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DOE OSTI2022

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Forecasting for the Weather Driven Energy System - A New Task under IEA Wind

The energy system needs a range of forecast types for its operation in addition to the narrow wind power forecast that has been the focus of considerable recent attention. Therefore, the group behind the former IEA Wind Task 36 Forecasting for Wind Energy has initiated a new IEA Wind Task with a much broader perspective, which includes prospective interaction with other IEA Technology Collaboration Programmes such as the ones for PV, hydropower, system integration, hydrogen etc. In the new IEA Wind Task 51 (entitled "Foreacsting for the Weather Drive Energy System") the existing Work Packages (WPs) are complemented by work streams in a matrix structure. The Task is divided in three WPs according to the stakeholders: WP1 is mainly aimed at meteorologists, providing the weather forecast basis for the power forecasts. In WP2, the forecast service vendors are the main stakeholders, while the end users populate WP3. The new Task 51 started in January 2022. Planned activities include 4 workshops. The first will focus on the state of the art in forecasting for the energy system plus related research issues and be held during September 2022 in Dublin. The other three workshops will be held later during the 4-year Task period and address (1) seasonal forecasting with emphasis on Dunkelflaute, storage and hydro, (2) minute-scale forecasting, and (3) extreme power system events. The issues and conclusions of each of the workshops will be documented by a published paper. Additionally, the Recommended Practice on Forecast Solution Selection will be updated to reflect the broader perspective.

geophysics computing↗

DOE OSTI2016

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task-based optimization framework provides a promising approach that maximizes imaging performance under the same total dose constraint.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance

The rise of the accelerator-based architectures and reconfigurable computing have showcased the weakness of software stack toolchains that still maintain a static view of the hardware instead of relying on a symbiotic relationship between static (e.g., compilers) and dynamic tools (e.g., runtimes). In the past decades, this need has given rise to adaptive runtimes with increasingly finer computational tasks. These finer tasks help to take advantage of the hardware by switching out when a long latency operation is encountered (because of the deeper memory hierarchies and new memory technologies that might target streaming instead of random access), thus trading off idle time for unrelated work. Examples of these finer task runtimes are Asynchronous Many Task (AMT) runtimes, in which highly efficient computational graphs run on a variety of hardware. Due to its inherent latency tolerant characteristics, Latency-sensitive applications, such as Graph Analytics and Big Data can effectively use these runtimes. This paper aims to present an example of how the careful design of an AMT can exploit the hardware substrate when faced with high latency applications such as the ones given in the Big Data domain. Moreover, with its introspection and adaptive capabilities, we aim to show the power of these runtimes when facing the changing requirements of the application workloads. We use the Performance Open Community Runtime (P-OCR) as our vehicle to demonstrate the concepts presented here.

adaptive runtime, big data analysis↗

DOE OSTI2023

Task 5: Developing a Tool to Quantify Liability of Geologic Carbon Storage

This talk provides an overview of work being done on NRAP Phase 3 Task 5. Task 5 involves the liability or cost of responding to potential adverse events. The focus of Task 5 is on the cost of responding to potential leakage of CO2 and brine out of the storage formation or induced seismic incidents.

Morgan, David↗

DOE OSTI2018

Remotely Teleoperating a Humanoid Robot to Perform Fine Motor Tasks with Virtual Reality - 18446

In this paper, we describe our ongoing work to develop cooperative control of NASA's R5 Valkyrie humanoid robot for performing dexterous manipulation tasks inside gloveboxes commonly found in many nuclear facilities. These tasks can be physically demanding and provide some element of risk to the operator when done by a person in situ. For example, if a glove is ruptured, the operator could be exposed to radioactive material. In many cases, the operator has low visibility and is unable to reach the entire task space, requiring the use of additional tools located inside the glovebox. Such tasks include cleaning particulate from inside the glovebox via sweeping or vacuuming, separating a specific amount of a compound to be weighed on a scale, or grasping and manipulating objects inside the glovebox. There is potential to move the operator to a nearby, safe location and instead place a humanoid robot in the potentially hazardous environment. However, teleoperating a humanoid robot to perform dexterous tasks at a comparable level to a human hand remains a difficult problem. Previous work for controlling humanoid robots often involves one or more operators using a standard 2D display with a mouse and keyboard as controllers. Successful interfaces use sensor fusion to provide information to the operator for increased situation awareness, but these designs have limitations. Gaining proper situation awareness by visualizing 3D information on a 2D screen requires time and increases the cognitive load on the user. Instead, if the operator is able to visualize and control the robot properly in three dimensions, it can increase situation and task awareness, reduce task time, reduce the chance of mistakes, and increase the likelihood of overall task success. We propose a two-part system that combines an HTC Vive virtual reality headset with either the Vive handheld controllers, or the Manus VR wearable gloves as the primary control. The operator wears the headset in a remote location and can visualize a reconstruction of the glovebox, created live by sensor scans from the robot and with sensors located inside the glovebox for a perspective traditionally unavailable to operators. By using the controllers or gloves to control the humanoid robots hands directly, they can plan actions in the virtual reconstruction. When the operator is satisfied with the plan, the actions are sent to the real robot. To test this system we have created a mockup of a glovebox that is accessible by Valkyrie, as well as several tasks that are a subsample of the tasks that might be required when working in a real glovebox. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Williston Basin CORE-CM Initiative Final Report

The University of North Dakota Energy & Environmental Research Center (EERC) is leading the Williston Basin Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to drive the expansion and transformation of coal and coal-based resource usage within the Williston Basin to produce rare-earth elements (REEs), CMs, and nonfuel carbon-based products (CBPs). This project is the first phase in a long-term program and set the stage for future work by assessing resource, market, technology, and infrastructure knowledge; identifying knowledge gaps; developing a series of plans to be carried out in future work; and initiating stakeholder engagement. Composed of several tasks, the project sought to identify, characterize, and assess several necessary aspects vital to make this future work a reality. The project’s fundamental task was to characterize the Williston Basin CORE-CM resources. Over 2500 samples from multiple sources were utilized to begin the assessment. Several locations were identified in western North Dakota where sample analysis identified the total REE (TREE) concentration as being over 500 parts per million (ppm), which is at a concentration level that would be suitable to consider for mining and extraction. Current operating coal mines have sufficient concentrations of TREEs for consideration. However, the current data across the basin are still not adequate to fully characterize REE and CM content nor give reliable estimates of the total resource potential. Waste stream reuse was also considered, and several streams were identified which ranged from potential energy sources to chemicals to material wastes. This includes streams that result from oil and gas production. These streams are not fully characterized, and further data are needed before they can be accurately assessed. Infrastructure within the Williston Basin is suitable for expansion of a new industry to mine, extract, and concentrate REEs and CMs. The development of this industry will not only preserve many existing jobs in the coal-mining industry but produce many new jobs. The supply chain for REEs and CMs is currently controlled outside of the United States in nations such as China, but the potential to develop the supply chain within the basin is considered possible. Processing of the mined materials for REEs and CMs needs further research. The technology and knowhow exist outside of the United States, and within the country much of the knowledge has been lost and must be regained. To develop the supply chain and regain lost processing technology, the creation of technology innovation centers (TICs) is crucial. The Williston Basin contains several similar centers and entrepreneurial assistance for other industries that can be applied in the development of REE and CM innovation centers. Education to develop the new skill sets required is also needed. Outreach is important for the development of the REE and CM industry within the basin. Understanding throughout federal and state governments, state agencies, industry, and resource end users is vital for the industry to form and grow. Through this project these groups have been contacted through bulletins, presentations, webinars, and annual symposiums. The report is a summary of the work conducted and throughout refers to a series of appendixes which contain more thorough and specific information about each section.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Automated Work Packages: Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Industry

The need to move conventional paper-based work packages into an electronic state motivated the development of a large span of electronic work package forms that ranged from simple Portable Document Format (PDF) files to adaptive and intelligent electronic forms. In parallel to this development, the Department of Energy Light Water Reactor Sustainability Program (LWRS) initiated the automated work package as a pilot project to evaluate implementing state of the art automation techniques into the work package process to improve the economic and safety of the work process. Through a multiple year’s effort, the automated work package project have developed a vision of the future work package that relies on automation in all critical and human factor challenging tasks. The vision identified gaps in the work process, the means to automate them, and evaluated the implementation, feasibility and benefits of these means. This was conducted through continues engagement with the nuclear power industry. The aim of this report is to study the potential of three automation technologies, which have been advancing in various industries, in the current work process of nuclear power plants. The study is to determine the feasibility and benefits of incorporating the technologies and determine potential gaps, if any, that need to be addressed to facilitate deployment of the studied technologies. The three automation technologies identified for this effort are ultra-high frequency (UHF) radio frequency identification (RFID), Bluetooth low energy (BLE) beacons, and video monitoring and recording. As part of this effort, the Idaho National Laboratory (INL) collaborated with Xcel Energy Inc. to evaluate these technologies. During the research and development scope of the effort, INL engaged Xcel Energy Inc. periodically and exchanged valuable insight on the means to implement these technologies in a nuclear power plant. Multiple pilot prototypes were developed and tested in a user study conducted at Xcel Energy Inc. in Minneapolis, Minnesota. The outcome of this effort resulted in significant findings that included the detailed means to custom fit the technologies to fit the nuclear power industry need, and identifying and evaluating several applications of high economic or safety potential. The limitations and obstacles that could impact deployment of the technologies were also identified, and the means of how to address these limitations and obstacles were studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2011

Radiation Transport Evaluations for Repository Science

This technical letter report documents work performed to meet the requirements of Task 4, titled Radiation Transport Evaluations, which is described in the ORNL FY11 Work Package for Repository Science/Criticality Analysis FTOR11UF0334 – DOE-NE Fuel Cycle Technologies Used Fuel Disposition Campaign (WBS: 1.02.08.03).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Beryllium Dynamic Strength Measurements (Report on Task 2, Agreement #B590737)

Goal of the work under Agreement #B590737 is development of experimentally justified model of beryllium shear strength of American production ( Be S200F ) in the pressure range of Р~10÷50 GPa and strain rates up to $\dot{ε_i}$ ≈10 5 ÷10 6 s -1 . The Be shear strength models, which are available in this range of parameters, have no sufficiently reliable experimental justification. Objective of this Task of Agreement #B590737 was demonstration of possibility to perform X-ray radiography recording of perturbation growth in Be in conditions of the R-T instability under quasi-isentropic loading of liners up to pressure P~40÷50 GPa and to perform quantitative measurements. Besides, this report presents data on measurements of liner velocity growth pace where the liner is accelerated by explosion products of HE of the second stage from the two-stage explosive device. The velocity was measured with use of the laser interferometric technique. The obtained experimental data are used for correct calculation of pressure at the boundary of the investigated liner ( Be S200F ) during calibration of the strength model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Preliminary Planning of Radwaste Management for the Decommissioning of Chinshan NPP in Taiwan - 18201

The Chinshan NPP was the first commercially operated nuclear power plant in Taiwan since 1978. There are two BWR units in Chinshan NPP, which each unit has electrical output of 636 MWe. After 40 year's period of license, the final shutdown date of Unit No. 1 and Unit No. 2 will be in December, 2018 and in July, 2019, respectively. According to 'Nuclear Reactor Facilities Regulation Act' in Taiwan, decommissioning of nuclear reactor facilities should be implemented by the strategy of DECON (Decontamination followed by dismantling) within 25 years when the permission is approved by Atomic Energy Council (AEC). The decommissioning plan of Chinshan NPP has been permitted by AEC in the end of June, 2017. The implementation of Chinshan NPP decommissioning will be started while the Environmental Impact Assessment is approved by EPA. In this study, the Turbine Building in Chinshan NPP is selected as a case study for the preliminary planning of decommissioning. First, we thoroughly examine the inventory of all macro-components in the Turbine Building to estimate the waste amounts. Accordingly, the work breakdown structure (WBS) for dismantling of facilities is scheduled. Then, considering to minimize waste amounts, several suitable decontamination techniques, such as chemical and mechanical methods, which are developed by INER are considered to be adopted. As for the estimation of man hours of dismantling facilities, all events during the decommissioning tasks are classified into 16 work procedures and appropriative factors of corresponding team hours are gotten. In addition, the detailed methodology of the preliminary plan of decommissioning is also discussed. Finally, we hope the results of this planning can provide practical benefits to upcoming decommissioning work in Taiwan. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

A Framework for Patient-Centered Pathways of Care for Radiopharmaceutical Therapy: An ASTRO Consensus Document

Radiopharmaceutical therapy (RPT) is an area of projected growth and importance with several agents in clinical use, new agents in late-phase clinical trials, and many others under testing and development. This article proposes a framework for developing pathways of care that can be broadly applied to all RPTs, representing the current status of RPT. It suggests foundational elements for many pathways of care for patients with cancer and concludes with areas in active development and the future horizon for RPT treatment centers. Developing a framework for patient-centered pathways of care is a critical step in establishing RPT as standard therapy for patients with a diverse spectrum of cancers. This expected increase in RPT treatment options will affect a much larger population of patients with complex cancer. It will also require enhanced coordination and collaboration among appropriately qualified personnel with diverse expertise in image acquisition, image interpretation, quantitative imaging, dosimetry calculation, radiation quality assurance and safety as well as oncology care and RPT-induced sequelae and response assessment. The essential role of this evolving RPT care team within multidisciplinary oncology care is a cornerstone of this framework for a patient-centered pathway of care for RPT. Given the status of current RPT practice and the horizon for future applications, this patient-centered pathway of care guidance is timely and should help inform future clinical RPT practice paradigms. A task force was recruited from the Theranostic Working Group of the American Society for Radiation Oncology (ASTRO) in May 2019 with equal representation from the nuclear medicine community. The task force expanded on a framework that was originally conceived by the Working Group for patient-centered care. This framework was developed to incorporate the strengths of both radiation oncologists and nuclear medicine physicians. The manuscript was then developed by the task force and posted on the ASTRO website for a 6-week public comment period ending in July 2020. Comments were adjudicated, and the draft was sent to external organizations for potential endorsement. This document was sent to the ASTRO Board of Directors in October 2020 for approval.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2026

Separation of Lithium and Magnesium from Brines Using Zwitterionic Simulated Moving Beds: Cooperative Research and Development (Final Report)

The purpose of this work was to separate lithium and magnesium from lithium-containing brines by applying a zwitterionic simulated moving bed (zSMB) system that NLR developed. This work was needed to validate lithium and magnesium separation for future development at scale. Below is a summary of the tasks outlined in the Statement of Work and the results that were generated.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers

On large supercomputers, the job scheduling systems may assign a non-contiguous node allocation for user applications depending on available resources. With parallel applications using MPI (Message Passing Interface), the default process ordering does not take into account the actual physical node layout available to the application. This contributes to non-locality in terms of physical network topology and impacts communication performance of the application. In order to mitigate such performance penalties, this work describes techniques to identify suitable task mapping that takes the layout of the allocated nodes as well as the application's communication behavior into account. During the first phase of this research, we instrumented and collected performance data to characterize communication behavior of critical US DOE (United States - Department of Energy) applications using an augmented version of the mpiP tool. Subsequently, we developed several reordering methods (spectral bisection, neighbor join tree etc.) to combine node layout and application communication data for optimized task placement. We developed a tool called mpiAproxy to facilitate detailed evaluation of the various reordering algorithms without requiring full application executions. This work presents a comprehensive performance evaluation (14,000 experiments) of the various task mapping techniques in lowering communication costs on Titan, the leadership class supercomputer at Oak Ridge National Laboratory.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Communication Characterization and Optimization of Applications Using Topology-Aware Task Mapping on Large Supercomputers

Sreepathi, Sarat↗

DOE OSTI2016

Wind power forecasting: IEA Wind Task 36 & future research issues

Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

17 WIND ENERGY↗

DOE OSTI2012

NEAMS Software Licensing, Release, and Distribution: Implications for FY2013 Work Package Planning

The vision of the NEAMS program is to bring truly predictive modeling and simulation (M&S) capabilities to the nuclear engineering community in order to enable a new approach to the analysis of nuclear systems. NEAMS anticipates issuing in FY 2018 a full release of its computational 'Fermi Toolkit' aimed at advanced reactor and fuel cycles. The NEAMS toolkit involves extensive software development activities, some of which have already been underway for several years, however, the Advanced Modeling and Simulation Office (AMSO), which sponsors the NEAMS program, has not yet issued any official guidance regarding software licensing, release, and distribution policies. This motivated an FY12 task in the Capability Transfer work package to develop and recommend an appropriate set of policies. The current preliminary report is intended to provide awareness of issues with implications for work package planning for FY13. We anticipate a small amount of effort associated with putting into place formal licenses and contributor agreements for NEAMS software which doesn't already have them. We do not anticipate any additional effort or costs associated with software release procedures or schedules beyond those dictated by the quality expectations for the software. The largest potential costs we anticipate would be associated with the setup and maintenance of shared code repositories for development and early access to NEAMS software products. We also anticipate an opportunity, with modest associated costs, to work with the Radiation Safety Information Computational Center (RSICC) to clarify export control assessment policies for software under development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗