Results for “control methods” — Page 17

DOE OSTI2016

MO-B-201-02: Motion Management for Proton Lung SBR

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-B-201-03: MRI-Guided Tracking and Gating

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and limitations of each discussed radiation beam control methodology and tumor tacking method; understand the key points in motion management for a high quality SBRT program.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Field Demonstration of Residential DER Service-Oriented Load Participation

Amidst a concerning surge in power consumption during peak hours, coupled with heightened power grid instability, and driven by a growing demand for electricity, aggregations of Distributed Energy Resource are becoming a viable means for providing essential reliability services.Electric utility companies have proactively implemented Demand Response programs for decades. These programs employ Direct Load Control methods to enhance power grid stability, achieved by controlling customers’ Distributed Energy Resource during peak hours to reduce power consumption. However, a notable drawback of Direct Load Control has been high unenrollment rates of DR program participants due to customer discomfort.Therefore, the underlying issue of over-consumption persists. To address these concerns, this paper introduces a Service-Oriented Load Participation approach to providing grid services such as Demand Response. Leveraging a Service-Oriented Architecture, this method offers the advantage of efficient service management and provisioning within the system. The SOLP approach not only aims to reduce power consumption but also to maintain customer satisfaction by ensuring a comfortable grid service experience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Towards intelligent emergency control for large-scale power systems: Convergence of learning, physics, computing and control

Here, this paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating closer to their limits with more uncertainties. Learning-based control methods are promising and have shown effectiveness for intelligent power system control. However, when they are applied to large-scale power systems, there are multifaceted challenges such as scalability, adaptiveness, and security posed by the complex power system landscape, which demand comprehensive solutions. The paper first proposes and instantiates a convergence framework for integrating power systems physics, machine learning, advanced computing, and grid control to realize intelligent grid control at a large scale. Our developed methods and platform based on the convergence framework have been applied to a large (more than 3000 buses) Texas power system, and tested with 56 000 scenarios. Our work achieved a 26% reduction in load shedding on average and outperformed existing rule-based control in 99.7% of the test scenarios. The results demonstrated the potential of the proposed convergence framework and DRL-based intelligent control for the future grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Theoretical study on electromagnetically induced transparency in molecular aggregate models using quantum Liouville equation method

Electromagnetically induced transparency (EIT), which is known as an efficient control method of optical absorption property, is investigated using the polarizability spectra and population dynamics obtained by solving the quantum Liouville equation. In order to clarify the intermolecular interaction effect on EIT, we examine several molecular aggregate models composed of three-state monomers with the dipole-dipole coupling. On the basis of the present results, we discuss the applicability of EIT in molecular aggregate systems to a new type of optical switch.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Stanfill, Bryan A.↗

DOE OSTI2021

Machine‐learning‐based construction of barrier functions and models for safe model predictive control

Abstract In this paper, we propose a control Lyapunov‐barrier function‐based model predictive control method utilizing a feed‐forward neural network specified control barrier function (CBF) and a recurrent neural network (RNN) predictive model to stabilize nonlinear processes with input constraints, and to guarantee that safety requirements are met for all times. The nonlinear system is first modeled using RNN techniques, and a CBF is characterized by constructing a feed‐forward neural network (FNN) model with unique structures and properties. The FNN model for the CBF is trained based on data samples collected from safe and unsafe operating regions, and the resulting FNN model is verified to demonstrate that the safety properties of the CBF are satisfied. Given sufficiently small bounded modeling errors for both the FNN and the RNN models, the proposed control system is able to guarantee closed‐loop stability while preventing the closed‐loop states from entering unsafe regions in state‐space under sample‐and‐hold control action implementation. We provide the theoretical analysis for bounded unsafe sets in state‐space, and demonstrate the effectiveness of the proposed control strategy using a nonlinear chemical process example with a bounded unsafe region.

Chen, Scarlett↗

DOE OSTI2015

SU-E-P-36: Evaluation of MLC Positioning Errors in Dynamic IMRT Treatments by Analyzing Dynalog Files

Purpose: To assess the accuracy of MLC positioning in Varian linear accelerator, in dynamic IMRT technique, from the analysis of dynalog files generated by the MLC controller. Methods: In Clinac accelerators (pre-TrueBeam technology), control system has an approximately 50ms delay (one control cycle time). Then, the system compares the measured position to the planned position corresponding to the next control cycle. As it has been confirmed by Varian technical support, this effect causes that measured positions appear in dynalogs one cycle out of phase with respect to the planned positions. Around 9000 dynalogs have been analyzed, coming from the three linear accelerators of our center (one Trilogy and two Clinac 21EX) equipped with a Millennium 120 MLC. In order to compare our results to recent publications, leaf positioning errors (RMS and 95th percentile) are calculated with and without delay effect. Dynalogs have been analyzed using a in-house Matlab software. Results: The RMS errors were 0.341, 0.339 and 0.348mm for each Linac; being the average error 0.343 mm. The 95th percentiles of the error were 0.617, 0.607 and 0.625; with an average of 0.617mm. A recent multi-institution study carried out by Kerns et al. found a mean leaf RMS error of 0.32mm and a 95th percentile error value of 0.64mm.Without delay effect, mean leaf RMS errors obtained were 0.040, 0.042 and 0.038mm for each treatment machine; being the average 0.040mm. The 95th percentile error values obtained were 0.057, 0.058 and 0.054 mm, with an average of 0.056mm. Conclusion: Results obtained for the mean leaf RMS error and the mean 95th percentile were consistent with the multi-institution study. Calculated error statistics with delay effect are significantly larger due to the speed proportional and systematic leaf offset. Consequently it is proposed to correct this effect in dynalogs analysis to determine the MLC performance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Predictive Control of Residential Gas Storage Water Heaters [SWR-13-36]

Predictive Control of Residential Gas Storage Water Heaters provides an energy-efficient control method for residential gas storage water heaters. Predictive Control of Residential Gas Storage Water Heaters discovers users' hot water consumption patterns from historical data and automatically modulates the thermostat setpoints to conserve energy while maintaining thermal comfort. The starting time of hot water draw events is recorded and used for clustering analysis. Time intervals are generated from the clusters in which hot water draw events are more likely to occur. The setpoint is set at normal level to maintain thermal comfort, and decreased to a lower level outside these time intervals to reduce tank loss and thereby improving energy efficiency of the water heater.

Christensen, Dane↗

DOE OSTI2017

Core Reactivity Control for a Soluble Boron Free Small Modular Reactor

Soluble boron has been used in pressurized water reactors (PWRs) to control the core excess reactivity in a uniform and stable way without distorting power distributions. It also enables current commercial PWRs to have high core power density. Despite its outstanding advantages, the soluble boron raises several significant concerns such as soluble boron-induced corrosion of structures, a large amount of liquid waste generation, and a possibility of positive moderator temperature coefficient (MTC) at high boron concentration. These concerns become more serious as the concentration of boron becomes higher. Therefore boron in the primary coolant has been a hindrance to the power uprate and cycle extension operation of PWRs. Currently a government-supported research project is underway to develop technologies for the soluble-boron-free (SBF) operation of a PWR-type small modular reactor (SMR). This paper presents preliminary results of the SBF SMR core reactivity control methods including optimization of burnable absorbers (BA) and control rod design, and development of secondary shutdown system (SSS)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

A Novel Method for Phasor Measurement Unit Sampling Time Error Compensation

This paper focuses on a novel method for successive approximation register analog to digital converter control in synchronized phasor measurement units (PMUs). To compensate for the sampling time error caused by the division remainder between the desirable sampling rate and the oscillator frequency, a variable sampling interval control method is presented by interlacing two integers under a proposed criterion. The frequency of the onboard oscillator is monitored in real-time using the pulse per second (PPS) timing reference from global positioning system. The sampling control is adaptively adjusted each second according to the latest estimated oscillator frequency. The “saw tooth” in phasor angle error and DC offset and spikes in frequency error can be effectively eliminated by applying the proposed method. The simulation and experiment results validate the effectiveness and accuracy of the proposed method, which is believed to be able to greatly improve the performance of PPS-disciplined synchronous sampling methods in PMUs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Effect of metal–support interactions in Ni/Al2O3 catalysts with low metal loading for methane dry reforming

Not Available

Ewbank, Jessica L.↗

DOE OSTI2013

Quality Control of High-Dose-Rate Brachytherapy: Treatment Delivery Analysis Using Statistical Process Control

Purpose: Statistical process control (SPC) is a quality control method used to ensure that a process is well controlled and operates with little variation. This study determined whether SPC was a viable technique for evaluating the proper operation of a high-dose-rate (HDR) brachytherapy treatment delivery system. Methods and Materials: A surrogate prostate patient was developed using Vyse ordnance gelatin. A total of 10 metal oxide semiconductor field-effect transistors (MOSFETs) were placed from prostate base to apex. Computed tomography guidance was used to accurately position the first detector in each train at the base. The plan consisted of 12 needles with 129 dwell positions delivering a prescribed peripheral dose of 200 cGy. Sixteen accurate treatment trials were delivered as planned. Subsequently, a number of treatments were delivered with errors introduced, including wrong patient, wrong source calibration, wrong connection sequence, single needle displaced inferiorly 5 mm, and entire implant displaced 2 mm and 4 mm inferiorly. Two process behavior charts (PBC), an individual and a moving range chart, were developed for each dosimeter location. Results: There were 4 false positives resulting from 160 measurements from 16 accurately delivered treatments. For the inaccurately delivered treatments, the PBC indicated that measurements made at the periphery and apex (regions of high-dose gradient) were much more sensitive to treatment delivery errors. All errors introduced were correctly identified by either the individual or the moving range PBC in the apex region. Measurements at the urethra and base were less sensitive to errors. Conclusions: SPC is a viable method for assessing the quality of HDR treatment delivery. Further development is necessary to determine the most effective dose sampling, to ensure reproducible evaluation of treatment delivery accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

Systems and methods for spatiotemporal control of a laser and applications of same

Methods and systems are disclosed for using a chromatic lens system to provide a “flying focus”—i.e., an advanced focusing scheme enabling spatiotemporal control of a focal location. In a method, a photon beam is emitted from a source at a wavelength. The photon beam may have more than one wavelength. The photon beam is focused to a focal location using a chromatic lens system. The focal location is at a first longitudinal distance along an optical axis from the chromatic lens system. The wavelength of the photon beam is changed as a function of time to change the focal location as a function of time. The wavelength may be changed such that the focal location changes with a focal velocity.

Froula, Dustin H.↗

DOE OSTI2021

Systems and methods for spatiotemporal control of a laser and applications of same

Methods and systems are disclosed for using a chromatic lens system to provide a “flying focus”—i.e., an advanced focusing scheme enabling spatiotemporal control of a focal location. In a method, a photon beam is emitted from a source at a wavelength. The photon beam may have more than one wavelength. The photon beam is focused to a focal location using a chromatic lens system. The focal location is at a first longitudinal distance along an optical axis from the chromatic lens system. The wavelength of the photon beam is changed as a function of time to change the focal location as a function of time. The wavelength may be changed such that the focal location changes with a focal velocity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm: Preprint

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10- 15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗

DOE OSTI2019

Short-Term Forecasting Across a Network for the Autonomous Wind Farm

In an autonomous wind farm, turbines will use information from nearby turbines to achieve wind farm-level objectives such as optimizing the overall performance of a wind farm, ensuring resiliency when other sensors fail, and adapting to changing local conditions. In this paper, the wind farm can be modeled as a network within which turbines (nodes) share information across designated communication channels, with a focus on turbines at the outside of the wind farm capturing local effects and sharing that information with downstream turbines. Understanding of varied inflow conditions can be especially important in complex terrain. This information can be used to monitor turbines, self-organize turbines into groups, and predict the power performance of a wind farm. In particular, this paper describes an autonomous wind farm that incorporates information from local sensors in real time to predict wind speed and wind direction at each turbine over a short-term horizon. Results indicate that the estimate of wind direction can be used to improve the knowledge of the wind speed and direction over the persistence method on a 10-15-minute time horizon. These short-term forecasts can also be used to facilitate advanced control methods such as feedforward control within a wind farm.

17 WIND ENERGY↗