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At least 1,513 records · Page 84

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↗

An Approach to Bayesian Optimization for Design Feasibility Check on Discontinuous Black-Box Functions

The paper presents a novel approach to applying Bayesian Optimization (BO) in predicting an unknown constraint boundary, also representing the discontinuity of an unknown function, for a feasibility check on the design space, thereby representing a classification tool to discern between a feasible and infeasible region. Bayesian optimization is a low-cost black-box global optimization tool in the Sequential Design Methods where one learns and updates knowledge from prior evaluated designs, and proceeds to the selection of new designs for future evaluation. However, BO is best suited to problems with the assumption of a continuous objective function and does not guarantee true convergence when having a discontinuous design space. This is because of the insufficient knowledge of the BO about the nature of the discontinuity of the unknown true function. In this paper, we have proposed to predict the location of the discontinuity using a BO algorithm on an artificially projected continuous design space from the original discontinuous design space. The proposed approach has been implemented in a thin tube design with the risk of creep-fatigue failure under constant loading of temperature and pressure. The stated risk depends on the location of the designs in terms of safe and unsafe regions, where the discontinuities lie at the transition between those regions; therefore, the discontinuity has also been treated as an unknown creep-fatigue failure constraint. The proposed BO algorithm has been trained to maximize sampling toward the unknown transition region, to act as a high accuracy classifier between safe and unsafe designs with minimal training cost. The converged solution has been validated for different design parameters with classification error rate and function evaluations at an average of <1% and ~150, respectively. Finally, the performance of our proposed approach in terms of training cost and classification accuracy of thin tube design is shown to be better than the existing machine learning (ML) algorithms such as Support Vector Machine (SVM), Random Forest (RF), and Boosting.

Engineering↗

SU-E-T-429: Uncertainties of Cell Surviving Fractions Derived From Tumor-Volume Variation Curves

Purpose: To evaluate uncertainties of cell surviving fraction reconstructed from tumor-volume variation curves during radiation therapy using sensitivity analysis based on linear perturbation theory. Methods: The time dependent tumor-volume functions V(t) have been calculated using a twolevel cell population model which is based on the separation of entire tumor cell population in two subpopulations: oxygenated viable and lethally damaged cells. The sensitivity function is defined as S(t)=[δV(t)/V(t)]/[δx/x] where δV(t)/V(t) is the time dependent relative variation of the volume V(t) and δx/x is the relative variation of the radiobiological parameter x. The sensitivity analysis was performed using direct perturbation method where the radiobiological parameter x was changed by a certain error and the tumor-volume was recalculated to evaluate the corresponding tumor-volume variation. Tumor volume variation curves and sensitivity functions have been computed for different values of cell surviving fractions from the practically important interval S{sub 2}=0.1-0.7 using the two-level cell population model. Results: The sensitivity functions of tumor-volume to cell surviving fractions achieved a relatively large value of 2.7 for S{sub 2}=0.7 and then approached zero as S{sub 2} is approaching zero Assuming a systematic error of 3-4% we obtain that the relative error in S{sub 2} is less that 20% in the range S2=0.4-0.7. This Resultis important because the large values of S{sub 2} are associated with poor treatment outcome should be measured with relatively small uncertainties. For the very small values of S2<0.3, the relative error can be larger than 20%; however, the absolute error does not increase significantly. Conclusion: Tumor-volume curves measured during radiotherapy can be used for evaluation of cell surviving fractions usually observed in radiation therapy with conventional fractionation.

60 APPLIED LIFE SCIENCES↗

SU-E-T-221: Computational Evaluation of Proton Induced Gain in a Portable Faraday Cup

Purpose: The design of a new Portable Faraday Cup (PFC) used to calibrate proton accelerators was evaluated for energies between 50 and 220 MeV. Monte Carlo simulations performed in Geant4–10.0 were used to evaluate experimental results and reduce the relative detector error for this vacuum-less and low mass system, and invalidate current MCNP releases. Methods: The detector construction consisted of a copper conductor coated with an insulator and grounded with silver. Monte Carlo calculations in Geant4 were used to determine the net charge per proton input (gain) as a function of insulator thickness and beam energy. Kapton was chosen as the insulating material and was designed to capture backscattered electrons. Charge displacement from/into Kapton was assumed to follow a linear proportionality to the origin/terminus depth toward the outer ground layer. Kapton thicknesses ranged from 0 to 200 microns, proton energies were set to match empirical studies ranging from 70 to 250 MeV. Each setup was averaged over 1 million events using the FTFP-BERT 2.0 physics list. Results: With increasing proton energy, the gain of Cu+KA gradually converges to the limit of pure copper, with relative error between 1.52% and 0.72%. The Ag layer created a more diverging behavior, accelerating the flux of negative charge into the device and increasing relative error when compared to pure copper from 1.21% to 1.63%. Conclusion: Gain vs. beam energy signatures were acquired for each device. Further analysis reveals proportionality between insulator thickness and measured gain, albeit an inverse proportionality between beam energy and in-flux of electrons. Increased silver grounding layer thickness also decreases gain, though the relative error expands with beam energy, contrary to the Kapton layer.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Technical Note: Cortical thickness and density estimation from clinical CT using a prior thickness-density relationship

Purpose: Cortical thickness and density are critical components in determining the strength of bony structures. Computed tomography (CT) is one possible modality for analyzing the cortex in 3D. In this paper, a model-based approach for measuring the cortical bone thickness and density from clinical CT images is proposed. Methods: Density variations across the cortex were modeled as a function of the cortical thickness and density, location of the cortex, density of surrounding tissues, and imaging blur. High resolution micro-CT data of cadaver proximal femurs were analyzed to determine a relationship between cortical thickness and density. This thickness-density relationship was used as prior information to be incorporated in the model to obtain accurate measurements of cortical thickness and density from clinical CT volumes. The method was validated using micro-CT scans of 23 cadaver proximal femurs. Simulated clinical CT images with different voxel sizes were generated from the micro-CT data. Cortical thickness and density were estimated from the simulated images using the proposed method and compared with measurements obtained using the micro-CT images to evaluate the effect of voxel size on the accuracy of the method. Then, 19 of the 23 specimens were imaged using a clinical CT scanner. Cortical thickness and density were estimated from the clinical CT images using the proposed method and compared with the micro-CT measurements. Finally, a case-control study including 20 patients with osteoporosis and 20 age-matched controls with normal bone density was performed to evaluate the proposed method in a clinical context. Results: Cortical thickness (density) estimation errors were 0.07 ± 0.19 mm (−18 ± 92 mg/cm{sup 3}) using the simulated clinical CT volumes with the smallest voxel size (0.33 × 0.33 × 0.5 mm{sup 3}), and 0.10 ± 0.24 mm (−10 ± 115 mg/cm{sup 3}) using the volumes with the largest voxel size (1.0 × 1.0 × 3.0 mm{sup 3}). A trend for the cortical thickness and density estimation errors to increase with voxel size was observed and was more pronounced for thin cortices. Using clinical CT data for 19 of the 23 samples, mean errors of 0.18 ± 0.24 mm for the cortical thickness and 15 ± 106 mg/cm{sup 3} for the density were found. The case-control study showed that osteoporotic patients had a thinner cortex and a lower cortical density, with average differences of −0.8 mm and −58.6 mg/cm{sup 3} at the proximal femur in comparison with age-matched controls (p-value < 0.001). Conclusions: This method might be a promising approach for the quantification of cortical bone thickness and density using clinical routine imaging techniques. Future work will concentrate on investigating how this approach can improve the estimation of mechanical strength of bony structures, the prevention of fracture, and the management of osteoporosis.

60 APPLIED LIFE SCIENCES↗

SU-G-JeP1-08: Dual Modality Verification for Respiratory Gating Using New Real- Time Tumor Tracking Radiotherapy System

Purpose: The respirato ry gating system combined the TrueBeam and a new real-time tumor-tracking radiotherapy system (RTRT) was installed. The RTRT system consists of two x-ray tubes and color image intensifiers. Using fluoroscopic images, the fiducial marker which was implanted near the tumor was tracked and was used as the internal surrogate for respiratory gating. The purposes of this study was to develop the verification technique of the respiratory gating with the new RTRT using cine electronic portal image device images (EPIDs) of TrueBeam and log files of the RTRT. Methods: A patient who underwent respiratory gated SBRT of the lung using the RTRT were enrolled in this study. For a patient, the log files of three-dimensional coordinate of fiducial marker used as an internal surrogate were acquired using the RTRT. Simultaneously, the cine EPIDs were acquired during respiratory gated radiotherapy. The data acquisition was performed for one field at five sessions during the course of SBRT. The residual motion errors were calculated using the log files (E{sub log}). The fiducial marker used as an internal surrogate into the cine EPIDs was automatically extracted by in-house software based on the template-matching algorithm. The differences between the the marker positions of cine EPIDs and digitally reconstructed radiograph were calculated (E{sub EPID}). Results: Marker detection on EPID using in-house software was influenced by low image contrast. For one field during the course of SBRT, the respiratory gating using the RTRT showed the mean ± S.D. of 95{sup th} percentile E{sub EPID} were 1.3 ± 0.3 mm,1.1 ± 0.5 mm,and those of E{sub log} were 1.5 ± 0.2 mm, 1.1 ± 0.2 mm in LR and SI directions, respectively. Conclusion: We have developed the verification method of respiratory gating combined TrueBeam and new real-time tumor-tracking radiotherapy system using EPIDs and log files.

60 APPLIED LIFE SCIENCES↗

An Efficient, Globally Convergent Method for Optimization Under Uncertainty Using Adaptive Model Reduction and Sparse Grids

We present a new approach to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages two sources of inexactness that trade accuracy for speed: (1) stochastic collocation based on dimension-adaptive sparse grids (SGs), which approximates the stochastic objective function with a limited number of quadrature nodes, and (2) projection-based reduced-order models (ROMs), which generate efficient approximations to PDE solutions. These two sources of inexactness lead to inexact objective function and gradient evaluations, which are managed by a trust-region method that guarantees global convergence by adaptively refining the SG and ROM until a proposed error indicator drops below a tolerance specified by trust-region convergence theory. A key feature of the proposed method is that the error indicator---which accounts for errors incurred by both the SG and ROM---must be only an asymptotic error bound, i.e., a bound that holds up to an arbitrary constant that need not be computed. This allows the approach to be applicable to a wide range of problems, including those where sharp, computable error bounds are not available; this distinguishes the proposed method from previous works. Numerical experiments performed on a model problem from optimal flow control under uncertainty verify global convergence of the method and demonstrate the method's ability to outperform previously proposed alternatives.

97 MATHEMATICS AND COMPUTING↗

Collagen Turnover in Relation to Risk Factors and Hemodynamics in Human Intracranial Aneurysms

Determinants for molecular and structural instability, that is, impending growth or rupture, of intracranial aneurysms (IAs) remain uncertain. To elucidate this, we endeavored to estimate the actual turnover rates of the main molecular constituent in human IA (collagen) on the basis of radiocarbon ( 14 C) birth dating in relation to IA hemodynamics. Collagen turnover rates in excised human IA samples were calculated using mathematical modeling of 14 C birth dating data of collagen in relation to risk factors and histological markers for collagen maturity/turnover in selected IA. Hemodynamics were simulated using image-based computational fluid dynamics. Correlation, logistic regression, and receiver operating characteristic analyses were performed. Collagen turnover rates were estimated in 46 IA (43 patients); computational fluid dynamics could be performed in 20 IA (20 patients). The mean collagen turnover rate (γ) constituted 126% (±1% error) per year. For patients with arterial hypertension, γ was greater than 2600% annually, whereas γ was distinctly lower with 32% (±1% error) per year for patients without risk factors, such as smoking and hypertension. There was a distinct association between histological presence of rather immature collagen in human IA and the presence of modifiable risk factors. Spatial-temporal averaged wall shear stress predicted rapid collagen turnover (odds ratio, 1.6 [95% CI, 1.0–2.7]). Receiver operating characteristic analysis demonstrated a good test accuracy (area under the curve, 0.798 [95% CI, 0.598–0.998]) for average wall shear stress with a threshold ≥4.9 Pa for rapid collagen turnover. Our data indicate that turnover rates and stability of collagen in human IA are strongly associated with the presence of modifiable risk factors and aneurysmal hemodynamics. Finally, these findings underline the importance of strict risk factor modification in patients with unruptured IA. Future should include more detailed risk factor data to establish a more causal understanding of hemodynamics and the rupture risk of individual IA.

60 APPLIED LIFE SCIENCES↗

Moving beyond the total sea ice extent in gauging model biases

Here, reproducing characteristics of observed sea ice extent remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total sea ice distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total sea ice area, or some measure of its equatorward extent, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differences between simulated and observed sea ice. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of sea ice cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much sea ice in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total sea ice area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric sea ice area or extent can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of sea ice characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.

54 ENVIRONMENTAL SCIENCES↗

Performance Analysis for the New g-2 Experiment at Fermilab

The new g-2 experiment at Fermilab aims to measure the muon anomalous magnetic moment to a precision of ±0.14 ppm - a fourfold improvement over the 0.54 ppm precision obtained in the g-2 BNL E821experiment. Achieving this goal requires the delivery of highly polarized 3.094 GeV/c muons with a narrow ±0.5% Δp/p acceptance to the g-2 storage ring. In this study, we describe a muon capture and transport scheme that should meet this requirement. First, we present the conceptual design of our proposed scheme wherein we describe its basic features. Then, we detail its performance numerically by simulating the pion production in the (g-2) production target, the muon collection by the downstream beamline optics as well as the beam polarization and spin-momentum correlation up to the storage ring. The sensitivity in performance of our proposed channel against key parameters such as magnet apertures and magnet positioning errors is analyzed

43 PARTICLE ACCELERATORS↗

Safety Case for Service Contracts

Safety cases developed for the Facilities Management and Operations Center (FMOC) are based on the requirements in MN471021, Work Planning and Control Criteria for Safe Design and Operations. The FMOC performs maintenance activities in various locations at Sandia National Laboratories, New Mexico (SNL/NM). SNL/NM consists of more than 6,000,000 square feet of buildings, structures, and site infrastructure on approximately 13,000 acres of land. The FMOC performs approximately 7500 service contract work orders a year to assist with operations and maintenance at the SNL/NM site and facilities. As part of the continual improvement process, this Safety Case will be reviewed and updated, as needed, or at a minimum every three years. People tend to underestimate the probability of an accident if none have occurred previously or if the person performing the work is skilled, and they tend to trust each other’s competence. Human error within systems must be identified and considered. The FMOC uses failure mode analysis (FMA) to determine how a system might fail and cause accidents, as well as the amount and types of controls needed. The FMOC includes interconnected elements, such as people, environment, procedures, facilities, equipment, and the hazards identified in the work analysis. A daily pre-task plan is required prior to any work activity. Changes in work practices will be communicated clearly to all service contractors and personnel by way of contractor pre-task planning, activity-specific plans, contract amendments, and/or training. The FMOC has created a safe-by-design intent approach for service contract execution starting at the planning stage and extending through the execution phase. The Safety Program (see Figure 2) summarizes how the FMOC connects work analysis elements with service contracts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

CBP for Field Workers – Results and Insights from Three Usability and Interface Design Evaluations

Nearly all activities that involve human interaction with the systems in a nuclear power plant are guided by procedures. Even though the paper-based procedures (PBPs) currently used by industry have a demonstrated history of ensuring safety, improving procedure use could yield significant savings in increased efficiency as well as improved nuclear safety through human performance gains. The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use and adherence, researchers in the Light-Water Reactor Sustainability (LWRS) Program, together with the nuclear industry, have been investigating the possibility and feasibility of replacing the current paper-based procedure process with a computer-based procedure (CBP) system. This report describes a field evaluation of new design concepts of a prototype computer-based procedure system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Making Compiler-Based Tools Accessible Online

Compiler-based tools are widely used to analyze and optimize source codes for many purposes, including extracting insights about applications’ properties or restructuring code for better performance. However, using compiler-based tools is often difficult due to tedious and error-prone steps to configure and install such tools on various machines. In this paper, we describe a solution to use CGI + Bash to expose compilerbased tools to a web page so users can directly use these tools without installing them.

97 MATHEMATICS AND COMPUTING↗

Making Compiler-Based Tools Accessible Online

Compiler-based tools are widely used to analyze and optimize source codes for many purposes, including extracting insights about applications’ properties or restructuring code for better performance. However, using compiler-based tools is often difficult due to tedious and error-prone steps to configure and install such tools on various machines. In this paper, we describe a solution to use CGI + Bash to expose compilerbased tools to a web page so users can directly use these tools without installing them.

97 MATHEMATICS AND COMPUTING↗

VALID Past, Present, and Future [Slides]

This presentation discusses the Verified, Archived Library of Inputs and Data (VALID) procedure which is managed per computational procedure under the overall SCALE quality assurance plan. The principle behind VALID is that two independent, qualified people prepare and review the model, while a dual, independent check acts as a primary barrier to prevent errors in the library. A final check by VALID QAC of procedural compliance is then performed. The future for VALID includes plans to add more experiments, a review for all ICSBEP cases containing Deuterium, ZEUS intermediate and fast spectrum evaluations, intermediate enrichment experiments, other cases of interest to sponsors, and mixed/intermediate spectrum experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

In-situ mid-circuit qubit measurement and reset in a single-species trapped-ion quantum computing system

We implement in-situ mid-circuit measurement and reset (MCMR) operations on a trapped-ion quantum computing system by using metastable qubit states in $^{171}\textrm{Yb}^+$ ions. We introduce and compare two methods for isolating data qubits from measured qubits: one shelves the data qubit into the metastable state and the other drives the measured qubit to the metastable state without disturbing the other qubits. We experimentally demonstrate both methods on a crystal of two $^{171}\textrm{Yb}^+$ ions using both the $S_{1/2}$ ground state hyperfine clock qubit and the $S_{1/2}$-$D_{3/2}$ optical qubit. These MCMR methods result in errors on the data qubit of about $2\%$ without degrading the measurement fidelity. With straightforward reductions in laser noise, these errors can be suppressed to less than $0.1\%$. The demonstrated method allows MCMR to be performed in a single-species ion chain without shuttling or additional qubit-addressing optics, greatly simplifying the architecture.

Atomic Physics (physics.atom-ph)↗

Future changes in isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) under the Shared Socioeconomic Pathways: the importance of physicochemical dependency

Abstract. Secondary organic aerosol (SOA) is a dominant contributor of fine particulate matter in the atmosphere, but the complexity of SOA formation chemistry hinders the accurate representation of SOA in models. Volatility-based SOA parameterizations have been adopted in many recent chemistry modeling studies and have shown a reasonable performance compared to observations. However, assumptions made in these empirical parameterizations can lead to substantial errors when applied to future climatic conditions as they do not include the mechanistic understanding of processes but are rather fitted to laboratory studies of SOA formation. This is particularly the case for SOA derived from isoprene epoxydiols (IEPOX SOA), for which we have a higher level of understanding of the fundamental processes than is currently parameterized in most models. We predict future SOA concentrations using an explicit mechanism and compare the predictions with the empirical parameterization based on the volatility basis set (VBS) approach. We then use the Community Earth System Model 2 (CESM2.1.0) with detailed isoprene chemistry and reactive uptake processes for the middle and end of the 21st century under four Shared Socioeconomic Pathways (SSPs): SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5. With the explicit chemical mechanism, we find that IEPOX SOA is predicted to increase on average under all future SSP scenarios but with some variability in the results depending on regions and the scenario chosen. Isoprene emissions are the main driver of IEPOX SOA changes in the future climate, but the IEPOX SOA yield from isoprene emissions also changes by up to 50 % depending on the SSP scenario, in particular due to different sulfur emissions. We conduct sensitivity simulations with and without CO2 inhibition of isoprene emissions that is highly uncertain, which results in factor of 2 differences in the predicted IEPOX SOA global burden, especially for the high-CO2 scenarios (SSP3–7.0 and SSP5–8.5). Aerosol pH also plays a critical role in the IEPOX SOA formation rate, requiring accurate calculation of aerosol pH in chemistry models. On the other hand, isoprene SOA calculated with the VBS scheme predicts a nearly constant SOA yield from isoprene emissions across all SSP scenarios; as a result, it mostly follows isoprene emissions regardless of region and scenario. This is because the VBS scheme does not consider heterogeneous chemistry; in other words, there is no dependency on aerosol properties. The discrepancy between the explicit mechanism and VBS parameterization in this study is likely to occur for other SOA components as well, which may also have dependencies that cannot be captured by VBS parameterizations. This study highlights the need for more explicit chemistry or for parameterizations that capture the dependence on key physicochemical drivers when predicting SOA concentrations for climate studies.

54 ENVIRONMENTAL SCIENCES↗

Significant Improvement in PV Module Performance Prediction Accuracy Using a New Model Based on IEC-61853 Data: Preprint

This paper presents a significant improvement in accuracy for photovoltaic (PV) module performance prediction using a new approach based on IEC-61853 test data. The method is based on the concept of a single diode model and calibrates its performance across a broad set of operating conditions. The new method reduces irradiance-weighted error in maximum power point (MPP) power relative to the standard 6-parameter single diode model, on average across 20 different module types, by 88% across the entire range of measured irradiance and temperature conditions, while retaining a continuous mathematical representation of the full current-voltage characteristic that allows for accurate off-MPP module modeling.

14 SOLAR ENERGY↗