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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2017

Analyst-to-Analyst Variability in Simulation-Based Prediction

This report describes findings from the culminating experiment of the LDRD project entitled, "Analyst-to-Analyst Variability in Simulation-Based Prediction". For this experiment, volunteer participants solving a given test problem in engineering and statistics were interviewed at different points in their solution process. These interviews are used to trace differing solutions to differing solution processes, and differing processes to differences in reasoning, assumptions, and judgments. The issue that the experiment was designed to illuminate -- our paucity of understanding of the ways in which humans themselves have an impact on predictions derived from complex computational simulations -- is a challenging and open one. Although solution of the test problem by analyst participants in this experiment has taken much more time than originally anticipated, and is continuing past the end of this LDRD, this project has provided a rare opportunity to explore analyst-to-analyst variability in significant depth, from which we derive evidence-based insights to guide further explorations in this important area.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗

DOE OSTI2011

Visual Text Analytics for Impromptu Analysts

The Scalable Reasoning System (SRS) is a lightweight visual analytics framework that makes analytical capabilities widely accessible to a class of users we have deemed “impromptu analysts.” By focusing on a deployment of SRS, the Lessons Learned Explorer (LLEx), we examine how to develop visualizations around analytical-oriented goals and data availability. We discuss how to help impromptu analysts to explore deeper patterns. Through designing consistent interactions, we arrive at an interdependent view capable of showcasing patterns. With the combination of SRS widget visualizations and interactions around the underlying textual data, we aim to transition the casual, infrequent user into a viable–albeit impromptu–analyst.

Analyst↗

DOE OSTI2022

Applying Waveform Correlation and Waveform Template Metadata to Mining Blasts to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high - quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. In this study we use waveform template event metadata to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We build upon events detected in a prior waveform correlation study of mining blasts in two geographic regions, Wyoming and Scandinavia. Using a set of expert analyst-reviewed waveform correlation events that were declared to be true positive detections, we explore criteria for choosing the waveform correlation detections that are most likely to lead to bulletin-worthy events and reduction of analyst effort.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Women in Science: Fermilab cybersecurity analyst Jeny Teheran

With 11 February marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and from Fermilab share their experiences of building a career in science. Jeny Teheran is a security analyst and cybersecurity researcher at Fermi National Accelerator Laboratory. That means keeping up with and taking care of hardware and software vulnerabilities so that the experiments can carry out their science in a secure manner. It's a fast-paced job where you have to come with the best solution you can put in place, right in the moment. "I would recommend this job because it challenges you. It pushes you to be on top of your game. You have to improve your analytical skills; you have to react fast; you have to communicate better." - Jeny says. Jeny came to Fermilab from the Caribbean coast of Colombia. She grew up in a house with few toys but lots of books, and says she has always felt close to science. With a degree in systems and computing engineering, she arrived at Fermilab four years ago as an intern to work on the offline production team for neutrino experiments. A year later, she was hired as a security analyst. "And I'm loving it," she says. Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2013

How Analysts Cognitively “Connect the Dots”

As analysts attempt to make sense of a collection of documents, such as intelligence analysis reports, they may wish to “connect the dots” between pieces of information that may initially seem unrelated. This process of synthesizing information between information requires users to make connections between pairs of documents, creating a conceptual story. We conducted a user study to analyze the process by which users connect pairs of documents and how they spatially arrange information. Users created conceptual stories that connected the dots using organizational strategies that ranged in complexity. We propose taxonomies for cognitive connections and physical structures used when trying to “connect the dots” between two documents. We compared the user-created stories with a data-mining algorithm that constructs chains of documents using co-occurrence metrics. Using the insight gained into the storytelling process, we offer design considerations for the existing data mining algorithm and corresponding tools to combine the power of data mining and the complex cognitive processing of analysts.

data mining↗

DOE OSTI2021

Applying Waveform Correlation to Reduce Seismic Analyst Workload Due to Repeating Mining Blasts

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high–quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment to detect and identify mining blasts for two regions, Wyoming (U.S.A.) and Scandinavia, using waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear–Test–Ban Treaty Organization (CTBTO PrepCom) for up to 10 yr prior to the time of interest. We discuss approaches for template selection, threshold setting, and event detection that are specialized for characterizing mining blasts using a sparse, global network. We apply the approaches to one week of data for each of the two regions to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be generally applied to operational monitoring systems with a sparse network. Here, we compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to assess potential reduction in analyst workload.

58 GEOSCIENCES↗

DOE OSTI2016

Special Nuclear Material Gamma-Ray Signatures for Reachback Analysts

These are slides on special nuclear material gamma-ray signatures for reachback analysts for an LSS Spectroscopy course. The closing thoughts for this presentation are the following: SNM materials have definite spectral signatures that should be readily recognizable to analysts in both bare and shielded configurations. One can estimate burnup of plutonium using certain pairs of peaks that are a few keV apart. In most cases, one cannot reliably estimate uranium enrichment in an analogous way to the estimation of plutonium burnup. The origin of the most intense peaks from some SNM items may be indirect and from ‘associated nuclides.' Indirect SNM signatures sometimes have commonalities with the natural gamma-ray background.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

SNL will be able to provide well-calibrated models to weapons systems analysts by integrating an engine for constitutive model calibration with the GRANTA materials database

Researchers at Sandia National Laboratories have integrated the GRANTA materials database with the MatCal calibration engine to calibrate material models from characterization data. GRANTA is gaining acceptance across the NNSA Tri-lab complex and is being populated with weapons-specific test data by Sandia experimentalists. To use that data to create material models for use by weapons systems analysts, MatCal has been enabled import calibration data and test conditions from GRANTA to quickly and reproducibly produce a calibrated set of parameters for a given constitutive model. The team is currently working to store the parameters characterizing material behavior in GRANTA to make them accessible by all weapons analysts.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Applying Waveform Correlation and Waveform Template Metadata to Aftershocks in the Middle East to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize recurring events such as aftershocks to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is a technique that is effective in finding similar waveforms from repeating seismic events. In this study, we apply waveform correlation in combination with template event metadata to two aftershock sequences in the Middle East to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We use waveform templates from stations that are within regional distance of aftershock sequences to detect subsequent events, then use template event metadata to discover what stations are likely to record corroborating arrival waveforms for recurring aftershock events at the same location, and develop additional waveform templates to seek corroborating detections. We evaluate the results with the goal of determining whether applying the method to aftershock events will improve the choice of waveform correlation detections that lead to bulletin-worthy events and reduction of analyst effort.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2023

DOE Radiological Triage Program: Analyst Open Book Exam 2021

This document contains the open book exam for Radiological Triage Program Analysts for Los Alamos National Laboratory. "The following questions test your knowledge relevant to the DOE Radiological Triage program. There is no time limit, and you may use any reference materials or software you like. You may discuss with other analysts but please show your own work. Spectra are provided in electronic form. There are 10 questions and up to 1 point of extra credit is available. A score of 80% is required to pass. Please send your answers in any convenient form to Mercer@LANL.gov."

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

DOE Radiological Triage Program Analyst Open Book Exam 2022

This document contains the 2022 open book examination for Radiological Triage Program Analysts for Los Alamos National Laboratory. "The following questions test your knowledge relevant to the DOE Radiological Triage program. There is no time limit, you may use any reference materials or software you like, and you may discuss with other analysts. No electronic spectra are provided or needed. Please send your answers in any convenient form to Mercer@LANL.gov. You may also take the exam using Survey Monkey (which will provide immediate feedback). A score of 80% is required to pass. There are 25 multiple-choice questions each worth 1 point."

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2012

Storing and managing information artifacts collected by information analysts using a computing device

Systems and computer-implemented processes for storage and management of information artifacts collected by information analysts using a computing device. The processes and systems can capture a sequence of interactive operation elements that are performed by the information analyst, who is collecting an information artifact from at least one of the plurality of software applications. The information artifact can then be stored together with the interactive operation elements as a snippet on a memory device, which is operably connected to the processor. The snippet comprises a view from an analysis application, data contained in the view, and the sequence of interactive operation elements stored as a provenance representation comprising operation element class, timestamp, and data object attributes for each interactive operation element in the sequence.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2015

A Comparative Study of Automated Infrasound Detectors - PMCC and AFD with Analyst Review.

Automated detections calculated by the progressive multi-channel correlation (PMCC) method (Cansi, 1995) and the adaptive F detector (AFD) (Arrowsmith et al., 2009) are compared to the signals identified by five independent analysts. Each detector was applied to a four-hour time sequence recorded by the Korean infrasound array CHNAR. This array was used because it is composed of both small (<100 m) and large (~1000 m) aperture element spacing. The four hour time sequence contained a number of easily identified signals under noise conditions that have average RMS amplitudes varied from 1.2 to 4.5 mPa (1 to 5 Hz), estimated with running five-minute window. The effectiveness of the detectors was estimated for the small aperture, large aperture, small aperture combined with the large aperture, and full array. The full and combined arrays performed the best for AFD under all noise conditions while the large aperture array had the poorest performance for both detectors. PMCC produced similar results as AFD under the lower noise conditions, but did not produce as dramatic an increase in detections using the full and combined arrays. Both automated detectors and the analysts produced a decrease in detections under the higher noise conditions. Comparing the detection probabilities with Estimated Receiver Operating Characteristic (EROC) curves we found that the smaller value of consistency for PMCC and the larger p-value for AFD had the highest detection probability. These parameters produced greater changes in detection probability than estimates of the false alarm rate. The detection probability was impacted the most by noise level, with low noise (average RMS amplitude of 1.7 mPa) having an average detection probability of ~40% and high noise (average RMS amplitude of 2.9 mPa) average detection probability of ~23%.

58 GEOSCIENCES↗

DOE OSTI2017

Developing a Streamlined Approach to Criticality Safety Analyst Training/Qualification

The Los Alamos National Laboratory (LANL) Criticality Safety Analyst (CSA) Qualification Standard was a multidivisional effort forged in late 2012. The result of the effort is a well-documented and efficient approach to training, encompassing local and national Nuclear Criticality Safety (NCS) training courses for incoming criticality safety staff, as well as a model for professional development of qualified CSAs at LANL. Five years later, the approach to training and qualification for CSAs has evolved into a streamlined safety management function, integrated in all phases of employee recruitment, development, deployment, and management.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗

DOE OSTI2019

Deep Learning Models Augment Analyst Decisions for Event Discrimination

Long-term seismic monitoring networks are well positioned to leverage advances in machine learning because of the abundance of labeled training data that curated event catalogs provide. In this study, we explore the use of Convolutional and Recurrent Neural Networks to accomplish discrimination of explosive and tectonic sources for local distances. Using a 5-year event catalog generated by the University of Utah Seismograph Stations we train models to produce automated event labels using 90 s event spectrograms from 3-component and single-channel sensors. Both network architectures are able to replicate analyst labels above 98%. Most commonly, model error is the result of label error (70% of cases). Accounting for mislabeled events (~1% of the catalog) model accuracy for both models increases to above 99%. Finally, classification accuracy remains above 98% for shallow tectonic events, indicating that spectral characteristics controlled by event depth do not play a dominant role in event discrimination.

58 GEOSCIENCES↗

DOE OSTI2016

Contingency Contractor Optimization Tool Prototype (Phase 3 Extension- Analyst Tutorial)

This tutorial walks the user through analysis examples using the Contingency Contractor Optimization Tool Prototype. The examples are designed to showcase key capabilities of the tool. The main goal of this tutorial is to provide examples of how to use the tool to perform analyses to those users acting in the analyst role. All examples and locations used in the prototype are fictional, but are intended to be realistic. Users reading this manual are expected to have a basic understanding and familiarity with the Contingency Contractor Optimization Tool Prototype. This tutorial includes scenarios for the occurrence of two wars, Prussia and New Granada.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗