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DOE OSTI2024

Field Programmable Gate Array-Based Reactor Protection Systems and Potential for Inclusion of Secure Elements to Improve Cybersecurity

For acceptable implementations of technologies like wireless communications, remote monitoring, etc., strong mitigations must be developed and evaluated to ensure that new attack pathways do not increase risk for Advanced Reactors. Secure Elements can be adopted and adapted for this purpose based on tamper resistance and cryptographic abilities, but research must be done to properly integrate into critical components such as FPGA-based Important to Safety systems in conjunction with current and future regulations on cyber security features in Advanced Reactors. Typically, the integration of a Secure Element happens during the POST and UEFI boot of a computing platform, performed by the Operating System, which is not possible with FPGAs because they do not include these firmware components. Work must be done to identify a reliable and secure method for integration in FPGA-based systems which lack Operating Systems and therefore complex boot procedures, system calls, etc.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Excitonic couplings between molecular crystal pairs by a multistate approximation

In this paper, we present a diabatization scheme to compute the excitonic couplings between an arbitrary number of states in molecular pairs. The method is based on an algebraic procedure to find the diabatic states with a desired property as close as possible to that of some reference states. In common with other diabatization schemes, this method captures the physics of the important short-range contributions (exchange, overlap, and charge-transfer mediated terms) but it becomes particularly suitable in presence of more than two states of interest. The method is formulated to be usable with any level of electronic structure calculations and to diabatize different types of states by selecting different molecular properties. These features make the diabatization scheme presented here especially appropriate in the context of organic crystals, where several excitons localized on the same molecular pair may be found close in energy. In this paper, the method is validated on the tetracene crystal dimer, a well characterized case where the charge transfer (CT) states are closer in energy to the Frenkel excitons (FE). The test system was studied as a function of an external electric field (to explore the effect of changing the relative energy of the CT excited state) and as a function of different intermolecular distances (to probe the strength of the coupling between FE and CT states). Additionally, we illustrate how the approximation can be used to include the environment polarization effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Likelihood-based docking of models into cryo-EM maps

Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimized strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selection criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Multi-Objective Optimization of a Wrought Magnesium Alloy for High Strength and Ductility

An optimization technique is coupled with crystal plasticity based finite element (CPFE) computations to aid the microstructural design of a wrought magnesium alloy for improved strength and ductility. The initial microstructure consists of a collection of sub-micron sized grains containing deformation twins. The variables used in the simulations are crystallographic texture, and twin spacing within the grains. It is assumed that plastic deformation occurs mainly by dislocation slip on two sets of slip systems classified as hard and soft modes. The hard modes are those slip systems that are inclined to the twin planes and the soft mode consists of dislocation glide along the twin plane. The CPFE code calculates the stress-strain response of the microstructure as a function of the microstructural parameters and the length-scale of the features. A failure criterion based on a critical shear strain and a critical hydrostatic stress is used to define ductility. The optimization is based on the sequential generation of an initial population defined by the texture and twin spacing variables. The CPFE code and the optimizer are coupled in parallel so that new generations are created and analyzed dynamically. In each successive generation, microstructures that satisfy at least 90% of the mean strength and mean ductility in the current generation are retained. Multiple generation runs based on the above procedure are carried out in order to obtain maximum strength-ductility combinations. Finally, the implications of the computations for the design of a wrought magnesium alloy are discussed. Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Computed Tomography Automation Architecture Developed from a Comprehensive Literature Review

This paper presents a literature review on techniques related to the computed tomography procedure that incorporate automation elements in their research investigations or industrial applications. Computed tomography (CT) is a non-destructive testing (NDT) technique in that the imaging and inspection are performed without damaging the sample, allowing for additional or repeated analysis if necessary. The reviewed literature is organized based on the steps associated with a general NDT task in order to define an end-to-end computed tomography automation architecture. The process steps include activities prior to image collection, during the scan, and after the data are collected. It further reviews efforts related to repeating this process based on a previous scan result. By analyzing the multiple existing but disparate efforts found in the literature, we present a framework for fully automating NDT procedures and discuss the remaining technical gaps in the developed framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Resilience-based Recovery Scheduling of Transportation Network in Mixed Traffic Environment: A Deep-Ensemble-Assisted Active Learning Approach

Devising effective post-hazard recovery strategies is critical in enhancing the resilience of transportation networks (TNs). However, existing work does not consider the multiclass users’ travel behavior in network functionality quantification and the metaheuristic solution procedures often suffer from extensive computational burden due to the exploration need in large solution space and the expensive functionality quantification. Here, this study develops a bilevel decision-making framework for the resilience-based recovery scheduling of the TN in a mixed traffic environment with connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs). The lower level quantifies the TN's functionality over time considering different travel behavior of CAV and HDV users arisen from their different levels of information perception. The upper level presents a novel deep-ensemble-assisted active learning approach to balance optimization performance and computational cost. This framework can help decision makers better quantify the TN's functionality to support effective recovery scheduling of TN with different mixed traffic scenarios ranging from HDV-only to future CAV-dominant traffic. The optimization approach bears the potential to be extended to solving general large-scale network recovery scheduling problems effectively and efficiently. The proposed methodology is demonstrated using a real-world traffic network in Southern California under earthquake considering deterministic and stochastic repair durations.

42 ENGINEERING↗
DOE OSTI2019

Automatic detection of small bowel tumors in wireless capsule endoscopy images using ensemble learning

Purpose Wireless Capsule Endoscopy (WCE) is a minimally invasive diagnosis tool for lesion detection in the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the significant amount of acquired data leads to difficulties in the diagnosis by the physicians; which can be eased with computer assistance. This paper addresses a method for the automatic detection of tumors in WCE by using a two‐step based procedure: region of interest selection and classification. Methods The first step aims to separate abnormal from normal tissue by using automatic segmentation based on a Gaussian Mixture Model (GMM). A modified version of the Anderson method for convergence acceleration of the expectation–maximization (EM) algorithm is proposed. The proposed features for both segmentation and classification are based on the CIELab color space, as a way of bypassing lightness variations, where the L component is discarded. Tissue variability among subjects, light inhomogeneities and even intensity differences among different devices can be overcome by using simultaneously features from both regions. In the second step, an ensemble system with partition of the training data with a new training scheme is proposed. At this stage, the gating network is trained after the experts have been trained decoupling the joint maximization of both modules. The partition module is also used at the test step, leading the incoming data to the most likely expert allowing incremental adaptation by preserving data diversity. Results This algorithm outperforms others based on texture features selected from Wavelets and Curvelets transforms, classified by a regular support vector machine (SVM) in more than 5%. Conclusions This work shows that simpler features can outperform more elaborate ones if appropriately designed. In the current case, luminance was discarded to cope with saturated tissue, facilitating the color perception. Ensemble systems remain an open research field. In the current case, changes in both topology and training strategy have led to significant performance improvements. A system with this level of performance can be used in current clinical practice.

Vieira, Pedro M.↗
DOE OSTI2013

Feasibility of an online adaptive replanning method for cranial frameless intensity-modulated radiosurgery

To introduce an approach for online adaptive replanning (i.e., dose-guided radiosurgery) in frameless stereotactic radiosurgery, when a 6-dimensional (6D) robotic couch is not available in the linear accelerator (linac). Cranial radiosurgical treatments are planned in our department using intensity-modulated technique. Patients are immobilized using thermoplastic mask. A cone-beam computed tomography (CBCT) scan is acquired after the initial laser-based patient setup (CBCT{sub setup}). The online adaptive replanning procedure we propose consists of a 6D registration-based mapping of the reference plan onto actual CBCT{sub setup}, followed by a reoptimization of the beam fluences (“6D plan”) to achieve similar dosage as originally was intended, while the patient is lying in the linac couch and the original beam arrangement is kept. The goodness of the online adaptive method proposed was retrospectively analyzed for 16 patients with 35 targets treated with CBCT-based frameless intensity modulated technique. Simulation of reference plan onto actual CBCT{sub setup}, according to the 4 degrees of freedom, supported by linac couch was also generated for each case (4D plan). Target coverage (D99%) and conformity index values of 6D and 4D plans were compared with the corresponding values of the reference plans. Although the 4D-based approach does not always assure the target coverage (D99% between 72% and 103%), the proposed online adaptive method gave a perfect coverage in all cases analyzed as well as a similar conformity index value as was planned. Dose-guided radiosurgery approach is effective to assure the dose coverage and conformity of an intracranial target volume, avoiding resetting the patient inside the mask in a “trial and error” way so as to remove the pitch and roll errors when a robotic table is not available.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Automatic tuning of the Community Atmospheric Model (CAM5) by using short-term hindcasts with an improved downhill simplex optimization method

Traditional trial-and-error tuning of uncertain parameters in global atmospheric general circulation models (GCMs) is time consuming and subjective. This study explores the feasibility of automatic optimization of GCM parameters for fast physics by using short-term hindcasts. An automatic workflow is described and applied to the Community Atmospheric Model (CAM5) to optimize several parameters in its cloud and convective parameterizations. We show that the auto-optimization leads to 10 % reduction of the overall bias in CAM5, which is already a well-calibrated model, based on a predefined metric that includes precipitation, temperature, humidity, and longwave/shortwave cloud forcing. The computational cost of the entire optimization procedure is about equivalent to a single 12-year atmospheric model simulation. The tuning reduces the large underestimation in the CAM5 longwave cloud forcing by decreasing the threshold relative humidity and the sedimentation velocity of ice crystals in the cloud schemes; it reduces the overestimation of precipitation by increasing the adjustment time in the convection scheme. The physical processes behind the tuned model performance for each targeted field are discussed. Limitations of the automatic tuning are described, including the slight deterioration in some targeted fields that reflect the structural errors of the model. It is pointed out that automatic tuning can be a viable supplement to process-oriented model evaluations and improvement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A spherical harmonic transform approach to the indexing of electron back-scattered diffraction patterns

A new approach is proposed for the indexing of electron back-scattered diffraction (EBSD) patterns. The algorithm employs a spherical master EBSD pattern and computes its cross-correlation with a back-projected experimental pattern using the spherical harmonic transform (SHT). This approach is significantly faster than the recent dictionary indexing algorithm, but shares the latter’s robustness against noise. The underlying theory is presented, followed by example applications, one on a series of Ni EBSD data sets recorded with decreasing signal-to-noise ratio, the other on a large shot-peened Al data set. The dependence of indexing speed and memory usage on the SHT bandwidth is explored. The speed gains of the new algorithm are achieved by executing real-valued Fast Fourier Transforms, explicitly incorporating crystallographic symmetry in the cross-correlation computation, and using efficient loop ordering to improve the caching behavior. The algorithm produces a cross-correlation array in the zyz Euler space; an orientation refinement procedure is proposed based on analytical derivatives of the Wigner d functions. As a result, the new approach can be applied to any diffraction modality for which the scattered intensity can be represented on a spherical surface.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives precisely the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-50: Evaluation of Monte Carlo Simulations Performance for Pediatric Brachytherapy Dosimetry

Purpose: Pediatric tumors are generally treated with multi-modal procedures. Brachytherapy can be used with pediatric tumors, especially given that in this patient population low toxicity on normal tissues is critical as is the suppression of the probability for late malignancies. Our goal is to validate the GATE toolkit on realistic brachytherapy applications, and evaluate brachytherapy plans on pediatrics for accurate dosimetry on sensitive and critical organs of interest. Methods: The GATE Monte Carlo (MC) toolkit was used. Two High Dose Rate (HDR) 192Ir brachytherapy sources were simulated (Nucletron mHDR-v1 and Varian VS2000), and fully validated using the AAPM and ESTRO protocols. A realistic brachytherapy plan was also simulated using the XCAT anthropomorphic computational model .The simulated data were compared to the clinical dose points. Finally, a 14 years old girl with vaginal rhabdomyosarcoma was modelled based on clinical procedures for the calculation of the absorbed dose per organ. Results: The MC simulations resulted in accurate dosimetry in terms of dose rate constant (Λ), radial dose gL(r) and anisotropy function F(r,θ) for both sources.The simulations were executed using ∼1010 number of primaries resulting in statistical uncertainties lower than 2%.The differences between the theoretical values and the simulated ones ranged from 0.01% up to 3.3%, with the largest discrepancy (6%) being observed in the dose rate constant calculation.The simulated DVH using an adult female XCAT model was also compared to a clinical one resulting in differences smaller than 5%. Finally, a realistic pediatric brachytherapy simulation was performed to evaluate the absorbed dose per organ and to calculate DVH with respect to heterogeneities of the human anatomy. Conclusion: GATE is a reliable tool for brachytherapy simulations both for source modeling and for dosimetry in anthropomorphic voxelized models. Our project aims to evaluate a variety of pediatric brachytherapy schemes using a population of pediatric phantoms for several pathological cases. This study is part of a project that has received funding from the European Union Horizon2020 research and innovation programme under the MarieSklodowska-Curiegrantagreement.No691203.The results published in this study reflect only the authors view and the Research Executive Agency (REA) and the European Commission is not responsible for any use that may be madeof the information it contains.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Systematic measurements of whole-body imaging dose distributions in image-guided radiation therapy

Purpose: The full benefit of the increased precision of contemporary treatment techniques can only be exploited if the accuracy of the patient positioning is guaranteed. Therefore, more and more imaging modalities are used in the process of the patient setup in clinical routine of radiation therapy. The improved accuracy in patient positioning, however, results in additional dose contributions to the integral patient dose. To quantify this, absorbed dose measurements from typical imaging procedures involved in an image-guided radiation therapy treatment were measured in an anthropomorphic phantom for a complete course of treatment. The experimental setup, including the measurement positions in the phantom, was exactly the same as in a preceding study of radiotherapy stray dose measurements. This allows a direct combination of imaging dose distributions with the therapy dose distribution. Methods: Individually calibrated thermoluminescent dosimeters were used to measure absorbed dose in an anthropomorphic phantom at 184 locations. The dose distributions from imaging devices used with treatment machines from the manufacturers Accuray, Elekta, Siemens, and Varian and from computed tomography scanners from GE Healthcare were determined and the resulting effective dose was calculated. The list of investigated imaging techniques consisted of cone beam computed tomography (kilo- and megavoltage), megavoltage fan beam computed tomography, kilo- and megavoltage planar imaging, planning computed tomography with and without gating methods and planar scout views. Results: A conventional 3D planning CT resulted in an effective dose additional to the treatment stray dose of less than 1 mSv outside of the treated volume, whereas a 4D planning CT resulted in a 10 times larger dose. For a daily setup of the patient with two planar kilovoltage images or with a fan beam CT at the TomoTherapy unit, an additional effective dose outside of the treated volume of less than 0.4 mSv and 1.4 mSv was measured, respectively. Using kilovoltage or megavoltage radiation to obtain cone beam computed tomography scans led to an additional dose of 8-46 mSv. For treatment verification images performed once per week using double exposure technique, an additional effective dose of up to 18 mSv was measured. Conclusions: Daily setup imaging using kilovoltage planar images or TomoTherapy megavoltage fan beam CT imaging can be used as a standard procedure in clinical routine. Daily kilovoltage and megavoltage cone beam computed tomography setup imaging should be applied on an individual or indication based protocol. Depending on the imaging scheme applied, image-guided radiation therapy can be administered without increasing the dose outside of the treated volume compared to therapies without image guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework

In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great uncertainty in the Community Land Model (CLM) for a given value of the output LH. The unknown parameters include those that have been identified as the most influential factors on the simulations of surface and subsurface runoff, latent and sensible heat fluxes, and soil moisture in CLM4.0. We set up the inversion problem in the Bayesian framework in two steps: (i) building a surrogate model expressing the input–output mapping, and (ii) performing inverse modeling and computing the posterior distributions of the input parameters using observation data for a given value of the output LH. The development of the surrogate model is carried out with a Bayesian procedure based on the variable selection methods that use gPC expansions. Our approach accounts for bases selection uncertainty and quantifies the importance of the gPC terms, and, hence, all of the input parameters, via the associated posterior probabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Real-time x-ray fluoroscopy-based catheter detection and tracking for cardiac electrophysiology interventions

Purpose: X-ray fluoroscopically guided cardiac electrophysiology (EP) procedures are commonly carried out to treat patients with arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of a three-dimensional (3D) roadmap derived from preprocedural volumetric images can be used to add anatomical information. It is useful to know the position of the catheter electrodes relative to the cardiac anatomy, for example, to record ablation therapy locations during atrial fibrillation therapy. Also, the electrode positions of the coronary sinus (CS) catheter or lasso catheter can be used for road map motion correction.Methods: In this paper, the authors present a novel unified computational framework for image-based catheter detection and tracking without any user interaction. The proposed framework includes fast blob detection, shape-constrained searching and model-based detection. In addition, catheter tracking methods were designed based on the customized catheter models input from the detection method. Three real-time detection and tracking methods are derived from the computational framework to detect or track the three most common types of catheters in EP procedures: the ablation catheter, the CS catheter, and the lasso catheter. Since the proposed methods use the same blob detection method to extract key information from x-ray images, the ablation, CS, and lasso catheters can be detected and tracked simultaneously in real-time.Results: The catheter detection methods were tested on 105 different clinical fluoroscopy sequences taken from 31 clinical procedures. Two-dimensional (2D) detection errors of 0.50 {+-} 0.29, 0.92 {+-} 0.61, and 0.63 {+-} 0.45 mm as well as success rates of 99.4%, 97.2%, and 88.9% were achieved for the CS catheter, ablation catheter, and lasso catheter, respectively. With the tracking method, accuracies were increased to 0.45 {+-} 0.28, 0.64 {+-} 0.37, and 0.53 {+-} 0.38 mm and success rates increased to 100%, 99.2%, and 96.5% for the CS, ablation, and lasso catheters, respectively. Subjective clinical evaluation by three experienced electrophysiologists showed that the detection and tracking results were clinically acceptable.Conclusions: The proposed detection and tracking methods are automatic and can detect and track CS, ablation, and lasso catheters simultaneously and in real-time. The accuracy of the proposed methods is sub-mm and the methods are robust toward low-dose x-ray fluoroscopic images, which are mainly used during EP procedures to maintain low radiation dose.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SURROGATE MODEL DEVELOPMENT AND VALIDATION FOR RELIABILITY ANALYSIS OF REACTOR PRESSURE VESSELS

In nuclear light water reactors (LWRs), the reactor coolant, core and shroud are contained within a massive, thick walled steel vessel known as a reactor pressure vessel (RPV). Given the tremendous size of these structures, RPVs typically contain a large population of pre-existing flaws introduced in the manufacturing process. After many years of operation, irradiation-induced embrittlement makes these vessels increasingly susceptible to fracture initiation at the locations of the pre-existing flaws. Because of the uncertainty in the loading conditions, flaw characteristics and material properties, probabilistic methods are widely accepted and used in assessing RPV integrity. The Fracture Analysis of Vessels – Oak Ridge (FAVOR) computer program developed by researchers at Oak Ridge National Laboratory is widely used for this purpose. This program can be used in order to perform deterministic and probabilistic risk-informed analyses of the structural integrity of an RPV subjected to a range of thermal-hydraulic events. FAVOR uses a one-dimensional representation of the global response of the RPV, which is appropriate for the beltline region, which experiences the most embrittlement, and employs an influence coefficient technique to rapidly compute stress intensity factors for axis-aligned surface-breaking flaws. The Grizzly code is currently under development at Idaho National Laboratory (INL) to be used as a general multiphysics simulation tool to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled RPVs. Grizzly can be used to model the thermo-mechanical response of an RPV under transient conditions observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local 3D models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. To use Grizzly for probabilistic analysis, it is necessary to have a way to rapidly evaluate stress intensity factors. To accomplish this goal, a reduced order model (ROM) has been developed to efficiently represent the behavior of a detailed 3D Grizzly model used to calculate fracture parameters. This approach uses the stress intensity factor influence coefficient method that has been used with great success in FAVOR. Instead of interpolating between tabulated solutions, as FAVOR does, the ROM approach uses a response surface methodology to compute fracture solutions based on a sampled set of results used to train the ROM. The main advantages of this approach are that the process of generating the training data can be fully automated, and the procedure can be readily used to consider more general flaw configurations. This paper demonstrates the procedure used to generate a ROM to rapidly compute stress intensity factors for axis-aligned flaws. The results from this procedure are in good agreement with those produced using the traditional influence coefficient interpolation procedure, which gives confidence in this method. This paves the way for applying this procedure for more general flaw configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗