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DOE OSTI2023

Unraveling the impact of the degree of dry mixing on dry-processed lithium-ion battery electrodes

Dry processing of lithium-ion battery electrodes facilely realizes the powder-to-film manner, which is thus regarded as a highly promising strategy for lithium-ion battery manufacturing. However, a fundamental understanding of the impact of the involved dry mixing is still rarely reported. In this work, the degree of dry mixing is monitored by the dry mixing time, and a set of dry-processed electrodes with different degree of dry mixing is accordingly prepared and comprehensively studied. This work novelly reveals that the degree of dry mixing exhibits pronounced impact on the morphology, the homogeneity of electrode components and the degree of PTFE fiberization, which leads to difference in the mechanical strength and electrochemical performance of dry-processed electrodes. Accordingly, it is suggested that a moderate degree of dry mixing is preferred for high-performance dry-processed lithium-ion battery electrodes.

25 ENERGY STORAGE↗

DOE OSTI2022

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Process Development of the Vaporizing Foil Actuator Welding Technique

The industrial focus on continuous improvement for products is leading design engineers to consider multi-material design concepts more frequently. The design concepts use the advantages of each material while simultaneously minimizing the drawbacks. It also allows for the overall weight of the products to be reduced. Some traditional joining methods, though, struggle to join dissimilar material combinations. A technique known as vaporizing foil actuator welding, which was developed around ten years ago, is a solid-state joining method that has the potential to overcome the barriers to dissimilar material joining. The biggest drawbacks of vaporizing foil actuator welding are that it is still exclusively used in laboratory settings and early in the technology development process. As such, there is not enough confidence in the process for it to be transitioned to manufacturing environments yet. This work begins by analyzing the current state of the technology and identifying a roadmap to achieve a transition to manufacturing. The analysis found that increased confidence in the technology requires sample to sample repeatability to be improved. Beyond that, the process also needs to be fully automated before it can be considered as a viable technique for mass production. In order to further develop the technique, a fully automated work cell was constructed. By removing the human element from the process, this cell helped identify iii the aspects which contribute to process variability. The positioning of the vaporizing foil actuator was identified as the most important factor in process stability. A small set of samples were made in the automated cell with the addition of one component epoxy adhesive around the perimeter of the weld. These samples showed improved process repeatability compared with the samples made without adhesive. This indicates that small amounts of adhesive may be critical in using the process in industrial settings. Additionally, work was performed with manual positioning and adhesive dispensing. This work found that a hybrid joint behaves like traditional weld bonding, where the addition of adhesive makes the joint stronger than if either of the two joining methods were used on their own. To realize this performance with vaporizing foil actuator welding, though, the adhesive needs to be protected from burning during the rapid compression of air during the impact process.

36 MATERIALS SCIENCE↗

DOE OSTI2020

High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska

It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, highresolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Tool for Ranking Research Options

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

Ortiz, James N.↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRS2018

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗

DOE OSTI2019

Experimental and theoretical study of the plasma physics of antihydrogen generation and trapping. Final Scientific Report

The main goal of the project was to determine if matter and antimatter are exact conjugates. According to the current best understanding of the universe, this property should hold. The ALPHA collaboration performed a series of high precision measurements on trapped antihydrogen and compared the results to those that would be expected for hydrogen. Any difference would have enormous implications for our understanding of basic physics because a difference would mean the CPT theorem is violated. In pursuit of this goal, we needed to understand plasma and atomic processes for a novel set of plasma parameters: extremely low temperature (a few 10's of K) and high magnetic field (a couple T). Our attempts to control/manipulate these plasmas led to important goals related directly to plasma physics. For example, the radiative coupling of the cyclotron motion to a microwave cavity can display collective effects as the number of positrons increases. This DOE award mainly provided support for theoretical studies of the atomic and plasma processes that determine the outcome of the experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Risk-Informed and Performance-Based Evaluation of Defense-in-Depth Adequacy

This document supports the work contained in Nuclear Energy Institute (NEI) 18-04 “Risk-Informed Performance-Based Technology Inclusive Guidance for Advanced Reactor Licensing Basis Development” Revision 0. NEI 18-04 presents a modern, technology-inclusive, risk-informed, and performance-based (TI-RIPB) process for selection of Licensing Basis Events (LBEs); safety classification of structures, systems, and components (SSCs) and associated risk-informed special treatments; and determination of defense-in-depth (DID) adequacy for non-LWRs. The NEI guidance document provides one acceptable means for addressing the aforementioned topics as part of demonstrating a specific design provides reasonable assurance of adequate radiological protection. This report provides the framework and associated methodology guidelines and discussion for establishing, then evaluating, confirming, and documenting the adequacy of defense-in-depth (DID) for advanced non-light-water reactor technologies. It was developed as part of the Licensing Modernization Project led by Southern Company and cost-shared by the United States Department of Energy and has benefited from considerable NRC formal reviews and public workshops. The methodology converts the DID philosophy into a structured process that is implementable, embraces existing United States and international definitions and philosophies of DID that set the foundation for the process. It builds on the DID framework developed in the Department of Energy Next Generation Nuclear Plant Project and earlier works on this subject. The approach to establishing DID adequacy involves the incorporation of DID attributes into the plant capabilities and programmatic elements of DID. The integrated evaluation of DID adequacy includes both quantitative elements to incorporate risk-informed and performance-based (RIPB) considerations and qualitative elements that address uncertainties and limitations in the quantitative models and supporting data. Demonstration of DID adequacy ensures that there are multiple layers of defense for risk-significant challenges to the design and that the plant capabilities and programs that support each layer are provided in a manner that minimizes dependencies among these layers. The focus of this report is assurance of DID adequacy with respect to protection of the public from radiological exposures resulting from accidental releases of radioactive material. While other hazards are not specifically addressed, this methodology is expected to be beneficial for determining DID adequacy for them as well. Risk-informed evaluation of DID considers the integrated performance of all plant SSCs and associated programs to manage daily operational activities, transients, and accidents, including the evaluation of strategies for accident prevention and mitigation. The RIPB LBE scenario methodology used in this evaluation defines the challenges to the plant safety features included in the plant design basis and beyond, and the scope of all deterministic and probabilistic safety evaluations. By examining event sequences across the whole spectrum of LBEs, a systematic assessment of DID can be accomplished.

42 ENGINEERING↗

NASA NTRS2009

Multi-Mission Automated Task Invocation Subsystem

Multi-Mission Automated Task Invocation Subsystem (MATIS) is software that establishes a distributed data-processing framework for automated generation of instrument data products from a spacecraft mission. Each mission may set up a set of MATIS servers for processing its data products. MATIS embodies lessons learned in experience with prior instrument- data-product-generation software. MATIS is an event-driven workflow manager that interprets project-specific, user-defined rules for managing processes. It executes programs in response to specific events under specific conditions according to the rules. Because requirements of different missions are too diverse to be satisfied by one program, MATIS accommodates plug-in programs. MATIS is flexible in that users can control such processing parameters as how many pipelines to run and on which computing machines to run them. MATIS has a fail-safe capability. At each step, MATIS captures and retains pertinent information needed to complete the step and start the next step. In the event of a restart, this information is retrieved so that processing can be resumed appropriately. At this writing, it is planned to develop a graphical user interface (GUI) for monitoring and controlling a product generation engine in MATIS. The GUI would enable users to schedule multiple processes and manage the data products produced in the processes. Although MATIS was initially designed for instrument data product generation,

Cheng, Cecilia S.↗

DOE OSTI2019

Support for Next-Generation Ecosystem Experiments (NGEE Arctic) Field Campaign Report

An important challenge for Earth System Models (ESMs) is to represent land surface and subsurface processes and their complex interactions in a warming climate. This is especially important for arctic ecosystems where permafrost extent, topography, hydrology, vegetation, disturbance, and biogeochemistry are inextricably linked. The implications of such linkages include permafrost thaw and deepening of the active layer, microbial decomposition of vulnerable soil organic matter, altered productivity and migration of tall woody shrubs, and watershed-scale changes in surface and groundwater transport and storage. Although ESMs describe some of these interactions for high-latitude ecosystems, their representation requires extensive confrontation with field and laboratory observations to test and improve models, and to use those models to inspire new observations and experiments. The Next-Generation Ecosystem Experiments (NGEE Arctic) is a 10-year project (2012 to 2022) to improve our predictive understanding of carbon-rich arctic system processes and feedbacks to climate. This is achieved through experiments, observations, and synthesis of existing data sets that strategically inform model process representation and parameterization, and that enhance the knowledge base required for model initialization, calibration, and evaluation. One question of special interest to the NGEE Arctic project addresses how above- and below-ground plant functional traits might change across environmental gradients, and what are the consequences for arctic ecosystem C, water, and nutrient fluxes? Arctic plant traits, and their variation in response to changing environmental conditions, will play a key role in the response of tundra ecosystems to warming, permafrost thaw, and the wetter or drier conditions expected in the future. The appropriate representation of these functional traits in models is necessary to accurately represent ecosystem C, water, and nutrient cycling in tundra ecosystems, now and in the future. We characterized the variation in above- and below-ground plant traits in response to varying edaphic and environmental conditions in Utqia&gdot;vik (formerly Barrow), Alaska. These new data, combined with remote-sensing and synthesis activities across the Arctic and the globe, have been used to inform model structure and parameterization of key processes such as photosynthesis, nutrient dynamics, and trait variation across the landscape.

North Slope of Alaska, arctic processes (meteorolo↗

DOE OSTI2019

COMBIgor: Data-Analysis Package for Combinatorial Materials Science

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Here, due to maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment, designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data sets. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data analysis and visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

CROCUS Urban Fluxes of CO₂, H₂O, and Turbulence at University of Illinois Chicago

As of May 12, 2026 this dataset is currently being versioned to include data up to April 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. This dataset was collected at the UIC Plant Research Laboratory in Chicago, Illinois, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory. The site provides continuous atmospheric flux measurements, focusing on CO₂, H₂O, and heat and momentum transport in an urban setting. The data is processed at 30 minutes interval using the Eddy Covariance method and includes quality control and diagnostic data generated by EddyPro software. The data is stored in the netCDF files following CF conventions. The UIC Plant Research Laboratory is located near major highways and urban infrastructure, including buildings and parking areas. The surrounding landscape consists of a mix of turf, plants, trees, and impervious surfaces such as concrete and asphalt, making it ideal for studying urban at for studies on urban sustainability, air quality, and the effects of urbanization on atmospheric processes on urban climate dynamics, air quality, and surface-atmosphere exchanges within the city of Chicago. This dataset is funded by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research (BER) program.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States

The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Online data analysis and reduction: An important co-design motif for extreme-scale computers

A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.

Data Analysis↗

NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique signature of visual behavior. This is true even in a restricted domain, such as piloting an aircraft, where patterns of visual signatures might represent activities like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these activities based on their behavioral signatures. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as τ. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration τ, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to counts by multiplying by τ divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We have investigated the method using a set of 10 synthetic "activities," that sample 4 AOIs. Four of these activities visit 3 of the 4 AOIs, with equal probability; as there are four different ways to leave-one- out, there are four such activities. Similarly, there are six different activities that leave-two-out. Sequences of simulated behavior were generated by running each activity for 40 seconds, in sequence, for a total of 6.7 minutes. The figure to the right shows the matrix of chi-square statistics, using a value of 2.8 seconds for τ, corresponding to 10 fixations. Low values (dark) indicate poor evidence for activity differences, while high values (bright) indicate strong evidence. The dark squares along the main diagonal each correspond to the forty second intervals in which the activity was held constant; the 4x4 block at the lower left corresponds to the four leave-one-out activities, while the 6x6 block in the upper right corresponds to the leave-two-out activities. (The anti-diagonal pattern of white squares indicates those activity pairs that share no AOIs.) The chi-square values can be binarized by choosing a particular significance level; we are interested in grouping bins that represent the same activity, effectively accepting the null hypothesis. Therefore, we may adopt a relatively lax criterion; for example, choosing a p-value of 0.2 means that two behaviors that have only a 1-in-5 chance of being produced by a single activity might nevertheless be clustered together. We have explored several methods to perform clustering on the data and solving for the activity probabilities. Greedy methods begin by selecting the time bin that is similar to the most (or least) other bins, and then forming a cluster from it and all other non-discriminable bins. These methods show mediocre performance, as they do not take into account temporal contiguity. Preliminary results indicate that methods that "grow" clusters in time from seed points perform better.

activity analysis↗

NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗

DOE OSTI2020

Using Digital and Web-Based Platforms to Enhance Nuclear Power Plant Knowledge Transfer - 20203

As the workforce ages, the loss of experienced personnel can result in a loss of important knowledge. Updating Electric Power Research Institute (EPRI) research and guidance with the latest technology developments and operating experience is an important method to transfer knowledge between the retiring and incoming workforce. Studies suggest that the incoming workforce is accustomed to using digital and/or internet-based platforms to find information and may have a higher comfort with these types of platforms than they have with static, written reports. Additionally, the ease and speed of updating and delivering content through digital formats may offer an effective method for knowledge transfer and combining information from multiple reports into a single access point. EPRI has recently produced an online Decommissioning Hub available to members and is working on replicating the effort in the area of radioactive waste management called the Radwaste Web References. EPRI has extensive guidance in both disciplines. The Decommissioning Hub uses a wiki format to provide a platform that allows for both the updating of that guidance resulting from new research and new operating experiences, and combining related topical information from multiple reports. It also allows users to access the information based on key words and topical searches, and can be a tool for users to input experience to share with others. The Decommissioning Hub is accessed via a web-based portal and includes topical pages; experience summaries; a question and answer capability; and a smart search function of all EPRI decommissioning reports. Use of a wiki format allows users to input new experiences or modify existing experience summaries to add additional detail. EPRI moderates all content. The experience data base has been initially populated with information available in published EPRI reports and unpublished information currently available within EPRI. Moving forward, population of the database will continue with information available within the open literature, new information developed from current decommissioning projects, and user inputs. The web site became active in late 2017, and a major update will be issued in early 2020. Larger scale updates are planned biannually, and smaller-scale updates will occur continuously. Capturing and applying lessons learned from industry experiences is a hallmark of the global nuclear industry. This is even more important in the decommissioning technology area since very few plant staff have relevant experience and thus there is a steep learning curve. Moreover, decommissioning involves a number of complex, non-routine and specialized tasks. The web-accessible and searchable experience database provides an easy-to-use resource for capturing and disseminating practical experiences from completed and ongoing decommissioning projects. The EPRI Radwaste Web References will build upon the philosophy and objectives of the Radwaste Desk References that were published in the 1990's. The purpose of the original Radwaste Desk References was to provide nuclear power plant professionals with a how-to manual for managing radioactive waste. The Radwaste Web References will adopt this original purpose and will be a wiki type web site that provide fundamental practical and theoretical information, operating experience (OE), and information about advanced technologies and methods. As much as practicable, features that allow for interaction between users to share OE, best practices, and benchmarking will be added. Where they exist and are appropriate, the various EPRI Guidelines documents on radwaste topics will be updated and incorporated into the Radwaste Web References. The first Radwaste Web Reference will be on Low Level Waste Characterization and will build upon the EPRI Low Level Waste Characterization Guidelines (EPRI Report TR-107201, 1996) and will be available in 2020. The next Radwaste Web Reference will be on the topic of liquid radioactive waste processing and management, tentatively set for unveiling in 2021. This paper summarizes the EPRI's previous experiences with web-based platforms and future plans in this area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗