Cooperative modulation for long haul relay in sensor networks
Cooperative modulation techniques can reduce the energy requirements for the long haul transmission of data from localized sensor networks.
modulation sensor networks↗
SEARCH · Engineering Papers
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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.
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[Space Weather Impact on the Electricity Market]
Forbes & St. Cyr (2004, hereafter "FISC") have provided evidence that the electricity market can be impacted by space weather. Our analysis indicated that the estimated market impact for PJM was 3.7 % or approximately $500 million dollars over the 19 month sample period. Kappenman has taken exception to this estimate and contends that we have exaggerated the magnitude of the problem that space weather poses to PJM. There are four specific issues: (1) he claims that we have ignored relevant literature; (2) he asserts that Dst is not an appropriate proxy for GICs in PJM; (3) he charges that our findings are inconsistent with the impact of the 17 September 2000 storm; and (4) he alleges that our discussion of October 2003 storms is misleading. In our article, we have explained our methodology, multivariate regression analysis, with a particular focus on how it compares to correlation analysis. We have also explained the limitations of our analysis. We noted that "...While the Dstlprice relationship was found to be robust, the precise estimate should be treated with a relatively high degree of caution given that econometric modeling is not an exact science as well as the fact that the measure of space weather may be a poor proxy for GICs" (paragraph 96). We have also noted that additional research using local magnetometer data are needed (paragraph 97). We did not claim that that our findings for PJM are representative of the impact of space weather on other power grids. On the contrary, we noted that ... "Only analysis of other power grids will tell. " (paragraph 97). Kappenman inaccurately asserts that we have indicated that our findings . . . "imply much higher total costs are likely across the US and elsewhere in the world." He also inaccurately asserts that we have claimed that " . . . Dst is the most suited proxy for GIC in the PJM grid.. ." Moreover, he inaccurately refers to our analysis as a correlation study that uses Dst as quasi-binary indicator.
SaintCyr, O. Chris↗
Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling
An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.
Imhoff, Marc L.↗
OTF CCSDS SM and C Interoperability Prototype
A presentation is provided to demonstrate the interoperability between two space flight Mission Operation Centers (MOCs) and to emulate telemetry, actions, and alert flows between the two centers. One framework uses a COTS C31 system that uses CORBA to interface to the local OTF data network. The second framework relies on current Houston MCC frameworks and ad hoc clients. Messaging relies on SM and C MAL, Core and Common Service formats, while the transport layer uses AMS. A centralized SM and C Registry uses HTTP/XML for transport/encoding. The project's status and progress are reviewed.
Reynolds, Walter F.↗
Infrared Imaging System for Studying Brain Function
A proposed special-purpose infrared imaging system would be a compact, portable, less-expensive alternative to functional magnetic resonance imaging (fMRI) systems heretofore used to study brain function. Whereas a typical fMRI system fills a large room, and must be magnetically isolated, this system would fit into a bicycle helmet. The system would include an assembly that would be mounted inside the padding in a modified bicycle helmet or other suitable headgear. The assembly would include newly designed infrared photodetectors and data-acquisition circuits on integrated-circuit chips on low-thermal-conductivity supports in evacuated housings (see figure) arranged in multiple rows and columns that would define image coordinates. Each housing would be spring-loaded against the wearer s head. The chips would be cooled by a small Stirling Engine mounted contiguous to, but thermally isolated from, the portions of the assembly in thermal contact with the wearer s head. Flexible wires or cables for transmitting data from the aforementioned chips would be routed to an integrated, multichannel transmitter and thence through the top of the assembly to a patch antenna on the outside of the helmet. The multiple streams of data from the infrared-detector chips would be sent to a remote site, where they would be processed, by software, into a three-dimensional display of evoked potentials that would represent firing neuronal bundles and thereby indicate locations of neuronal activity associated with mental or physical activity. The 3D images will be analogous to current fMRI images. The data would also be made available, in real-time, for comparison with data in local or internationally accessible relational databases that already exist in universities and research centers. Hence, this system could be used in research on, and for the diagnosis of response from the wearer s brain to physiological, psychological, and environmental changes in real time. The images would also be stored in a relational database for comparison with corresponding responses previously observed in other subjects.
Mintz, Frederick↗
Antenna Axis Offset Estimation from VLBI
The antenna axis offsets were estimated from global solutions and single sessions. We have built a set of global solutions from R1 and R4 sessions and from the sets of sessions between SVETLOE repairs. We compared our estimates with local survey data for the stations of the QUASAR network. Svetloe station axis offset values have changed after repairs. For non-global networks, the axis offset value of a single station can significantly affect the EOP estimations.
Kurdubov, Sergey↗
Modeling the Ecosystem Services Provided by Trees in Urban Ecosystems: Using Biome-BGC to Improve i-Tree Eco
As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.
Brown, Molly E.↗
Investigation on Improvements in Lightning Retest Criteria for Spacecraft
Spacecraft are generally protected from a direct strike by launch the vehicle and ground structures, but protocols to evaluate the impact of nearby strikes are not consistent. Often spacecraft rely on the launch vehicle constraints to trigger a retest, but launch vehicles can typically evaluate the impact of a strike within minutes while spacecraft evaluation times can be on the order of hours or even days. For launches at the Kennedy Space Center where lightning activity is among the highest in the United States, this evaluation related delay could be costly with the possibility of missing the launch window altogether. This paper evaluated available data from local lightning measurements systems and computer simulations to predict the coupled effect from various nearby strikes onto a typical payload umbilical. Recommendations are provided to reduce the typical trigger criteria and costly delays.
Models↗
Relative Contribution of Monsoon Precipitation and Pumping to Changes in Groundwater Storage in India
The depletion of groundwater resources threatens food and water security in India. However, the relative influence of groundwater pumping and climate variability on groundwater availability and storage remains unclear. Here we show from analyses of satellite and local well data spanning the past decade that long-term changes in monsoon precipitation are driving groundwater storage variability in most parts of India either directly by changing recharge or indirectly by changing abstraction. We find that groundwater storage has declined in northern India at the rate of 2 cm/yr and increased by 1 to 2 cm/yr in southern India between 2002 and 2013. We find that a large fraction of the total variability in groundwater storage in north-central and southern India can be explained by changes in precipitation. Groundwater storage variability in northwestern India can be explained predominantly by variability in abstraction for irrigation, which is in turn influenced by changes in precipitation. Declining precipitation in northern India is linked to Indian Ocean warming, suggesting a previously unrecognized teleconnection between ocean temperatures and groundwater storage.
Climate-change impacts↗
Fully Coupled Aeroelastic Stability Analysis of Adaptive Shape Memory Alloy Structural Technologies for Airframe Noise Reduction
The objective of this work is the development of computational models and analysis of the coupled fluid-structure response of a slat gap filler (SGF) noise treatment applied to the leading-edge-slat component of a high-lift system typical of modern transport aircraft. The representative airframe chosen for this work is NASA’s High-lift Common Research Model (CRM-HL) in a baseline high-lift configuration. Superelastic shape memory alloys (SMAs) have been identified as enabling materials for these structural treatments. Since the technology elements rely upon having a highly reconfigurable structure, designs must be assessed for static aeroelastic deflection as well as dynamic aeroelastic stability using coupled computational fluid dynamics (CFD) and nonlinear computational structural dynamics (NL CSD) tools. The technical approach consists of solving for the flow field around the entire vehicle using a global CFD model, followed by extraction of relevant local subdomain data for CFD and NL-CSD co-simulations. The SGF design is assessed using both 2D and 3D co-simulations to predict quasi-static aeroelastic deformations and to assess dynamic aeroelastic stability.
Fluid structure interaction↗
Fully Coupled Aeroelastic Stability Analysis of Adaptive Shape Memory Alloy Structural Technologies for Airframe Noise Reduction
This final report documents work performed by ATA Engineering, Inc., (ATA) to develop computational models and analyze the coupled fluid-structure response of two types of noise treatments applied to the leading-edge-slat component of a high-lift system typical of modern transport aircraft. The first treatment is a slat-gap filler (SGF), which closes the gap between the suction surfaces of a deployed slat and an aircraft main wing, and the second treatment is a slat-cove filler (SCF), which replaces the recirculating flow on the slat cove with a surface that promotes flow attachment. The representative airframe chosen for this work was NASA’s High-Lift Common Research Model (CRM-HL) in a baseline high-lift configuration. Superelastic shape memory alloys (SMAs) have been identified as enabling materials for these structural treatments. Since the technology elements rely upon having a highly reconfigurable structure, designs were assessed for their static aeroelastic deflection as well as their dynamic aeroelastic stability using coupled computational fluid dynamics (CFD) and nonlinear computational structural dynamics (NL-CSD) tools. Specifically, fluid-structure interaction (FSI) problems were solved computationally using the CFD solver Loci/CHEM and the NL-CSD solver Abaqus. As a part of the overall project, a similar capability was implemented using the CFD solver FUN3D coupled to Abaqus, although that work is documented in a separate report and that FSI framework was not used to analyze any of NASA’s SGF and SCF configurations. The technical approach consisted of solving for the flow field around the entire vehicle using a global CFD model, followed by extraction of relevant local subdomain data for CFD and NL-CSD co-simulations. The SGF design was analyzed using both 2D and 3D co-simulations to predict quasi-static aeroelastic deformations and to assess dynamic aeroelastic stability, whereas the SCF was analyzed in 2D only. SGF static aeroelastic response predictions focused on characterizing the deformed shape, with maximum displacements predicted to be on the order of magnitude of the technology element panel thickness. SGF dynamic aeroelastic response predictions used Partial Floquet analysis of the temporal evolution of selected nodal displacements to quantify the sign and magnitude of aeroelastic damping. Results suggest that the CRM-HL operating conditions would result in a dynamically stable response. The simulated dynamic pressure was also increased up to a factor of about four, and resulting responses suggest that predicted dynamic stability would be achieved with some margin.
Fluid Structure Interaction↗
Exploring the Clouds of Venus: Science Driven Aerobot Missions to Our Sister Planet
Venus is essential to our understanding of the evolution and habitability of Earth-size planets throughout the galaxy. The selection of the VERITAS, EnVision, and DAVINCI missions by NASA and ESA in June 2021 is an important step in advancing the science. However, addressing many of the most challenging questions will require in situ platforms that can operate in the Venus environment for extended periods in order to capture the full complexity of our sister planet. Aerobots are aerial vehicles that exploit buoyancy to achieve long-duration operation in the Venus cloud layer where environmental conditions are comparatively benign. Buoyancy control, explained in more detail in a companion paper at this conference, allows aerobots to change altitude with little energy expenditure enabling new scientific measurement opportunities. These include atmospheric chemistry, dynamics, geophysical measurements of the crust and interior and geological investigations enabled by high resolution surface imaging. One aspect to our approach to defining missions that fit within the resource constraints of competitive missions is keeping the scale small. Today’s science-driven appetite for sophisticated measurements and large volumes of data is driving size upwards but advances in technology can enable aerobots that can be delivered to Venus at manageable costs. The other aspect is supporting the aerobot at Venus with orbiters providing data relay, localization and synergistic science. The recently selected orbiters, equipped with low-cost proximity relay systems routinely used at Mars may obviate the need for dedicated orbiters thereby enabling Discovery mission candidates. Four aerobot mission concepts have been defined which fit comfortably within the current New Frontiers (NF) cost cap ($900M in $FY22). One of these concepts would also be a candidate for a Discovery mission if that cost cap ($500M in $FY19) were raised. Raising the NF cost cap would enable more capable aerobot missions combining both altitude control with synergistic orbital observations. Investigations of surface geology at high resolution with subcloud NIR nightside imaging and dropsondes on the dayside of Venus could also benefit from collaborations with foreign contributions.
"O'Rourke, Joseph"↗
Global Arrays
Global Arrays (GA) is a distributed-memory programming model that allows for shared-memory-style programming combined with one-sided communication, to create a set of tools that combine high performance with ease-of-use. GA exposes a relatively straightforward programming abstraction, while supporting fully-distributed data structures, locality of reference, and high-performance communication. GA was originally formulated in the early 1990’s to provide a communication layer for the Northwest Chemistry (NWChem) suite of chemistry modeling codes that was being developed concurrently.
global arrays↗
Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output
The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.
Melin, Alexander M.↗
Archival, anonymization and presentation of HTCondor logs with GlideinMonitor
GlideinWMS is a pilot framework to provide uniform and reliable HTCondor clusters using heterogeneous and unreliable resources. The Glideins are pilot jobs that are sent to the selected nodes, test them, set them up as desired by the user jobs, and ultimately start an HTCondor schedd to join an elastic pool. These Glideins collect information that is very useful to evaluate the health and efficiency of the worker nodes and invaluable to troubleshoot when something goes wrong. This data, including local stats, the results of all the tests, and the HTCondor log files, is packed and sent to the GlideinWMS Factory. To access this information, developers and troubleshooters must exchange emails with Factory operators and dig manually into files. Furthermore, these files contain also information like email and IP addresses, and user IDs, that we want to protect and limit access to. GlideinMonitor is a Web application to make these logs more accessible and useful: it organizes the logs in an efficient compressed archive; it allows to search, unpack, and inspect them, all in a convenient and secure Web interface; via plugins like the log anonymizer, it can redact protected information preserving the parts useful for troubleshooting.
Mambelli, Marco↗
Utilizing GEOPHIRES-X Beyond Electricity
The GEOPHIRES tool is a techno-economic simulator for evaluating the thermal performance and cost-competitiveness of geothermal plants for electricity, heating, and/or cooling. The tool combines reservoir, wellbore, and surface plant cost and performance models to estimate overall techno-economic metrics such as net present value or levelized cost of electricity, heating, or cooling. We recently upgraded the tool to an object-oriented Python framework, presented in an accompanying paper. As part of the upgrade, we enhanced the capability to simulate the performance of geothermal plants for heating and cooling, which is the topic of this paper. Specifically, we (1) integrated absorption chillers to investigate the performance of utilizing geothermal heat for cooling, (2) integrated a heat pump module to boost the geothermal temperature and thermal output, (3) integrated a district heating module to estimate heating demand for a district based on local weather data, and simulated heat supply with geothermal energy and peaking boilers, and (4) integrated GEOPHIRES as an engine in the dGeo simulator to perform a geospatial analysis of geothermal district heating feasibility across a large region (e.g., a state or the entire United States) utilizing resource and thermal demand maps. This paper presents background information and case studies for several of these heating and cooling end-use options in GEOPHIRES.
absorption chiller↗
Demonstration and Feasibility Analyses of Using the Dual-Purpose Canister Drain Pipe to Support the Filling Process
This work documents experiments that are being used to determine the feasibility of filling dual-purpose canisters (DPCs) using the existing drain pipe. Mercury was identified as a surrogate filler for the initial experiments. Oak Ridge National Laboratory’s Target Test Facility (TTF), which is a full-scale Spallation Neutron Source (SNS) prototypical mercury loop, is being used for the planned pipe experiments using mercury. The pipe experiments were divided into two phases to provide a separate effects approach to the problem and to allow for development of system scalability. The first phase included taking strain measurements in a short length pipe, as well as measurements of flow-induced vibration. The second phase consists of the design and construction of a separated mercury flow loop capable of hosting exchangeable test sections and more localized instrumentation. Data acquisition of Phase I was performed during this work and is presented in the form of strain measurements and vibration frequency.
Dominguez-Ontiveros, Elvis↗
Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System
High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.
24 POWER TRANSMISSION AND DISTRIBUTION↗