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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Applications and Innovations for Use of High Definition and High Resolution Digital Motion Imagery in Space Operations

The first live High Definition Television (HDTV) from a spacecraft was in November, 2006, nearly ten years before the 2016 SpaceOps Conference. Much has changed since then. Now, live HDTV from the International Space Station (ISS) is routine. HDTV cameras stream live video views of the Earth from the exterior of the ISS every day on UStream, and HDTV has even flown around the Moon on a Japanese Space Agency spacecraft. A great deal has been learned about the operations applicability of HDTV and high resolution imagery since that first live broadcast. This paper will discuss the current state of real-time and file based HDTV and higher resolution video for space operations. A potential roadmap will be provided for further development and innovations of high-resolution digital motion imagery, including gaps in technology enablers, especially for deep space and unmanned missions. Specific topics to be covered in the paper will include: An update on radiation tolerance and performance of various camera types and sensors and ramifications on the future applicability of these types of cameras for space operations; Practical experience with downlinking very large imagery files with breaks in link coverage; Ramifications of larger camera resolutions like Ultra-High Definition, 6,000 [pixels] and 8,000 [pixels] in space applications; Enabling technologies such as the High Efficiency Video Codec, Bundle Streaming Delay Tolerant Networking, Optical Communications and Bayer Pattern Sensors and other similar innovations; Likely future operations scenarios for deep space missions with extreme latency and intermittent communications links.

Grubbs, Rodney↗
NASA NTRS2017

Modeling Meteor Flares for Spacecraft Safety

NASA's Meteoroid Environment Office (MEO) is tasked with assisting spacecraft operators and engineers in quantifying the threat the meteoroid environment poses to their individual missions. A more complete understanding of the meteoroid environment for this application requires extensive observations. One manner by which the MEO observes meteors is with dedicated video camera systems that operate nightly. Connecting the observational data from these video cameras to the relevant physical properties of the ablating meteoroids, however, is subject to sizable observational and theoretical uncertainties. Arguably the most troublesome theoretical uncertainty in ablation is a model for the structure of meteoroids, as observations clearly show behaviors wholly inconsistent with meteoroids being homogeneous spheres. Further complicating the interpretation of the observations in the context of spacecraft risk is the ubiquitous process of fragmentation and the flares it can produce, which greatly muddles any attempts to estimating initial meteoroid masses. In this talk a method of estimating the mass distribution of fragments in flaring meteors using high resolution video observations will be dis- cussed. Such measurements provide an important step in better understanding of the structure and fragmentation process of the parent meteoroids producing these flares, which in turn may lead to better constraints on meteoroid masses and reduced uncertainties in spacecraft risk.

Ehlert, Steven↗
NASA NTRS2017

Development and Testing of Harpoon-Based Approaches for Collecting Comet Samples

Comets, having bright tails visible to the unassisted human eye, are considered to have been known about since pre-historic times. In fact 3,000-year old written records of comet sightings have been identified. In comparison, asteroids, being so dim that telescopes are required for observation, were not discovered until 1801. Yet, despite their later discovery, a space mission returned the first samples of an asteroid in 2010 and two more asteroid sample return missions have already been launched. By contrast no comet sample return mission has ever been funded, despite the fact that comets in certain ways are far more scientifically interesting than asteroids. Why is this? The basic answer is the greater difficulty, and consequently higher cost, of a comet sample return mission. Comets typically are in highly elliptical heliocentric orbits which require much more time and propulsion for Space Craft (SC) to reach from Earth and then return to Earth as compared to many asteroids which are in Earth-like orbits. It is also harder for a SC to maneuver safely near a comet given the generally longer communications distances and the challenge of navigating in the comet's, when the comet is close to perihelion, which turns out to be one of the most interesting times for a SC to get close to the comet surface. Due to the science value of better understanding the sublimation of volatiles near the comet surface, other contributions to higher cost as desire to get sample material from both the comet surface and a little below, to preserve the stratigraphy of the sample, and to return the sample in a storage state where it does not undergo undesirable alterations, such as aqueous. In response to these challenges of comet sample return missions, the NASA Goddard Space Flight Center (GFSC) has worked for about a decade (2006 to this time) to develop and test approaches for comet sample return that would enable such a mission to be scientifically valuable, while having acceptably low risk and an affordable cost. A harpoon-based approach for gathering comet samples appears to offer the most effective way of accomplishing this goal. As described below, with a decade of development, analysis, testing and refinement, the harpoon approach has evolved from a promising concept to a practical element of a realistic comet sample return mission. Note that the following material includes references to videos, all of which are contained in different sections of the video supplement identified in the references. Each video will be identified as "SS##", where "SS" means the supplement section and "##" will be the number of the section.

Purves, Lloyd↗
NASA NTRS2015

ATM Technology Demonstration 1 (ATD-1) Project: Terminal Airspace Technologies for NextGen (Public)

This video highlights the human-in-the-loop (HITL) simulations conducted by the ATD-1 project and features visual elements developed for Traffic Management Advisor - Terminal Metering, Controller Managed Spacing, and Flight Deck Interval Management. The video content is fairly technical and intended for audiences that have some knowledge of air traffic management issues. This includes researchers and management from NASA, FAA, industry partners, and others interested in terminal metering, controller managed spacing, and interval management technologies. Please note that the media release only clears the video for peer audiences such as ATM conferences or as part of presentations to researchers.

Robinson, John E.↗
NASA NTRS2018

Applications of Phase-Based Motion Processing

Image pyramids provide useful information in determining structural response at low cost using commercially available cameras. The current effort applies previous work on the complex steerable pyramid to analyze and identify imperceptible linear motions in video. Instead of implicitly computing motion spectra through phase analysis of the complex steerable pyramid and magnifying the associated motions, instead present a visual technique and the necessary software to display the phase changes of high frequency signals within video. The present technique quickly identifies regions of largest motion within a video with a single phase visualization and without the artifacts of motion magnification, but requires use of the computationally intensive Fourier transform. While Riesz pyramids present an alternative to the computationally intensive complex steerable pyramid for motion magnification, the Riesz formulation contains significant noise, and motion magnification still presents large amounts of data that cannot be quickly assessed by the human eye. Thus, user-friendly software is presented for quickly identifying structural response through optical flow and phase visualization in both Python and MATLAB.

Branch, Nicholas A.↗
NASA NTRS2018

General Aviation Citizen Science Study to Help Tackle Remote Sensing of Harmful Algal Blooms (HABs)

We present a new, low-cost approach, based on volunteer pilots conducting high-resolution aerial imaging, to help document the onset, growth, and outbreak of harmful algal blooms (HABs) and related water quality issues in central and western Lake Erie. In this model study, volunteer private pilots acting as citizen scientists frequently flew over 200 mi of Lake Erie coastline, its islands, and freshwater estuaries, taking high-quality aerial photographs and videos. The photographs were taken in the nadir (vertical) position in red, green, and blue (RGB) and near-infrared (NIR) every 5 s with rugged, commercially available built-in Global Positioning System (GPS) cameras. The high-definition (HD) videos in 1080p format were taken continuously in an oblique forward direction. The unobstructed, georeferenced, high-resolution images, and HD videos can provide an early warning of ensuing HAB events to coastal communities and freshwater resource managers. The scientists and academic researchers can use the data to compliment a collection of in situ water measurements, matching satellite imagery, and help develop advanced airborne instrumentation, and validation of their algorithms. This data may help develop empirical models, which may lead to the next steps in predicting a HAB event as some watershed observed events changed the water quality such as particle size, sedimentation, color, mineralogy, and turbidity delivered to the Lake site. This paper shows the efficacy and scalability of citizen science (CS) aerial imaging as a complimentary tool for rapid emergency response in HABs monitoring, land and vegetation management, and scientific studies. This study can serve as a model for monitoring/management of freshwater and marine aquatic systems.

Ansari, Rafat R.↗
NASA NTRS2018

Enabling Technologies for Deep Space Motion Imagery

From the beginning of the Space Age, imagery, particularly motion imagery, has been a part of crewed and uncrewed missions. As technologies have evolved the imagery gets better, more compelling, and more useful for operations and monitoring of systems, crew, and spacecraft. Film, video and live television have engaged the public and sparked the imaginations of engineers, scientists, and artists alike. As we look forward now to crewed missions beyond low-Earth orbit, such as the Deep Space Gateway being considered as a pre-cursor to future crewed Mars missions, there are both opportunities and challenges in implementing a multi-faceted imaging system that advances mission capabilities and technology.This paper will present a vision for an imaging system that is relevant for operations of the ISS and future crewed missions in deep space, with a detailed look at some of the key innovative technologies required to enable such a system. In addition, impacts to Space Operations, video distribution to the public and to science investigators, and video system interoperability will be presented. Opportunities where standardization can enable interoperability are also identified for those imagery and communications functions planned for inclusion in the Consultative Committee for Space Data Systems (CCSDS) Blue Book.

Grubbs, Rodney↗
NASA NTRS2014

Maiden Voyage of the Rodent Habitat on ISS: Opportunities for Investigating Molecular Mechanisms and Biomedical Consequences of Long Duration Spaceflight

Research using rodents is an essential tool for advancing biomedical research on Earth and in space. The National Research Counsel’s Decadal survey (1) emphasized the importance of expanding NASAs life sciences research to perform long duration, rodent experiments on the International Space Station (ISS). To accomplish this objective, flight hardware, operations, and science capabilities were developed at NASA ARC to support both commercial and government-sponsored research. In preparation for the maiden voyage of the Rodent Habitat hardware and operations system (Rodent Research-1), and in close consultation with a Science Working Group comprised of veterinarians and experienced spaceflight investigators, we modified existing Animal Enclosure Module hardware, developed new hardware, operations, and science activities, and performed a series of ground-based verification tests. Preflight, ground based hardware tests included a simulation of SpaceX Dragon launch conditions (vibration and hypergravity) using the Transporter, and also two long-term biocompatibility tests (32 and 92 days) using the Habitat developed for long term housing on the ISS. The launch simulation test showed that adult mice housed in Transporter hardware adapted well, even if launch simulation was followed by a period of simulated weightlessness (via hind limb unloading). The biocompatibility tests demonstrated that the Habitat successfully supported animal health and also provided a useful video imaging system that enables frequent monitoring of animal health and behavior by veterinary and scientific experts on the ground, independent of ISS crew intervention. At the conclusion of all tests, mice were deemed healthy and suitable for conducting biological research. Additional preflight analyses of tissues preserved by freezing or fixation for gene expression analyses revealed that spleen and liver tissues recovered under conditions that simulated on-orbit activities yielded high quality RNA (RIN values 8-10) and liver enzyme activities and protein content (e.g. catalase). In addition, new methods were developed to optimize future science return by dissecting tissues post-euthanasia and storage. Various tissues were harvested from either intact or partially dissected, frozen carcasses after storage for ~2-6 months; most of the tissues (brain, heart, kidney, eye, adrenal glands and skeletal muscle) were of high RNA quality for science return, whereas some tissues (small intestine, bone marrow and bones) were not. These data demonstrated the protocols developed for future flight experiments supported science return despite delayed preservation post-euthanasia or prolonged storage, and furthermore, that high-quality RNA samples from many different tissues can be recovered by dissection following prolonged storage of the tissue in situ at -80˚C. The first flight experiments carrying 20 mice were launched on Sept 21, 2014 in an unmanned Dragon Capsule, SpaceX4; Rodent Research-1 is dedicated to achieving both NASA validation and CASIS science objectives. Ground based control groups (housed in flight hardware or standard cages) were maintained in environmental chambers at Kennedy Space Center. Crewmembers previously trained in animal handling transferred mice from the Transporter into Habitats under simultaneous veterinary supervision by video streaming and were deemed healthy. Health and behavior of all mice on the ISS was monitored by video feed on a daily basis. The 10 mice for validation (16wk old, female C57Bl6/J) ambulated freely and actively throughout the Habitat, relying heavily on their forelimbs for locomotion. The first on-orbit dissections of mice were performed successfully on Oct 12 and 13, 2014, and the validation mice will reside on ISS for up to 30 days. In conclusion, new capability for long duration rodent research is under development, including in-flight sample collection (which avoids the complication of reentry); results obtained to date will be described. This new Rodent Research system enables achievement of both basic science and translational research objectives to advance human exploration of space.

maiden voyage↗
NASA NTRS2019

Operations of the Optical Communications Demonstration for the Orion EM-2 Mission

The GSFC implementation of an Optical Communication System to demonstrate an operational optical communication link for Orion EM-2. It will serve as a base for providing an operational optical communications capability for future Orion missions. GSFC plans to maintain a development path for the optical communication flight terminal to allow commercialization and implementation on future Orion missions. The Orion optical module part of the optical communications flight terminal and its control electronics have a common architecture with the ILLUMA-T optical terminal provided by GSFC for use on the ISS. The plan is to flow data from Orion through the Optical Communication Fight Terminal to the Optical Communication Ground Terminal and reverse. NASA's Orion spacecraft is an exploratory vehicle designed for longer-duration flights beyond the Moon. Following Orion's Exploration Mission-1 (EM-1), during which the spacecraft will travel beyond the Moon, enter a distant retrograde orbit around the Moon and return to Earth unmanned, Exploration Mission-2 (EM-2) will see a crewed spacecraft complete a slightly different flight path. First crewed test flight of the Orion spacecraft, currently targeting a June 30, 2022 launch. The mission involves: One revolution in Low Earth Orbit (LEO) parking orbit to verify basic Orion systems functionality and deploy solar arrays. A single 42-hour Highly Elliptical Orbit (HEO) intermediate checkout orbit allows characterization of the Orion vehicle system performance prior to committing to a cis-lunar flight. Trans Lunar Injection (TLI) burn using Orion Service Module (SM) main engine, which sends Orion on a lunar flyby and free return. Skip reentry at lunar return velocities to splashdown off the coast of San Diego. Total mission duration is approximately 10 days. EM-2 is the first crewed mission of the Orion Spacecraft that crew brings more video up/downloads, file transfers, and real-time chats with family back home and high-rate communications enables live HD streaming for Crew conferences, Public Affairs Office (PAO) events, and significant mission events. Also still collecting vehicle data on numerous Orion subsystems via Development Flight Instrumentation (DFI) allows large data volume returns sooner for DFI and future science payloads, as opposed to waiting for end-of-mission. O2O is a demonstration of operational utility system tested as a Developmental Test Objective (DTO) and not required to meet mission requirements/success/ Flight Test Objectives (FTO). EM-2 architecture is as close to future mission operational architecture as possible.Orion subsystems (video, DFI, etc.) expected to generate ~250 GB of data in the first 24 hours of flight. Total data generated over the mission estimated to be more than 400 GBUsing S-Band alone, Orion limited to ~ 6GB of data downlink per day. Because of this limitation, Orion is planning to limit live video downlinks on EM-1 in order to downlink high priority fileswith 1 hour/day of Optical Communication, Orion could downlink ~6x more data per day (~ 36GB/day).The optical communication system is capable of multiple data rates up to at least 80 Mbps downlink for the transfer of Orion data to Earth while Orion is operating in the lunar vicinity.

Optical Communication↗
NASA NTRSDate not supplied

We Are All Potential Role Models: How We Can Support Scientist Engagement with Youth and the General Public

We all have the opportunity to be positive STEM role models. Yet scientists rarely identify themselves as a possible role model. In the training, “Empowering Effective STEM Role Models,” scientists practice research based strategies for engaging youth, particularly girls. This type of training is complementary to science communication, but is focused on equipping scientists with the skills needed to successfully encourage youth to pursue STEM careers. This training has been provided to over 150 STEM professionals at NASA and 14 federal agencies participated in a Train-the-Trainer version, organized by the White House Council for Women and Girls in STEM Working Group. Participants in this training reported that learning and practicing how to connect with and inspire children in STEM made them more confident stepping into further engagement opportunities. Confident, inspiring scientists are a highlight of a successful engagement event, but other factors make a positive experience possible.It’s important that all partners are thoughtful and intentional in preparing for public engagement events. The logistics are crucial, especially now while many engagements have moved to virtual platforms. Additional technology considerations make preparation essential. Two examples of virtual engagement highlight the support provided that led to successful engagements. The GLOBE Mission Earth project engages scientists in virtual classroom visits. To ensure both teacher and scientist expectations are met, a coordinator facilitates up front preparation by providing slide templates for the scientist to customize and providing video and other resources to the teacher and students to prompt student questions. Another example leverages the power of social media, particularly NASA Facebook. The NASA Earth Science Education Collaborative organizes citizen science challenges and engages the public on social. For one event, scientists were asked to share their connection to the investigation, but without access to NASA’s video production studio, the plans shifted. Scientists prepared audio files instead of videos and collaborated with communications leads to help craft their message. This weekly series has been flexible, adjusting to scientist's comfort levels, and has resulted in fresh and creative engagement.

Jessica Elaine Taylor↗
NASA NTRSDate not supplied

Battery Failure Databank

The Battery Failure Databank contains thermal runaway results gathered from nearly 300 small format fractional thermal runaway calorimetry (S-FTRC) experiments. A majority of these experiments were conducted at synchrotron facilities where high-speed x-ray videography was conducted of the cell while tested inside of the S-FTRC. The databank is a two-component system which consists of a Microsoft ExcelTM spreadsheet which provides S-FTRC results in tabular format and a radiographic video library containing the high-speed x-ray videos. Overall, the databank provides thermal results from S-FTRC experiments conducted on a mixture of commercially available lithium-ion (Li-ion) cells and specialized Li-ion test cells with varying cell format (18650, 21700, and D-cell) and trigger mechanism (heaters, heaters plus internal short circuiting device, and nail penetration). The radiography video component provides insight into the initiation and propagation of TR in the cells, in addition to consequences of TR measured by the FTRC. Fractions of mass ejected for the cell types are separated into regimes based on the different failure modes of the cells, such as purely venting, partial ejection, and total ejection. With knowledge of the rate and characterization of the internal degradation of the cells during TR, and the amounts of mass ejected and unrecovered, the extent of TR, and therefore the mitigation of TR, is revealed relative to cell types and failure modes.

Lithium-ion battery↗
NASA NTRS2018

Predicting Rapid Fire Growth (Flashover) Using Generative Adversarial Networks

A flashover occurs when a fire spreads very rapidly through crevices due to intense heat. Flashovers present one of the most frightening and challenging fire phenomena to those who regularly encounter them: firefighters. Firefighters’ safety and lives often depend on their ability to predict flashovers before they occur. Typical pre-flashover fire characteristics include dark smoke, high heat, and rollover (“angel fingers”) and can be quantified by color, size, and shape. Using a color video stream from a firefighter’s body camera, we applied generative adversarial neural networks for image enhancement. The neural networks were trained to enhance very dark fire and smoke patterns in videos and monitor dynamic changes in smoke and fire areas. Preliminary tests with limited flashover training videos showed that we predicted a flashover as early as 55 seconds before it occurred.

Lu, Thomas↗
NASA NTRSDate not supplied

Visualizing UPSP Data with Python

The Unsteady Pressure-Sensitive Paint (uPSP) projects uses Pressure-Sensitive paint applied over aerospace models during wind tunnel testing to collect pressure data with high spatial and temporal resolution in order to inform unsteady aerodynamics studies. For each of the 800+ experimental runs, four cameras generate up to 50 GB of video data, which must then be processed, analyzed, and visualized on the NASA Advanced Supercomputing system (NAS) to assess the result. One of the final data analysis products is the dynamic modal decomposition (DMD) results, which decomposes the pressure reading signals by their frequency component. The goal of this project is to visualize the DMD results over a 3D rendering of the model, using efficient and parallelized python routines. The software uses the pytecplot library, a high-level API that connects python scripting to a Tecplot 360 engine. Tecplot is an industry standard high-performance visualization tool that can handle large datasets and workflow. Various animation, rendering, and image-combination techniques were investigated to generate the final videos using OpenCV on the NAS. The final result is a software tool that takes in data products from the uPSP processing chain and generates high resolution visualization videos in parallel for every data file, allowing researchers to view their results efficiently and at an unprecedentedly detailed level.

Emma Dolores McMillian↗
NASA NTRSDate not supplied

Shoulder Postures in EVA Training in Reduced Gravity Analogues

Shoulder Postures in EVA Training in Reduced Gravity Analogues K. Guhl1, L. Vu2, H. Kim3, S. Rajulu4 1KBR Inc., Houston, TX, 2Aegis Aerospace Inc., Houston, TX, 3Leidos Innovations, Houston, TX, 4NASA Johnson Space Center, Houston, TX. During extravehicular activities (EVAs) and EVA training in both the Neutral Buoyancy Laboratory (NBL) and at the Active Response Gravity Offload System (ARGOS), crewmembers perform a variety of hand-intensive tasks with frequent arm/shoulder repositioning while wearing a pressurized spacesuit. As a result, crewmembers may experience ergonomic stressors such as awkward shoulder postures. The ergonomic shoulder risk is also compounded by limited or restricted shoulder mobility of the spacesuit, extreme work positions such as overhead tasks, and tasks with heavy tools and repetitive motions. Prolonged or frequent shoulder elevation and overhead work, in particular, can lead to excessive stresses and musculoskeletal injuries of the shoulder joints. Future EVA missions, specifically lunar surface EVAs, will also be longer in duration and thus increase the exposure to awkward shoulder postures. In this study, we aimed to assess the ergonomic risk of awkward shoulder postures in simulated lunar surface EVAs by quantifying when and how long the arms are raised above the chest level. We assessed video recordings of pilot lunar EVA simulations (3 lunar trials each in the NBL and at ARGOS and 2 microgravity EVA trials in the NBL). These runs consisted of both training and engineering test objectives. Actual demands for shoulder use varied for different EVA types and analogues, but many EVA runs have common tasks and require similar motion components. A video observation and event logging software was used to document the duration and occurrence of the subject’s arms being raised throughout the video recordings of each EVA run. An arm raised instance was classified as the arm being at 90 degrees or above with relation to gravity for lunar EVA training events and with relation to the body for microgravity EVA training events. Such events included EVA hardware maintenance or heavy geology sampling tool operations. Events where the arm load was partially supported by external objects, like climbing a ladder or leaning against a surface were separately identified and excluded. Statistical analysis was performed to summarize the timing, frequency, and durations of the arm raise events and compared across the different EVA tasks and analogue types. Preliminary observations indicated that the total duration and number of arm raised instances were surprisingly smaller for lunar surface EVA training as compared to microgravity EVA training. The observed difference may be attributed to differing task demands and unique environmental characteristics found in lunar EVAs in comparison to microgravity EVAs. A detailed statistical analysis will be performed between lunar surface EVA training events and microgravity EVA training events in the final submission. Overall, this analysis is expected to provide insight into how ergonomic recommendations can be refined for lunar EVA training with pressurized suits. It may also inform task design and influence suit padding design to better protect crewmembers during future lunar training.

Kaitlyn Lea Guhl↗
NASA NTRSDate not supplied

The Sun and Space Weather

Audio and video provided as separate files. • CHART 3 audio – “SrFeb022013_1954ut28.21_Ashcraft.mp3” • CHART 9 Sun video – “IA18167_304Whip_best.mpg” • CHART 15 sun animation – “Sun_Animation_Mar23A.mp4” • CHART 33 SDO plus SOHO C2 video – “X2_C2_combo.mov”

Sun↗
NASA NTRSDate not supplied

Learning About Routine Successful Pilot Techniques Using A Cued Retrospective Think-Aloud Task

Self-report can be a valuable method for collecting data about people’s goals and perceived motivations – data about aspects of crew thinking that are not otherwise readily observable. One of the challenges associated with collecting self-report data on routine successful performance, however, is that details may go unreported, be deemed unimportant, or may not be recalled. We report a study in which commercial airline flight crews participated in a video-cued retrospective think aloud after flying a high-fidelity simulated arrival into Charlotte airport. One day after flying the simulated arrival, crews were shown a video recording of their flight. The video was paused after each minute, and crew members were each asked to describe what they were doing and thinking during that interval. Reported data analysis focused on aspects of performance that are often ambiguously described as “pilot technique” or “airmanship,” in an attempt to provide more detail around these types of behaviors.

Jon Holbrook↗
NASA NTRS2022

“Just Do It” Mission Operations Training in a COVID World

“No”- “not”- “can’t do it” – these words don’t fly in M2020 Mission Operations. The M2020 Surface Mission Operations Team trained for landing the Perseverance Rover under COVID-19 remote work/mandatory stay-at-home conditions. Training activities included presenting Flight Schools to the team via video conferencing, training COVID personal safety requirements to on-premises staff, and constantly updating and communicating COVID restrictions to the team as safety requirements changed. This paper explores the impact of COVID on the Mission System Training for M2020 Mission Operations. The layers of COVID, aptly named the “COVID Tax” by team management, affected project roles, communications, personnel interactions, operations facility usage and training exercises practiced by the team. Flight Schools and Operational Readiness Tests (ORTs) are driving forces behind the surface mission operations training. These activities work hand-in-hand to prepare the team for landing day, surface operations that transition from cruise to nominal operations, and nominal operations. Under normal training conditions, Flight Schools and ORTs are only concerned with tactical operations for the Uplink (Command) Downlink (Analysis) and Campaign Implementation (Planning) Teams of scientists and system engineers. Due to COVID, and the necessity to maintain physical distance between people, training for the landing team needed to include the new category of COVID personal safety. COVID also necessitated remote teams and video conferencing of the entirety of Flight Schools. This reliance on distance learning had not been done on previous missions. We will explore the advantages and disadvantages of video conferencing as a training platform; training effectiveness in communicating and practicing the multiple changes to the COVID safety protocols; and the timing in which we received and responded to COVID directives. Additionally, this paper will review the practical measures taken by the on-premises team and how the team adapted during the readiness tests, landing, and early mission operations, as well as how the team responded to the post-vaccine ramping down of COVID Protocols. The M2020 Surface Mission Operations Team responded very well to the challenges of COVID. All pre-landing operational and COVID-related training was completed. Post-landing COVID Training was provided as needed to new on-premises personnel. Training presented on COVID for the first operational readiness test (ORT) consisted of 2.5 hours of training. Each ORT had COVID Training. A person who had participated in all of the ORTs from September 2020 – February 2021 would have received over 7 hours of COVID Training. By ORT-12 (approximately 8 weeks after the first ORT), the Training team consolidated the original COVID training to a one-hour COVID Basic Training course, with additional recommended training. The Basic training course was updated after landing, as vaccines became available. COVID Training had multiple Flight Schools in the self-directed Blackboard Learning system, as well as a Quick Reference Wiki for Onboarding of new on-premises personnel and keeping on-premises personnel up-to-date. COVID Training covered many topics including practical methods of 6-foot distancing, how to interact with an IT professional when help was needed at a workstation, and challenging indoor meal-eating protocols. COVID Training continued to be updated, as the lab and the project respond to the virus variants and federal, state and local ordinances.

Rosette, Theresa↗
NASA NTRSDate not supplied

ArcjetCV: Automating Recession Tracking

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗