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Lunar Landing Trajectory Design for Onboard Hazard Detection and Avoidance

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing the software and hardware technology needed to support a safe and precise landing for the next generation of lunar missions. ALHAT provides this capability through terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard detection system to select safe landing locations, and an Autonomous Guidance, Navigation, and Control (AGNC) capability to process these measurements and safely direct the vehicle to a landing location. This paper focuses on the key trajectory design issues relevant to providing an onboard Hazard Detection and Avoidance (HDA) capability for the lander. Hazard detection can be accomplished by the crew visually scanning the terrain through a window, a sensor system imaging the terrain, or some combination of both. For ALHAT, this hazard detection activity is provided by a sensor system, which either augments the crew s perception or entirely replaces the crew in the case of a robotic landing. Detecting hazards influences the trajectory design by requiring the proper perspective, range to the landing site, and sufficient time to view the terrain. Following this, the trajectory design must provide additional time to process this information and make a decision about where to safely land. During the final part of the HDA process, the trajectory design must provide sufficient margin to enable a hazard avoidance maneuver. In order to demonstrate the effects of these constraints on the landing trajectory, a tradespace of trajectory designs was created for the initial ALHAT Design Analysis Cycle (ALDAC-1) and each case evaluated with these HDA constraints active. The ALHAT analysis process, described in this paper, narrows down this tradespace and subsequently better defines the trajectory design needed to support onboard HDA. Future ALDACs will enhance this trajectory design by balancing these issues and others in an overall system design process.

Paschall, Steve↗

Dynamic Structural Fault Detection and Identification

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

Smith, Timothy↗

Lunar Reconnaissance Orbiter (LRO) Guidance, Navigation and Control (GN&C) Overview

The National Aeronautics and Space Administration s (NASA) Lunar Reconnaissance Orbiter (LRO) launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle and into a direct insertion trajectory to the oon. LRO, which was designed, built, and operated by the NASA Goddard Space Flight Center in Greenbelt, MD, is gathering crucial data on the lunar environment that will help astronauts prepare for long-duration lunar expeditions. The mission has a nominal life of 1 year as its seven instruments find safe landing sites, locate potential resources, characterize the radiation environment, and test new technology. To date, LRO has been operating well within the bounds of its requirements and has been collecting excellent science data images taken from the LRO Camera Narrow Angle Camera of the Apollo landing sites appeared on cable news networks. A significant amount of information on LRO s science instruments is provided at the LRO mission webpage. LRO s Guidance, Navigation and Control (GN&C) subsystem is made up of an onboard attitude control system (ACS) and a hardware suite of sensors and actuators. The LRO onboard ACS is a collection of algorithms based on high level and derived requirements, and reflect the science and operational events throughout the mission lifetime. The primary control mode is the Observing mode, which maintains the lunar pointing orientation and any offset pointing from this baseline. It is within this mode that all science instrument calibrations, slews and science data is collected. Because of a high accuracy requirement for knowledge and pointing, the Observing mode makes use of star tracker (ST) measurement data to determine an instantaneous attitude pointing. But even the star trackers alone do not meet the tight requirements, so a six-state Kalman Filter is employed to improve the noisy measurement data. The Observing mode obtains its rate information from an inertial reference unit (IRU) and in the event of an IRU failure, the rate data is be derived from the star tracker, but with degraded pointing performance. The Delta-V control mode responsibility is to maintain attitude pointing during the cruise trajectory, insertion burns and lunar orbit maintenance by adjustments made to the spacecraft s velocity magnitude and vector direction. The ACS also provides for a thruster based system momentum management algorithm (known as Delta-H) to maintain the system and wheel momentum to within acceptable levels. In the event an anomaly causes the LRO spacecraft to lose the ability to maintain its current attitude pointing, a Sun Safe mode is included in the ACS for the purpose of providing a known power and thermally safe coarse inertial sun attitude for an indefinite period of time, within the manageable limits of the reaction wheels. The Sun Safe mode is also the initial spacecraft control mode off of the launch vehicle and provides for a means to null tip-off rates immediately after separation. The nominal configuration is to use the IRU for rate information in the controller. In the event of a gyro failure a gyroless control mode was developed that computes rate information from the CSS data.

Garrick, Joseph↗

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration, experiment functionality, overall risk mitigation, flight test approach and results, and lessons learned of adaptive controls research of the Full-Scale Advanced Systems Testbed.

Pavlock, Kate M.↗

The First Flight Decision for New Human Spacecraft Vehicles - A General Approach

Determining when it is safe to fly a crew on a launch vehicle/spacecraft for the first time, especially when the test flight is a part of the overall system certification process, has long been a challenge for program decision makers. The decision on first flight is ultimately the judgment of the program and agency management in conjunction with the design and operations team. To aid in this decision process, a NASA team undertook the task to develop a generic framework for evaluating whether any given program or commercial provider has sufficiently complete and balanced plans in place to allow crewmembers to safely fly on human spaceflight systems for the first time. It was the team s goal to establish a generic framework that could easily be applied to any new system, although the system design and intended mission would require specific assessment. Historical data shows that there are multiple approaches that have been successful in first flight with crew. These approaches have always been tailored to the specific system design, mission objectives, and launch environment. Because specific approaches may vary significantly between different system designs and situations, prescriptive instructions or thorough checklists cannot be provided ahead of time. There are, however, certain general approaches that should be applied in thinking through the decision for first flight. This paper addresses some of the most important factors to consider when developing a new system or evaluating an existing system for whether or not it is safe to fly humans to/from space. In the simplest terms, it is time to fly crew for the first time when it is safe to do so and the benefit of the crewed flight is greater than the residual risk. This is rarely a straight-forward decision. The paper describes the need for experience, sound judgment, close involvement of the technical and management teams, and established decision processes. In addition, the underlying level of confidence the manager has in making the decision will also be discussed. By applying the outlined thought processes and approaches to a specific design, test program and mission objectives, a project team will be better able to focus the debate and discussion on critical areas for consideration and added scrutiny -- allowing decision makers to adequately address the first crewed flight decision.

Schaible, Dawn M.↗

Analysis of Control Strategies for Aircraft Flight Upset Recovery

This paper proposes a framework for studying the ability of a control strategy, consisting of a control law and a command law, to recover an aircraft from ight conditions that may extend beyond the normal ight envelope. This study was carried out (i) by evaluating time responses of particular ight upsets, (ii) by evaluating local stability over an equilibrium manifold that included stall, and (iii) by bounding the set in the state space from where the vehicle can be safely own to wings-level ight. These states comprise what will be called the safely recoverable ight envelope (SRFE), which is a set containing the aircraft states from where a control strategy can safely stabilize the aircraft. By safe recovery it is implied that the tran- sient response stays between prescribed limits before converging to a steady horizontal ight. The calculation of the SRFE bounds yields the worst-case initial state corresponding to each control strategy. This information is used to compare alternative recovery strategies, determine their strengths and limitations, and identify the most e ective strategy. In regard to the control law, the authors developed feedback feedforward laws based on the gain scheduling of multivariable controllers. In regard to the command law, which is the mechanism governing the exogenous signals driving the feed- forward component of the controller, we developed laws with a feedback structure that combines local stability and transient response considera- tions. The upset recovery of the Generic Transport Model, a sub-scale twin-engine jet vehicle developed by NASA Langley Research Center, is used as a case study.

Crespo, Luis G.↗

Control and Non-Payload Communications Generation 1 Prototype Radio Flight Test Report

Unmanned aircraft (UA) represent a new capability that will provide a variety of services in the Government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized because of the lack of a common understanding of what is required to safely operate Unmanned Aircraft Systems in the National Airspace System (UAS in the NAS). The desire and ability to fly UA is of increasing urgency. The application of UA to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UA to the NAS. Existing Federal Aviation Regulations, procedures, and technologies do not allow routine UA access to the NAS. Access to the NAS is hampered by challenges such as the lack of an onboard pilot to see and avoid other aircraft; the ability of a single pilot or operator to control multiple UA; the reliance on command and control (C2) links; the altitudes, speeds, and duration at which the aircraft fly; and the wide variation in UA size and performance. NASA is working with other Government agencies to provide solutions that reduce technical barriers and make access to the NAS routine. This goal will be accomplished through system-level integration of key concepts, technologies, or procedures and through demonstrations of these integrated capabilities in an operationally relevant environment. This project provides an opportunity to transition the acquired empirical data and knowledge to the Federal Aviation Administration and other stakeholders to help them define the requirements for routine UA access to the NAS.Radio communications channels for UA are currently managed through exceptions and use either Department of Defense frequencies for line-of-sight (LOS) and satellite-based communications links, low-power LOS links in amateur bands, or unlicensed Industrial/Scientific/Medical (ISM) frequencies. None of these frequency bands are designated for safety and regularity of flight. Only recently has radiofrequency (RF) spectrum been allocated by the International Telecommunications Union specifically for commercial UA C2, LOS communication (L-Band: 960 to 1164 MHz, and C-Band: 5030 to 5091 MHz). The safe and efficient integration of UA into the NAS requires the use of protected RF spectrum allocations and a new data communications system that is both secure and scalable to accommodate the potential growth of these new aircraft. Data communications for UA-referred to as control and non-payload communications (CNPC)-will be used to exchange information between a UA and a ground station (GS) to ensure safe, reliable, and effective UA flight operation. The focus of this effort is on validating and allocating new RF spectrum and data link communications to enable civil UA integration into the NAS. Through a cost-sharing cooperative agreement with Rockwell Collins, Inc., the NASA Glenn Research Center is exploring and performing the necessary development steps to realize a prototype UA CNPC system. These activities include investigating signal waveforms and access techniques, developing representative CNPC radio hardware, and executing relevant testing and validation activities. There is no intent to manufacture the CNPC end product, rather the goals are to study, demonstrate, and validate a typical CNPC system that will allow safe and efficient communications within the L-Band and C-Band spectrum allocations. The system is addressing initial "seed" requirements from RTCA, Inc., Special Committee 203 (SC-203) and is on a path to Federal Aviation Administration certification. This report provides results from the flight testing campaign of the Rockwell Collins Generation 1 prototype radio, referred hereafter as the "radio." The radio sets operate within the 960- to 977-MHz frequency band with both air and ground radios using identical hardware. Flight tests involved one aircraft and one GS. Results include discussion of aircraft flight paths and associated radio performance.

Shalkhauser, Kurt A.↗

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗

3-D Flash Lidar Performance in Flight Testing on the Morpheus Autonomous, Rocket-Propelled Lander to a Lunar-Like Hazard Field

For the first time, a 3-D imaging Flash Lidar instrument has been used in flight to scan a lunar-like hazard field, build a 3-D Digital Elevation Map (DEM), identify a safe landing site, and, in concert with an experimental Guidance, Navigation, and Control (GN&C) system, help to guide the Morpheus autonomous, rocket-propelled, free-flying lander to that safe site on the hazard field. The flight tests served as the TRL 6 demo of the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) system and included launch from NASA-Kennedy, a lunar-like descent trajectory from an altitude of 250m, and landing on a lunar-like hazard field of rocks, craters, hazardous slopes, and safe sites 400m down-range. The ALHAT project developed a system capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The Flash Lidar is a second generation, compact, real-time, air-cooled instrument. Based upon extensive on-ground characterization at flight ranges, the Flash Lidar was shown to be capable of imaging hazards from a slant range of 1 km with an 8 cm range precision and a range accuracy better than 35 cm, both at 1-delta. The Flash Lidar identified landing hazards as small as 30 cm from the maximum slant range which Morpheus could achieve (450 m); however, under certain wind conditions it was susceptible to scintillation arising from air heated by the rocket engine and to pre-triggering on a dust cloud created during launch and transported down-range by wind.

Roback, Vincent E.↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project KDP-C Review

The topics discussed are the UAS-NAS project life-cycle and ARMD thrust flow down, as well as the UAS environments and how we operate in those environments. NASA's Armstrong Flight Research Center at Edwards, CA, is leading a project designed to help integrate unmanned air vehicles into the world around us. The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS in the NAS, will contribute capabilities designed to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The project falls under the Integrated Systems Research Program office managed at NASA Headquarters by the agency's Aeronautics Research Mission Directorate. NASA's four aeronautics research centers - Armstrong, Ames Research Center, Langley Research Center, and Glenn Research Center - are part of the technology development project. With the use and diversity of unmanned aircraft growing rapidly, new uses for these vehicles are constantly being considered. Unmanned aircraft promise new ways of increasing efficiency, reducing costs, enhancing safety and saving lives 460265main_ED10-0132-16_full.jpg Unmanned aircraft systems such as NASA's Global Hawks (above) and Predator B named Ikhana (below), along with numerous other unmanned aircraft systems large and small, are the prime focus of the UAS in the NAS effort to integrate them into the national airspace. Credits: NASA Photos 710580main_ED07-0243-37_full.jpg The UAS in the NAS project envisions performance-based routine access to all segments of the national airspace for all unmanned aircraft system classes, once all safety-related and technical barriers are overcome. The project will provide critical data to such key stakeholders and customers as the Federal Aviation Administration and RTCA Special Committee 203 (formerly the Radio Technical Commission for Aeronautics) by conducting integrated, relevant system-level tests to adequately address safety and operational challenges of national airspace access by unmanned aircraft systems, or UAS. In the process, the project will work with other key stakeholders to define necessary deliverables and products to help enable such access. Within the project, NASA is focusing on five sub-projects. These five focus areas include assurance of safe separation of unmanned aircraft from manned aircraft when flying in the national airspace; safety-critical command and control systems and radio frequencies to enable safe operation of UAS; human factors issues for ground control stations; airworthiness certification standards for UAS avionics and integrated tests and evaluation designed to determine the viability of emerging UAS technology. Five Focus Areas of the UAS Integration in the NAS Project Separation Assurance Provide an assessment of how planned Next Generation Air Transportation System (NextGen) separation assurance systems, with different functional allocations, perform for UAS in mixed operations with manned aircraft Assess the applicability to UAS and the performance of NASA NextGen separation assurance systems in flight tests with realistic latencies and uncertain trajectories Assess functional allocations ranging from today's ground-based, controller-provided aircraft separation to fully autonomous airborne self-separation Communications Develop data and rationale to obtain appropriate frequency spectrum allocations to enable safe and efficient operation of UAS in the NAS Develop and validate candidate secure safety-critical command and control system/subsystem test equipment for UAS that complies with UAS international/national frequency regulations, standards and recommended practices and minimum operational and aviation system performance standards for UAS Perform analysis to support recommendations for integration of safety-critical command and control systems and air traffic control communications to ensure safe and efficient operation of UAS in the NAS Human Systems Integration Develop a research test bed and database to provide data and proof of concept for GCS - ground control station - operations in the NAS Coordinate with standards organizations to develop human-factors guidelines for GCS operation in the NAS Certification Define a UAS classification scheme and approach to determining Federal Aviation Regulation airworthiness requirements applicable to all UAS digital avionics Provide hazard and risk-related data to support development of type design criteria and best development practices Integrated Tests and Evaluation Integrate and test mature concepts from technical elements to demonstrate and test viability Evaluate the performance of technology development in a relevant environment (full-mission, human-in-the-loop simulations and flight tests)

outreach↗

Autonomous Contingency Management In Urban Air Mobility: The Communication Network Awareness Machine System

Next Generation Air Transportation System (NextGen) has begun the modernization of the nation’s air transportation system (NAS), with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness [1]. The overall objective of the Air Traffic Management-eXploration (ATM-X) project is to facilitate the goals of NextGen by conducting research to enable the growing demand of new, mission variant, air vehicles with safe access to the NAS. The implementation and utilization of new and burgeoning technologies that are both flexible, scalable, and systematically user-focused are requisite for ATM-X to achieve its intention of NAS safe entry [2]. Researchers from NASA Langley’s Flight Deck Integration Team have developed a system architecture that would allow ATM-X to leverage the necessary capabilities of an Increasingly Autonomous System (IAS), machine-agent that will promote the safe access and operation of air vehicles within what has become the byproduct of NextGen modernization, a Net-Centric airspace architecture and an Urban Air Mobility (UAM) community. Conducting flight operations within this type of architecture constrains the human-agent’s natural ability by data management. When the massive volume of data, its types, and the acquisition speed at which the data is ingested is observed it becomes evident that the human-agent will be functioning at an operational disadvantage. Therefore, the development and integration of intelligent machine-agents into the flight deck are a necessary implementation to achieve ATM-X overall objective of safe access and operation in the NAS.

Urban Air Mobility↗

Firmware Architecture of the ARMADAS Bolting Robot

The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project, under development at NASA Ames Research Center, has demonstrated on-ground autonomous robotic assembly of extensive digital structures, and it is now moving forward towards in-space demonstration. The ARMADAS system comprises of the operation software, the operation user interface (opsUI), and a swarm of robots. The robotic system consists of a multitude of collaborative agents specifically designed to transport, place and bolt the building blocks, called voxels (volumetric pixels). This paper focuses on the bolting robot, referred to as Mobile Metamaterial Internal Co-Integrator (MMIC-I). MMIC-I is a battery-powered crawling robot. It navigates the structure through extension, contraction and gripping. Two distinct controller boards operate the robot's two symmetric modules, referred to as module A and B. Board A is the master board: it coordinates motion planning and motion primitives execution, hosts the WiFi client, performs periodic self-assessment and system idle check and triggers faults if anomalies are detected. Board B periodically sends a heartbeat to board A, through a wired communication channel that uses the Serial protocol. Additionally, board A's WiFi client receives heartbeat packet requests or motion/bolting commands from a dedicated server board, and acknowledges reception sending back a response heartbeat packet containing information about the overall robot status, e. g. electrical current and voltage values, target and actual angles, operating mode, fault status. Whenever a motion command is sent, the motion planning section of the firmware determines the current robot configuration, using Inertial Measurement Unit readings and the motors Pulse Width Modulation values. Afterwards, it calculates the list of primitives needed to reach the target state, and controls their execution in the proper order. MMIC-I can receive and execute motion and bolting commands only when it is in operational mode. MMIC-I has three operating modes: standby, operational and safed. Standby mode is automatically entered upon startup. While in standby mode, all motors are powered off, and the only accepted commands are the ones relative to a change of mode and heartbeat packet request. Fault detection causes the robot to automatically enter safed or standby mode. Whenever the detected fault occurs within a motion and requires immediate intervention, e. g. an over-current situation, the robot enters safed mode. Safed mode powers off all motors except for the locomotion module, thus preventing the robot from collapsing. Conversely, when the detected fault doesn't require immediate intervention (low battery warning, for instance), the robot enters standby mode after completing the ongoing motion. This paper provides a detailed discussion of MMIC-I's firmware architecture. It accurately describes the implementation approach for each module: sensor data reading, motor control and actuation, WiFi server-client communication, intra-boards Serial communication, operating modes and autonomous fault detection, motion planning, coordination and execution, etc. Moreover, in support of the software description, this paper includes a thorough characterization of MMIC-I's hardware and avionics.

In-space assembly↗

Flight Test Exploration of Integrated Wildfire Response Operations with Crewed and Uncrewed Air Assets

Since 2016, Japan Aerospace Exploration Agency (JAXA) and NASA have partnered to investigate the safe and efficient integration of uncrewed aircraft systems (UAS) in disaster relief operations. Current disaster response operations would benefit from the use of UAS but are limited by the need for safe airspace integration technologies and enabling regulations. The work presented in this paper focuses on the safe integration of UAS and helicopters in active wildfire disaster response operations. The authors propose the use of mission planning and traffic management technologies, including onboard pilot situation awareness support technologies, to coordinate airspace operations between crewed and uncrewed aircraft (e.g., UAS). A representative wildfire scenario including a helicopter and UAS was developed. The helicopter mission included a flight path that mimicked the siphoning of water from a natural water reservoir (lake) and a subsequent water drop over vegetation along the progressing edge of a fire perimeter. Simulated UAS were assumed to conduct aerial ignition flights in the vicinity as part of a controlled burn of the vegetation ahead of the fire front to create a natural barrier between the fire and a nearby populated area. A situation awareness tool was developed and used to support the helicopter pilots’ task to stay clear of the volume of airspace where the UAS was conducting its operation while efficiently conducting the fire suppression mission. A flight test using JAXA’s experimental helicopter was conducted in August 2022 to validate the developed technology. The advantages of the developed technology were demonstrated, and pilot feedback confirmed that real-time awareness of the UAS operation airspace helped the flight planning and execution of a safe mission that minimized the flight time loss due to the potential interference with the UAS. Post-flight interviews with the pilots indicated no sufficient increase in the pilots’ workload and provided ideas for future technology development. Future research will provide recommendations to standards development organizations to support considerations for crewed-uncrewed interactions in disaster-response operations.

disaster response↗

NASA's Secured Advanced Federated Environment

In 1999, a NASA-wide team initially set out to create a collaborative environment to enable NASA's scientists and engineers to share information and tools across NASA locations and with world-wide partners. This paper describes the team's development process and solutions in resolving conflicting security issues of building a complex intra/inter-enterprise collaborative system. Based on the federated, hierarchical, compartmentalized principles, the Secured Advanced Federated Environment (SAFE) developed by the team is becoming a foundational element for building a collaborative infrastructure for NASA. This paper also introduces the concept of a Micro Security Domain which can achieve the balance between the need to collaborate and the need to enforce enterprise and local security rules. SAFE'S federated security concepts enables networks to be formed around the functional/security requirements. With the SAFE technologies and approaches, security will not be an afterthought of the enterprise network design.

network designs↗

Design Concepts to Meet EASA SC-VTOL-01 Single Failure Criteria

The objective of the current work is to discuss European Union Aviation Safety Agency (EASA) SC-VTOL-01 single failure criteria, VTOL.2250(c). Prior studies have developed concept distributed propulsion and flight control (DPFC) system architectures and found they comply with EASA SC-VTOL-01 probabilistic failure criteria, VTOL.2510(a). Prior work developed two all-electric DPFC systems utilized in a quadrotor concept aircraft developed by the National Aeronautics and Space Administration (NASA); one uses interconnecting shafts and gearboxes to interconnect redundant motors with each rotor system and the other uses gearboxes to connect redundant motors locally, near each rotor. Common between the two electric DPFC systems were rotor shafts, epicyclic systems, and motors. The current work explores Category I failures in drive systems, relevant research to support fail-safe design practices for gear systems, research and adjacent industry trends in motor fail-safety and reliability, and proposed design concepts to comply with VTOL.2250(c). Continued research in fail-safe design concepts and design guidance will benefit eVTOL and conventional rotorcraft, alike. Continued research in these areas will benefit eVTOL certification against SC-VTOL-01, and could optimistically translate to more widespread adoption of similar fail-safe design concepts into new rotorcraft designs certified against CS-29.

Rotorcraft↗

Fracture control methods for space vehicles. Volume 1: Fracture control design methods

A systematic approach for applying methods for fracture control in the structural components of space vehicles consists of four major steps. The first step is to define the primary load-carrying structural elements and the type of load, environment, and design stress levels acting upon them. The second step is to identify the potential fracture-critical parts by means of a selection logic flow diagram. The third step is to evaluate the safe-life and fail-safe capabilities of the specified part. The last step in the sequence is to apply the control procedures that will prevent damage to the fracture-critical parts. The fracture control methods discussed include fatigue design and analysis methods, methods for preventing crack-like defects, fracture mechanics analysis methods, and nondestructive evaluation methods. An example problem is presented for evaluation of the safe-crack-growth capability of the space shuttle crew compartment skin structure.

Liu, A. F.↗

MSFC Data Analysis of the SAFE/DAE Experiment

The Solar Array Flight Experiment (SAFE) on-orbit experiment for measurement of large structures dynamics consists of a dynamic sensing system designed to record and analyze the dynamic characteristics of the SAFE. The early availability of the SAFE and its basic large space structure characteristics made it a logical candidate for verification of the sensing system and evaluation technique. The characteristics of the solar array which place it well within the generic class of large space structures are: (1) Large size; (2) Low natural frequencies; (3) Mechanical complexity of its extendable/retractable mast; and (4) The inability to dynamic test in Earth atmosphere and one g.

Schock, R. W.↗