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At least 721 records · Page 40

TH-CD-207B-03: How to Quantify Temporal Resolution in X-Ray MDCT Imaging?

Purpose: In modern CT scanners, a quantitative metric to assess temporal response, namely, to quantify the temporal resolution (TR), remains elusive. Rough surrogate metrics, such as half of the gantry rotation time for single source CT, a quarter of the gantry rotation time for dual source CT, or measurements of motion artifact’s size, shape, or intensity have previously been used. In this work, a rigorous framework which quantifies TR and a practical measurement method are developed. Methods: A motion phantom was simulated which consisted of a single rod that is in motion except during a static period at the temporal center of the scan, termed the TR window. If the image of the motion scan has negligible motion artifacts compared to an image from a totally static scan, then the system has a TR no worse than the TR window used. By repeating this comparison with varying TR windows, the TR of the system can be accurately determined. Motion artifacts were also visually assessed and the TR was measured across varying rod motion speeds, directions, and locations. Noiseless fan beam acquisitions were simulated and images were reconstructed with a short-scan image reconstruction algorithm. Results: The size, shape, and intensity of motion artifacts varied when the rod speed, direction, or location changed. TR measured using the proposed method, however, was consistent across rod speeds, directions, and locations. Conclusion: Since motion artifacts vary depending upon the motion speed, direction, and location, they are not suitable for measuring TR. In this work, a CT system with a specified TR is defined as having the ability to produce a static image with negligible motion artifacts, no matter what motion occurs outside of a static window of width TR. This framework allows for practical measurement of temporal resolution in clinical CT imaging systems. Funding support: GE Healthcare; Conflict of Interest: Employee, GE Healthcare.

60 APPLIED LIFE SCIENCES↗

SU-G-JeP3-10: Update On a Real-Time Treatment Guidance System Using An IR Navigation System for Pleural PDT

Purpose: Photodynamic therapy (PDT) is used in conjunction with surgical debulking of tumorous tissue during treatment for pleural mesothelioma. One of the key components of effective PDT is uniform light distribution. Currently, light is monitored with 8 isotropic light detectors that are placed at specific locations inside the pleural cavity. A tracking system with real-time feedback software can be utilized to improve the uniformity of light in addition to the existing detectors. Methods: An infrared (IR) tracking camera is used to monitor the movement of the light source. The same system determines the pleural geometry of the treatment area. Software upgrades allow visualization of the pleural cavity as a two-dimensional volume. The treatment delivery wand was upgraded for ease of light delivery while incorporating the IR system. Isotropic detector locations are also displayed. Data from the tracking system is used to calculate the light fluence rate delivered. This data is also compared with in vivo data collected via the isotropic detectors. Furthermore, treatment volume information will be used to form light dose volume histograms of the pleural cavity. Results: In a phantom study, the light distribution was improved by using real-time guidance compared to the distribution when using detectors without guidance. With the tracking system, 2D data can be collected regarding light fluence rather than just the 8 discrete locations inside the pleural cavity. Light fluence distribution on the entire cavity can be calculated at every time in the treatment. Conclusion: The IR camera has been used successfully during pleural PDT patient treatment to track the motion of the light source and provide real-time display of 2D light fluence. It is possible to use the feedback system to deliver a more uniform dose of light throughout the pleural cavity.

60 APPLIED LIFE SCIENCES↗

Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a better performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.

acoustic↗

A compact ultra-clean system for deploying radioactive sources inside the KamLAND detector

We describe a compact, ultra-clean device used to deploy radioactive sources along the vertical axis of the KamLAND liquid-scintillator neutrino detector for purposes of calibration. The device worked by paying out and reeling in precise lengths of a hanging, small-gauge wire rope (cable); an assortment of interchangeable radioactive sources could be attached to a weight at the end of the cable. All components exposed to the radiopure liquid scintillator were made of chemically compatible UHV-cleaned materials, primarily stainless steel, in order to avoid contaminating or degrading the scintillator. To prevent radon intrusion, the apparatus was enclosed in a hermetically sealed housing inside a glove box, and both volumes were regularly flushed with purified nitrogen gas. Finally, an infrared camera attached to the side of the housing permitted real-time visual monitoring of the cable’s motion, and the system was controlled via a graphical user interface.

42 ENGINEERING↗

Rasterization with Data-Parallel Primitives

Parallel rasterization can suffer from race conditions during fragment generation, which is traditionally addressed by using specialized hardware accessible via vendor graphics APIs. Unfortunately, graphics APIs are increasingly problematic on high-performance computers, either because they are not provided or because of concerns about dependencies with in situ visualization. In response, we present a hardware-agnostic rasterization algorithm that handles race conditions using only data-parallel primitives (DPPs), enabling efficient rendering on HPC systems without graphics API dependencies and aligning with recent efforts to deliver visualization software with DPPs. Our evaluation consists of three phases: (1) evaluating portability across different CPU and GPU architectures, (2) evaluating competitiveness with a community standard, and (3) evaluating performance across varying workloads and available parallelism. The supporting experiments run on both AMD and NVIDIA GPUs, considering data sets as large as 460 million triangles and 160 million pixels. While performance generally falls short of graphics API baselines, it achieves interactive frame rates on most workloads. As a result, we conclude our approach is a viable solution for rasterization on high-performance computers since our approach is portably performant across different architectures without the need for specialized vendor support.

Buckley, Makani [University of Oregon] (ORCID:0009↗

Applications of visualization technology in the structural sciences

The structural sciences are undergoing a transformation driven by advancements in visualization technologies that aid researchers in understanding and communicating experimental data from complex molecular systems. New applications of integrative structural biological and biophysical approaches add a wide variety of complementary information from a broad range of scientific disciplines. These approaches extend structural biophysical methodologies to enable research by the incorporation of a variety of data streams and utilization of tools like molecular graphics, virtual reality, and machine learning. To redefine how structural data—particularly from cryo-electron microscopy and x-ray crystallography—are fed forward for scientific exploration and communication, the advances in tools for data visualization and interpretation have been critical. By bringing molecular systems into an interactive three-dimensional space, these novel technologies enhance research workflows, facilitate structure-based drug design, and create engaging educational experiences. Taken together, these visualization innovations are essential tools for advancing the field by making concepts more accessible and compelling.

Eng, Edward T. [New York Structural Biology Center↗

Molecular reorganization in bulk bottlebrush polymers: direct observation via nanoscale imaging

Bottlebrush polymers are important for a variety of applications ranging from drug delivery to electronics. The functional flexibility of the branched sidechains has unique assembly properties when compared to linear block polymer systems. However, reports of direct observation of molecular reorganization have been sparse. This information is necessary to enhance the understanding of the structure–property relationships in these systems and yield a rational design approach for novel polymeric materials. In this work, we report direct visualization of bottlebrush molecular organization and the formation of nematic-type ordering in an amorphous polymer bottlebrush system, captured with plasma etching and helium ion microscopy. By observing the unperturbed structure of this material at high resolution and quantifying image features, we were able to qualitatively link experimental results with structures predicted by coarse-grained molecular dynamics simulations. Here, the direct visualization and computation workflow developed in this work can be applied to a broad variety of polymers with different architectures, linking imaging results with other, independent channels of information for better understanding and control of these classes of materials.

36 MATERIALS SCIENCE↗

Exploratory Data analysis ENvironment eXtreme scale (EDENx)

EDENx is a multivariate data visualization tool that allows interactive user driven analysis of large-scale data sets with high dimensionality. EDENx builds on our earlier system, called EDEN to enable analysis of more dimensions and larger scale data sets. EDENx provides an initial overview of summary statistics for each variable in the data set under investigation. EDENx allows the user to interact with graphical summary plots of the data to investigate subsets and their statistical associations. These plots include histograms, binned scatterplots, binned parallel coordinate plots, timeline plots, and graphical correlation indicators. From the EDENx interface, a user can select a subsample of interest and launch a more detailed data visualization via the EDEN system. EDENx is best suited for high-level, aggregate analysis tasks while EDEN is more appropriate for detail data investigations.

Steed, Chad Allen↗

Lighting Studies for Fuelling Machine Deployed Visual Inspection Tool

Under subcontract to James Fisher Nuclear, Ltd., INL has been reviewing advanced vision systems for inspection of graphite in high radiation, high temperature, and high pressure environments. INL has performed calculations and proof-of-principle measurements of optics and lighting techniques to be considered for visual inspection of graphite fuel channels in AGR reactors in UK.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Systems and methods for vehicle propulsion recommendation

A method for providing a visual driving speed recommendation to an operator of a vehicle includes determining a current speed; determining a corresponding energy efficient speed; determining a higher corresponding less energy efficient speed; determining a first transition range between the corresponding energy efficient speed and the higher corresponding less energy efficient speed; and displaying, on a display, a display zone, the display zone comprising: a first indicator corresponding to the current speed; a first pattern corresponding to the corresponding energy efficient speed; a second pattern different from the first pattern and corresponding to the higher corresponding less energy efficient speed; and a first pattern range therebetween corresponding to the first transition range.

Poull, Claude P.↗

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗

Using Machine Learning to Identify Optimum Prospects for Offshore Geologic CO 2 Storage and Enhanced Oil Recovery in the Gulf of Mexico

The SECARB Offshore Partnership is a government-industry partnership focused on assembling the knowledge base required for secure, long-term, large-scale CO 2 subsea storage in saline formations and mature oil reservoirs. The SECARB Offshore Partnership is evaluating potential storage opportunities in the Central and Eastern planning areas of the outer continental shelf (OCS) of the Gulf of Mexico. The evaluation focuses on active and depleted oil and gas fields and potentially associated CO 2 -enhanced oil recovery (CO 2 -EOR), as well as, deep saline storage resources. As part of Subtask 3.0 (Offshore Storage Resources Characterization) and Subtask 4.0 (Risk Assessment, Simulation, and Modeling), Oklahoma State University (OSU) is developing a machine learning system that employs the SAS Institute’s Viya platform with visual data mining and machine learning to identify and characterize optimum prospects for enhanced oil recovery and stacked storage in saline reservoirs. This report summarizes this effort to date and discusses the many variables that can be used to characterize these storage objectives, as well as, the design vision of the Viya machine learning system.

02 PETROLEUM↗

Machine Vision-based Robot Manipulators for Nuclear Applications - 20370

Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Science Data Gateway for Environmental Management

Science data gateways are effective in providing complex science data collections to the world-wide user Q1 communities. In this paper we describe a gateway for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Built on top of established web service technologies, the ASCEM data gateway is specifically designed for environmental modeling applications. Its key distinguishing feature sinclude (1) handling of complex spatiotemporal data, (2) offering a variety of selective data access mechanisms, (3) providing state-of-the-art plotting and visualization of spatiotemporal data records, and (4) integrating seamlessly with a distributed workflow system using a RESTful interface. ASCEM projectscientists have been using this data gateway since 2011.

ASCEM, Akuna, Database Management↗

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Final Report: Non-Visible, Automated Target Acquisition and Tracking

The Roadside Tracker (RST) represents a new approach to radiation portal monitors. It uses a combination of gamma-ray and visible-light imaging to localize gamma-ray radiation sources to individual vehicles in free-flowing, multi-lane traffic. Deployed as two trailers that are parked on either side of the roadway (Fig. 1); the RST scans passing traffic with two large gamma-ray imagers, one mounted in each trailer. The system compensates for vehicle motion through the imager’s fields of view by using automated target acquisition and tracking (TAT) software applied to a stream of video images. Once a vehicle has left the field of view, the radiation image of that vehicle is analyzed for the presence of a source, and if one is found, an alarm is sounded. The gamma-ray image is presented to the operator together with the video image of the traffic stream when the vehicle was approximately closest to the system (Fig. 2). The offending vehicle is identified with a bounding box to distinguish it from other vehicles that might be present at the same time. The system was developed under a previous grant from the Department of Homeland Security’s (DHS’s) Domestic Nuclear Detection Office (DNDO). This report documents work performed with follow-on funding from DNDO to further advance the development of the RST. Specifically, the primary thrust was to extend the performance envelope of the system by replacing the visible-light video cameras used by the TAT software with sensors that would allow operation at night and during inclement weather. In particular, it was desired to allow operation after dark without requiring external lighting. As part of this work, the system software was also upgraded to allow the use of 64-bit computers, the current generation operating system (OS), software development environment (Windows 7 vs. Windows XP, and current Visual Studio.Net), and improved software version controls (GIT vs. Source Safe.) With the upgraded performance allowed by new computers, and the additional memory available in a 64-bit OS, the system was able to handle greater traffic densities, and this also allowed addition of the ability to handle stop-and-go traffic.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Estimation of Decommissioning Quantity Based on 3D Intelligent Model - 17075

A decommissioning support system for estimating waste quantity was developed on the basis of three dimensional models for projects to decommission nuclear power plants. On the basis of the developed system, the spatial distribution of the dose rate surrounding equipment and piping components can be visualized, and the number of containers required to store segmented waste objects can be counted. We confirm that the developed system can support decommissioning engineering systematically and effectively because of its ability to map radioactive inventory data to 3D objects to automatically calculate the dose rate and generate waste container models. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗