Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “function as a service”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Mobile radio alternative systems study satellite/terrestrial (hybrid) systems concepts

The use of satellites for mobile radio service in non-urban areas of the United States in the years from 1985 to 2000 was investigated. Several satellite concepts are considered: a system with single-beam coverage of the fifty United States and Puerto Rico, and multi-beam satellites with greater capacity. All of the needed functions and services identified in the market study are provided by the satellite systems, including nationwide radio access to vehicles without knowledge of vehicle location wideband data transmission from remote sites, two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The costs of providing the services are within acceptable limits, and the desired returns to the system investors are attractive. The criteria by which the Federal Communication judges the competing demands for public radio spectrum are reviewed with comments on how the criteria might apply to the consideration of land mobile satellites. Institutional arrangements for operating a mobile satellite system are based on the present institutional arrangements in which the services are offered to the end users through wireline and radio common carriers, with direct access by large private and government users.

Kiesling, J. D.↗
NASA NTRS2005

Interpreting the International Space Station Microgravity Environment

The International Space Station (ISS) serves as a platform for microgravity research for the foreseeable future. A microgravity environment is one in which the effects of gravity are drastically reduced which then allows physical experiments to be conducted without the overpowering effects of gravity. A physical environment with very low-levels of acceleration and vibration has been accomplished by both the free fall associated with orbital flight and the design of the International Space Station. The International Space Station design has been driven by a long-standing, high-level requirement for a microgravity mode of operation. The Space Acceleration Measurement System has been in operation for nearly four years on the ISS measuring the microgravity environment in support of principal investigators and to characterize the ISS microgravity environment. The Principal Investigator Microgravity Services project functions as a detective to ascertain the source of disturbances seen in the ISS microgravity environment to allow correlation between that environment and experimental data. Payload developers need to predict the microgravity environment that will be imposed upon an experiment and ensure that the science and engineering requirements will be met. The Principal Investigator Microgravity Services project is developing n interactive tool to predict the microgravity environment at science payloads based on user defined operational scenarios. These operations (predictions and post-analyses) allow a researcher to examine the microgravity acceleration levels expected to exist when their experiment is operated and then receive an analysis of the environment which existed during their experiment operations. Presented in this paper will be descriptions of the environment predictive tool and an investigation into a previously unknown disturbance in the ISS microgravity environment.

DeLombard, Richard↗
DOE OSTI2023

Human‐induced salinity changes impact marine organisms and ecosystems

Abstract Climate change is fundamentally altering marine and coastal ecosystems on a global scale. While the effects of ocean warming and acidification on ecology and ecosystem functions and services are being comprehensively researched, less attention is directed toward understanding the impacts of human‐driven ocean salinity changes. The global water cycle operates through water fluxes expressed as precipitation, evaporation, and freshwater runoff from land. Changes to these in turn modulate ocean salinity and shape the marine and coastal environment by affecting ocean currents, stratification, oxygen saturation, and sea level rise. Besides the direct impact on ocean physical processes, salinity changes impact ocean biological functions with the ecophysiological consequences are being poorly understood. This is surprising as salinity changes may impact diversity, ecosystem and habitat structure loss, and community shifts including trophic cascades. Climate model future projections (of end of the century salinity changes) indicate magnitudes that lead to modification of open ocean plankton community structure and habitat suitability of coral reef communities. Such salinity changes are also capable of affecting the diversity and metabolic capacity of coastal microorganisms and impairing the photosynthetic capacity of (coastal and open ocean) phytoplankton, macroalgae, and seagrass, with downstream ramifications on global biogeochemical cycling. The scarcity of comprehensive salinity data in dynamic coastal regions warrants additional attention. Such datasets are crucial to quantify salinity‐based ecosystem function relationships and project such changes that ultimately link into carbon sequestration and freshwater as well as food availability to human populations around the globe. It is critical to integrate vigorous high‐quality salinity data with interacting key environmental parameters (e.g., temperature, nutrients, oxygen) for a comprehensive understanding of anthropogenically induced marine changes and its impact on human health and the global economy.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Distributed Active Archive Center

The Goddard Space Flight Center Version 0 Distributed Active Archive Center (GSFC V0 DAAC) is being developed to enhance and improve scientific research and productivity by consolidating access to remote sensor earth science data in the pre-EOS time frame. In cooperation with scientists from the science labs at GSFC, other NASA facilities, universities, and other government agencies, the DAAC will support data acquisition, validation, archive and distribution. The DAAC is being developed in response to EOSDIS Project Functional Requirements as well as from requirements originating from individual science projects such as SeaWiFS, Meteor3/TOMS2, AVHRR Pathfinder, TOVS Pathfinder, and UARS. The GSFC V0 DAAC has begun operational support for the AVHRR Pathfinder (as of April, 1993), TOVS Pathfinder (as of July, 1993) and the UARS (September, 1993) Projects, and is preparing to provide operational support for SeaWiFS (August, 1994) data. The GSFC V0 DAAC has also incorporated the existing data, services, and functionality of the DAAC/Climate, DAAC/Land, and the Coastal Zone Color Scanner (CZCS) Systems.

Bodden, Lee↗
NASA NTRS1996

A mission operations architecture for the 21st century

An operations architecture is proposed for low cost missions beyond the year 2000. The architecture consists of three elements: a service based architecture; a demand access automata; and distributed science hubs. The service based architecture is based on a set of standard multimission services that are defined, packaged and formalized by the deep space network and the advanced multi-mission operations system. The demand access automata is a suite of technologies which reduces the need to be in contact with the spacecraft, and thus reduces operating costs. The beacon signaling, the virtual emergency room, and the high efficiency tracking automata technologies are described. The distributed science hubs provide information system capabilities to the small science oriented flight teams: individual access to all traditional mission functions and services; multimedia intra-team communications, and automated direct transparent communications between the scientists and the instrument.

Tai, W.↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Technology requirements for communication satellites in the 1980's

The key technology requirements are defined for meeting the forecasted demands for communication satellite services in the 1985 to 1995 time frame. Evaluation is made of needs for services and technical and functional requirements for providing services. The future growth capabilities of the terrestrial telephone network, cable television, and satellite networks are forecasted. The impact of spacecraft technology and booster performance and costs upon communication satellite costs are analyzed. Systems analysis techniques are used to determine functional requirements and the sensitivities of technology improvements for reducing the costs of meeting requirements. Recommended development plans and funding levels are presented, as well as the possible cost saving for communications satellites in the post 1985 era.

Burtt, J. E.↗
NASA NTRS1978

Emergency Communications Console

NASA has applied its communications equipment expertise to development of a communications console that provides, in a compact package only slightly larger than an electric typewriter, all the emergency medical services communications functions needed for a regional hospital. A prototype unit, built by Johnson Space Center, has been installed in the Odessa (Texas) Medical Center Hospital. The hospital is the medical control center for the 17-county Permian Basin Emergency Medical System in west Texas. The console project originated in response to a request to NASA from the Texas governor's office, which sought a better way of providing emergency medical care in rural areas. Because ambulance travel time is frequently long in remote areas of west Texas, it is important that treatment begin at the scene of the emergency rather than at the hospital emergency room. A radio and telephone system linking ambulance emergency technicians and hospital staff makes this possible. But earlier equipment was complex, requiring specialized operators. A highly reliable system was needed to minimize breakdowns and provide controls of utmost simplicity, so that the system could be operated by physicians and nurses rather than by communications specialists. The resulting console has both radio and telephone sections. With the radio equipment, hospital personnel can communicate with ambulance drivers and paramedics, receive incoming electrocardiagrams, consult with other hospitals, page hospital staff and set up a radio-to-telephone "patch." The telephone portion of the system includes a hotline from the Permian Basin Emergency Medical Service's resource control center, an automatic dialer for contacting special care facilities in the Permian Basin network, a hospital intercom terminal and a means of relaying cardioscope displays and other data between hospitals. The integrated system also provides links with local disaster and civil defense organizations and with emergency "Dial 911" control points.

Source record↗
DOE OSTI2025

Valued peaks: Sustainable water allocation for small hydropower plants in an era of explicit ecological needs

Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.

13 HYDRO ENERGY↗
DOE OSTI2022

Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing

Soil organic carbon (SOC) is a key variable to determine soil functioning, ecosystem services, and global carbon cycles. Spectroscopy, particularly optical hyperspectral reflectance coupled with machine learning, can provide rapid, efficient, and cost-effective quantification of SOC. However, how to exploit soil hyperspectral reflectance to predict SOC concentration, and the potential performance of airborne and satellite data for predicting surface SOC at large scales remain relatively underknown. Here, this study utilized a continental-scale soil laboratory spectral library (37,540 full-pedon 350–2500 nm reflectance spectra with SOC concentration of 0–780 g·kg –1 across the US) to thoroughly evaluate seven machine learning algorithms including Partial-Least Squares Regression (PLSR), Random Forest (RF), K-Nearest Neighbors (KNN), Ridge, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) along with four preprocessed spectra, i.e. original, vector normalization, continuum removal, and first-order derivative, to quantify SOC concentration. Furthermore, by using the coupled soil-vegetation-atmosphere radiative transfer model, we simulated twelve airborne and spaceborne hyper/multi-spectral remote sensing data from surface bare soil laboratory spectra to evaluate their potential for estimating SOC concentration of surface bare soils. Results show that LSTM achieved best predictive performance of quantifying SOC concentration for the whole data sets (R 2 = 0.96, RMSE = 30.81 g·kg –1 ), mineral soils (SOC ≤ 120 g·kg –1 , R 2 = 0.71, RMSE = 10.60 g·kg –1 ), and organic soils (SOC > 120 g·kg –1 , R 2 = 0.78, RMSE = 62.31 g·kg –1 ). Spectral data preprocessing, particularly the first-order derivative, improved the performance of PLSR, RF, Ridge, KNN, and ANN, but not LSTM or CNN. We found that the SOC models of mineral and organic soils should be distinguished given their distinct spectral signatures. Finally, we identified that the shortwave infrared is vital for airborne and spaceborne hyperspectral sensors to monitor surface SOC. This study highlights the high accuracy of LSTM with hyperspectral/multispectral data to mitigate a certain level of noise (soil moisture <0.4 m 3 ·m –3 , green leaf area < 0.3 m 2 ·m –2 , plant residue <0.4 m 2 ·m –2 ) for quantifying surface SOC concentration. Forthcoming satellite hyperspectral missions like Surface Biology and Geology (SBG) have a high potential for future global soil carbon monitoring, while high-resolution satellite multispectral fusion data can be an alternative.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Field experiments show no consistent reductions in soil microbial carbon in response to warming

Soil microbes play an essential role in maintaining soil functions and services, but the dynamics of soil microbial biomass carbon (MBC) under global climate change remain unclear. Recently, Patoine et al. combined a global MBC data set with Random Forest modeling and reported that global MBC decreased over 1992–2013, mainly driven by increasing temperatures. Contrarily, using MBC field observations from soil warming manipulation experiments and in-situ long-term measurements across the globe, we found that MBC showed no significant changes under soil warming. Our findings indicate that soil MBC is unlikely to have decreased significantly due to the global warming of 0.28 °C during 1992–2013, and that further mechanistic studies are needed to understand potential changes in MBC under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A compendium of bacterial and archaeal single-cell amplified genomes from oxygen deficient marine waters

Oxygen-deficient marine waters referred to as oxygen minimum zones (OMZs) or anoxic marine zones (AMZs) are common oceanographic features. They host both cosmopolitan and endemic microorganisms adapted to low oxygen conditions. Microbial metabolic interactions within OMZs and AMZs drive coupled biogeochemical cycles resulting in nitrogen loss and climate active trace gas production and consumption. Global warming is causing oxygen-deficient waters to expand and intensify. Therefore, studies focused on microbial communities inhabiting oxygen-deficient regions are necessary to both monitor and model the impacts of climate change on marine ecosystem functions and services. Here we present a compendium of 5,129 single-cell amplified genomes (SAGs) from marine environments encompassing representative OMZ and AMZ geochemical profiles. Of these, 3,570 SAGs have been sequenced to different levels of completion, providing a strain-resolved perspective on the genomic content and potential metabolic interactions within OMZ and AMZ microbiomes. Hierarchical clustering confirmed that samples from similar oxygen concentrations and geographic regions also had analogous taxonomic compositions, providing a coherent framework for comparative community analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Small-Scale Irrigation: Improving Food Security under Changing Climate and Water Resource Conditions in Ethiopia

We develop a new systems modeling tool that integrates knowledge from hydrology, agriculture, and economics to understand the effect of small-scale irrigation on food security and groundwater sustainability in Ethiopia. Irrigation is an effective tool to mitigate climate impacts and improve agricultural yields. Small-scale irrigation, such as decentralized groundwater irrigation, is well suited for developing countries where smallholder farming communities are widely dispersed and can only afford small infrastructure investment. We study the underlying interdependencies between food and water systems in Ethiopia, where small-holder agriculture is the foundation of the nation’s economy and climate variability has led to great challenges to its food security. Our coupled market and crop model with groundwater module captures the interdependencies of climate, water availability (including irrigation), crop yield, farmland allocation, crop production, transport and consumption based on a system approach across multiple spatial scales. We study the implication of small-scale irrigation to Ethiopia’s food security and water resource conditions as a “what-if” question by comparing an irrigation scenario to the calibrated baseline in 2015, a year of significant drought and crop failure over a large portion of Ethiopia. Our model offers fresh insights into geographic disparities in outcomes that are driven by baseline climate variability, soil fertility, and market conditions. In general, we find that small-scale irrigation can potentially improve food security through increases in food consumption, but it requires policy support to direct the increases of production to domestic consumption while maintaining a sustainable groundwater condition. By using Ethiopia as an example, we show the strength of our model to study how water infrastructure resources support critical functions and service in water and food systems.

Zhang, Ying↗
DOE OSTI2022

Artificial light at night: an underappreciated effect on phenology of deciduous woody plants

Artificial light at night (ALAN), an increasing anthropogenic driver, is widespread and shows rapid expansion with potential adverse impact on the terrestrial ecosystem. However, whether and to what extent does ALAN affect plant phenology, a critical factor influencing the timing of terrestrial ecosystem processes, remains unexplored due to limited ALAN observation. Here, we used the Black Marble ALAN product and phenology observations from USA National Phenology Network to investigate the impact of ALAN on deciduous woody plants phenology in the conterminous United States. We found that (1) ALAN significantly advanced the date of breaking leaf buds by 8.9 ± 6.9 days (mean ± SD) and delayed the coloring of leaves by 6.0 ± 11.9 days on average; (2) the magnitude of phenological changes was significantly correlated with the intensity of ALAN (P < 0.001); and (3) there was an interaction between ALAN and temperature on the coloring of leaves, but not on breaking leaf buds. We further showed that under future climate warming scenarios, ALAN will accelerate the advance in breaking leaf buds but exert a more complex effect on the coloring of leaves. This study suggests intensified ALAN may have far-reaching but underappreciated consequences in disrupting key ecosystem functions and services, which requires an interdisciplinary approach to investigate. Developing lighting strategies that minimize the impact of ALAN on ecosystems, especially those embedded and surrounding major cities, is challenging but must be pursued.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CCE Phase 1: Consequence Prioritization

Idaho National Laboratory (INL) developed the Consequence-driven Cyber-informed Engineering (CCE) methodology to provide public and private organizations with steps to work collaboratively and establish a working relationship to protect critical infrastructure and other national assets. This process is a considerable undertaking, iterative in nature, and—as time and resources allow—should become a part of a company’s culture. By focusing on the impact of potentially negative Events, CCE provides a better understanding of how and why adversaries can affect critical functions and services using cyber-enabled sabotage. This document describes Phase 1 of the CCE process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Lawrence Livermore National Laboratory Experimental Test Site, Site 300: Soil Study Institutional Review Board #1081 Soil Sampling and Analysis Plan

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Functional Area/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) to collect soil quality data at an area located at Lawrence Livermore National Laboratory’s (LLNL’s) Experimental Test Site, Site 300 (Site 300) (project) (Figures 1 and 2). The purpose of the project is to determine the chemical and radiological quality of soil in the project area to support feasibility and design of future improvements. This SAP identifies chemicals of concern and describes the procedures for collection and analysis of environmental samples, and evaluation of analytical data (chemical and radiological) to determine the reuse potential of shallow soil at the project area. This SAP follows the criteria established in LLNL’s Soils Screening and Management Plan (SSMP) (LLNL 2022), which is consistent with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, U.S. DOD 2000). The scope of this SAP is based on preliminary design information provided by PMO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Living-off-the-land Techniques Unlikely to Supplant Energy Sector-Focused OT-Specific Malware

Despite increased reports of energy sector-focused threat actors using living-off-the-land (LOTL) techniques, it is unlikely LOTL techniques will wholly supplant malware in energy sector operational technology (OT)-focused cyber operations. Threat actors leverage LOTL techniques to access energy sector networks, abstracting process information and maintaining persistence. Although threat actors using LOTL techniques have successfully interrupted energy sector industrial control environments, designed features of OT-specific malware likely increase the cyber-physical impact of an attack and delay recovery of critical functions and services. Malicious actors will very likely continue to use LOTL techniques for stealth, while designing malware to bolster final impacts on cyber-physical systems in energy sector OT environments.

99 GENERAL AND MISCELLANEOUS↗