Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data storage”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Using Dashboards to Improve Energy and Comfort in Federal Buildings

Federal agencies are taking many steps to improve the sustainability of their operations, including improving the energy efficiency of their buildings, promoting recycling and reuse of materials, encouraging carpooling and alternative transit schemes, and installing low flow water fixture units are just a few of the common examples. However, an often overlooked means of energy savings is to provide feedback to building users about their energy use through information dashboards connected to a building?s energy information system. An Energy Information System (EIS), broadly defined, is a package of performance monitoring software, data acquisition hardware, and communication systems that is used to collect, store, analyze, and display energy information. At a minimum, the EIS provides the whole-building energy-use information (Granderson 2009a). We define a ?dashboard? as a display and visualization tool that utilizes the EIS data and technology to provide critical information to users. This information can lead to actions resulting in energy savings, comfort improvements, efficient operations, and more. The tools to report analyzed information have existed in the information technology as business intelligence (Few 2006). The dashboard is distinguished from the EIS as a whole, which includes additional hardware and software components to collect and storage data, and analysis for resources and energy management (Granderson 2009b). EIS can be used for a variety of uses, including benchmarking, base-lining, anomaly detection, off-hours energy use evaluation, load shape optimization, energy rate analysis, retrofit and retro-commissioning savings (Granderson 2009a). The use of these EIS features depends on the specific users. For example, federal and other building managers may use anomaly detection to identify energy waste in a specific building, or to benchmark energy use in similar buildings to identify energy saving potential and reduce operational cost. There are several vendors of EIS technology that provide information on energy and other environmental variables in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Zero-Power Analog Optical Processing

The motivation behind this research is the growing challenge of handling the massive amounts of data generated by modern imaging systems. Conventional digital image processing techniques are struggling to keep pace with the demands of high-resolution and high-speed imaging systems for remote sensing due to their high-power consumption and data storage requirements. We present a novel approach based on analog photonics to address this challenge. The proposed system utilizes a silicon-photonics-based image encoder positioned after image formation and initial optical-to-electrical conversion. The photonic encoder compresses image data using a passive disordered photonic structure to perform kernel-type random projections of the raw data. The compressed data is then processed by a back-end neural network, which reconstructs the original image with high fidelity (structural similarity exceeding 90%). Our proposed approach has the potential to compress images with ~ 1000X lower power consumption compared to digital approaches with data rates exceeding 1 terapixel/second.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Lessons learned supporting onboard solid-state recorders

With the advance of semiconductor technology, Solid-State Recorders (SSR) have matured and been accepted as primary onboard data storage devices. Their high reliability, simpler interface and control, and high flexibility have made the SSR's a superb choice in today's spacecraft design. While there are many benefits, the use of SSR's may also add significant complexity to ground data systems. For instance, real-time and playback data may be interleaved into the same data stream, making data sequencing and time ordering difficult. Stored data may be played back out of time order, increasing processing load significantly. Data may also be played back after being sorted by Virtual Channels in the SSR, potentially creating bursts in packet rates that exceed the real-time processing capabilities of the ground systems. This paper presents a summary of lessons learned through the efforts in supporting a number of NASA's missions that employ SSR's. It describes various problems encountered through the design process, and their potential impact on ground system performance, resources, and cost. Recommended approaches to minimizing the impact are demonstrated by examples. The discussion leads to the conclusion that the use of SSR's demands an even higher level of cooperation between spacecraft and ground system designers in order to build the most cost effective end-to-end system.

Shi, Jeff↗
NASA NTRS2021

The Analysis of Using Satellite Soil Moisture Observations for Flood Detection, Evaluating Over the Thailand’s Great Flood of 2011

A flood monitoring and warning system provides critical information that can protect property and save lives. A basin-scale flood monitoring system requires an effective observation platform that offers extensive ground coverage of flood conditions, low latency, and high spatiotemporal resolution. While satellite imagery offers substantial spatial flood extent in detail due to its high spatial resolution, the coarse temporal resolution and cloud obstruction limit its near real-time application. Daily soil moisture data derived from satellite sensors at a scale of a few km can be used to monitor extreme wet surface conditions arising in flood occurrences. This study analyses the flood detection capabilities of several sources of soil moisture information, including the Soil Moisture and Ocean Salinity mission (SMOS), the Advanced Microwave Scanning Radiometer on EOS (AMSR-E), the Advanced SCATterometer (ASCAT) on MetOp, the Global Land Data Assimilation System (GLDAS), and the WaterGAP Global Hydrology Model (WGHM). In addition to soil moisture, the analysis includes measurements of surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS), precipitation measurements from the Tropical Rainfall Measuring Mission (TRMM), and terrestrial water storage estimates from the Gravity Recovery And Climate Experiment (GRACE) as proxies for flood inundations. The analysis was conducted over the Chao Phraya River Basin (CPB) in Thailand, where the Great Flood of 2011 led to one of the most significant economic losses in the country's history. Satellite-derived soil moisture exhibits a stronger correlation with the flood inundations than the precipitation, model-derived soil moisture, and terrestrial water storage data. SMOS soil moisture observation agrees best with the MODIS-derived flood extent/occurrence, both in terms of spatial distribution and timing, and providing approximated flood lead-time of one week or longer. A neural network constructed from SMOS and MODIS data is used to predict flood intensity/occurrence (given soil moisture input) with a predicted time window from eight days to thirty-two days. The short-term prediction (e.g., eight days) achieves the highest accuracy with an averaged recovery rate of approximately 60% (correlation coefficient). This study's results suggest a potential application of satellite soil moisture data in assisting flood monitoring and warning systems.

Satellite soil moisture↗
NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗
DOE OSTI2015

Atomic memory access hardware implementations

Atomic memory access requests are handled using a variety of systems and methods. According to one example method, a data-processing circuit having an address-request generator that issues requests to a common memory implements a method of processing the requests using a memory-access intervention circuit coupled between the generator and the common memory. The method identifies a current atomic-memory access request from a plurality of memory access requests. A data set is stored that corresponds to the current atomic-memory access request in a data storage circuit within the intervention circuit. It is determined whether the current atomic-memory access request corresponds to at least one previously-stored atomic-memory access request. In response to determining correspondence, the current request is implemented by retrieving data from the common memory. The data is modified in response to the current request and at least one other access request in the memory-access intervention circuit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possible design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

From Data to Models and Analytics: An Integrated Scientific Computing Platform to Accelerate Environmental Research SBIR Phase I (Final Technical Report)

Phase I research was conducted to investigate the technical feasibility of an integrated open source platform GeoLib to provide turnkey solutions for model-data integration for environmental systems science (ESS), using modern web technologies, advances in HPC and cloud computing and high-performance visualization. A key feature of our platform is that it minimizes and automates data movement between data storage and computing systems. Another critical feature of the design is that it enables users to perform high-fidelity post-processing by performing high-performance visualization server-side and in-situ on the compute cluster close to the data. The investigation, which was performed over a 12-month period ending April 2019, centered on developing prototype software to demonstrate the key enabling technologies required for this system. This included: (i) rapid access to data from multiple remote sources, via a unified data interface; (ii) software for scalable geospatial visualization of raster, vector, and point cloud data on the web; (iii) development of an easy-to-use API for creating simulation and modeling workflows; (iv) remote data visualization and processing on middle-tier servers; and (v) remote data processing on high-performance computing systems. A critical part of this work is that all of these capabilities be accessible to end users through standard desktop tools such as Project Jupyter, which is widely adopted for ESS simulation and modeling.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Analysis of Moessbauer Data from Mars: A Database and Artificial Neural Network for Identification of Iron-bearing Phases

The exploration of the planet Mars is one of the major goals within the Solar system exploration programs of the US-American space agency NASA and the European Space Agency ESA. In particular the search for water and life and understanding of the history of the surface and atmosphere will be the major tasks of the upcoming space missions to Mars. The miniaturized Moessbauer spectrometer MIMOS II has been selected for the NASA Mars-Exploration-Rover twin-mission to Mars in 2003 and the ESA 2003 Mars-Express Beagle 2 mission. Reduced in size and weight, in comparison to ordinary laboratory setup, the sensor head just weights approximately 400 g, with a volume of (50x50x90) cu mm, and holds two gamma-ray sources: the stronger for experiments and the weaker for calibrations. The collimator (in sample direction) also shields the primary radiation off the detectors. Around the drive four detectors are mounted. The detectors are made of Si-PIN-photodiodes in chip form (100 sq mm, thickness of 0.5 mm). The control unit is located in a separate electronics board. This board is responsible for the power supply, generation of the drive's velocity reference signal, read of the detector pulses to record the spectrum, data storage and communication with the host computer. After more than four decades from the discovery of the Moessbauer effect, more than 400 minerals were studied at different temperatures. Their Moessbauer parameters were reported in the literature, and have been recently collected in a data bank. Previous Mars-missions, namely Viking and Mars Pathfinder, revealed Si, Al, Fe, Mg, Ca, K, Ti, S and Cl to be the major constituents in soil and rock elemental composition of the red planet. More than 200 minerals already studied by Moessbauer spectroscopy contain significant amounts of these elements. A considerable number of Moessbauer studies were also carried out on meteorites and on Moon samples. Looking backward in the studies of the whole Moessbauer community, we have built a specific library containing Moessbauer parameters of those possible Mars minerals. The selected minerals, their Moessbauer parameter values (min. max. s.d and number of available data), main site substitution, behavior as a function of temperature and a ranking as expected to be found on Mars were organized. Mars-analogue Fe-bearing minerals not studied by Moessbauer spectroscopy are being collected and investigated. In addition, it an identification system based on Artificial Neural Networks (ANN) was implemented which enables fast and precise mineral identification from the experimental Moessbauer parameters at a given temperature.

P A de Souza Jr.↗
NASA NTRS1977

The Viking seismometer

The Viking seismometer, operating on the Martian surface in the region of Utopia Planitia, includes three inertial velocity transducers, amplifiers, filters, automatic event detectors, data compactors, and temporary data storage capability within a unit weighing 2.2 kg. The seismometer functions at a peak magnification of 218,000 with a ground resolution of 2 nanosec and 3 Hz. Since the telemetry capacities associated with the system are limited, the seismometer instrument package employs three data processing modes: a high sampling rate mode; a heavily filtered background monitoring mode; and a frequently-used data compacting mode.

Miller, W. F.↗
NASA NTRS1992

Autonomous support for microorganism research in space

A preliminary design for performing on orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the Commercial Experiment Transporter (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with in-flight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibrations, and radiation are provided for environmental regulation and experimental data collection. Additional experimental data acquisition includes optical density measurement, microscopy, video, and film photography. On-board full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.

Fleet, Mary L.↗
NASA NTRS1992

Autonomous support for microorganism research in space

A preliminary design for performing on-orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the COMmercial Experiment Transported (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with inflight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibration, and radiation are provided for environmental regulation and experimental data collection. Additional experiment data acquisition includes optical density measurement, microscopy, video, and file photography. Onboard full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.

Luttges, M. W.↗
DOE OSTI2025

Geospatial Data Workflow Orchestration and Architecture

In an era characterized by explosive growth in geospatial data, the selection of appropriate technologies for data storage, processing, and orchestration is critical for organizations aiming to maintain competitive advantages. This white paper provides a comprehensive analysis of how Oak Ridge National Laboratory (ORNL) has effectively employed various cloud technologies, including containerized applications, container orchestrators, and workflow orchestrators, to develop robust geospatial data processing solutions. We explore the fundamental concepts behind these technologies and compare multiple deployment models tailored to diverse use cases. Our findings conclude that while Kubernetes has emerged as the preferred platform for truly scalable and fault-tolerant production workflows, the choice of workflow orchestration tool requires careful consideration of team needs, pipeline complexity, and deployment environments. This paper aims to serve as a strategic guide for organizations leveraging geospatial data, articulating the balance between technology choices and practical implementation to enhance workflow efficacy and scalability.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

The Mariner Venus Mercury flight data subsystem.

The flight data subsystem (FDS) discussed handles both the engineering and scientific measurements performed on the MVM'73. It formats the data into serial data streams, and sends it to the modulation/demodulation subsystem for transmission to earth or to the data storage subsystem for storage on a digital tape recorder. The FDS is controlled by serial digital words, called coded commands, received from the central computer sequencer of from the ground via the modulation/demodulation subsystem. The eight major blocks of the FDS are: power converter, timing and control, engineering data, memory, memory input/output and control, nonimaging data, imaging data, and data output. The FDS incorporates some 4000 components, weighs 17 kg, and uses 35 W of power. General data on the mission and spacecraft are given.

Whitehead, P. B.↗
DOE OSTI2025

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Real-Time Interactive 4D-STEM Phase-Contrast Imaging From Electron Event Representation Data: Less computation with the right representation

The arrival of direct electron detectors (DED) with high frame-rates in the field of scanning transmission electron microscopy has enabled many experimental techniques that require collection of a full diffraction pattern at each scan position, a field which is subsumed under the name four dimensional-scanning transmission electron microscopy (4D-STEM). DED frame rates approaching 100 kHz require data transmission rates and data storage capabilities that exceed commonly available computing infrastructure. Current commercial DEDs allow the user to make compromises in pixel bit depth, detector binning or windowing to reduce the per-frame file size and allow higher frame rates. This change in detector specifications requires decisions to be made before data acquisition that may reduce or lose information that could have been advantageous during data analysis. The 4D Camera, a DED with 87 kHz frame-rate developed at Lawrence Berkeley National Laboratory, reduces the raw data to a linear-index encoded electron event representation (EER). Here we show with experimental data from the 4D Camera that linear-index encoded EER and its direct use in 4D-STEM phase contrast imaging methods enables real-time, interactive phase-contrast from large-area 4D-STEM datasets. Furthermore, we detail the computational complexity advantages of the EER and the necessary computational steps to achieve real-time interactive ptychography and center-of-mass differential phase contrast using commonly available hardware accelerators.

4D-STEM↗
DOE OSTI2026

Data Center Market Report

The data center market is poised to explode in the coming decade due to undeniable drivers such as continued adoption of generative AI, increased data storage needs, and enterprise integration of AI in numerous industries [1] [2] [3]. Scalable power and increased computational capacity are at the forefront of considerations for hyperscalers, the major cloud service providers in this space. Lawrence Livermore National Laboratory is uniquely poised to help with informed decision making for data center market leaders during this phase of explosive expansion. National grid modeling expertise and cutting edge innovations in computer cooling systems place LLNL in an enviable position for creating economic impact in the data center industry by leveraging its expertise in these areas which can help the data center market keep up with growing demand.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Microspacecraft and Earth observation: Electrical field (ELF) measurement project

The Utah State University space system design project for 1989 to 1990 focuses on the design of a global electrical field sensing system to be deployed in a constellation of microspacecraft. The design includes the selection of the sensor and the design of the spacecraft, the sensor support subsystems, the launch vehicle interface structure, on board data storage and communications subsystems, and associated ground receiving stations. Optimization of satellite orbits and spacecraft attitude are critical to the overall mapping of the electrical field and, thus, are also included in the project. The spacecraft design incorporates a deployable sensor array (5 m booms) into a spinning oblate platform. Data is taken every 0.1 seconds by the electrical field sensors and stored on-board. An omni-directional antenna communicates with a ground station twice per day to down link the stored data. Wrap-around solar cells cover the exterior of the spacecraft to generate power. Nine Pegasus launches may be used to deploy fifty such satellites to orbits with inclinations greater than 45 deg. Piggyback deployment from other launch vehicles such as the DELTA 2 is also examined.

Olsen, Tanya↗