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At least 307 records · Page 17

Effects of forest structural and compositional change on forest microclimates across a gradient of disturbance severity

Forest structural diversity and community composition are key in regulating forest microclimates. When disturbance affects structural diversity or composition, forest microclimates may be altered due to changes in soil temperature, soil water content, and light availability. It is unclear however which structural or compositional components, when changed or to what extent, result in microclimatic change. To address this question, we used data from a large scale, manipulative stem-girdling experiment in northern, lower Michigan—the Forest Resilience and Threshold Experiment (FoRTE). FoRTE follows a factorial design with multiple levels of disturbance severity (0, 45, 65, 85%) based on targeted reductions in gross leaf area index via stem-girdling induced mortality. These disturbance severity treatments are applied in two ways: either as top-down (largest trees are killed) or bottom-up (small to medium trees killed) treatments. We examined how multiple components of structural diversity and community composition changed as a product of disturbance severity and type, and then tested for resulting effects on forest microclimates (light availability, soil temperature, and soil water), using a multivariate, Random Forest framework. We found that measures of community composition (species richness, species evenness, and Shannon-Wiener Diversity Index) and stand structure (basal area, standard deviation of DBH, tree size diversity) declined more following disturbance than did measures of canopy cover, heterogeneity, arrangement, or height. However, when changes in each variable from pre- to post-disturbance, measured as log change, were employed in a multivariate, Random Forest regression framework, structural diversity measures of heterogeneity (rugosity, top rugosity), cover (canopy cover), and arrangement (porosity) were the most influential variables, but with differences among bottom-up and top-down treatments We found that the death of large trees from disturbance impacts soil temperature, water, and light environments more substantially and uniformly across disturbance gradients than does the death of smaller trees. Furthermore, our results have implications for both statistical and process-based modeling of forest disturbance.

54 ENVIRONMENTAL SCIENCES↗

All-sky aerosol direct radiative effects at the ARM SGP site

All-sky aerosol direct radiative effect (DRE) was estimated for the first time at the Atmospheric Radiation Measurement Southern Great Plains site using multi-year ground-based observations. The NASA Langley Fu-Liou radiation model was employed. Observed inputs for the radiation model include aerosol and cloud vertical extinction profile from Raman lidar; spectral aerosol optical depth, single-scattering albedo, and asymmetry factor from Aerosol Robotic Network; cloud water content profiles from radars; temperature and water vapor profiles from radiosondes; and surface shortwave spectral albedo from radiometers. A cloudy-sky radiative closure experiment was performed. The relative mean differences between modeled and observed surface downwelling shortwave total fluxes were 6% (7%) for transparent (opaque) cloudy-skies. The estimated annual mean all-sky aerosol DRE is -2.13±0.54W m -2 at the top of atmosphere (TOA) and -5.95±0.87 W m -2 at the surface, compared to -3.00±0.58 W m -2 AND -6.85±1.00 W m -2 , respectively, under clear-sky conditions. The seasonal cycle of all-sky aerosol DRE is similar to that of the clear-sky, except with secondary influences of the clouds: The cloud radiative effect is strongest (most negative) in the spring, which reduces the all-sky aerosol DRE. The relative uncertainties in all-sky aerosol DRE due to measurement errors are generally comparable to those in clear-sky conditions except for the aerosol single-scattering albedo. Finally, the TOA all-sky aerosol DRE relative uncertainty due to aerosol single-scattering albedo uncertainty is larger than that in clear-sky, leading to a larger total relative uncertainty. The measurement errors in cloud properties have small effects on the all-sky aerosol DRE.

54 ENVIRONMENTAL SCIENCES↗

Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics

Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Peatland emissions are projected to increase under climate change, as rising temperatures and shifting precipitation accelerate microbial metabolic pathways favorable for CH 4 production. However, how these changing environmental factors will impact peatland emissions over the long term remains unknown. Here, we investigate a novel data set spanning an exceptionally long 11 years to analyze the influence of soil temperature and water table elevation on peatland CH 4 emissions. We show that higher water tables dampen the springtime increases in CH 4 emissions as well as their subsequent decreases during late summer to fall. These results imply that any hydroclimatological changes in northern peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if temperature remains unchanged. Furthermore, advancing hydrological understanding in peatland watersheds will be crucial for improving predictions of CH 4 emissions.

54 ENVIRONMENTAL SCIENCES↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

Multiple Indicators of Extreme Changes in Snow-Dominated Streamflow Regimes, Yakima River Basin Region, USA

Snow plays a major role in the hydrological cycle. Variations in snow duration and timing can have a negative impact on water resources. Excluding predicted changes in snowmelt rates and amounts could result in deleterious infrastructure, military mission, and asset impacts at military bases across the US. A change in snowpack can also lead to water shortages, which in turn can affect the availability of irrigation water. We performed trend analyses of air temperature, snow water equivalent (SWE) at 22 SNOTEL stations, and streamflow extremes for selected rivers in the snow-dependent and heavily irrigated Yakima River Basin (YRB) located in the Pacific Northwest US. There was a clear trend of increasing air temperature in this study area over a 30 year period (water years 1991–2020). All stations indicated an increase in average air temperatures for December (0.97 °C/decade) and January (1.12 °C/decade). There was also an upward trend at most stations in February (0.28 °C/decade). In December–February, the average air temperatures were 0.82 °C/decade. From these trends, we estimate that, by 2060, the average air temperatures for December–February at most (82%) stations will be above freezing. Furthermore, analysis of SWE from selected SNOTEL stations indicated a decreasing trend in historical SWE, and a shift to an earlier peak SWE was also assumed to be occurring due of the shorter snow duration. Decreasing trends in snow duration, rain-on-snow, and snowmelt runoff also resulted from snow modeling simulations of the YRB and the nearby area. We also observed a shift in the timing of snowmelt-driven peak streamflow, as well as a statistically significant increase in winter maximum streamflow and decrease in summer maximum and minimum streamflow trends by 2099. From the streamflow trends and complementary GEV analysis, we show that the YRB basin is a system in transition with earlier peak flows, lower snow-driven maximum streamflow, and higher rainfall-driven summer streamflow. This study highlights the importance of looking at changes in snow across multiple indicators to develop future infrastructure and planning tools to better adapt and mitigate changes in extreme events.

54 ENVIRONMENTAL SCIENCES↗

miniDOT Logger Dissolved Oxygen and Temperature Data of Wetland Surface Water, Old Woman Creek NERR, Huron, OH, 2022-06-15 to 2023-12-15

This dataset contains timeseries data of dissolved oxygen (DO) and temperature measurements of the surface water in a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the overlying water column of wetland to assess how oxygen changed over time with hydrological events. Measurements were collected by a miniDOT Logger. Data was collected over 1.5 years (June 2022 to December 2023). The miniDOT_DO_Temp_DataFile.csv contains the DO and temperature measurements that were collected every 10 minutes. The water levels of the site varied over-time as the wetland flooded and dried. So, sometimes the miniDOT logger would be out of the water column, resulting in high oxygen levels. Depth of the water column was recorded at every in-person site visit. The miniDOT_Depth_DataFile.csv contains the hand-measured surface water depth measurements for comparison to the logger-collected data. Information on the deployment and measurement methods can be found in the miniDOT_InstallationMethods.csv file.

54 ENVIRONMENTAL SCIENCES↗

Climatic Drivers for the Variation of Gross Primary Productivity Across Terrestrial Ecosystems in the United States

Abstract Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future.

Environmental Sciences & Ecology↗

Mapping the Temperature-dependent and network site-specific onset of spectral diffusion at the surface of a water cluster cage

We explore the kinetic processes that sustain equilibrium in a microscopic, finite system. This is accomplished by monitoring the spontaneous, time-dependent frequency evolution (the frequency autocorrelation) of a single OH oscillator, embedded in a water cluster held in a temperature-controlled ion trap. The measurements are carried out by applying two-color, IR-IR photodissociation mass spectrometry to the D3O+?(HDO)(D2O)19 isotopologue of the “magic number” protonated water cluster, H+?(H2O)21. The OH group can occupy any one of the five spectroscopically distinct sites in the distorted pentagonal dodecahedron cage structure. The OH frequency is observed to evolve over tens of milliseconds in the temperature range (90-120 K). Starting at 100 K, large “jumps” are observed between two OH frequencies separated by ~300 cm-1 indicating migration of the OH group from the bound OH site at 3350 cm-1 to the free position at 3686 cm-1. Increasing the temperature to 110 K leads to partial interconversion among many sites. All sites are observed to interconvert at 120 K such that the distribution of the unique OH group among them adopts the form one would expect for a canonical ensemble. The spectral dynamics displayed by the clusters thus offer an unprecedented view into the molecular-level processes that drive spectral diffusion in an extended network of water molecules.

Yang, Nan↗

Water Freezes at Near-Zero Temperatures Using Carbon Nanotube-Based Electrodes under Static Electric Fields

Although static electric fields have been effective in controlling ice nucleation, the highest freezing temperature ( T f ) of water that can be achieved in an electric field ( E ) is still uncertain. In this study, we performed a systematic study of the effect of an electric field on water freezing by varying the thickness of a dielectric layer and the voltage across it in an electrowetting system. Results show that T f first increases sharply with E and then reaches saturation at –3.5 °C after a critical value E of 6 × 10 6 V/m. Using classical heterogeneous nucleation theory, it is revealed that this behavior is due to saturation in the contact angle of the ice embryo with the underlying substrate. Finally, we show that it is possible to overcome this freezing saturation by controlling the uniformity of the electric field using carbon nanotubes. We achieve a T f of –0.6 °C using carbon nanotube-based electrodes with an E of 3 × 10 7 V/m. This work sheds new light on the control of ice nucleation and has the potential to impact many applications ranging from food freezing to ice production.

25 ENERGY STORAGE↗

Utah FORGE Phase 3 Native State Model: 2022 Update

This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. This data archive consists of 10 files, 4 of which are simulation input files and the remaining 6 are simulation output files. There is an included readme.txt file that contains details on each of the data files. The input files include meshes, FALCON code inputs, tabulated data of water properties, temperature values, and model boundaries. The output files include simulation outfiles and point data of modeled material properties.

15 GEOTHERMAL ENERGY↗

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗

Understanding Lead Times of Warm Water Volumes to ENSO Sea Surface Temperature Anomalies

The equatorial Pacific warm water volume (WWV) and western equatorial Pacific WWV (WWV w ) are two important long-lead time El Niño-Southern Oscillation (ENSO) event precursors. Here, for this work, we utilize the recharge-discharge oscillator framework to obtain the analytical solution of WWV and WWV w lead times to ENSO sea surface temperatures (SSTs). Both WWV and WWVw lead times show a strong dependence on the inherent ENSO periodicity, whereas WWV lead time is further modulated by the air-sea coupling strength and ENSO SST spatial pattern. The derived solution is able to explain observed decadal variations in lead times of WWV to SST in terms of variations in ENSO periodicity and air-sea coupling strength.

54 ENVIRONMENTAL SCIENCES↗

Droplet Growth or Evaporation Does Not Buffer the Variability in Supersaturation in Clean Clouds

Abstract Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth. Significance Statement The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.

54 ENVIRONMENTAL SCIENCES↗

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Abstract Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH 4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH 4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH 4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH 4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH 4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

Environmental Sciences & Ecology↗

Ab initio thermodynamics reveals the nanocomposite structure of ferrihydrite

Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Porous Transport Layer In-Plane Conduction on Spatially Resolved Current and EIS Measurements in a Proton Exchange Membrane Water Electrolyzer

An XY segmented cell was developed for low temperature PEM water electrolysis (PEMWE). The system can assess the local performance by enabling in situ measurements of spatial currents and impedances. In this work, we show through experiments, as well as through modelling work, that the porous transport layer (PTL) must be segmented to eliminate crosstalk. Accurate measurements are only possible when crosstalk is fully eliminated. The XY segmented cell is applied to a case study characterizing the impact of a PTL platinum coating void on spatial performance. The localized performance impact of the coating void is found to be orientation specific: coating voids facing the catalyst layer reduce performance significantly more than coating voids facing the flow field. The results suggest that the tolerances for PTL coating uniformity can be lower at the side facing the flow field. The work showcases the feasibility of the XY segmented cell for impact assessment studies. The presented XY segmented cell enables the characterization of spatial phenomena in PEMWE devices and is envisioned to support modeling efforts and the investigation of manufacturing related tolerances for mass produced PEMWE devices.

08 HYDROGEN↗

Vanderbilt Alumni Hall

This dataset includes processed and raw data from the Vanderbilt Alumni Hall Building (VAH) located on the University of Vanderbilt Campus in Nashville, TN. VAH is a mixed use commercial building (LEED Gold Certified) that consists of classrooms, meeting rooms, office rooms, conference rooms, an exercise room, and others. This dataset spans one year of time-series data from 2019 and includes measurements corresponding to whole building electrical power, thermal power, zone level thermal power, set-point, indoor temperature, humidity, water and air side supply and return temperatures and flow rates as CSV files. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Code Benchmark of Depressurized Conduction Cooldown Transient in the High Temperature Test Facility

This paper presents results from modeling of a depressurized conduction cooldown (DCC) transient at the High Temperature Test Facility (HTTF) as part of the OECD-NEA Thermal Hydraulics Code Validation Benchmark for High-Temperature Gas-Cooled Reactors using HTTF Data . This paper briefly describes the benchmark and the models being used. It then presents a comparison of steady state and transient results based on the Problem 2 Exercise 1A and 1B definitions. We compare block and helium temperature distributions, mass flow distribution, and energy balance in steady state. All models show comparable mass flow distributions and energy balances. The temperatures within the core and outer regions are comparable in all models too, but inner reflector temperatures can vary significantly. Despite that, we find that the models are in good agreement for the full-power steady state. In the DCC, we look at block temperature at the core midplane and RCCS water exit temperature. The INL and ANL models are found to be in excellent agreement with one another on block temperature over time, while the agreement when the KAERI and NRG models are added into consideration is good. Differences in the transient heat removal from the RCCS cause the differences in block temperature over time in these models. The CNL models show similar trends to the INL, ANL, KAERI, and NRG models, but the temperatures are high because the volumes used in calculating the average temperature include the heater rods in the CNL models only. The HUN-REN model shows results that suggest significantly lower heat removal in the RCCS which merit further investigation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗