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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

A Web of Data Analytics Services

Cloud Computing has become the ubiquitous approach to our Big Data challenge. However, one will quickly discover that moving (a.k.a. forklifting) existing on-premise data analytics solutions to the Cloud doesn’t always translate to costing saving and performance boost. The Cloud’s elasticity, its availability, and its wide selection of computing options and selections of costing models making Cloud an attractive environment to tackle our Big Data challenge. The fact is Cloud, on its own, is not the silver bullet to our daunting challenge need for analyze and derive scientific inferences through vast collections of multi-sensor measurements. We would like to have all scientific data in one easy to access environment, but getting the world of scientific data in one analytic system is immensely difficult to achieve. This paper describes the data analytics web architecture NASA is developing by infusing instances of Integrated Data Analytics systems next to the data. The goal is to minimize unnecessary data movement through collection of data access and analytics webservices for researchers to interact with and analyze measurements without have to download data to their local computer. These services are RESTful and provisioned by the data centers with the help from subject matter and science experts. These services encapsulate the physical computing infrastructure, which could local computing cluster, on-premise or public Cloud environment.

Huang, Thomas↗
NASA NTRSDate not supplied

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗
NASA NTRSDate not supplied

All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders

Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

pcrtm↗
NASA NTRSDate not supplied

20-Years of Atmospheric Temperature, Water Vapor, Cloud, and Surface Temperature Anomalies and Trends Derived From Operational Hyperspectral Ir Sounders

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The SiFSAP retrieval algorithm also uses the same climatology a priori and associated covariances, which makes it ideal for generating high quality products for both weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗
NASA NTRSDate not supplied

Remote Sensing of Atmospheric Temperature, Water Vapor, Trace Gases, Cloud, and Surface Properties on Daily and Decadal Time Scales

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Development of Radiative Transfer Models and Retrieval Algorithms for Satellite Remote Sensors

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

PREFIRE at ASDC Revolutionizing Polar System Observations

In the ongoing battle against climate change, early detection is key to minimizing their devastating impact on communities and ecosystems. Hosted by the Atmospheric Science Data Center (ASDC) at NASA's Langley Research Center, PREFIRE mission aims to bridge a critical knowledge gap in climate science by focusing on the far-infrared (FIR) portion of the electromagnetic spectrum, which has been historically under-observed.

Hazem M↗
NASA NTRSDate not supplied

A Spectral Fingerprinting Method for Deriving Consistent Climate Data Records from Multiple Satellite IR Sounders

Deriving Climate Data Records (CDRs) from multiple IR sounders such AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C requires from current operational products are challenging due to different radiative transfer models and retireavl algorithms used for processing level 2 data. We developed a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm, which uses a single set of radiative kernels a robust spectral fingerprinting method to performs retrievals using spatiotemporally averaged L1 hyperspectral radiances directly. The ClimFiSP algorithm provides accurate data fusion CDR products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. We plan to add IASI to the CDR data set in the future. The ClimFiSP is being transitioned to NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRS2024

Lattice Confinement Fusion-Fast-Fission

Lattice Confinement Fusion (LCF) • Published 2020, Physical Review C 1,2 • Patented and Commercialized 2024, Astral Systems • LCF in compact neutron generator 50x increase in neutron flux, 99% from LCF • Produce medical radioisotopes • LCF Fast-Fission Hybrid Reaction • No Enriched Uranium • Demonstrated with US Navy and GEC • Modeling and Scaling under NIAC and NSF funding • Application • Deep space • Power: Icy worlds • Propulsion: Nuclear Electric Propulsion • Planetary Surface Power: Lunar and Mars • Terrestrial • DoD Operational Energy • Onsite power for Data Centers

lattice confinement fusion↗
NASA NTRSDate not supplied

Lattice Confinement Fusion-Fast-Fission

Lattice Confinement Fusion (LCF) • Published 2020, Physical Review C 1,2 • Patented and Commercialized 2024, Astral Systems • LCF in compact neutron generator 50x increase in neutron flux, 99% from LCF • Produce medical radioisotopes • LCF Fast-Fission Hybrid Reaction • No Enriched Uranium • Demonstrated with US Navy and GEC • Modeling and Scaling under NIAC and NSF funding • Application • Deep space • Power: Icy worlds • Propulsion: Nuclear Electric Propulsion • Planetary Surface Power: Lunar and Mars • Terrestrial • DoD Operational Energy • Onsite power for Data Centers

nuclear electric propulsion↗
DOE OSTI2021

Priority-enabled Load Balancing for Dispersed Computing

Opportunistic managed access to local in-network compute resources can improve the performance of distributed applications and reduce the dependence on shared network resources. Instead of backhauling application data to a centralized cloud data center for processing, networked services may be adaptively and continuously dispersed into shared compute resources that are closer to the source of need. While this approach has several benefits, support for mission-aware access to computation is often an afterthought, and is implemented as a brittle extension over traditional load-balancer solutions.In this work, we investigate the design of two priority-aware resource allocation strategies and two load-balancing dispatching strategies as first class citizens in an open-source dispersed computing middleware. We present a control theoretic analysis of these load-balancing primitives to identify weaknesses and strengths in our design, and recommend future directions. In parallel, we prototype two priority-aware allocation algorithms to validate our priority predictions. In initial experiments our prototype shows substantial gains in processing prioritized load. Finally, we make our source-code and experimental configurations open source.

Paulos, Aaron↗
DOE OSTI2021

Markets and Economic Requirements for Fission Batteries and Other Nuclear Systems

Fission Batteries (FBs) are nuclear reactors defined by five characteristics which enable large-scale deployment: cost competitive, standardized sizes for economic mass production, easy installation and removal, secure and safe unattended operation with high reliability. FBs are not defined by technology or power level. Technical and market considerations suggest that most FBs will produce 20 to 30 MWt. This proceedings reports on the outcomes of two workshops that were held in January 2021 to better define markets and economic challenges for FBs. Three major markets were identified. The largest market is the industrial and commercial heat market. There are about 4000 industrial users (excluding utilities) that require more than one megawatt of heat. The number of customers versus size of heat demand was determined. In a low-carbon world there is the potential for many additional customers—including expanded biofuels production and district heat. The second market is for non-grid electricity. This includes co-generation plants that produce heat and electricity for a single customer. The third market is the maritime market with ~100,000 ships worldwide. In the United States, natural gas is the low-cost energy option today and will remain so unless constraints or taxes impact its use. If restrictions on greenhouse gas emissions, the FB competition includes natural gas with carbon capture, biofuels, hydrogen and grid electricity. Natural gas with carbon capture is not economically viable on a small scale. Biofuels may be expensive but may be the economically preferred option for locations with small energy demands of a few megawatts. Hydrogen is a potential competitor with many of the characteristics of natural gas. Grid electricity is not a competitive source of heat. For FBs to be economically competitive, the price of delivered heat must be $20-50/MWh ($6-15/million BTU). The economically competitive range for non-grid electricity is estimated at $70-100/MWh. These electricity prices are competitive with the retail prices of electricity in many parts of the United States for the customer. FBs are not expected to be competitive selling wholesale electricity to the grid. To achieve the aforementioned cost targets for heat and electricity markets, FB designers must (1) maximize the power output within the constraints of a FB (e.g., truck transportability, passive decay heat removal), (2) drastically reduce the size of onsite staff, (3) adopt core designs with low fuel costs (enrichment and fabrication), and (4) develop a system design that is efficiently manufactured in factories. The business case depends upon more than being just a replacement for natural gas. The largest incentives for adoption of FBs is where they create new markets and new sources of revenue. An example is the paper and pulp industry that burns biomass wastes to provide heat and electricity to make paper. An external heat source could meet the demand for heat and electricity by the paper process and enable converting waste biomass into liquid biofuels rather than burning to provide heat. Other markets, such as data centers, are driven by special energy requirements such as extreme reliability. Most customers are not in the energy business but need heat and electricity to produce a product—a manufactured good, education, retail sales (shopping malls), marine transport or some other product. As a consequence, there will be large incentives to lease rather than own FBs. Leasing avoids the regulatory challenges that remain with the owner of the FB. Leasing creates large incentives for FP standardization of sizes and transportability to maintain the value of the FB at the end of the lease—similar to the leasing of jet engines and aircraft. The economic constraints combined with technical constraints suggest competitive FBs will likely have outputs exceeding 10 MWt. There appear to be little incentives for very long-lived reactor cores because such machines require much larger inventories of fuel. Maintenance requirements and the options to provide technology updates may favor shorter lifetimes (~5 years). The assessment is that there is the potential for FBs to be economically viable and play a major role in global decarbonization in three markets: heat, non-grid electricity and maritime applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Reducing Commercial Building Process Loads and Refrigeration Unit Energy Consumption

This resource provides guidance on larger PPLs, many of which are hardwired. Examples include elevators, enterprise servers, freezers, and water fountains with chillers, which are often collectively referred to as "process loads." This resource also outlines how to assess process loads in a building, describes the procedure for identifying which loads to target for reduction, and provides an overview of reduction strategies. In this resource, process loads are broken into five categories - food handling, refrigeration, internal mobility, data center and information technology, and water handling.

commercial buildings↗
DOE OSTI2023

Progress Update from the EV Charging Working Group (#982)

The EV charging working group (#982) was formed in summer 2022 to define the equip, points, relationships, and operational data related to Level 1-2 (AC) and Level 3 (DC) Electric Vehicle Supply Equipment (EVSE). Last year, the working group developed formal EVSE-related equipment definitions, where were merged into the Project Haystack documentation in November 2022. More recently the group has also been working to expand and improve Haystack definitions related to electrical equipment and circuits. This initiative is important both for EV charging related applications and to improve Project Haystack's appeal to other industry verticals such as data centers, commercial building electrification, and more. In this presentation we will share the working group's motivation, progress, and near-term objectives.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗