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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rice husk and charred husk amendments increase porewater and plant Si but water management determines grain As and Cd concentration

Abstract Purpose Rice is a staple crop worldwide and a silicon (Si) hyperaccumulator with Si levels reaching 5–10% of its mass; this can result in desilication and Si-deficiency if plant residues are not managed correctly. Rice is also uniquely subject to arsenic (As) and cadmium (Cd) contamination depending on soil conditions. Our goal is to quantify the effects of rice husk (a Si-rich milling byproduct) amendments and different water management strategies on rice uptake of Si, As, and Cd. Methods We employed 4 husk amendment treatments: Control (no husk), Husk (untreated husk), Biochar (husk pyrolyzed at 450 °C), and CharSil (husk combusted at > 1000 °C). Each of these amendments was studied under nonflooded, alternate wetting and drying (AWD), and flooded water management in a pot study. Porewater chemistry and mature plant elemental composition were measured. Results Husk and Biochar treatments, along with flooding, increased porewater and plant Si. Vegetative tissue As decreased with increasing porewater Si, but grain As and plant Cd were primarily controlled by water management. Grain As and Cd were inversely correlated and are simultaneously minimized in a redox potential (Eh) range of 225–275 mV in the studied soil. Ferrihydrite in root iron plaque decreased As translocation from porewater to grain, but amendments were not able to increase plaque ferrihydrite content. Conclusion We conclude moderate husk amendment rates (i.e., 4 years’ worth) with minimal pretreatment strongly increases rice Si content but may not be sufficient to decrease grain As in low Si and As soil.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Divanadium substituted keggin [PV 2 W 10 O 40 ] on non-reducible supports-Al 2 O 3 and SiO 2 : synthesis, characterization, and catalytic properties for oxidative dehydrogenation of propane

Molecular metal oxide cluster, K 5 [α-1,2-PV 2 W 10 O 40 ] (PV 2 W 10 ), was found to have intrinsic catalytic activity for the oxidative dehydrogenation of propane with high selectivity (> 80%) to propylene at low propane conversion (0.3%). Synthesis of dispersed PV 2 W 10 in non-reducible supports, γ-Al 2 O 3 and SiO 2 , was done by incipient wetness impregnation. The supported catalysts were characterized by IR, Raman spectroscopy, nitrogen adsorption, x-ray powder diffraction (PXRD), elemental analysis, hydrogen temperature-programmed reduction (H 2 –TPR), and ammonia temperature-programmed desorption (NH 3 –TPD). Catalytic testing of the supported PV 2 W 10 at equimolar cluster concentration revealed that when supported in γ-Al 2 O 3 it is more active (sevenfold increase in propane conversion) but in SiO 2 it is more selective to propylene (94%). The observed performance was due to both an increase in reducibility and higher concentration of strong acid sites for PV 2 W 10 supported in γ-Al 2 O 3 versus SiO 2 . Lastly, PV 2 W10 was shown to remain intact under reaction conditions indicating its thermal and oxidative stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Addition of Boron to Melt-Spun Fe-6.5%Si Ribbons

Fe-6.5%Si has higher electrical resistivity, lower magnetocrystalline anisotropy, and lower magnetostriction than traditional Fe-3.2%Si silicon steel. The reduced iron losses of Fe-6.5%Si render it a highly favorable candidate for high-speed motors and transformers. However, large-scale production of wide Fe-6.5%Si tape by rapid solidification can be challenging mainly because of its high melting point. In this work, boron is alloyed to Fe-6.5%Si to reduce its melting temperature and interfacial energy to improve the alloy’s processability. Boron additions from 0.01 wt.% to 2.24 wt.% into Fe-6.5%Si and its effect on ribbon thickness, grain size, magnetic, and mechanical properties were studied. Further, minor boron alloying significantly changed the melt pool stability and wetting on the quench wheel and in turn increased the quench rate with minimum impact on the magnetic saturation and ductility. Boron addition of < 0.06 wt.% was also found beneficial to the magnetic property of the alloy by lowering both its hysteresis and eddy current losses.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Avoiding surface instability and slurry jamming in simultaneous multilayer coating of structured particulate films

Simultaneous multilayer coating techniques are widely known, but their industrial application remains limited to narrow market sectors. One barrier to adoption may be the mismatch between industries that are familiar with such processes but have no need, and industries that have need but are not familiar. Moreover, there are application-specific technical challenges to developing multilayer-coating processes. In this article, we describe our resolution of two specific issues in simultaneous multilayer coating of all aqueous highly loaded slurries for new and emerging energy applications. The first issue is particle jamming (associated with Shear-thickening) of the highly loaded slurries in the die internals, which we alleviated by adding small amounts of viscosity modifiers without reducing the solid loading. The second issue is a Marangoni-driven surface instability that resembles top layer de-wetting, which we solved by carefully selecting surfactants to tune the dynamic surface tensions of each slurry. Both issues were resolved early in a step-wise development, saving significant development cost which in our case was driven by expensive materials.

08 HYDROGEN↗
DOE OSTI2025

Evaluating indoor thermal resilience of passive and low-power cooling shelters for outdoor workers in India

India’s 231 million outdoor workers are exposed to deadly heat during heat waves. We report results from a simulation-based study that focuses on passive design of cooling shelters for the hot and dry climate zone of India. The goal is to design a cooler-than-outdoor shelter for outdoor workers’ intermittent rest and recovery from heat stress during their arduous outdoor work, to avoid heat-related morbidities and mortality. Expected indoor thermal conditions in low-cost cooling shelters deploying a range of passive designs and low-power active measures are investigated, consistent with the current Indian standards and practices, located in the city of Jodhpur in western India. Heat resilience of the shelter was measured with the predicted reduction of hazardous hours inside the shelter based on the wet-bulb globe temperature (WBGT) and extended heat index. These measures include improving the building envelope, installing cool roofs, using internal thermal mass, and natural ventilation. Additionally, a low-power active measure of using ventilation fans and ceiling fans is explored. EnergyPlus-based simulation results show that simple, commonly available measures, particularly natural ventilation and ceiling fans, achieve the most significant reductions in overheating danger hours, by 22% and 21%, respectively, while more complex or costly passive strategies yield only marginal additional benefits. Moreover, combined measure packages are identified that can reduce the indoor WBGT by 8 to 10 °C, eliminating overheating danger hours. These findings highlight the critical importance of scalable, low-cost, and easily deployable cooling solutions for developing resilient cooling shelters for vulnerable outdoor workers during heat waves in India.

building performance↗
DOE OSTI2021

Ultrasound-driven fabrication of high-entropy alloy nanocatalysts promoted by alcoholic ionic liquids

High-entropy alloy nanoparticles (HEA-NPs) are highly underutilized in heterogeneous catalysis due to the absence of a reliable, sustainable, and facile synthetic method. Herein, we report a facile synthesis of HEA nanocatalysts realized via an ultrasound-driven wet chemistry method promoted by alcoholic ionic liquids (AILs). Owing to the intrinsic reducing ability of the hydroxyl group, AILs were synthesized and utilized as environmentally friendly alternatives to conventional reducing agents and volatile organic solvents in the synthetic process. Under high-intensity ultrasound irradiation, Au 3+ , Pd 2+ , Pt 2+ , Rh 3+ , and Ru 3+ ions were co-reduced and transformed into single-phase HEA (AuPdPtRhRu) nanocrystals without calcination. Characterization results reveal that the as-synthesized nanocrystals are composed of elements of Au, Pd, Pt, Rh, and Ru as expected. Compared to the monometallic counterparts such as Pd-NPs, the carbon-supported HEA nanocatalysts show superior catalytic performance for selective hydrogenation of phenol to cyclohexanone in terms of yield and selectivity. Our synthetic strategy provides an improved and facile methodology for the sustainable synthesis of multicomponent alloys for catalysis and other applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis of amorphous Pd-based nanocatalysts for efficient alcoholysis of styrene oxide and electrochemical hydrogen evolution

Amorphous nanomaterials with long-range disordered structures could possess distinct properties and promising applications, especially in catalysis, as compared with their conventional crystalline counterparts. It is imperative to achieve the controlled preparation of amorphous noble metal-based nanomaterials for the exploration of their phase-dependent applications. Here, in this work, we report a facile wet-chemical reduction strategy to synthesize various amorphous multimetallic Pd-based nanomaterials, including PdRu, PdRh, and PdRuRh. The phase-dependent catalytic performances of distinct Pd-based nanomaterials towards diverse catalytic applications have been demonstrated. Specifically, the usage of PdRu nanocatalysts with amorphous and crystalline face-centered cubic (fcc) phases can efficiently switch the ring-opening route of styrene oxide to obtain different products with high selectivity through alcoholysis reaction and hydrogenation reaction, respectively. Moreover, when used as an electrocatalyst for hydrogen evolution reaction (HER), the synthesized amorphous PdRh nanocatalyst exhibits low overpotential and high turnover frequency values, outperforming its crystalline fcc counterpart and most of the reported Pd-based HER electrocatalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparative Study of Flash and Acid Hydrolysis of Microalgae (Scenedesmus sp.) for the Recovery of Biochemicals and Production of Porous Biocarbon Nanosheets

An integrated biorefinery concept is a novel and economical process intensification methodology for efficient utilization of biomass components. In this research, microalgae (Scenedesmus sp.) slurry with biomass concentration of 8.5 wt.% was parallelly fractionated using two techniques: 'flash hydrolysis (FH)' and 'acid hydrolysis (AH)'. FH was performed at 240 degrees C with a residence time of 10 +/- 2 s in a continuous flow reactor, whereas AH was performed at 155 degrees C and reaction time of 15 min in a batch reactor. About 63% of microalgal biomass was solubilized in liquid hydrolysate through both FH and AH. However, AH had an advantage over FH in recovering microalgae proteins and carbohydrates. FAME recovery through solvent extraction from FH and AH derived wet solids (insoluble microalgae) was 40 and 63%, respectively. Finally, the FH- and AH-derived post extraction solid residue was thermally activated using K2CO3 to produce highly microporous biocarbon nanosheets with BET surface areas of 712 and 1289 m2 g-1, respectively. Overall, an integrated process was developed using two potential hydrolysis techniques to maximize utilization of microalgae components.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2021

Atmospheric humidity deficits tell us how soil moisture deficits down-regulate ecosystem evaporation

Knowing how actual evaporation is down-regulated from potential evaporation during periods with soil moisture deficits is one of the greatest challenges towards computing evaporation everywhere on a regular basis. We propose the hypothesis that vegetated landscapes transmit information on soil moisture deficits through its down-regulation of evaporation, which in turn affects the humidification and growth of the planetary boundary layer. To test this hypothesis, here, we examined how the evaporative fraction, defined as the ratio between actual and potential evaporation, corresponds with the soil moisture stress index, defined as the relative humidity with a power law dependence on vapor pressure deficit times a parameter, β. We tested the parameterized soil moisture stress index with direct eddy covariance measurements of actual evaporation and computations of potential evaporation based on meteorological conditions, averaged on monthly time steps. The analysis was conducted on a dataset obtained from 144 FLUXNET sites. These sites spanned much of the world's climates and biomes and contained over 5900 months of observations. Observations of the evaporative fraction fit the model of the soil moisture stress index best for semi-arid and arid ecosystems, and least for the humid and wet ecosystems. Consequently, a significant relationship between measurements of the evaporative fraction and soil moisture stress index held for about one-half of the population of sites. Under this condition, the median value of the parameter, β, was 1.41. To investigate the mechanism of this empirical soil moisture stress index, we diagnosed it with a coupled evaporation-planetary boundary layer model. The soil moisture stress index is strongly related to surface resistance, as defined by inverting Penman-Monteith equation. Consequently, this index provides an independent estimate of surface resistance based on easy to measure mean monthly weather conditions like relative humidity and temperature. Thereby, this soil moisture stress index has potential to be applied to weather, climate and biogeochemical models and the interpretation of satellite derived evaporation products, like the one provided by the ECOSTRESS mission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soybean fallow and nitrification inhibitors: Strategies to reduce N 2 O emission intensities and N losses in Australian sugarcane cropping systems

The Australian sugar industry is facing mounting pressure to reduce the nitrogen (N) losses and nitrous oxide (N 2 O) emissions associated with N fertiliser use. Research has shown that N 2 O emissions from sugarcane (Saccharum officinarum L.) cropping systems can be reduced with the use of fertilisers coated with nitrification inhibitors, or by sowing legume crops in the fallows between sugarcane crop cycles. However, the efficacy of these two N management strategies across different climatic zones is still unclear, as results from field studies have been contradictory. The objectives of this study were therefore to use the DayCent model to assess the long-term effects of the two strategies (separately or in combination) on N 2 O emissions, N losses and yields. The model was parameterised using data from eight field experiments (39 treatments) conducted across four of the five main districts of the Australian sugarcane industry. A series of long-term scenarios embracing a range of N fertiliser rates (0- 160 kg N ha -1 applied as urea), climatic regions (Tropics and Subtropics), soil textures (fine- and coarse-textured soils) and N-loss risk scenarios (crop fertilised well before or close to the on-set of the wet season) were tested for both N management strategies. Simulations identified that the combined use of soybean (Glycine max L.) fallows and N fertiliser coated with the 3,4-dimethylpyrazole phosphate (DMPP) nitrification inhibitor was the most effective strategy to maintain or even increase current yields while significantly reducing N 2 O and cumulative N (mainly due to nitrate) losses. When used alone, the soybean fallow strategy on average reduced N losses over the entire crop cycle by 29 % compared with current industry best practice. However, this strategy showed a limited capacity to reduce N 2 O emissions over the entire cane crop cycle (median: -3% compared with current industry best practice), or even increased them in scenarios at high-risk of N losses in the Tropics. The use of urea coated with DMPP alone allowed current fertiliser N rates to be reduced by 30 % without any substantial yield penalty. In environments prone to high N losses, DMPP urea abated overall N losses and N 2 O emissions by 41 % and 30 %, respectively. This was the first study to use such an extensive dataset to parameterise a biogeochemical model for yields, N 2 O emissions and N losses in sugarcane cropping systems. Finally, the findings will be instrumental in guiding future research and policies designed to improve the profitability and environmental sustainability of this industry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Tree growth, transpiration, and water-use efficiency between shoreline and upland red maple (Acer rubrum) trees in a coastal forest

Coastal shoreline forests are vulnerable to seawater exposure, the impacts of which will increase due to sea-level rise, but the longterm adaption strategies and vulnerability of coastal forests are not well understood. We used whole-tree transpiration, leaf water potential, tree-ring width, and tree-ring d13C (a proxy for intrinsic water use efficiency, iWUE) to examine the long-term adaption strategies of red maple (Acer rubrum) trees at the coastal interface (i.e., shoreline) and nearby upland in Maryland, USA. Red maple trees that grew along the shoreline and were exposed to slightly saline water (up to two PSU) had higher transpiration rates than those growing in the nearby upland forest during a wet year, but these differences disappeared during a normal precipitation year. Shoreline trees grew more slowly than upland trees over the last four decades, but these growth differences have disappeared in the last six years. Shoreline and upland trees had similar variation in iWUE, indicating that higher transpiration rates of the seawater exposed trees did not translate into differences in water use efficiency. There were no differences in predawn and midday water potential between upland and shoreline trees, suggesting no water stress occurs in shoreline trees. These findings indicate that urrent soil salinity is below the threshold to constrain coastal red maple physiological activities.

Wang, Wenzhi↗
DOE OSTI2022

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Turbulence regimes in the nocturnal roughness sublayer: Interaction with deep convection and tree mortality in the Amazon

We investigated the influence of seasonality and proximity to the forest canopy on nocturnal turbulence regimes in the roughness sublayer of a Central Amazon forest. Since convective systems of different scales are common in this region, we also analyzed the effect of extreme wind gusts (propagated from convective downdrafts) on the organization of the turbulence regimes, and their potential to cause the mortality of canopy trees. Our data include high-frequency winds, temperature and ozone concentration at different heights during the dry and wet seasons of 2014. In addition, we used critical wind-speed data derived from a tree-winching experiment and a modeling study conducted in the same study site. Two different turbulence regimes were identified at three heights above the canopy: a weakly stable (WS) and a very stable regime (VS). The threshold wind speeds that mark the transition between turbulence regimes were larger during the dry season and increased as a function of the height above the canopy. The turbulent fluxes of sensible heat and momentum during the WS accounted for 88% of the entire nighttime flux. Downdrafts occurred only in the WS and favored a fully coupled state of wind flow along the canopy profile. The destructive potential of winds was four times higher than on nights without downdrafts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Interannual variability of spring and summer monsoon growing season carbon exchange at a semiarid savanna over nearly two decades

Eddy covariance measurements of land-atmosphere energy, carbon, and water exchange now span multiple decades at some sites, supporting an improved understanding of flux interannual variability (IAV) and its ecophysiological and physical controls. Most eddy covariance IAV studies have focused on temperate forest ecosystems, where carbon fluxes are large and flux records are longest – but also where IAV is much lower than in dryland regions, which have been identified as an essential driver of the trend and variability in the global terrestrial carbon sink. In this study, we leveraged 19 years of continuous micrometeorological measurements at the AmeriFlux US-SRM mesquite savanna site in southern Arizona, USA to quantify the IAV, trends, and drivers of carbon fluxes during the distinct spring and summer growing seasons. We also assessed the ability of modern satellite and land surface models to capture the IAV of seasonal water and carbon fluxes. Annual net ecosystem production (NEP) was small and highly variable (23 +/- 64 gC m –2 yr –1 ). Precipitation and associated measures of water availability determined most of the variability in NEP, largely through their influence on annual and seasonal gross ecosystem productivity (GEP) as opposed to ecosystem respiration (ER). Root-zone soil moisture captured between 73% (spring) and 85% (summer) of GEP variability and between 73% (spring) and 58% (summer) of ER variability. Throughout the study period, soil moisture and greenness increased with associated increases in GEP, ER and NEP. These trends were strongly influenced by very productive and wet summer growing seasons during the last two years, which were characterized by abundant understory grass cover. Typically, less than half of the variability in growing season GEP and evapotranspiration was captured by satellite-based estimates and land surface model simulations with local site forcing and calibration, highlighting the ongoing utility of long-term datasets to support careful model testing and improvement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of storage and blending of algae and forest product residue on fuel blendstock production

Seasonal impacts on the production of algae biomass require blending with other feedstocks such as wood to maintain consistent annual conversion capacity. Idaho National Laboratory (INL) has developed a long-term storage strategy for algae biomass using ensiling, or anaerobic wet storage, that was tested for blends of algae and wood to stabilize the feedstock supply for processing to fuels. Additionally, blending biomass (algae and wood) leverages existing biomass storage approaches commonly used by the feed and forage industry. Earlier research also has demonstrated positive results that indicate ensiling is more effective and economical in normalizing biomass feedstock supply prior to conversions such as HTL (hydrothermal liquefaction) than preserving biomass by drying. By assessing impacts beginning with upstream logistic operations and proceeding through each conversion step, this work focuses on conversion of ensiled and blended biomass to fungible liquid transportation fuel blendstocks. This is accomplished by conversion of the blended biomass (62% Chlorella sp. blended with 38% loblolly pine forest product residues [FPR]) to bio-crude through HTL and subsequent upgrading through HT (hydrotreating) with a commercial refinery catalyst analogous to a refinery process to produce hydrocarbon fuel. In this work, results indicate that carbon retention and quality are preserved in both the bio-crude and upgraded fuel from the ensiled blend, indicating the potential of this approach for managing seasonal variations in algae biomass productivity.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Finally, three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Reproducible benchmark for the SNAP 8 experimental reactor at operating conditions

This work presents fully reproducible multiphysics benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor at operating conditions with coolant flow. Wet experiment (with coolant, at power) validation benchmarks are presented using both deterministic (Serpent-Griffin) and Monte-Carlo (OpenMC-Cardinal) multiphysics frameworks coupled with thermal-hydraulic solvers in MOOSE. Reactivity coefficient measurements including fuel temperature, isothermal temperature, and power coefficients show good agreement with experiments, with discrepancies within experimental uncertainty. Reactivity worth experiments for coolant, samarium, and xenon poisoning are reproduced with differences under 200 pcm. Comparison between Serpent-Griffin and OpenMC-Cardinal frameworks reveal multiphysics coupling introduces positive reactivity effects (100-200 pcm) compared to uniform temperature and density fields at nominal operating conditions. Comparison between Serpent-Griffin and reference Serpent solution shows that power distributions maintain consistent radial and axial peaking behavior. All models, assumptions, thermophysical and thermomechanical properties, and material definitions are thoroughly documented with cited references; model inputs and model generating scripts are stored in the snapReactors GitHub repository.

SNAP↗