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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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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Visualizing redox orbitals and their potentials in advanced lithium-ion battery materials using high-resolution x-ray Compton scattering

Reduction-oxidation (redox) reactions are the key processes that underlie the batteries powering smartphones, laptops, and electric cars. A redox process involves transfer of electrons between two species. For example, in a lithium-ion battery, current is generated when conduction electrons from the lithium anode are transferred to the redox orbitals of the cathode material. The ability to visualize or image the redox orbitals and how these orbitals evolve under lithiation and delithiation processes is thus of great fundamental and practical interest for understanding the workings of battery materials. In this study, we show that inelastic scattering spectroscopy using high-energy x-ray photons (Compton scattering) can yield faithful momentum space images of the redox orbitals by considering lithium iron phosphate (LiFePO 4 or LFP) as an exemplar cathode battery material. Our analysis reveals a new link between voltage and the localization of transition metal 3d orbitals and provides insight into the puzzling mechanism of potential shift and how it is connected to the modification of the bond between the transition metal and oxygen atoms. Our study thus opens a novel spectroscopic pathway for improving the performance of battery materials.

25 ENERGY STORAGE↗
DOE OSTI2020

3D Morphology of Bimodal Porous Copper with Nano-Sized and Micron-Sized Pores to Enhance Transport Properties for Functional Applications

Multiscale porous metals with multiscale porosity from nanometer to micrometer have a high specific surface area and high effective diffusivity for ion transport, thereby enhancing functionalities and extending the applications of porous metals. Herein, the Cu–Fe–Al ternary system was selected as the precursor alloy to construct multiscale, bimodal porous copper by the chemical dealloying method. The effect of the phase composition and initial microstructure of precursor alloys (Al x Fe 75– x Cu 25 , x = 10–60) on the three-dimensional (3D) morphology of multiscale porous metals was systematically investigated, with a goal to precisely control the multiscale porous structure. The four crystal structure phases (body-centered cubic (BCC), face-centered cubic (FCC), CsCl type (B2), and monoclinic) in precursor alloys were analyzed by synchrotron X-ray diffraction refinement. The 3D morphology, feature size distribution, and tortuosity of four representative porous Cu after dealloying Al x Fe 75– x Cu 25 ( x = 10, 30, 50, and 60) precursor alloys were directly visualized and quantified via advanced synchrotron X-ray nanotomography. The relationship between the phases/crystal structures of precursor alloys and their corresponding porous morphology was established: the micron-sized pores in bimodal porous Cu are formed by dissolving the CuFeAl phase with BCC and monoclinic crystal structures, and the nano-sized pores are formed by dealloying the CuFeAl phase with FCC and B2 crystal structures. The size of the nanoporous structure depends on the ratio between the more noble and more active components in the precursor alloy, while the size of the microporous structure depends on the corresponding phase size in the precursor alloy. The tortuosity results showed that the multiscale porous structure with both nanoporosity and microporosity exhibits lower tortuosity, which will enhance transport properties for functional applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Transport–Friendly Microstructure in SSC–MEA: Unveiling the SSC Ionomer–Based Membrane Electrode Assemblies for Enhanced Fuel Cell Performance

The significant role of the cathodic binder in modulating mass transport within the catalyst layer (CL) of fuel cells is essential for optimizing cell performance. This investigation focuses on enhancing the membrane electrode assembly (MEA) through the utilization of a short-side-chain perfluoro-sulfonic acid (SSC-PFSA) ionomer as the cathode binder, referred to as SSC-MEA. This study meticulously visualizes the distinctive interpenetrating networks of ionomers and catalysts, and explicitly clarifies the triple-phase interface, unveiling the transport-friendly microstructure and transport mechanisms inherent in SSC-MEA. The SSC-MEA exhibits advantageous microstructural features, including a better-connected ionomer network and well-organized hierarchical porous structure, culminating in superior mass transfer properties. Relative to the MEA bonded by long-side-chain perfluoro-sulfonic acid (LSC-PFSA) ionomer, noted as LSC-MEA, SSC-MEA exhibits a notable peak power density (1.23 W cm –2 ), efficient O 2 transport, and remarkable proton conductivity (65% improvement) at 65 °C and 70% relativity humidity (RH). These findings establish crucial insights into the intricate morphology-transport-performance relationship in the CL, thereby providing strategic guidance for developing highly efficient MEA.

25 ENERGY STORAGE↗
DOE OSTI2026

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗
DOE OSTI2017

Morse-Smale Analysis of Ion Diffusion in Ab Initio Battery Materials Simulations

Ab initio molecular dynamics (AIMD) simulations are increasingly useful in modeling, optimizing and synthesizing materials in energy sciences. In solving Schrödinger’s equation, they generate the electronic structure of the simulated atoms as a scalar field. However, methods for analyzing these volume data are not yet common in molecular visualization. The Morse-Smale complex is a proven, versatile tool for topological analysis of scalar fields. In this paper, we apply the discrete Morse-Smale complex to analysis of first-principles battery materials simulations. We consider a carbon nanosphere structure used in battery materials research, and employ Morse-Smale decomposition to determine the possible lithium ion diffusion paths within that structure. Our approach is novel in that it uses the wavefunction itself as opposed distance fields, and that we analyze the 1-skeleton of the Morse-Smale complex to reconstruct our diffusion paths. Furthermore, it is the first application where specific motifs in the graph structure of the complete 1-skeleton define features, namely carbon rings with specific valence. We compare our analysis of DFT data with that of a distance field approximation, and discuss implications on larger classical molecular dynamics simulations.

25 ENERGY STORAGE↗
DOE OSTI2026

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE↗
DOE OSTI2020

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical consequences of battery particles’ evolving (de)attachment with the conductive matrix. Herein, we tackle this issue with a unique combination of multiscale experimental approaches, machine-learning-assisted statistical analysis, and experiment-informed mathematical modeling. Our results suggest that the degree of particle detachment is positively correlated with the charging rate and that smaller particles exhibit a higher degree of uncertainty in their detachment from the carbon/binder matrix. We further explore the feasibility and limitation of utilizing the reconstructed electron density as a proxy for the state-of-charge. Our findings highlight the importance of precisely quantifying the evolving nature of the battery electrode’s microstructure with statistical confidence, which is a key to maximize the utility of active particles towards higher battery capacity.

25 ENERGY STORAGE↗
DOE OSTI2020

Quantitative probing of the fast particle motion during the solidification of battery electrodes

Synchrotron x-ray tomography represents one of the most powerful imaging techniques that can visualize the three-dimensional microstructural complexity with a high spatial resolution. To date, however, the temporal resolution of this technique has been handicapped by the intrinsic limitations in the data acquisition speed and the lack of a suitable data processing method. The present study aims to fundamentally resolve this challenge by implementing a data analysis method that is based on differentiating discrete tomography reconstruction from a continuous scan reconstruction. With this methodological development, we capture and quantify the particle motion during the solidification of battery electrodes and reveal the statistics of the dynamically evolving motion in the drying process, which has been challenging to resolve. We discover that the particle motion exhibits a strong dependence on its geometric location within a drying electrode. Our results also imply that the final electrode quality can be controlled by balancing the solvent evaporation rate and the particle mobility in the region close to the drying surface.

25 ENERGY STORAGE↗
DOE OSTI2016

In situ TEM probing of crystallization form-dependent sodiation behavior in ZnO nanowires for sodium-ion batteries

Development of sodium-ion battery (SIB) electrode materials currently lags behind electrodes in commercial lithium-ion batteries (LIBs). However, in the long term, development of SIB components is a valuable goal. Their similar, but not identical, chemistries require careful identification of the underlying sodiation mechanism in SIBs. Here in this study, we utilize in situ transmission electron microscopy to explore quite different sodiation behaviors even in similar electrode materials through real-time visualization of microstructure and phase evolution. Upon electrochemical sodiation, single-crystalline ZnO nanowires (sc-ZNWs) are found to undergo a step-by-step electrochemical displacement reaction, forming crystalline NaZn 13 nanograins dispersed in a Na 2 O matrix. This process is characterized by a slowly propagating reaction front and the formation of heterogeneous interfaces inside the ZNWs due to non-uniform sodiation amorphization. In contrast, poly-crystalline ZNWs (pc-ZNWs) exhibited an ultrafast sodiation process, which can partly be ascribed to the availability of unobstructed ionic transport pathways among ZnO nanograins. Thus the reaction front and heterogeneous interfaces disappear. The in situ TEM results, supported by calculation of the ion diffusion coefficient, provide breakthrough insights into the dependence of ion diffusion kinetics on crystallization form. This points toward a goal of optimizing the microstructure of electrode materials in order to develop high performance SIBs.

25 ENERGY STORAGE↗
DOE OSTI2019

Quantitative Parameter Estimation, Model Selection, and Variable Selection in Battery Science

Numerical physics-based models are useful in understanding battery performance and devel- oping optimal battery design architectures. Data science developments have enabled software algorithms to perform data analysis and decision making that traditionally could only be per- formed by technical experts. Traditional workflows of model development - manual parameter estimation through visual comparison of simulations to experimental observations, and model discrimination through expert intuition - are time-consuming, and difficult to justify. This paper compares the conclusions derived from computationally scalable algorithms to conclu- sions developed by expert researchers. This paper illustrates how data science techniques, such as cross-validation and lasso regression, can be used to augment physics-based simulations to perform data analysis such as parameter estimation, model selection, variable selection, and model-guided design of experiment. The validation of these algorithms is that they produce results similar to those of the expert modeler. The algorithms outlined are well-established and the approaches are general, so can be applied to a variety of battery chemistries and architectures. The conclusions reached using these approaches are in agreement with expert analysis (literature results), were reached with minimal human intervention, and provide quantitative justification. By minimizing the amount of expert time, and providing rigorous quantitative justifications, these methods may accelerate battery development.

25 ENERGY STORAGE↗
DOE OSTI2014

A new method for tracking organ motion on diagnostic ultrasound images

Purpose: Respiratory-gated irradiation is effective in reducing the margins of a target in the case of abdominal organs, such as the liver, that change their position as a result of respiratory motion. However, existing technologies are incapable of directly measuring organ motion in real-time during radiation beam delivery. Hence, the authors proposed a novel quantitative organ motion tracking method involving the use of diagnostic ultrasound images; it is noninvasive and does not entail radiation exposure. In the present study, the authors have prospectively evaluated this proposed method. Methods: The method involved real-time processing of clinical ultrasound imaging data rather than organ monitoring; it comprised a three-dimensional ultrasound device, a respiratory sensing system, and two PCs for data storage and analysis. The study was designed to evaluate the effectiveness of the proposed method by tracking the gallbladder in one subject and a liver vein in another subject. To track a moving target organ, the method involved the control of a region of interest (ROI) that delineated the target. A tracking algorithm was used to control the ROI, and a large number of feature points and an error correction algorithm were used to achieve long-term tracking of the target. Tracking accuracy was assessed in terms of how well the ROI matched the center of the target. Results: The effectiveness of using a large number of feature points and the error correction algorithm in the proposed method was verified by comparing it with two simple tracking methods. The ROI could capture the center of the target for about 5 min in a cross-sectional image with changing position. Indeed, using the proposed method, it was possible to accurately track a target with a center deviation of 1.54 ± 0.9 mm. The computing time for one frame image using our proposed method was 8 ms. It is expected that it would be possible to track any soft-tissue organ or tumor with large deformations and changing cross-sectional position using this method. Conclusions: The proposed method achieved real-time processing and continuous tracking of the target organ for about 5 min. It is expected that our method will enable more accurate radiation treatment than is the case using indirect observational methods, such as the respiratory sensor method, because of direct visualization of the tumor. Results show that this tracking system facilitates safe treatment in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

How Can Construction Process Simulation Modeling Aid the Integration of Lean Principles in the Factory-Built Housing Industry?

New and existing factories that produce and deliver factory-built housing can benefit from construction process simulation modeling to explore the integration of Lean principles in their operations. Construction process simulation modeling provides digital or virtual recreations of the real-world factory environments to visualize, quantify, analyze, and optimize their underlying behavior, including factory productivity, material flow, labor dynamics, bottlenecks, and work scope. One of the key benefits of process simulation modeling is the ability to create and compare "what-if" scenarios, including integrating Lean principles such as reducing waste (for example, transportation, waiting), line balancing, and just-in-time concepts. In general, three process simulation methods are widely used: discrete event simulation (DES), agentbased modeling (ABM), and system dynamics (SD). Myriad process simulation software also is available, but depending on the industry, complexity of the system, and purposes of the simulation, some software might be more appropriate. Similar to how computer-aided design (CAD) software such as AutoCAD and Rhinoceros enable building design of modular or factory-built housing, process simulation modeling software such as jStrobe, ProModel, and AnyLogic can enable factory design of new and existing factories to deliver modular affordable housing at scale, as opposed to traditional site-built construction. Software with DES capabilities can help generate a process model that is a logical representation of resources and activities in a factory. Software with CAD-DES integration can leverage product-process data integration to help spatially visualize a DES model of the factory in the CAD environment. Software with multimethod simulation capabilities, widely used in the manufacturing industry, brings together DES, ABM, and SD in a single platform that allows visualization, quantification, analyses, and optimization at varying data fidelities. Near-real-time data from an existing factory can be directly plugged into multimethod simulation software so that the construction process simulation model is a near-accurate representation of the real-world factory conditions. This report provides insights into the use of simulation as an aid to integrate Lean concepts in factories, including guidelines for selecting the appropriate process simulation modeling method and software. These insights have been developed as part of ongoing process simulation modeling research, development, and demonstration projects at the U.S. Department of Housing and Urban Development, the U.S. Department of Energy, and the National Renewable Energy Laboratory focused on how process simulation models can enable better integration of resilience, energy efficiency, and low-carbon design strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Impact of supercritical carbon dioxide on the frictional strength of and the transport through thin cracks in shale

Understanding the mechanical and transport behavior of thin (i.e. small aperture) cracks slipping under supercritical carbon dioxide (sc-CO 2 ) conditions is essential to evaluate the integrity of sealing formations with buoyant sc-CO 2 below and the success of waterless fracturing. The two major items of interest in this work are frictional strength and permeability change of the crack. We used a triaxial cell that permits in situ visualization to conduct and monitor slippage along the faces of narrow cracks subjected to triaxial stresses. Such cracks are analogs to small geological faults. We tested carbonate-rich, 1-inch diameter Wolfcamp shale samples that are saw cut 30° to vertical to create a thin crack. Friction coefficients ranged from about 0.6 to 0.8 consistent with expectations for brittle rocks. The sc-CO 2 generally did not alter friction coefficient over the time scale of experiments. From a transport perspective, saturating cracks with sc-CO 2 substantially decreased permeability of the crack by 26%–52%, while slip resulted in a variety of permeability responses. Overall, the combined impact of sc-CO 2 saturation and slip reduced fault permeability for all tests. Our observations support the notion that the sealing capacity of some caprocks improves when saturated with sc-CO 2 and that some slip of small fractures is not necessarily detrimental to caprock integrity.

58 GEOSCIENCES↗
NASA NTRS2012

Effects of Dietary Iron and Gamma Radiation on the Rat Retina

A health risk of concern for NASA relates to radiation exposure and its synergistic effects with other space environmental factors, includi ng nutritional status of the crew. Astronauts consume almost three times the recommended daily allowance of iron due to the use of fortifie d foods aboard the International Space Station, with iron intake occa sionally exceeding six times the recommended values. Recently, NASA has become concerned with visual changes associated with spaceflight, a nd research is being conducted to elucidate the etiology of eye structure alterations in the spaceflight environment. Terrestrially, iron o verload is also associated with certain optic neuropathies. In additi on, due to its role in Fenton reactions, iron can potentiate oxidative stress, which is a recognized cause of cataract formation. As part o f a study investigating the combined effects of radiation exposure an d iron overload on multiple physiological systems, we focused on defining the effects of both treatments on eye biology. In this study, 12- week-old Sprague-Dawley rats were assigned to one of four experimental groups: normal iron/no radiation (Control/Sham), high iron/no radiat ion (Fe/Sham), normal iron/gamma radiation (3 Gy cumulative dose, fra ctionated at 0.375 Gy/d every other day for 16 d) (Control/Rad), and high iron/gamma radiation (Fe/Rad). Oxidative stress-induced DNA damag e, measured as concentration of the marker 8-hydroxy-2'-deoxyguanosine (8OHdG) in eye retinal tissue by enzyme-immunoanalysis did not show significant changes among treatments. However, there was an overall i ncrease in 8OHdG immunostaining density in retina sections due to radiation exposure (P = 0.05). Increased dietary iron and radiation expos ure had an interactive effect (P = 0.02) on 8OHdG immunostaining of t he retinal ganglion cell layer with iron diet increasing the signal in the group not exposed to radiation (P = 0.05). qPCR gene expression profiling of relevant target genes indicated upregulation of ferritin light chain (P = 0.09) as a result of dietary iron but no change in e xpression of the gene for ferritin heavy chain. Immunolocalization of light chain and heavy chain of the iron storage protein ferritin showed the expected distribution in the choroid, photoreceptor layer, inn er nuclear layer and in the inner plexiform layer that corresponded t o the synaptic terminals of bipolar cells. Evidence of stress and damage in the retina was also suggested by a decrease in expression of th e survival marker Bcl2 (P = 0.01) and the protective proteins clusterin (P = 0.04) and heat shock factor 1 (Hsf1, P < 0.001), as a result o f increased dietary iron. The effect of increased iron on expression of the antioxidant enzyme heme oxygenase 1 (Hmox1) had a significant interaction with the effect of radiation (P < 0.001). In summary, the results of this study indicate that both gamma radiation exposure and a moderate increase in dietary iron can contribute to deleterious cha nges in retinal health and physiology.

Morgan, Jennifer↗
DOE OSTI2017

Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery

The in-depth understanding of the minority phases’ roles in functional materials, e.g., batteries, is critical for optimizing the system performance and the operational efficiency. Although the visualization of battery electrode under operating conditions has been demonstrated, the development of advanced data-mining approaches is still needed in order to identify minority phases and to understand their functionalities. The present study uses nanoscale X-ray spectromicroscopy to study a functional LiCoO 2 /Li battery pouch cell. The data-mining approaches developed herein were used to search through over 10 million X-ray absorption spectra that cover more than 100 active cathode particles. Two particles with unanticipated chemical fingerprints were identified and further analyzed, providing direct evidence and valuable insight into the undesired side reactions involving the cation dissolution and precipitation as well as the local overlithiation-caused subparticle domain deactivation. As a result, the data-mining approach described in this work is widely applicable to many other structurally complex and chemically heterogeneous systems, in which the secondary/minority phases could critically affect the overall performance of the system, well beyond battery research.

25 ENERGY STORAGE↗
DOE OSTI2017

Experimental and Theoretical Analysis of Ink Dispersion Stability for Polymer Electrolyte Fuel Cell Applications

The aggregate size in fuel cell catalyst inks depends on the type of dispersion medium, particle concentration, and addition of stabilizing agents. In this work, ink stability and particle size of carbon black and carbon black/Nafion dispersions in four non-aqueous media, viz., methanol, ethanol, isopropanol and ethyl acetate are studied. Based on visual inspection, isopropanol is found to be the best medium for dispersion of carbon black inks. To rationalize this observation, a semi-empirical model based on diffusion-limited aggregation was developed to evaluate the rate of particle aggregation and predict the ink stability time for each dispersion medium. The proposed model supports the experimental observation by qualitatively predicting the same relationship between carbon stability and the dispersion media. The model also showed that the dielectric constant of the dispersion medium and the particle zeta potential are primarily responsible for the ink stability. Particle size for the different inks was determined by dynamic light scattering with and without dilution. Experimental results show that Nafion is a strong stabilizing agent, increasing the ink stability and decreasing the particle size of carbon aggregates. The beneficial effects of Nafion are independent of its concentration and are observed even at Nafion volume fractions of 10 wt%. The interaction energy is found to be a strong function of the surface potential for the dispersion medium with a higher dielectric constant.

25 ENERGY STORAGE↗
DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗