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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

PANTHER. Pattern ANalytics To support High-performance Exploitation and Reasoning.

Sandia has approached the analysis of big datasets with an integrated methodology that uses computer science, image processing, and human factors to exploit critical patterns and relationships in large datasets despite the variety and rapidity of information. The work is part of a three-year LDRD Grand Challenge called PANTHER (Pattern ANalytics To support High-performance Exploitation and Reasoning). To maximize data analysis capability, Sandia pursued scientific advances across three key technical domains: (1) geospatial-temporal feature extraction via image segmentation and classification; (2) geospatial-temporal analysis capabilities tailored to identify and process new signatures more efficiently; and (3) domain- relevant models of human perception and cognition informing the design of analytic systems. Our integrated results include advances in geographical information systems (GIS) in which we discover activity patterns in noisy, spatial-temporal datasets using geospatial-temporal semantic graphs. We employed computational geometry and machine learning to allow us to extract and predict spatial-temporal patterns and outliers from large aircraft and maritime trajectory datasets. We automatically extracted static and ephemeral features from real, noisy synthetic aperture radar imagery for ingestion into a geospatial-temporal semantic graph. We worked with analysts and investigated analytic workflows to (1) determine how experiential knowledge evolves and is deployed in high-demand, high-throughput visual search workflows, and (2) better understand visual search performance and attention. Through PANTHER, Sandia's fundamental rethinking of key aspects of geospatial data analysis permits the extraction of much richer information from large amounts of data. The project results enable analysts to examine mountains of historical and current data that would otherwise go untouched, while also gaining meaningful, measurable, and defensible insights into overlooked relationships and patterns. The capability is directly relevant to the nation's nonproliferation remote-sensing activities and has broad national security applications for military and intelligence- gathering organizations.

58 GEOSCIENCES↗
DOE OSTI2018

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants

Maintenance activities in the United States nuclear power industry are mainly centered on preventive and corrective maintenance. Predictive maintenance, which is a variable time basis maintenance strategy that is dependent on the condition of the equipment, is less utilized but potentially more effective. In the current maintenance practices, the nuclear power plants rely on manual processes to supply information to a human decision making process. The plants have several processes that generate information that is not typically used beyond the intended target for collecting that information. This information is a source of data that is manually collected by labor intensive tasks. The data is therefore expensive to collect, yet limited in use. The industry has realized the opportunity present in reducing the labor intensive tasks by automating them and increasing the uses of the data collected by either developing advanced predictive maintenance methods using data-driven decision making that could span from trending to machine learning and artificial intelligence. This shift in maintenance strategy may result in high cost saving impact. In addition to reducing labor requirements and frequency of maintenance activities, this shift in strategy will reduce the materials portion of the operations and maintenance cost as well. The aim of this specific effort is to focus on the automation of data collection process. It is part of a series of planned efforts to target multiple elements of migrating the current preventive maintenance approach in nuclear power plants to a data-driven approach. These elements include data collection, management, analysis, visualization, in addition to value analysis and change enabling. The other five elements of migration were not considered because they are planned to be explicitly studied in multiple parallel efforts. Challenges including regulations requirements or limitations are planned in a future effort that focuses on change enabling. The risk and benefit/cost of the approach shift is planned in another effort targeted towards value. The storage, communication, computational power, data architecture, and protection are part of the information infrastructure and are planned in dedicated data management effort. The best means to present the data for assisted human decision making is planned in a data visualization effort. The data interpretation and patterns recognition for machine decision making is planned through multiple efforts in data analytics over the following years. This work identified seventeen data sources collection methods in nuclear power plants that could be automated for an integrated data platform that enables comprehensive and informed decision making. For each of the identified seventeen data sources, the base, modern, and state of the art states were described. The current state of data collection used by most utilities was identified as the "base state". The current achievable state was identified as the "modern state", a state that has either been achieved by at least some US utilities or in other industries. The future state that requires research and development to reach was identified as the "state of the art" state. The described states used an out-of-the-box thinking approach. This effort found that there is a hug potential for task automation and data fidelity improvements by evolving the current industry data collection methods. The majority of the processes analyzed were found to be manual and labor intensive and fell in the base state. As a result, the modern state often targeted reducing the manual logging efforts by using electronic and semi-intelligent means or complementing the work with sensors and mobile or fixed technologies that can reduce the demand of labor activities. The state of the art state involved applications advanced methods of data correlation, data mining, and machine learning along with increasing the spatial distribution and fidelity of data, coupling multiple data sources, and enabling the use of sophisticated mobile devices and machine comprehension methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Liquid-to-gas transfer of sodium in a liquid cathode glow discharge

Abstract Plasma-liquid interactions have been extensively studied with a focus on the transport of reactive species from the plasma to the liquid phase and their induced liquid phase chemistry and resulting applications. While solute transfer from the liquid to the gas phase in plasmas has been widely used in analytical chemistry, the underlying processes remain relatively unexplored. We report spatially and temporally resolved absolute density measurements of sodium in a plasma with a NaCl solution cathode using two-photon absorption laser induced fluorescence (TaLIF). The observed non-linear increase in sodium density with solution conductivity is shown to correlate with droplet generation as visualized by Mie scattering. The findings are explained by droplet generation by electrospray induced by Taylor cone formation as underpinning mechanism for the introduction of sodium in the plasma. An analytical sheath model combined with a scaling law shows an increase in electric field force with solution conductivity that is consistent with the observed non-linear increase in sodium density in the plasma with solution conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Role of electron pathway in dimensionally increasing water splitting reaction sites in liquid electrolytes

Hydrogen from water splitting is one of the most promising alternatives for fossil fuels in solving the global energy crisis, while its electrochemical reaction mechanism, especially in liquid electrolytes, remains unclear. Herein, how the electrode conductivity affects the reaction sites of oxygen evolution reactions (OERs) in acidic and alkaline solutions was investigated by employing visualization system and electrochemical testing. Inserting Au nanolayers greatly increased electrode conductivities, improved OER kinetics and reduced cell ohmic resistance, leading to excellent water splitting performances in both acidic and alkaline electrolytes. Furthermore, the in-situ visualization results showed more reaction sites and higher catalyst utilizations were achieved by augmenting the electrode conductivity, and reaction sites increased from 1-dimension to 2-dimension. Additionally, it was discovered that electrical conductivities of acidic and alkaline solutions are insufficient to overcome the sharp drop of potential in the electrical double layer for activating OER uniformly on low-conductivity catalysts, indicating the importance of electrical conductivity of the electrode in acidic and alkaline water electrolyzers. This study provided a guidance on how to develop efficient and compact electrodes for acidic and alkaline water electrolyzer stacks and other electrochemical devices, such as fuel cell, N2 reduction, CO 2 conversion, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Direct atomic fabrication and dopant positioning in Si using electron beams with active real-time image-based feedback

We report that semiconductor fabrication is a mainstay of modern civilization, enabling the myriad applications and technologies that underpin everyday life. However, while sub-10 nanometer devices are already entering the mainstream, the end of the Moore's law roadmap still lacks tools capable of bulk semiconductor fabrication on sub-nanometer and atomic levels, with probe-based manipulation being explored as the only known pathway. Here we demonstrate that the atomic-sized focused beam of a scanning transmission electron microscope can be used to manipulate semiconductors such as Si on the atomic level, inducing growth of crystalline Si from the amorphous phase, reentrant amorphization, milling, and dopant front motion. These phenomena are visualized in real-time with atomic resolution. We further implement active feedback control based on real-time image analytics to automatically control the e-beam motion, enabling shape control and providing a pathway for atom-by-atom correction of fabricated structures in the near future. Lastly, these observations open a new epoch for atom-by-atom manufacturing in bulk, the long-held dream of nanotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Designing Unmanned Aerial Survey Monitoring Program to Assess Floating Litter Contamination

Monitoring marine contamination by floating litter can be particularly challenging since debris are continuously moving over a large spatial extent pushed by currents, waves, and winds. Floating litter contamination have mostly relied on opportunistic surveys from vessels, modeling and, more recently, remote sensing with spectral analysis. This study explores how a low-cost commercial unmanned aircraft system equipped with a high-resolution RGB camera can be used as an alternative to conduct floating litter surveys in coastal waters or from vessels. The study compares different processing and analytical strategies and discusses operational constraints. Collected UAS images were analyzed using three different approaches: (i) manual counting (MC), using visual inspection and image annotation with object counts as a baseline; (ii) pixel-based detection, an automated color analysis process to assess overall contamination; and (iii) machine learning (ML), automated object detection and identification using state-of-the-art convolutional neural network (CNNs). Our findings illustrate that MC still remains the most precise method for classifying different floating objects. ML still has a heterogeneous performance in correctly identifying different classes of floating litter; however, it demonstrates promising results in detecting floating items, which can be leveraged to scale up monitoring efforts and be used in automated analysis of large sets of imagery to assess relative floating litter contamination.

Almeida, Sílvia (ORCID:0000000320636826)↗
DOE OSTI2020

In-situ visualization of corrosion behavior of Al CoCrFeNi high-entropy alloys during electrochemical polarization

In this study, the corrosion behavior of the Al x CoCrFeNi (x = 0.3, 0.5, 0.7) high-entropy alloys (HEAs) is investigated by an in-situ visualization system. Surface morphology changes on both micro-spatial and temporal scales are monitored in the 3.5 wt% NaCl solution during the potentiodynamic polarization. The microstructures of the Al x CoCrFeNi HEAs are characterized by SEM, EBSD, and EDS. The results show that the microstructure evolves from singe face-centered cubic (FCC) phase to multi-phases by increasing the Al content. The in-situ observations directly reveal the different localized corrosion processes in the AlxCoCrFeNi HEAs. In the single FCC phase Al 0.3 CoCrFeNi HEA, localized corrosion shows in the form of pitting. In the Al 0.5 CoCrFeNi and Al 0.7 CoCrFeNi alloys, which possess FCC and body-centered cubic (BCC) phases, the localized corrosion initiates and propagates in the Cr-depleted BCC phase. In addition, the in-situ visualization uncovers the evolution of current serration, which represents the propagation and repassivation of metastable pit during the polarization. The frequent occurrence of metastable pits indicates distinct repassivation ability of the Al 0.3 CoCrFeNi HEA.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Lund jet plane

Lund diagrams, a theoretical representation of the phase space within jets, have long been used in discussing parton showers and resummations. We point out that they can be created for individual jets through repeated Cambridge/Aachen declustering, providing a powerful visual representation of the radiation within any given jet. Concentrating here on the primary Lund plane, we outline some of its analytical properties, highlight its scope for constraining Monte Carlo simulations and comment on its relation with existing observables such as the zg variable and the iterated soft-drop multiplicity. We then examine its use for boosted electroweak boson tagging at high momenta. It provides good performance when used as an input to machine learning. Much of this performance can be reproduced also within a transparent log-likelihood method, whose underlying assumption is that different regions of the primary Lund plane are largely decorrelated. This suggests a potential for unique insight and experimental validation of the features being used by machine-learning approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Determining Coal Ash Impacts on Radium and Thorium Background Levels in Soil Using Rare Earth Element Analyses - 18604

One challenge at large remediation sites contaminated with radiological materials is differentiating between low-level site-related contamination and NORM. This is because sites contaminated with radiological materials, such as thorium processing and mining and milling facilities, often generate wastes that contain contaminants that are similar to NORM deposits. For sites in urban areas, this issue is further compounded due to the presence of historic industrial fill (historic fill) containing materials such as fly ash, coal ash, and red brick, that exhibit elevated radioactivity levels. These materials often have activity levels near, or even well above, a site's cleanup goal. At a large Superfund Site in the eastern US (Site), many of the suspected Site-related fill areas are commingled with coal and fly ash. As the cleanup criteria for the radionuclides of concern (ROC), radium (Ra) and thorium (Th), is 5 pico-Curies per gram above background, a four-pronged approach was developed to determine if the coal and fly ash are impacting the background levels of the ROCs. This evaluation included a review of boring logs to visually confirm the presence of historic fill, as well as coal fragments and coal ash; a literature review to establish the typical concentrations of Ra and Th found in coal and fly ash from US sources; the use of rare earth analyses to establish chemical signatures for non-Site related historic fill containing coal ash versus Site-related fill; and a quantitative analysis of Site-related data to determine if the radioactivity levels in historic fill containing coal were elevated. Soil samples were collected from two locations at the Site; fill areas containing coal ash that were not suspected to be impacted by Site activities, as well as fill areas containing coal ash that were associated with the former processing facility. These samples were analyzed for rare earth elements (REE), as well as Ra-228 and Th-232 and the ratios of lanthanum, cerium, and neodymium to Ra-228 and Th-232 were established for each sample. Based on a comparison of these data, a strong correlation was established between the rare earth/thorium decay chain ratios and the classification of material as either Site or non-Site related. These data were used to develop a higher background activity for fill areas containing non-Site related NORM. While the cleanup level defined in the Record of Decision remained unchanged, the higher background derived from the fly ash/coal ash material, as identified by REE analyses, resulted in higher project screening levels, which ensured that excavation activities did not 'chase' material that was not Site-related. To date, use of the coal ash background level has saved millions of dollars in cleanup costs since non-Site related contamination is not being remediated. Use of this approach to determine the appropriate background level for a site is relatively straightforward since it relies on visual observation of the soil for coal and fly ash, along with REE analyses, which is an inexpensive, quick, and established analytical method for soil samples. As long as a good rare earth profile of both contaminated and natural (in this case fly ash and coal ash) material can be established, the results can be quite definitive, which could result in significant volume reduction by minimizing the amount of material excavated and disposed of. This will lead to cost and time savings for what could be an otherwise costly and potentially complex excavation. Anyone performing environmental remediation of NORM contaminated sites may benefit from this paper and presentation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Evaluating lignocellulosic biomass, its derivatives, and downstream products with Raman spectroscopy

The creation of fuels, chemicals, and materials from plants can aid in replacing products fabricated from non-renewable energy sources. Before using biomass in downstream applications, it must be characterized to assess chemical traits, such as cellulose, lignin, or lignin monomer content, or the sugars released following an acid or enzymatic hydrolysis. The measurement of these traits allows researchers to gage the recalcitrance of the plants and develop efficient deconstruction strategies to maximize yields. Standard methods for assessing biomass phenotypes often have experimental protocols that limit their use for screening sizeable numbers of plant species. Raman spectroscopy, a non-destructive, non-invasive vibrational spectroscopy technique, is capable of providing qualitative, structural information and quantitative measurements. Applications of Raman spectroscopy have aided in alleviating the constraints of standard methods by coupling spectral data with multivariate analysis to construct models capable of predicting analytes. Hydrolysis and fermentation products, such as glucose and ethanol, can be quantified off-, at-, or on-line. Raman imaging has enabled researchers to develop a visual understanding of reactions, such as different pretreatment strategies, in real-time, while also providing integral chemical information. Finally, this review provides an overview of what Raman spectroscopy is, and how it has been applied to the analysis of whole lignocellulosic biomass, its derivatives, and downstream process monitoring.

09 BIOMASS FUELS↗
DOE OSTI2023

Visual Brick model authoring tool for building metadata standardization

In this study, the Brick ontology is a unified semantic metadata standard for building assets and their relationships, serving as a key enabler for effective interoperability and automation of building systems and analytics. However, creating a Brick model, in other words, standard semantic metadata based on the Brick ontology for a building dataset, can be a complex task. This paper presents two case studies of the creation of Brick models for real-world residential and commercial building datasets, highlighting the challenges during the Brick model creation process. Additionally, the paper introduces VizBrick, an interactive authoring tool for creating semantic building metadata. VizBrick facilitates the creation of Brick models by providing an intuitive visual interface and interactive capabilities, such as keyword search, automatic mapping suggestions, and recommendations. The use of VizBrick is shown to significantly reduce the time and effort required during the Brick model creation process.

42 ENGINEERING↗
DOE OSTI2022

Recent progress in in-situ visualization of electrochemical reactions in electrochemical energy devices

A growing body of evidence indicates that bubble dynamics are crucial performance-limiting factors on electrochemical reactions and energy conversion efficiencies in both half-cell and full cell device levels. This review aims to summarize the recent progress in in-situ visualization characterizations of electrochemical reactions and reactant/product transport in electrochemical energy systems. The latest achievements of various new electrodes, transparent cell designs, and development for simultaneous visualization of reactions at both electrodes and electrolyte/electrode interface are highlighted. The new insights into the influence of bubbles on reaction sites and associated electrochemical performances are discussed. Lastly, some perspectives on potential strategies for mitigating the bubble-induced energy losses are proposed for future research directions and opportunities in water electrolysis and other electrochemical energy systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Coupling of Independent Electrochemical Reactions and Fluorescence at Closed Bipolar Interdigitated Electrode Arrays

Electrochemical reactions occurring at the opposite ends of bipolar electrodes (BPEs) are necessarily coupled, enabling electron transfer events at one end to be read out optically, for example, by coupling to fluorogenic reactions at the other end. In order to explore the potential of this technique for studying multiple redox events, arrays of parallel BPE interdigitated electrode arrays (IDEAs) were fabricated and integrated with separate analytical and reporter microfluidic channels, respectively, in a closed BPE configuration. The apparatus was initially evaluated employing Fe(CN) 6 3/4- in the analytical channel coupled to weakly emissive resazurin and strongly emissive resorufin as the fluorogenic redox reporter pair. We then used the device to investigate a proton-coupled electron transfer reaction, hydroquinone (QH 2 ) oxidation, in structures with an integrated pH modulation electrode (PME). A pH-sensitive dye, fluorescein, was co-introduced into the analytical channel to monitor PME modulation of solution pH, and its coupling to QH 2 oxidation, thereby permitting changes in solution pH, and consequently QH 2 oxidation rate, to be monitored directly in the analytical channel and compared to the fluorescence in the reporter channel. Additionally, diffusion of OH - generated at the PME produced a spatial pH profile that was visualized via fluorescein emission, and, because the oxidation of QH 2 at each BPE is strongly dependent on the local pH, via the coupled fluorogenic reaction at the opposite pole of the corresponding BPE digit in the reporter channel. Thus, BPE IDEAs support the coupling of independent redox reactions and the use of fluorescence imaging to explore a diverse set of spatially varying electrochemical phenomena realized in a variety of electrochemical geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

OpenSAMPL: An Open Source Library for Timing and Synchronization Measurements and Analytics

Today's power grid operators are implementing timing and synchronization solutions that provide resilience to Global Navigation Satellite System (GNSS) vulnerabilities. These vendor-specific solutions often come with additional software applications that are designed to monitor that vendor's synchronization performance data. However, resilient timing architectures often resulting in multi-vendor solutions, including approaches that blend terrestrial clocks with space-based subscription services. In such an environment, collecting, analyzing, and visualizing data from a variety of sources within a single platform was heretofore not possible. To address this need, the US Department of Energy's Center for Alternative Synchronization and Timing (CAST) developed OpenSAMPL, the Open Synchronized Analytics and Monitoring Platform, an open-source Python framework for processing, loading, and observing clock measurement data from distributed devices. OpenSAMPL enables the ingestion of diverse clock-probe sources into a scalable time-series database and applies robust analytics. OpenSAMPL currently supports two vendor data pipelines, and will be extended to more in the near future, enabling seamless monitoring of a variety of timing and synchronization devices in a common environment.

Grant, Josh [ORNL] (ORCID:0000000163475060)↗
DOE OSTI2023

Imaging Field–Driven Melting of a Molecular Solid at the Atomic Scale

Solid–liquid phase transitions are basic physical processes, but atomically resolved microscopy has yet to capture their full dynamics. A new technique is developed for controlling the melting and freezing of self–assembled molecular structures on a graphene field–effect transistor (FET) that allows phase–transition behavior to be imaged using atomically resolved scanning tunneling microscopy. This is achieved by applying electric fields to 2,3,5,6–tetrafluoro–7,7,8,8–tetracyanoquinodimethane–decorated FETs to induce reversible transitions between molecular solid and liquid phases at the FET surface. Nonequilibrium melting dynamics are visualized by rapidly heating the graphene substrate with an electrical current and imaging the resulting evolution toward new 2D equilibrium states. An analytical model is developed that explains observed mixed–state phases based on spectroscopic measurement of solid and liquid molecular energy levels. The observed nonequilibrium melting dynamics are consistent with Monte Carlo simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Additive friction stir deposition induced stress ripples in aluminum alloy

In additive manufacturing, modification of the viscosity of softened or molten metal plays a significant role in the development of mechanical properties distribution. Similar to soft polymers, molten or softened metal usually exhibits vastly different viscoelastic properties. During scratching tests, viscoelastic polymers undergo spatiotemporal stress development and relaxation, causing stress ripples to form on their surfaces. Here, it is observed that friction stir-based solid-state manufacturing can yield similar stress ripples on softened aluminum alloys due to the linear motion of the deposition tool. Softened aluminum alloys exhibit viscoelastic and viscoplastic responses similar to polymeric material during the solid-state deposition process. In the final product, residual stress ripples appear on the surface of the metal alloy due to periodic residual stress relaxation, leading to oscillatory behavior from the bulk mechanical properties of the material. The orientation of the in-built stress pattern formed in the bulk of the additively manufactured metal alloy underneath the visually evident onion ring-like surface pattern formation is diametrically in the opposite direction. The experimentally observed results are consistent with analytical calculation and numerical simulations in terms of behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamics of oil–water interface at the beginning of the ultrasonic emulsification process

A lot of effort has been dedicated in recent years towards understanding the basics of cavitation induced emulsification, mainly in the form of single cavitation bubbles. Regarding bulk acoustic emulsification, a lot less research has been done. In our here presented work we utilize advanced high-speed observation techniques in visible light and X-Rays to build upon that knowledge and advance the understanding of bulk emulsion preparation. During research we discovered that emulsion formation has an acute impact on the behavior of the interface and more importantly on its position relative to the horn, hence their interdependence must be carefully studied. We did this by observing bulk emulsification with 2 cameras simultaneously and corroborating these measurements with observation under X-Rays. Since the ultrasonic horns location also influences interface behavior, we shifted its initial position to different locations nearer to and further away from the oil–water interface in both phases. We found that a few millimeters distance between the horn and interface is not enough for fine emulsion formation, but that they must be completely adjacent to each other, with the horn being located inside the oil–water interface. We also observed some previously undiscovered phenomena, such as the splitting of the interface to preserve continuous emulsion formation, climbing of the interface up the horn and circular interface protrusions towards the horn forming vertical emulsion streams. Interestingly, no visible W/O emulsion was ever formed during our experiments, only O/W regardless of initial horn position.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Reverse engineering (RE) analysts struggle to address critical questions about the safety of binary code accurately and promptly, and their supporting program analysis tools are simply wrong sometimes. The analysis tools have to approximate in order to provide any information at all, but this means that they introduce uncertainty into their results. And those uncertainties chain from analysis to analysis. We hypothesize that exposing sources, impacts, and control of uncertainty to human binary analysts will allow the analysts to approach their hardest problems with high-powered analytic techniques that they know when to trust. Combining expertise in binary analysis algorithms, human cognition, uncertainty quantification, verification and validation, and visualization, we pursue research that should benefit binary software analysis efforts across the board. We find a strong analogy between RE and exploratory data analysis (EDA); we begin to characterize sources and types of uncertainty found in practice in RE (both in the process and in supporting analyses); we explore a domain-specific focus on uncertainty in pointer analysis, showing that more precise models do help analysts answer small information flow questions faster and more accurately; and we test a general population with domain-general sudoku problems, showing that adding "knobs" to an analysis does not significantly slow down performance. This document describes our explorations in uncertainty in binary analysis.

97 MATHEMATICS AND COMPUTING↗