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At least 613 records · Page 34

EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers part I: Computational models and workflow

Computational simulations have become central to the seismic analysis and design of major infrastructure over the past several decades. Most major structures are now “proof tested” virtually through representative simulations of earthquake-induced response. More recently, with the advancement of high-performance computing (HPC) platforms and the associated massively parallel computational ecosystems, simulation is beginning to play a role in increased understanding and prediction of ground motions for earthquake hazard assessments. However, the computational requirements for regional-scale geophysics-based ground motion simulations are extreme, which has restricted the frequency resolution of direct simulations and limited the ability to perform the large number of simulations required to numerically explore the problem parametric space. In this article, recent developments toward an integrated, multidisciplinary earth science-engineering computational framework for the regional-scale simulation of both ground motions and resulting structural response are described with a particular emphasis on advancing simulations to frequencies relevant to engineered systems. This multidisciplinary computational development is being carried out as part of the US Department of Energy (DOE) Exascale Computing Project with the goal of achieving a computational framework poised to exploit emerging DOE exaflop computer platforms scheduled for the 2022–2023 timeframe.

58 GEOSCIENCES↗

Discovery top-down proteomics in symbiotic soybean root nodules

Proteomic methods have been widely used to study proteins in complex biological samples to understand biological molecular mechanisms. Most well-established methods (known as bottom-up proteomics, BUP) employ an enzymatic digestion step to cleave intact proteins into smaller peptides for liquid chromatography (LC) mass spectrometry (MS) detection. In contrast, top-down proteomics (TDP) directly characterizes intact proteins including all possible post-translational modifications (PTMs), thus offering unique insights into proteoform biology where combinations of individual PTMs may play important roles. We performed TDP on soybean root nodules infected by the symbiotic Bradyrhizobium japonicum in both the wildtype bacterium and a nifH- mutant, which lacks the ability to fix nitrogen in the soybean root nodule. TDP captured 1648 proteoforms derived from 313 bacterial genes and 178 soybean genes. Leghemoglobin, the most abundant protein in the sample, existed in many truncated proteoforms. Interestingly, these truncated proteoforms were considerably more abundant in the wildtype relative to the nifH- mutant, implicating protease activity as an important factor in nitrogen fixation. Proteoforms with various PTMs and combinations thereof were identified using an unrestricted open modification search. This included less common PTMs such as myristoylation, palmitoylation, cyanylation, and sulfation. In parallel, we collected high resolution MS imaging (MSI) data of intact proteins and biopolymers (<20 kDa due to current technical limitations) from sections of the soybean root nodules using matrix-assisted laser desorption/ionization (MALDI) coupled to high resolution Orbitrap. Several detected proteoforms exhibited unique spatial distributions inside the infection zone and cortex, suggesting functional compartmentalization in these regions. A subset of peaks from the MALDI-MSI were assigned to proteoforms detected in TDP LCMS data based on matching accurate masses. Many of the proteins detected in both LCMS and MALDI-MSI are currently uncharacterized in UniProt: the PTM and spatial information presented here will be valuable in understanding their biological functions. Taken together, our study demonstrates how untargeted TDP approach can provide unique insights into plant proteoform biology. On-going technology developments are expected to further improve TDP coverage for more comprehensive high-throughput analysis of proteoforms.

59 BASIC BIOLOGICAL SCIENCES↗

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗

Platinum group metal-free (PGM-free) integrated tandem junction photoelectrochemical (PEC) water splitting devices (Final Technical Report)

This project involves using solar light, a photoabsorber, and a catalyst to split water and produce hydrogen. The Department of Energy (DOE) targets for integrated photoelectrochemical (PEC) cells emphasize cost (electrode cost < $200/m 2 ), performance (> 15% solar to hydrogen (STH) efficiency), and stability (> 6 months electrode lifetime), but most approaches skew toward one specific metric. This project exploited interfacial integration of platinum group metal-free (PGM-free) catalysts on the high performance and high value tandem solar cells to attain or exceed the DOE benchmark STH energy conversion efficiency and durability. This was investigated in two thrusts by developing two PEC devices for direct comparison: the first is a high-performance monolithic device based on state-of-the-art GaInP 2 /GaAs tandem solar cells developed at National Renewable Energy Laboratory (NREL), and the second is a high-value device based on earth-abundant wide band gap photoabsorber materials including oxynitride and hybrid organic-inorganic perovskite (HOIP) coupled with commercial narrow band gap silicon (Si). Both these devices were paired with electrocatalysts developed for this purpose at Rutgers University by adapting them to thin films on the photoabsorbers. These catalysts are based on the hydrogen evolution reaction (HER) catalysts (Ni 5 P 4 ), oxygen evolution reaction (OER) catalysts (LiCo 2 O 4 ) previously developed at Rutgers for high-efficiency electrolyzers. For using the high-performance tandem solar cell and Ni 5 P 4 catalysts, we achieved a durability of > 200 h at a STH efficiency of > 10%. For using the high-value wide band gap single junction solar cells on n + Si, we achieved 0.73 mA/cm 2 at 1.23V vs reversible hydrogen electrode (RHE) and -15.9 mA/cm 2 at 0V vs RHE using the oxynitride- and HOIP-based photoelectrodes, respectively. After comparing their photocurrent densities, we down selected the HOIP photoabsorber to couple Si for fabrication of a tandem photocathode. However, due to the COVID-19 pandemic, both the laboratories at Rutgers and NREL were locked down for three months and reopened only partially in 2020. The HOIP/Si tandem photocathode using robust nickel phosphide thin film catalysts cannot be developed within the project period, which is expected to achieve a STH efficiency of > 20%. Also, the low-cost LiCo 2 O 4 OER catalysts need to replace the benchmark IrO 2 for evaluation. Finally, techonomic analysis of full high-performance and high-value integrated PEC devices needs to be carried out for comparison in terms of cost.

08 HYDROGEN↗

Uncovering New Physics in the Cosmic Microwave Background: Developing Novel Theoretical Models and Machine-Learning-Powered Constraints

The search for evidence of new physics via its signatures in the cosmos is a cornerstone goal of the Office of High Energy Physics in the DOE Office of Science. Indeed, the current concordance cosmological model provides intriguing hints for beyond-the-standard-model (BSM) physics, such as dark matter and dark energy. Recently, a potential breakdown has appeared in this model, which could be initial evidence toward a further important revision in our fundamental theoretical understanding of cosmology. This breakdown is reflected in disagreements between inferences of the current expansion rate of the universe, H 0 (the Hubble constant), based on indirect, cosmological data (e.g., from the early universe) and based on direct, local measurements. Despite significant effort, a compelling new concordance cosmological model has yet to be found; achieving significant progress on this front was the first major focus of the project. Theoretical considerations indicate that if the observational discrepancies are not due to systematic errors, they strongly suggest new physics operating in the redshift range just prior to recombination, when cosmic microwave background (CMB) photons last scattered. Crucially, almost all such models produce unique signatures in the CMB temperature and polarization power spectra, which will be measured with unprecedented precision by ongoing and upcoming experiments, including the DOE-supported CMB-S4 project. However, these subtle hints of new physics must be uncovered from beneath a swath of Galactic and extragalactic foreground contamination. Current CMB analysis methods, although powerful, do not optimally infer the CMB power spectrum in the presence of non-Gaussian foregrounds. There is thus scope for theoretical improvement in this foundational challenge of cosmological inference, which formed the second major focus of the project. The primary objectives of the project were two-fold: (1) to develop new theoretical models in cosmology that can restore concordance amongst the full suite of cosmological data sets, thereby potentially providing evidence of novel BSM physics; (2) to develop new theoretical machinery to enable significant sensitivity improvements in searches for new physics in cosmology, particularly via the CMB power spectrum. The two objectives are intertwined, as the analysis methodology improvements in (2) will enable the tightest possible constraints on the signatures of new physics predicted by the novel scenarios in (1). The theoretical approaches to restore concordance focused on models involving novel scalar field dynamics in the pre-recombination universe (the “early dark energy” scenario and modifications thereof), as well as couplings between this field and other components in the standard cosmological model, such as dark matter. We also studied a model featuring a generalization of the decaying dark matter scenario, in which a sub-component of dark matter converts into dark radiation at late times in cosmic history. While these ideas are mostly driven by phenomenological considerations, this tactic has proven extremely successful in cosmology throughout the past few decades, including in the early history of evidence for dark matter and dark energy. The new theoretical machinery envisioned in (2) is undergirded by developments in signal processing and machine learning, which will enable improvements in CMB power spectrum estimation in the presence of non-Gaussian foreground contaminants. In turn, this will yield optimal sensitivity in searches for new physics in the CMB, by maximizing the cosmological information that is extracted from this observable. The most ambitious outcome of this work would be the construction of a new cosmological model that restores concordance amongst data sets. Although the individual models studied here did not fully achieve that goal, significant progress in narrowing down the model space was made, as described below. Moreover, the outcome of the methodological improvements in (2) will significantly impact a wide range of theoretical cosmology, by enabling the tightest possible constraints on any model that leaves novel signatures in the CMB temperature and polarization power spectra.

79 ASTRONOMY AND ASTROPHYSICS↗

Collaborative Research: Improved Efficiency and Coupling of the Radiation Code in the ACME Earth System Model (Final Report)

The complexity of radiative transfer, its importance to the exchange of energy in the climate system, and its high computational cost establishes importance of an accurate and efficient radiative transfer parameterization for climate simulation. Previous work by the proposing team at AER led to the development of the radiation code, RRTMG, which has been widely accepted by the global modeling community as a fast and accurate advancement over the previous generation of radiation codes. It has been in use in the NCAR CESM for many years, and it has been implemented in the initial version the DOE E3SM model. However, its computational cost remains high relative to other components in part due to its complexity and to its inefficient use of modern optimization strategies, and this project helped address this limitation for the code’s application in E3SM. Under other funding, the Investigators of this project led an effort to develop a high-performance broadband radiation code, called RTE+RRTMGP, which is a completely restructured code that will take advantage of modern computational capabilities to enhance its performance while retaining the strengths and accuracy of the original code. Designed to perform over a range of computer architectures, RTE+RRTMGP makes extensive use of Fortran 2003 features to improve both its efficiency and its use of memory. RTE+RRTMGP is expected to be adopted in the next generation of RTE+RRTMGP. This project allowed for advancements to the code’s computational capabilities and adding new and enhanced features. This included revising RTE+RRTMGP to run on GPU processors, analysis of and improvements to the code’s timing, modifying the gas optics in RRTMGP to increase the code’s accuracy, extensive validation of computed fluxes, heating rates and forcings, generating a cloud optical property and vertical sampling capabilities for RTE+RRTMGP, implementing a fast and accurate longwave scattering capability, and groundwork for the inclusion of a capability to specify solar variability. Many of the accomplishment in this project necessitated significant collaboration with the E3SM development team. The result of this project was optimization of a key physical component (radiative transfer calculations) of E3SM, directly supporting E3SM’s overarching global modeling objectives. More broadly, this project provided overall advancements in the use of radiative transfer calculations in atmospheric modeling and simulation, particularly for climate.

58 GEOSCIENCES↗

Optomechanical Tuning of Second Harmonic Generation Anisotropy in Janus MoSSe/MoS 2 Heterostructures

Symmetry breaking in van der Waals materials enables the realization of quantum states and advanced device functionalities. Janus transition-metal dichalcogenides (TMDs) exhibit distinctive nonlinear optical properties due to their broken out-of-plane mirror symmetry. However, the dynamic control of second harmonic generation (SHG) anisotropy and resonance behavior via optical excitation remains elusive. Here, in this work, we investigate the SHG response of Janus MoSSe/MoS 2 heterostructures with 2H and 3R stackings. We can tune the SHG response by varying the incident photon wavelength from 800 to 1000 nm, which shows a resonance-dependent enhancement in intensity and a deviation from 6-fold symmetry, indicating wavelength-dependent anisotropy. The ratio between maximum and minimum intensity in the armchair directions, associated with the SHG anisotropy, reaches a value of 1.73 at the excitation wavelength of 1000 nm. Group theory analysis and first-principles calculations reveal that the observed anisotropy arises from optically induced strain. Our findings highlight the role of symmetry breaking and optical resonance contributing to the optomechanical tuning of SHG anisotropy, offering opportunities for developing Janus TMD-based photonic devices for frequency conversion, light generation, and optical switching.

Janus transition metal dichalcogenides↗

Flexible FlueCO2

Carbon dioxide (CO2) emission reductions remain a significant challenge on the path to clean energy. There are increasing legislative, social, and environmental factors motivating CO2 emissions reduction from power plants with carbon capture and storage (CCS). CCS in natural gas combined cycle (NGCC) power plants is critical to achieve a net-zero carbon electricity grid. Enhanced 45Q tax credits provide new incentives, but currently available technologies are unable to profitably operate in grids with deep variable renewable penetration which require flexible NGCC operation. Luna Labs has developed the FlueCO2 membrane to enable a profitable NGCC-CCS process. The FlueCO2 membrane couples steam transport across the membrane to CO2 transport in the opposite direction, enabling high capture efficiencies and low energy costs even at low CO2 concentrations. The dual-phase membrane can operate in the range of typical flue gas temperatures and pressures and does not require temperature or pressure cycling. Luna Labs’ FlueCO2 technology enables flexible and profitable operation of NGCC plants with lower capital investment and impact on electricity prices. In this Phase 1 project, Luna Labs utilized experimental testing, modeling, process simulation, and standardized costing methodologies to evaluate the techno-economic value of a 650 MW greenfield NGCC plant with FlueCO2 (NGCC-FlueCO2). Key design requirements for operation were established and plant performance under load-leveling conditions was validated through computational fluid dynamics and process modeling. Luna Labs developed a dynamic modeling tool which modeled plant operational modes across a variety of tax structures and electricity pricing scenarios to project the overall Net Present Value (NPV) of the NGCC-FlueCO2. FlueCO2 minimizes the impact of CCS integration on plant operation by integrating directly into the NGCC heat recovery steam generator (HRSG). By tapping into the plant’s low-pressure (LP) steam, operators can divert LP steam to the greenfield NGCC and/or CCS process in response to dynamic markets. Since FlueCO2 will not significantly affect HRSG (or NGCC) operation, CCS only turns off during peak power demand (>$250/MWh). Under baseload conditions, FlueCO2 lowers the capital (37%), energy (36%) and carbon capture (<$40/tonne) costs and can increase the overall plant lifetime NPV by approximately ~$1B in comparison with NGCC solvent-based capture reference cases (NETL Case 31B). Luna Labs has shared its costing tools with several interested partners and customers, which follows a generalizable approach to costing analysis.

Kelly, Jesse↗

Assessment of Impurities in Neptunium Metal Using Double-Focusing SF-ICP-MS

In the transmutation process, minor actinides such as neptunium, americium and curium obtained from spent nuclear fuel are incorporated into new fuel that can be placed into a fast reactor, where these elements fission into products with shorter half-lives which reduces the health and safety hazards. In order to better understand the all the involved processes, fundamental physical properties of actinides should be investigated, and for that reason, high-purity materials need to be produced. One of the main challenges in characterizing these materials is the lack of pure metal available for study, and lack of analytical methods to determine the purity. Trans-uranic elements are challenging to study because of the need to be handled in specialized facilities, safeguards concerns and they are not easily purchased and/or produced. High-purity Np metal is being produced at the Materials and Fuels Complex (MFC) of Idaho National Laboratory (INL), in a process of direct oxide reduction developed by Squires and Lessing, with a target purity of 99.999%. The goal of this research is to develop methods to determine the impurities in the Np metal, with detection limits low enough to achieve this purity level. In this work, we have used several ICP-MS and ICP OES techniques, but the focus was the method development using a recently acquired Double-Focusing Sector Field Inductively Coupled Plasma Mass Spectrometer (SF-ICP-MS). To produce the Np metal, approximately 20 g of the neptunium oxide powder was calcined at 800 oC for 6 h in a magnesium oxide crucible, which is placed inside a stainless steel crucible, that goes into the Hot Uniaxial Press (HUP) furnace insert. After the calcining step, the Np oxide was mixed with approximately 9 g of calcium metal and 100 g of ultra-dry calcium chloride. The HUP furnace was heated in a ramp rate of 50 oC min -1 up to 1000 oC. When the reaction mixture reached 850 oC, a tantalum stirrer was activated at 100 rpm. After the tantalum stirrer was removed and the mixture cooled overnight, the MgO crucible was opened with a hammer and chisel to retrieve the Np metal button at the bottom of the reaction mixture. Prior to the dissolution process, the surface contaminants of the sample were removed. The Np button was washed in 10 mL of ultra-pure water for 1 min, with a faint reaction observed on the surface, indicating the presence of Ca metal. The water-washed sample was placed in a tube with 2 M HCl for only 3 s, as a vigorous reaction in the button surface was observed. The leachates were saved for further analysis. The sample was then rinsed with ultra-pure water and air-dried prior to dissolution. The cleaned sample was placed in a PTFE beaker and 25 mL of 6 M HCl and 150 µL of 24 M HF were added. After 10 minutes of reaction, the beaker was placed on a hot plate for 1 h and 30 min, followed by the addition of 1 mL of 16 M HNO3 and allowed to react for a further 1 h and 20 min. The sample was removed from heat and 10 mL of HNO3 16 M was added to react with the HCl. The beaker was covered and left for overnight reaction, producing a solution with approximately 20 mL of final volume. A Quadrupole Inductively Coupled Plasma Mass Spectrometer (Q-ICP-MS, Perkin Elmer ELAN DRC II Q-ICP-MS) was used to obtain qualitative mass spectra for the dissolution blank, each of the leachates and the dissolved sample. In the water leachate spectrum mainly Ca and Mg were observed, while the acid wash had a similar peak pattern to the one observed for the Np metal sample, indicating that the process not only removed surface contamination, but also reacted with the sample itself. In the Np material spectrum, Ta and actinides were identified as candidates for major contaminants, as the most intense peaks corresponded to the mass-to-charge ratios of these elements. Minor contaminants included Al, Au, Ca, Cr, Fe, I, Na, Nb, Pb, Sn, Ti, Tl, V, Y. The presence of impurities in the material could have originated from several sources, such as the materials used for the casting process, the use of impure NpO2 or contamination of reagents and materials used for the analysis. Some of the isotopes listed as potential contaminants are susceptible to spectral interferences, so Double-Focusing SF-ICP-MS (Nu Instruments Attom ES HR-ICP-MS) was used for the quantitative analysis. For each isotope determined, several items were evaluated: raw signal of a blank solution, sensitivity and determination coefficient of calibration curves, possibility of interferences and comparison of results obtained for at least two resolving powers (RP): 300 and 4000. The evaluation of the signal in a blank solution can indicate if a spectral interference from the plasma gas and/or the solvent was successfully resolved (commonly observed for 52Cr+/40Ar12C+, for example). It is important to highlight that a signal reduction is expected when a higher RP is used, as the ion beam transmission is decreased by the use of narrower slits

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗

One-bond 13 C– 13 C spin-coupling constants in saccharides: a comparison of experimental and calculated values by density functional theory using solid-state 13 C NMR and X-ray crystallography

Methyl aldohexopyranosides were 13 C-labeled at contiguous carbons, crystallized, and studied by single-crystal X-ray crystallography and solid-state 13 C nuclear magnetic resonance (NMR) spectroscopy to examine the degree to which density functional theory (DFT) can calculate one-bond 13C–13C spin-coupling constants ( 1 J CC ) in saccharides with sufficient accuracy to permit their use in MA'AT analysis, a newly-reported hybrid DFT/NMR method that provides probability distributions of molecular torsion angles in solution (Zhang et al., J. Phys. Chem. B, 2017, 121, 3042–3058; Meredith et al., J. Chem. Inf. Model., 2022, 62, 3135–3141). Experimental 1 J CC values in crystalline samples of the doubly 13 C-labeled compounds were measured by solid-state 13 C NMR and compared to those calculated from five different DFT models: (1) 1 J CC values calculated from single structures identical to those observed in crystalline samples by X-ray crystallography (all atom refinement); (2) 1 J CC values calculated from the single structures in (1) but after Hirshfeld atom refinement (HAR); (3) 1 J CC values calculated from the single structures in (1) after DFT-optimization of hydrogen atoms only; and (4 and 5) 1 J CC values calculated in rotamers of torsion angle θ 2 (C1–C2–O2–O2H) or ω(C4–C5–C6–O6) from which either specific or generalized parameterized equations were obtained and used to calculate 1 J CC values in the specific θ 2 or ω rotamers observed in crystalline samples. Good qualitative agreement was observed between calculated 1 J CC values and those measured by solid-state 13 C NMR regardless of the DFT model, but in no cases were calculated 1 J CC values quantitative, differing (over-estimated) on average by 4–5% from experimental values. These findings, and those reported recently from solution NMR studies (Tetrault et al., J. Phys. Chem. B 2022, 126, 9506–9515), indicate that improvements in DFT calculations are needed before calculated 1 J CC values can be used directly as reliable constraints in MA'AT analyses of saccharides in solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions

Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.

17 WIND ENERGY↗

The bond energy of UN + : Guided ion beam studies of the reactions of U + with N 2 and NO

In this work, a guided ion beam tandem mass spectrometer was used to study the reactions of U + with N 2 and NO. Reaction cross sections were measured over a wide range of energy for both systems. In each reaction, UN + is formed by an endothermic process, thereby enabling the direct measurement of the threshold energy and determination of the UN + bond dissociation energy. For the reaction of U + + N 2 , a threshold energy (E 0 ) of 4.02 ± 0.11 eV was measured, leading to D 0 (UN + ) = 5.73 ± 0.11 eV. The reaction of U + + NO yields UO + through an exothermic, barrierless process that proceeds with 94 ± 23% efficiency at the lowest energy. Analysis of the endothermic UN + cross section in this reaction provides E 0 = 0.72 ± 0.11 eV and, therefore, D 0 (UN + ) = 5.78 ± 0.11 eV. Averaging the values obtained from both reactions, we report D 0 (UN + ) = 5.76 ± 0.13 eV as our best value (uncertainty of two standard deviations). Combined with precise literature values for the ionization energies of U and UN, we also derive D 0 (UN) = 5.86 ± 0.13 eV. Both bond dissociation energies agree well with high-level theoretical treatments in the literature. The formation of UN + in reaction of U + with NO also exhibits a considerable increase in reaction probability above ~3 eV. Theory suggests that this may be consistent with the formation of UN + in excited quintet spin states, which we hypothesize are dynamically favored because the number of 5f electrons in reactants and products is conserved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Anoxic Iron Corrosion on WIPP Brine Geochemistry FY23 Final Report (U)

A 280-day study was completed to evaluate the effect of zero-valent iron (Fe 0 ) on the Waste Isolation Pilot Plant (WIPP) brine geochemistry under anticipated reducing conditions. Hydrogen (H 2 ) gas is expected to be present in the repository after closure due to the anoxic corrosion of a vast quantity of iron contained in the waste forms disposed at WIPP; therefore, a background argon atmosphere containing H 2 was chosen for this study. WIPP groundwater brine pH and E h will impact the mobility and fate of plutonium within the repository. Modeling and laboratory results for Castile WIPP brine indicate that equilibrium fa values relative to the standard hydrogen electrode (SHE) are 40 mV more reducing (i.e., more negative) than those for Salado WIPP brine (-480 mV vs. -440 mV, respectively) because of the higher pH of the Castile brine (pH 9 .3 for Castile vs. pH 8.8 for Salado). The E h and pH data were corrected for the effects of high ionic strength. The experimental results for both brines are consistent with thermodynamic predictions using OLI Systems' Mixed Solvent Electrolyte chemical equilibrium model. The measured and corrected pH and E h data from this study are provided in Table ES-I and Table ES-2, respectively. The experimental study, with four test conditions in triplicate, was performed in a dual glovebox with a nominally 3 vol.% H 2 in argon atmosphere (target H 2 range: 3 ± I vol.%). Simulants containing MgO only ( experimental control) and MgO+Fe 0 (WIPP base case) were prepared for both the Salado and Castile brines. MgO was included in all simulants to account for the use of bulk magnesium oxide in the WIPP repository. Fe 0 was included in some simulants to incorporate the effects of the anoxic corrosion of iron and in-situ hydrogen generation in the study. The brine compositions were developed by Sandia National Laboratory (SNL; Xiong, 2008) and have been used in previous WIPP evaluations. The test method (agitation, etc.) is partially based on ASTM D3987-12. Twelve rounds of periodic measurements of pH and E h were performed over the course of the study. Chemical analysis results for liquids and solids (ICP-MS, ICP-ES, IC Anion, TIC, SEM-EDX) are consistent with the pH, E h , and thermodynamic modeling results. This study included the following conditions that deviate from anticipated post-closure conditions following brine intrusion, but were selected to facilitate bench-scale testing to validate modeling of pH and E h for the post-closure WIP P repository: an anoxic glove box atmosphere containing ≤ 4 vol. % H 2 vs. substantially higher H 2 gas concentrations assumed in the WIPP Performance Assessment (PA); a significantly higher liquid-to-solid test ratio compared to the much lower phase ratio anticipated in the WIP P repository; agitation of the simulant bottles to maximize mass transfer; and finally the use of Fe 0 reagents having a much greater surface area than expected in the WIP P repository. Non-representative conditions were chosen for various reasons such as: to provide bounding conservative results, to provide a margin of safety for testing, or to facilitate simulant sub-sampling and analysis. In a parallel effort, aqueous electrolyte thermodynamic models were developed for the synthetic Salado and Castile brines to inform the experimental design, facilitate laboratory data interpretation, and allow extension of evaluations beyond the parameters tested. Thermodynamic modeling simulations including the MgO and Fe 0 additives that are directly relevant to the experimental measurements (e.g., pH calibration curve, ORP corrections) are included in this report. The measured fa of the simulants was close to the OLI model predictions for both brines and was largely controlled by the background H 2 partial pressure in the vapor phase as well as H 2 generated in situ in the aqueous phase by the Fe 0 corrosion. The H 2 gas-phase concentration tested and thermodynamically evaluated was much lower than is assumed in the WIPP PA; however, H 2 (g) concentrations significantly below this level are still predicted to result in very reducing conditions. In conclusion: • The experimental results are consistent with thermodynamic model predictions for fa, pH, and the effects of high ionic strength. • Evidence to date suggests that the H2 concentration in the glovebox atmosphere ultimately determined the final E h values of the simulants and resulted in highly reducing conditions. As a result, little difference was observed between the control simulants containing only MgO and the WIPP base-case simulants that contained MgO and Fe 0 . • This test methodology is recommended for future studies evaluating WIPP repository conditions. The methodology includes: (1) background H 2 in argon with agitation ( or could alternatively include in-situ-generated H 2 in sealed bottles); (2) carefully measured and corrected ORP data ( with much effort focused on allowing the probes to fully stabilize); and (3) ionic-strength-corrected pH data. Other best practices, such as simulant sparging/handling, ORP probe replacement, etc., should also be considered. • The coupling of experimental studies and thermodynamic modeling is also highly recommended because these methods inform and direct one another leading to greater confidence in and understanding of the results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗

A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

36 MATERIALS SCIENCE↗

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗

Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation

This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.

ITER↗