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At least 1,009 records · Page 56

SU-E-J-247: Time Evolution of Radiation-Induced Lung Injury After Stereotactic Proton Therapy

Purpose: Quantitative metrics to assess patient-specific radiation-induced lung injury have the potential to guide individualization of therapy and be early indicators of recurrence. Here we investigate computed tomography (CT) density changes in normal lung after stereotactic Proton Therapy. Methods: Participants in a phase-I clinical trial for stereotactic body radiation therapy (SBRT) with protons are analyzed on a rolling basis. The dataset includes 9 patients with 34 CT images to date. Follow-up images are registered to the planning CT using deformable image registration and the change in CT density is correlated to the dose to examine the time-evolution of Hounsfield Unit (HU) changes after large doses of proton radiation. Results: The lung density observed on the follow-up images increases significantly with dose for all dose levels above 5 Gy(RBE) (p<0.001) for 8/9 patients. The change per unit dose [HU/Gy] varies significantly among the patients, from 0.1 (for the one patient without significant correlation) to 5.7 ΔHU/Gy(RBE). The current population average of ΔHU/Gy(RBE) is 2.1, i.e. a 1 Gy(RBE) increase in dose leads on average to a 2.1 HU increase in CT density. The slope of the dose-response curve is constant for all timepoints investigated (from 3–24+ months). Additionally a pronounced non-linearity in the dose response curve is noted for long follow-up times (>18 months). Conclusion: CT density changes have a robust correlation with proton dose, quantitatively similar to photon dose, and may allow estimation of a patient’s intrinsic radiosensitivity after proton therapy. The stability of the correlation with time however diverges from what is known about CT response after photon irradiation. This could have important implications for clinical decision-making during proton therapy for lung cancer, especially for scheduling of follow-up CT/PET imaging and diagnosis of recurrence.

60 APPLIED LIFE SCIENCES↗

Mechanistic understanding of aging behaviors of critical-material-free Li 4 Ti 5 O 12 //LiNi 0.9 Mn 0.1 O 2 cells with fluorinated carbonate-based electrolytes for safe energy storage with ultra-long life span

Behind-the-meter storage (BTMS) systems - a viable method to minimize potential risk of blackout events and stabilize the grid - require a different type of cost-effective energy storage with excellent safety, ultra-long (>20 years) cycle life and reasonable energy density compared that of electric vehicles. To increase the energy density and reduce the cost of a long-term cyclable lithium-titanate-based cell, it is required to employ a critical-material-free high voltage cathode and an electrolyte with good electrochemical and transport properties. In this report the long-term electrochemical performance and behaviors of selected critical-material-free Li 4 Ti 5 O 12 (LTO)//LiNi 0.9 Mn 0.1 O 2 (LNMO) full cells for BTMS applications are evaluated and analyzed in the optimized voltage range of 1.4-2.7 V at 45 degrees C with different fluorinated carbonate-based electrolytes. The fluoroethylene carbonate (FEC)-based electrolyte cell shows the highest capacity retention of 57.9% and Coulombic efficiency (CE) of 99.96% after 1000 cycles, potentially attributed to a dense, homogenous and less resistive LiF-rich solid-electrolyte interphase (SEI) layer formed on the surface of LTO that may mitigate electrolyte decomposition and maintain relatively low cell impedance during cycling. The 3,3,3-fluoroethylmethyl carbonate (F-EMC)-based electrolyte cell, however, presents the worst performance with lower capacity and a sharp decrease of CE, due to unstable and non-uniform SEI formation and continuous oxidative electrolyte decomposition. This mechanistic understanding of cell aging behaviors and failure mechanisms with detailed analysis of surface chemistry and electrode morphology can guide design of new electrode chemistries and electrolyte formulations for the development of BTMS batteries.

25 ENERGY STORAGE↗

Evaluation of Stream and Wetland Restoration Using UAS-Based Thermal Infrared Mapping

Large-scale wetland restoration often focuses on repairing the hydrologic connections degraded by anthropogenic modifications. Of these hydrologic connections, groundwater discharge is an important target, as these surface water ecosystem control points are important for thermal stability, among other ecosystem services. However, evaluating the effectiveness of the restoration activities on establishing groundwater discharge connection is often difficult over large areas and inaccessible terrain. Unoccupied aircraft systems (UAS) are now routinely used for collecting aerial imagery and creating digital surface models (DSM). Lightweight thermal infrared (TIR) sensors provide another payload option for generation of sub-meter-resolution aerial TIR orthophotos. This technology allows for the rapid and safe survey of groundwater discharge areas. Aerial TIR water-surface data were collected in March 2019 at Tidmarsh Farms, a former commercial cranberry peatland located in coastal Massachusetts, USA (41°54′17″ N 70°34′17″ W), where stream and wetland restoration actions were completed in 2016. Here, we present a 0.4 km2 georeferenced, temperature-calibrated TIR orthophoto of the area. The image represents a mosaic of nearly 900 TIR images captured by UAS in a single morning with a total flight time of 36 min and is supported by a DSM derived from UAS-visible imagery. The survey was conducted in winter to maximize temperature contrast between relatively warm groundwater and colder ambient surface environment; lower-density groundwater rises above cool surface waters and thus can be imaged by a UAS. The resulting TIR orthomosaic shows fine detail of seepage distribution and downstream influence along the several restored channel forms, which was an objective of the ecological restoration design. The restored stream channel has increased connectivity to peatland groundwater discharge, reducing the ecosystem thermal stressors. Such aerial techniques can be used to guide ecological restoration design and assess post-restoration outcomes, especially in settings where ecosystem structure and function is governed by groundwater and surface water interaction.

54 ENVIRONMENTAL SCIENCES↗

Searching for Grid-Forming Technologies That Do Not Impact Protection Systems: A promising technology

The design of legacy-line protection elements has been guided by the behavior of synchronous machines during faults. Because of the significant field-winding inductance and rotating mass, the magnitude, angular frequency, and phase angle of the back-electromotive force (EMF) voltage waveforms of synchronous machines remain practically constant for several hundreds of milliseconds after a fault occurs. Furthermore this has facilitated the engineering of the memory-polarization technique in mho distance elements, which has been effective for machine-dominant power grids. However, this assumption is no longer held for inverter-based resources (IBRs) because of the lack of field winding and moment of inertia in power electronics devices. Notably, the negative-sequence directional overcurrent protection and the quadrilateral distance elements have been impacted by early IBRs with grid-following (GFL) controls because they did not inject negative-sequence currents during asymmetrical faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rapid Aero Modeling for Urban Air Mobility Aircraft in Computational Experiments

Rapid Aero Modeling (RAM) applied to computational testing, RAM-C, is an approach to efficiently and automatically obtain aerodynamic models during computational investigations. RAM-C is designed to estimate models appropriate for flight dynamics studies and simulations. The approach responds to a demand for experimental efficiency and model fidelity that has increased with growing aircraft complexity and aerodynamic nonlinearities associated with hybrid and electric vertical takeoff and landing (eVTOL) aircraft. In an Urban Air Mobility (UAM) transportation system, it is expected that aircraft will embrace many features from both airplanes and rotorcraft. These vehicles present many more factors than conventional aircraft which can lead to increased computational costs and missed key factor interactions when applying traditional testing and modeling methods. RAM-C provides feedback loops around computational codes to rapidly guide testing toward aerodynamic models meeting user-defined fidelity goals. It combines and extends concepts from design of experiment theory and aircraft system identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity in terms of prediction error. RAM-C only collects enough data required to meet the user-specified prediction error requirements thus saving computational time and resources. The overall achievable fidelity of the final model also depends on the accuracy of the test facility, or in this case, the computational modeling approach. Previous studies to support development of the RAM-T process were conducted in wind tunnel tests to assess potential metrics, algorithms, and procedures. This paper presents results from the next steps taken and tests conducted for the development of RAM-C technology and highlights some of the unique features of RAM applied eVTOL configurations in a computational study.

Aerodynamics↗

Kinetic and thermodynamic properties of a convecting plasma in a two-dimensional dipole field

Charged particle guiding center motion is considered in the magnetic field of a two-dimensional ('line') dipole on which is superimposed a small, static, perpendicular electric field. The parallel equation of motion is that of a simple harmonic oscillator for cos theta, the cosine of magnetic colatitude theta. Equations for the perpendicular electric and magnetic drifts are derived as well as their bounce-averaged forms. The latter are solved to yield a bounce-averaged guiding center trajectory, which is the same as that obtained from conversation of magnetic moment mu, longitudinal invariant J, and total (kinetic plus electrostatic) energy K. The algebraic simplicity of the trajectory equations is also manifest in the forms of the invariants. An interesting result is that guiding centers drift in such a way that they preserve the values of their equatorial pitch angles and (equivalently) mirror latitudes. The most general Maxwellian form of the equilibrium one-particle distribution function f is constructed from the invariants, and spatially varying density and pressure moments, parallel and perpendicular to the magnetic field, are identified. Much of the paper deals with the more restricted problem in which f is specified as a bi-Maxwellian over a straight line of finite length in the equatorial plane of the dipole and perpendicular to field lines. This might be thought of as specifying a cross-tail ion injection source; our formalism then describes the subsequent spatial development. The distribution away from the source is a scaled bi-Maxwellian but one that is cut off at large and small kinetic energies, which depend on position. Density and pressure components are reduced from the values they would have if the total content of individual flux tubes convected intact. The equatorial and meridional variations of density and pressure components are examined and compared systematically for the isotropic and highly anisotropic situations. There appears to be little qualitative difference due to anisotropy. An anisotropy measure is defined, and its spatial variation determined as a signature of possible MHD instability. Extreme values are found, larger than at the source, but the plasma beta in such regions is probably so low as to render the effect inconsequential energetically. Finally, the possible consequence of 'nonadia- batic' pressure profiles on electrostatic interchanges is considered, and a boundary delineating stabilizing and destabilizing regions determined.

Huang, T. S.↗

High-power non-perturbative laser delivery diagnostics at the final focus of 100-TW-class laser pulses

Controlling the delivery of multi-terawatt and petawatt laser pulses to final focus, both in position and angle, is critical to many laser applications such as optical guiding, laser–plasma acceleration, and laser-produced secondary radiation. We present an online, non-destructive laser diagnostic, capable of measuring the transverse position and pointing angle at focus. The diagnostic is based on a unique double-surface-coated wedged-mirror design for the final steering optic in the laser line, producing a witness beam highly correlated with the main beam. By propagating low-power kilohertz pulses to focus, we observed spectra of focus position and pointing angle fluctuations dominated by frequencies below 70 Hz. The setup was also used to characterize the excellent position and pointing angle correlation of the 1 Hz high-power laser pulses to this low-power kilohertz pulse train, opening a promising path to fast non-perturbative feedback concepts even on few-hertz-class high-power laser systems.

47 OTHER INSTRUMENTATION↗

Modelling pulsed field magnetization of iron-based bulk superconductors

Abstract Bulk superconductors can be used as super-strength quasi-permanent magnets capable of providing magnetic flux densities considerably superior to conventional permanent magnets. This makes them attractive for several engineering applications that rely on strong magnetic fields like rotating machines, NMR/MRI and magnetic drug delivery systems. Recently, the authors reported a record trapped magnetic field in an iron-based bulk superconductor: 2.83 T was trapped in potassium-doped barium iron arsenide (Ba, K)Fe 2 As 2 (or Ba122) at 5 K. Of particular significance is that the strength and temporal stability of this magnetic field exceeds the requirements of MRI machines, indicating iron-based bulks can now perform at levels demanded by engineering applications. One crucial challenge for their practical use, however, is the need to apply and remove an external magnetic field to magnetize them. Pulsed field magnetization (PFM) shows great promise as a practical method of magnetizing bulks, but the process generates heat in the bulk that is detrimental to its superconducting performance and ability to act as a super-strength magnet. In this paper, coupled electromagnetic–thermal numerical models are used to simulate the PFM of iron-based bulk superconductors. Here we focus on the recent-record-breaking, fine-grain polycrystalline K-doped Ba122 bulks. The impact that the specific J c ( B ) characteristics and thermal properties of the Ba122 material—all of which have been experimentally measured from state-of-the-art samples—have on the magnetic flux dynamics and thermal behaviour during PFM, including the final trapped field, is investigated. We show that because the thermal properties are similar to those of REBa 2 Cu 3 O 7 −δ bulks, a similar response to pulsed fields is obtained. A maximum trapped field of ∼0.81 T (∼43.3% of the maximum trapped field capability under ideal, field-cooling conditions) was simulated at 5 K, with a magnetization efficiency of ∼54%. The modelling framework provides a fast and flexible tool for optimising the practical PFM process at different operating temperatures to maximise the trapped field in state-of-the-art Ba122 bulks and to guide the design of future experiments.

bulk superconductors↗

A 3D Lithiophilic Mo 2 N–Modified Carbon Nanofiber Architecture for Dendrite–Free Lithium–Metal Anodes in a Full Cell

The pursuit for high-energy-density batteries has inspired the resurgence of metallic lithium (Li) as a promising anode, yet its practical viability is restricted by the uncontrollable Li dendrite growth and huge volume changes during repeated cycling. Herein, a new 3D framework configured with Mo 2 N-mofidied carbon nanofiber (CNF) architecture is established as a Li host via a facile fabrication method. The lithiophilic Mo 2 N acts as a homogeneously pre-planted seed with ultralow Li nucleation overpotential, thus spatially guiding a uniform Li nucleation and deposition in the matrix. The conductive CNF skeleton effectively homogenizes the current distribution and Li-ion flux, further suppressing Li-dendrite formation. As a result, the 3D hybrid Mo 2 N@CNF structure facilitates a dendrite-free morphology with greatly alleviated volume expansion, delivering a significantly improved Coulombic efficiency of ≈99.2% over 150 cycles at 4 mA cm –2 . Symmetric cells with Mo 2 N@CNF substrates stably operate over 1500 h at 6 mA cm –2 for 6 mA h cm –2 . Furthermore, full cells paired with LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC811) cathodes in conventional carbonate electrolytes achieve a remarkable capacity retention of 90% over 150 cycles. Finally, this work sheds new light on the facile design of 3D lithiophilic hosts for dendrite-free lithium-metal anodes.

25 ENERGY STORAGE↗

Test and Validate Distributed Coaxial Cable Sensors for in situ Condition Monitoring of Coal-Fired Boiler Tubes

This project aims to test, validate, and advance the technology readiness level (from TRL5 to TRL7) of a novel low-cost distributed stainless-steel/ceramic coaxial cable sensing (SSC-CCS) technology for in situ monitoring of the boiler tube temperature in existing coal-fired power plants. The novel SSC-CCS sensing technology and associated condition-based monitoring (CBM) software to be demonstrated in this project will lead to an improved understanding of the boiler tube failure mechanisms and a prognostic system to improve the overall performance, reliability, and flexibility of the nation’s coal-fired power plant fleet. A boiler tube monitoring system with distributed coaxial cable temperature sensors and a sensor acquisition system was constructed. The high-temperature coaxial cable sensor with a length of 1.3m was made by using a quartz tube (1mm inner diameter (ID) and 6mm outer diameter (OD)) to concentrically separate a 304 stainless-steel (SS) rod (1mm OD) and SS tube (7.94mm OD and 6.16mm ID). The sensor acquisition system includes a vector network analyzer (VNA), a radio frequency (RF) power amplifier, multiple switches and a USB hub. The distributed stainless-steel quartz coaxial cable sensor (SSQ-CCS) had a linear response to temperature with a resolution uncertainty of σ = 0.77℃. To withstand the harsh conditions of 3,300 steam pressures and 800℃ high temperatures, the sensor was shielded by a protective tube made of the same material as the boiler tube. The protection tube had an OD of 1.5 inches and a thickness of 0.25 inches. In the laboratory tests, the sensor showed good sensitivity and fast response. The drift was bounded between +0.33% and -0.67% during a test at 600℃ for 350 hours, indicating good stability of the sensor. A field test was conducted where four sensors were welded on four superheat tubes (SH-Ts) at a coal-fired power station over 400 days. Conventional thermocouples were welded to the superheater tubes alongside the coaxial cable sensors for the purpose of comparison. Two sensors were capable of distributed sensing, with three multiplexed sensing sections. The other two sensors were single section. During the 400-day test period, the power plant experienced startups and shutdowns. At the steady state operations, the temperature of the boiler tube is about 600℃ (1112°F). The sensors recorded the entire coal-firing processes (start-up, steady state, and shut-down) and the glitch event. A GSM modem and a Watchdog were added to the system to ensure reliable data recording. The GSM modem sent daily messages to plant managers and Clemson team to inform the status of the sensor system. If the system was not normally working, the Watchdog would reboot the system automatically. The new coaxial cable based distributed sensing technology has been proven to be successful in both laboratory and field tests. A comprehensive four-stage multi-physics computational framework has been developed to assist the design, optimization, installation, and operation of SSQ-CCS. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. A conditional-based monitoring system is implemented as well. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

01 COAL, LIGNITE, AND PEAT↗

SU-F-J-136: Impact of Audiovisual Biofeedback On Interfraction Motion Over a Course of Liver Cancer Stereotactic Body Radiotherapy

Purpose: In abdominal radiotherapy inconsistent interfraction respiratory motion can result in deviations during treatment from what was planned in terms of target position and motion. Audiovisual biofeedback (AVB) is an interactive respiratory guide that produces a guiding interface that the patient follows over a course of radiotherapy to facilitate regular respiratory motion. This study assessed the impact of AVB on interfraction motion consistency over a course of liver cancer SBRT. Methods: Five liver cancer patients have been recruited into this study, 3 followed AVB over their course of SBRT and 2 were free breathing (FB). Respiratory signals from the Varian RPM were obtained during 4DCT and each treatment fraction. Respiratory signals were organized into 10 respiratory bins, and interfraction consistency was quantified by the difference between each treatment fraction respiratory bin and each respiratory bin from 4DCT. Interfraction consistency was considered as both the relative difference (as a percentage) and absolute difference (in centimeters) between treatment respiratory bins and 4DCT respiratory bins. Results: The relative difference between 4DCT and treatment respiratory bins was 22 ± 16% for FB, and 15 ± 10% for AVB, an improvement of 32% (p < 0.001) with AVB. The absolute difference between 4DCT and treatment respiratory bins was 0.15 ± 0.10 cm for FB, and 0.14 ± 0.13 cm for AVB, an improvement of 4% (p = 0.6) with AVB. Conclusion: This was the first study to compare the impact of AVB breathing guidance on interfraction motion consistency over a course of radiotherapy. AVB demonstrated to significantly reduce the relative difference between 4DCT and treatment respiratory motion, but the absolute differences were comparable, largely due to one AVB patient exhibiting a larger amplitude than the other patients. This study demonstrates the potential benefit of AVB in reducing motion variations during treatment from what was planned. Paul Keall, Sean Pollock, Ricky OBrien and Kuldeep Makhija are shareholders of Respiratory Innovations, an Australian company that is developing a device to improve breathing stability. No funding or support was provided by Respiratory Innovations. Paul Keall is one of the inventors of US patent # 7955270.

60 APPLIED LIFE SCIENCES↗

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗

Reducing Non-Radiative Recombination in Perovskite Solar Cells with a SiO2-Graphene Oxide Buried Interface Layer

Perovskite solar cells (PSCs) have emerged as a transformative photovoltaic technology. However, the device performance of inverted PSCs is dramatically limited by surface defects and the underlying film morphology of metal halide perovskite (MHP) thin film. Herein, we report a novel buried interface layer consisting of SiO2 nanoparticles (NPs) chemically bonded to graphene oxide (GO), deposited atop a hydrophobic hole extraction layer (HEL) to address this limitation. The SiO2 NPs serve as insoluble scaffolds that immobilize GO sheets on the hydrophobic HEL surface, enabling the formation of homogeneous MHP thin films. Meanwhile, the GO functional groups interact with surface-uncoordinated Pb2+, suppressing interfacial defects and guiding crystal grain growth of the resultant MHP thin films. This synergistic effect suppresses non-radiative charge recombination and enhances charge extraction efficiency. As a result, a 26.07% efficiency with significantly suppressed photocurrent hysteresis is observed from PSCs incorporating the SiO2-GO buried interface layer. Moreover, the above PSCs maintain 92% of their initial PCE after 1800 h of continuous operation at the maximum power point under AM 1.5 G (100 mW/cm2) illumination at 25 degrees C in air with 50-60% relative humidity. These results demonstrate that we have developed a facile and effective way to realize high-performance inverted PSCs.

14 SOLAR ENERGY↗

Guiding Principles for Geochemical/Thermodynamic Model Development and Validation in Nuclear Waste Disposal: A Close Examination of Recent Thermodynamic Models for H + —Nd 3+ —NO 3 - (—Oxalate) Systems

Development of a defensible source-term model (STM), usually a thermodynamical model for radionuclide solubility calculations, is critical to a performance assessment (PA) of a geologic repository for nuclear waste disposal. Such a model is generally subjected to rigorous regulatory scrutiny. In this article, we highlight key guiding principles for STM model development and validation in nuclear waste management. We illustrate these principles by closely examining three recently developed thermodynamic models with the Pitzer formulism for aqueous H + —Nd 3+ —NO 3 - (—oxalate) systems in a reverse alphabetical order of the authors: the XW model developed by Xiong and Wang, the OWC model developed by Oakes et al., and the GLC model developed by Guignot et al., among which the XW model deals with trace activity coefficients for Nd(III), while the OWC and GLC models are for concentrated Nd(NO 3 ) 3 electrolyte solutions. The principles highlighted include the following: (1) Principle 1. Validation against independent experimental data: A model should be validated against experimental data or field observations that have not been used in the original model parameterization. We tested the XW model against multiple independent experimental data sets including electromotive force (EMF), solubility, water vapor, and water activity measurements. The results show that the XW model is accurate and valid for its intended use for predicting trace activity coefficients and therefore Nd solubility in repository environments. (2) Principle 2. Testing for relevant and sensitive variables: Solution pH is such a variable for an STM and easily acquirable. All three models are checked for their ability to predict pH conditions in Nd(NO 3 ) 3 electrolyte solutions. The OWC model fails to provide a reasonable estimate for solution pH conditions, thus casting serious doubt on its validity for a source-term calculation. In contrast, both the XW and GLC models predict close-to-neutral pH values, in agreement with experimental measurements. (3) Principle 3. Honoring physical constraints: Upon close examination, it is found that the Nd(III)-NO 3 association schema in the OWC model suffers from two shortcomings. Firstly, its second stepwise stability constant for Nd(NO 3 ) 2+ (log K 2 ) is much higher than the first stepwise stability constant for NdNO 3 2+ (log K 1 ), thus violating the general rule of (log K 2 –log K 1 ) < 0, or $\frac{K1}{K2}$>1. Secondly, the OWC model predicts abnormally high activity coefficients for Nd(NO 3 ) 2 + (up to ~900) as the concentration increases. (4) Principle 4. Minimizing degrees of freedom for model fitting: The OWC model with nine fitted parameters is compared with the GLC model with five fitted parameters, as both models apply to the concentrated region for Nd(NO 3 ) 3 electrolyte solutions. The latter appears superior to the former because the latter can fit osmotic coefficient data equally well with fewer model parameters. The work presented here thus illustrates the salient points of geochemical model development, selection, and validation in nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High-fidelity multiphysics load following and accidental transient modeling of microreactors using NEAMS tools: Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts

The feasibility of modeling microreactors using high-fidelity models with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) tools is investigated in this report. Three overarching questions guided this research: can NEAMS tools readily be applied for high-fidelity multiphysics modeling of different types of transients in microreactor designs; how accurate are the results obtained; and are improvements needed in accuracy or user experience of NEAMS tools, especially considering newly developed capabilities? This work builds upon FY-2022 work, and two microreactor concepts considering heat pipe (HP-MR) and gas-cooled (GC-MR) technologies were further analyzed using high-fidelity multiphysics simulations. The NEAMS tools considered and coupled within the MultiApp environment are Griffin for neutronics, BISON for thermo-mechanics, Sockeye for heat pipe modeling (in HP-MR), SAM for 1D Fluid – 3D solid modeling of coolant channels and system modeling of balance of plant components (in GC-MR), and the SWIFT code for hydrogen redistribution in hydride moderator. The Heat Pipe MicroReactor (HP-MR) concept was further analyzed in FY-2023 to demonstrate the stochastic TRISO failure modeling capability in BISON to check operational limits of the TRISO fuel. A new full-core Gas-Cooled MicroReactor (GC-MR) model was developed based on the initial assembly-model used in Y-2022 and used for steady-state and accidental depressurization transient simulations. Accuracy of the simulations performed was assessed through 1) verification analyses completed on the different physics with code-to-code comparison, and 2) validation of the multiphysics simulations based on modeling of the Kilopower Reactor Using Stirling Technology (KRUSTY) experiment. In FY-2023, the mesh and model of KRUSTY was updated to closely match publicly available data, and the neutronic model was verified and validated against experimental control rod worth measurements. The multiphysics model of KRUSTY was developed and used for steady-state analysis and for modeling reactivity insertion transient. The calculated power increase and stabilization agrees well with experimental data following adjustment in fuel thermal expansion coefficient. As an important component of this project, the ANL team gathered experience with a wide range of NEAMS tools: the MOOSE Mesh System, Griffin, BISON, SWIFT, Sockeye, SAM, Workbench, and the MOOSE MultiApp System, and provided assessment of new capabilities. Noteworthy are the user assessment of the “vapor-only” flow model in Sockeye and development of a multiphysics startup transient in HP-MR unit cell for use as tutorial in Sockeye. The full-core GC-MR model was used for assessment of SAM for balance of plant modeling and for demonstrating the SWIFT code capability for hydrogen redistribution modeling in multiphysics transient analyses. In this process, several bugs/issues were identified and reported to developers. Finally, the assembly GC-MR model developed in FY-2022 coupling Griffin, BISON and SAM through flow blockage and rod ejection transients was published to the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB). The Heat Pipe MicroReactor (HP-MR) concept high-fidelity multiphysics coupling of Griffin/BISON/Sockeye in load-following and heat pipe failure transients was also published on the VTB. Those submissions are enabling thorough review of these models as well as wide distribution to industry, regulator, and university users. In this analysis, several new research questions were uncovered, and follow-up analyses are recommended to further improve some models, consider additional transients, and continue development of VTB models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Radial density profile and stability of capillary discharge plasma waveguides of lengths up to 40 cm

We measured the parameter reproducibility and radial electron density profile of capillary discharge waveguides with diameters of 650 μm to 2 mm and lengths of 9 to 40 cm. To the best of the authors’ knowledge, 40 cm is the longest discharge capillary plasma waveguide to date. This length is important for ≥10 GeV electron energy gain in a single laser-driven plasma wakefield acceleration stage. Evaluation of waveguide parameter variations showed that their focusing strength was stable and reproducible to <0.2% and their average on-axis plasma electron density to <1%. These variations explain only a small fraction of laser-driven plasma wakefield acceleration electron bunch variations observed in experiments to date. Measurements of laser pulse centroid oscillations revealed that the radial channel profile rises faster than parabolic and is in excellent agreement with magnetohydrodynamic simulation results. We show that the effects of non-parabolic contributions on Gaussian pulse propagation were negligible when the pulse was approximately matched to the channel. However, they affected pulse propagation for a non-matched configuration in which the waveguide was used as a plasma telescope to change the focused laser pulse spot size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Charting the relationship between phase type-surface area-interactions between the constituent atoms and oxygen reduction activity of Pd–Cu nanocatalysts inside fuel cells by in operando high-energy X-ray diffraction

The activity and stability of nanoalloy catalysts for chemical reactions driving devices for clean energy conversion, in particular the oxygen reduction reaction (ORR), depend critically on optimizing major structural characteristics of the nanoalloys, such as the phase composition, surface area and bonding interactions between the constituent atoms, for the harsh operating conditions inside the devices. The effort requires good knowledge of the potential effect of changes in these characteristics on the catalytic functionality of the nanoalloys and, hence, on the devices' performance. We present the results from an in operando high-energy X-ray diffraction (HE-XRD) study on the concurrent changes in the structural characteristics and ORR activity of Pd–Cu nanoalloy catalysts as they function at the cathode of a proton exchange membrane fuel cell (PEMFC). We find that the as-prepared Pd–Cu nanoalloys with a chemical composition close to Pd1Cu1 are better ORR catalysts in comparison with Pd1Cu2, i.e. Pd-poor, and Pd3Cu1, i.e. Pd-rich, nanoalloys. Under operating conditions though, the former suffers a big loss in ORR activity appearing as a slow-mode oscillation in the current output of the PEMFC. Losses in ORR activity suffered by the latter also exhibit sudden drops and rises during the PEMFC operation. Through atomic pair distribution function (PDF) analysis of the in operando HE-XRD data, we identify the structural changes of Pd–Cu alloy NPs that are behind the peculiar decay of their ORR activity. The results uncover the instant link between the ever-adapting structural state of ORR nanocatalysts inside an operating PEMFC and the performance of the PEMFC. Besides, our results indicate that, among others, taking control over the intra-particle diffusion of metallic species in nanoalloy catalysts may improve the performance of PEMFCs significantly and, furthermore, in operando HE-XRD can be an effective tool to guide the effort. Finally, we argue that, though showing less optimal ORR activity in the as-prepared state, monophase Pd–Cu alloy catalysts with a composition ranging between Pd1Cu1 and Pd3Cu1 may deliver optimal performance inside operating PEMFCs.

Maswadeh, Yazan↗

Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗