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At least 145 records · Page 8

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION

Celestial Mapping System Videos

The Celestial Mapping System (CMS) is a software platform to generate virtual 3D globes for celestial bodies within our solar system. Multiple planetary data layers can be added to the virtual globe to provide visualization of high-resolution imagery and elevation data, which enables precise measurements, tools for analytical capabilities and a broad range of other functionalities to assist planetary scientists and mission planners. Third-party planetary data can be ingested into CMS with minimal effort. The present focus of CMS is on developing lunar mapping tools to provide features such as: 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo, CLPS and international mission landing site annotations, 3D Models, stereoscopic view, terrain profiling, line of sight analysis, sunlight shading and many more. The application has been developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placement and traverse path optimization.

Mapping

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

Kao, David

Graphic Three-Axes Presentation of Residual Gas Analyser Data

Residual gas analyzers (RGA) are commonly used to measure the composition of residual gases in thermal-vacuum test chambers. Measurements from RGAs are often used to identify and quantify outgassing contaminants from a test article during thermal-vacuum testing. RGA data is typically displayed as snapshots in time, showing instantaneous concentrations of ions from ionized residual gas molecules at different atomic masses. A method was devised by the authors to present RGA data in a three-axis format, plotting atomic mass unit (AMU), ion concentration as a function of AMU, and time, to provide a clear graphic visualization ot trends in gas concentration changes and to initiate a valuable analytical tool to interpret test article outgassing rates during thermal-vacuum testing.

data analysis

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC

Comparison of simulator fidelity model predictions with in-simulator evaluation data

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

Parrish, R. V.

Twelfth Annual Conference on Manual Control

Main topics discussed cover multi-task decision making, attention allocation and workload measurement, displays and controls, nonvisual displays, tracking and other psychomotor tasks, automobile driving, handling qualities and pilot ratings, remote manipulation, system identification, control models, and motion and visual cues. Sixty-five papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile, and remote control systems.

Wempe, T. E.

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung

A comparative review of optical surface contamination assessment techniques

This paper will review the relative sensitivities and practicalities of the common surface analytical methods that are used to detect and identify unwelcome adsorbants on optical surfaces. The compared methods include visual inspection, simple reflectometry and transmissiometry, ellipsometry, infrared absorption and attenuated total reflectance spectroscopy (ATR), Auger electron spectroscopy (AES), scanning electron microscopy (SEM), secondary ion mass spectrometry (SIMS), and mass accretion determined by quartz crystal microbalance (QCM). The discussion is biased toward those methods that apply optical thin film analytical techniques to spacecraft optical contamination problems. Examples are cited from both ground based and in-orbit experiments.

Heaney, James B.

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations i The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzyinference identification can be used to reflect changes in simulator fidelity for the task examined.

Zeyada, Y.

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations. The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy-inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzy-inference identification can be used to reflect changes in simulator fidelity for the task examined.

Zeyada, Y.

Analytical and experimental study of flow phenomena in noncavitating rocket pump inducers

The flow processes in rocket pump inducers are summarized. The experimental investigations were carried out with air as the test medium. The major characteristics features of the rocket pump inducers are low flow coefficient (0.05 to 0.2) large stagger angle (70 deg to 85 deg) and high solidity blades of little or no camber. The investigations are concerned with the effect of viscosity not the effects of cavitation. Flow visualization, conventional and hot wire probe measurement inside and at the exit of the blade passage, were the analytical methods used. The experiment was carried out using four three and two bladed inducers with cambered blades. Both the passage and the exit flow were measured. The basic research and boundary layer investigation was carried out using a helical flat plate (of some dimensions as the inducer blades tested), and flat plate helical inducer (four bladed). Detailed mean and turbulence flow field inside the passage as well as the exit of the rotor were derived from these measurement. The boundary layer, endwall, and other passage data reveal extremely complex nature of the flow, with major effects of viscosity present across the entire passage. Several analyses were carried out to predict the flow field in inducers. These included an approximate analysis, the shear pumping analysis, and a numerical solution of exact viscous equations with approximate modeling for the viscous terms.

Lakshminarayana, B.

Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and address challenges of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used in the Global Natural Products Social Molecular Networking platform, are a prominent strategy for exploring and visualizing molecular relationships and improving annotation. MNs are mathematical graphs showing the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated with a single molecular identity. Here, this paper introduces “molecular hypernetworks” (MHNs) as more complex MN models able to natively represent multiway relationships among observations. Compared to MNs, MHNs can more parsimoniously represent the inherent complexity present among groups of observations, initially supporting improved exploratory data analysis and visualization. MHNs also promise to increase confidence in annotation propagation, for both human and analytical processing. We first illustrate MHNs with simple examples, and build them from liquid chromatography- and ion mobility spectrometry-separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.

Leveraging AI and Spatial Data to Unlock Pipeline Integrity Insights: NETL’s Advanced Infrastructure Integrity Model (AIIM)

Maintaining the integrity of natural gas infrastructure plays a critical role in ensuring energy security. Robust, data-driven foundational AI models for pipeline integrity can help address risk management and mitigation issues. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. The AIIM dashboard was released in 2022 and utilizes multi-ML models for ensemble-type insights. It was expanded to include analytics on reported incidents. It was developed as an ESRI Dashboard to support data visualization & interrogation and contains pipeline data and model results.

Advanced Infrastructure Integrity Model (AIIM)

Characterization and measurement of polymer wear

Analytical tools which characterize the polymer wear process are discussed. The devices discussed include: visual observation of polymer wear with SEM, the quantification with surface profilometry and ellipsometry, to study the chemistry with AES, XPS and SIMS, to establish interfacial polymer orientation and accordingly bonding with QUARTIR, polymer state with Raman spectroscopy and stresses that develop in polymer films using a X-ray double crystal camera technique.

Buckley, D. H.

Characterization and measurement of polymer wear

Analytical tools which characterize the polymer wear process are discussed. The devices discussed include: visual observation of polymer wear with SEM, the quantification with surface profilometry and ellipsometry, to study the chemistry with AES, XPS and SIMS, to establish interfacial polymer orientation and accordingly bonding with QUARTIR, polymer state with Raman spectroscopy and stresses that develop in polymer films using a X-ray double crystal camera technique.

Buckley, D. H.

A Solution in Search of Problems

Ferrofluids offered vast-problem solving potential. Under license for the NASA technology, Dr. Ronald Moskowitz and Dr. Ronald Rosensweig formed Ferrofluids Corporation. First problem they found a solution for was related to the manufacture of semiconductor "chips" for use in electronic systems. They developed a magnetic seal composed of ferrofluid and a magnetic circuit. Magnetic field confines the ferrofluid in the regions between the stationary elements and the rotary shaft of the seal. Result is a series of liquid barriers that totally bar passage of contaminants. Seal is virtually wear-proof and has a lifetime measured in billions of shaft revolutions. It has reduced maintenance, minimizes "downtime" of production equipment, and reduces the cost of expensive materials that had previously been lost through seal failures. Products based on ferrofluid are exclusion seals for computer disc drives and inertia dampers for stepper motors. Uses are performance-improving, failure-reducing coolants for hi-fi loudspeakers. Other applications include analytical instrumentation, medical equipment, industrial processes, silicon crystal growing furnaces, plasma processes, fusion research, visual displays, and automated machine tools.

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