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DOE OSTI2024

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗

NASA NTRSDate not supplied

Sensing Small Uncrewed Aerial Vehicles with Distributed Radars for Advanced Air Mobility Surveillance

In the context of Advanced and Urban Air Mobility major attention is being reserved to the development of sensing strategies for small Uncrewed Aerial Vehicles (sUAVs) to enable their safe operations in and around urban areas. Such strategies should rely on non-cooperative distributed sensors to strengthen the surveillance solution towards the unreliability of Global Navigation Satellite System (GNSS) positioning information, which is typical for low-altitude-flying platforms in urban regions, and increase the monitored airspace volume. To this aim, this paper proposes a fusion solution for a network of distributed ground-based radars, which can be exploited to not only increase the coverage over large airspace volumes but also improve the overall detectability and traceability of sUAVs by leveraging on multiple views over the same area. The solution exploits a centralized fusion scheme in which measurements collected by each radar are shared with a Fusion Center where Kalman Filtering is exploited to build a unique, fused track. Tests conducted on experimental data collected using two sUAVs as flying targets and three distributed radars showed that the proposed solution can produce an increase in coverage from about 20 % (single radar configuration) to about 80 % of the targets’ flight path, as well as a finer accuracy yielding meter and meter-per-second root mean square error values on position and velocity components.

Federica Vitiello↗

NASA NTRS2010

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗

NASA NTRSDate not supplied

Assessing Performance of Radar and Visual Sensing Techniques for Ground-To-Air Surveillance in Advanced Air Mobility

The safe integration of Unmanned Aircraft Vehicles (UAV) within the civil airspace is of great interest to NASA’s Advanced Air Mobility project, which envisions high density of operations in and around urban areas that include both UAV and AAM aircraft. To enable safe autonomous operations of both platforms, reliable airspace surveillance strategies must be designed and experimentally validated in relevant scenarios, where multiple small UAV operate flying in low altitude conditions. An example of such a scenario is described in this paper which provides performance assessment of various sensing strategies experimentally tested during flight campaigns with four UAV completing simultaneous missions from vertiports. Such campaigns are performed by the High Density Vertiplex subproject which assesses a prototype of Urban Air Mobility ecosystem. For the purposes of this work, the flights are observed from multiple sensing nodes each with radar and camera sensors. The visual detection and tracking algorithms achieved 96.1% to 99.9% average tracking coverage of the UAV above the horizon, reaching detection ranges larger than 1 kilometer for octocopter. Radar-based tracking shows a lower coverage mainly due to ground clutter removal challenges but provides comparable detection ranges and meter-level range accuracy.

Federica Vitiello↗

DOE OSTI2025

Vertical column dual-comb spectroscopy to a TBS

Open-path dual-frequency-comb spectroscopy (DCS) is a broadband, high spectral resolution, and high precision method for measuring gas concentrations over kilometer-scale paths. It has been used for detection and quantification of emissions of pollutants, hazardous gasses, and greenhouse gasses (GHGs). DCS has been shown to measure trace-gas mixing ratios with 0.14%-0.4% agreement between instruments. To achieve high signal-to-noise ratios (SNRs) with DCS, comb light is targeted onto a retroreflector at the end of the measurement path, which returns the signal to a detector co-located with the launch signal. Installing the retroreflector on a mobile platform such as a balloon or unmanned aerial vehicle (UAV) extends the capabilities of DCS by enabling variable path lengths, greater mobility, and access to higher altitudes. Mobile-target DCS has many uses in plume and leak detection, emissions modeling, and planetary boundary layer (PBL) studies. It is a promising method for observing vertical distributions of GHGs and mixing processes in the PBL, which are difficult to measure but important for pollution and climate monitoring as well as for understanding transport of gasses through the atmosphere. Tethered balloons are an intriguing platform because they enable longer flight durations and higher altitudes than easily obtainable with a UAV and thus allow for column measurements up to and above the PBL. New measurements completed in October/November 2024 reach the highest altitudes above ground level yet achieved by mobile-target DCS. For these measurements, the retroreflector was mounted on a 7 m diameter tethered helium balloon. An actively tracking gimbal on the ground holds the DCS launch telescope and keeps the 5 cm beam pointed onto the retroreflector while the balloon is lifted, lowered, and moved by wind and turbulence.

atmosphere↗

NASA NTRS2011

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

Chien, Chiun-Hong↗

NASA NTRS2005

Vision guided landing of an an autonomous helicopter in hazardous terrain

Future robotic space missions will employ a precision soft-landing capability that will enable exploration of previously inaccessible sites that have strong scientific significance. To enable this capability, a fully autonomous onboard system that identifies and avoids hazardous features such as steep slopes and large rocks is required. Such a system will also provide greater functionality in unstructured terrain to unmanned aerial vehicles. This paper describes an algorithm for landing hazard avoidance based on images from a single moving camera. The core of the algorithm is an efficient application of structure from motion to generate a dense elevation map of the landing area. Hazards are then detected in this map and a safe landing site is selected. The algorithm has been implemented on an autonomous helicopter testbed and demonstrated four times resulting in the first autonomous landing of an unmanned helicopter in unknown and hazardous terrain.

Mars Landing↗

NASA NTRS1993

Activities of the Center for Space Construction

The Center for Space Construction (CSC) at the University of Colorado at Boulder is one of eight University Space Engineering Research Centers established by NASA in 1988. The mission of the center is to conduct research into space technology and to directly contribute to space engineering education. The center reports to the Department of Aerospace Engineering Sciences and resides in the College of Engineering and Applied Science. The college has a long and successful track record of cultivating multi-disciplinary research and education programs. The Center for Space Construction is prominent evidence of this record. At the inception of CSC, the center was primarily founded on the need for research on in-space construction of large space systems like space stations and interplanetary space vehicles. The scope of CSC's research has now evolved to include the design and construction of all spacecraft, large and small. Within this broadened scope, our research projects seek to impact the underlying technological basis for such spacecraft as remote sensing satellites, communication satellites, and other special purpose spacecraft, as well as the technological basis for large space platforms. The center's research focuses on three areas: spacecraft structures, spacecraft operations and control, and regolith and surface systems. In the area of spacecraft structures, our current emphasis is on concepts and modeling of deployable structures, analysis of inflatable structures, structural damage detection algorithms, and composite materials for lightweight structures. In the area of spacecraft operations and control, we are continuing our previous efforts in process control of in-orbit structural assembly. In addition, we have begun two new efforts in formal approach to spacecraft flight software systems design and adaptive attitude control systems. In the area of regolith and surface systems, we are continuing the work of characterizing the physical properties of lunar regolith, and we are at work on a project on path planning for planetary surface rovers.

Source record↗

NASA NTRSDate not supplied

Design of a Thruster Vector Servo-Elastic Filter

This presents a method to improve the thruster vector servo elasticity (TVSE) stability. TVSE is the coupling between the TVC system engine dynamics and the vehicle flexible modes. It can lead to instability of the flexible modes due to the energy injection from the thrust. For large boosters with heavy TVC engine, TVSE is more likely to cause instability. This instability is part of the plant dynamics and is not detected by the flight control. In this paper, the TVSE is treated as a disturbance rejection problem with the inertial force of the flexible motion viewed as an external disturbance to the TVC actuator control system. By effectively rejecting this disturbance, the engine can be decoupled from the flexible dynamics thus improving TVSE stability. The actuator disturbance transfer function is modified by inserting a TVSE filter into the control system. The filter aims to reduce the magnitude and introduce phase lead of the disturbance transfer function over the TVSE sensitive frequency range while maintaining adequate stability margins of the actuator control system. A prefilter is also designed for good command tracking. The filter and prefilter resulting from this method are usually of low order and can be included to the existing actuator controller if the controller is programmable. This method was demonstrated for a hydraulic Simplex actuator model. Its applications to SLS B1 and B2 TVC actuator are also described. B2 actuator controller is modified based on this method. The tradeoff between TVSE stability and the control system stability can be balanced by adjusting the amount of phase lead introduced by the TVSE filter. This method provides a useful way to solve the TVSE instability issue without costly and time-consuming a TVC system redesign. This method is based on the basic control principles of loop shaping and disturbance rejection and has been proven to be effective under proper circum-stances.

Thrust vector control↗

DOE OSTI2021

Study of Hydrogen Fuel Cell Technology for Freight Rail Propulsion and Review of Relevant Industry Standards.

Alternatives to conventional diesel electric propulsion are currently of interest to rail operators. In the U.S., smaller railroads have implemented natural gas and other railroads are exploring hydrogen technology as a cleaner alternative to diesel. Diesel, battery, hydrogen fuel cell, or track electrification all have trade-offs for operations, economics, safety, and public acceptability. A framework to compare different technologies for specific applications is useful to optimize the desired results. Standards from the Association of American Railroads (AAR) and other industry best practices were reviewed for applicability with hydrogen fuel cell technology. Some technical gaps relate to the physical properties of hydrogen, such as embrittlement of metals, invisible flames, and low liquid temperatures. A reassessment of material selection, leak/flame detection, and thermal insulation methods is required. Hydrogen is less dense and diffuses more easily than natural gas, and liquid hydrogen is colder than liquefied natural gas. Different densities between natural gas and hydrogen require modifications to tank designs and flow rates. Leaked hydrogen will rise rather than pool on the ground like diesel, requiring a modification to the location of hydrogen tanks on rolling stock. Finally, the vibration and shock experienced in the rail environment is higher than light-duty vehicles and stationary applications for which current fuel cell technology has been developed, requiring a modification in tank design requirements and testing.

08 HYDROGEN↗

DOE OSTI2024

Automated Inspection of Criticality Control Overpacks for Surplus Plutonium Disposition: Qualification Update – 25313

In an effort to reduce the amount of nuclear waste in South Carolina, the Department of Energy (DOE) tasked the Savannah River Site (SRS) with diluting and disposing of the amount of plutonium in the state. This process involves the movement and shipment of over 100,000 criticality control overpacks (CCOs) throughout the project lifespan, lending itself to the use of automation to reduce worker radiation exposure and more efficiently utilize human capital. Due to the large scope, this overarching process was broken down into several different “automation projects” to be developed. The first opportunity pursued was the receipt and inspection of empty CCO drums coming into SRS, identified as Automation Project 1 (AP1), and is the focus of this paper. AP1 was developed to unpack incoming CCOs and inspect them for unwanted foreign objects and any damage to the drum or its contents. This process is accomplished by the combination of an automated guided vehicle (AGV) that delivers CCOs to a robotic arm which uses a suite of custom tools to disassemble a CCO, inspect the inside and outside of the CCO and its inner criticality control container (CCC), reassemble the CCC and CCO, and apply a tamper indicating device (TID) to the inspected drum. In past years, the robotic work cell had been developed in a small-scale testing facility for proof-of-concept. This year, major improvements were made to the robotic work cell to perform the process, including integration into the final facility where CCOs will be inspected. Other technical improvements include the implementation of sensor feedback and safety relays into the control system to allow the state of the work cell to be better tracked, and additional development of the TID application process to complete the robotic inspection. Further enhancements were made to the robotic vision processes and robot pathing, as well as development on a computer vision inspection process to detect inspection criteria anomalies in CCOs. In addition to developmental improvements, the work cell underwent a six-month testing period to ensure the project requirements were met. Results of this testing period demonstrate the work cell’s capability to meet project throughput goals at an acceptable level, successfully document the status of each CCO inspected, and reduce the toll on technical operations’ human power by two thirds. At the time of this paper, the work cell is capable of autonomously handling up to eight CCOs with an AGV, delivering CCOs to and from the robot work cell, and having a robotic arm perform a full receipt and inspection procedure on each CCO. Moving forward, repeatability will be improved so that these CCOs can be run back-to-back seamlessly, as well as improving the system to handle more significant edge cases and failure modes.

Spivey, Nicholas↗

NASA NTRS2013

Test and Evaluation Metrics of Crew Decision-Making And Aircraft Attitude and Energy State Awareness

NASA has established a technical challenge, under the Aviation Safety Program, Vehicle Systems Safety Technologies project, to improve crew decision-making and response in complex situations. The specific objective of this challenge is to develop data and technologies which may increase a pilot's (crew's) ability to avoid, detect, and recover from adverse events that could otherwise result in accidents/incidents. Within this technical challenge, a cooperative industry-government research program has been established to develop innovative flight deck-based counter-measures that can improve the crew's ability to avoid, detect, mitigate, and recover from unsafe loss-of-aircraft state awareness - specifically, the loss of attitude awareness (i.e., Spatial Disorientation, SD) or the loss-of-energy state awareness (LESA). A critical component of this research is to develop specific and quantifiable metrics which identify decision-making and the decision-making influences during simulation and flight testing. This paper reviews existing metrics and methods for SD testing and criteria for establishing visual dominance. The development of Crew State Monitoring technologies - eye tracking and other psychophysiological - are also discussed as well as emerging new metrics for identifying channelized attention and excessive pilot workload, both of which have been shown to contribute to SD/LESA accidents or incidents.

Bailey, Randall E.↗

DOE OSTI2021

Using Machine Learning to Track Objects Across Cameras

Video surveillance is one of the most important technologies used by the International Atomic Energy Agency in international safeguards. At large, complicated facilities, multiple surveillance cameras are deployed to monitor the transfer of safeguards-relevant objects across the site. During inspections, all surveillance videos are reviewed to ensure the objects are not manipulated or diverted during transfer, a laborious, time-consuming task. This work describes using deep machine learning algorithms to track objects automatically across multiple cameras, greatly improving the efficiency of the review process. The fundamental problem in this object tracking task across multiple cameras is how to associate the same object, which may show extreme intra-class variations, such as viewpoints, occlusions, and various scales, in different and even non-overlapped cameras. Object re-identification (Re-ID) in nuclear facility video surveillance is even more challenging than classic person or vehicle Re-ID problems because different instances in the same category may display an identical appearance. One observation from nuclear facility surveillance videos is that all objects must be carted (e.g., via forklift) to move. Therefore, the spatial context information of an object, which provides the feature from the carrier, is critical for the object Re-ID task. This work proposes a two-stream convolutional neural networks model that takes features of objects and their surrounding regions into account. Moreover, the custom videos usually are gleaned from different scenes from the training data, which may have extreme variations in illumination changes and/or cluttered backgrounds. Directly applying the trained model to custom videos will dramatically decrease the performance. To tackle this problem, an advanced domain adaptation technique is proposed to mitigate the gap between the data taken from different scenes. The proposed framework will track objects of interest across a nuclear complex. The resulting tracks can be used in further analyses, such as event/activity recognition, anomaly detection, etc.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRSDate not supplied

Design of a Thrust Vector Servoelastic Filter for SLS Block 2 Booster Thrust Vector Control System

This paper presents a method to improve the thrust vector servoelastic (TVSE) response of a launch vehicle. TVSE is the coupling between the Thrust Vector Control (TVC) system nozzle dynamics and the vehicle flexible modes. A poorly phased TVC response, i.e. in phase with the structural velocity, can lead to instability of the flexible modes due to the energy injection from the thrust. For large boosters with heavy nozzles, TVSE is more likely to cause instability. This instability is part of the plant dynamics and may not be readily detected by the flight control system. In this paper, TVSE is treated as a disturbance rejection problem with the inertial force of the flexible motion viewed as an external disturbance to the TVC actuator control system. By effectively rejecting this disturbance, the engine can be decoupled from the flexible dynamics thus improving TVSE stability. The actuator disturbance transfer function is modified by inserting a filter into the servo-loop control system. The filter aims to reduce the magnitude and introduce phase lead of the disturbance transfer function over the TVSE sensitive frequency range while maintaining adequate stability margins of the actuator control system. A prefilter is also designed to improve command tracking performance. The filter and prefilter resulting from this method are usually of low order and can be included to an existing actuator controller if the controller is programmable. This method was demonstrated for a hydraulic Simplex actuator model. Its applications to the Space Launch System (SLS) Block 1 and Block 2 TVC actuator are also described. The Block 2 actuator controller was modified based on the results of this method. The tradeoff between TVSE stability and the servo-loop stability can be balanced by adjusting the amount of phase lead introduced by the TVSE filter. This method provides a useful way to solve the TVSE instability issue without costly and time-consuming hardware solutions. This method is based on the basic control principles of loop shaping and disturbance rejection and has been proven to be effective under proper circumstances.

Thrust vector control↗

NASA NTRS2012

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

Source record↗

NASA NTRS1994

A teleoperated system for remote site characterization

The detection and characterization of buried objects and materials is an important step in the restoration of burial sites containing chemical and radioactive waste materials at Department of Energy (DOE) and Department of Defense (DOD) facilities. By performing these tasks with remotely controlled sensors, it is possible to obtain improved data quality and consistency as well as enhanced safety for on-site workers. Therefore, the DOE Office of Technology Development and the US Army Environmental Center have jointly supported the development of the Remote Characterization System (RCS). One of the main components of the RCS is a small remotely driven survey vehicle that can transport various combinations of geophysical and radiological sensors. Currently implemented sensors include ground-penetrating radar, magnetometers, an electromagnetic induction sensor, and a sodium iodide radiation detector. The survey vehicle was constructed predominantly of non-metallic materials to minimize its effect on the operation of its geophysical sensors. The system operator controls the vehicle from a remote, truck-mounted, base station. Video images are transmitted to the base station by a radio link to give the operator necessary visual information. Vehicle control commands, tracking information, and sensor data are transmitted between the survey vehicle and the base station by means of a radio ethernet link. Precise vehicle tracking coordinates are provided by a differential Global Positioning System (GPS).

Sandness, Gerald A.↗

NASA NTRSDate not supplied

NASA’s Identified Risks of Adverse Outcomes Due to Inadequate Human Systems Integration Architecture in Human Spaceflight

The NASA Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. One of the identified risks is due to inadequate human systems integration architecture (HSIA) and a driving factor of this risk is that given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors. The HSRB uses Directed Acyclic Graphs (DAGs) as a communication tool for describing how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes and as the basis for understanding intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes. The HSIA risk DAG will be presented and described. Historically, critical malfunctions requiring Crew/MCC management occurred at a rate of 1.7 times per year for ISS averaged over the lifetime and 3-4 times per year in the burn in phase for the vehicle. These averages do not include EVA data, which greatly increases the incident rate. Prior experience from the Apollo program showed 10/11 crewed missions experienced significant anomalies where crew relied heavily on MCC expertise in real-time. These failure patterns are in line with those observed in other complex engineered systems (e.g., oil rigs, launch systems, commercial aviation, etc.) It is likely that general malfunction and error rates are > 10% for short duration missions (<30 days), based on past and current spaceflight operations data. Likelihood of adverse outcomes has the potential to increase as crew conduct work with new, complex systems and with less ground support. For Low Earth Orbit missions and Lunar missions less than 30 days, assuming minimal comm delays, disruptions and bandwidth limitations, malfunctions and errors can affect mission objectives and crew health but may be mitigated by ground support. For Lunar missions greater than 30 days and any potential Mars mission malfunctions and errors can have Loss of Crew and Loss of Mission consequences due to reduced ground support (communication delays, constraints and blackouts) for more complex operations, as well as reduced resupply and evacuation options.

Daniel M Buckland↗

NASA NTRS2018

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin J.↗