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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

SPARTAN: A High-Fidelity Simulation for Automated Rendezvous and Docking Applications

bd Systems (a subsidiary of SAIC) has developed the Simulation Package for Autonomous Rendezvous Test and ANalysis (SPARTAN), a high-fidelity on-orbit simulation featuring multiple six-degree-of-freedom (6DOF) vehicles. SPARTAN has been developed in a modular fashion in Matlab/Simulink to test next-generation automated rendezvous and docking guidance, navigation,and control algorithms for NASA's new Vision for Space Exploration. SPARTAN includes autonomous state-based mission manager algorithms responsible for sequencing the vehicle through various flight phases based on on-board sensor inputs and closed-loop guidance algorithms, including Lambert transfers, Clohessy-Wiltshire maneuvers, and glideslope approaches The guidance commands are implemented using an integrated translation and attitude control system to provide 6DOF control of each vehicle in the simulation. SPARTAN also includes high-fidelity representations of a variety of absolute and relative navigation sensors that maybe used for NASA missions, including radio frequency, lidar, and video-based rendezvous sensors. Proprietary navigation sensor fusion algorithms have been developed that allow the integration of these sensor measurements through an extended Kalman filter framework to create a single optimal estimate of the relative state of the vehicles. SPARTAN provides capability for Monte Carlo dispersion analysis, allowing for rigorous evaluation of the performance of the complete proposed AR&D system, including software, sensors, and mechanisms. SPARTAN also supports hardware-in-the-loop testing through conversion of the algorithms to C code using Real-Time Workshop in order to be hosted in a mission computer engineering development unit running an embedded real-time operating system. SPARTAN also contains both runtime TCP/IP socket interface and post-processing compatibility with bdStudio, a visualization tool developed by bd Systems, allowing for intuitive evaluation of simulation results. A description of the SPARTAN architecture and capabilities is provided, along with details on the models and algorithms utilized and results from representative missions.

Turbe, Michael A.↗
NASA NTRS2008

J-2X Abort System Development

The J-2X is an expendable liquid hydrogen (LH2)/liquid oxygen (LOX) gas generator cycle rocket engine that is currently being designed as the primary upper stage propulsion element for the new NASA Ares vehicle family. The J-2X engine will contain abort logic that functions as an integral component of the Ares vehicle abort system. This system is responsible for detecting and responding to conditions indicative of impending Loss of Mission (LOM), Loss of Vehicle (LOV), and/or catastrophic Loss of Crew (LOC) failure events. As an earth orbit ascent phase engine, the J-2X is a high power density propulsion element with non-negligible risk of fast propagation rate failures that can quickly lead to LOM, LOV, and/or LOC events. Aggressive reliability requirements for manned Ares missions and the risk of fast propagating J-2X failures dictate the need for on-engine abort condition monitoring and autonomous response capability as well as traditional abort agents such as the vehicle computer, flight crew, and ground control not located on the engine. This paper describes the baseline J-2X abort subsystem concept of operations, as well as the development process for this subsystem. A strategy that leverages heritage system experience and responds to an evolving engine design as well as J-2X specific test data to support abort system development is described. The utilization of performance and failure simulation models to support abort system sensor selection, failure detectability and discrimination studies, decision threshold definition, and abort system performance verification and validation is outlined. The basis for abort false positive and false negative performance constraints is described. Development challenges associated with information shortfalls in the design cycle, abort condition coverage and response assessment, engine-vehicle interface definition, and abort system performance verification and validation are also discussed.

Santi, Louis M.↗
NASA NTRS2007

Implementation of a Point Algorithm for Real-Time Convex Optimization

The primal-dual interior-point algorithm implemented in G-OPT is a relatively new and efficient way of solving convex optimization problems. Given a prescribed level of accuracy, the convergence to the optimal solution is guaranteed in a predetermined, finite number of iterations. G-OPT Version 1.0 is a flight software implementation written in C. Onboard application of the software enables autonomous, real-time guidance and control that explicitly incorporates mission constraints such as control authority (e.g. maximum thrust limits), hazard avoidance, and fuel limitations. This software can be used in planetary landing missions (Mars pinpoint landing and lunar landing), as well as in proximity operations around small celestial bodies (moons, asteroids, and comets). It also can be used in any spacecraft mission for thrust allocation in six-degrees-of-freedom control.

Acikmese, Behcet↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Trevino, Luis↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
NASA NTRS2000

Rapid Prototyping and Evaluation of Control System Designs for Manned and Unmanned Applications

The development and optimization of flight control systems for modem fixed- and rotary- wing aircraft consume significant time and cost during aircraft development. Similarly, as unmanned aerial vehicles perform more complex tasks, sometimes autonomously, the control system design requirements for this class of vehicles, and the corresponding time and cost requirements, are also becoming significant. Therefore, for both manned and unmanned vehicles, substantial program savings can be achieved if integrated design and optimization tools are employed to shorten the design and flight-test cycle for new or upgraded,pontrol systems. To bring about this reduction in the length of the design-cycle, and therefore its cost, Madab and Simulink are being used to implement block diagrams and to rapidly evaluate the expected responses of the completed systems. In conjunction, CONDUIT (CONtrol Designer's Unified InTerface) is being used to enable the controls engineers to optimize their control laws and ensure that all the relevant quantitative criteria are satisfied.

Mansur, M. Hossein↗
NASA NTRS1987

Mechanisms of selective attention and space motion sickness

The neural mismatch theory of space motion sickness asserts that the central and peripheral autonomic sequelae of discordant sensory input arise from central integrative processes falling to reconcile patterns of incoming sensory information with existing memory. Stated differently, perceived novelty reaches a stress level as integrative mechanisms fail to return a sense of control to the individual in the new environment. Based on evidence summarized here, the severity of the neural mismatch may be dependent upon the relative amount of attention selectively afforded to each sensory input competing for control of behavior. Components of the limbic system may play important roles in match-mismatch operations, be therapeutically modulated by antimotion sickness drugs, and be optimally positioned to control autonomic output.

NASA Discipline Neuroscience↗
NASA NTRS2015

Flight Testing of Guidance, Navigation and Control Systems on the Mighty Eagle Robotic Lander Testbed

During 2011 a series of progressively more challenging flight tests of the Mighty Eagle autonomous terrestrial lander testbed were conducted primarily to validate the GNC system for a proposed lunar lander. With the successful completion of this GNC validation objective the opportunity existed to utilize the Mighty Eagle as a flying testbed for a variety of technologies. In 2012 an Autonomous Rendezvous and Capture (AR&C) algorithm was implemented in flight software and demonstrated in a series of flight tests. In 2012 a hazard avoidance system was developed and flight tested on the Mighty Eagle. Additionally, GNC algorithms from Moon Express and a MEMs IMU were tested in 2012. All of the testing described herein was above and beyond the original charter for the Mighty Eagle. In addition to being an excellent testbed for a wide variety of systems the Mighty Eagle also provided a great learning opportunity for many engineers and technicians to work a flight program.

Hannan, Mike↗
NASA NTRS2012

Fast Paced, Low Cost Projects at MSFC

What does an orbiting microsatellite, a robotic lander and a ruggedized camera and telescope have in common? They are all fast paced, low cost projects managed by Marshall Space Flight Center (MSFC) teamed with successful industry partners. MSFC has long been synonymous with human space flight large propulsion programs, engineering acumen and risk intolerance. However, there is a growing portfolio/product line within MSFC that focuses on these smaller, fast paced projects. While launching anything into space is expensive, using a managed risk posture, holding to schedule and keeping costs low by stopping at egood enough f were key elements to their success. Risk is defined as the possibility of loss or failure per Merriam Webster. The National Aeronautics and Space Administration (NASA) defines risk using procedural requirement 8705.4 and establishes eclasses f to discern the acceptable risk per a project. It states a Class D risk has a medium to significant risk of not achieving mission success. MSFC, along with industry partners, has created a niche in Class D efforts. How did the big, cautious MSFC succeed on these projects that embodied the antithesis of its heritage in human space flight? A key factor toward these successful projects was innovative industry partners such as Dynetics Corporation, University of Alabama in Huntsville (UAHuntsville), Johns Hopkins Applied Physics Laboratory (JHU APL), Teledyne Brown Engineering (TBE), Von Braun Center for Science and Innovation (VCSI), SAIC, and Jacobs. Fast Affordable Satellite Technology (FastSat HSV01) is a low earth orbit microsatellite that houses six instruments with the primary scientific objective of earth observation and technology demonstration. The team was comprised of Dynetics, UAHuntsvile, SAIC, Goddard Space Flight Center (GSFC) and VCSI with the United States Air Force Space Test Program as the customer. The team completed design, development, manufacturing, environmental test and integration in one year. FastSat HSV01 also deployed a Poly Picosatellite Orbital Deployer (PPOD) for a separate nano ]satellite class spacecraft (Cubesat: Nano Sail Demonstration) in partnership with Ames Research Center. The Robotic lunar lander is a MSFC JHU APL partnership that led to the development of a flexible architecture for landers to support robotic missions to a wide range of lunar and asteroid destinations. The team started with the goal of meeting NASA agency directives that led to the creation of a test bed focusing on GN&C and software to demonstrate the descent and landing on any airless body for the final 30 to 60 meters. The team created a complex technology demonstration as well as Guidance Control and Navigation (GN&C) algorithms providing autonomous control of the lander. The team uses a green propellant of 90% hydrogen peroxide and has completed 18 successful test flights. The International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) is a technology demonstration payload to assist the SERVIR project with environmental monitoring for disaster relief and humanitarian efforts. The ISERV project was a partnership with TBE. The ISERV payload consists of a commercial off the shelf camera, telescope, and MSFC developed power distribution box and interfaces on ISS with the Window Observational Research Facility in the US Lab. MSFC has identified three key areas that enabled the low cost mission success to include culture, partnering, and cost/schedule control. This paper will briefly discuss these three Class D efforts, FastSat HSV-01, the Robotic Lunar Lander and the ISERV camera system, the lessons learned, their successes and challenges.

Watson-Morgan, Lisa↗
NASA NTRS2015

AMO EXPRESS: A Command and Control Experiment for Crew Autonomy Onboard the International Space Station

The Autonomous Mission Operations project is investigating crew autonomy capabilities and tools for deep space missions. Team members at Ames Research Center, Johnson Space Center and Marshall Space Flight Center are using their experience with ISS Payload operations and TIMELINER to: move earth based command and control assets to on-board for crew access; safely merge core and payload command procedures; give the crew single action intelligent operations; and investigate crew interface requirements.

Cornelius, Randy↗
NASA NTRS1983

Autonomous failure detection and correction on Landsat-4

An integrated hardware/software fault tolerant system for an earth oriented, computer controlled spacecraft is described. The design philosophy as well as the rationale behind the chosen fault tolerant system is outlined. In-flight performance of the system is included for several different instances where the Failure Detection and Correction system acted autonomously to protect the spacecraft. This system exceeded the expectations of the designers by demonstrating the capability to provide a measure of safety to the spacecraft for inadvertent and undesirable ground commands as well as satisfying its primary function of monitoring the flight hardware and software for failures.

Welch, R. V.↗
NASA NTRS2008

The Next 25 Years of Deep Space Navigation

This slide presentation reviews the missions that will be flown into deep space in the next 25 years, the navigational challenges for these missions, and the strategies that will be used to overcome these challenges. The challenges include: (1) an incresed need for autonomous navigation, (2) an increased use of in-situ and optical navigation, (3) an increased use of low-thrust propulsion, (4) an increased need for higher accuracy in guidance, navigation, and control, and an increased need for integration between flight path and attitude control. The enabling strategies that are planned for use are: (1) Advance Radio-Metric Tracking Capabilities, (2) Expand the Use of Optical Navigation, (3) Develop General-Purpose Autonomous Navigation Capabilities, (4) Improve Frequency and Timing Systems, and (5) Develop In-situ Tracking Infrastructure. Future trends that are being developed are Optical and Autonomous Navigation

optical navigation↗
NASA NTRS1998

STS-90 Day 07 Highlights

On this seventh day of the STS-90 mission, the flight crew, Cmdr. Richard A. Searfoss, Pilot Scott D. Altman, and Mission Specialists Richard M. Linnehan, Dafydd Rhys Williams and Kathryn P. Hire, and Payload Specialists Jay C. Buckey and James A. Pawelczyk continue experiments that looks at the autonomic nervous system, the part of the nervous system that automatically controls blood pressure. These investigations are designed to uncover changes that take place in blood pressure control during space flight. Crewmembers use the Lower Body Negative Pressure (LBNP) device which places a stress on the cardiovascular system similar to what is experienced when standing in Earth's gravity environment.

Source record↗
NASA NTRS1994

Development of the dynamic motion simulator of 3D micro-gravity with a combined passive/active suspension system

The establishment of those in-orbit operations like 'Rendez-Vous/Docking' and 'Manipulator Berthing' with the assistance of robotics or autonomous control technology, is essential for the near future space programs. In order to study the control methods, develop the flight models, and verify how the system works, we need a tool or a testbed which enables us to simulate mechanically the micro-gravity environment. There have been many attempts to develop the micro-gravity testbeds, but once the simulation goes into the docking and berthing operation that involves mechanical contacts among multi bodies, the requirement becomes critical. A group at the Tokyo Institute of Technology has proposed a method that can simulate the 3D micro-gravity producing a smooth response to the impact phenomena with relatively simple apparatus. Recently the group carried out basic experiments successfully using a prototype hardware model of the testbed. This paper will present our idea of the 3D micro-gravity simulator and report the results of our initial experiments.

Yoshida, Kazuya↗
NASA NTRS2011

Interface Supports Multiple Broadcast Transceivers for Flight Applications

A wireless avionics interface provides a mechanism for managing multiple broadcast transceivers. This interface isolates the control logic required to support multiple transceivers so that the flight application does not have to manage wireless transceivers. All of the logic to select transceivers, detect transmitter and receiver faults, and take autonomous recovery action is contained in the interface, which is not restricted to using wireless transceivers. Wired, wireless, and mixed transceiver technologies are supported. This design s use of broadcast data technology provides inherent cross strapping of data links. This greatly simplifies the design of redundant flight subsystems. The interface fully exploits the broadcast data link to determine the health of other transceivers used to detect and isolate faults for fault recovery. The interface uses simplified control logic, which can be implemented as an intellectual-property (IP) core in a field-programmable gate array (FPGA). The interface arbitrates the reception of inbound data traffic appearing on multiple receivers. It arbitrates the transmission of outbound traffic. This system also monitors broadcast data traffic to determine the health of transmitters in the network, and then uses this health information to make autonomous decisions for routing traffic through transceivers. Multiple selection strategies are supported, like having an active transceiver with the secondary transceiver powered off except to send periodic health status reports. Transceivers can operate in round-robin for load-sharing and graceful degradation.

Block, Gary L.↗
DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗