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At least 289 records · Page 16

Unmanned Aerial Vehicle Path Generation for Image Collection to Assist Heliostat Field Optical Characterization

This paper focuses on applications of unmanned aerial vehicles (UAVs) for measuring optical error of heliostats in concentrating solar power (CSP) plants. In CSP, there is a need to measure solar-field optical errors, which is critical for future production improvement as well as for operations and maintenance of a heliostat field. This latter need is particularly challenging because of the large number of heliostats (over 10,000 for a utility-scale power plant) that individually track the sun in the field. To address this issue, a camera-equipped UAV, with an optimized drone flight path developed and uploaded to it, collects images of a precise reflection of the tower on each heliostat to evaluate optical error sources without interrupting plant operation. Generation of the drone path for capturing the reflected images is affected by a number technical and realistic constraints, which include the camera angle used to capture the image, the blocking of the camera view due to surrounding heliostats, the location of the camera in reference to the target heliostat, and the target heliostat position with reference to the tower. The effect of these constraints on calculating the camera position will be discussed in detail in this article. An effective drone-path algorithm is generated to fulfil the need of image collection under various constraints.

concentrated solar power↗

Speeding up particle track reconstruction using a parallel Kalman filter algorithm

One of the most computationally difficult problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD architectures that are now prevalent in high-performance hardware. In this paper, we discuss the design and performance of the improved tracking algorithm, referred to as mkFit. A key piece of the algorithm is the Matriplex library, containing dedicated code to optimally vectorize operations on small matrices. The physics performance of the mkFit algorithm is comparable to the nominal CMS tracking algorithm when reconstructing tracks from simulated proton-proton collisions within the CMS detector. We study the scaling of the algorithm as a function of the parallel resources utilized and find large speedups both from vectorization and multi-threading. mkFit achieves a speedup of a factor of 6 compared to the nominal algorithm when run in a single-threaded application within the CMS software framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Solving phase appearance/disappearance two-phase flow problems with high resolution staggered grid and fully implicit schemes by the Jacobian-free Newton–Krylov Method

The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integration methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.

97 MATHEMATICS AND COMPUTING↗

Magellan adaptive optics first-light observations of the exoplanet β PIC b. II. 3–5 μm direct imaging with MagAO+Clio, and the empirical bolometric luminosity of a self-luminous giant planet

Young giant exoplanets are a unique laboratory for understanding cool, low-gravity atmospheres. A quintessential example is the massive extrasolar planet β Pic b, which is 9 AU from and embedded in the debris disk of the young nearby A6V star β Pictoris. We observed the system with first light of the Magellan Adaptive Optics (MagAO) system. In Paper I we presented the first CCD detection of this planet with MagAO+VisAO. Here we present four MagAO+Clio images of β Pic b at 3.1 μm, 3.3 μm, L′, and M{sup ′}, including the first observation in the fundamental CH{sub 4} band. To remove systematic errors from the spectral energy distribution (SED), we re-calibrate the literature photometry and combine it with our own data, for a total of 22 independent measurements at 16 passbands from 0.99 to 4.8 μm. Atmosphere models demonstrate the planet is cloudy but are degenerate in effective temperature and radius. The measured SED now covers >80% of the planet’s energy, so we approach the bolometric luminosity empirically. We calculate the luminosity by extending the measured SED with a blackbody and integrating to find log(L{sub bol}/L{sub ⊙}) = −3.78±0.03. From our bolometric luminosity and an age of 23 ± 3 Myr, hot-start evolutionary tracks give a mass of 12.7 ± 0.3 M{sub Jup}, radius of 1.45 ± 0.02 R{sub Jup}, and T{sub eff} of 1708 ± 23 K (model-dependent errors not included). Our empirically determined luminosity is in agreement with values from atmospheric models (typically −3.8 dex), but brighter than values from the field-dwarf bolometric correction (typically −3.9 dex), illustrating the limitations in comparing young exoplanets to old brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗

Field quality of the 4.5 m-long MQXFA pre-series magnets for the HL-LHC Upgrade as observed during magnet assembly

We report that the U.S. High-Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP) is developing MQXFA magnets, a series of 4.5 m long 150 mm aperture high-field Nb 3 Sn quadrupole magnets for the HL-LHC upgrade at CERN. Five pre-series magnets, MQXFA03 through MQXFA07, have been developed. During the magnet assembly stage, we perform magnetic measurements on the coil-pack sub-assembly and magnets after loading to track the field quality for two purposes. First, it serves as a quality assurance tool to check if the magnetic field quality is on track to meet the acceptance criteria. Magnetic measurements are used to understand if magnetic shims are needed to compensate low-order field errors and to meet the field quality targets. Second, the measurements during the assembly stage can also help understand the field quality, especially the geometric field errors, for Nb 3 Sn accelerator magnets. Here we summarize the measurement results of the pre-series MQXFA magnets, including the magnetic axis and twist angle. The results will provide useful feedback for the series production of Nb 3 Sn magnets and on the optimization of field quality of accelerator magnets based on the wind-and-react Nb 3 Sn technology.

43 PARTICLE ACCELERATORS↗

Theoretical Control-Centric Modeling for Precision Model-Based Sliding Mode Control of a Hydraulic Artificial Muscle Actuator

Artificial muscles (AMs) typically rely on pneumatic sources of fluid power. The use of hydraulics can increase the power and force to weight and volume ratios of AM actuators. This paper develops a control-centric third-order single-input single-output (SISO) lumped-parameter dynamic model and sliding mode position controller based on Filippov's principle of equivalent dynamics for a braided hydraulic artificial muscle (HAM) actuator. The model predicts the nonlinear behavior of the HAM free contraction and captures the fluid and actuator nonlinear dynamic interactions in addition to the braid deformation. Model simulations are compared to experimental results for quasi-static pressurization, isometric pressurization, and open-loop square wave commands at 0.25, 0.5, and 1 Hz. Experiments of sine wave tracking at 0.25, 0.5, and 1 Hz and continuous square wave tracking at 0.067 Hz are conducted using a sliding mode controller (SMC) derived from the model. The SMC achieves a steady-state error of 6 μm at multiple setpoints within the actuator's 17 mm stroke. Compared to a proportional-integral-derivative (PID) controller, the SMC root-mean-square (RMS) error, mean error, and absolute maximum error are reduced on average by 53%, 61%, and 44%, respectively, demonstrating the benefit of model-based approaches for controlling HAMs.

42 ENGINEERING↗

A Polynomial-Time Classical Algorithm for Noisy Quantum Circuits

We provide a polynomial-time classical algorithm for noisy quantum circuits. The algorithm computes the expectation value of any observable for any circuit, with a small average error over input states drawn from an ensemble (e.g., the computational basis). Our approach is based upon the intuition that noise exponentially damps nonlocal correlations relative to local correlations. This enables one to classically simulate a noisy quantum circuit by keeping track of only the dynamics of local quantum information. Our algorithm also enables sampling from the output distribution of a circuit in quasipolynomial time, so long as the distribution anticoncentrates. A number of implications are discussed, including a fundamental limit on the efficacy of noise mitigation strategies: For constant noise rates, any quantum circuit for which error mitigation succeeds in polynomial-time on most input states can also be classically simulated in polynomial-time on most input states. Our algorithms scale exponentially in the inverse noise rate, which is fundamental and makes them impractical for current quantum devices.

decoherence↗

Method To Determine MgO and MgOHCl in Chloride Molten Salts

A commercial blend of mainly carnallite (KCl∙MgCl 2 ∙6H 2 O) is considered as a next-generation heat transfer fluid in solar thermal plants. Corrosive properties of MgCl2 hydrates must be addressed at the operating temperatures of 500-720 degrees C. For successful chemical monitoring of the carnallite heat transfer fluid, an experimental method was developed to separate and titrate for MgO and MgOHCl from solid carnallite. This new method was assessed for error and accuracy. The method's relative error for MgOHCl was -7.0% for a mass fraction of 9.0 wt % MgOHCl in the carnallite salt. The method's relative error for MgO was less than +1.0% for a mass fraction of 12.0 wt % MgO in the carnallite salt. Titration results were used to track changes in the MgOHCl concentration in carnallite salt through the carnallite's dehydration and purification.

14 SOLAR ENERGY↗

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

This letter presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. Here, the robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.

42 ENGINEERING↗

SU-C-202-03: A Tool for Automatic Calculation of Delivered Dose Variation for Off-Line Adaptive Therapy Using Cone Beam CT

Purpose: Monitoring the delivered dose is an important task for the adaptive radiotherapy (ART) and for determining time to re-plan. A software tool which enables automatic delivered dose calculation using cone-beam CT (CBCT) has been developed and tested. Methods: The tool consists of four components: a CBCT Colleting Module (CCM), a Plan Registration Moduel (PRM), a Dose Calculation Module (DCM), and an Evaluation and Action Module (EAM). The CCM is triggered periodically (e.g. every 1:00 AM) to search for newly acquired CBCTs of patients of interest and then export the DICOM files of the images and related registrations defined in ARIA followed by triggering the PRM. The PRM imports the DICOM images and registrations, links the CBCTs to the related treatment plan of the patient in the planning system (RayStation V4.5, RaySearch, Stockholm, Sweden). A pre-determined CT-to-density table is automatically generated for dose calculation. Current version of the DCM uses a rigid registration which regards the treatment isocenter of the CBCT to be the isocenter of the treatment plan. Then it starts the dose calculation automatically. The AEM evaluates the plan using pre-determined plan evaluation parameters: PTV dose-volume metrics and critical organ doses. The tool has been tested for 10 patients. Results: Automatic plans are generated and saved in the order of the treatment dates of the Adaptive Planning module of the RayStation planning system, without any manual intervention. Once the CTV dose deviates more than 3%, both email and page alerts are sent to the physician and the physicist of the patient so that one can look the case closely. Conclusion: The tool is capable to perform automatic dose tracking and to alert clinicians when an action is needed. It is clinically useful for off-line adaptive therapy to catch any gross error. Practical way of determining alarming level for OAR is under development.

60 APPLIED LIFE SCIENCES↗

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗

Chapter 11.2: Inverters, Power Optimizers, and Microinverters

Inverters span a wide range of sizes, topologies, and connection voltages: from utility-scale megawatt inverters to string inverters. Switch-mode power conversion relies on high frequency chopping of DC signal to periodically charge and discharge energy storage elements, such as inductors and capacitors. Additional circuit components are required to address practical issues in inverters such as voltage ripple and harmonic distortion. Inverters are beginning to incorporate components with a bandgap above should be 3 eV, such as SiC and GaN. Photovoltaic (PV) modules respond dynamically to changing temperature and irradiation conditions. Thus, maximum DC power extraction requires periodic adjustment of the PV voltage and current operating point. An inverter's total efficiency is measured by the product of its conversion efficiency and the maximum-power-point tracking (MPPT) efficiency. This chapter lists the primary functions of inverters that include auxiliary capabilities, such as monitoring of DC and AC performance, and other error reporting.

14 SOLAR ENERGY↗

Model-predictive optimal control of ferrofluidic microrobots in three-dimensional space

Ferrofluid microrobots have emerged as promising tools for minimally invasive medical procedures. Their unique properties to navigate complex fluids and reach otherwise inaccessible regions of the human body have enabled new applications in targeted drug delivery, tissue engineering, and diagnostics. Here, this paper proposes a model-predictive controller for the external magnetic manipulation of ferrofluid microrobots in three dimensions (3D). The internal optimization routine of the controller determines appropriate changes in the applied electromagnetic field to minimize the deviation between the actual and desired trajectories of the microrobot. A linear system governing locomotion is derived and used as the equality constraints of the optimization problems associated with the feedback index. In addition to ferrofluid droplets, the controller presented in this work may be applied to other magnetically-pulled microrobots. Several experiments are performed to validate the controller and showcase its ability to adapt to changes in system parameters such as the desired tracking trajectory and the size, orientation, deformation, and velocity of the microrobot. The accuracy of the controller is analyzed for each experiment, and the average error is found to be within 0.25 mm for small velocities. An additional experiment is performed to demonstrate significant improvement over a PID controller that is optimally tuned using Bayesian optimization. The results presented in this paper suggest that the proposed control algorithm could enable new microrobotic capabilities in minimally invasive medical procedures, lab-on-a-chip applications, and microfluidics.

60 APPLIED LIFE SCIENCES↗

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recent Measurement of Flavor Asymmetry of Antiquarks in the Proton by Drell–Yan Experiment SeaQuest at Fermilab

A measurement of the flavor asymmetry of the antiquarks ($\bar{d}$ and $\bar{u}$) in the proton is described in this thesis. The proton consists of three valence quarks, sea quarks, and gluons. Antiquarks in the proton are sea quarks. They are generated from the gluon splitting: g → q + $\bar{q}$. According to QCD (Quantum Chromodynamics), the gluon splitting is independent of quark flavor. It suggests that the amounts of $\bar{d}$ and $\bar{u}$ should be the same in the proton. However, the NMC experiment at CERN found that the amount of $\bar{d}$ is larger than that of $\bar{u}$ in the proton using the deep inelastic scattering in 1991. This result is obtained for $\bar{d}$ and $\bar{u}$ integrated over Bjorken x. Bjorken x is the fraction of the momentum of the parton to that of the proton. The NA51 experiment (x ~ 0.2) at CERN and E866/NuSea experiment (0.015 < x < 0.35) at Fermilab measured the flavor asymmetry of the antiquarks ($\bar{d}$/$\bar{u}$) in the proton as a function of x using Drell–Yan process. The experiments reported that the flavor symmetry is broken over all measured x values. Understanding the flavor asymmetry of the antiquarks in the proton is a challenge of the QCD. The theo- retical investigation from the first principle of QCD such as lattice QCD calculation is important. In addition, the QCD effective models and hadron models such as the meson cloud model can also be tested with the flavor asymmetry of antiquarks. From the experimental side, it is important to measure with higher accuracy and in a wider x range. The SeaQuest (E906) experiment measures $\bar{d}$/$\bar{u}$ at large x (0.15 < x < 0.45) accurately to understand its behavior. The SeaQuest experiment is a Drell–Yan experiment at Fermi National Accelerator Laboratory (Fermilab). In the Drell–Yan process of proton-proton reaction, an antiquark in a proton and a quark in another proton annihilate and create a virtual photon, which then decays into a muon pair (q$\bar{q}$ → γ* → µ + µ - ). The SeaQuest experiment uses a 120 GeV proton beam extracted from Fermilab’s Main Injector. The proton beam interacts with hydrogen and deuterium targets. The SeaQuest spectrometer detects the muon pairs from the Drell–Yan process. The $\bar{d}$/$\bar{u}$ ratio at 0.1 < x < 0.58 is extracted from the number of detected Drell–Yan muon pairs. After the detector construction, commissioning run and detector upgrade, the SeaQuest experiment started the physics data acquisition from 2013. We finished so far three periods of physics data acquisition. The fourth period is in progress. The detector construction, detector performance evaluation, data taking and data analysis for the flavor asymmetry of the antiquarks $\bar{d}$/$\bar{u}$ in the proton are my contribution to SeaQuest. The cross section ratio of Drell–Yan process in p- p and p-d reactions is obtained from dimuon yields. In the experiment with high beam intensity, it is important to control the tracking efficiency of charged particles through the magnetic spectrometer. The tracking efficiency depends on the chamber occupancy, and the appropriate method for the correction is important. The chamber occupancy is the number of hits in drift chambers. A new method of the correction for the tracking efficiency is developed based on the occupancy, and applied to the data. This method reflects the real response of the drift chambers. Therefore, the systematic error is well controlled by this method. The flavor asymmetry of antiquarks is obtained at 0.1 < x < 0.58. At 0.1 < x < 0.45, the result is $\bar{d}$/$\bar{u}$ > 1. The result at 0.1 < x < 0.24 agrees with the E866 result. The result at x > 0.24, however, disagrees with the E866 result. The result at 0.45 < x < 0 the statistical errors. u¯ results extracted from experiments are used to investigate the validity of the theoretical models. The present experimental result provides the data points in wide x region. It is useful for understanding the proton structure in the light of QCD and effective hadron models. The present result has a practical application as well. Antiquark distributions are important as inputs to simulations of hadron reactions such as W± production in various experiments. The new knowledge on antiquark distributions helps to improve the precision of the simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Augmented Reality To Track Prescription Drug Inventories

The technology was originally designed to assist workers using gloveboxes to document nuclear materials handling issues. The application defined in the DisrupTech process was the use of the technology to improve tracking and handling of materials in pharmacies or in pharmaceutical manufacturing. This report focuses on the use of the technology in pharmacy applications to reduce drug errors.

47 OTHER INSTRUMENTATION↗

Inspecta Annual Technical Report

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

42 ENGINEERING↗

Improved Reanalysis and Prediction of Atmospheric Fields Over the Southern Ocean Using Campaign‐Based Radiosonde Observations

Abstract This study investigated the impact of radiosonde observations from the Southern Ocean obtained by the Australian R/V Aurora Australis on the ALERA2 experimental ensemble reanalysis data set and ensemble forecast experiment. An observing system experiment (OSE) that included additional ship‐launched radiosonde data captured the atmospheric structure over the Southern Ocean. ALERA2 without additional radiosondes had positive temperature biases exceeding 7 °C in the upper troposphere when low‐pressure cyclonic systems passed over the ship. The spread in the upper level was reduced by 15% in the OSE, which propagated downstream from the ship's position because of the sparse observing network over southern high latitudes. Comparison of two 63‐member ensemble forecast experiments initialized by ALERA2 and the OSE revealed that prediction of midlatitude cyclone tracks was improved by the realistic representation of upper‐level troughs in the OSE forecast. This confirms that additional radiosondes over the Southern Ocean reduce uncertainty and error in midlatitude cyclone forecasts.

54 ENVIRONMENTAL SCIENCES↗