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High-flux plasma exposure of ultra-fine grain tungsten

Here we examine the response of an ultra-fine grained (UFG) tungsten material to high-flux deuterium plasma exposure. UFG tungsten has received considerable interest as a possible plasma-facing material in magnetic confinement fusion devices, in large part because of its improved resistance to neutron damage. However, optimization of the material in this manner may lead to trade-offs in other properties. Moreover, we address two aspects of the problem in this work: (a) how high-flux plasmas modify the structure of the exposed surface, and (b) how hydrogen isotopes become trapped within the material. The specific UFG tungsten considered here contains 100 nm-width Ti dispersoids (1 wt%) that limit the growth of the W grains to a median size of 960 nm. Metal impurities (Fe, Cr) as well as O were identified within the dispersoids; these species were absent from the W matrix. To simulate relevant particle bombardment conditions, we exposed specimens of the W-Ti material to low energy (100 eV), high-flux (> 10 22 m -2 s -1 ) deuterium plasmas in the PISCES-A facility at the University of California, San Diego. To explore different temperature-dependent trapping mechanisms, we considered a range of exposure temperatures between 200 °C and 500 °C. For comparison, we also exposed reference specimens of conventional powder metallurgy warm-rolled and ITER-grade tungsten at 300 °C. Post-mortem focused ion beam profiling and atomic force microscopy of the UFG tungsten revealed no evidence of near-surface bubbles containing high pressure D2 gas, a common surface degradation mechanism associated with plasma exposure. Thermal desorption spectrometry indicated moderately higher trapping of D in the material compared with the reference specimens, though still within the spread of values for different tungsten grades found in the literature database. Finally, for the criteria considered here, these results do not indicate any significant obstacles to the potential use of UFG tungsten as a plasma-facing material, although further experimental work is needed to assess material response to transient events and high plasma fluence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SU-D-213-06: Dosimetry of Modulated Electron Radiation Therapy Using Fricke Gel Dosimeter

Purpose: Modulated electron radiation therapy (MERT) has been proposed as an effective modality for treatment of superficial targets. MERT utilizes multiple beams of different energies which are intensity modulated to deliver optimized dose distribution. Energy independent dosimeters are thus needed for quantitative evaluations of MERT dose distributions and measurements of absolute doses delivered to patients. Thus in the current work we study the feasibility of Fricke gel dosimeters in MERT dosimetry. Methods: Batches of radiation sensitive Fricke gel is fabricated and poured into polymethyl methacrylate cuvettes. The samples were irradiated in solid water phantom and a thick layer of bolus was used as a buildup. A spectrophotometer system was used for measuring the color changes (the absorbance) before and after irradiation and then we calculate net absorbance. We constructed calibration curves to relate the measured absorbance in terms of absorbed dose for all available electron energies. Dosimetric measurements were performed for mixed electron beam delivery and we also performed measurement for segmented field delivery with the dosimeter placed at the junction of two adjacent electron beams of different energies. Dose measured by our gel dosimetry is compared to that calculation from our precise treatment planning system. We also initiated a Monte Carlo study to evaluate the water equivalence of our dosimeters. MCBEAM and MCSIM codes were used for treatment head simulation and phantom dose calculation. PDDs and profiles were calculated for electron beams incident on a phantom designed with 1cm slab of Fricke gel. Results: The calibration curves showed no observed energy dependence with all studied electron beam energies. Good agreement was obtained between dose calculated and that obtained by gel dosimetry. Monte Carlo results illustrated the tissue equivalency of our Gel dosimeters. Conclusion: Fricke Gel dosimeters represent a good option for the dosimetric quality assurance prior to MERT application.

60 APPLIED LIFE SCIENCES↗

A wire calorimeter for the SPIDER beam: Experimental tests and feasibility study

To study and optimize negative ion production and acceleration, in view of the use of neutral beam injectors in the ITER project, the SPIDER test facility (particle energy 100keV; beam current 50A, distributed over 1280 beamlets) is under construction in Padova, with the aim of testing beam characteristics and to verify the source proper operation, by means of several diagnostic systems. An array of tungsten wires, directly exposed to the beam and consequently heated to high temperature, is used in similar experiments at IPP-Garching to study the beam optics, which is one of the most important issues, in a qualitative way. The present contribution gives a description of an experimental investigation of the behavior of tungsten wires under high heat loads in vacuum. Samples of tungsten wires are heated by electrical currents and the emitted light is measured by a camera in the 400-1100nm wavelength range, which is proposed as a calibration tool. Simultaneously, the voltage applied to the wire is measured to study the dependency of emissivity on temperature. The feasibility study of a wire calorimeter for SPIDER is finally proposed; to this purpose, the expected behaviour of tungsten with the two-dimensional beam profile in SPIDER is numerically addressed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Description of reaction and vibrational energetics of CO 2 –NH 3 interaction using quantum computing algorithms

CO 2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO 2 . Thus, it is crucial to study the chemical absorption of CO 2 by amine-based solvents to better understand and optimize CO 2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO 2 and a simplified amine-based solvent model—NH 3 . Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular vibrational calculations by including anharmonicity. We implement a variational quantum eigensolver (VQE) algorithm in a quantum simulator to calculate ground state vibrational energies of reactants and products of the CO 2 and NH 3 reaction. The VQE calculations yield ground vibrational energies of CO 2 and NH 3 with similar accuracy to classical computing. In the presence of hardware noise, Compact Heuristic for Chemistry (CHC) ansatz with shallower circuit depth performs better than Unitary Vibrational Coupled Cluster. The “Zero Noise Extrapolation” error-mitigation approach in combination with CHC ansatz improves the vibrational calculation accuracy. Excited vibrational states are accessed with quantum equation of motion method for CO 2 and NH 3 . Using quantum Hartree–Fock (HF) embedding algorithm to calculate electronic energies, the corresponding reaction profile compares favorably with Coupled Cluster Singles and Doubles while being more accurate than HF. Our research showcases quantum computing applications in the study of CO 2 capture reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Clostridium autoethanogenum alters cofactor synthesis, redox metabolism, and lysine-acetylation in response to elevated H 2 :CO feedstock ratios for enhancing carbon capture efficiency

Clostridium autoethanogenum is an acetogenic bacterium that autotrophically converts carbon monoxide (CO) and carbon dioxide (CO 2 ) gases into bioproducts and fuels via the Wood–Ljungdahl pathway (WLP). To facilitate overall carbon capture efficiency, the reaction stoichiometry requires supplementation of hydrogen at an increased ratio of H 2 :CO to maximize CO 2 utilization; however, the molecular details and thus the ability to understand the mechanism of this supplementation are largely unknown. In order to elucidate the microbial physiology and fermentation where at least 75% of the carbon in ethanol comes from CO 2 , we established controlled chemostats that facilitated a novel and high (11:1) H 2 :CO uptake ratio. We compared and contrasted proteomic and metabolomics profiles to replicate continuous stirred tank reactors (CSTRs) at the same growth rate from a lower (5:1) H 2 :CO condition where ~ 50% of the carbon in ethanol is derived from CO 2 . Our hypothesis was that major changes would be observed in the hydrogenases and/or redox-related proteins and the WLP to compensate for the elevated hydrogen feed gas. Our analyses did reveal protein abundance differences between the two conditions largely related to reduction–oxidation (redox) pathways and cofactor biosynthesis, but the changes were more minor than we would have expected. While the Wood–Ljungdahl pathway proteins remained consistent across the conditions, other post-translational regulatory processes, such as lysine-acetylation, were observed and appeared to be more important for fine-tuning this carbon metabolism pathway. Metabolomic analyses showed that the increase in H 2 :CO ratio drives the organism to higher carbon dioxide utilization resulting in lower carbon storages and accumulated fatty acid metabolite levels. This research delves into the intricate dynamics of carbon fixation in C. autoethanogenum, examining the influence of highly elevated H 2 :CO ratios on metabolic processes and product outcomes. The study underscores the significance of optimizing gas feed composition for enhanced industrial efficiency, shedding light on potential mechanisms, such as post-translational modifications (PTMs), to fine-tune enzymatic activities and improve desired product yields.

09 BIOMASS FUELS↗

Technical Note: Experimental carbon ion range verification in inhomogeneous phantoms using prompt gammas

Purpose: The purpose of this study was to experimentally assess the possibility to monitor carbon ion range variations—due to tumor shift and/or elongation or shrinking—using prompt-gamma (PG) emission with inhomogeneous phantoms. Such a study is related to the development of PG monitoring techniques to be used in a carbon ion therapy context. Methods: A 95 MeV/u carbon ion beam was used to irradiate phantoms with a variable density along the ion path to mimic the presence of bone and lung in homogeneous humanlike tissue. PG profiles were obtained after a longitudinal scan of the phantoms. A setup comprising a narrow single-slit collimator and two detectors placed at 90° with respect to the beam axis was used. The time of flight technique was applied to allow the selection between PG and background events. Results: Using the positions at 50% entrance and 50% falloff of the PG profiles, a quantity called prompt-gamma profile length (PGPL) is defined. It is possible to observe shifts in the PGPL when there are absolute ion range shifts as small as 1–2 mm. Quantitatively, for an ion range shift of −1.33 ± 0.46 mm (insertion of a Teflon slab), a PGPL difference of −1.93 ± 0.58 mm and −1.84 ± 1.27 mm is obtained using a BaF{sub 2} and a NaI(Tl) detector, respectively. In turn, when an ion range shift of 4.59 ± 0.42 mm (insertion of a lung-equivalent material slab) is considered, the difference is of 4.10 ± 0.54 and 4.39 ± 0.80 mm for the same detectors. Conclusions: Herein, experimental evidence of the usefulness of employing PG to monitor carbon ion range using inhomogeneous phantoms is presented. Considering the homogeneous phantom as reference, the results show that the information provided by the PG emission allows for detecting ion range shifts as small as 1–2 mm. When considering the expected PG emission from an energy slice in a carbon ion therapy scenario, the experimental setup would allow to retrieve the same PGPL as the high statistics of the full experimental dataset in 58% of the times. However, this success rate increases to 93% when using a better optimized setup by means of Monte Carlo simulations.

60 APPLIED LIFE SCIENCES↗

Portable, heterogeneous ensemble workflows at scale using libEnsemble

libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator–allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a simulator or generator should be called. The generator steers the ensemble based on simulation results. Generators may, for example, apply methods for numerical optimization, machine learning, or statistical calibration. libEnsemble communicates between a manager and workers. Flexibility is provided through multiple manager–worker communication substrates each of which has different benefits. These include Python’s multiprocessing, mpi4py, and TCP. Multisite ensembles are supported using Balsam or Globus Compute. We overview the unique characteristics of libEnsemble as well as current and potential interoperability with other packages in the workflow ecosystem. We highlight libEnsemble’s dynamic resource features: libEnsemble can detect system resources, such as available nodes, cores, and GPUs, and assign these in a portable way. These features allow users to specify the number of processors and GPUs required for each simulation; and resources will be automatically assigned on a wide range of systems, including Frontier, Aurora, and Perlmutter. Such ensembles can include multiple simulation types, some using GPUs and others using only CPUs, sharing nodes for maximum efficiency. We also describe the benefits of libEnsemble’s generator–simulator coupling, which easily exposes to the user the ability to cancel, and portably kill, running simulations based on models that are updated with intermediate simulation output. We demonstrate libEnsemble’s capabilities, scalability, and scientific impact via a Gaussian process surrogate training problem for the longitudinal density profile at the exit of a plasma accelerator stage. In conclusion, the study uses gpCAM for the surrogate model and employs either Wake-T or WarpX simulations, highlighting efficient use of resources that can easily extend to exascale.

Dynamic ensembles↗

Overview of the TCV tokamak program: Scientific progress and facility upgrades

The TCV tokamak is augmenting its unique historical capabilities (strong shaping, strong electron heating) with ion heating, additional electron heating compatible with high densities, and variable divertor geometry, in a multifaceted upgrade program designed to broaden its operational range without sacrificing its fundamental flexibility. The TCV program is rooted in a three-pronged approach aimed at ITER support, explorations towards DEMO, and fundamental research. A 1 MW, tangential neutral beam injector (NBI) was recently installed and promptly extended the TCV parameter range, with record ion temperatures and toroidal rotation velocities and measurable neutral-beam current drive. ITER-relevant scenario development has received particular attention, with strategies aimed at maximizing performance through optimized discharge trajectories to avoid MHD instabilities, such as peeling-ballooning and neoclassical tearing modes. Experiments on exhaust physics have focused particularly on detachment, a necessary step to a DEMO reactor, in a comprehensive set of conventional and advanced divertor concepts. The specific theoretical prediction of an enhanced radiation region between the two X-points in the low-field-side snowflake-minus configuration was experimentally confirmed. Fundamental investigations of the power decay length in the scrape-off layer (SOL) are progressing rapidly, again in widely varying configurations and in both D and He plasmas; in particular, the double decay length in L-mode limited plasmas was found to be replaced by a single length at high SOL resistivity. Experiments on disruption mitigation by massive gas injection and electron-cyclotron resonance heating (ECRH) have begun in earnest, in parallel with studies of runaway electron generation and control, in both stable and disruptive conditions; a quiescent runaway beam carrying the entire electrical current appears to develop in some cases. Developments in plasma control have benefited from progress in individual controller design and have evolved steadily towards controller integration, mostly within an environment supervised by a tokamak profile control simulator. TCV has demonstrated effective wall conditioning with ECRH in He in support of the preparations for JT-60SA operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Using the Model Perennial Grass Brachypodium sylvaticum to Engineer Resistance to Multiple Abiotic Stresses

We are using the perennial model grass Brachypodium sylvaticum to identify combinations of transgenes that enhance tolerance to multiple, simultaneous abiotic stresses. The most successful transgene combinations will ultimately be used to create improved switchgrass (Panicum virgatum L.) cultivars. To further develop B. sylvaticum as a perennial model grass, and facilitate our planned transcriptional profiling, we are sequencing and annotating the genome. We have generated ~40x genome coverage using PacBio sequencing of the largest possible size selected libraries (18, 22, 25 kb). Our initial assembly using only long-read sequence contained 320 Mb of sequence with an N50 contig length of 315 kb and an N95 contig length of 40 kb. This assembly consists of 2,430 contigs, the largest of which was 1.6 Mb. The estimated genome size based on c-values is 340 Mb indicating that about 20 Mb of presumably repetitive DNA remains yet unassembled. Significantly, this assembly is far superior to an assembly created from paired-end short-read sequence, ~100x genome coverage. The short-read-only assembly contained only 226 Mb of sequence in 19k contigs. To aid the assembly of the scaffolds into chromosome-scale assemblies we produced an F2 mapping population and have genotyped 480 individuals using a genotype by sequence approach. One of the reasons for using B. sylvaticum as a model system is to determine if the transgenes adversely affect perenniality and winter hardiness. Toward this goal, we examined the freezing tolerance of wild type B. sylvaticum lines to determine the optimal conditions for testing the freezing tolerance of the transgenics. A survey of seven accessions noted significant natural variation in freezing tolerance. Seedling or adult Ain-1 plants, the line used for transformation, survived an 8 hour challenge down to -6 oC and 50% survived a challenge down to -9 oC. Thus, we will be able to easily determine if the transgenes compromise freezing tolerance. In the effort to develop biotechnological tools for perennial grass improvement, we have completed the transformation of B. sylvaticum with constructs containing 20 genes shown to be associated with enhanced abiotic stress tolerance in monocots. In addition, we have transformed plants with constructs containing a combination of genes (i.e. SARK::IPT- Ubi::HSR1::Ubi::NHX1) in order to simultaneously overexpress genes associated with drought + heat tolerance + salt tolerance. We generated single copy insert T1 lines for all constructs and the generation and bulking of homozygous T2 lines is well underway. In addition to our B. sylvaticum transgenics, we transformed B. distachyon with many of the same genes. Some of the transgenic B. distachyon plants subjected to a combined stress of both drought and salinity were able to produced higher yields than wild type plants. Our results indicate a great potential for the development of grasses with improved performance and yield in water-limited areas.

Gordon, Sean↗

High Radiation Environment Nuclear Fragment Separator Magnet

Superconducting coils wound with HTS conductor can be used in magnets located in a high radiation environment. NbTi and Nb 3 Sn superconductors must operate at 4.5 K or below where removal of heat is less efficient. The HTS conductor can carry significant current at higher temperatures where the Carnot efficiency is significantly more favorable and where the coolant heat capacity is much larger. Using the HTS conductor the magnet can be operated at 40 K. This project examines the use of HTS conductor for the Michigan State University Facility For Rare Isotope Beams (FRIB) fragment separator dipole magnet which bends the beam by 30° and is located in a high radiation region that will not be easily accessible. Two of these magnets are needed to select the chosen isotope. There are a number of technical challenges to be addressed in the design of this magnet. The separator dipole is 2 m long and subtends a large angle. The magnet should keep a constant transverse field profile along its beam reference path. Winding coils with a curved inner segment is difficult as the conductor will tend to unwind during the process. In the Phase I project two approaches to winding the conductor were examined. The first was to wind the coils with curved sections on the inner and outer segments with the inner segment wound with negative curvature. The alternate approach was to use a straight segment on the inner segment to avoid negative curvature. In Phase I coils with a limited number of turns were successfully wound and tested at 77 K for both coil configurations. The Phase II program concentrated on the design, coil winding procedures, structural analysis, prototyping and testing of an HTS curved dipole coil at 40 K with a heat load representative of the radiation environment. One of the key criteria of the design of this magnet is to avoid the use of organic materials that would degrade rapidly in radiation. The Lorentz forces expected from the coils interacting with the magnetic field are large and in order minimize the deformation of the coils, mechanical support must be provided. Since the support structure cannot be made of organic materials with minimal thermal conductivity, an optimization was explored comparing the amount of coil deformation that can be tolerated and the amount of heat leakage that can be endured. A test coil containing 500 m of HTS was constructed to be tested at the 40 K operating temperature. The anticipated heat load was simulated with heater strips to demonstrate that the heat could be removed and that the coil can operate in a stable state. The FRIB project has decided that using HTS coils for this magnet was too risky considering their time and funding constraints and has opted for a more conservative approach with conventional coils. As an outcome of this STTR project, it is likely that HTS coils operating at higher temperatures will have beneficial applications for future accelerator projects.

40 K↗

Lithiophilic V 2 O 5 nanobelt arrays decorated 3D framework hosts for highly stable composite lithium metal anodes

The lithium metal anode has been considered to be an optimal anode material for high-energy-density battery system due to its ultrahigh specific capacity. However, the sharp dendrite growth and infinite volume expansion have significantly impeded its commercial application. In this paper, we propose that V 2 O 5 as the lithiophilic substance can be decorated onto 3D stable frameworks to fabricate dendrite-suppressed composite Li metal anodes via a molten Li infusion method. It is demonstrated that the energetic chemical reaction between V 2 O 5 and molten Li together with the capillary effect based on the nanostructure of interconnected V 2 O 5 nanobelt arrays contributes synergistically to the great Li affinity of the V 2 O 5 -Ni foam (V 2 O 5 -NF) host and facilitate the efficient and uniform intake of molten Li into the 3D framework. Benefitting from the homogeneous Li distribution in the framework, the decreased local current density of the electrode and the stable property of the host, dendrite-free Li stripping/plating behavior and alleviated volume fluctuation have been achieved for the Li-V 2 O 5 -NF composite anode. Compared with the bare Li anode, the as-obtained Li-V 2 O 5 -NF composite anode exhibits much stable stripping/plating profiles with low overpotential (~18 mV) for ultralong lifespan (1600 h) at a current density of 1 mA cm -2 in symmetric Li/Li cell. Furthermore, outstanding rate capability and long-term cycling performance (78.8% capacity retention after 500 cycles under 2 C) are obtained in full cells when coupled with Li 4 Ti 5 O 12 (LTO) cathodes, indicating a promising potential for practical application. Moreover, this work demonstrates that using a new lithiophilic material, V 2 O 5 , should be an effective method to construct high stable 3D Li metal anode for Li metal battery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probabilistic flux limiters

The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular method to virtually eliminate Gibbs oscillations caused by numerical discretization in under-resolved simulations is to use a flux limiter. A wide range of flux limiters have been studied in the literature, with recent interest in their optimization via machine learning methods trained on high-resolution datasets. The common use of flux limiters in numerical codes as plug-and-play blackbox components makes them key targets for design improvement. Even for deterministic dynamical models, numerical uncertainty is introduced via coarse-graining required by insufficient computational power to solve all scales of motion. Conventional flux limiters are deterministic and lack the capacity to address uncertainties, both aleatoric (inherent randomness) and epistemic (modeling uncertainty due to limited knowledge), which arise in coarse-grained numerical simulations. Here, we introduce a conceptually distinct type of flux limiter that is designed to handle the effects of randomness in the model and uncertainty in model parameters. Unlike traditional single-function flux limiters, these new probabilistic flux limiters incorporate multiple flux limiting functions, each applied with a learned probability drawn from high-resolution data to mitigate the effects of uncertainty in numerical simulations. This approach departs from traditional single-function limiters by explicitly modeling and incorporating uncertainty into the shock capturing process. Using the example of Burgers' equation as a testbed, we show that a machine learned, probabilistic flux limiter may be used in a shock capturing code to more accurately capture shock profiles. In particular, we show that our probabilistic flux limiter outperforms standard limiters and can be successively improved upon (up to a point) by expanding the set of probabilistically chosen flux limiting functions.

97 MATHEMATICS AND COMPUTING↗

Computational Fluid Dynamics Simulations to Support Efficiency Improvements in Aluminum Smelting Process

Smelting is broadly described as the extraction of a metal from its ore. In the United States, aluminum is commonly produced by smelting alumina in bauxite using the Hall-Héroult process. Optimization of equipment and processes in conventional smelting is crucial to enhancing process efficiency and productivity, is necessary for improving the techno-economic feasibility, which directly manifests as the growth of the American economy. To achieve optima, insightful data on the multiphysics phenomena that are inherent to the process must be obtained through physical investigation or high-fidelity numerical simulations. The resolution of relevant scales in time and space for smelting operations requires intensive, high-performance computing (HPC) simulations. Hostile operating conditions limit physical data acquisition to specific techniques; therefore, these data do not describe the multiscale interaction of simultaneous effects. Fortunately, in recent decades, significant advancements in computing hardware and computational methods have made the numerical resolution of such a complex process possible. In this study, a high-fidelity simulation of aluminum smelting was performed using an open-source tool, OpenFOAM, which analyzed many parameters characteristic to underlying phenomena. A multiphysics model based on the Eulerian-Eulerian multifluid approach was adopted. This model can resolve critical issues in the electrolytic smelting of aluminum, such as bubbling of carbon dioxide from the anode(s), magnetohydrodynamics from electromagnetic effects, ionic dissolution of the alumina in the electrolyte, and the evolution of thermal profiles. This study provides valuable connectivity for characteristic data that can direct the future designs of efficient smelters. A basic framework to model and simulate the smelting process using OpenFOAM is presented for user modification in keeping with process development. Of relevance to the flow field, a detailed investigation of vortices produced by bubble motion and electromagnetics is discussed, along with their impact on the evolution of thermal profiles. The predictions show small-scale vortices in the clearance between the anode and cathode caused by magnetic forces. Predictions also indicate relatively large-scale vortices in the inter-anode space resulting from carbon dioxide rising through the electrolytic flow field. The formation of vortices at the edges of anodes was shown to direct alumina charged by the feeder to the bottom of the anodes, thus preventing the entrapment of gas bubbles in the periphery of the bottom of the anode. Symmetry was observed in the location of cold spots in the electrolytic mixture in the vicinity of the feeder. Cold spots were also observed in the clearance between the anode and cathode due to the flow’s transmission of unconverted alumina to this region.

36 MATERIALS SCIENCE↗

Diagnosing Near-Surface Model Errors with Candidate Physics Parameterization Schemes for the Multiphysics Rapid Refresh Forecast System (RRFS) Ensemble during Winter over the Northeastern United States and Southern Great Plains

Abstract During the winter of 2020/21 an ensemble of FV3-LAM forecasts was produced over the contiguous United States for the Winter Weather Experiment using five physics suites. These forecasts are evaluated with the goal of optimizing physics parameterizations within the future operational Rapid Refresh Forecast System (RRFS) in the Unified Forecast System (UFS) realm and for selecting suitable physics suites for a multiphysics RRFS ensemble. The five physics suites have different combinations of land surface models (LSMs), planetary boundary layer (PBL) parameterizations, and surface layer schemes, chosen from those used in current and possible future operational systems and likely to be supported in the operational UFS. Full-season evaluation reveals a persistent near-surface cold bias in the U.S. Northeast from one suite and a nighttime warm bias in the southern Great Plains in another suite, while other suites have smaller biases. A representative case is chosen to diagnose the cause for each of these biases using sensitivity simulations with different physics combinations or modified parameters and verified with additional mesonet observations. The cold bias in the Northeast is attributed to aspects of the Noah-MP LSM over snow cover, where Noah-MP simulates lower soil water content, and thus lower thermal conductivity than other LSMs, leading to less upward ground heat flux during nighttime and consequently lower surface temperature. The nighttime warm bias found in the southern Great Plains is attributed to overestimation of vertical mixing in the K -profile-based eddy-diffusivity mass-flux (K-EDMF) PBL scheme and insufficient land–atmospheric coupling from the GFS surface layer scheme over short vegetation. A few key parameters driving these systematic biases are identified.

Meteorology & Atmospheric Sciences↗

SU-E-T-262: Development of An In-House Forward Planning System for Conformal Arc Therapy

Purpose: Conformal radiotherapy with forward planning has many practical advantages (e.g., more uniform target dose) and has been used routinely for stereotactic body radiation therapy (SBRT) and other conventional treatment. This study investigates a forward-planning approach for conformal arc therapy and a dedicated treatment planning system (TPS) for a newly designed cobalt 60 machine with a ring type gantry and a multileaf collimator (MLC). Methods: Conformal arcs were modeled with continuous delivery of treatment fields conformal to the target cross-section. Treatment plans were further optimized by weighting or offsetting beams based on the target-critical structure relationship. CT and structure data of seven previous SBRT patients treated at our center were used for plan evaluation. An in-house forward planning tool was developed to aid the forward planning process. A graphical user interface (GUI) was designed with interactive and automatic adjustment between beam gantry angle and the beam weight. Dose distributions were calculated using our in-house Monte Carlo based TPS. Dose contributions from individual beam angles were summed together with different weight factors, which were continuously optimized until the pre-set dose conformity goal was met. Results: We were able to achieve target coverage and critical structure sparing to meet the required clinical criteria in all studied cases. It should be mentioned that those cases were selected having critical structures not proximal to the target. However, this was usually the case in the majority of SBRT cases especially those involving lung targets. The developed GUI tool was very useful in the forward treatment planning process. Conclusion: Conformal arcs can be used successfully on the new Cobalt 60 modality for the treatment of a sizeable fraction of cancer patients, which can be efficiently planned with our simple forward planning approach.

60 APPLIED LIFE SCIENCES↗

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗

Independent calculation of monitor units for VMAT and SPORT

Purpose: Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT). Methods: The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms. Results: For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation. Conclusions: A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

60 APPLIED LIFE SCIENCES↗