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NASA NTRSDate not supplied

Material Response Analysis of PICA-NuSil at the Hypersonic Materials Environmental Test System

Phenolic impregnated carbon ablator (PICA) is a thermal protection system (TPS) that gained heritage during the Stardust mission and is the baseline TPS material for expeditions to Mars (e.g., Mars Science Laboratory and Mars 2020).1 PICA is friable; therefore, a polysiloxane resin (NuSil CV-1144-0) is deposited onto the surface of flight hardware before assembly, test, and launch operations (ATLO) to mitigate particle shedding. Furthermore, the Mars Science Laboratory (MSL) and Mars 2020 heatshields were instrumented with an array of thermocouple plugs (MEDLI Integrated Sensor Plugs or MISP) designed to measure the in-depth thermal response of PICA during flight. Post-flight analysis of MISP data suggests that recession was lower than predicted, and NuSil is suspected as a reasonable cause. NuSil primarily consists of a copolymer blend of dimethyl and diphenyl-substituted polysiloxane resin. Four decades of research in the field of polymer-derived ceramics demonstrate that polysiloxane resins form oxidation-resistant silicon oxycarbide materials at pyrolysis temperatures as low as 800 °C. -2 Furthermore, silicon oxycarbide materials exhibit excellent thermal stability at relatively high-temperatures (< 1200 °C) but eventually decompose via carbothermal reduction. -3 Therefore, it is reasonable to suggest that NuSil forms an oxidation-resistant thermal barrier coating on the TPS surface and influences the material response during atmospheric entry. Evidence for this notion was observed during prior arc-jet testing at both the Aerodynamic Heating Facility (AHF) and the Panel Test Facility (PTF) at the NASA Ames Research Center. Articles of PICA were subjected to testing in airflow, and a temperature discontinuity was recorded at the surface of coupons coated with NuSil. A glassy coating was observed to form at the surface in shear flow configurations (wedge and panel) under moderate heat fluxes. Furthermore, state-of-the-art material response models have yet to account for the underlying physics and chemistry of the temperature discontinuity. To this end, a pathfinder test campaign was executed at the Hypersonic Materials Environmental Test System (HyMETS) to enhance the fundamental understanding of PICA-NuSil ablation phenomena and provide a preliminary data set to aid in the development of material response models.

PICA↗

NASA NTRS2010

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗

NASA NTRS2005

Autonomous Assembly of Modular Structures in Space and on Extraterrestrial Locations

The fulfillment of the new US. National Vision for Space Exploration requires many new enabling technologies to accomplish the goal of utilizing space for commercial activities and for returning humans to the moon and extraterrestrial environments. Traditionally, flight structures are manufactured as complete systems and require humans to complete the integration and assembly in orbit. These structures are bulky and require the use of heavy launch vehicles to send the units to the desired location, e.g. International Space Station (ISS). This method requires a high degree of safety, numerous space walks and significant cost for the humans to perform the assembly in orbit. For example, for assembly and maintenance of the ISS, 52 Extravehicular Activities (EVA's) have been performed so far with a total EVA time of approximately 322 hours. Sixteen (16) shuttle flights haw been to the ISS to perform these activities with an approximate cost of $450M per mission. For future space missions, costs have to be reduced to reasonably achieve the exploration goals. One concept that has been proposed is the autonomous assembly of space structures. This concept is an affordable, reliable solution to in-space and extraterrestrial assembly operations. Assembly is autonomously performed when two components containing onboard electronics join after recognizing that the joint is appropriate and in the precise position and orientation required for assembly. The mechanism only activates when the specifications are correct and m a nominal range. After assembly, local sensors and electronics monitor the integrity of the joint for feedback to a master controller. To achieve this concept will require a shift in the methods for designing space structures. In addition, innovative techniques will be required to perform the assembly autonomously. Monitoring of the assembled joint will be necessary for safety and structural integrity. If a very large structure is to be assembled in orbit, then the number of integrity sensors will be significant. Thus simple, low cost sensors are integral to the success of this concept. This paper will address these issues and will propose a novel concept for assembling space structures autonomously. The paper will present Several autonomous assembly methods. Core technologies required to achieve in space assembly will be discussed and novel techniques for communicating, sensing, docking and assembly will be detailed. These core technologies are critical to the goal of utilizing space in a cost efficient and safe manner. Finally, these technologies can also be applied to other systems both on earth and extraterrestrial environments.

Alhorn, Dean C.↗

NASA NTRSDate not supplied

Lunar Search & Rescue Applications of Lunar GNSS

Accurate lunar navigation and timing knowledge provides for the development of safety-critical services in the cislunar and lunar surface domain. Currently under development, the Goddard Space Flight Center’s (GSFC) Search and Rescue Mission Office is investigating and integrating search and rescue (SAR) capability into planned and future lunar communication and navigation interfaces. Lunar Search and Rescue (LunaSAR) development has a stated end-goal for assured, reliable, and timely indication of distress events for a wide variety of lunar surface users, including government-sponsored, commercial, and international users. LunaSAR performance requirements are modelled after the current terrestrial Cospas-Sarsat distress notification system, leveraging an internationally robust global navigation satellite system (GNSS) ecosystem as a core element of survivor locating capability. This presentation will discuss NASA’s work to develop user-focused distress messaging capabilities including infusion of example sensor data for triggering of automated distress alerts coupled with location-tagging. Additionally, the presentation will examine overall message structures, rotating fields for use in bi-directional distress messaging, and specific use cases based on NASA’s lunar exploration and lunar communication relay architectures. Modelling and simulation of LunaSAR use by individual lunar explorers will be discussed, based on notional industry and government design reference missions and mission considerations. Results from GSFC-funded Internal Research and Development (IRAD) efforts will be detailed, including successful distress message formulation simulating the ingestion of example legacy space suit telemetry fields. Hardware-in-the-loop testing using high-reliability software defined radio (SDR) modules serve as an example of IRAD successes and the framework for technical requirements. Architectural development and technical evolution from 2020 to 2021 included alignment of LunaSAR distress waveforms with ongoing NASA LunaNet interoperability development, as well as engagement with NASA Lunar Spectrum authorities for allocation of UHF-band distress frequencies on the lunar surface. S-Band and UHF-band transmission characteristics will be detailed, along with band-specific applications of each emission type. Additionally, examples of ingestion and formatting of GNSS signals (using historical terrestrial National Marine Electronics Association-formatted GNSS data) will be detailed, underscoring lunar user needs for a common lunar GNSS receiver output message framework. Maturity and ability to support evolving lunar exploration goals has been demonstrated and will be detailed, with maturity gaps such as position, navigation, and timing (PNT) and lunar reference frames identified within the context of distress message generation. Provision of LunaSAR services for lunar surface users represents a new era of ensured safety for lunar explorers and builds off of forty years of the Cospas-Sarsat program, underscoring the importance of lunar GNSS for safety-critical applications and growing interest in safe, reliable lunar surface operations. Enabled by new GNSS systems being developed by government and industry partners, NASA will continue to evolve and integrate lunar GNSS types into distress message generation, with a focus on compact and efficient message transmission over various lunar communication links. When fielded, LunaSAR will be the first dedicated search and rescue notification system employed on another celestial body. Robust lunar navigation and timing services form the core of LunaSAR capabilities, allowing for system syncing with time-dominant sensors, and high-accuracy location of those in distress while engaged in lunar surface activities.

Search and Rescue↗

NASA NTRS2007

Emphasizing Spectrum Management for Sustainable Development Research and Applications in Disaster Management

NASA's spaceborne Earth and Heliospheric Observatories and airborne sensors provide a plethora of measurements. These measurements are used in science research to understand the climatology of our home planet and the solar fluxes and cycle of the only star in our solar system 'Sun' which is critical driver for the retention of life on Earth. Specifically, these measurements help us to understand the water and energy cycle, the carbon cycle, weather and climate, atmospheric chemistry, solar variability, and solid Earth and interior to feed into sophisticated mathematical models to analyze and predict the Earth's behavior as an integrated system. The main thrust of this research is on improving the prediction capability in the areas of weather, long term climate and solid Earth processes, and further help the humanity and future generations in terms of societal benefits in managing natural disasters, sustainability issues and many more. This work is further linked with our contributions in the Global Earth Observing System of Systems (GEOSS) Specifically, the data and knowledge resulting from the Earth observing systems and analytical models of the Earth can be made available for assimilation into decision support systems to serve society for disaster management. Through partnerships with national and international agencies and organizations, NASA's Science Mission Directorate's, Applied Sciences Program contributes to benchmarking practical uses of observations and predictions from Earth science remote sensing systems research. The objective is to establish innovative solutions using Earth observations and science information to provide decision support that can be adapted in applications of national and international priority. We along with the international community will continue this critical field of investigation by using our existing and future sensors from space, airborne and insitue environment. In our quest to expanding our knowledge, there will be a need for deploying additional sensors to obtain high spatial, temporal and spectral resolution measurements. These sensors operate in multiple spectral band ranging from UV, visible, infrared, microwave and radio frequency ranges. Of a particular concern is the microwave frequency bands which play a key role in land, ocean, moisture sensing. This is because of a growing commercial demand in the area of high speed broadband communication all over the world, the electronic manufacturers are looking into high frequency microwave spectral bands. This may present a risk to the remote sensing sensors because of additional sources of noise that can impair the highly sensitive passive remote sensing instruments.

Ambrose, Stephen↗

NASA NTRS2006

Sensor to User - NASA/EOS Data for Coastal Zone Management Applications Developed from Integrated Analyses: Verification, Validation and Benchmark Report

The NASA Applied Sciences Program seeks to transfer NASA data, models, and knowledge into the hands of end-users by forming links with partner agencies and associated decision support tools (DSTs). Through the NASA REASoN (Research, Education and Applications Solutions Network) Cooperative Agreement, the Oceanography Division of the Naval Research Laboratory (NRLSSC) is developing new products through the integration of data from NASA Earth-Sun System assets with coastal ocean forecast models and other available data to enhance coastal management in the Gulf of Mexico. The recipient federal agency for this research effort is the National Oceanic and Atmospheric Administration (NOAA). The contents of this report detail the effort to further the goals of the NASA Applied Sciences Program by demonstrating the use of NASA satellite products combined with data-assimilating ocean models to provide near real-time information to maritime users and coastal managers of the Gulf of Mexico. This effort provides new and improved capabilities for monitoring, assessing, and predicting the coastal environment. Coastal managers can exploit these capabilities through enhanced DSTs at federal, state and local agencies. The project addresses three major issues facing coastal managers: 1) Harmful Algal Blooms (HABs); 2) hypoxia; and 3) freshwater fluxes to the coastal ocean. A suite of ocean products capable of describing Ocean Weather is assembled on a daily basis as the foundation for this semi-operational multiyear effort. This continuous realtime capability brings decision makers a new ability to monitor both normal and anomalous coastal ocean conditions with a steady flow of satellite and ocean model conditions. Furthermore, as the baseline data sets are used more extensively and the customer list increased, customer feedback is obtained and additional customized products are developed and provided to decision makers. Continual customer feedback and response with new improved products are required between the researcher and customer. This document details the methods by which these coastal ocean products are produced including the data flow, distribution, and verification. Product applications and the degree to which these products are used successfully within NOAA and coordinated with the Mississippi Department of Marine Resources (MDMR) is benchmarked.

Hall, Callie↗

NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

NASA NTRS1990

X-wing fly-by-wire vehicle management system

A complete, computer based, vehicle management system (VMS) for X-Wing aircraft using digital fly-by-wire technology controlling many subsystems and providing functions beyond the classical aircraft flight control system. The vehicle management system receives input signals from a multiplicity of sensors and provides commands to a large number of actuators controlling many subsystems. The VMS includes--segregating flight critical and mission critical factors and providing a greater level of back-up or redundancy for the former; centralizing the computation of functions utilized by several subsystems (e.g. air data, rotor speed, etc.); integrating the control of the flight control functions, the compressor control, the rotor conversion control, vibration alleviation by higher harmonic control, engine power anticipation and self-test, all in the same flight control computer (FCC) hardware units. The VMS uses equivalent redundancy techniques to attain quadruple equivalency levels; includes alternate modes of operation and recovery means to back-up any functions which fail; and uses back-up control software for software redundancy.

Fischer, Jr., William C.↗

NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under off-nominal conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace, demands the need of robust risk monitoring framework for assessing the safety of airspace, ground-structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV's predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV's trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Portia Banerjee↗

NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under Off-nominal Conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace demands the need of robust risk monitoring framework for assessing the safety of airspace, ground structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV’s predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV’s trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Bayesian network↗

NASA NTRS2021

Comparisons of IMERG Version 06 Precipitation at and between Passive Microwave Overpasses in the Tropics

The Integrated Multisatellite Retrievals for Global Precipitation Measurement Mission (IMERG) is a global precipitation product that uses precipitation retrievals from the virtual constellation of satellites with passive microwave (PMW) sensors, as available. In the absence of PMW observations, IMERG uses a Kalman filter scheme to morph precipitation from one PMW observation to the next. In this study, an analysis of convective systems observed during the Convective Process Experiment (CPEX) suggests that IMERG precipitation depends more strongly on the availability of PMW observations than previously suspected. Following this evidence, we explore systematic biases in IMERG through bulk statistics. In two CPEX case studies, cloud photographs, pilot’s radar, and infrared imagery suggest that IMERG represents the spatial extent of precipitation relatively well when there is a PMW observation but sometimes produces spurious precipitation areas in the absence of PMW observations. Also, considering an observed convective system as a precipitation object in IMERG, the maximum rain rate peaked during PMW overpasses, with lower values between them. Bulk statistics reveal that these biases occur throughout IMERG Version 06. We find that locations and times without PMW observations have a higher frequency of light precipitation rates and a lower frequency of heavy precipitation rates due to retrieval artifacts. These results reveal deficiencies in the IMERG Kalman filter scheme, which have led to the development of the Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood (SHARPEN; described in a companion paper) that will be applied in the next version of IMERG.

Manikandan Rajagopal↗

NASA NTRSDate not supplied

Dissemination of Global Flood Severity and Surface Water Mapping using Remote Sensing Data to Global Stakeholders

Flooding is a natural event that occurs frequently with high severity worldwide, responsible for significant societal and economic impacts. Disaster managers face significant challenges managing essential information for preparedness, response, and recovery efforts. The development of an open access, global flood alerting system for effective identification of flood impacted areas, classification of potential impacts, and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood models and remote sensing data sources from multiple platforms. NASA is currently funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity estimation using Earth observation (EO) datasets and derived flood products. A new initiative in the Disasters Program is underway to disseminate flood products from different hydrologic models and sensors to global stakeholders via Pacific Disaster Center’s DisasterAWARE®, NASA’s Disasters Mapping Portal and potentially other mechanisms. This initiative focuses on improving response capacity and use of EO products in near real-time by a broader community for resource planning in case of extreme events. As part of this initiative, we have deployed Model of Models (MoM) – an open-source ensemble approach, that integrates outputs from hydrologic models and EO data from optical imagery to assess flood severity daily at sub-watershed level globally. The MoM output is integrated with the incident event system of DisasterAWARE to generate flood severity risk and flood impact boundaries, which are disseminated via the DisasterAWARE platform to different stakeholders globally for decision-making and response efforts. The next step will focus on using MoM outputs to estimate flood depth and extent mapping using high-resolution Synthetic Aperture Radar imagery, impact assessment using optical imagery and population datasets, and damage estimation using critical infrastructure datasets, which would be disseminated via DisasterAWARE to decision-makers, emergency managers and first responders around the world.

flood↗

NASA NTRS1977

Flight-control/navigation inertial reference system

The preliminary design of a redundant strapdown navigation system for integrated flight-control/navigation use has been completed. Based on application of tuned-gimbal gyros, a compact configuration (13 in x 13 in x 14 in) has been achieved for fail-operational/fail-operational redundancy. Test data are presented for strapdown system test programs including flight testing of the LN-50 tuned-gimbal gyro system. Testing of a redundant sensor configuration is currently in process. Strapdown gyro development also includes ring laser and nuclear magnetic resonance techniques.

Ebner, R. E.↗

NASA NTRS1982

Inversion of data from diffraction-limited multiwavelength remote sensors. II - Nonlinear dependence of observables on the geophysical parameters

Linear shift-invariant spatial filtering is applied to inversion of radiometric measurements of the earth in both polarizations at the following frequencies: 6.6, 10.7, 18, 21, and 37 GHz. For purposes of radiative transfer calculations at these frequencies, the state of the ocean-atmosphere system is described by a seven-parameter model. The parameters are near-surface wind speed, sea surface temperature, integrated water vapor mass, scale height of water vapor in an exponential distribution, integrated liquid water mass, height of the liquid water, and characteristic drop radius in a Best (1950) drop size distribution. Also described is a spatial filtering algorithm by means of which geophysical parameters are retrieved from measurements made over the ocean by the scanning multichannel microwave radiometer on the Nimbus 7 satellite. The parameters here are near-surface wind speed, sea surface temperature, rain rate, integrated atmospheric water vapor content, and integrated liquid water content (including rain).

Rosenkranz, P. W.↗

NASA NTRS1984

Radiometric calibration and processing procedure for reflective bands on LANDSAT-4 protoflight Thematic Mapper

The radiometric subsystem of NASA's LANDSAT-4 Thematic Mapper (TM) sensor is described. Special emphasis is placed on the internal calibrator (IC) pulse shapes and timing cycle. The procedures for the absolute radiometric calibration of the TM channels with a 122-centimeter integrating sphere and the transfer of radiometric calibration from the channels to the IC are reviewed. The use of the IC to calibrate TM data in the ground processing system consists of pulse integration, pulse averaging, IC state identification, linear regression analysis, and histogram equalization. An overview of the SCROUNGE-era (before August 1983) method is presented. Procedural differences between SCROUNGE and the TIPS-era (after July 1983) and the implications of these differences are discussed.

Barker, J. L.↗

NASA NTRS1987

Flight test of a digital controller used in a helicopter autoland system

This paper describes the flight test evaluation of an advanced digital helicopter flight control system. The controller was designed using an optimal control design procedure for a fully coupled lateral and longitudinal vehicle model. Explicit integrals of the guidance error were included to produce a type 1 characteristic. Gain scheduling was used to account for changes in the vehicle dynamics. The digital controller was exercised by combining it with state estimators, a trajectory generator, and a closed-loop guidance algorithm to form a helicopter autoland system. A CH-47 tandem rotor helicopter was equipped with sensors, on-board digital flight computers, and electrohydraulic actuators. The system was exercised by automatically flying straight-in descending decelerating trajectories typcial of VFR manual landing approaches. A description of the test-ground facilities, the flight hardware and software, and the velocity and position tracking performance is included.

Downing, David R.↗

NASA NTRS1988

Telerobotics for the efficient utilization of space

Telerobotics is a new technology that is being developed to perform remote manipulation in space. It seeks to accommodate the needs arising from a rapidly increasing investment in space assets and from the large costs deriving from human operations in space, especially EVA. Telerobotics applies advanced automation and artificial intelligence technology and combines the immediacy of execution of teleoperation (the replication at a distance of the physical motions of the operator) with the efficiency and precision of supervised robotic autonomy (the accomplishment of assignments through machine task decomposition and interpretation of sensor information). One of the key goals of this approach is the achievement of a seamless transition between teleoperation and supervised autonomy. The basis of this technology and of the NASA telerobotics research and development activities are described. They consist of five elements: core research, laboratory integration testbed, mission analysis, application demonstrations and flight experiments. Current advances, both in research and system integration are reported including the first integration of the laboratory testbed and quantitative comparisons obtained in a buoyant facility. Planned future goals are outlined.

Varsi, Giulio↗

NASA NTRS2005

Autonomous Assembly of Modular Structures in Space and on Extraterrestrial Locations

The new U.S. National Vision for Space Exploration requires many new enabling technologies to accomplish the goals of space commercialization and returning humans to the moon and extraterrestrial environments. Traditionally, flight elements are complete subsystems requiring humans to complete the integration and assembly. These bulky structures also require the use of heavy launch vehicles to send the units to a desired location. This philosophy necessitates a high degree of safety, numerous space walks at a significant cost. Future space mission costs must be reduced and safety increased to reasonably achieve exploration goals. One proposed concept is the autonomous assembly of space structures. This concept is an affordable, reliable solution to in-space and extraterrestrial assembly. Assembly is autonomously performed when two components join after determining that specifications are correct. Local sensors continue monitor joint integrity post assembly, which is critical for safety and structural reliability. Achieving this concept requires a change in space structure design philosophy and the development of innovative technologies to perform autonomous assembly. Assembly of large space structures will require significant numbers of integrity sensors. Thus simple, low-cost sensors are integral to the success of this concept. This paper addresses these issues and proposes a novel concept for assembling space structures autonomously. Core technologies required to achieve in space assembly are presented. These core technologies are critical to the goal of utilizing space in a cost efficient and safe manner. Additionally, these novel technologies can be applied to other systems both on earth and extraterrestrial environments.

Alhorn, Dean C.↗