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At least 1,297 records · Page 72

Integration of high confinement, high poloidal beta plasma with dual radiated power and detachment controls for divertor protection and ELM suppression

Divertor detachment without serious core confinement quality loss in DIII-D’s high poloidal β scenario has been combined with impurity-induced ELM mitigation without disruption. Use of Ne previously granted access to a detached, non-ELMing regime that retained high confinement quality due to stimulation of Internal Transport Barrier (ITB) growth, but suffered from on-going core fuel dilution and high disruptivity. Excess Ne accumulation in the core plasma has now been avoided by feeding back core radiated power ($P_{rad}$) measurements to control Ne seeding, rather than using attachment fraction ($A_{frac}$) control with Ne; this also reduces disruptivity. At the same time, N 2 seeding is used in a feedback loop with $A_{frac}$ measurements, which previously posed low disruption risk. In this way, the effect of Ne in the core is managed while avoiding excess seeding, and N 2 acts to correct for any excess heat exhaust that might interfere with detachment. The average Ne flow rate was 38% of what was used in pure Ne $A_{frac}$ control, plus average N 2 flow that was 43% of pure N 2 $A_{frac}$ control, even while meeting an even deeper detachment target. Meanwhile, a steep pressure gradient in the core plasma reduces sensitivity to impurity-induced degradation of the pedestal and reasonable confinement quality was maintained despite operational challenges that blocked formation of an ITB in these experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

To improve the marketability of novel microreactor designs, there is a need for automated and optimal control of these reactors. This paper presents a methodology for performing multiobjective optimization of control drum operation for a microreactor under normal and off-nominal conditions. Here, two different case studies are used where the control drum configuration is optimized for the reactor to be critical with some desired power distribution that would satisfy peaking limits. A surrogate model for power distribution is developed based on a feedforward neural network. The process for determining weights for scalarization of the multiobjective optimization problem is also detailed. Six optimization algorithms: evolutionary strategies, differential evolution, grey wolf optimization, Harris hawks optimization, moth flame optimization and particle swarm optimization, are all applied to these cases and the results analyzed. Although all these algorithms will demonstrate optima-seeking behavior, for real-time control it is necessary to identify the best algorithm to efficiently provide reasonable optima without operator interference. The moth flame optimization algorithm was found to perform particularly well on both cases. Overall, it was found that the algorithms capable of supplying the best optima were also the most consistent. Finally, the found optima were verified with the original model used to train surrogates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High-dimensional control co-design of a wave energy converter with a novel pitch resonator power takeoff system

Researchers are exploring adding wave energy converters to existing oceanographic buoys to provide a predictable source of renewable power. A ”pitch resonator” power take-off system has been developed that generates power using a geared flywheel system designed to match resonance with the pitching motion of the buoy. However, the novelty of the concept leaves researchers uncertain about various design aspects of the system. This work presents a novel design study of a pitch resonator to inform design decisions for an upcoming deployment of the system. The assessment uses control co-design via WecOptTool to optimize control trajectories for maximal electrical power production while varying five design parameters of the pitch resonator. Given the large search space of the problem, the control trajectories are optimized within a Monte Carlo analysis to identify optimal designs, followed by parameter sweeps around the optimum to identify trends between the design parameters. The gear ratio between the pitch resonator spring and flywheel are found to be the most sensitive design variables to power performance. Finally, the assessment also finds similar power generation for various sizes of resonator components, suggesting that correctly designing for optimal control trajectories at resonance is more critical to the design than component sizing.

16 TIDAL AND WAVE POWER↗

Virtual storage capability of residential buildings for sustainable smart city via model-based predictive control

This paper evaluates the virtual storage capability of a residential air-conditioning (AC) system by utilizing the building mass as a thermal storage to enable sustainable cities through model-based predictive control (MPC). The control-oriented building model was developed with a grey-box model structure based on the experimental data to predict the indoor air temperature. Based on the model, the operation cost-saving potential of the MPC was investigated in a single house with different comfort levels, electricity prices, and prediction horizons. The cost-saving of the MPC was approximately 10.6 % compared to the conventional control. The MPC was expanded to a residential building cluster considering the peak demand charge. In an hourly shedding and load-up scenario, the performances of the MPC and the heuristic prior-based control (PBC) are promising. When shedding was enforced all day, the peak demand saving of the MPC was 36~38 %, whereas that of the PBC was 25.7 % compared to the baseline. In addition, the monthly electricity bill, including the operation and peak demand cost, was investigated with different demand charge rates and weather conditions. The total saving decreased with a low demand charge rate and hot conditions, and the operation cost saving was compromised with more aggressive demand shedding.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Investigation of pressure-controlled injection molding on the mechanical properties and embodied energy of recycled high-density polyethylene

Manufacturing with secondary feedstock has been identified as an effective strategy to improve plastic circularity. However, product quality inconsistencies arise due to variations in molecular weight, rheology, and mechanical properties. This work evaluates the processing of recycled high-density polyethylene using pressure-controlled injection molding with a focus on processing behavior and energy consumption. Further, the effects of injection velocity, packing pressure, and transfer position are benchmarked against a conventional velocity-controlled process. The experimental results show that the novel process control strategy significantly affects the mechanical properties, in-mold rheology, and energy consumption. Parts fabricated using pressure-controlled injection molding showed higher tensile properties due to increased macromolecular orientation. Additionally, reduced energy was used due to lower melt pressures required to completely replicate the cavity geometry. The results demonstrate the potential of the technology to support increased utilization of secondary feedstock and reduced carbon footprint.

36 MATERIALS SCIENCE↗

Control systems and data management for high-power laser facilities

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community

47 OTHER INSTRUMENTATION↗

Structural basis for dimerization quality control

Most quality control pathways target misfolded proteins to prevent toxic aggregation and neurodegeneration 1 . Dimerization quality control further improves proteostasis by eliminating complexes of aberrant composition 2 , but how it detects incorrect subunits remains unknown. Here we provide structural insight into target selection by SCF-FBXL17, a dimerization-quality-control E3 ligase that ubiquitylates and helps to degrade inactive heterodimers of BTB proteins while sparing functional homodimers. We find that SCF-FBXL17 disrupts aberrant BTB dimers that fail to stabilize an intermolecular β-sheet around a highly divergent β-strand of the BTB domain. Furthermore, complex dissociation allows SCF-FBXL17 to wrap around a single BTB domain, resulting in robust ubiquitylation. SCF-FBXL17 therefore probes both shape and complementarity of BTB domains, a mechanism that is well suited to establish quality control of complex composition for recurrent interaction modules.

59 BASIC BIOLOGICAL SCIENCES↗

Variational control forces for enhanced sampling of nonequilibrium molecular dynamics simulations

We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis is made possible by explicit forms for the gradients of a cost function in terms of the susceptibility of driven trajectories to changes in variational parameters. We consider probabilities of time-integrated dynamical observables as characterized by their large deviation functions and find that in many cases, the variational estimate is quantitatively accurate. Additionally, we provide expressions to exactly correct the variational estimate that can be evaluated directly. We benchmark this algorithm against the numerically exact solution of a model of a driven particle in a periodic potential, where the control force can be represented with a complete basis. Additionally, we then demonstrate the utility of the algorithm in a model of repulsive particles on a line, which undergo a dynamical phase transition, resulting in singular changes to the form of the optimal control force. In both systems, we find fast convergence and are able to evaluate large deviation functions with significant increases in statistical efficiency over alternative Monte Carlo approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Localizing resonant magnetic perturbations for edge localized mode control in KSTAR

An external 3D magnetic perturbation typically drives a resonant response at the rational surfaces from the core to the edge of tokamak plasmas, due to strong mode coupling and amplification. In this paper, we present a method to isolate the edge from core resonant fields using the ideal perturbed equilibrium code and to design an edge-localized resonant magnetic perturbation (RMP) for effective edge localized mode (ELM) control. A robust feature of the edge-localized RMP is the curtailed response to the field at the low-field-side (LFS) midplane, as opposed to typical RMPs which strongly resonate with the LFS fields. This emphasizes the importance of off-midplane coils to improve ELM control without provoking a large core response that could lead to devastating instabilities. The conceptual design of new ELM control coils based on the edge-localized RMP in KSTAR shows how this new insight can be utilized to enhance the efficiency of our ELM suppression capabilities. Simple window-pane coils matching the edge-localized resonant mode structure substantially expand in the ELM suppression window beyond the existing coil. Further optimization using the flexible optimized coils using space-curves code leads to additional enhancement in the edge-localized control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas

A theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X.

neoclassical modelling↗

Evaluation of ITER divertor shunts as a synthetic diagnostic for detachment control

Reliable diagnostics that measure the detached state of the ITER divertor plasma will be necessary to control heat flux to the divertor targets during steady state, burning plasma operation. This paper conducts an initial exploration into the feasibility of the divertor shunt diagnostic as a lightweight, robust, and real-time detachment sensor. This diagnostic is a set of shunt lead pairs that measure the voltage drop along the divertor cassette body, from which the plasma scrape-off layer (SOL) current is calculated. Using SOLPS-ITER simulations for control-relevant ITER plasma scenarios, the thermoelectric current magnitude along the SOL is shown to decrease significantly with the onset of partial detachment at the outer divertor target. Electromagnetic modelling of a simplified divertor cassette is used to develop a control-oriented inductance-resistance circuit model, from which SOL currents can be calculated from shunt pair voltage measurements. The sensitivity and frequency-response of the resulting system indicates that the diagnostic will accurately measure SOL thermoelectric currents during ITER operation. These currents will be a good measure of the detached state of the divertor plasma, making the divertor shunt diagnostic a potentially extremely valuable and physically robust sensor for real-time detachment control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Regulation compliant AI for fusion: explainable image-based feedback control of divertor detachment in DIII-D tokamak

While artificial intelligence (AI) has been promising for fusion control, its inherent black-box nature will make compliant implementation in regulatory environments a challenge. This study implements and validates a real-time AI-enabled linear and interpretable control system for successful divertor detachment control with the DIII-D lower divertor camera. Using D 2 gas, we demonstrate successful feedback divertor detachment control with a mean absolute difference of 2% from the target for both detachment and reattachment. This automatic training and linear processing framework can be extended to any image-based diagnostic for future fusion reactors.

computer vision↗

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗

Embedded EPICS server for PowerPMAC motion controllers

An embedded server layer of Experimental Physics and Industrial Control System (EPICS) for PowerPMAC motion controllers has been developed and deployed at two undulator beamlines of the National Institute of General Medical Sciences and the National Cancer Institute (GM/CA) Structural Biology Facility at the Advanced Photon Source (APS). This compact, open source solution makes the power and versatility of PowerPMAC motion controls directly accessible to distributed EPICS clients. At GM/CA the system controls about 200 servo and stepper motors — both encoded and unencoded — and multiple digital and analog I/O accessories. The server stack comprises two sublayers: a lower-level driver and database that communicates directly with PowerPMAC, and a facility-specific soft sublayer built on top. The paper describes installing EPICS on PowerPMAC, the implementation of both layers and client examples, including on-the-fly scanning.

EPICS↗

Closed-Loop Control of Active Nematic Flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Active nematics↗

Quantum optimal control of ten-level nuclear spin qudits in Sr 87

We study the ability to implement unitary maps on states of the I = 9 / 2 nuclear spin in Sr 87 , a d = 10 dimensional (qudecimal) Hilbert space, using quantum optimal control. Through a combination of nuclear spin resonance and a tensor ac Stark shift, by solely modulating the phase of a radio-frequency magnetic field, the system is quantum controllable. Alkaline-earth-metal atoms, such as Sr 87 , have a very favorable figure of merit for such control due to narrow intercombination lines and the large hyperfine splitting in the excited states. We numerically study the quantum speed limit, optimal parameters, and the fidelity of arbitrary state preparation and full SU(10) maps, including the presence of decoherence due to optical pumping induced by the light-shifting laser. We also study the use of robust control to mitigate some dephasing due to inhomogeneities in the light shift. We find that with an rf Rabi frequency of Ω rf and 0.5% inhomogeneity in the the light shift we can prepare an arbitrary Haar-random state in a time T = 4.5 π / Ω rf with average fidelity ( F ψ ) = 0.9992 , and an arbitrary Haar-random SU(10) map in a time T = 24 π / Ω rf with average fidelity ( F U ) = 0.9923 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Qubit control noise spectroscopy with optimal suppression of dephasing

Here, we extend quantum noise spectroscopy (QNS) of amplitude control noise to settings where dephasing noise or detuning errors make significant contributions to qubit dynamics. Previous approaches to characterize amplitude noise are limited by their vulnerability to low-frequency dephasing noise and static detuning errors, which can overwhelm the target control noise signal and introduce bias into estimates of the amplitude noise spectrum. To overcome this problem, we leverage optimal control to identify a family of amplitude control waveforms that optimally suppress low-frequency dephasing noise and detuning errors, while maintaining the spectral concentration in the amplitude filter essential for spectral estimation. The waveforms found via numerical optimization have surprisingly simple analytic forms, consisting of oscillating sine waves obeying particular amplitude and frequency constraints. In numerically simulated QNS experiments, these waveforms demonstrate superior robustness, enabling accurate estimation of the amplitude noise spectrum in regimes where existing approaches are biased by low-frequency dephasing noise and detuning errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implementation of a High-Speed Multichannel Data Acquisition System for Magnetic Diagnostics and Plasma Centroid Position Control in ISTTOK

In tokamak and other fusion devices, magnetic control is the main tool that allows to regulate the plasma current, position and shape; it is in charge of actuating the desired plasma current waveform, steering the plasma position to a given set point and maintain the plasma shape close to a prescribed plasma equilibrium. This work describes the application of several physics concepts and computational tools in order to obtain a novel optimal controller for the plasma centroid position, which has been implemented and tested in the real-time plasma control system at the ISTTOK tokamak. A key point for the development of the new control system was the installation of a recently upgraded hardware, that numerically integrates in real-time the magnetic probes signals.

poloidal field coils↗