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At least 307 records · Page 17

Self-driving thin film laboratory: autonomous epitaxial atomic-layer synthesis via real-time computer vision analysis of electron diffraction

Emerging materials science platforms with the ability to make autonomous decisions on the fly are fundamentally changing the outlook and protocols for materials optimization and discovery. Because AI-driven self-navigating schemes can effectively reduce the total number of iterations needed to arrive at the "answer" (i.e. the best stochiometric composition for a desired physical property, optimum materials processing parameters, etc.) by significant margins, they have the potential to revolutionize materials and chemical manufacturing processes at large in research laboratory settings as well as in industrial plants. Here, we demonstrate a successful implementation of real-time closed-loop autonomous navigation of a multi-dimensional materials synthesis parameter space for fabricating phase-pure epitaxial films of a metastable phase of a functional oxide in a combinatorial pulsed laser deposition chamber. Sequential epitaxial growth iterations in search of the optimized recipe to stabilize the desired crystal phase were performed using frame-by-frame quantitative computer vision analysis of reflection high-energy electron diffraction (RHEED) images of the unit-cell level film being deposited. The autonomous scheme regularly resulted in > 30-fold reduction in the number of required experiments compared to a comprehensive mapping of the parameter space. The real-time workflow developed here can be readily extended to a variety of thin film synthesis platforms opening the door for self-driving atomic-level materials design as well as autonomous optimization of semiconductor manufacturing.

36 MATERIALS SCIENCE↗

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the above-mentioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

54 ENVIRONMENTAL SCIENCES↗

Out-of-Pile Testing and Instrumentation Transient Water Irradiation System

Current initiatives to increase the burnup of conventional nuclear fuels past the approximate 62 GWd/t limit have been spurred on by direct savings to refueling and waste storage. The technical justification for a new license limit requires extensive qualification through experimental testing. Unlike beginning-of-life fuels, high-burnup fuels are more susceptible to fuel fragmentation, relocation, and dispersal (FFRD), therefore more data is needed to characterize fuels under key accident scenarios. The Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory has developed a testing apparatus architecture to test fuels and claddings at prototypic conditions. The Transient Water Irradiation System (TWIST) is the latest iteration of a testing device capable of conducting loss of coolant accidents (LOCAs) in TREAT. The Out-of-Pile Testing and Instrumentation TWIST (OPTI-TWIST) is an electrically heated device that is analogous to TWIST. OPTI-TWIST allows for detailed instrumentation and thermal-hydraulic characterization. TWIST ultimately aims to conduct the most advanced in-situ diagnostics to evaluate FFRD in a prototypic LOCA. Moreover, it will explore the phenomenological bifurcation of a decay-energy heat up driven LOCA and a stored-energy heat up driven LOCA. The instrumentation suite includes conventional thermocouples and pressure transducers in addition to an electro impedance sensor, an acoustic emission sensor, an optical pressure sensor, and an optical pyrometer. Characterizing these instruments in OPTI-TWIST eliminates complications of irradiation effects while preserving extreme thermal-hydraulic conditions. Finally, benchmarking both devices to a thermal-hydraulic code like the Reactor Excursion and Leak Analysis Program (RELAP)5-3D provides a unique opportunity for iteration. Pre-test predictions and post-test interpretations inform the physical designs, operational procedures, test conditions, and instrumentation types and positions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗

Angular Distribution of Dimuons from Drell-Yan Production in p+Fe Interactions at 120 GeV Beam Energy

In the E906/SeaQuest Fermilab experiment, we report a measurement of the angular distributions by measuring the angular parameters $\lambda$, $\mu$, and $\nu$ of Drell-Yan dimuons produced using a 120 GeV proton beam incident on an iron target. The angular distribution in the naive Drell-Yan model does not show any $\cos2\phi$ dependency, where $\phi$ denotes the azimuthal angle of dimuons in the Collins-Soper frame. However, pion-induced Drell-Yan experiments, such as NA10 and E615, have observed a significant dependence on $\cos2\phi$. The Boer–Mulders function, a transverse momentum-dependent distribution function, represents the correlation between the transverse spin and the transverse momentum of the quark. A non-zero Boer-Mulders function or an improved higher-order Drell-Yan model considering QCD effects can produce a $\cos 2\phi$ modulation in the Drell-Yan angular distribution. To measure the angular distributions, we have used an event mixing method to construct the combin atorial background, which was then subtracted from the data to isolate the Drell-Yan signal. Following this, we corrected the detector, trigger, and reconstruction efficiencies using a doubly-iterative Bayesian Unfolding method. This iterative unfolding technique improves the response matrix based on the results of the previous unfolding step, ensuring robust convergence without exaggeration of uncertainties. The angular distributions of the dimuons were measured over the invariant mass range $5.0 < M_{\mu^+ \mu^-} < 8.0$ $GeV/c^2$, with dimuon transverse momentum $P_T < 2$ GeV/c and Feynman-x $-0.18 < x_F < 0.9$. The measured angular distributions are then compared with the QCD calculations for $p + \text{Fe}$ interactions, and proton-induced angular distribution measurements from other experiments. We have observed weak $\cos 2\phi$ modulations as a function of $P_T$. For $P_T > 1.0 \, \text{GeV}/c$, the predicted NNLO perturbative QCD value of $\nu$ is larger than what we have me asured at E906/SeaQuest. Moreover, we have not observed a strong dependence of $\nu$ on the kinematic variables, such as dimuon mass $M_{\mu^+ \mu^-}$ and Bjorken-$x$. The spin alignment of the virtual photon, $\lambda$, measured from the SeaQuest Drell-Yan $p+\text{Fe}$ data, is found to be strongly dependent on $P_T$, decreasing as $P_T$ increases. $\lambda$ also holds to the upper bound condition $\lambda < 1.0$ within the statistical uncertainty, showing a trend similar to that predicted by NNLO perturbative QCD. However, for $1.0 < P_T < 2.0 \, \text{GeV}/c$, the extracted $\lambda$ value from SeaQuest is smaller than that predicted by perturbative QCD at NNLO.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the Pion Exclusive Electro-Production Cross-Section in the E12-19-006 Experiment in Hall-C at Jefferson Lab

One of the most effective methods for exploring the transition from hadronic degrees of freedom to quark-gluon degrees of freedom in Quantum Chromodynamics (QCD) is through the investigation of \exclusive" pion and kaon electro-production reactions at various Q2 and ?t values. The E12-19-006 experiment is conducted within the confi?nes of experimental Hall C at the Thomas Jefferson National Accelerator Facility, USA, for such studies. The primary aim of the experiment is to ?first enhance our comprehension of the pion electro-production cross-section and its form factor at Q2 = 0.38 and 0.42 GeV2. This is the fi?rst run period of the E12-19-006 experiment which ran in summer 2019. A more profound understanding of the pion electro-production reaction, 1H(e,e'?+)n, at low Q2 is deemed essential to employ this electro-production reaction (an indirect technique) for the high Q2 studies, thereby delving deeper into the realm of QCD. Consequently, this dissertation presents a thorough analysis of the experimental data acquired in the ?first run period of the E12-19-006 experiment. In pursuit of precision, a series of systematic studies (target boiling correction study, the elastic reaction cross-section measurements, study for determining vari- ous kinematics o?sets, etc.) are conducted to discern the accuracy of the analyzed data, a prerequisite for the use of Rosenbluth separation technique to separate the pion electro-production cross-section terms in t bins. The separated pion electro-production cross-section through the Rosenbluth separation technique is then used to extract the pion electromagnetic form factor. In this dissertation, the pion electro-production cross-section is carefully dissected into its four constituent components: longitudinal (?L), transverse (?T ), longitudinal-transverse (?LT ), and transverse-transverse (?TT ), using the full version of Rosenbluth separation technique for the Q2 = 0.38 GeV2. The technique is simultaneously fi?tted to the unseparated pion electro-production cross-sections at the three values of polarization of the virtual photon (?), i.e., ? = 0.286, 0.629 and 0.781. An iterative process is applied to re?ne the parameters of the model cross-sections until the yield ratio of experimental and Monte Carlo simulation converges. In this study, 21 iterations are conducted to re?ne the model cross-section parameters. The fi?nal pion electro-production cross-section terms are then determined for 7 t bins using the optimized parameters of the model cross-sections.

Kumar, Vijay↗

Detailed Characterization of CZT Detector Response for Improved Coded-Aperture Imaging Performance

Gamma-ray imaging is a powerful method for locating and quantifying sources of radiation. The coded-aperture technique demonstrates superior angular resolution in comparison to other methods (e.g., Compton reconstruction). In this method, a mask constructed of highly attenuating material encodes the scene as a shadow pattern on a position-sensitive detector; this pattern can then be used to recreate the origin(s) of incident radiation. This is typically done through convolution of the mask and shadow patterns. Iterative methods which attempt to reconstruct the observed shadow pattern using a weighted combination of simulated patterns may also be employed. In either case, errors in event position reconstruction due to detector imperfections alter the shadow pattern and will therefore degrade system performance and may introduce imaging artifacts. These effects can be mitigated with a detailed understanding of such errors – allowing for the generation of representative simulations that include the errors and/or correction of raw imager data to remove the errors. We present a calibration process for a commercially available cadmium zinc telluride (CZT) gamma imager which provides a comprehensive characterization of the spatial and energy dependence of event reconstruction. By illuminating a mask featuring a regular grid of pinholes with a calibration source, the localized response of the detector can be measured with fine granularity. These local responses are combined to generate a full detector response map which can be used to distort simulations in a manner that is representative of the observed detector data. Details of the calibration procedure and an assessment of the impact of its end products on the performance of iterative imaging methods will be presented.

Ziock, Klaus-Peter↗

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗

DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving

Time-Independent Differential Equations (TIDEs) are central to modeling equilibrium behavior across a wide range of scientific and engineering domains, from electrostatics to porous media flow. Conventional numerical solvers offer reliable solutions but incur significant computational costs due to fine-grained discretization and iterative procedures. Machine learning-based approaches address this by replacing iterative solving processes with one-time inference; however, their sophisticated models require extensive training resources that often exceed those of traditional solvers. Consequently, designing a TIDE solver that achieves high accuracy, broad applicability, and exceptional computational efficiency remains a fundamental challenge. In this paper, we propose DS-TIDE, a novel hardware solver that is inspired by, and subsequently leverages, the intrinsic connection between Dynamical Systems (DS) and Differential Equations (DEs) to efficiently and accurately solve TIDEs. DS-TIDE employs a CMOS-compatible DS-based processor, whose physical states evolve under carefully designed DE-driven dynamics and naturally converge to equilibrium -- the solution of the target TIDE -- within ~1µs on a ~1-watt DS-TIDE processor. To enhance expressivity, DS-TIDE incorporates Heterogeneous Dynamics with Temporal Layering (HDTL), which solves TIDEs through a three-stage DS evolution -- conditioning, solving, and decoding -- each governed by specialized dynamics. The entire evolution process is analogous to an infinitely deep neural network temporally unrolled, offering the system the capability of representing complex equations. Furthermore, DS-TIDE is equipped with an on-device DS-DE Auto-Alignment mechanism that dynamically adapts intrinsic hardware dynamics within milliseconds, effectively aligning the system’s dynamics to diverse target DEs. Experimental results across TIDEs from a wide range of scientific and engineering domains demonstrate that DS-TIDE achieves ~10^3× speedup, ~10^5× energy savings, and competitive or superior accuracy compared to state-of-the-art numerical and ML-based solvers.

Liu, Chuan↗

Neural-Network Inverse Design of SRF Cavities and Transmons for Bosonic Quantum Computation

Three-dimensional superconducting radio-frequency (SRF) cavities provide exceptionally long-lived electromagnetic modes and, when coupled to nonlinear elements such as transmon qubits, become promising architectures for bosonic quantum information processing. The inverse design of such systems, i.e., recovering device geometries that produce specified electromagnetic and coupling targets, is generally a one-to-many problem. The qubit-cavity coupling strength depends sensitively on both the transmon geometry and its position within the cavity's electromagnetic field. As these systems scale up and their design parameter spaces grow, the cost of conventional iterative simulation becomes prohibitive. We present two deep neural network (DNN) approaches that address this inverse-design problem at complementary levels of the design stack. The first proposes SRF cavity geometries that produce target cavity observables. The second proposes transmon qubit designs that produce target qubit-cavity parameters - the coupling rate, qubit frequency, and anharmonicity $(g, ν_q, α)$. The recovered candidate designs match the targets to within ~5% (cavity) and ~2% (transmon), confirmed by end-to-end re-simulation. Both approaches map desired device behavior directly to candidate designs, a fast alternative to the iterative simulation studies usually required.

Yaker, Joseph [Fermilab; Northwestern U.]↗

Graphical User Interface for a Biasing Board for the PSEC6

The PSEC6 is an application-specific integrated circuit (ASIC) designed for a readout system for a large area picosecond photodetector (LAPPD). The PSEC6 is currently in fabrication and pending testing. The testing system for the PSEC5, the previous iteration of the ASIC, required expensive and non-portable equipment, because the ASIC needs twelve adjustable reference voltages. The new testing system consists of an low-cost, open-source, cross-platform graphical user interface (GUI), a digital system, and a biasing board. The digital system is the interface between the GUI and biasing board, and can be implemented on a microcontroller or field-programmable gate array (FPGA). The biasing board contains twelve digital-to-analog converters (DACs) that are configurable via the GUI, which gives users the ability to write voltage values to all or specific DACs. The GUI was developed in C on Linux using the widget library GTK4 and cross-compiled for Windows compatibility. I2C and SPI protocols were implemented on an Adafruit Feather ESP32-S3 microcontroller to write commands to the DACs and PSEC6. A hardware implementation of the I2C protocol is in development on an FPGA. Since LAPPDs will be used by the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) at Fermilab, the PSEC6 testing system in this internship project can potentially benefit future neutrino research. The project is relevant to the Department of Energy’s microelectronics mission, because the PSEC6 is an ASIC that will handle fast time signals arriving from the detector for readout. It also provided experience with building a cross-platform user interface, practicing digital design and implementation in hardware description language (HDL), and using simulations to inform new design iterations.

Guerrero, Sasha Camila [North Central Coll.]↗

Summary of the 5th IAEA technical meeting on fusion data processing, validation and analysis (FDPVA)

The purpose of the 5th International Atomic Energy Agency technical meeting on fusion data processing, validation and analysis (FDPVA) (Ghent University, Ghent, Belgium, 12–15 June 2023) was to provide a platform during which a set of topics relevant to FDPVA were discussed with the view of meeting the needs of next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics data analysis and synthetic diagnostics reported at the meeting, including concept description of new devices; fusion databases; integrated data analysis; inverse problems; uncertainty propagation, verification and validation; probabilistic methods and machine learning. The relevant results underline trends observed in the current major fusion confinement devices.

fusion databases↗

Testing of Fusion Machine Components Against Cryogenic Pellet Impacts

Shattered pellet injection (SPI), currently the most effective method of disruption mitigation, is currently implemented on tokamaks worldwide for experimental purposes. Cryogenic pellets are formed and fired into an angled surface before entering the plasma. The impact with the angled surface causes the pellets to fragment into a cloud of particles with the purpose of increasing the surface area for ablation. As pellets traverse guide tubes, depending on design, there is a chance of an off-normal pellet impact. Pellet impacts are also, depending on design, possible in the plasma chamber if not fully ablated and assimilated, or if the fragment plume is not directed in the proper direction. This paper outlines a series of pellet impact tests on various tiles and components relevant to the ITER, JET, and ASDEX Upgrade SPI systems. In conclusion, testing was done to assess the potential damage from pellet and fragment plume impacts through high-speed imaging and the visual inspection of components.

Cryogenic pellets↗

Role of E × B Drift in Divertor Detachment Control via Boron Powder Injection on EAST

Here, the effects of B powder injection on plasma detachment about EAST discharge were studied by using SOLPS-ITER code package with the effects of E × B drifts considered. The simulation results show that plasma detachment occurs at the inner target in favourable toroidal magnetic field (B t ) direction at a relatively low B powder flow rate, one order of magnitude lower than that at the outer target. In a similar scenario with unfavourable B t , it is found that the detachment thresholds of B flow rate for both the inner and outer targets are close and of the same order as that for the outer target with favourable Bt. In favourable B t direction at B powder flow rate of 1.2 × 10 21 atoms/s, a localized, broadened high-density region is formed near the inner target benefitted by the injection location and the E × B drift, and a radiation-intensified zone, mostly contributed by B 1+ and B 2+ , occurs there. The E × B drift facilitates plasma detachment at the inner target and simultaneously amplifies the in–out divertor asymmetry. In addition, the simulation results with three different injection locations show that the injection from outer strike point leads to the lowest Z eff inside the separatrix and has an intermediate flow rate for detachment at the outer target, comparing with the X-point and upstream locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performance characterization of x-ray crystal spectroscopy highly oriented pyrolytic graphite reflectors based on x-ray diffractometry experiments

The use of Highly Oriented Pyrolytic Graphite (HOPG) reflectors is often proposed in the design of X-ray Crystal Spectroscopy (XCS) diagnostic systems for the next-generation tokamak devices, including the ITER project. Here, this study introduces an experimental study based on the X-Ray Diffractometry (XRD) method to evaluate the performance of HOPG reflectors. The experimental method provides both the angular responses and the reflectivities of the HOPG reflectors. A demonstrative XRD experiment is conducted, and the details of the experiment are introduced. This method enables precise studies on HOPG reflectors, facilitating the design of XCS diagnostic systems for future tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermal energy mitigation and toroidal peaking effects in JET disruptions

Previous investigations on JET suggest half or less of plasma stored thermal energy W th is radiated (f rad,th ≲ 0.5) using either massive gas injection (MGI) or shattered pellet injection (SPI) disruption mitigation. We investigate whether the apparent incomplete f rad,th is explained by radiation peaking near the injection plume. High toroidal peaking throughout the pre-thermal quench is found in argon–deuterium MGI on JET, with typically >3× higher radiation near the injector than toroidally distant. Previously unexplained toroidal bolometry measurements in neon–deuterium SPI are reproduced with similar peaking using the Emis3D radiation analysis code. These observations align with results from Alcator C-Mod and KSTAR. This peaking is not captured by previous JET studies that found poor thermal mitigation. Two sets of neon–deuterium SPI and two sets of argon–deuterium MGI are analyzed using Emis3D. In SPI, f rad,th rises from no-plume estimates of 0.31 and 0.66 to lower bounds of 0.84 and 0.92, respectively, and f rad,th ∼ 1 is possible. In MGI, the toroidal spread of the peaking feature is poorly constrained. f rad,th up to 0.85 and 0.65 are possible using the largest possible spread, increasing from 0.42 and 0.28, although f rad,th ∼ 1 does not appear to be reached. Revised mitigation estimates on JET suggest a lower melt risk to the divertor in mitigated disruptions on ITER and SPARC than previously thought. However, peaking near injectors could increase flash melting risk on nearby plasma facing components.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Global energy balance simulations of shattered pellet injection

The dynamics of shattered pellet injection (SPI) shutdowns are simulated using a time-dependent global energy balance model, based on a modification of the KPRAD framework. The new SPI particle source in the model calculates the ablation of individual pellet fragments that enter the plasma as a temporally resolved plume, thus capturing the effects of earlier fragments on the ablation of those that follow, which has a significant impact on the overall assimilation. Despite the reduced physics and the global averaging of all quantities, results from a large number of DIII-D, KSTAR, and JET experiments are well reproduced, including the plasma cooling timescales, particle assimilation, and current quench (CQ) rates. Cooling timescales and CQ rates are in good agreement for pellets containing as little as ∼1% neon, while particle assimilations are most accurate for neon fractions above ∼15% by number of atoms. Below this, the assimilation tends to be overestimated due to the lack of radial transport in the particle balance, which becomes important in the low-Z limit. Predictive simulations of mixed-composition dual-SPI shutdowns in ITER are compared against those with the 3D non-linear magnetohydrodynamic code JOREK and are found to reproduce overall trends observed in the higher-fidelity modeling across a range of injection scenarios. The general success of the model points to the critical role of energy balance in determining SPI particle assimilation and the subsequent disruption dynamics and highlights the value of these simulations for experimental interpretation and for optimizing the deployment of computationally expensive, higher-fidelity models.

energy balance model↗

Multi-machine validation of plasma initiation modelling and prospects for future devices: Predicting plasma initiation using only hardware design and control room input data

This paper reports on the generic prediction capability of full electromagnetic plasma initiation modelling with DYON, which was carried out for the first time in fusion research by the joint modelling of the International Tokamak Physics Activity—Integrating Operation Scenario group. The following devices were included in the experiment database: VEST (spherical torus, copper coils, Stainless steel wall, R/a = 0.3 m/0.2 m, V v = 3.7 m 3 ), MAST-U (spherical torus, copper coils, C wall, R/a = 0.7 m/0.5 m, V v = 55 m 3 ), EAST (conventional tokamak, superconducting coils, metallic wall, R/a = 1.85 m/0.5 m, V v = 38 m 3 ), DIII-D (conventional tokamak, copper coils, C wall, R/a = 1.67 m/0.65 m, V v = 35 m 3 ), and KSTAR (conventional tokamak, superconducting coils, C wall, R/a = 1.8 m/0.5 m, V v = 55 m 3 ). Despite the different hardware features of the devices, the required operating spaces of the loop voltage induction and prefill gas pressure for inductive plasma initiation in each device were successfully reproduced by the predictive simulations with DYON using only the individual hardware design and the control room input data for each discharge. This successful validation across multiple machines demonstrates that the full electromagnetic DYON modelling can capture the essential physics of inductive plasma initiation. The simulation settings commonly employed for all modelling and the modifications necessary to account for the discrepancies between individual devices are reported. Predictions for ITER based on the multi-machine validation indicate that a wide range of prefill gas pressures exists for the Townsend breakdown and the plasma burn-through (0.01–1.5 mPa).

DYON↗