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Results for “Uncertainty visualization”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Abstract for CRADA between VariGrid Explorations Inc. and NETL (AGMT-0863)

As the energy industry continues to invest in data, big data, and advanced analytics to improve production, reduce operation and maintenance costs, improve safety, and reduce risks, uncertainty will serve as a limiting factor in the success of these operations. Intuitive communication of uncertainty can provide more transparency in the decision-making process; offering the ability to more accurately evaluate the risk and impact of decisions, identify data and knowledge gaps, and evaluate trade-offs. The issue of uncertainty will thus play a large role in the success of investments that rely on big data and data analytics. However, no robust method for representation of uncertainty in spatial data visuals currently exists. As such, uncertainty is, at best, communicated using multiple independent visuals and aggregated in final displays, or frequently omitted altogether. Failure to accurately and effectively quantify and communicate uncertainty poses a barrier, limiting critical information that would better allow businesses to make more accurate and intelligent decisions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation using Visual Analytics

We describe a novel study of decision-making processes around misinformation on social media. Using a custom-built visual analytic system, we presented users with news content from social media accounts from a variety of news outlets, including outlets engaged in distributing misinformation. We conducted controlled experiments to study decision-making regarding the veracity of these news outlets and tested the role of confirmation bias (the tendency to ignore contradicting information) and uncertainty of information on human decision-making processes. Our findings reveal that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways. We also find that instructing participants even to explicitly disconfirm given hypotheses does not significantly impact their decision-making regarding misinformation when compared to a control condition. Our findings have the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

misinformation, decision making, social media, vis↗
DOE OSTI2019

The Role of Sensitivity Analysis in the Building Performance Analysis: A Critical Review

A building system is highly nonlinear and commonly includes a variety of parameters ranging from the architectural design to the building mechanical and energy system. Serving as a powerful tool to understand the complicated building system, sensitivity analysis (SA) has been receiving increasing attention in the recent decade. This review paper focused on the application of SA in the building performance analysis (BPA). First, the existing review papers on the application of SA for BPA were briefly reviewed and summarized. Then, a large amount of recent SA case studies in BPA were reviewed. The critical information regarding the implementation of a SA, such as the sampling method, the SA method, etc., were extracted and summarized. Next, an extensive analysis was performed to evaluate the role of the SA in the BPA. This includes: 1) The typical selection of the input and output parameters for the SA were visualized; 2) The uncertainty level and sampling strategies for the input parameters were investigated; 3) The principles, benefits, and drawbacks of the SA methods were analyzed and summarized; and 4) The various tools used in the SA, including the simulation software, sampling tools, and SA tools were introduced to facilitate the practitioners. Lastly, several conclusions were summarized on the role of the SA in the BPA. Suggestions were also provided to offer practical solutions to the current challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Streamlining the Coupling of BISON and Dakota Through the NEAMS Workbench

Metallic nuclear fuels for use in advanced reactors are an active area of research and development. Robust, accurate metallic fuel performance models are necessary for the design, analysis, and licensing of such reactors. However, metallic fuel performance models require additional development; they are not as mature as uranium dioxide fuel performance models. To support further metallic fuel development, Oak Ridge National Laboratory and the University of Florida have streamlined the coupling of the BISON fuel performance code with Design Analysis Kit for Optimization and Terascale Applications (Dakota) statistical analysis tool through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench. This work included performing three different sensitivity analyses on metallic nuclear fuel models in BISON. The analyses examined were a general model of the IFR-1 experiment, the X430 experiment T654 pin, and the X430 experiment T651 pin. The results suggest that BISON and Dakota can be integrated through NEAMS Workbench to perform sensitivity and uncertainty analyses and visualize the results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Circular Trajectory Approach for Online Sinusoidal Signal Distortion Monitoring and Visualization

The increasing complexity and uncertainties of modern power systems are placing significant demands on signal monitoring techniques. This work proposes the Circular Trajectory Approach (CTA) for online sinusoidal signal distortion monitoring and visualization. CTA can detect distortions of a sinusoidal signal. Compared with existing waveform anomaly detection techniques, CTA is faster in detection and less computation intensive. It thus supports edge devices and online applications. CTA also offers a new means of sinusoidal signal distortion visualization. It can reveal the distorted sections in a sinusoidal cycle and clearly display the distortions. The proposed approach is tested on real data from an open source EPRI dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Sci-Thur PM – Brachytherapy 03: Identifying the impact of seroma visualization on permanent breast seed implant brachytherapy

Purpose: Uncertainties in target identification can reduce treatment accuracy in permanent breast seed implant (PBSI) brachytherapy. This study evaluates the relationship between seroma visualization and seed placement accuracy. Methods: Spatially co-registered CT and 3D ultrasound (US) images were acquired for 10 patients receiving PBSI. Seromas were retrospectively contoured independently by 3 radiation oncologists on both CT and US and respective consensus volumes were defined, CTV{sub CT} and CTV{sub US}. The seroma clarity and inter-user conformity index (CI), as well as inter-modality CI, volume, and positional differences were evaluated. Correlations with seed placement accuracy were then assessed. CTVs were expanded by 1.25cm to create PTV{sub CT} and PTV{sub US} and evaluate the conformity with PTV{sub Clinical} (CTV{sub Clinical}+1.25cm) used in treatment planning. The change in PTV coincidence by expanding PTV{sub Clinical} by 0.25cm was determined. Results: CTV{sub US} were a mean 68 ± 12% smaller than CTV{sub CT} and generally had improved clarity and inter-user conformity. No correlations between seed displacement and CTV{sub US}-CTV{sub CT} positional difference or CI were observed. Greater seed displacements were associated with larger CTV{sub US}-CTV{sub CT} volume differences (r=−0.65) and inter-user CT CI (r=−0.74). A median (range) 88% (71–99%) of PTV{sub CT} and 83% (69–100%) of PTV{sub US} were contained within PTV{sub Clinical}. Expanding treatment margins to 1.5cm increased coincidence to 98% (86–100%) and 94% (82–100%), respectively. Conclusions: Differences in seroma visualization impacts seed displacement in PBSI. Reducing dependence on CT by incorporating 3DUS into target identification, or expanding CT-based treatment margins to 1.5cm may reduce or mitigate uncertainties related to seroma visualization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Confidence-Guided Technique for Tracking Time-Varying Features

Application scientists often employ feature tracking algorithms to capture the temporal evolution of various features in their simulation data. However, as the complexity of the scientific features is increasing with the advanced simulation modeling techniques, quantification of reliability of the feature tracking algorithms is becoming important. One of the desired requirements for any robust feature tracking algorithm is to estimate its confidence during each tracking step so that the results obtained can be interpreted without any ambiguity. To address this, we develop a confidence-guided feature tracking algorithm that allows reliable tracking of user-selected features and presents the tracking dynamics using a graph-based visualization along with the spatial visualization of the tracked feature. Here, the efficacy of the proposed method is demonstrated by applying it to two scientific datasets containing different types of time-varying features.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Variable Grid Method

NETL’s Variable Grid Method (VGM) is a novel approach that leverages GIS capabilities to simultaneously visualize and quantify spatial data trends and underlying data uncertainty. The flexible VGM approach utilizes a range of spatial datasets and uncertainty quantifications, which can be calculated using data related to sample density, sample variance, interpolation error, multiple simulations, etc., to create an integrated visualization of data and uncertainty. The intuitive manner of the VGM helps communicate the relationship between uncertainty and spatial data to effectively guide research, support advanced computation analyses, and helps inform research, management and policy decisions. The VGM approach is being developed into a standalone tool designed to integrate into a variety of research workflows, providing users the capabilities to utilize the VGM for their datasets, analysis, and models in support of their decision making needs. The VGM approach was developed as part of NETL’s Offshore portfolio. It was further matured and utilized in projects associated with both NETL’s Unconventional Resources and Carbon Storage portfolios, and is now being further developed by Varigrid, LLC.

Carbon Storage↗
DOE OSTI2025

Visual‐Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning

Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real‐world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision‐makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically developed tools for scenario analysis rigorously quantify the combined effects of multiple sources of uncertainty, but the practical application of these models is limited by the challenges of information visualization and communication of results. In short, municipal water supply planners lack access to planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user‐friendly visual and interactive tools to enhance user accessibility. In this work, we fill this gap by proposing Visual‐Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. Santa Barbara faces multiple uncertainties from pending state and federal regulations to changing hydrology and water demand. The city seeks to increase its water portfolio robustness by expanding its seawater desalination plant, but must decide how much capacity to add. We introduce computational tools that assess uncertainty across nine uncertain drivers identified with the help of water planners in SB. To allow public participation in the desalination expansion decision, we develop interactive visual‐analytics to aid decision‐makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness and aim to enhance participation and uncertainty characterization of urban water planning efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Investigation of Relevant Distribution System Representation With DG for Voltage Stability Margin Assessment

This paper emphasizes the importance of including unbalanced distribution systems for voltage stability studies in power systems. The paper aims to: discuss the various simulation methods for power system analysis; highlight the need for modeling unbalanced distribution system for accurate load margin assessment; demonstrate the influence of net-load unbalance (NLU) on voltage stability margin (VSM). We also share a T&D co-simulation interface with commercial power system solvers. The distribution system is evolving rapidly with high proliferation of distributed energy resources (DERs); these are not guaranteed to proliferate in a balanced manner and uncertainty resulting due to these DERs is well acknowledged. These uncertainties cannot be captured or visualized without representing the distribution system in detail along with the transmission system. We show the impact of proliferation of DERs in various 3-phase proportions on voltage stability margin through T&D co-simulation. We also study the impact of volt/VAR control on voltage stability margin. This analysis is only possible by representing the distribution system in detail through T&D co-simulation. In conclusion, higher percentage of net-load unbalance (NLU) in distribution system aggravates the voltage stability margin of the distribution system, which can further negatively influence the overall voltage stability margin of the system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

SIMPA

SIMPA (Spatially Integrated Multivariate Probabilistic Assessment) is a Python-based fuzzy logic tool designed to help assess the likelihood of fluid and/or gas migration pathways throughout the subsurface. The SIMPA tool helps users develop and apply fuzzy logic to various datasets to construct knowledge-based inferential rules that reduce uncertainty and results in a visual representation depicting the likelihood of potential fluid and/or gas migration pathways. SIMPA results can offers an understanding of the magnitude and extent of natural and anthropogenic subsurface pathways, offering insight to subsurface hazards to improve storage assessments and critical information for improving industry decisions related to the use of various CCS methods and technologies. In addition, SIMPA can offer new insights for areas with little to no data to help inform site selection and production, evaluate potential risks and hazards, and support various decision making and risk management needs.

carbon storage↗
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↗
DOE OSTI2022

Quantifying uncertainties in crystal electric field Hamiltonian fits to neutron data

We systematically examine uncertainties from fitting rare earth single-ion crystal electric field (CEF) Hamiltonians to inelastic neutron scattering data. Using pyrochlore and delafossite structures as test cases, we find that uncertainty in CEF parameters can be large despite visually excellent fits. These results show Yb ^{3+} 3 + compounds have particularly large g g -tensor uncertainty because of the few available peaks. In such cases, additional constraints are necessary for meaningful fits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗