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The Nuclear Energy Knowledge and Validation Center – Summary of Activities Conducted in FY15

The Nuclear Energy Knowledge and Validation Center (NEKVaC) is a new initiative by the Department of Energy and the Idaho National Laboratory to coordinate and focus the resources and expertise that exist with the DOE Complex toward solving issues in modern nuclear code validation. In time, code owners, users, and developers will view the Center as a partner and essential resource for acquiring the best practices and latest techniques for validating codes, for guidance in planning and executing experiments, for facilitating access to, and maximizing the usefulness of, existing data, and for preserving knowledge for continual use by nuclear professionals and organizations for their own validation needs. The scope of the center covers many inter-related activities which will need to be cultivated carefully in the near-term and managed properly once the Center is fully functional. Three areas comprise the principal mission: 1) identification and prioritization of projects that extend the field of validation science and its application to modern codes, 2) adapt or develop best practices and guidelines for high fidelity multiphysics/multiscale analysis code development and associated experiment design, and 3) define protocols for data acquisition and knowledge preservation and provide a portal for access to databases currently scattered among numerous organizations. These mission areas, while each having a unique focus, are inter-dependent and complementary. Likewise, all activities supported by the NEKVaC, both near-term and long-term), must possess elements supporting all three. This cross-cutting nature is essential to ensuring that activities and supporting personnel do not become ‘stove-piped’, i.e. focused so much on a specific function that the activity itself becomes the objective rather than the achieving the larger vision. Achieving the broader vision will require a healthy and accountable level of activity in each of the areas. This will take time and significant DOE support. Growing too fast (budget-wise) will not allow ideas to mature, lessons to be learned, and taxpayer money to be spent responsibly. The process should be initiated with a small set of tasks, executed over a short but reasonable term, that will exercise most if not all aspects of the Center’s potential operation. The initial activities described in this report have a high potential for near-term success in demonstrating Center objectives but also to work out some of the issues in task execution, communication between functional elements, and the ability to raise awareness of the Center and cement stakeholder buy-in. This report begins with a description of the Mission areas; specifically the role played by each and the types of activities for which they are responsible. It then lists and describes the proposed near-term tasks upon which future efforts can build.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An Overview of the Applied Meteorology Unit (AMU)

The Applied Meteorology Unit (AMU) acts as a bridge between research and operations by transitioning technology to improve weather support to the Shuttle and American space program. It is a NASA entity operated under a tri-agency agreement by NASA, the US Air Force, and the National Weather Service (NWS). The AMU contract is managed by NASA, operated by ENSCO, Inc. personnel, and is collocated with Range Weather Operations at Cape Canaveral Air Force Station. The AMU is tasked by its customers in the 45th Weather Squadron, Spaceflight Meteorology Group, and the NWS in Melbourne, FL with projects whose results help improve the weather forecast for launch, landing, and ground operations. This presentation describes the history behind the formation of the AMU, its working relationships and goals, how it is tasked by its customers, and examples of completed tasks.

Merceret, Francis↗

Failure tolerant operation of kinematically redundant manipulators

Redundant manipulators may compensate for failed joints with their additional degrees of freedom. In this paper such a manipulator is considered fault tolerant if it can guarantee completion of a task after any one of its joints has failed. This fault tolerance of kinematically redundant manipulators is insured here. Methods to analyze the manipulator's work space find regions inherently suitable for critical tasks because of their high level of failure tolerance. Constraints are then placed on the manipulator's range of motion to guarantee completion of a task.

Lewis, Christopher L.↗

Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction

Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.

NASA Discipline Space Human Factors↗

Hanford Double Shell Waste Tank Corrosion Studies (Final Report FY2019)

During fiscal year (FY) 2019, the Savannah River National Laboratory (SRNL) focused on four primary tasks for Hanford Double Shell Tanks (DSTs) corrosion studies. The first task, New Limits, was a continuation from the electrochemical work started in FY16, to expand electrochemical testing to elevated temperatures and elevated hydroxide concentrations and evaluate how these factors will influence pitting corrosion. Using the pitting factor (PF) equation, these new conditions were validated to provide a conservative estimate for the susceptibility of pitting corrosion on legacy carbon steel. The second task, Secondary Liner Corrosion, focused on Vapor Space Corrosion (VSC) and immersion testing studies using two commercially available vapor corrosion inhibitors (VCIs). For this FY, the VCI strategy was applied mid-experiment to determine performance on weathered coupons. The third task, Long-Term Open Circuit Potential (OCP) Drift, was performed using simplified simulated chemistries to evaluate change in pitting corrosion risk due to evolution of corrosion potential for mill-scale and freshly polished 600-grit surfaces. Finally, the fourth task, Microbiologically-Influenced Corrosion (MIC) studies, was focused on the study of leak detection pit (LDP) water sent from the Hanford tank farm for determination of bacteria that can be conducive to corrosion using commercially available kits: BART TM and MICkit® 5. In addition, this FY, a secondary task was added which was a continuation of the study of the Quartz-enhanced Photoacoustic Spectroscopy (QEPAS) system. Work was started but was ultimately not pursued. A summary of each task performed is presented below.

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Haar-Like Wavelets on Hierarchical Trees

Here, discrete wavelet methods, originally formulated in the setting of regularly sampled signals, can be adapted to data defined on a point cloud if some multiresolution structure is imposed on the cloud. A wide variety of hierarchical clustering algorithms can be used for this purpose, and the multiresolution structure obtained can be encoded by a hierarchical tree of subsets of the cloud. Prior work introduced the use of Haar-like bases defined with respect to such trees for approximation and learning tasks on unstructured data. This paper builds on that work in two directions. First, we present an algorithm for constructing Haar-like bases on general discrete hierarchical trees. Second, with an eye towards data compression, we present thresholding techniques for data defined on a point cloud with error controlled in the $L$ $\infty$ norm and in a Hölder-type norm. In a concluding trio of numerical examples, we apply our methods to compress a point cloud dataset, study the tightness of the $L$ $\infty$ error bound, and use thresholding to identify MNIST classifiers with good generalizability.

97 MATHEMATICS AND COMPUTING↗

Challenges of developing an electro-optical system for measuring man's operational envelope

In designing work stations and restraint systems, and in planning tasks to be performed in space, a knowledge of the capabilities of the operator is essential. Answers to such questions as whether a specific control or work surface can be reached from a given restraint and how much force can be applied are of particular interest. A computer-aided design system has been developed for designing and evaluating work stations, etc., and the Anthropometric Measurement Laboratory (AML) has been charged with obtaining the data to be used in design and modeling. Traditional methods of measuring reach and force are very labor intensive and require bulky equipment. The AML has developed a series of electro-optical devices for collecting reach data easily, in computer readable form, with portable systems. The systems developed, their use, and data collected with them are described.

Woolford, B.↗

Voice measures of workload in the advanced flight deck: Additional studies

These studies investigated acoustical analysis of the voice as a measure of workload in individual operators. In the first study, voice samples were recorded from a single operator during high, medium, and low workload conditions. Mean amplitude, frequency, syllable duration, and emphasis all tended to increase as workload increased. In the second study, NASA test pilots performed a laboratory task, and used a flight simulator under differing work conditions. For two of the pilots, high workload in the simulator brought about greater amplitude, peak duration, and stress. In both the laboratory and simulator tasks, high workload tended to be associated with more statistically significant drop-offs in the acoustical measures than were lower workload levels. There was a great deal of intra-subject variability in the acoustical measures. The results suggested that in individual operators, increased workload might be revealed by high initial amplitude and frequency, followed by rapid drop-offs over time.

Schneider, Sid J.↗

Evaluation and selection of assembly plans

Two criteria are introduced for the evaluation and selection of assembly plans. The first criterion is to maximize the number of different sequences encompassed by the assembly plan. The second criterion is to maximize the amount of parallelism (i.e., simultaneity) that is possible in the execution of the assembly tasks. While the metrics corresponding to the criteria used in previous work can be expressed as a sum of terms, each being a function of a task or a state, the metrics corresponding to the criteria introduced are more complex functions of the whole assembly plan. An algorithm that performs a heuristic search for the best assembly plan over the AND/OR graph representation of assembly plans introduced in previous work is presented. Admissible heuristics for each of the two criteria are presented.

Homem De Mello, L. S.↗

Mars power system concept definition study. Volume 2: Appendices

This report documents the work performed by Rockwell International's Rocketdyne Division on NASA Contract No. NAS3-25808 (Task Order No. 16) entitled 'Mars Power System Definition Study'. This work was performed for NASA's Lewis Research Center (LeRC). The report is divided into two volumes as follows: Volume 1 - Study Results; and Volume 2 - Appendices. The results of the power system characterization studies, operations studies, and technology evaluations are summarized in Volume 1. The appendices include complete, standalone technology development plans for each candidate power system that was investigated.

Littman, Franklin D.↗

Outer Solar System Nomenclature

The Principal Investigator's responsibilities on this grant fell into two categories according to his participation. In the nomenclature work of the International Astronomical Union (IAU). Owen is chair of the Task Group for the Outer Solar System. He is also a member of the IAU's Working Group on Planetary and Satellite Nomenclature (WGPSN) which is composed of the chairs of the several Task Groups plus the presidents of two IAU Commissions and several outside consultants. The WGPSN is presided over by its President, Professor Kaare Aksnes from the Rosseland Institute for Theoretical Astrophysics in Oslo, Norway.

OUTER SPACE↗

Supersonics Project: Airport Noise Technical Challenge

This presentation gives an overview of the work being done under the Airport Noise Technical Challenge portion of the Supersonics Project in the Fundamental Aeronautics Program. The objective of the Challenge is to provide technology (e.g. low noise nozzle concepts) and engineering tools required for a viable supersonic aircraft. To accomplish this we have activities divided into Prediction, Diagnostics, and Engineering elements. Each of the tasks reviewed here have potential applications to work being done at other flight regimes and other aircraft and are of interest to the Acoustics Technical Working Group.

Bridges, James E.↗

Exposure Evaluation for Benzene, Lead and Noise in Vehicle and Equipment Repair Shops

An exposure assessment was performed at the equipment and vehicle maintenance repair shops operating at the U. S. Department of Energy Hanford site, in Richland, Washington. The maintenance shops repair and maintain vehicles and equipment used in support of the Hanford cleanup mission. There are three general mechanic shops and one auto body repair shop. The mechanics work on heavy equipment used in construction, cranes, commercial motor vehicles, passenger-type vehicles in addition to air compressors, generators, and farm equipment. Services include part fabrication, installation of equipment, repair and maintenance work in the engine compartment, and tire and brake services. Work performed at the auto body shop includes painting and surface preparation which involves applying body filler and sanding. 8-hour time-weighted-average samples were collected for benzene and noise exposure and task-based samples were collected for lead dust work activities involving painted metal surfaces. Benzene samples were obtained using 3M™ 3520 sampling badges and were analyzed for additional volatile organic compounds. These compounds were selected based on material safety data sheet information for the aerosol products used by the mechanics for each day of sampling. The compounds included acetone, ethyl ether, toluene, xylene, VM&P naphtha, methyl ethyl ketone, and trichloroethylene. Laboratory data for benzene, VM&P naphtha, methyl ethyl ketone and trichloroethylene were all below the reporting detection limit. Airborne concentrations for acetone, ethyl ether, toluene and xylene were all less than 10% of their occupational exposure limit. The task-based samples obtained for lead dusts were submitted for a metal scan analysis to identify other metals that might be present. Laboratory results for lead dusts were all below the reporting detection limit and airborne concentration for the other metals observed in the samples were less than 10% of the occupational exposure limit. Noise dosimetry sampling was performed on a random basis and was representative of the different work activities within the four shops. Twenty three percent of the noise samples exceeded the occupational exposure limit of 85 decibels for an 8-hour time-weightedaverage. Work activities where noise levels were higher included use of impact wrenches and grinding wheels.

54 ENVIRONMENTAL SCIENCES↗

Reconfigurable, Cognitive Software-Defined Radio

Software-defined radio (SDR) technology allows radios to be reconfigured to perform different communication functions without using multiple radios to accomplish each task. Intelligent Automation, Inc., has developed SDR platforms that switch adaptively between different operation modes. The innovation works by modifying both transmit waveforms and receiver signal processing tasks. In Phase I of the project, the company developed SDR cognitive capabilities, including adaptive modulation and coding (AMC), automatic modulation recognition (AMR), and spectrum sensing. In Phase II, these capabilities were integrated into SDR platforms. The reconfigurable transceiver design employs high-speed field-programmable gate arrays, enabling multimode operation and scalable architecture. Designs are based on commercial off-the-shelf (COTS) components and are modular in nature, making it easier to upgrade individual components rather than redesigning the entire SDR platform as technology advances.

Bhat, Arvind↗

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Plutonium Oxide Process Capability Work Plan

Pacific Northwest National Laboratory (PNNL) has been tasked to develop a Pilot-scale Plutonium-oxide Processing Unit (P3U) providing a flexible capability to produce 200g (Pu basis) samples of plutonium oxide using different chemical processes for use in identifying and validating nuclear forensics signatures associated with plutonium production. Materials produced can also be used as exercise and reference materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Policy, Regulatory, Legal, and Permitting Evaluation Task 6.0 (Technical Report)

This report revisits and updates work completed for the Phase I CarbonSAFE Illinois - East Sub Basin project, the precursor to the Phase II Wabash CarbonSAFE project; the current report summarizes the policy, regulatory, legal, and permitting considerations to-date as related to geologic CO 2 storage at the Wabash Valley Resources (WVR) gasification plant site in Vigo County, Indiana.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗