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157 records · Page 9

Effects of the 8 psia / 32% O2 Atmosphere on the Human in the Spaceflight Environment

Extravehicular activity (EVA) is at the core of a manned space exploration program. There are elements of exploration that may be safely and effectively performed by robots, but there are critical elements of exploration that will require the trained, assertive, and reasoning mind of a human crewmember. To effectively use these skills, NASA needs a safe, effective, and efficient EVA component integrated into the human exploration program. The EVA preparation time should be minimized and the suit pressure should be low to accommodate EVA tasks without undue fatigue, physical discomfort, or suit-related trauma. Commissioned in 2005, the Exploration Atmospheres Working Group (EAWG) had the primary goal of recommending to NASA an internal environment that allowed efficient and repetitive EVAs for missions that were to be enabled by the former Constellation Program. At the conclusion of the EAWG meeting, the 8.0 psia and 32% oxygen (O2) environment were recommended for EVA intensive phases of missions. As a result of selecting this internal environment, NASA gains the capability for efficient EVA with low risk of decompression sickness (DCS), but not without incurring additional negative stimulus of hypobaric hypoxia to the already physiologically challenging spaceflight environment. This paper provides a literature review of the human health and performance risks associated with the 8 psia/32% O2 environment. Of most concern are the potential effects on the central nervous system including increased intracranial pressure, visual impairment, sensorimotor dysfunction, and oxidative damage. Other areas of focus include validation of the DCS mitigation strategy, incidence and treatment of acute mountain sickness (AMS), development of new exercise countermeasures protocols, effective food preparation at 8 psia, assurance of quality sleep, and prevention of suit-induced injury. As a first effort, the trade space originally considered in the EAWG was re-evaluated looking for ways to decrease the hypoxic dose by further enriching the O2% or increasing the pressure. After discussion with the NASA engineering and materials community, it was determined that the O2 could be enriched from 32% to 34% and the pressure increased from 8.0 to 8.2 psia without significant penalty. These two small changes increase alveolar O2 pressure by 11 mmHg, which is expected to significantly benefit crewmembers. The 8.2/34 environment (inspired O2 pressure = 128 mmHg) is also physiologically equivalent to the staged decompression atmosphere of 10.2 psia / 26.5% O2 (inspired O2 pressure = 127 mmHg) used on 34 different shuttle missions for approximately a week each flight. Once decided, the proposed internal environment, if different than current experience, should be evaluated through appropriately simulated research studies. In many cases, the human physiologic concerns can be investigated effectively through integrated multi-discipline ground-based studies. Although missions proposing to use an 8.2/34 environment are still years away, it is recommended that these studies begin early enough to ensure that the correct decisions pertaining to vehicle design, mission operational concepts, and human health countermeasures are appropriately informed.

Environmental control↗

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗

TPSAS-NF1676L-32493-DND

The Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has supported the Open Data Cube (ODC) initiative to provide a data architecture solution that has value to its global users and increases the impact of EO satellite data. ODC is an open-source platform for processing satellite data. We have developed software products and tools around the core ODC that would help users perform machine learning on EO satellite data. The recent United Nations (UN) Sustainable Development Agenda provides a shared blueprint for peace and prosperity for people and for the planet, considering our current situation and helping to create a plan. The core of this agenda is a set of seventeen Sustainable Development Goals (SDGs), which represent an urgent call for action by all countries - both developed and developing - in a global partnership. The CEOS SEO team has recently developed and released a set of innovative Jupyter notebooks addressing UN SDGs 6.6.1 (spatial extents of water-related ecosystems), 11.3.1 (ratio of land consumption rate to population growth rate), and 15.3.1 (proportion of land that is degraded over total land area). These notebooks empower users by providing features that will assist with streamlining analysis ready data retrieval, processing, and visualization. We have recently incorporated several machine learning techniques in these notebooks. In this paper, we present the lessons learned from our experience on classifying land using supervised and unsupervised machine learning techniques using ODC framework for UN SDGs. We identify the current limitations of ODC to seamlessly support machine learning techniques. We propose features that would help machine learning, specifically within the ODC framework. We propose a thematic indexing/loading of data for both unsupervised learning as well as data annotation/labeling pipeline. Currently, ODC supports machine learning by separating data-management from the analysis process. It works as a mechanism to load cubes of data. ODC does not natively support features that are vital in machine learning such as validation splits, fair/balanced sampling, establishing load size constraints, etc. We believe that our proposed features will empower users by providing features that bring machine learning techniques closed to ODC. Enhancements to ODC to better accommodate machine learning techniques can assist in fulfilling UN SDGs such as 6.3.2, 6.4.2, 6.6.1, 11.3.1, 14.1.1, 15.1.1, 15.3.1, and 15.4.2.

Syed R Rizvi↗

Surface Map Traffic Intent Displays and Net-Centric Data-link Communications for NextGen

By 2025, U.S. air traffic is predicted to increase three fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a revolutionary new concept has been proposed for U.S. aviation operations, termed the Next Generation Air Transportation System or "NextGen". Many key capabilities are being identified to enable NextGen, including the use of data-link communications. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen. The paper describes simulation research, conducted at National Aeronautics and Space Administration (NASA) Langley Research Center, examining data-link communications and traffic intent data during envisioned four-dimensional trajectory (4DT)-based and equivalent visual (EV) surface operations. Overall, the results suggest that controller pilot data-link communications (CPDLC) with the use of mandatory pilot read-back of all clearances significantly enhanced situation awareness for 4DT and EV surface operations. The depiction of graphical traffic state and intent information on the surface map display further enhanced off-nominal detection and pilot qualitative reports of safety and awareness.

Shelton, Kevin J.↗

Optical Diagnosis of Gas Turbine Combustors Being Conducted

Researchers at the NASA Glenn Research Center, in collaboration with industry, are reducing gas turbine engine emissions by studying visually the air-fuel interactions and combustion processes in combustors. This is especially critical for next generation engines that, in order to be more fuel-efficient, operate at higher temperatures and pressures than the current fleet engines. Optically based experiments were conducted in support of the Ultra-Efficient Engine Technology program in Glenn's unique, world-class, advanced subsonic combustion rig (ASCR) facility. The ASCR can supply air and jet fuel at the flow rates, temperatures, and pressures that simulate the conditions expected in the combustors of high-performance, civilian aircraft engines. In addition, this facility is large enough to support true sectors ("pie" slices of a full annular combustor). Sectors enable one to test true shapes rather than rectangular approximations of the actual hardware. Therefore, there is no compromise to actual engine geometry. A schematic drawing of the sector test stand is shown. The test hardware is mounted just upstream of the instrumentation section. The test stand can accommodate hardware up to 0.76-m diameter by 1.2-m long; thus sectors or small full annular combustors can be examined in this facility. Planar (two-dimensional) imaging using laser-induced fluorescence and Mie scattering, chemiluminescence, and video imagery were obtained for a variety of engine cycle conditions. The hardware tested was a double annular sector (two adjacent fuel injectors aligned radially) representing approximately 15 of a full annular combustor. An example of the two-dimensional data obtained for this configuration is also shown. The fluorescence data show the location of fuel and hydroxyl radical (OH) along the centerline of the fuel injectors. The chemiluminescence data show C2 within the total observable volume. The top row of this figure shows images obtained at an engine low-power condition, and the bottom row shows data from a higher power operating point. The data show distinctly the differences in flame structure between low-power and high-power engine conditions, in both location and amount of species produced (OH, C2) or consumed (fuel). The unique capability of the facility coupled with its optical accessibility helps to eliminate the need for high-pressure performance extrapolations. Tests such as described here have been used successfully to assess the performance of fuel-injection concepts and to modify those designs, if needed.

Hicks, Yolanda R.↗

Model based estimation of image depth and displacement

Passive depth and displacement map determinations have become an important part of computer vision processing. Applications that make use of this type of information include autonomous navigation, robotic assembly, image sequence compression, structure identification, and 3-D motion estimation. With the reliance of such systems on visual image characteristics, a need to overcome image degradations, such as random image-capture noise, motion, and quantization effects, is clearly necessary. Many depth and displacement estimation algorithms also introduce additional distortions due to the gradient operations performed on the noisy intensity images. These degradations can limit the accuracy and reliability of the displacement or depth information extracted from such sequences. Recognizing the previously stated conditions, a new method to model and estimate a restored depth or displacement field is presented. Once a model has been established, the field can be filtered using currently established multidimensional algorithms. In particular, the reduced order model Kalman filter (ROMKF), which has been shown to be an effective tool in the reduction of image intensity distortions, was applied to the computed displacement fields. Results of the application of this model show significant improvements on the restored field. Previous attempts at restoring the depth or displacement fields assumed homogeneous characteristics which resulted in the smoothing of discontinuities. In these situations, edges were lost. An adaptive model parameter selection method is provided that maintains sharp edge boundaries in the restored field. This has been successfully applied to images representative of robotic scenarios. In order to accommodate image sequences, the standard 2-D ROMKF model is extended into 3-D by the incorporation of a deterministic component based on previously restored fields. The inclusion of past depth and displacement fields allows a means of incorporating the temporal information into the restoration process. A summary on the conditions that indicate which type of filtering should be applied to a field is provided.

Damour, Kevin T.↗

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗

Automated Management of Small Unmanned Aircraft System (UAS) Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation Systems (UAS) Traffic Management↗

Test Capability Enhancements to the NASA Langley 8-Foot High Temperature Tunnel

The NASA Langley 8-Foot High Temperature Tunnel produces true enthalpy environments simulating flight from Mach 4 to Mach 7, primarily for airbreathing propulsion and aerothermal/thermo-structural testing. Flow conditions are achieved through a methane-air heater and nozzles producing aerodynamic Mach numbers of 4, 5 or 7 and have exit diameters of 8 feet or 4.5 feet. The 12-ft long free-jet test section, housed inside a 26-ft vacuum sphere, accommodates large test articles. Recently, the facility underwent significant upgrades to support hydrocarbon fueled scramjet engine testing and to expand flight simulation capability. The upgrades were required to meet engine system development and flight clearance verification requirements originally defined by the joint NASA-Air Force X-43C Hypersonic Flight Demonstrator Project and now the Air Force X-51A Program. Enhancements to the 8-Ft. HTT were made in four areas: 1) hydrocarbon fuel delivery; 2) flight simulation capability; 3) controls and communication; and 4) data acquisition/processing. The upgrades include the addition of systems to supply ethylene and liquid JP-7 to test articles; a Mach 5 nozzle with dynamic pressure simulation capability up to 3200 psf, the addition of a real-time model angle-of-attack system; a new programmable logic controller sub-system to improve process controls and communication with model controls; the addition of MIL-STD-1553B and high speed data acquisition systems and a classified data processing environment. These additions represent a significant increase to the already unique test capability and flexibility of the facility, and complement the existing array of test support hardware such as a model injection system, radiant heaters, six-component force measurement system, and optical flow field visualization hardware. The new systems support complex test programs that require sophisticated test sequences and precise management of process fluids. Furthermore, the new systems, such as the real-time angle of attack system and the new programmable logic controller enhance the test efficiency of the facility. The motivation for the upgrades and the expanded capabilities is described here.

Harvin, S. F.↗

Design and Performance Evaluation of a UWB Communication and Tracking System for Mini-AERCam

NASA Johnson Space Center (JSC) is developing a low-volume, low-mass, robotic free-flying camera known as Mini-AERCam (Autonomous Extra-vehicular Robotic Camera) to assist the International Space Station (ISS) operations. Mini-AERCam is designed to provide astronauts and ground control real-time video for camera views of ISS. The system will assist ISS crewmembers and ground personnel to monitor ongoing operations and perform visual inspections of exterior ISS components without requiring extravehicular activity (EAV). Mini-AERCam consists of a great number of subsystems. Many institutions and companies have been involved in the R&D for this project. A Mini-AERCam ground control system has been studied at Texas A&M University [3]. The path planning and control algorithms that direct the motions of Mini-AERCam have been developed through the joint effort of Carnegie Mellon University and the Texas Robotics and Automation Center [5]. NASA JSC has designed a layered control architecture that integrates all functions of Mini-AERCam [8]. The research described in this report is part of a larger effort focused on the communication and tracking subsystem that is designed to perform three major tasks: 1. To transmit commands from ISS to Mini-AERCam for control of robotic camera motions (downlink); 2. To transmit real-time video from Mini-AERCam to ISS for inspections (uplink); 3. To track the position of Mini-AERCam for precise motion control. The ISS propagation environment is unique due to the nature of the ISS structure and multiple RF interference sources [9]. The ISS is composed of various truss segments, solar panels, thermal radiator panels, and modules for laboratories and crew accommodations. A tracking system supplemental to GPS is desirable both to improve accuracy and to eliminate the structural blockage due to the close proximity of the ISS which could at times limit the number of GPS satellites accessible to the Mini-AERCam. Ideally, the tracking system will be a passive component of the communication system which will need to operate in a time-varying multipath environment created as the robot camera moves over the ISS structure. In addition, due to many interference sources located on the ISS, SSO, LEO satellites and ground-based transmitters, selecting a frequency for the ISS and Mini-AERCam link which will coexist with all interferers poses a major design challenge. To meet all of these challenges, ultrawideband (UWB) radio technology is being studied for use in the Mini-AERCam communication and tracking subsystem. The research described in this report is focused on design and evaluation of passive tracking system algorithms based on UWB radio transmissions from mini-AERCam.

Barton, Richard J.↗

Navier-Stokes Simulation of Airconditioning Facility of a Large Modem Computer Room

NASA recently assembled one of the world's fastest operational supercomputers to meet the agency's new high performance computing needs. This large-scale system, named Columbia, consists of 20 interconnected SGI Altix 512-processor systems, for a total of 10,240 Intel Itanium-2 processors. High-fidelity CFD simulations were performed for the NASA Advanced Supercomputing (NAS) computer room at Ames Research Center. The purpose of the simulations was to assess the adequacy of the existing air handling and conditioning system and make recommendations for changes in the design of the system if needed. The simulations were performed with NASA's OVERFLOW-2 CFD code which utilizes overset structured grids. A new set of boundary conditions were developed and added to the flow solver for modeling the roomls air-conditioning and proper cooling of the equipment. Boundary condition parameters for the flow solver are based on cooler CFM (flow rate) ratings and some reasonable assumptions of flow and heat transfer data for the floor and central processing units (CPU) . The geometry modeling from blue prints and grid generation were handled by the NASA Ames software package Chimera Grid Tools (CGT). This geometric model was developed as a CGT-scripted template, which can be easily modified to accommodate any changes in shape and size of the room, locations and dimensions of the CPU racks, disk racks, coolers, power distribution units, and mass-storage system. The compute nodes are grouped in pairs of racks with an aisle in the middle. High-speed connection cables connect the racks with overhead cable trays. The cool air from the cooling units is pumped into the computer room from a sub-floor through perforated floor tiles. The CPU cooling fans draw cool air from the floor tiles, which run along the outside length of each rack, and eject warm air into the center isle between the racks. This warm air is eventually drawn into the cooling units located near the walls of the room. One major concern is that the hot air ejected to the middle isle might recirculate back into the cool rack side and cause thermal short-cycling. The simulations analyzed and addressed the following important elements of the computer room: 1) High-temperature build-up in certain regions of the room; 2) Areas of low air circulation in the room; 3) Potential short-cycling of the computer rack cooling system; 4) Effectiveness of the perforated cooling floor tiles; 5) Effect of changes in various aspects of the cooling units. Detailed flow visualization is performed to show temperature distribution, air-flow streamlines and velocities in the computer room.

Source record↗

Evidence Report: Risk of Hypobaric Hypoxia from the Exploration Atmosphere

Extravehicular activity (EVA) is at the core of a manned space exploration program. Some elements of exploration may be safely and effectively performed by robots, but certain critical elements will require the trained, assertive, and reasoning mind of a human crewmember. To effectively use these skills, NASA needs a safe, effective, and efficient EVA component integrated into the human exploration program. The EVA preparation time should be minimized and the suit pressure should be low to accommodate EVA tasks without causing undue fatigue, physical discomfort, or suit-related trauma. Commissioned in 2005, the Exploration Atmospheres Working Group (EAWG) had the primary goal of recommending to NASA an internal environment that allowed efficient and repetitive EVAs for missions that were to be enabled by the former Constellation Program. At the conclusion of the EAWG meeting, the 8.0 psia and 32% oxygen (O2) environment were recommended for EVA-intensive phases of missions. After re-evaluation in 2012, the 8/32 environment was altered to 8.2 psia and 34% O2 to reduce the hypoxic stress to a crewmember. These two small changes increase alveolar O2 pressure by 11 mmHg, which is expected to significantly benefit crewmembers. The 8.2/34 environment (inspired O2 pressure = 128 mmHg) is also physiologically equivalent to the staged decompression atmosphere of 10.2 psia / 26.5% O2 (inspired O2 pressure = 127 mmHg) used on 34 different shuttle missions for approximately a week each flight. As a result of selecting this internal environment, NASA gains the capability for efficient EVA with low risk of decompression sickness (DCS), but not without incurring the additional negative stimulus of hypobaric hypoxia to the already physiologically challenging spaceflight environment. This report provides a review of the human health and performance risks associated with the use of the 8.2 psia / 34% O2 environment during spaceflight. Of most concern are the potential effects on the central nervous system (CNS), including increased intracranial pressure, visual impairment, sensorimotor dysfunction, and oxidative damage. Other areas of focus include validation of the DCS mitigation strategy, incidence and treatment of transient acute mountain sickness (AMS), development of new exercise countermeasure protocols, effective food preparation at 8.2 psia, assurance of quality sleep, and prevention of suit-induced injury. Although missions proposing to use an 8.2/34 environment are still years away, it is recommended that these studies begin early enough to ensure that the correct decisions pertaining to vehicle design, mission operational concepts, and human health countermeasures are appropriately informed.

Norcross, Jason R.↗

Configuring the Orion Guidance, Navigation, and Control Flight Software for Automated Sequencing

The Orion Crew Exploration Vehicle is being designed with greater automation capabilities than any other crewed spacecraft in NASA s history. The Guidance, Navigation, and Control (GN&C) flight software architecture is designed to provide a flexible and evolvable framework that accommodates increasing levels of automation over time. Within the GN&C flight software, a data-driven approach is used to configure software. This approach allows data reconfiguration and updates to automated sequences without requiring recompilation of the software. Because of the great dependency of the automation and the flight software on the configuration data, the data management is a vital component of the processes for software certification, mission design, and flight operations. To enable the automated sequencing and data configuration of the GN&C subsystem on Orion, a desktop database configuration tool has been developed. The database tool allows the specification of the GN&C activity sequences, the automated transitions in the software, and the corresponding parameter reconfigurations. These aspects of the GN&C automation on Orion are all coordinated via data management, and the database tool provides the ability to test the automation capabilities during the development of the GN&C software. In addition to providing the infrastructure to manage the GN&C automation, the database tool has been designed with capabilities to import and export artifacts for simulation analysis and documentation purposes. Furthermore, the database configuration tool, currently used to manage simulation data, is envisioned to evolve into a mission planning tool for generating and testing GN&C software sequences and configurations. A key enabler of the GN&C automation design, the database tool allows both the creation and maintenance of the data artifacts, as well as serving the critical role of helping to manage, visualize, and understand the data-driven parameters both during software development and throughout the life of the Orion project.

Odegard, Ryan G.↗