mainstream theory for radiation damage in nuclear graphite (which assumes additional basal plane formation as the sole reason) to be an incorrect interpretation of defect evolution contributing to irradiation-induced property changes at higher temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Hot-carrier dynamics in InAs/AlAsSb multiple-quantum wells

A type-II InAs/AlAs 0.16 Sb 0.84 multiple-quantum well sample is investigated for the photoexcited carrier dynamics as a function of excitation photon energy and lattice temperature. Time-resolved measurements are performed using a near-infrared pump pulse, with photon energies near to and above the band gap, probed with a terahertz probe pulse. The transient terahertz absorption is characterized by a multi-rise, multi-decay function that captures long-lived decay times and a metastable state for an excess-photon energy of >100 meV. For sufficient excess-photon energy, excitation of the metastable state is followed by a transition to the long-lived states. Excitation dependence of the long-lived states map onto a nearly-direct band gap (E g ) density of states with an Urbach tail below E g . As temperature increases, the long-lived decay times increase < E g , due to the increased phonon interaction of the unintentional defect states, and by phonon stabilization of the hot carriers > E g . Additionally, Auger (and/or trap-assisted Auger) scattering above the onset of the plateau may also contribute to longer hot-carrier lifetimes. Meanwhile, the initial decay component shows strong dependence on excitation energy and temperature, reflecting the complicated initial transfer of energy between valence-band and defect states, indicating methods to further prolong hot carriers for technological applications.

14 SOLAR ENERGY↗
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Urban weather modeling using WRF: linking physical assumptions, code implementation, and observational needs

The Weather Research and Forecasting (WRF) model includes urban schemes that simulate the influence of urban surfaces on the atmosphere using parameterizations for flux, and radiative exchanges. Three core schemes – the Bulk urban parameterization, Single-Layer Urban Canopy Model (SLUCM), and Multi-Layer Urban Canopy Model (MLUCM) – represent increasing levels of complexity. Although the parameterizations within these urban schemes are described in the literature, their specific implementation remains poorly documented, thus slowing down model development efforts. This manuscript provides a roadmap to the three urban schemes in WRF version 4.5.2, presenting equations using the same symbols as in the model code, along with references to code lines, and including graphics and explanations that connect the code to its physical foundations. Our thorough review of the urban parameterizations implemented in WRF version 4.5.2 highlighted a handful of parameters that may introduce discontinuities in simulations: (i) in the SLUCM, a 1 mm h −1 rain rate threshold is employed to switch between two minimum moisture availability parameterizations, thus impacting latent heat flux calculations; (ii) in the SLUCM a threshold is used to partition shortwave radiation into direct and diffuse components; (iii) in all three urban schemes, the bulk Richardson number is employed to select the similarity function, which influences the vertical distribution of heat and momentum. We also identified a highly simplified treatment of the radiative balance on roof surfaces. The implications of these simplifications can be assessed through targeted observations across relevant conditions, including varying precipitation rates, cloud cover, and transitions between stability regimes. Furthermore, the widespread application of the Monin-Obukhov similarity theory in these urban schemes warrants model evaluation under highly stable and unstable conditions and in heterogeneous urban settings with variable land cover and building heights on scales finer than model resolution. To address these challenges, we offer guidance on observational strategies, emphasizing the need for multi-parametric measurements to capture potential compensating biases and multi-height measurements that align with the levels where quantities are diagnostic and prognosed in the model (i.e., the lowest atmospheric level of the WRF model). Finally, our inspection of the code revealed implementation bugs that have now been corrected in WRF versions 4.6.0 and 4.6.1. Sensitivity tests over the Atlanta urban area show that these corrections affect surface temperatures, underscoring the importance of performing rigorous documentation and verification of the implementation of parameterizations in model code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assessment of Updraft Modeling Bias Using Computational Fluid Dynamics

Golden Eagle (Aquila chrysaetos) habitats may overlap with wind energy development in some regions of the US. Eagles, and similar soaring bird species, are therefore at risk of collision with wind turbines when flying through wind farms. Recently developed behavioral modeling approaches can predict the presence of eagles near turbines within the rotor-swept layer but require reliable prediction of atmospheric flowfield conditions. In particular, the vertical component of the wind speed dictates a soaring bird's ability to maintain or gain altitude, since they rely on updrafts to subsidize their flight. In this work, we investigate the atmospheric conditions around a wind farm in complex terrain and compare methods for atmospheric characterization. We use computational fluid dynamics (specifically, large-eddy simulations, or LES) to simulate the atmospheric boundary layer over a region encompassing multiple wind farms with high temporal and spatial resolution (seconds and 10's of meters, respectively). We compare traditional non-simulation-based methods of determining the orographic updraft potential based on wind direction, terrain slope and aspect, with the flowfields from LES that include both orographic updrafts alone and combined thermal and orographic updrafts. Preliminary analysis suggests that although the model captures the horizontal pattern of vertical updrafts, their magnitude can be improved with information about the surface heat flux, which is usually correlated with time of the day. Within our study region, we found that the low-fidelity model may over- or underestimate updraft potential by up to 400% at 80 m AGL, depending on local orographic features. This can result in an inaccurate representation of eagle presence and, consequently, risk. Another important finding is that flowfield time-averaging can hide important details about the flight environment, including how thermally generated flow structures within the atmospheric boundary layer (e.g., convective rolls and/or cells) may be important drivers of eagle flight.

atmospheric turbulence↗