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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Implementation Plan for Combined Heat and Power Systems VOLTTRON Controller: Performance Monitoring and Real-Time Commissioning Algorithm Verification

Building-integrated cooling, heating, and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV, and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of clean, efficient, reliable, and affordable next-generation integrated energy system. Previous report listed the components for which PM, real-time CxV, and AFDD algorithms will be developed, how the algorithms will be tested, and the metrics that will be used to validate the algorithms and their ease of deployment. Deployment of these algorithms in the field will result in a reduction in energy consumption of between 10% and 20% (for both CHP and conventional building systems). This report builds upon the previous report by detailing the process by which PNNL will implement performance monitoring and real-time commissioning algorithms for CHP systems in conjunction with the use of the VOLTTRON CHP economic dispatch agent in host facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2000

Biocybernetic Control of Vigilance Task Parameters

The major focus of the present proposal was to examine psychophysiological variables that are related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Freeman, Frederick G.↗
DOE OSTI2021

Lyapunov stability of smart inverters using linearized distflow approximation

Fast-acting smart inverters that utilize preset operating conditions to determine real and reactive power injection/consumption can create voltage instabilities (over-voltage, voltage oscillations and more) in an electrical distribution network if set-points are not properly configured. In this work, linear distribution power flow equations and droop-based Volt–Var and Volt–Watt control curves are used to analytically derive a stability criterion using Lyapunov analysis that includes the network operating condition. The methodology is generally applicable for control curves that can be represented as Lipschitz functions. The derived Lipschitz constants account for smart inverter hardware limitations for reactive power generation. A local policy is derived from the stability criterion that allows inverters to adapt their control curves by monitoring only local voltage, thus avoiding centralized control or information sharing with other inverters. The criterion is independent of the internal time-delays of smart inverters. Simulation results for inverters with and without the proposed stabilization technique demonstrate how smart inverters can mitigate voltage oscillations locally and mitigate real and reactive power flow disturbances at the substation under multiple scenarios. The study concludes with illustrations of how the control policy can dampen oscillations caused by solar intermittency and cyberattacks.

42 ENGINEERING↗
DOE OSTI2017

An Advanced Extreme-Environment Wireless Telemetry System for Turbine Blade Instrumentation

As advanced natural gas power generation systems evolve, the thrust for increased efficiencies and reduced emissions results in increasingly harsh conditions inside the turbine environment. These high temperatures, pressures, and corrosive atmospheres result in accelerated rates of degradation, leading to failure of turbine materials and components. Wolfspeed, A Cree Company, Siemens Energy, and Siemens Corporate Technology, in collaboration with the Department of Energy (DOE)'s National Energy Technology Laboratory, are developing a reliable and long-term monitoring capability in the turbine hot gas path in the form of novel ceramic-based thermocouples and wide bandgap instrumentation electronics that will contribute to the overall reliability of gas turbines. When equipped with better monitoring and controls, power plants can operate with increased fuel-burning efficiency, improved process dynamics and gas concentrations, and increased overall longevity of the power plant components. This will result in increased turbine availability and a reduction in outages and maintenance costs. The technology being developed in this program is based on advanced techniques and innovations in nearly every aspect of high-temperature electronics, including materials, semiconductor devices, subcomponents, electronic packaging, and system integration. The environment in which this wireless system must operate has continuous centrifugal loads with a gravitation force on the order of 16,000 times the force of gravity (16,000 g) and temperatures exceeding 400°C. This article will specifically discuss the background and motivation for the high-temperature instrumentation system and will explain the high-level electrical system, the construction of the instrumentation package, the techniques used for integration onto rotating components, as well as the wireless power and data transmission systems. In addition to the electrical and mechanical design, this article will also discuss results from laboratory bench testing as well as heated spin rig testing. Lastly, this article will highlight the future direction of the instrumentation system evolution, with a final objective of insertion into Siemens natural gas turbine power plants.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A new aerial approach for quantifying and attributing methane emissions: implementation and validation

Methane (CH 4 ) is a powerful greenhouse gas that is produced by a diverse set of natural and anthropogenic emission sources. Biogenic methane sources generally involve anaerobic decay processes such as those occurring in wetlands, melting permafrost, or the digestion of organic matter in the guts of ruminant animals. Thermogenic CH 4 sources originate from the breakdown of organic material at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C 2 H 6 ). Here, we present the development and deployment of an uncrewed aerial system (UAS) that employs a fast (1 Hz) and sensitive (1–0.5 ppb s -1 ) CH 4 and C 2 H 6 sensor and ultrasonic anemometer. The UAS platform is a vertical-takeoff, hexarotor drone (DJI Matrice 600 Pro, M600P) capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. Simultaneous measurements of CH 4 and C 2 H 6 concentrations, vector winds, and positional data allow for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The system has been used for direct quantification of methane point sources, such as orphan wells, and distributed emitters, such as landfills and wastewater treatment facilities. With detectable source rates as low as 0.04 and up to ~1500 kg h -1 , this UAS offers a direct and repeatable method of horizontal and vertical profiling of emission plumes at scales that are complementary to regional aerial surveys and localized ground-based monitoring.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Automated Hydrogen Gas Leak Detection System

The Gencorp Aerojet Automated Hydrogen Gas Leak Detection System was developed through the cooperation of industry, academia, and the Government. Although the original purpose of the system was to detect leaks in the main engine of the space shuttle while on the launch pad, it also has significant commercial potential in applications for which there are no existing commercial systems. With high sensitivity, the system can detect hydrogen leaks at low concentrations in inert environments. The sensors are integrated with hardware and software to form a complete system. Several of these systems have already been purchased for use on the Ford Motor Company assembly line for natural gas vehicles. This system to detect trace hydrogen gas leaks from pressurized systems consists of a microprocessor-based control unit that operates a network of sensors. The sensors can be deployed around pipes, connectors, flanges, and tanks of pressurized systems where leaks may occur. The control unit monitors the sensors and provides the operator with a visual representation of the magnitude and locations of the leak as a function of time. The system can be customized to fit the user's needs; for example, it can monitor and display the condition of the flanges and fittings associated with the tank of a natural gas vehicle.

Source record↗
DOE OSTI2017

DACCIWA Cloud-Aerosol Observations in West Africa Field Campaign Report

Interactions between aerosols and clouds, and their effects on radiation, precipitation, and regional circulations, are one of the largest uncertainties in understanding climate. With reducing uncertainties in predictions of weather, climate, and climate impacts in mind, the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project, funded by the European Commission, set out to improve our understanding of cloud-aerosol interactions in southern West Africa. This region is ideal for studying cloud-aerosol interactions because of its rich mix of natural and anthropogenic aerosols and diverse clouds, and because of the strong dependence on the regional and global climate of the sensitive West African monsoon. The overview of DACCIWA is described in Knippertz et al. 2015. The interdisciplinary DACCIWA team includes not only several European and African universities, but also Met Centres in the UK, France, Germany, Switzerland, Benin, Ghana, and Nigeria. One of the crucial research activities in DACCIWA is the major field campaign in southern West Africa from June to July 2016, comprising a benchmark data set for assessing detailed processes on natural and anthropogenic emissions; atmospheric composition; air pollution and its impacts on human and ecosystem health; boundary layer processes; couplings between aerosols, clouds, and rainfall; weather systems; radiation; and the monsoon circulation. Details and highlights of the campaign can be found in Flamant et al. 2017. To provide aerosol/cloud microphysical and optical properties that are essential for model evaluations and for the linkage between ground-based, airborne, and spaceborne observations, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility loaned two sun photometers to the DACCWIA team for the campaign from June 8 to July 29, 2016. The first sun photometer was deployed at Kumasi, Ghana (6.67962°N, 1.56019°W) by the University of Leeds (UK). The instrument was supposed to operate in normal aerosol mode in clear-sky conditions for aerosol monitoring, and operate in cloud mode for measuring cloud properties when clouds block the sun. Unfortunately, the robot of the sun photometer did not work properly from the beginning of the deployment, and remained problematic throughout the campaign. No useful data was recovered. The second sun photometer was deployed at Savé, Benin (8.000842°N, 2.413115°E), set up and maintained by the Karlsruher Institut fuer Technologie, Germany. Unlike most sun photometers that are designed to monitor aerosol properties and thus operated in normal aerosol mode, this sun photometer at Savé was operated in a special cloud mode, pointing vertically and measuring zenith radiance continuously at wavelengths of 440, 500, 675, 870, 1020, and 1640 nm with 10-sec temporal resolution. Zenith radiances at 440, 870, and 1640 nm alone can be used to retrieve cloud optical depth and column-mean effective radius (Chiu et al. 2010, 2012). The following section takes 6 and 7 July as an example to highlight a typical diurnal cycle of clouds observed during the campaign. Cloud properties retrieved from zenith radiance are compared against those retrieved from microwave radiometer (MWR) measurements, and against in situ measurements collected from the Twin Otter aircraft.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Technical Performance and Cost Optimization of Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) for Wide-area Surveillance and Identification of Marine Life at Marine Energy Installations

Florida Atlantic University developed an underwater optical monitoring system prototype - Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) - suitable for marine energy full project lifecycle observation (baseline, commissioning, and decommissioning), with an automated real-time classification of marine animals. With precursor 2014 DOE funding (award DE-EE0006787), a prototype UMSLI was demonstrated in a controlled laboratory environment and achieved a TRL 6. This EERE DE-EE0007828 award aimed to both increase the TRL of the UMSLI by improving the technology performance (e.g., increase distance of marine animal target detection capability, add additional species classification capabilities, improve the system performance during the day, etc.) and reduce the cost. The UMSLI presents a novel application of underwater distributed Light Detection And Ranging (LiDAR), an advanced remote sensing method that uses light in the form of laser pulses for an application, this paired with an algorithm provides 360 degrees underwater detection, imaging, and classification of marine life. This solution for underwater monitoring of biota preserves the advantages of traditional optical and acoustic solutions while overcoming many associated disadvantages for marine energy site environmental monitoring, such as difficulties in species detection and classification in low light or night and turbid environments. This new approach is a purposefully designed, reconfigurable adaptation of an existing class 3B laser technology into one UMSLI instrument that can be easily mounted on or around different classes of marine energy equipment, such as devices to capture ocean current energy or wave energy. The system uses relatively low average power, utilizes far-red (> 635nm) laser illumination to be invisible and eye-safe to marine animals, is compact, and cost-effective. The equipment is designed for long-term, maintenance-free operations (i.e., current design is targeting more than 7 days continuous operation), to inherently generate a sparse primary dataset that only includes detected anomalies, and to allow robust real-time automated animal classification and identification with a low data bandwidth requirement. The technology’s overarching goal for application, is a system that can be deployed to collect pre-installation baseline species observations at a proposed marine energy deployment site with minimal post-processing overhead. The envisioned system will also produce high-resolution imagery of marine animals through a wide range of conditions and support automated tracking and notification of the presence of managed animals within established perimeters of marine energy equipment to satisfy deployed marine energy projects’ endangered and threatened species monitoring requirements. Through the current project, we demonstrated the UMSLI prototype in an operational environment and increased the UMSLI’s Technology Readiness Level from 6 to 7. The project resulted in many novel technologies, including: 1) an eye-safe red laser based, low-cost LiDAR system that can detect targets up to 10 meters distance; 2) the GAN-based machine learning underwater LiDAR image enhancement technique (this is the first known application of GAN technique in underwater LiDAR); 3) LiDAR-based real-time automated detection capabilities; and 4) a template matching based automated classification tool. These technologies build a solid foundation for future efforts to develop an extended range electro-optical monitoring system suitable for marine energy deployments. In addition to technology development, a key lesson learned is that addressing regulatory and safety requirements must be front and center in any marine energy monitoring applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Condition monitoring and false alarm reducing of sensors in NPP - 222

With more and more application of digital I and C systems in nuclear power plants (NPP), more and more sensors are also required. Large amount of sensors really can make contribution to the condition monitoring of systems and equipment in NPP, whereas the heavy use also increases the malfunction risk of sensor self. Therefore the reliability and effectiveness of sensors must be guaranteed first. Thus the condition of sensors should be monitored first in a NPP. Since the precise mathematical models of sensors in complex systems are relative difficult to establish, however quantity of operating data can be easily obtained due to the wide application of digital I and C systems, thus this article adopts principal component analysis (PCA) to carry out condition monitoring for sensors. The PCA model developed for sensors is proved to be effective with operating data acquired from a real NPP. It can detect and isolate the fault when an artificial fault is imposed to the normal data. Then the monitoring results are further processed by another control limit (second confidence limit) besides T 2 and Q statistics (first confidence limit) in PCA. The value of second confidence limit is calculated based on the probability statistics of T 2 and Q statistics. And simulation tests show that the application of the second confidence limit can greatly reduce false alarms in the PCA model and the model performance can be greatly improved with the application of false alarms reducing method. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1989

A capacitive technique for real-time monitoring polymer coating thickness on carbon filaments during prepregging process

A technique for gauging the coating thickness during prepreg processing of carbon fibers was developed. It is based on the concept of measuring the capacitance of a cylindrical condenser through which a bundle of prepregged fibers is passed axially. Empirical results indicate the capacitance of this condenser element is linearly related to the polymer coating thickness on the fibers in the bundle. The capacitive transducer was successfully used to measure the polymer thickness on several test fiber bundles under static conditions.

Eftekhari, Abe↗
NASA NTRS2022

A Compact Electron-Proton Spectrometer for Moon / Mars Surface Space Weather Monitoring and Crew Protection (CEPS)

Small mass/low-power sensors are needed for autonomous Moon/Mars surface ops that provide alerts to impending adverse space weather conditions. In order to use current operational forecasting tools, a sensor capable of measuring both high-energy electrons and protons is needed. By combining high-TRL Timepix technology with a CdTe layer, this project leverages known technology to fill a critical gap for surface operations. Typical space weather sensors are at least an order of magnitude higher in mass than is expected from Timepix-based devices and are deployed on robotic assets away from human crews. High fidelity measurements at the crew location and subsequent ability are needed to provide warnings to crews to shelter with a device that can easily be carried on the Lunar and Martian surfaces.​ The aim of this project is the development of compact, low power space weather sensors for crew protection based on the combination of AES flight heritage Timepix hardware with novel CdTe (Cadmium Telluride) sensors. CdTe technology has only recently matured to a point where it can be reliably used with Timepix detectors. These detectors will be able to measure electron spectra in an energy range relevant to the RELEASE model, which is used operationally by NASA to provide crew early warning of Solar Energetic Particle Events as well as protons in the energy ranges relevant to human health allowing for event ‘nowcasting’ and total event crew dose prediction. Compared to existing solutions these detectors will be compact enough to travel with crew, providing a significant advantage to space environment situation awareness. Project results indicate that CdTe-based Timepix sensors respond well to energetic electrons, and particle tracks are sufficiently distinct to be able to measure in a mixed radiation field. Thermal testing results point to a needed design modification to mitigate high temperatures the detector will see in space. Radiation susceptibility testing was conducted to assess the radiation hardness of the CdTe-Timepix assembly. Overall, the assembly continued to operate up to 100 kRad of gamma-ray exposure. The system calibration did show drift over time but recovered once exposure was complete.

Dan James Fry↗
NASA NTRS2014

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗
DOE OSTI2018

Instrumentation and Control Selection for the 12 GeV Hall-B Magnets at Jefferson Lab

Here, as part of the Jefferson Lab 12 GeV accelerator upgrade, the Experimental Physics Hall B detector system requires two superconducting magnets – a Torus and a Solenoid. The specifications required maximum space for the detectors which led to the choice of conduction cooling for each magnet. The Torus consists of 6 trapezoidal 'race-track'-type coils connected in series with an operating current of 3770 A. The Solenoid is an actively shielded 5 Tesla magnet consisting of 5 coils connected in series operating at 2416 A. Within the hall the two magnets are located in close proximity to each other and are surrounded by particle detectors. We describe the philosophy behind the instrumentation selection and control design that accounts for this proximity and other challenging working conditions. We describe the choice of sensor technologies, as well as the control and data acquisition methods. The magnet power and cryogenic control sub-systems are implemented using Allen Bradley Control Logix 1756-L72 Programmable Logic Controllers. Sensor instrumentation read-backs are routed into the PLC via National Instruments cRIO hardware (Field Programmable Gate Arrays or FPGA/RT application) using Jefferson Lab designed FPGA-based multi-sensor-excitation-chassis. Configuration, monitoring, and alarm handlers for the magnet systems are provided via an Experimental Physics Instrumentation & Control System interface (EPICS). Failure Modes and Effects Analysis (FMEA) and the requirement to monitor critical parameters during operation guided the selection of instrumentation and associated hardware. The design of the quench protection and voltage tap sub-systems was driven by the anticipated level of voltages developed during a magnet quench. The primary hard-wired quench detection and protection sub-system together with the secondary PLC-based protection sub-system is also discussed. The successful commissioning and subsequent performance of these magnets demonstrates the robustness of the design and implementation approach that was adopted by the Jefferson Lab team and serves as an excellent 'How To' guide for future projects of this size and complexity.

12 GeV↗
DOE OSTI2020

Assessing atomically thin delta-doping of silicon using mid-infrared ellipsometry

Hydrogen lithography has been used to template phosphine-based surface chemistry to fabricate atomic-scale devices, a process we abbreviate as atomic precision advanced manufacturing (APAM). In this work, we use mid-infrared variable angle spectroscopic ellipsometry (IR-VASE) to characterize single-nanometer thickness phosphorus dopant layers (δ-layers) in silicon made using APAM compatible processes. A large Drude response is directly attributable to theδ-layer and can be used for nondestructive monitoring of the condition of the APAM layer when integrating additional processing steps. Furthermore, the carrier density and mobility extracted from our room temperature IR-VASE measurements are consistent with cryogenic magneto-transport measurements, showing that APAM δ-layers function at room temperature. Finally, the permittivity extracted from these measurements shows that the doping in the APAM δ-layers is so large that their low-frequency in-plane response is reminiscent of a silicide. However, there is no indication of a plasma resonance, likely due to reduced dimensionality and/or low scattering lifetime.

2D material↗
NASA NTRS1991

NSI operations center

The NASA Science Internet (NSI) Network Operations Staff is responsible for providing reliable communication connectivity for the NASA science community. As the NSI user community expands, so does the demand for greater interoperability with users and resources on other networks (e.g., NSFnet, ESnet), both nationally and internationally. Coupled with the science community's demand for greater access to other resources is the demand for more reliable communication connectivity. Recognizing this, the NASA Science Internet Project Office (NSIPO) expands its Operations activities. By January 1990, Network Operations was equipped with a telephone hotline, and its staff was expanded to six Network Operations Analysts. These six analysts provide 24-hour-a-day, 7-day-a-week coverage to assist site managers with problem determination and resolution. The NSI Operations staff monitors network circuits and their associated routers. In most instances, NSI Operations diagnoses and reports problems before users realize a problem exists. Monitoring of the NSI TCP/IP Network is currently being done with Proteon's Overview monitoring system. The Overview monitoring system displays a map of the NSI network utilizing various colors to indicate the conditions of the components being monitored. Each node or site is polled via the Simple Network Monitoring Protocol (SNMP). If a circuit goes down, Overview alerts the Network Operations staff with an audible alarm and changes the color of the component. When an alert is received, Network Operations personnel immediately verify and diagnose the problem, coordinate repair with other networking service groups, track problems, and document problem and resolution into a trouble ticket data base. NSI Operations offers the NSI science community reliable connectivity by exercising prompt assessment and resolution of network problems.

Zanley, Nancy L.↗
NASA NTRS2001

Cross Calibration of TOMS, SBUV/2 and Sciamachy Radiances from Ground Observations

Verification of a stratospheric ozone recovery remains a high priority for environmental research and policy definition. Models predict an ozone recovery at a much lower rate than the measured depletion rate observed to date. Therefore improved precision of the satellite and ground ozone observing systems are required over the long term to verify recovery. We have shown that validation of radiances is the most effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. Validation of radiances will also improve all higher level data products derived from the satellite observations. Backscatter algorithms suffer from several errors such as unrepresentative a-priori data and air mass factor corrections. Radiance comparisons employ forward models but are inherently more accurate and than inverse (retrieval) algorithms. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called "Skyrad", employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS. SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOME-2, OMI, and OMPS. Initial ground observations taken from Goddard Space Flight Center compared with radiative transfer calculations has indicated the feasibility of this method.

Hillsenrath, Ernest↗
NASA NTRS2002

Cross Calibration of TOMS, SBUV/2 and SCIAMACHY Radiances from Ground Observations

We have shown that validation of radiances is a very effective means for correcting absolute accuracy and long term drifts of backscatter type satellite measurements. This method by-passes the algorithms used for both satellite and ground based measurements which are normally used to validate and correct the satellite data. A new method for satellite validation is planned which will compliment measurements from the existing ground-based networks. This method will employ very accurate comparisons between ground based zenith sky radiances and satellite nadir radiances. These comparisons will rely heavily on the experience derived from the Shuttle SBUV (SSBUV) program which provided a reference standard of radiance measurements for SBUV/2, TOMS, and GOME. This new measurement program, called 'Skyrad', employs two well established capabilities at the Goddard Space Flight Center, 1) the SSBUV calibration facilities and 2) the radiative transfer codes used for the TOMS and SBUV/2 algorithms and their subsequent refinements. Radiative transfer calculations show that ground based zenith sky and satellite nadir backscatter ultraviolet comparisons can be made very accurately under certain viewing conditions. The Skyrad instruments (SSBUV, Brewer spectrophotometers, and possibly others) will be calibrated and maintained to a precision of a few tenths of a percent. Skyrad data will then enable long term calibration of upcoming satellite instruments such as QuickTOMS, SBUV/2s and SCIAMACHY with a high degree of precision. This technique can be further employed to monitor the performance of future instruments such as GOMEZ, OMI, and OMPS. Additional information is included in the original extended abstract.

Hilsenrath, Ernest↗
NASA NTRS2012

Onboard Sensor Data Qualification in Human-Rated Launch Vehicles

The avionics system software for human-rated launch vehicles requires an implementation approach that is robust to failures, especially the failure of sensors used to monitor vehicle conditions that might result in an abort determination. Sensor measurements provide the basis for operational decisions on human-rated launch vehicles. This data is often used to assess the health of system or subsystem components, to identify failures, and to take corrective action. An incorrect conclusion and/or response may result if the sensor itself provides faulty data, or if the data provided by the sensor has been corrupted. Operational decisions based on faulty sensor data have the potential to be catastrophic, resulting in loss of mission or loss of crew. To prevent these later situations from occurring, a Modular Architecture and Generalized Methodology for Sensor Data Qualification in Human-rated Launch Vehicles has been developed. Sensor Data Qualification (SDQ) is a set of algorithms that can be implemented in onboard flight software, and can be used to qualify data obtained from flight-critical sensors prior to the data being used by other flight software algorithms. Qualified data has been analyzed by SDQ and is determined to be a true representation of the sensed system state; that is, the sensor data is determined not to be corrupted by sensor faults or signal transmission faults. Sensor data can become corrupted by faults at any point in the signal path between the sensor and the flight computer. Qualifying the sensor data has the benefit of ensuring that erroneous data is identified and flagged before otherwise being used for operational decisions, thus increasing confidence in the response of the other flight software processes using the qualified data, and decreasing the probability of false alarms or missed detections.

Wong, Edmond↗