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At least 91 records · Page 5

ICI optical data storage tape: An archival mass storage media

At the 1991 Conference on Mass Storage Systems and Technologies, ICI Imagedata presented a paper which introduced ICI Optical Data Storage Tape. This paper placed specific emphasis on the media characteristics and initial data was presented which illustrated the archival stability of the media. More exhaustive analysis that was carried out on the chemical stability of the media is covered. Equally important, it also addresses archive management issues associated with, for example, the benefits of reduced rewind requirements to accommodate tape relaxation effects that result from careful tribology control in ICI Optical Tape media. ICI Optical Tape media was designed to meet the most demanding requirements of archival mass storage. It is envisaged that the volumetric data capacity, long term stability and low maintenance characteristics demonstrated will have major benefits in increasing reliability and reducing the costs associated with archival storage of large data volumes.

Ruddick, Andrew J.↗

MeV ion-beam analysis of optical data storage films

Our objectives are threefold: (1) to accurately characterize optical data storage films by MeV ion-beam analysis (IBA) for ODSC collaborators; (2) to develop new and/or improved analysis techniques; and (3) to expand the capabilities of the IBA facility itself. Using H-1(+), He-4(+), and N-15(++) ion beams in the 1.5 MeV to 10 MeV energy range from a 5.5 MV Van de Graaff accelerator, film thickness (in atoms/sq cm), stoichiometry, impurity concentration profiles, and crystalline structure were determined by Rutherford backscattering (RBS), high-energy backscattering, channeling, nuclear reaction analysis (NRA) and proton induced X-ray emission (PIXE). Most of these techniques are discussed in detail in the ODSC Annual Report (February 17, 1987), p. 74. The PIXE technique is briefly discussed in the ODSC Annual Report (March 15, 1991), p. 23.

Leavitt, J. A.↗

Electrical Energy Storage Data Submission Guidelines, Version 2

Energy storage technologies are positioned to play a substantial role in power delivery systems. They have the potential to serve as an effective new resource to maintain reliability and allow for increased penetration of renewable energy. However, because of their relative infancy, there is a lack of knowledge about how these resources truly operate over time. A data analysis can help ascertain the operational and performance characteristics of these emerging technologies. Rigorous testing and a data analysis are important for all stakeholders to ensure a safe, reliable system that performs predictably on a macro level. Standardizing testing and analysis approaches to verify the performance of energy storage devices, equipment, and systems when integrating them into the grid will improve the understanding and benefit of energy storage over time from technical and economic vantage points. Demonstrating the life-cycle value and capabilities of energy storage systems begins with the data that the provider supplies for the analysis. After a review of energy storage data received from several providers, some of these data have clearly shown to be inconsistent and incomplete, raising the question of their efficacy for a robust analysis. This report reviews and proposes general guidelines, such as sampling rates and data points, that providers must supply for a robust data analysis to take place. Consistent guidelines are the basis of a proper protocol and ensuing standards to (1) reduce the time that it takes for data to reach those who are providing the analysis; (2) allow them to better understand the energy storage installations; and (3) enable them to provide a high-quality analysis of the installations. The report is intended to serve as a starting point for what data points should be provided when monitoring. Readers are encouraged to use the guidance in the report to develop specifications for new systems, as well as enhance current efforts to ensure optimal storage performance. As battery technologies continue to advance and the industry expands, the report will be updated to remain current.

25 ENERGY STORAGE↗

Data Storage and Visualization Solutions for Real Time Simulations and Experiments

There are multiple challenges in performing real time simulations and real time experiments. Data storage and visualization are challenges that could be solved easily and when solved provide rich and valuable insights into the experiments. In this presentation, we will talk about the National Renewable Energy Laboratory solutions to tackle these issues while running real time experiments and simulations. The NREL team has made these open-source for the community to utilize with real time simulations and experiments.

data storage↗

Trap‐Engineering the Persistent Luminescence of Ca 3 Ga 4 O 9 :Tb 3+ via Al 3+ Substitution for Optical Data Storage

Abstract Optically stimulated luminescence (OSL) materials hold great potential for optical data storage (ODS) and anticounterfeiting applications. Nevertheless, the scarcity of suitable luminescent materials with deep‐level traps remains a significant obstacle. Herein, a host substation strategy have been employed to tune the persistent luminescence (PersL) and OSL properties of Ca 3 Ga 4 O 9 :Tb 3+ by Al 3+ substitution through trap engineering and demonstrated their potential. Specifically, the photoluminescence of the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ of Tb 3+ is first investigated due to its different occupancies of Ca 2+ . The influence of host substitution on the crystal structure, trap depth, trap density, PersL, and OSL properties have further investigated. A series of strong PersL and OSL peaks from the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ with bluish‐green emissions have been observed. The Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ have shown controllable photon release upon thermal and optical stimuli, enhancing their performance for ODS. Thermally stimulated luminescence suggests that vacancy and defect concentrations inside the Ca 3‐x% (Ga 1‐y% Al y% ) 4 O 9 :x%Tb 3+ can be manipulated by Tb 3+ doping and Al 3+ substitution, which ultimately leads to the formation of deep traps and a broad distribution of traps with increased deep trap concentration. The work demonstrates that trap engineering through Al 3 ⁺ substitution is an effective method for tuning PersL and OSL properties of Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ for ODS.

Abeywickrama, Thulitha M. [Department of Chemistry↗

Offshore Geologic Carbon Storage Data Collection and Data Gaps Analysis

This is a TRS documenting the Offshore Geologic Carbon Storage Data Collection. It describes the Data Collection web application and its creation as well as an accompanying Data Gaps Assessment. We present an interactive data collection and data gaps analysis to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS in the United States. This data collection and data gaps analysis 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.

58 GEOSCIENCES↗

Energy Storage Data Submission Guidelines

In order to consider and understand emerging energy storage technologies, data analysis can be executed to ascertain proper operation and performance. The technical benefits of rigorous testing and data analysis are important for the customer, the planner, developer, and system operator: the end-user has a safe, reliable system that performs predictably on a macro level. The test-and-analyze approach to verifying performance of energy storage devices, equipment, and systems integration into the grid improves the understanding of the value of energy storage over time from the economic vantage point. Demonstrating the lifecycle value of energy storage begins with the data the provider supplies for analysis. After review of energy storage data received from several providers, it has become clear that some ESS data is inconsistent and incomplete - thus leading to a question of the inefficacy of the data when it comes time to analyze it. This paper will review and propose general guidelines such as sampling rates and data points that providers must supply in order for robust data analysis to take place. Consistent guidelines are the basis of the proper protocol to (a) reduce time it takes data to reach those who are providing analyses; (b) allow them to better understand the energy storage installations; and (c) provide high quality analysis of the installation. This paper intends to serve as a starting point for what data points should be provided when monitoring. As battery technologies continue to advance and the industry expands, this paper will be updated to remain current.

25 ENERGY STORAGE↗

Mariner 9 data storage subsystem flight performance summary

The performance is summarized of the Mariner 9 Data Storage Subsystem (DSS) throughout the primary and extended missions. Information presented is limited to reporting of anomalies which occurred during the playback sequences. Tables and figures describe the anomalies (dropouts, missing and added bits, in the imaging data) as a function of time (accumulated tape passes). The data results indicate that the performance of the DSS was satisfactory and within specification throughout the mission. The data presented is taken from the Spacecraft Team Incident/Surprise Anomaly Log recorded during the mission. Pertinent statistics concerning the tape transport performance are given. Also presented is a brief description of DSS operation, particularly that related to the recorded anomalies. This covers the video data encoding and how it is interpreted/decoded by ground data processing and the functional operation of the DSS in abnormal conditions such as loss of lock to the playback signal.

Thomas, N. E.↗

Systems and methods for data storage and retrieval

A method includes directing a probe beam to a target that includes an array of data portions in a data storage medium arranged so that a beam area of the probe beam extends across a plurality of adjacent data portions, the array including a data portion subset with each data portion of the subset responsive to the probe beam to produce a response illumination, receiving the response illumination at a detector, and determining data values corresponding to the plurality of adjacent data portions based on the received response illumination. Apparatus and systems are also disclosed.

Gotthold, David W.↗

Systems and methods for data storage and retrieval

A method includes directing a probe beam to a target that includes an array of data portions in a data storage medium arranged so that a beam area of the probe beam extends across a plurality of adjacent data portions, the array including a data portion subset with each data portion of the subset responsive to the probe beam to produce a response illumination, receiving the response illumination at a detector, and determining data values corresponding to the plurality of adjacent data portions based on the received response illumination. Apparatus and systems are also disclosed.

97 MATHEMATICS AND COMPUTING↗

Differential Power Processing for Ultra-Efficient Data Storage

Here this paper presents the hardware, software, and power codesign of an ultra-efficient data storage server with differential power processing (DPP). DPP can reduce the power conversion stress, improve the efficiency, and enhance the functionality of modular power electronics systems. The power inputs of a large number of hard disk drives (HDDs) were connected in series and supported by a multiport ac-coupled differential power processing (MAC-DPP) converter through a multiwinding transformer. Methods for controlling the multi-input multi-output power flow in the multiwinding transformer while avoiding core saturation were investigated. A ten-port MAC-DPP prototype with 700-W/in 3 power density was built to support a 450-W HDD storage system with ten series-stacked voltage domains. The prototype was tested on a 50-HDD server testbench, and the overall system loss is below 1 W (99.77% system efficiency). The server was able to maintain high-speed reading and writing operation of all 50 HDDs against the worst hot-swapping scenarios. A variety of hardware/software configurations and many cloud storage techniques were tested on the fully functioning server. Experimental results show that the energy efficiency of large-scale information systems (CPU/GPU clusters, memory banks, HDD arrays, etc.) can be greatly improved by software, hardware, and power codesign.

42 ENGINEERING↗

Comparative I/O workload characterization of two leadership class storage clusters. In: PDSW '15 Proceedings of the 10th Parallel Data Storage Workshop

The Oak Ridge Leadership Computing Facility (OLCF) is a leader in large-scale parallel file system development, design, deployment and continuous operation. For the last decade, the OLCF has designed and deployed two large center-wide parallel file systems. The first instantiation, Spider 1, served the Jaguar supercomputer and its predecessor, Spider 2, now serves the Titan supercomputer, among many other OLCF computational resources. The OLCF has been rigorously collecting file and storage system statistics from these Spider systems since their transition to production state. In this paper we present the collected I/O workload statistics from the Spider 2 system and compare it to the Spider 1 data. Our analysis show that the Spider 2 workload is more more write-heavy I/O compared to Spider 1 (75% vs. 60%, respectively). The data also show the OLCF storage policies such as periodic purges are effectively managing the capacity resource of Spider 2. Furthermore, due to improvements in tdm_multipath and ib_srp software, we are utilizing the Spider 2 system bandwidth and latency resources more effectively. The Spider 2 bandwidth usage statistics shows that our system is working within the design specifications. However, it is also evident that our scientific applications can be more effectively served by a burst buffer storage layer. All the data has been collected by monitoring tools developed for the Spider ecosystem. We believe the observed data set and insights will help us better design the next-generation Spider file and storage system. It will also be helpful to the larger community for building more effective large-scale file and storage systems.

Gunasekaran, Raghul↗

Alabama Carbon Storage: Data Sharing and Engagement (Final Report)

This report is the final technical report on Alabama Carbon Storage: Data Sharing Engagement (ACS:DSE) project activities. The goals of the ACS:DSE project are to compile geologic, geophysical, infrastructure, and other relevant CCUS datasets for the study area and develop a geologic model of the study area; develop an online platform to serve data to stakeholders; engage with the public, students, and industry to educate them about CCUS and the data platform; and ensure energy and environmental justice is central to all aspects of the project. Datasets compiled and expanded include formation depths and elevations, digital geophysical well logs, reservoir properties, geologic structures, and geologic models. The geologic data were used to create a three-dimensional geologic model, structure grids, structure contour maps, and fault trace maps. In addition to downloadable datasets, links to CCUS relevant regulatory agencies (e.g., OGB, U.S. Environmental Protection Agency) and sources for infrastructure and educational information were included on the website Educational materials on CCUS for use by K-12 teachers were produced as part of the ACS:DSE project.

01 COAL, LIGNITE, AND PEAT↗

Telemetry data storage systems technology for the Space Station Freedom era

This paper examines the requirements and functions of the telemetry-data recording and storage systems, and the data-storage-system technology projected for the Space Station, with particular attention given to the Space Optical Disk Recorder, an on-board storage subsystem based on 160 gigabit erasable optical disk units each capable of operating at 300 M bits per second. Consideration is also given to storage systems for ground transport recording, which include systems for data capture, buffering, processing, and delivery on the ground. These can be categorized as the first in-first out storage, the fast random-access storage, and the slow access with staging. Based on projected mission manifests and data rates, the worst case requirements were developed for these three storage architecture functions. The results of the analysis are presented.

Dalton, John T.↗

Data storage technology: Hardware and software, Appendix B

This project involves the development of more economical ways of integrating and interfacing new storage devices and data processing programs into a computer system. It involves developing interface standards and a software/hardware architecture which will make it possible to develop machine independent devices and programs. These will interface with the machine dependent operating systems of particular computers. The development project will not be to develop the software which would ordinarily be the responsibility of the manufacturer to supply, but to develop the standards with which that software is expected to confirm in providing an interface with the user or storage system.

Sable, J. D.↗

Trade-off study of data storage technologies

The need to store and retrieve large quantities of data at modest cost has generated the need for an economical, compact, archival mass storage system. Very significant improvements in the state-of-the-art of mass storage systems have been accomplished through the development of a number of magnetic, electro-optical, and other related devices. This study was conducted in order to do a trade-off between these data storage devices and the related technologies in order to determine an optimum approach for an archival mass data storage system based upon a comparison of the projected capabilities and characteristics of these devices to yield operational systems in the early 1980's.

Kadyszewski, R. V.↗