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DOE OSTI2024

Nonlinear control of the minimum safety factor in tokamaks by optimal allocation of spatially moving electron cyclotron current drive

The minimum value of the safety factor profile is related to the magnetohydrodynamic (MHD) stability of the plasma confined in a tokamak. Therefore, active control of the minimum safety factor may mitigate MHD instabilities that can degrade or even terminate plasma confinement. Typically, in most tokamak scenarios, the minimum safety factor evolves spatially with time, i.e., the location at which the safety factor achieves the minimum value changes with time. In addition to the inherent nonlinearities in the minimum safety factor evolution, its spatial variation makes the control design challenging. In particular, complexity in control design may arise from the need for time-dependent nonlinear models that account for spatial variation of the minimum safety factor. Furthermore, the minimum safety factor may drift to locations where the actuator authority is low. The problem of minimum safety factor control with target location tracking and moving electron cyclotron current drive (ECCD) is addressed in this work. A nonlinear time-dependent model that incorporates the spatial variation of the minimum safety factor is presented. A nonlinear controller based on optimal feedback linearization is developed to track a target minimum safety factor. The proposed controller treats the ECCD position as a controllable variable. In other words, the controller prescribes the ECCD position (in addition to the non-inductive powers) in real time based on an optimal criterion that is defined a priori. This work also presents the steps necessary to integrate the minimum safety factor controller with a total energy controller to achieve multiple control objectives simultaneously. In conclusion, the proposed integrated control algorithm is tested using nonlinear simulations in the Control Oriented Transport SIMulator (COTSIM) for a DIII-D tokamak scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

An inkjet vision measurement technique for high-frequency jetting

Inkjet technology has been used as manufacturing a tool for printed electronics. To increase the productivity, the jetting frequency needs to be increased. When using high-frequency jetting, the printed pattern quality could be non-uniform since the jetting performance characteristics including the jetting speed and droplet volume could vary significantly with increases in jet frequency. Therefore, high-frequency jetting behavior must be evaluated properly for improvement. However, it is difficult to measure high-frequency jetting behavior using previous vision analysis methods, because subsequent droplets are close or even merged. In this paper, we present vision measurement techniques to evaluate the drop formation of high-frequency jetting. The proposed method is based on tracking target droplets such that subsequent droplets can be excluded in the image analysis by focusing on the target droplet. Finally, a frequency sweeping method for jetting speed and droplet volume is presented to understand the overall jetting frequency effects on jetting performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP, a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as a simulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundary shape. To understand the response of the plasma current, stored energy, and central safety factor to these actuators and to enable systematic design of control algorithms, simulations were run in which the actuators were modulated and a linearized dynamic response model was generated. A multi-variable model-based control scheme that accounts for the coupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed and simulated. Simulations show that modest changes in the outer gap and heating power can improve the response time of the system, reject perturbations, and track target values of the controlled values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Duty-Cycle Predictive Control of Quasi-Z-Source Modular Cascaded Converter Based Photovoltaic Power System

A duty-cycle predictive control is proposed for dc grid integration of front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The post-stage qZS half-bridge dc-dc converter deals with PV maximum power point tracking, dc grid integration, and dc-link voltage balance; whereas, the front-end isolation converters operate at a constant duty cycle of 50%. Thus, it saves control hardware resources while overcoming challenges from PV-panel voltage variations and dc-bus voltage limit. The proposed control uses the derived circuit model to predict the global active-state duty cycle for grid-connected current control and predict the shoot-through duty cycles for dc-link voltage balance, achieving a fast and accurate tracking target. The proposed control method has advantages of: i) eliminating weighting factors that exist in conventional model predictive control (MPC), ii) no sophisticated loop parameters design that exists in proportional-integral (PI) control, iii) operating at constant switching frequency that is different from the conventional MPC with variable switching frequency. Simulation and experimental tests are carried out to verify the effectiveness of the proposed control method and compare with the PI-based control system.

42 ENGINEERING↗

DOE OSTI2021

Multiagent-Based Dynamic Voltage Support of Power Converters During Fault Ride-Through

Reference point of applicability (RPA) is a predefined point in a distribution network that performance requirements shall apply. As RPA is not directly controlled by a dedicated distributed energy resource (DER), it requires an aggregate response of multiple DERs over a complex meshed network. Here, this article presents a multiagent-based distributed dynamic voltage support (DDVS) method for coordinated aggregate response of multiple DER units to support RPA voltage profile during and after fault ride-through. DDVS implements a multiagent-based leader target tracking scheme with velocity matching and flock centering features to avoid uncoordinated current injections of cooperative DERs. The DDVS is an event-based approach based on RPA requirements. Two-dimensional voltage support objective is handled: 1) coordinated positive sequence current injection for voltage magnitude boosting and 2) coordinated negative sequence current injection for unbalance voltage mitigation. The results demonstrate that the proposed DDVS algorithm addresses emerging coordinated DVS requirement of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Optimal Power Flow Pursuit

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall, the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

SU-C-17A-07: The Development of An MR Accelerator-Enabled Planning-To-Delivery Technique for Stereotactic Palliative Radiotherapy Treatment of Spinal Metastases

Purpose: To develop an MR accelerator-enabled online planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases. The technical challenges include; automated stereotactic treatment planning, online MR-based dose calculation and MR guidance during treatment. Methods: Using the CT data of 20 patients previously treated at our institution, a class solution for automated treatment planning for spinal bone metastases was created. For accurate dose simulation right before treatment, we fused geometrically correct online MR data with pretreatment CT data of the target volume (TV). For target tracking during treatment, a dynamic T2-weighted TSE MR sequence was developed. An in house developed GPU based IMRT optimization and dose calculation algorithm was used for fast treatment planning and simulation. An automatically generated treatment plan developed with this treatment planning system was irradiated on a clinical 6 MV linear accelerator and evaluated using a Delta4 dosimeter. Results: The automated treatment planning method yielded clinically viable plans for all patients. The MR-CT fusion based dose calculation accuracy was within 2% as compared to calculations performed with original CT data. The dynamic T2-weighted TSE MR Sequence was able to provide an update of the anatomical location of the TV every 10 seconds. Dose calculation and optimization of the automatically generated treatment plans using only one GPU took on average 8 minutes. The Delta4 measurement of the irradiated plan agreed with the dose calculation with a 3%/3mm gamma pass rate of 86.4%. Conclusions: The development of an MR accelerator-enabled planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases was presented. Future work will involve developing an intrafraction motion adaptation strategy, MR-only dose calculation, radiotherapy quality-assurance in a magnetic field, and streamlining the entire treatment process on an MR accelerator.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-C-BRF-07: A Pattern Fusion Algorithm for Multi-Step Ahead Prediction of Surrogate Motion

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogate signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-BRA-07: Megavoltage Spectral Imaging with a Layered Detector

Purpose: The aim of the current work is to investigate the feasibility of megavoltage spectral imaging using a multiple layered detector for enhancement of low contrast detectability through material segmentation and discrimination (such as bone, markers and metal implants). Potentially the technique can be applied to improve detection and reduce dose in Megavoltage Cone Beam Computed Tomography (MV-CBCT). Methods: Experiments were performed with a prototype multi-layer imager (MLI) which has higher detective efficiency and lower noise characteristics than conventional Electronic Portal Imaging Devices (EPIDs). Images of a solid water phantom were acquired at 2.5 MV, 6MV and 6MV without flattening filter (FFF). The following materials were placed within a stack of solid water: aluminum, copper and gold. Material separation was assessed based on Contrast-to-Noise Ratio (CNR) of the weighted image, formed by a weighted subtraction of the images from two layers of the MLI. A range of weighting factors were investigated for material separation. Results: CNR can be minimized for each material by appropriate selection of the subtraction weighting factor. This is equivalent to a selective subtraction of specific materials from the image. Using multiple layers simultaneously also decreases the dose requirement and removes any registration errors. The minimum CNR for aluminum, copper and gold at the weighted image formed with 2.5MV was obtained at weighting factors equal to 0.92, 0.76 and 0.64 respectively. The corresponding values at 6MVFFF were 0.99, 0.92 and 0.78 respectively. Conclusion: In the current work, an MV spectral imaging feasibility study was attempted using a novel multi-layer prototype EPID imager. Initial results suggest that material separation based on spectral differences between different layers is possible. This spectral imaging technique has potential advantages in MV-CBCT for real-time target tracking, patient set-up imaging and adaptive radiotherapy. The project was supported, partially, by a grant from Varian Medical Systems, Inc., and Award No. R01CA188446-01 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-AB-BRA-02: Automated Triplet Beam Orientation Optimization for MRI-Guided Co-60 Radiotherapy

Purpose: MRI guided Co-60 provides daily and intrafractional MRI soft tissue imaging for improved target tracking and adaptive radiotherapy. To remedy the low output limitation, the system uses three Co-60 sources at 120° apart, but using all three sources in planning is considerably unintuitive. We automate the beam orientation optimization using column generation, and then solve a novel fluence map optimization (FMO) problem while regularizing the number of MLC segments. Methods: Three patients—1 prostate (PRT), 1 lung (LNG), and 1 head-and-neck boost plan (H&NBoost)—were evaluated. The beamlet dose for 180 equally spaced coplanar beams under 0.35 T magnetic field was calculated using Monte Carlo. The 60 triplets were selected utilizing the column generation algorithm. The FMO problem was formulated using an L2-norm minimization with anisotropic total variation (TV) regularization term, which allows for control over the number of MLC segments. Our Fluence Regularized and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLN) produced by an experienced dosimetrist. Results: The mean PTV D95, D98, and D99 differ by −0.02%, +0.12%, and +0.44% of the prescription dose between planning methods, showing same PTV dose coverage. The mean PTV homogeneity (D95/D5) was at 0.9360 (FROST) and 0.9356 (CLN). R50 decreased by 0.07 with FROST. On average, FROST reduced Dmax and Dmean of OARs by 6.56% and 5.86% of the prescription dose. The manual CLN planning required iterative trial and error runs which is very time consuming, while FROST required minimal human intervention. Conclusions: MRI guided Co-60 therapy needs the output of all sources yet suffers from unintuitive and laborious manual beam selection processes. Automated triplet orientation optimization is shown essential to overcome the difficulty and improves the dosimetry. A novel FMO with regularization provides additional controls over the number of MLC segments and treatment time. Varian Medical Systems; NIH grant R01CA188300; NIH grant R43CA183390.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP,a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as asimulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundaryshape. To understand the response of the plasma current, stored energy, and central safety factor to these actuatorsand to enable systematic design of control algorithms, simulations were run in which the actuators were modulated anda linearized dynamic response model was generated. A multi-variable model-based control scheme that accounts for thecoupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed andsimulated. Simulations show that modest changes in the outer gap and heating power can improve the response time ofthe system, reject perturbations, and track target values of the controlled values.

Predictive simulations↗

DOE OSTI2025

The Satellite Image Simulation Toolkit

The Satellite Image Simulation Toolkit (SatIST) is a python software package designed to generate diverse and realistic satellite imaging scenarios. It serves as a toolkit for simulating data that supports the development and testing of algorithms used in satellite detection, calibration, and characterization. SIST provides a suite of simulation tools that allow users to replicate various satellite observation conditions, including sidereal and target tracking. By enabling the creation of scenarios that mimic real-world satellite operations, SIST facilitates advancements in satellite image data processing and the study of satellite behavior under different observational parameters.

Perloff, AlexxS [Lawrence Livermore National Labor↗

DOE OSTI2020

Batch Measurement Extremum Seeking Control of Distributed Energy Resources to Account for Communication Delays and Information Loss

Distributed Energy Resources (DER) have great potential to enhance the operation of electric power distribution systems. Previously, we explored the use of 2 Dimensional Extremum Seeking (2D-ES) control algorithms to enable model-free optimal control of DER to provide grid services to both the distribution and transmissions systems. Motivated by preliminary deployments of DER managed by 2D-ES algorithms in hardware-in-the-loop tests and in operational distribution grids, in this work, we extend the control scheme to accommodate communication delays and information loss. We propose a modification to the 2D-ES scheme to allow for the processing of batches of possibly noncontiguous objective function measurements at unknown and possibly uneven intervals. We provide a proof of the convergence of the batch 2D-ES (2D-BES) scheme when optimizing a generic convex objective function, as well as simulation results that demonstrate the suitability of the approach for substation active and reactive power target tracking.

Sankur, Michael↗

DOE OSTI2016

Final Report: Non-Visible, Automated Target Acquisition and Tracking

The Roadside Tracker (RST) represents a new approach to radiation portal monitors. It uses a combination of gamma-ray and visible-light imaging to localize gamma-ray radiation sources to individual vehicles in free-flowing, multi-lane traffic. Deployed as two trailers that are parked on either side of the roadway (Fig. 1); the RST scans passing traffic with two large gamma-ray imagers, one mounted in each trailer. The system compensates for vehicle motion through the imager’s fields of view by using automated target acquisition and tracking (TAT) software applied to a stream of video images. Once a vehicle has left the field of view, the radiation image of that vehicle is analyzed for the presence of a source, and if one is found, an alarm is sounded. The gamma-ray image is presented to the operator together with the video image of the traffic stream when the vehicle was approximately closest to the system (Fig. 2). The offending vehicle is identified with a bounding box to distinguish it from other vehicles that might be present at the same time. The system was developed under a previous grant from the Department of Homeland Security’s (DHS’s) Domestic Nuclear Detection Office (DNDO). This report documents work performed with follow-on funding from DNDO to further advance the development of the RST. Specifically, the primary thrust was to extend the performance envelope of the system by replacing the visible-light video cameras used by the TAT software with sensors that would allow operation at night and during inclement weather. In particular, it was desired to allow operation after dark without requiring external lighting. As part of this work, the system software was also upgraded to allow the use of 64-bit computers, the current generation operating system (OS), software development environment (Windows 7 vs. Windows XP, and current Visual Studio.Net), and improved software version controls (GIT vs. Source Safe.) With the upgraded performance allowed by new computers, and the additional memory available in a 64-bit OS, the system was able to handle greater traffic densities, and this also allowed addition of the ability to handle stop-and-go traffic.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2015

Minimum Cost Multi-way Data Association for Optimizing Multitarget Tracking of Interacting Objects

This paper presents a general formulation for a minimum cost data association problem which associates data features via one-to-one, m-to-one and one-to-n links with minimum total cost of the links. A motivating example is a problem of tracking multiple interacting nanoparticles imaged on video frames, where particles can aggregate into one particle or a particle can be split into multiple particles. Many existing multitarget tracking methods are capable of tracking non-interacting targets or tracking interacting targets of restricted degrees of interactions. The proposed formulation solves a multitarget tracking problem for general degrees of inter-object interactions. The formulation is in the form of a binary integer programming problem. We propose a polynomial time solution approach that can obtain a good relaxation solution of the binary integer programming, so the approach can be applied for multitarget tracking problems of a moderate size (for hundreds of targets over tens of time frames). The resulting solution is always integral and obtains a better duality gap than the simple linear relaxation solution of the corresponding problem. The proposed method was validated through applications to simulated multitarget tracking problems and a real multitarget tracking problem.

Binary Integer Programming↗

DOE OSTI2015

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

60 APPLIED LIFE SCIENCES↗