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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analysis of an Elasto-Hydrodynamic Seal by Using the Reynolds Equation

This paper reports numerical studies of an Elasto-Hydrodynamic (EHD) seal, which is being developed for supercritical CO2 (sCO2) turbomachinery applications. Current sCO2 turbomachinery suffers from high leakage rates, which is creating a major roadblock to the full realization of sCO2 power technology. The high leakage rates not only penalize the efficiencies but also create environmental concerns due to greenhouse effects caused by the increased CO2 discharge to the atmosphere. The proposed EHD seal needs to work at elevated pressures (10–35 MPa) and temperatures (350–700 °C) with low leakage and minimal wear. The unique mechanism of the EHD seal provides a self-regulated constriction effect to restrict the flow without substantial material contact, thereby minimizing leakage and wear. This work utilizes a physics-based modeling approach. The flow through the gradually narrowing seal clearance is modeled by the well-known Reynolds equation in EHD lubrication theory, while the deformation of the seal is modeled by using the governing equations of three-dimensional solid mechanics. As for the solution methodology, COMSOL’s Thin-Film Flow and Solid Mechanics modules were employed with their powerful capabilities. The numerical results were presented and discussed. It was observed that the Reynolds equation fully coupled with the surface deformation was able to successfully capture the constriction effect. The maximum and minimum leakages were calculated to be 2.25 g/s and 0.1 g/s at P = 5.5 MPa and P = 11 MPa for the design seal, respectively. It was interesting to observe that the seal leakage followed a quadratic trend with increasing pressure differential, which can become advantageous for high-pressure applications such as sCO2 power generation technology.

42 ENGINEERING↗
DOE OSTI2021

Identifying schools at high-risk for elevated lead in drinking water using only publicly available data

Estimating the risk of lead contamination of schools' drinking water at the State level is a complex, important, and unexplored challenge. Variable water quality among water systems and changes in water chemistry during distribution affect lead dissolution rates from pipes and fittings. In addition, the locations of lead-bearing plumbing materials are uncertain. We tested the capability of six machine learning models to predict the likelihood of lead contamination of drinking water at the schools' taps using only publicly available datasets. The predictive features used in the models correspond to those with a proven correlation to the dominant, but commonly unavailable, factors that govern lead leaching: the presence of lead-bearing plumbing materials and water quality conducive to lead corrosion. By combining water chemistry data from public reports, socioeconomic information from the US census, and spatial features using Geographic Information Systems, we trained and tested models to estimate the likelihood of lead contaminated tap water in over 8,000 schools across California and Massachusetts. Our best-performing model was a Random Forest, with a 10-fold cross validation score of 0.88 for Massachusetts and 0.78 for California using the average Area Under the Receiver Operating Characteristic Curve (ROC AUC) metric. The model was then used to assign a lead leaching risk category to half of the schools across California (the other half was used for training). There was good agreement between the modeled risk categories and the actual lead leaching outcomes for every school; however, the model overestimated the lead leaching risk in up to 17% of the schools. This model is the first of its kind to offer a tool to predict the risk of lead leaching in schools at the State level. Further use of this model can help deploy limited resources more effectively to prevent childhood lead exposure from school drinking water.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Hydride-based thermal energy storage

Abstract The potential and research surrounding metal hydride (MH) based thermal energy storage is discussed, focusing on next generation thermo-chemical energy storage (TCES) for concentrated solar power. The site availability model to represent the reaction mechanisms of both the forward and backward MH reaction is presented, where this model is extrapolated to a small pilot scale reactor, detailing how a TCES could function/operate in a real-world setting using a conventional shell & tube reactor approach. Further, the important parameter of effective thermal conductivity is explored using an innovative multi-scale model, to providing extensive and relevant experimental data useful for reactor and system design. Promising high temperature MH material configurations may be tuned by either destabilisation, such as using additions to Ca and Sr based hydrides, or by stabilisation, such as fluorine addition to NaH, MgH 2 , or NaMgH 3 . This versatile thermodynamic tuning is discussed, including the challenges in accurately measuring the material characteristics at elevated temperatures (500 –700 °C). Attention to scale up is explored, including generic design and prototype considerations, and an example of a novel pilot-scale pillow-plate reactor currently in development; where materials used are discussed, overall tank design scope and system integration.

25 ENERGY STORAGE↗
DOE OSTI2022

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗
DOE OSTI2021

Data from: "Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest"

This data package contains data used to support conclusions drawn in “Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest”, by Kueppers et al. 2017. Data were collected in field sites within the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, on the eastern slope of the Colorado Rocky Mountains, USA. Files containing geospatial data are also included, to provide additional locational context.There are four document formats associated with this archive: three comma-separated values (.csv) files, three Microsoft Excel (.xlsx) files, one .pdf data user’s guide, four keyhole markup language (.kml) files, and a compressed folder containing seven ESRI shapefiles (.shp). The .csv files can be opened using any simple text-editor software, R, or Microsoft Excel. The .xlsx files can only be opened using Microsoft Excel. The .kml file can be opened by Google Earth and Google Maps, and the shapefiles can be opened with any GIS application compatible with the file type, such as ESRI’s ArcGIS, and QGIS.We provide two versions of the seedling data file: “PIEN_PIFLseedlings20150522_20150525rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2015) and “PIEN_PIFLseedlings20160408rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2016). PIEN_PIFLseedlings2015 contains the data we used in the paper. PIEN_PIFLseedlings2016 contains an updated version of these data that includes sampling from later years. The main differences between the two files lie in the columns titled “k[YEAR],” which describe the number of seedlings that were killed in a particular year. In PIEN_PIFLseedlings2016, there also is an additional year of data for k2015, and k2014 also has additional data input for the 2014 cohort. Additionally, in years 2010-2014, there are minor differences in the number of seedlings killed -- in as few as 0 plots (in 2011) to as many as 5 plots (in 2014) -- due to errors in data input that were rectified in later years.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Upslope range shifts by subalpine tree species are a widely anticipated effect of climate change. Climate niche models predict subalpine forests to expand upslope, given more suitable growing conditions for adult trees. However, these models do not take into account climates required for successful seedling recruitment and establishment, an essential element for expansion. Further, localized upper treeline populations are hypothesized to contain favorable traits for colonizing the alpine. To test these expectations and to expand our knowledge of seedling recruitment under climate change, we designed a common garden, climate-warming experiment spread across an elevation gradient at Niwot Ridge in the Colorado Rocky Mountains. We focus on two widespread Western North American species, Engelmann spruce (Picea engelmannii Parry ex. Engelm) and limber pine (Pinus flexilis James), which occur at treeline. While the former is considered a late-seral species more tolerant of shade, limber pine is a shade-intolerant pioneer species able to establish on infertile sites.Every autumn, seeds of the two species were collected from high- (3370 m–3570 m) and low-provenance (2910–3240 m) sources close to the experimental sites and sown in our plots. A subset of plots were heated and another subset watered over the summer months to offset the effects of warming. Across five years, we found that seeds originating from low elevation recruited more strongly for both species, although this provenance difference diminished by the fourth year for Engelmann spruce, likely due to small sample sizes. Despite the recruitment of low-provenance seed, warming treatments decreased recruitment at all elevations. Combining this with the likeliness and availability of lower-quality, high provenance seed moving upslope at the treeline, tree migration into the alpine may be slowed. Overall, our findings suggest that the hardier limber pine is likely to become a more significant species in subalpine forest communities in the future, while the more sensitive Engelmann spruce may experience range contraction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Kilometer-Scale Hydrologic Exchange Flows in a Gravel Bed River Corridor and Their Implications to Solute Migration

In this work, a well-characterized field site along a major river corridor was used to investigate the dynamic pathways and impacts of subsurface hydrogeologic structures on kilometer-scale hydrologic exchange flows between river water and groundwater. A aqueous uranium (U aq ) plume exists at the site that discharges to the Columbia River. We performed temporally intensive monitoring of specific conductance (SpC) and U aq concentrations within the plume at increasing distances from the river shoreline and at locations both within and outside a presumed subsurface pathway of lateral hydrologic exchange. Specific conductance and U aq were utilized as in-situ tracers of hydrologic exchange and associated groundwater-surface water mixing. Monitoring data was collected for an approximate two year period during which seasonal river elevations varied by more than 2 m causing distinct events of river water intrusion and retreat from the near-shore aquifer, and large temporal variations in well-water analyte concentrations. Statistical clustering analysis was applied to identify well groupings exhibiting common time series behaviors. PFLOTRAN was implemented within a modeling domain of 3.3 x 1.9 km with dynamic flow boundary conditions and accurate subsurface topography for the basal aquitard underlying the aquifer. In-silico calculations of river water tracer behavior were performed to assess predominant flow directions and velocities influenced by river stage variations and variable aquitard topography, and their collective influences on SpC and U aq concentrations. We demonstrate complicated multidirectional flow behaviors at the kilometer scale resulting from hydrologic exchange and subsurface structure that influence plume dynamics and determine the overall system behavior.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Influence of crossover on capacity fade of symmetric redox flow cells

Volumetrically unbalanced compositionally symmetric cell cycling with potentiostatic (CV) or galvanostatic-with-potential-hold (CCCV) protocols is a rigorous technique for evaluating the calendar lifetime of reactants for redox flow batteries. Here, we evaluate the influence of reactant crossover through the membrane on symmetric cell cycling behavior. We tested symmetric cells of anthraquinone disulfonic acid (AQDS) with Nafion membranes of varied thickness and manufacture (NR211, NR212, N115, and N117, ranging 25–183 μm). Membranes were tested both as-received and pretreated with a common procedure of soaking in water at elevated temperature and then in dilute hydrogen peroxide. We found no significant difference in capacity fade rates of symmetric cells with any of the membranes as-received, indicating a negligible influence of crossover. However, we observed increased capacity fade with increased permeability through pretreated membranes. Supported by zero-dimensional modeling and operando UV-vis spectrophotometry, we propose a mechanism for net crossover in AQDS symmetric cells based on a higher time-averaged concentration of quinhydrone dimers in the non-capacity limiting side (NCLS) compared to the capacity limiting side (CLS), driving net crossover of AQDS reactants out of the CLS. Further, we illustrate other hypothetical scenarios of net crossover using the zero-dimensional model. Overall, many membrane–electrolyte systems used in symmetric cell studies have sufficiently low crossover flux as to avoid the influence of crossover on capacity fade, but under conditions of higher crossover flux, complex interactions of crossover and chemical reactions may result in diverse capacity fade trajectories, the mechanisms of which may be untangled with operando characterization and modeling.

25 ENERGY STORAGE↗
DOE OSTI2025

Diffusion coefficients predicting facet-dependent crystallization in amorphous silicon nitride

Amorphous silicon nitride is a common material in microelectronics devices, which acts as an insulating barrier. Extended annealing times at elevated temperature can initiate crystallization of α-Si 3 ⁢ N 4 , which does not possess the same barrier properties. Molecular dynamics can resolve the fundamental mechanism for α-Si 3 ⁢N 4 crystallization and the influence of local environments. Here, we compare two interatomic potentials and conclude that these models predict structural features (e.g., angular distributions and densities) which span the range of experimental measurements. We confirmed these models reproduce experimental estimates of activation energy and leveraged these models to identify crystallization drivers. We conclude that near-T g , facet-dependent silicon nitride crystal growth rates can be predicted directly by either bulk or interfacial diffusion properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A method for predicting failure statistics for steady state elevated temperature structural components

This paper presents the initial development of a high temperature life prediction method that accounts for the variability in the material properties of Grade 91 steel. The method accounts for material variability by fitting a variable 3-parameter Weibull distribution to experimental rupture data and accounts for the variability of creep deformation on the steady-state stresses via a Monte Carlo approach. To ensure reasonable computational times, the model represents the material as an extremely viscous Stokes fluid with a non-Newtonian viscosity, therefore solving the stress relaxation problem with a steady, static, instead of transient, analysis. Furthermore, the complete statistical analysis combines this model for creep deformation with a probabilistic model for creep rupture to evaluate the probability of premature failure for a set of sample problems, comparing the predicted failure statistics to the design life predicted by the ASME Boiler and Pressure Vessel Code rules.

42 ENGINEERING↗
DOE OSTI2021

Propagation of positive discharges in an air bubble having an embedded water droplet

Low temperature plasmas generated inside gas bubbles immersed in water is an effective method of rapidly transferring plasma generated reactive species to the water for applications in biomedicine, agriculture and environment. Reactive species are generally produced in the gas phase plasma and then solvate into the liquid. The large surface-to-volume ratio (SVR) of the bubble accelerates this process. In generating bubbles in water, aerosols and droplets are also contained within the bubble. These droplets also have a large SVR and so can be rapidly plasma activated. However, the presence of the droplets can also impact the propagation of the plasma in the bubble. In this paper, results are discussed from computational and experimental investigations of the formation and evolution of discharges in an air bubble immersed in water with an embedded water droplet. The computations were performed with a two-dimensional plasma hydrodynamics model. Experiments were performed with a quasi-2D bubble apparatus. In bubbles having a droplet, a plasma filament typically bridges from the powered electrode to the droplet, and then from the droplet to the bubble surface. A surface-hugging streamer also occurs on the inner bubble surface and on the surface of the droplet. Both surface streamers result in part from surface charge accumulation and can dominate the formation of reactive species that transport into the droplet. Increasing droplet conductivity suppresses propagation of the surface discharge and leads to a lower density of aqueous reactive species. Increasing conductivity of the surrounding water does not change the overall structure of the discharge but does slightly elevate the discharge intensity. Finally, the size and shape of the embedded droplet can significantly affect the formation and propagation of the streamer.

2D fluid modelling↗
DOE OSTI2022

Carbonate Minerals and Dissimilatory Iron-Reducing Organisms Trigger Synergistic Abiotic and Biotic Chain Reactions under Elevated CO 2 Concentration

Increasing CO 2 emission has resulted in pressing climate and environmental issues. While abiotic and biotic processes mediating the fate of CO 2 have been studied separately, their interactions and combined effects have been poorly understood. To explore this knowledge gap, an iron-reducing organism, Orenia metallireducens, was cultured under 18 conditions that systematically varied in headspace CO 2 concentrations, ferric oxide loading, and dolomite (CaMg(CO 3 ) 2 ) availability. The results showed that abiotic and biotic processes interactively mediate CO 2 acidification and sequestration through "chain reactions", with pH being the dominant variable. Specifically, dolomite alleviated CO 2 stress on microbial activity, possibly via pH control that transforms the inhibitory CO 2 to the more benign bicarbonate species. The microbial iron reduction further impacted pH via the competition between proton (H + ) consumption during iron reduction and H + generation from oxidization of the organic substrate. Under Fe(III)-rich conditions, microbial iron reduction increased pH, driving dissolved CO 2 to form bicarbonate. Spectroscopic and microscopic analyses showed enhanced formation of siderite (FeCO 3 ) under elevated CO 2 , supporting its incorporation into solids. In conclusion, the results of these CO 2 -microbe-mineral experiments provide insights into the synergistic abiotic and biotic processes that alleviate CO 2 acidification and favor its sequestration, which can be instructive for practical applications (e.g., acidification remediation, CO 2 sequestration, and modeling of carbon flux).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dissolving salt is not equivalent to applying a pressure on water

Abstract Salt water is ubiquitous, playing crucial roles in geological and physiological processes. Despite centuries of investigations, whether or not water’s structure is drastically changed by dissolved ions is still debated. Based on density functional theory, we employ machine learning based molecular dynamics to model sodium chloride, potassium chloride, and sodium bromide solutions at different concentrations. The resulting reciprocal-space structure factors agree quantitatively with neutron diffraction data. Here we provide clear evidence that the ions in salt water do not distort the structure of water in the same way as neat water responds to elevated pressure. Rather, the computed structural changes are restricted to the ionic first solvation shells intruding into the hydrogen bond network, beyond which the oxygen radial-distribution function does not undergo major change relative to neat water. Our findings suggest that the widely cited pressure-like effect on the solvent in Hofmeister series ionic solutions should be carefully revisited.

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

COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients

Background: The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. Methods: Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. Results: Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. Conclusion: Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Machine learning assisted prediction of the Young’s modulus of compositionally complex alloys

We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach are scalability, rapidity, and reasonably accurate predictions. ML tools were implemented to predict Young’s modulus of refractory-based CCAs by employing different ML models. Our results, in conjunction with experimental validation, suggest that average valence electron concentration, the difference in atomic radius, a geometrical parameter λ and melting temperature of the alloys are the key features that determine the Young’s modulus of CCAs and refractory-based CCAs. The Gradient Boosting model provided the best predictive capabilities (mean absolute error of 6.15 GPa) among the models studied. Our approach integrates high-quality validation data from experiments, literature data for training machine-learning models, and feature selection based on physical insights. It opens a new avenue to optimize the desired materials property for different engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stress Relaxation Cracking of Alloys at Temperatures Higher Than 540°C

Type 347H stainless steel (347H SS), used in commercial concentrating solar power (CSP) thermal energy storage to store solar-salt at a temperature of 565°C, has been reported in the literature to be susceptible to stress-relaxation cracking (SRC). The welded heat-affected zone (HAZ) and fusion zone (FZ) of 347H SS, particularly in thick sections, are known to be susceptible to failure during post-weld heat treatment (reheat cracking). SRC could also occur after months or years under an elevated-temperature service environment. Two conditions must be present for failure to occur in the HAZ and/or FZ: 1) a modified or sensitized microstructure and 2) sufficiently high tensile residual stresses present at the elevated service temperature. The overarching goal of this project is to recommend SRC mitigation protocols to avoid susceptibility to fail through SRC at temperatures relevant for CSP. Post weld heat treatment conditions and alternative alloys are investigated as potential mitigation solutions to SRC. We used Gleeble thermomechanical simulation tests and finite element (FE) models to understand the susceptibility of 347H SS to SRC as a function of temperature, stress, and microstructure. We started with a literature review of weldability issues with 347H SS and techniques to mitigate SRC in 347H SS weldments. Next, we used Gleeble experiments to determine reheat cracking susceptibility in the simulated HAZ of 347SS weldments and an alternative alloy, 316L SS (NUCL 167 SPH) with boron added. We also performed Gleeble experiments to compare the reheat cracking susceptibility of 347H cross welded with two different fillers: E347, which is used in some commercial CSP TES tanks, and E16.8.2. We validated the experimental results with FE models of the residual stresses. We found that although the 316L (NUCL 167 SPH) is less susceptible to reheat cracking, it is slightly weaker than 347H and ASME BP&V codes limit its use to a service condition of 565°C. We also found that welds using E16.8.2 as the weld filler are less susceptible to failure than those using E347, likely due to the higher creep ductility of E16.8.2, and that it may be used as an alternative filler for repair welding of 347H welds or as the primary choice of filler for newly developed weld joints. We also found that post weld heat treatment could be a viable solution for mitigating stress in E347-347H SS thick, constrained welds, like those found in CSP tanks, and propose several options for mitigating SRC in existing and future TES tanks.

14 SOLAR ENERGY↗
DOE OSTI2020

Impacts of land use change and elevated CO 2 on the interannual variations and seasonal cycles of gross primary productivity in China

Climate change, rising CO 2 concentration, and landuse and land cover change (LULCC) are primary driving forces for terrestrialgross primary productivity (GPP), but their impacts on the temporal changesin GPP are uncertain. In this study, the effects of the three main factorson the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPPin China were investigated using 12 terrestrial biosphere models from theMulti-scale Synthesis and Terrestrial Model Intercomparison Project. Thesimulated ensemble mean value of China's GPP between 1981 and 2010, drivenby common climate forcing, LULCC and CO 2 data, was found to be7.4±1.8 Pg C yr -1 . In general, climate was the dominant controlfactor of the annual trends, IAV and seasonality of China's GPP. Theoverall rising CO2 led to enhanced plant photosynthesis, thusincreasing annual mean and IAV of China's total GPP, especially innortheastern and southern China, where vegetation is dense. LULCC decreasedthe IAV of China's total GPP by ~7%, whereas rising CO 2 induced an increase of 8 %. Compared to climate change andelevated CO 2 , LULCC showed less contributions to GPP's temporalvariation, and its impact acted locally, mainly in southwestern China.Furthermore, this study also examined subregional contributions to thetemporal changes in China's total GPP. Southern and southeastern Chinashowed higher contributions to China's annual GPP, whereas southwestern andcentral parts of China explained larger fractions of the IAV in China's GPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Stimulation of isoprene emissions and electron transport rates are a key mechanism of thermal tolerance in the tropical species Vismia guianensis

Tropical forests absorb large amounts of atmospheric CO 2 through photosynthesis, but high surface temperatures suppress this absorption while promoting isoprene emissions. While mechanistic isoprene emission models predict a tight coupling to photosynthetic electron transport (ETR) as a function of temperature, direct field observations of these phenomenon are lacking in the tropics and are necessary to assess the impact of a warming climate on global isoprene emissions. In this paper, we demonstrate that in the early successional species Vismia guianensis in the central Amazon, ETR rates increased with temperature in concert with isoprene emissions, even as stomatal conductance ($g _s$) and net photosynthetic carbon fixation ($P_n$) declined. We observed the highest temperatures of continually increasing isoprene emissions yet reported (50°C). While $P_n$ showed an optimum value of 32.6 ± 0.4°C, isoprene emissions, ETR, and the oxidation state of PSII reaction centers (q L ) increased with leaf temperature with strong linear correlations for ETR (ρ = 0.98) and q L (ρ= 0.99) with leaf isoprene emissions. In contrast, other photoprotective mechanisms, such as non-photochemical quenching (NPQ), were not activated at elevated temperatures. Inhibition of isoprenoid biosynthesis repressed $P_n$ at high temperatures through a mechanism that was independent of stomatal closure. While extreme warming will decrease $g_s$ and $P_n$ in tropical species, our observations support a thermal tolerance mechanism where the maintenance of high photosynthetic capacity under extreme warming is assisted by the simultaneous stimulation of ETR and metabolic pathways that consume the direct products of ETR including photorespiration and the biosynthesis of thermoprotective isoprenoids. Our results confirm that models which link isoprene emissions to the rate of ETR hold true in tropical species and provide necessary "ground-truthing" for simulations of the large predicted increases in tropical isoprene emissions with climate warming.

54 ENVIRONMENTAL SCIENCES↗