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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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NASA NTRS2000

STS-99 Flight Day 04 Highlights and Crew Activities Report

The primary objective of the STS-99 mission was to complete high resolution mapping of large sections of the Earth's surface using the Shuttle Radar Topography Mission (SRTM), a specially modified radar system. This radar system produced unrivaled 3-D images of the Earth's Surface. The mission was launched at 12:31 on February 11, 2000 onboard the space shuttle Endeavour. and led by Commander Kevin Kregel. The crew was Pilot Dominic L. Pudwill Gorie and Mission Specialists Janet L. Kavandi, Janice E. Voss, Mamoru Mohri from the National Space Development Agency (Japanese Space Agency), and Gerhard P. J. Thiele from DARA (German Space Agency).On the fourth day of the mission the blue team's Dominic Gorie led off the day's tape with a brief memorial to Charles Schultz, as he spoke of some of the vessels that were named for characters in Peanuts, and called to mind the Silver Snoopy, one of the highest awards NASA bestows. Janice Voss answered a couple of questions sent over the internet about a problem with a small thruster on the end of the 200 foot long mast. Mamoru Mohri talks about the EarthKam. Gerhard Thiele and Janet Kavandi describe the process of achieving the digital map of the entire world. At the end of the videotape some of the recently released views from the SRTM are shown. These include shots of the South Island of New Zealand.

Source record↗

NASA NTRS1975

Instruction manual, optical effects module electronic controller and processor, model OEMCP

The OEM-1 electronic module is discussed; it is comprised of four subsystems: the signal processing and display; the stepper motor controls; the chopper controls; and the dc-dc invertor. The OEM-1 module controls the sample wheel so that the relative transmittance of the samples can be compared to the clear aperture position. The 3-1/2 digit digital voltmeter displays the clear aperture signal level as well as the ratio of the remaining sample positions relative to the clear aperture position. The sample wheel position is decoded so that the signals and ratios can be correlated to the data. The OEM is automatically reset to the I sub o on initial turn-on and can be reset to the '0' position by actuating a front panel switch. The sample wheel can be interrupted to change samples or induce a longer integration time if desired by a front panel command. Integration times from 1 - 50 seconds are provided at the front panel, and BCD data for external interfacing is provided.

Source record↗

NASA NTRS1995

Making intelligent systems team players. A guide to developing intelligent monitoring systems

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Land, Sherry A.↗

NASA NTRS2010

Establishing a Robotic, LEO-to-GEO Satellite Servicing Infrastructure as an Economic Foundation for Exploration

The strategy for accomplishing civilian exploration goals and objectives is in the process of a fundamental shift towards a potential new approach called Flexible Path. This paper suggests that a government-industry or public-private partnership in the commercial development of low Earth orbit to geostationary orbit (LEO-to-GEO (LTG)) space, following or in parallel with the commercialization of Earth-to-LEO and International Space Station (ISS) operations, could serve as a necessary, logical step that can be incorporated into the flexible path approach. A LTG satellite-servicing infrastructure and architecture concept is discussed within this new strategic context. The concept consists of a space harbor that serves as a transport facility for a fleet of specialized, fully- or semi-autonomous robotic servicing spacecraft. The baseline, conceptual system architecture is composed of a space harbor equipped with specialized servicer spacecraft; a satellite command, communication, and control system; a parts station; a fuel station or depot; and a fuel/parts replenishment transport. The commercial servicer fleet would consist of several types of spacecraft, each designed with specialized robotic manipulation subsystems to provide services such as refueling, upgrade, repair, inspection, relocation, and removal. The space harbor is conceptualized as an ISS-type, octagonal truss structure equipped with radiation tolerant subsystems. This space harbor would be primarily capable of serving as an operational platform for various commercially owned and operated servicer spacecraft positioned and docked symmetrically on four of the eight sides. Several aspects of this concept are discussed, such as: system-level feasibility in terms of ISS-truss-type infrastructure and subsystems emplacement and maintenance between LEO and GEO; infrastructure components assembly in LEO, derived from ISS assembly experience, and transfer to various higher orbital locations; the evolving Earth-to-orbit (ETO) capability to deliver humans and cargo to LEO for assembly purposes; system architectural definition, optimal orbital parameters, mass estimations, delta velocity ( V) estimations, power and propulsion options, and assessments of various critical technologies. Large-scale, robotic, LTG satellite servicing is considered as an essential economic pre-condition and next parallel or sequential step on the road toward exploration beyond LEO. Such a step might produce the necessary pre-requisite economic value that can be used by future decision makers to justify further investment in exploration beyond LEO.

Horsham, Gary A. P.↗

NASA NTRS2016

The Geostationary Operational Satellite R Series SpaceWire Based Data System

The Geostationary Operational Environmental Satellite R-Series Program (GOES-R, S, T, and U) mission is a joint program between National Oceanic & Atmospheric Administration (NOAA) and National Aeronautics & Space Administration (NASA) Goddard Space Flight Center (GSFC). SpaceWire was selected as the science data bus as well as command and telemetry for the GOES instruments. GOES-R, S, T, and U spacecraft have a mission data loss requirement for all data transfers between the instruments and spacecraft requiring error detection and correction at the packet level. The GOES-R Reliable Data Delivery Protocol (GRDDP) [1] was developed in house to provide a means of reliably delivering data among various on board sources and sinks. The GRDDP was presented to and accepted by the European Cooperation for Space Standardization (ECSS) and is part of the ECSS Protocol Identification Standard [2]. GOES-R development and integration is complete and the observatory is scheduled for launch November 2016. Now that instrument to spacecraft integration is complete, GOES-R Project reviewed lessons learned to determine how the GRDDP could be revised to improve the integration process. Based on knowledge gained during the instrument to spacecraft integration process the following is presented to help potential GRDDP users improve their system designs and implementation.

Networks↗

NASA NTRS1986

Mission adaptive wing soars at NASA Facility

Research pilots have flown the Mission Adaptive Wing (MAW) aircraft, a highly modified F-111 jet fighter, from subsonic speeds up to Mach 1.4 in initial flight tests. The inital test flights are clearing the envelope with the wings flexed at various curvatures. This process allows further research data to be safely gathered so that designers of future variable camber wing aircraft have the best information possible. The altitude envelope was cleared from 27,500 down to 7,500 feet where denser air can cause more stress on the aircraft. Testing with the aircraft was conducted with wing sweep angles of 26 and 58 degrees. At the conclusion of the performance tests in the manual configuration, the system will be reconfigured for automatic mode tests. The limited automatic modes include maneuver camber control where the wings are deflected automatically to the best lift versus drag combination for a particular speed; cruise camber control which can help protect the aircraft from high G stresses; and maneuver enhancement/gust alleviation which is designed to improve the aircraft's up and down movement response to pilot commands and reduce the aircraft response to turbulence.

Rahn, D.↗

NASA NTRS2019

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗

NASA NTRS1991

Giotto Extended Mission (GEM)

The primary objectives of the Giotto Extended Mission (GEM), are to determine the composition and physical state of the Grigg Skjellerup Comet's nucleus; to determine the processes that govern the composition and distribution of neutral and ionized species in the cometary atmosphere. Giotto consists of a single European Space Agency (ESA) spacecraft that was launched in 1985 from Center Spatial Guyanis in French Guiana on an Ariane launch vehicle. After a successful launch into geostationary orbit and a heliocentric transfer trajectory, the spacecraft successfully encountered Halley's Comet in 1986. One month after encountering Halley's Comet, Mar. 1986, the spacecraft was placed in hibernation in a heliocentric orbit slightly less than 1 AU. Between Feb. and Jul. 1990 the spacecraft was successfully reactivated, checked out, and placed on a trajectory course to intercept comet Grigg Skjellerup. The spacecraft has been in hibernation since Jul. 1990. Information is presented in tabular form in the following areas: coverage goals, Deep Space Network Support, frequency assignments, telemetry, command, and tracking support responsibility.

Wilkins, D. E. B.↗

NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗

NASA NTRS2018

SpaceWire as a Cube-Sat Instrument Interface

SpaceWire is used in the control and data interface for an instrument on a pair of small satellites, one of which was launched in summer 2017. The instrument SpaceWire interface is implemented in a Field Programmable Gate Array as an instantiated core controlled by a LEON3FT CPU, which is also implemented as an instantiated core. The UT699 processor in the flight computer provides the spacecraft side’s SpaceWire interface. A simple message based protocol consisting of four message types was defined, based on existing SpaceWire standards. One was for passing commands to and responses from the instrument in the form of text strings similar to those from a system console where each line of text is passed in a SpaceWire message. Another was for passing spacecraft time to the instrument. The third was for transferring files using a subset of the Remote Memory Access Protocol (RMAP). The fourth was for retrieving science data from the instrument. A set of user application programming interface (API) routines provided an abstracted interface to both the serial console (used during debug) and the SpaceWire device interface. Early instrument development and testing was done with a set of utilities that controlled a Star-Dundee USB-SpaceWire brick providing a user interface similar to a serial console terminal emulator with the addition of file and data transfers. Later in the integration and test process, these utilities were integrated with the COSMOS ground systems software used for spacecraft control, providing a seamless transition from standalone instrument tests to benchtop flat-sat test and full spacecraft level tests.

Lux, James P.↗

NASA NTRS1993

Driving a car with custom-designed fuzzy inferencing VLSI chips and boards

Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human-like reasoning schemes which may include as little as six elemental behaviors embodied in fourteen qualitative rules.

Pin, Francois G.↗

NASA NTRS1998

Aerothermal Effects of Cavities and Protuberances for High-Speed Sample Return Capsules

Extraterrestrial sample return is a growing component of solar system exploration. Currently, four missions, Stardust, 1 Muses-C, 2 Genesis, and Mars Sample Return, are under development that employ sample return as a prime component of the mission architecture. Respectively, these missions will return samples from the tail of a comet, an asteroid, the solar wind, and, Mars. An important component of these missions and the focus of this paper is the design of the sample return capsule (SRC). The purpose of the SRC is to safely return to Earth any gathered samples for terrestrial analysis. The two major design constraints for any SRC are as follows: 1) it must be able to survive a high-speed Earth entry (11 km/s to as a high as 15 km/s), 2) the mass of the SRC must be as small as possible. Because the SRC mass is carried from Earth to the sample sight and back, the SRC mass is a strong driver in the mission mass budget. Further, for the Mars Sample Return Capsule, planetary protection is another constraint. For this capsule, the probability of planetary contamination at Earth due to an SRC failure at entry must be minimal. For an SRC, a possible failure mechanism is severe local heating as a result of cavities and or protuberances in the SRC forebody heatshield. For example, the Apollo Command Module had a number of cavities and protuberances as part of the baseline designs Wind-tunnel tests of models containing small cavities and protuberances showed severe local heating augmentations in the vicinity of these surface discontinuities.4-5 As another example, the Genesis SRC forebody heat-shield contains penetrations (cavities) to mount the vehicle to the carrier bus. It is expected that these penetrations will also experience a severe local heating environment. A concern is that the large thermal gradients may produce sufficient thermal stress to cause local mechanical failure of the heatshield. Penetrations to the forebody heat-shield can also result from damage at vehicle integration, during launch, or during transportation of the sample return capsule from earth to the sample site and back. For example, the Starting SRC was damaged near the shoulder during the heatshield integration process producing a local surface discontinuity. Also, the Starting SRC traverses through the tail of a comet and is in space for 7 years. Thus, damage to the heatshield as a result of micrometeroid impact is a concern. Finally, it is difficult to characterize the effects of these potential heatshield singularities with ground-test facilities. Either detailed simulation or a dedicated flight test is required.

Olynick, David↗

NASA NTRS2010

The NASA MLAS Flight Demonstration - A Review of a Highly Successful Test

NASA has tested the Max Launch Abort System (MLAS) as a risk-mitigation design should problems arise with the baseline Orion spacecraft launch abort design. The Max in MLAS is not Maximum, but rather dedicated to Max Faget, The renowned NASA Spacecraft designer. In the fall of 2009, the mission was flown, with great success, from the NASA Wallops Flight Facility. The MLAS flight test vehicle prototype consists of a boost ring, coast ring, and the MLAS fairing itself, which houses an Orion Command Module (CM) boilerplate. The objective of the MLAS flight test is to reorient the fairing with the CM, weighing approximately 29,000 lbs and traveling 290 fps, 180 degrees to an orientation suitable for the release of the CM during a pad abort and low altitude abort. Although multiple parachute deployments are used in the MLAS flight test vehicle to complete its objective, there are only two parachute types employed in the flight test. Five of the nine parachutes used for MLAS are 27.6 ft DO ribbon parachutes, and the remaining four are standard G-12 cargo parachutes. This paper presents an overview of the 27.6 ft DO ribbon parachute system employed on the MLAS flight test vehicle for coast ring separation, fairing reorientation, and as drogue parachutes for the CM after separation from the fairing. Discussion will include: the process used to select this design, previously proven as a spin/stall recovery parachute; descriptions of all components of the parachute system; the minor modifications necessary to adapt the parachute to the MLAS program; the techniques used to analyze the parachute for the multiple roles it performs; a discussion of the rigging techniques used to interface the parachute system to the vehicle; a brief description of how the evolution of the program affected parachute usage and analysis; and a summary of the results of the flight test, including video of the flight test and subsequent summary analysis. . A discussion of the flight test which was highly successful as well as the flight test observations will be a significant portion of the review.

Taylor, Anthony P.↗

NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

NASA NTRS1998

Grid Generation Techniques Utilizing the Volume Grid Manipulator

This paper presents grid generation techniques available in the Volume Grid Manipulation (VGM) code. The VGM code is designed to manipulate existing line, surface and volume grids to improve the quality of the data. It embodies an easy to read rich language of commands that enables such alterations as topology changes, grid adaption and smoothing. Additionally, the VGM code can be used to construct simplified straight lines, splines, and conic sections which are common curves used in the generation and manipulation of points, lines, surfaces and volumes (i.e., grid data). These simple geometric curves are essential in the construction of domain discretizations for computational fluid dynamic simulations. By comparison to previously established methods of generating these curves interactively, the VGM code provides control of slope continuity and grid point-to-point stretchings as well as quick changes in the controlling parameters. The VGM code offers the capability to couple the generation of these geometries with an extensive manipulation methodology in a scripting language. The scripting language allows parametric studies of a vehicle geometry to be efficiently performed to evaluate favorable trends in the design process. As examples of the powerful capabilities of the VGM code, a wake flow field domain will be appended to an existing X33 Venturestar volume grid; negative volumes resulting from grid expansions to enable flow field capture on a simple geometry, will be corrected; and geometrical changes to a vehicle component of the X33 Venturestar will be shown.

Alter, Stephen J.↗

NASA NTRS1994

Beware of agents when flying aircraft: Basic principles behind a generic methodology for the evaluation and certification of advanced aviation systems

There is currently a growing interest in the aeronautical community to assess the effects of the increasing levels of automation on pilots' performance and overall safety. The first effect of automation is the change in the nature of the pilot's role on the flight deck. Pilots have become supervisors who monitor aircraft systems in usual situations and intervene only when unanticipated events occur. Instead of 'hand flying' the airplane, pilots contribute to the control of aircraft by acting as mediators, instructions given to the automation. By eliminating the need for manually controlling normal situations, such a role division has reduced the opportunities for the pilot to acquire experience and skills necessary to safely cope with abnormal events. Difficulties in assessing the state and behavior of automation arise mainly from four factors: (1) the complexity of current systems and consequence mode-related problems; (2) the intrinsic autonomy of automation which is able to fire mode transitions without explicit commands from the pilots; (3) the bad quality of feed-back from the control systems displays and interfaces to the pilots; and (4) the fact that the automation currently has no explicit representation of the current pilots' intentions and strategy. Assuming certification has among its major goals to guarantee the passengers' and pilots' safety and the airplane integrity under normal and abnormal operational conditions, the authors suggest it would be particularly fruitful to come up with a conceptual reference system providing the certification authorities both with a theoretical framework and a list of principles usable for assessing the quality of the equipment and designs under examination. This is precisely the scope of this paper. However, the authors recognize that the conceptual presented is still under development and would thus be best considered as a source of reflection for the design, evaluation and certification processes of advanced aviation technologies.

Javaux, Denis↗

NASA NTRS2012

Information Systems Coordinate Emergency Management

The rescue crews have been searching for the woman for nearly a week. Hurricane Katrina devastated Hancock County, the southernmost point in Mississippi, and the woman had stayed through the storm in her beach house. There is little hope of finding her alive; the search teams know she is gone because the house is gone. Late at night in the art classroom of the school that is serving as the county s emergency operations center, Craig Harvey is discussing the search with the center s commander. Harvey is the Chief Operating Officer of a unique company called NVision Solutions Inc., based at NASA s Stennis Space Center in Bay St. Louis, only a couple of miles away. He and his entire staff have set up a volunteer operation in the art room, supporting the emergency management efforts using technology and capabilities the company developed through its NASA partnerships. As he talks to the commander, Harvey feels an idea taking shape that might lead them to the woman s location. Working with surface elevation data and hydrological principles, Harvey creates a map showing how the floodwaters from the storm would have flowed along the topography of the region around the woman s former home. Using the map, search crews find the woman s body in 15 minutes. Recovering individuals who have been lost is a sad reality of emergency management in the wake of a disaster like Hurricane Katrina in 2005. But the sooner answers can be provided, the sooner a community s overall recovery can take place. When damage is extensive, resources are scattered, and people are in dire need of food, shelter, and medical assistance, the speed and efficiency of emergency operations can be the key to limiting the impact of a disaster and speeding the process of recovery. And a key to quick and effective emergency planning and response is geographic information. With a host of Earth-observing satellites orbiting the globe at all times, NASA generates an unmatched wealth of data about our ever-changing planet. This information can be captured, analyzed, and visualized by geographic information systems (GIS) to produce maps, charts, and other tools that can reveal information essential to a wide variety of applications including emergency management. Knowing precise, real-time information about the size, location, environmental conditions, and resulting damage of an event like a flood or wildfire as well as the location and numbers of emergency responders and other resources contributes directly to the effectiveness of disaster mitigation. The need for such information is also evident when responding to homeland security threats, such as a terrorist attack. Recognizing the value of its geospatial information resources for this and other purposes, in 1998 Stennis and the state of Mississippi partnered to form what became the Enterprise for Innovative Geospatial Solutions (EIGS) industry cluster, supporting the growth of remote sensing and GIS-based research and business. As part of EIGS, several companies partnered with NASA through dual use and Small Business Innovation Research (SBIR) contracts. Among those was NVision.

Source record↗

NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗