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At least 1,117 records · Page 62

Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages

This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multiscale Approach to Fast ModSim for Laser Processing of Metals for Future Nuclear Deterrence Environments

Predicting performance of parts produced using laser-metal processing remains an out- standing challenge. While many computational models exist, they are generally too computationally expensive to simulate the build of an engineering-scale part. This work develops a reduced order thermal model of a laser-metal system using analytical Green's function solutions to the linear heat equation, representing a step towards achieving a full part performance prediction in an "overnight" time frame. The developed model is able to calculate a thermal history for an example problem 72 times faster than a traditional FEM method. The model parameters are calibrated using a non-linear solution and microstructures and residual stresses calculated and compared to a non-linear case. The calibrated model shows promising agreement with a non-linear solution.

36 MATERIALS SCIENCE↗

Stockpile Assessment (Quad Chart)

Our goal was to characterize certain aspects of shaped charges. In order to determine the pressure field created by the jet and the jet velocity, I worked with and modified simulations using CTH, a code developed at Sandia. I was able to manipulate and modify certain variables in order to observe their effects and measure the pressure and velocities at different points in the simulation.

42 ENGINEERING↗

Evaluation of Used Fuel Disposition in Clay-Bearing Rock

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key advances in experimental and modeling aspects of chemical and physical phenomena towards the long-term safety assessment of nuclear waste disposition in deep clay/shale/argillaceous rock. Experimental activities on clay barrier interactions with fluids and radionuclides provide the much needed knowledge to evaluate engineered barrier system (EBS) performance. Thermal-Hydrological-Mechanical-Chemical (THMC) model development of clay provides a rigorous simulation platform to assess the complex dynamic behavior of engineered and natural barrier materials in response to coupled process phenomena induced by heat-generating nuclear waste. This report describes the ongoing disposal R&D efforts on the advancement and refinement of coupled THMC process models, hydrothermal experiments and geochemical modeling of on barrier material (clay/metal) interactions, spent fuel and canister material degradation, radiolytic phenomena and UO 2 degradation, and thermodynamic database development. These play an important role to the evaluation of sacrificial zones as part of the EBS exposure to thermally-driven chemical and transport processes. Clay-zeolite phase equilibria play a key role in the mineralogical transformations of clay barrier conducive to loss in swelling properties but also in controlling H 2 0 uptake/release through hydration/dehydration reactions. The result is volume changes can affect the interface / bulk phase porosities, transport, and the mechanical (stress) state of the bentonite barrier. Characterization studies on barrier samples (bentonite/cement) from controlled tests at underground research laboratories (URLs) provide key insights into barrier materials interactions at EBS interfaces. Spent fuel degradation modeling coupled with canister and cladding corrosion effects demonstrate the strong influence of H 2 generation on the source term.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Constrained Bayesian Optimization of Criticality Experiments [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗

A New Reduced Order Model For The Mechanistic Creep Behavior Of UO 2

This manuscript describes an ongoing NEAMS effort to better determine the performance of advanced nuclear fuels, in particular the creep behavior of doped UO$_2$ for light water reactors. In our previous work, we outlined a method to utilize data generated from lower length scale simulations and implement it into the engineering scale fuel performance analysis. This process has been further refined, and in addition, new data has been used to train the surrogate model which has also been substantially improved since the previous iteration. The new model is compared against the current empirical model used in BISON using both scoping calculations to define the performance over the parameter space and using integral instrumented fuel assessment cases to determine the impact of these models on the overall fuel performance. Suggestions and guidance for future improvements to this method are provided to ensure the model covers relevant parameter space and phenomena.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hardened Novikov Gears as the Last Stage of General-Purpose Gear Systems

The creation of general-purpose gear systems with hardened Novikov gears of relatively low precision is considered. By solving three-dimensional elastic-contact problems and modeling, the replacement of expensive high-precision involute gears in the final stage of general-purpose gear systems by less expensive hardened Novikov gears of lower precision is shown to be expedient. Preliminary calculations of prospective high-precision Novikov gears are presented. They offer considerable advantages over their involute counterparts.

42 ENGINEERING↗

Virtual Testing in Assembly

The possibility of improving the manufacture of high-precision products by means of virtual assembly is considered. Such technology is found to significantly improve the assembly process and to reduce the associated costs.

42 ENGINEERING↗

Radioactive Demonstrations Of Fluidized Bed Steam Reforming (FBSR) With Hanford Low Activity Wastes

Several supplemental technologies for treating and immobilizing Hanford low activity waste (LAW) are being evaluated. One immobilization technology being considered is Fluidized Bed Steam Reforming (FBSR) which offers a low temperature (700-750?C) continuous method by which wastes high in organics, nitrates, sulfates/sulfides, or other aqueous components may be processed into a crystalline ceramic (mineral) waste form. The granular waste form produced by co-processing the waste with kaolin clay has been shown to be as durable as LAW glass. The FBSR granular product will be monolithed into a final waste form. The granular component is composed of insoluble sodium aluminosilicate (NAS) feldspathoid minerals such as sodalite. Production of the FBSR mineral product has been demonstrated both at the industrial, engineering, pilot, and laboratory scales on simulants. Radioactive testing at SRNL commenced in late 2010 to demonstrate the technology on radioactive LAW streams which is the focus of this study.

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Process Simulation Role in the Development of New Alloys Based on Integrated Computational Material Science and Engineering

To accelerate the introduction of new materials and components, the development of metal casting processes requires the teaming between different disciplines, as multi-physical phenomena have to be considered simultaneously for the process design and optimization of mechanical properties. The required models for physical phenomena as well as their validation status for metal casting are reviewed. The data on materials properties, model validation, and relevant microstructure for materials properties are highlighted. One vehicle to accelerate the development of new materials is through combined experimental-computational efforts. Integrated computational/experimental practices are reviewed; strengths and weaknesses are identified with respect to metal casting processes. Specifically, the examples are given for the knowledge base established at Oak Ridge National Laboratory and computer models for predicting casting defects and microstructure distribution in aluminum alloy components.

Sabau, Adrian S↗

Code Comparison Study Fosters Confidence in the Numerical Simulation of Enhanced Geothermal Systems

Numerical simulation has become a standard analytical tool for scientists and engineers to evaluate the potential and performance of enhanced geothermal systems. A variety of numerical simulators developed by industry, universities, and national laboratories are currently available and being applied to better understand enhanced geothermal systems at the field scale. To yield credible predictions and be of value to site operators, numerical simulators must be able to accurately represent the complex coupled processes induced by producing geothermal systems, such as fracture aperture changes due to thermal stimulation, fracture shear displacement with fluid injection, rate of thermal depletion of reservoir rocks, and permeability alteration with mineral precipitation or dissolution. A suite of numerical simulators was exercised on a series of test problems that considered coupled thermal, hydraulic, geomechanical, and geochemical (THMC) processes. Problems were selected and designed to isolate selected coupled processes, to be executed on workstation class computers, and have simple but illustrative metrics for result comparisons. This paper summarizes the initial suite of seven benchmark problems, describes the code comparison activities, provides example results for problems and documents the capabilities of currently available numerical simulation codes to represent coupled processes that occur during the production of geothermal resources. Code comparisons described in this paper use the ISO (International Organization for Standardization) standard ISO-13538 for proficiency testing of numerical simulators. This approach was adopted for a recent code comparison study within the radiation transfer-modeling field of atmospheric sciences, which was focused on canopy reflectance models. This standard specifies statistical methods for analyzing laboratory data from proficiency testing schemes to demonstrate that the measurement results do not exhibit evidence of an unacceptable level of bias.

benchmark problems↗

Fission gas swelling in U{sub 3}Si{sub 2} at LWR conditions

In order to evaluate the feasibility of replacing uranium dioxide fuel with U{sub 3}Si{sub 2} fuel, it is crucial to examine the fuel performance of the silicide fuel under typical LWR conditions. At this early stage of U{sub 3}Si{sub 2} fuel development, before undertaking costly in-pile irradiation experiments and corresponding post-irradiation examinations, it is appropriate to utilize modeling tools to estimate the behavior of U{sub 3}Si{sub 2} in LWRs based on available in-pile irradiation experiments as well as the state-of-the-art calculation capabilities provided by density functional theory (DFT). Therefore, a comprehensive investigation of the fission gas swelling behavior of U{sub 3}Si{sub 2} at LWR conditions is reported here. The modeling efforts in this study are based on the Gas Release and Swelling Subroutine for Steady-State and Transient (GRASS-SST) rate theory (RT) model of fission gas bubble evolution that has been successfully applied to a variety of fuel materials in numerous types of reactors. Both existing in-pile irradiation data and DFT-based calculations were used for the optimized parametrization of the RT model. In addition, the fuel-cladding interaction was captured by coupling the RT model with simplified mechanical correlations. Both the swelling behavior and the fission gas bubble size distribution were predicted by the rate theory model. At LWR conditions, the RT model predicts that intragranular bubbles dominate the gaseous swelling behavior and that the evolution of intergranular bubbles and corresponding gas release are suppressed, confirming the qualification of U{sub 3}Si{sub 2} as a LWR fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydraulic and mixing evaluations for SRS miscible liquid solutions

The hydraulic results demonstrate that pump head pressure of 20 psi recirculates about 5.6 liters/min flowrate through the existing 0.131-inch orifice when a valve connected to NT-41 is closed. In case of the valve open to NT-41, the solution flowrates to Savannah River Site (SRS) tanks, NT-21 and NT-41, are found to be about 0.5 lpm and 5.2 lpm, respectively. The modeling calculations for the mixing operations of miscible fluids contained in the SRS HB-Line tank NT-21 were performed by taking a three-dimensional Computational Fluid Dynamics (CFD) approach. The CFD modeling results were benchmarked against the literature results and the previous SRNL test results to validate the model. Final performance calculations were performed for the nominal case by using the validated model to quantify the mixing time for the HB-Line tank. The results demonstrate that when a pump recirculates a solution volume of 5.7 liters every minute out of the 72-liter tank contents containing two acid solutions of 2.7 M and 0 M concentrations (i.e., water), a minimum mixing time of 1.5 hours is adequate for the tank contents to get the tank contents adequately mixed. In addition, the sensitivity results for the tank contents of 8 M existing solution and 1.5 M incoming species show that the mixing time takes about 2 hours to get the solutions mixed. (authors)

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R and DE Robotic Sensor Intern Team: Remote 3D Mapping Sensor Suite

The primary goal of the sensor suite is to provide an internal 3D map of the HCAEX tunnel. When looking for a sensor that would provide XYZ point cloud data for mapping the decision was between a stereo camera, a 3D Lidar, or a 2D Lidar that would need to be spun around. The issues with the stereo camera were that it does not have a large field-of-view and that its depth information was not nearly as accurate as even the baseline Lidars. The selection between Lidars is detailed. The Hokuyo UTM-30LX-EW shown provides a 270 deg. FOV with high accuracy and resolution while the largest FOV on a 3D Lidar is 40 deg.. This was the reason a 2D Lidar was chosen over the 3D Lidar. Even though the 2D Lidar requires additional components and software to generate a 3D map, its FOV advantage is too great given that the HCAEX tunnel is a relatively confined space. The rotating planar scan from the 2D Lidar can be stitched into a 3D scan as shown in the graphic below. Along with XYZ data, the Lidar provides return intensity data in color which can be used to distinguish between different materials within the tunnel. To provide visual feedback a camera system needed to be identified. The common solution for this is a high resolution camera with a small FOV mounted on a pan-tilt system. But, given the critical nature of the visual feedback we looked into solutions without the need for moving parts. Two panospheric cameras give a FOV large enough to get a full 360 deg. view.. Camera color data (RGB) can also be combined with the 3D mapping data from the Lidar and overlaid on the map to give the user the ability to see inside the entire length of the tunnel as if they were inside. Situational awareness is required for the crawler in the tunnel in order for it to be able to register the 3D scans to create a final map. For this we procured a Microstrain 3DM-GX5-25 Inertial Measurement Unit (IMU). To perform the Lidar rotation we have two servos driving the pan and tilt. The servo controls and most data processing will be performed via an onboard computer. The sensor components are to be packaged together using 3D printed mounts into a standalone unit.

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R and DE Robotic Sensor Intern Team: Sensor Suite Software and User Interface

The sensor tree developed for the H-Canyon tunnel inspection project produces a large quantity of camera and Lidar data. A postprocessing pipeline was created to facilitate the analysis of these data. The pipeline follows the following routine: 1) Registration - Salient local features in subsequent scans are identified and used to align the scans with one another. This allows production of a single cohesive map of the tunnel. 2) Sensor Fusion - RGB camera data is 'painted' onto the depth data created by the Lidar. 3) Segmentation - Individual surfaces from within the scene are segmented out separately for individual analysis. 4) Degradation Analysis - Automatic mapping of local deviation from the plane in position or surface normal is performed, as is detection of exposed rebar using Lidar return intensity. 5) Obstacle Detection - Lidar data is also used in real time to detect obstacles in the environment. This could give feedback to the operator to successfully drive in the tunnel. 6) Graphic User Interface - a custom GUI was created to facilitate customer use of the system. The system provides real-time feedback from both the cameras and Lidar. During alignment, local features are used to recognize points within the walls that are especially unique and noticeable (salient) based on their deviation from the expected surface of the wall. These are used as landmarks to register the clouds, which also informs precise localization of the base at each scan point. After registration, clouds are 'painted' with RGB data from the spherical cameras, as shown below. The painted clouds provide a 3D, colorized model of the environment which improves the realism of the experience for the user. Painting also labels high-resolution color imagery from the 3D cameras with depth values. Following sensor fusion, individual walls and cylindrical duct surfaces are segmented from the scene for individual analysis using a Random Sample Consensus algorithm. This algorithm allows segmentation of planar walls and cylindrical ducts. Once individual walls are identified, each point within the wall can be compared to its neighbors and the wall overall in order to detect local areas with damaged concrete. Automatic rebar detection is also performed using the contrast in Lidar return intensity between iron and concrete. The Lidar point-cloud data is also used for obstacle detection. As the Lidar spins, various algorithms are run to analyze the current 'slice' and obstacles in the environment are determined and registered on a cost-map. A Graphical User Interface (GUI) was developed to allow the user to easily command the crawler to set the rotational speed of the Lidar, perform a scan, and register and save the 3D generated cloud after a scan is done. For the good of the crawler, a critical aspect of the GUI design is to allow the user to cancel a scan any time after it is commanded and before it is saved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗