Results for “Visualization & Storage” — Page 8

DOE OSTI2023

ER4047 Filler Wire Development - Initial Studies

This report describes the results of bead on pipe welding trials for the purpose of evaluating commercial off the shelf (COTS) 0.047” ER4047 filler material vendors for down selection of the of best candidate filler material for future Gas-metal Arc Welding (GMAW) development efforts. Four candidate COTS ER4047 filler wires were evaluated during this work - Astrolite, Alcotec, Hobart, and Lincoln. The storage condition of each of these filler wires was documented and visual inspection was performed.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Automated Selection Of Pictures In Sequences

Method of automated selection of film or video motion-picture frames for storage or examination developed. Beneficial in situations in which quantity of visual information available exceeds amount stored or examined by humans in reasonable amount of time, and/or necessary to reduce large number of motion-picture frames to few conveying significantly different information in manner intermediate between movie and comic book or storyboard. For example, computerized vision system monitoring industrial process programmed to sound alarm when changes in scene exceed normal limits.

Rorvig, Mark E.↗

DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗

DOE OSTI2018

Optimizing Scientist Time through In Situ Visualization and Analysis

In situ processing produces reduced size persistent representations of a simulations state while the simulation is running. The need for in situ visualization and data analysis is often described in terms of supercomputer size and performance in relation to available storage size.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Offshore Geologic Carbon Storage Data Collection and International Project Inventory

We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.

Mulhern, Julia↗

DOE OSTI2024

International Offshore Geologic Carbon Storage Project Inventory and Data Collection

We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.

Mulhern, Julia↗

DOE OSTI2024

International Offshore Geologic Carbon Storage Inventory and Data Collection

We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.

Mulhern, Julia↗

NASA NTRS1976

Effects of nuclear radiation and elevated temperature storage on electroexplosive devices

Aerospace type electroexplosive devices (EEDs) were subjected to nuclear radiation. Components and chemicals used in the EEDs were also included. The kind of radiation and total dosage administered were those which may be experienced in a space flight of 10 years duration, based on information available at this time. After irradiation, the items were stored in elevated constant-temperature ovens to accelerate early effects of the exposure to radiation. Periodically, samples were withdrawn for visual observation and testing. Significant changes occurred which were attributed to elevated-temperature storage and not radiation.

Menichelli, V. J.↗

DOE OSTI2020

Using Machine Learning to Identify Optimum Prospects for Offshore Geologic CO 2 Storage and Enhanced Oil Recovery in the Gulf of Mexico

The SECARB Offshore Partnership is a government-industry partnership focused on assembling the knowledge base required for secure, long-term, large-scale CO 2 subsea storage in saline formations and mature oil reservoirs. The SECARB Offshore Partnership is evaluating potential storage opportunities in the Central and Eastern planning areas of the outer continental shelf (OCS) of the Gulf of Mexico. The evaluation focuses on active and depleted oil and gas fields and potentially associated CO 2 -enhanced oil recovery (CO 2 -EOR), as well as, deep saline storage resources. As part of Subtask 3.0 (Offshore Storage Resources Characterization) and Subtask 4.0 (Risk Assessment, Simulation, and Modeling), Oklahoma State University (OSU) is developing a machine learning system that employs the SAS Institute’s Viya platform with visual data mining and machine learning to identify and characterize optimum prospects for enhanced oil recovery and stacked storage in saline reservoirs. This report summarizes this effort to date and discusses the many variables that can be used to characterize these storage objectives, as well as, the design vision of the Viya machine learning system.

02 PETROLEUM↗

DOE OSTI2017

Advanced Characterization of Unconventional Oil and Gas Reservoirs to Enhance CO 2 Storage Resource Estimates – Organic Structure and Porosity of Organic Rich Shales

Poster presented at Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, Pennsylvania, August 1–3, 2017. Advanced analytical and image analysis techniques have been employed to examine the detailed structure of organic matter (OM) in the shales of the Bakken Formation. Samples from three different locations in the Bakken Formation with varying levels of thermal maturity (immature, marginally mature, and mature) were selected for analysis. The goal of this project is to use an advanced field emission scanning electron microscope (FESEM), image analysis, and computed tomography (CT) visualization techniques to identify and quantify key features that could affect CO 2 storage in unconventional formations.

02 PETROLEUM↗

DOE OSTI2020

Large Plate Experiment of Chloride-induced Stress Corrosion Cracking in Spent Nuclear Fuel Storage Canisters

This report provides a description of the testing (in progress at the Savannah River National Laboratory) to evaluate the corrosion behavior of a large section of welded plate material harvested from the Sandia National Laboratories’ full-size mockup of a spent nuclear fuel (SNF) dry storage canister. The details of the establishment of this plate test, the interim corrosion results (from visual examination), and the general plan for examination of the plate in CY21 to evaluate crack growth behavior (if any) are provided. This work is intended to inform aging management programs for SNF canisters under conditions of extended dry storage. A “large plate” (approximately 51 x 46 cm with thickness 16 mm and weight about 30 kg) and containing a circumferential weldment from the mockup is the test specimen. The knowledge of the salt, temperature, humidity conditions for chloride-induced stress corrosion cracking (CISCC) including the threshold stress intensity factor, K iscc , were used to setup the large plate test in which a set of part-through-wall and through-wall electrical discharge machined (EDM) defects were positioned in the weld residual stress field of the welded plate material from the mockup canister. A marine salt solution was applied to this plate specimen with an air-brush spray, then dried, and then exposed to a sustained 71-73% RH condition at an ambient room temperature of 22 °C. The salt loading and environmental condition is expected to be aggressive to cause CISCC

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1990

The role of data management in discipline-independent data visualization

The common data format (CDF) is described in terms of its support applications for the database management of visualization systems. The CDF is a self-describing data abstraction technique for the storage and manipulation of multidimensional data that are based on block structures. The discipline-independent approach is designed to manage, manipulate, archive, display, and analyze data, and can be applied to heterogeneous equipment communicating different data structures over networks. An improved CDF version incorporates a hyperplane access allowing random aggregate access to subdimensional blocks within a multidimensional variable. The visualization pipeline is also discussed, which controls the flow of data and permits the visualization of different classes of data representation techniques. The system is found to accommodate a large variety of scientific data structures and large disk-based data sets.

Treinish, Lloyd A.↗

DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗

DOE OSTI2017

SNF Data Visualization on the Centralized Used Fuel Resource for Information Exchange (CURIE) Website

To better inform stakeholders regarding the nature of spent nuclear fuel (SNF) at utility sites, an online data visualization system has been created for the U.S. Department of Energy's Office of Nuclear Energy (DOENE). The data visualization system is part of the Centralized Used Fuel Resource for Information Exchange (CURIE) website, hosted by the Oak Ridge National Laboratory (ORNL) for DOE-NE. The visualization employs a database that is part of an analysis tool known as the Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST[and]DARDS). Because many of the previous document management and sharing tools related to SNF have been terminated (or are inaccessible), a new tool, the CURIE, was developed for DOE-NE and launched on March 1, 2013 at http://curie.ornl.gov. In addition to supporting DOE SNF programs, CURIE is a national resource that is accessible to industry, vendor, federal, and laboratory partners, as well as other stakeholders. CURIE's architecture was initially based on previous work that supported DOE's Bioenergy Technologies Office on the Bioenergy Knowledge Discovery Framework (KDF). The site uses an open-source search engine, Apache Solr, which provides intuitive search results based on a faceted search method similar to that used by Amazon.com{sup R}. This algorithm helps to ensure that finding documents and data is straightforward. SNF data visualization capability was added to the CURIE website which provides a capability to post and access documents and data related to the management of SNF. CURIE currently maintains over 4,100 documents and the Siting Experience Database (SED), which was developed in response to a near-term recommendation by the Blue Ribbon Commission on America's Nuclear Future (BRC). The SED is a database of the experience that has been gained and relevant documentation that has been produced in efforts to site nuclear waste facilities, both in the US and abroad. Most of these documents are publicly accessible. In addition, CURIE maintains a current calendar of related events, an SNF image gallery, featured documents, and external links to related databases and websites. CURIE also maintains private groups (or communities) to facilitate collaborative development through sharing and editing documents that are not publicly available. There are more than 250 registered users in 23 different communities within CURIE.ORNL has also been developing UNF-ST[and]DARDS to provide a controlled source of technical data for various waste management system analysis/evaluation tools, access to key technical data, and analysis capabilities for characterizing the SNF inventory. UNF-ST[and]DARDS also provides enhanced capabilities to assess safety, risk, and uncertainty throughout the integrated waste management system. This paper describes the UNF-ST[and]DARDS data available for visualization and the associated visualization techniques used by CURIE to display this data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

In Situ Visualization and Production of Extract Databases

Simulations running at high concurrency on HPC systems generate large volumes of data that are impractical to write to disk due to time and storage constraints. Applications often adapt by saving data infrequently, resulting in datasets with poor temporal resolution. This can make datasets difficult to interpret during post hoc visualization and analysis, or worse, it can lead to lost science. In Situ visualization and analysis can enable efficient production of small data products such as rendered images or surface extracts that consist of polygonal geometry plus fields. These data products are far smaller than their source data and can be processed much more economically in a traditional post hoc workflow using far fewer computational resources. We used the SENSEI and Libsim in situ infrastructures to implement rendering workflow and surface data extraction workflows in the AVF-LESLIE combustion code. Finally, these workflows were then demonstrated at high levels of concurrency and showed significant data reductions and limited impact on the simulation runtime.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Multidimensional visualization of the dynamic evolution of Li metal via in situ/operando methods

The growing demands for high-energy density electrical energy storage devices stimulate the coupling of conversion-type cathodes and lithium (Li) metal anodes. While promising, the use of these “Li-free” cathodes brings new challenges to the Li anode interface, as Li needs to be dissolved first during cell operation. In this study, we have achieved a direct visualization and comprehensive analysis of the dynamic evolution of the Li interface. The critical metrics of the interfacial resistance, Li growth, and solid electrolyte interface (SEI) distribution during the initial dissolution/deposition processes were systematically investigated by employing multidimensional analysis methods. They include three-electrode impedance tests, in situ atomic force microscopy, scanning electrochemical microscopy, and cryogenic scanning transmission electron microscopy. The high-resolution imaging and real-time observations show that a loose, diffuse, and unevenly distributed SEI is formed during the initial dissolution process. This leads to the dramatically fast growth of Li during the subsequent deposition, deviating from Fick’s law, which exacerbates the interfacial impedance. The compactness of the interfacial structure and enrichment of electrolyte species at the surface during the initial deposition play critical roles in the long-term stability of Li anodes, as revealed by operando confocal Raman spectroscopic mapping. In conclusion, our observations relate to ion transfer, morphological and structural evolution, and Li (de)solvation at Li interfaces, revealing the underlying pathways influenced by the initial dissolution process, which promotes a reconsideration of anode investigations and effective protection strategies.

25 ENERGY STORAGE↗

DOE OSTI2022

In situ visualization of multicomponents coevolution in a battery pouch cell

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

25 ENERGY STORAGE↗

DOE OSTI2018

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregate $\mathcal{O}$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗