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At least 865 records · Page 48

Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300

The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.

54 ENVIRONMENTAL SCIENCES↗

Parametric Study of Used Nuclear Oxide Fuel Constituent Dissolution in Molten LiCl-KCl-UCl 3

Prior work identified dissolution of used nuclear oxide fuel constituents from a uranium oxide matrix into molten LiCl-KCl-UCl 3 at 500°C, prompting a subsequent series of three progressive studies (including an initial scoping study, an electrolytic dissolution study, and a chemical-seeded dissolution study) to further investigate associated parameters and mechanisms. Thermodynamic calculations were performed to identify possible reaction mechanisms and their propensities in used oxide fuel constituent dissolution. Used nuclear oxide fuels with varying preconditions from fast and thermal test reactors were separately immersed in the subject salt system to assess fuel constituent migration from the bulk fuel matrix to the salt phase in an initial scoping study. Dissolution of expected fuel constituents, including alkali, alkaline earth, lanthanide, and transuranium oxides, into the chloride salt phase varied widely, ranging from 12% to 99% in the initial study. Uranium isotope blending between the salt phase and bulk fuel matrix was also observed, which was attributed to reducing conditions in the fuel matrix. Electrolytic and chemical-seeded dissolution studies were subsequently performed to effect reducing conditions in the fuel. Other parameters, including temperature (at 500°C, 650°C, 725°C, and 800°C) and uranium trichloride concentrations (at 6, 9, and 19 wt% uranium), were investigated in the latter two studies, resulting in fuel constituent dissolution above 90%. Extents of dissolution were based on initial and final fuel constituent concentrations in the oxide fuels following operations in the salt and subsequent removal of the salt via distillation. Finally, in this series of progressive studies, oxide fuel preconditioning and in situ reducing conditions, along with elevated temperature and uranium trichloride concentrations, were the primary parameters promoting used nuclear oxide fuel constituent dissolution in accordance with identified reaction mechanisms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ORGANIC RANKINE CYCLE TURBINE AND HEAT EXCHANGER SIZING FOR LIQUID AIR COMBINED CYCLE

Cryogenic energy storage offers several opportunities to design turbomachinery and other equipment for novel cycles. This paper presents the design and analysis of turbomachinery and heat exchangers for an Organic Rankine Cycle (ORC) subsystem for a hybrid energy storage concept. The Liquid Air Combined Cycle is an energy storage system that stores air at cryogenic conditions at times with high variable renewable energy to be dispatched along with a gas turbine to recover the exhaust heat. In order to re-vaporize the air, the liquid air is coupled with an ORC as an additional bottoming cycle. The ORC turbine is expected to expand the fluid with a pressure ratio of nearly 30 and a flow rate of approximately 45 kg/s. Sizing calculations for both a radial and axial turbine solution were performed over a range of speeds and stages to determine the optimal design point. The results show that either an axial (8- or 9-stage) or radial (four stages at two shaft speeds) turbine are capable of handling the pressure ratios. Further trades of the two configurations would be required to determine the best option. The ORC system also incorporates five heat exchangers to distribute heat, vaporize the liquid air, or recover exhaust heat from the gas turbine. Three heat exchangers were analyzed to understand the size of heat exchangers and pressure drop for the overall system. Different types of heat exchangers were explored for the different purposes, including plate-fin heat exchangers, gasketed plate heat exchangers and shell-in-tube heat exchangers. It was determined that the ORC recuperator, liquid-air vaporizer, and vaporized air pre-heater would be counter-flow heat exchangers using a gasketed plate design. Keywords: Energy Storage, Liquid Air Energy Storage, Organic Rankine Cycle

Pryor, Owen↗

Diverse Super-Resolution (diversity_SR) [SWR-21-60]

Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.

Glaws, Andrew↗

Mechanical Testing of FeCrAl Tubing

The axial tensile properties of C26M tube were successful measured at Los Alamos National Laboratory. Test were conducted at a constant strain rate of 10 -3 s -1 and three different temperatures (22, 300, and 600°C). As typically expected, an increase in the testing temperature lead to a decrease in both the yield stress (YS), from 710 to 273 MPa, and ultimate tensile strength (UTS), from 730 to 290 MPa. The ultimate tensile strength was observed almost immediately post-yielding for all test conditions, and thus the uniform elongation was limited to 1.2-1.6%. The total elongation of the 600°C specimens was notably higher (~47%) than both the 22 and 300°C specimens, which exhibited a similar response (~10%).

36 MATERIALS SCIENCE↗

Flame Characterization and Flashback Studies of Hydrogen-Enriched Low-Swirl Flames Using High-Speed OH-PLIF

Here, this paper reports the flashback mechanism observed in hydrogen-enriched flames stabilized in a low-swirl burner (LSB) at atmospheric temperature and pressure. The fundamentals of hydrogen-rich stable flames and spatiotemporal information of flashback phenomena were observed experimentally using a high-repetition-rate nanosecond (ns)-duration hydroxyl planar laser-induced fluorescence (OH-PLIF) diagnostic. Testing was conducted for methane and hydrogen (50–90%H 2 , by mole) blends in an optically accessible LSB premixer with measured swirl numbers varying from 0.43 to 0.49. The flashback propensity showed dependence on liftoff length, which was dependent on premixer velocity (𝑉), hydrogen content (𝑋 H 2 ), and equivalence ratio (𝜙) at constant temperature and pressure. High-speed OH-PLIF images revealed that lifted flames were first observed at low 𝜙/𝑋 H 2 conditions, which were changed to an M-shaped flame attached to the burner rim with an increase in 𝜙/𝑋 H 2 . A further increase in 𝜙/𝑋 H 2 triggered the flame flashback into the premixer. Flame 𝜙 at flashback (𝜙 FB ) showed an expected linearly increasing trend with increasing 𝑉 and decreasing 𝑋 H 2 , and the conclusions drawn aligned well with detailed liftoff length investigations. The 𝜙 FB increased with increasing perforated plate hole diameter and increasing swirler vane angle. The vane angle had little effect on flashback tendency at high premixer velocity.

combustion↗

Impact of Hydrogen Combustion on the Oxidation-induced Degradation of Heavy-duty Diesel Engine Piston Materials

High temperature ferritic-martensitic steels are candidate materials for heavy-duty diesel engine pistons. The envisioned transition to hydrogen blended fuels is expected to alter the post-combustion atmosphere in the engines, primarily resulting in a higher water vapor content (> 20 vol%) and potentially higher exhaust gas temperatures. The oxidation resistance of existing and newly developed alloys will be a critical life-limiting mechanism under these conditions. In the present work, the oxidation behavior of candidate piston alloys was evaluated in air+10 vol.% H2O and air+30 vol.% H2O at 700°C. Thermal cyclic (1h cycle) exposures were conducted for two variants of commercial UNSS42200 ferritic-martensitic steel and two developmental alloy steels for up to 300h. The developmental alloys each have similar compositions but with one containing elevated Cu levels of 3 wt.%, A significant reduction in resistance to breakaway oxidation was observed for the commercial alloys in the higher water vapor atmosphere. Microstructural characterization (optical metallography, scanning electron microscopy and electron microprobe analysis) revealed the formation of thick Fe-rich oxides even for the high Cr (~12 wt.%) steels after an initial stage of protective oxidation with MnCr-rich spinels. The impact of the evaporation-induced loss of Cr on the time and temperature dependent compositional changes in the alloys was correlated with experimental findings. For the developmental alloys, Cu additions appear to play a role in significantly reducing oxidation kinetics in air+30 vol.% H2O at 700°C.

Pillai, Rishi [ORNL] (ORCID:0000000243688197)↗

Effectiveness of Advanced Three Fluid Heat and Mass Exchanger

Advanced internally-cooled membraned-based heat and mass exchangers (HMX), which accounts for three separate fluid streams, are capable of utilizing the sensible and latent heat removed from spacecooling to heat water. The technology provides a unique approach of enhancing the efficiency and cost effectiveness of future HVAC equipment. This paper aims to numerically identify and understand the impact of geometric size, operation conditions, and membrane properties on the overall effectiveness of three-fluid HMXs. The simulations are based on an ORNL in-house open-source HMX model which is capable of simulating such three-fluid HMX components for various flow patterns. The results are expected to enable detailed configuration evaluation and provide in-depth understanding of optimal three-fluid HMX performance at cost effectiveness.

Gao, Zhiming↗

Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning

Nuclear reactors and related systems are becoming increasingly complex due to advancing technologies in next-generation power reactors. This increased complexity necessitates enhanced automation and data management capabilities. To successfully realize autonomous systems, methods must be developed to handle vast volumes of data and effectively distinguish anomalous data from noise and expected data. While impressive models utilizing digital twins and similar approaches are under development, here we propose a simplified model for analyzing fundamental methods and techniques. Initially, we created a general dataset by using initial data from PCTRAN in order to represent ideal steady-state conditions. We then inserted anomalies based on prevalent sensor anomaly types (e.g., point anomalies, linear drift, and downward deviations), along with unusual anomalies such as exponential drift and upward deviations. To detect anomalies, we developed a program that employs data partitioning and linear regression to preprocess and filter the anomalous data. A K-Means machine learning (ML) method was then applied to separate and count the data within the anomalous partition. The results from all datasets—apart from exponential growth—demonstrated positive outcomes, with each returning multiple instances of greaterthan-95% accuracy. We conducted further investigations using Idaho National Laboratory’s RAVEN software to perform a sensitivity analysis on the input variables (R 2 Tolerance, Slope Tolerance, and Window Size) and found that the output variables (Accuracy and Time) were most sensitive to the Window Size. Despite the promising results published, further development is required to effectively apply these methods to nuclear systems. Nevertheless, the strengths of this approach are evident and hold promise for future applications in the field.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel

Here, predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally onerous. To address this limitation, a new approach is proposed whereby a surrogate constitutive model (SM) of the inelastic response of 316H steel is derived from a mechanistic crystal plasticity-based polycrystal model tracking the evolution of dislocation densities on all slip systems. The latter is used to generate a database of the expected plastic response and dislocation content evolution associated with several instances of creep loading. From the database, a SM is developed. It relies on the use of orthogonal polynomial regression to describe the evolution of the dislocation content. The SM is then validated against predictions of the dead load creep response given by the polycrystal model across a range of temperatures and stresses. When the SM is used to predict the response of 316H during complex non monotonic loading, extrapolating to new loading conditions, it is found that predictions compare particularly well against those from the physics-based polycrystal model.

36 MATERIALS SCIENCE↗

200 h of discharge cycling with an all-aqueous copper thermally regenerative ammonia battery

Thermally regenerative ammonia batteries (TRABs) offer an approach to energy storage and electricity generation by harnessing low-grade heat (T < 150 °C). A TRAB discharge resembles that of a flow battery, where electrochemical reactions produce electrical power from energy stored within aqueous electrolytes. While there are many types of TRABs, the all-aqueous copper TRAB (Cu aq -TRAB) has produced the largest power and energy storage densities. Despite many improvements to TRAB performance, most tests have only lasted a few hours, which are not representative of operation times expected of these devices. Herein, we operated a Cu aq -TRAB for 200 h of constant current discharging to assess battery performance and component stability. After 200 h of testing, the average power density increased slightly to 7.2 mW cm -2 , which was within 0.01 % of starting conditions. Likewise, the average energy density for the final cycle was only 0.03 % lower than the initial cycle. The overall insensitivity of the power cell to cycling represents a major milestone in the advancement of TRAB systems. In conclusion, energy dispersive X-ray spectroscopy provides evidence to suggest that these small changes in power and energy density are likely to the membrane acclimating to TRAB electrolytes.

25 ENERGY STORAGE↗

Regulation of the normalized rate of driven magnetic reconnection through shocked flux pileup

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.

Physics↗

Immobilizing Pertechnetate in Ettringite via Sulfate Substitution

Until recently, a nuclear waste form did not exist for the immobilization and long-term storage of the anionic form of radionuclide technetium-99 (99Tc), pertechnetate (TcO 4 - ). Across international nuclear waste sites, the inability to capture TcO 4 - poses a threat to the local environment due to the anion’s long half-life and environmental mobility under environmentally oxic conditions. To combat this challenge, most waste forms would capture 99Tc using materials that reduce TcO 4 - to Tc(IV) species, e.g. 99Tc oxides or 99Tc sulfides. However, this is a short-lived solution unless reducing capacities can be regenerated to last over the long life expectancy of some nuclear waste forms (~10,000 years). In light of recent experimental observations gained from the development of cementitious waste forms and unconfirmed hypotheses from the literature, this work explores how ettringite, a common mineral formed in cementitious materials with demonstrated success in incorporating oxyanions, may be used to immobilize TcO 4 - directly and over the life-time of the waste form. Using batch precipitation experiments, solid phase characterization techniques, and ab initio molecular dynamics simulations, we demonstrate herein successful incorporation of TcO 4 - into ettringite via substitution for SO 4 2- within the ettringite crystal structure. Here, these results are first of their kind and confirm the hypothesis that ettringite acts as an immobilizing mineral within cementitious waste forms for the highly mobile TcO 4 - oxyanion, enhancing the overall performance of these waste forms over time.

36 MATERIALS SCIENCE↗

Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network

Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH 2 )O-C(=O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Effect of Historical SST Patterns on Radiative Feedback

Here, we investigate the dependence of radiative feedback on the pattern of sea-surface temperature (SST) change in fourteen Atmospheric General Circulation Models (AGCMs) forced with observed variations in SST and sea-ice over the historical record from 1871 to near-present. We find that over 1871-1980, the Earth warmed with feedbacks largely consistent and strongly correlated with long term climate sensitivity feedbacks (diagnosed from corresponding atmosphere-ocean GCM abrupt 4xCO2 simulations). Post 1980 however, the Earth warmed with unusual trends in tropical Pacific SSTs (enhanced warming in the west, cooling in the east) and cooling in the Southern Ocean that drove climate feedback to be uncorrelated with – and indicating much lower climate sensitivity than – that expected for long-term CO 2 increase. We show that these conclusions are not strongly dependent on the AMIP II SST dataset used to force the AGCMs, though the magnitude of feedback post 1980 is generally smaller in nine AGCMs forced with alternative HadISST1 SST boundary conditions. We quantify a ‘pattern effect’ (defined as the difference between historical and longterm CO 2 feedback) equal to 0.48 ± 0.47 [5-95%] W m -2 K -1 for the time-period 1871-2010 when the AGCMs are forced with HadISST1 SSTs, or 0.70 ± 0.47 [5-95%] W m -2 K -1 when forced with AMIP II SSTs. Assessed changes in the Earth’s historical energy budget agree with the AGCM feedback estimates. Furthermore satellite observations of changes in top-of-atmosphere radiative fluxes since 1985 suggest that the pattern effect was particularly strong over recent decades but may be waning post 2014.

54 ENVIRONMENTAL SCIENCES↗

Reinforcement learning-based design of shape-changing metamaterials

During the last decade, artificially architected materials have been designed to obtain properties unreachable by naturally occurring materials, whose properties are determined by their atomic structure and chemical composition. In this work, we implement a new reinforcement learning (RL) method able to rationally design unique metamaterial structures at the nano-, micro-, and macroscale, which change shape during operational conditions. As an example, we apply this method to design nanostructured silicon anodes for Li-ion batteries (LIBs). The RL model is designed to apply different actions and predict change during operational conditions. The multi-component reward function comprises an increase in the total storage capacity of the resulting battery electrode and structural parameters, such as the minimum distance between the individual components of the nanostructure. Upon experimental validation using a polymer-based 3D printing technique, we expect that the newly discovered structures improve the current Si-based LIB anodes state-of-the-art by almost three times and almost ten times the current commercial LIB based on a graphitic anode. Furthermore, this RL-based optimization method opens up vast design space for other responsive metamaterials with tailored properties and pre-programmed structural transformation.

25 ENERGY STORAGE↗

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗