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The Alignment and Phasing System for the Thirty Meter Telescope: Risk Mitigation and Status Update

Alignment and Phasing System (APS) is responsible for the optical alignment via starlight of the approximately 12,000 degrees of freedom of the primary, secondary and tertiary mirrors of Thirty Meter Telescope (TMT). APS is based on the successful Phasing Camera System (PCS) used to align the Keck Telescopes. Since the successful APS conceptual design in 2007, work has concentrated on risk mitigation, use case generation, and alignment algorithm development and improvement. Much of the risk mitigation effort has centered around development and testing of prototype APS software which will replace the current PCS software used at Keck. We present an updated APS design, example use cases and discuss, in detail, the risk mitigation efforts.

Optical Alignment

Implementation of Enhanced Propulsion Control Modes for Emergency Flight Operation

Aircraft engines can be effective actuators to help pilots avert or recover from emergency situations. Emergency control modes are being developed to enhance the engines performance to increase the probability of recovery under these circumstances. This paper discusses a proposed implementation of an architecture that requests emergency propulsion control modes, allowing the engines to deliver additional performance in emergency situations while still ensuring a specified safety level. In order to determine the appropriate level of engine performance enhancement, information regarding the current emergency scenario (including severity) and current engine health must be known. This enables the engine to operate beyond its nominal range while minimizing overall risk to the aircraft. In this architecture, the flight controller is responsible for determining the severity of the event and the level of engine risk that is acceptable, while the engine controller is responsible for delivering the desired performance within the specified risk range. A control mode selector specifies an appropriate situation-specific enhanced mode, which the engine controller then implements. The enhanced control modes described in this paper provide additional engine thrust or response capabilities through the modification of gains, limits, and the control algorithm, but increase the risk of engine failure. The modifications made to the engine controller to enable the use of the enhanced control modes are described, as are the interaction between the various subsystems and importantly, the interaction between the flight controller/pilot and the propulsion control system. Simulation results demonstrate how the system responds to requests for enhanced operation and the corresponding increase in performance.

Csank, Jeffrey T.

A New View of Radiation-Induced Cancer: Integrating Short- and Long-Term Processes. Part II: Second Cancer Risk Estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Shuryak, Igor

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

Mach, Douglas M.

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.

An Operational Algorithm for Evaluating Satellite Collision Consequence

Risk is properly considered as the combination of likelihood and consequence; but conjunction assessment has usually limited itself to the consideration of only collision likelihood. When considered from an orbital regime protection perspective, the focus shifts to the question of the amount of debris that a collision might produce (the “consequence”). The present paper presents an operational algorithm for determining the expected amount of debris production should a conjunction result in a collision, and an assessment of the algorithm’s fidelity against a database of characterized objects.

Lechtenberg, Travis

An Operational Algorithm for Evaluating Satellite Collision Consequence

Risk is properly considered as the combination of likelihood and consequence; but conjunction assessment has usually limited itself to the consideration of only collision likelihood. When considered from an orbital regime protection perspective, the focus shifts to the question of the amount of debris that a collision might produce (the “consequence”). The present paper presents an operational algorithm for determining the expected amount of debris production should a conjunction result in a collision, and an assessment of the algorithm’s fidelity against a database of characterized objects.

Lechtenberg, Travis

Simple, Scalable, Script-Based Science Processor (S4P)

The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.

Lynnes, Christopher

Geostationary Lightning Mapper for GOES-R and Beyond

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch readiness in December 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fUlly operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight models will be underway in the latter part of 2007. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) forecast offices in Southern and Eastern Region. This effort is designed to help improve our understanding of the application of these data in operational settings.

Goodman, Steven J.

MSFC Robotic Lunar Lander Testbed and Current Status of the International Lunar Network (ILN) Anchor Nodes Mission

The lunar lander robotic exploration testbed at Marshall Spaceflight Center provides a test environment for robotic lander test articles, components and algorithms to reduce the risk on the airless body designs during lunar landing. Also included is a chart comparing the two different types of Anchor nodes for the International Lunar Network (ILN): Solar/Battery and the Advanced Stirling Radioisotope generator (ARSG.)

Cohen, Barbara

The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

The next generation Geostationary Operational Environmental Satellite (GOES-R) series is a follow on to the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral (3x), spatial (4x), and temporal (5x) resolution for the Advanced Baseline Imager (ABI). The GLM, an optical transient detector and imager operating in the near-IR at 777.4 nm will map all (in-cloud and cloud-to-ground) lighting flashes continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate Day-1 user readiness for this new capability.

Goodman, Steven J.

The Geostationary Lightning Mapper (GLM) for the GOES-R Series Next Generation Operational Environmental Satellite Constellation

The next generation Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2015 is a follow on to the existing GOES system currently operating over the Western Hemisphere. The system will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. The system provides products including lightning, cloud properties, rainfall rate, volcanic ash, air quality, hurricane intensity, and fire/hot spot characterization. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral, spatial, and temporal resolution for the 16-channel Advanced Baseline Imager (ABI). The Geostationary Lightning Mapper (GLM), an optical transient detector will map total (in-cloud and cloud-to-ground) lightning flashes continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the higher level algorithms and applications using the GLM alone and decision aids incorporating information from the ABI, ground-based weather radar, and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional lightning networks are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time total lightning mapping data are also being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate early on-orbit user readiness for this new capability.

Goodman, Steven J.

The GOES-R Series Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), which will have just completed Critical Design Review and move forward into the construction phase of instrument development. The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (an engineering development unit and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms

Goodman, Steven J.

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.

The Goes-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Goodman, Steven J.

A Web-Based Negotiation Tool for Conflict Resolution in Upper Class E Traffic Management

In Upper Class E airspace 60,000 feet (or Flight level / FL600), vehicles such as High Altitude Long Endurance (HALE) balloons and slow fixed-wing gliders have diverse vehicle characteristics and limited maneuverability. Due to these unique characteristics of high-altitude operations, a new type of strategic negotiation-based conflict resolution method has been proposed to avoid potential conflict between vehicles in Upper Class E airspace, well in advance of the conflict point and with ample time for bilateral negotiation. This paper introduces the first real-time web-based negotiation tool for high-altitude operations. To facilitate negotiation, this tool incorporates a bilateral negotiation model with an algorithm to assess conflict risks and generate new flight trajectories with a given flight path deviation. This tool allows users to make decisions during negotiation manually and automatically while enforcing the needed constraints for negotiation to be successful. Operators can make decisions at every step while they interact with each other on separate devices. To conduct sensitivity analysis, a mechanism that automates human inputs to the user interface is also developed for this web-based negotiation tool, such that fast-time simulations can be constructed and used to explore various scenarios to gain insights into this web-based negotiation model. Using this tool, a study was conducted to evaluate the impact of different negotiation strategies, vehicle types, vehicle crossing angles, and operator response times during the negotiations on metrics such as total negotiation completion time, number of negotiation rounds, and extra flight distance to avoid the conflict due to negotiation, compared to ones without negotiation. The results suggest that operators benefit from using negotiated flight paths with quick response times, across various crossing angles and vehicle types. Various Negotiation Strategies are investigated to simulate the behaviors associated with different types of negotiations. The findings demonstrate that, in comparison to the conventional method where a single operator assumes full responsibility, negotiation-based strategic deconfliction reduces the total extra flight distance by an average of 24% - 27%. On an individual basis, each operator may be able to save an average of 65% of their extra flight distance.

Upper Class E Traffic Management (ETM)

UAV Path Planning for Wildfires - Sustainably Fighting Wildfires with Automated Path Planning for UAVs

As the severity and frequency of wildfires increase, infrastructure, properties, national parks, animal habitats, and human lives (civilians and firefighters) are put at greater risk. This paper examines the possible application of algorithmic path planning for UAV reconnaissance to reduce damage and safety risks, as aforementioned. When the location of a wildfire is known, UAVs are immediately dispatched from an operating base to fly to the fire and support the firefighters as quickly as possible. Then, the algorithm incrementally analyzes different environmental factors to create a path for the UAV to follow. This work focuses on generating a path for the UAV to follow given a set of polygons representing obstacles. The most important features of this algorithm are its fast response time and obstacle maneuverability. The use of an efficient path planning algorithm could potentially save lives, infrastructure, and acres of forest destruction.

UAV

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.