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NASA NTRS2018

Stereo Imaging Miniature Endoscope with Single Imaging Chip and Conjugated Multi-Bandpass Filters

A dual objective endoscope for insertion into a cavity of a body for providing a stereoscopic image of a region of interest inside of the body including an imaging device at the distal end for obtaining optical images of the region of interest (ROI), and processing the optical images for forming video signals for wired and/or wireless transmission and display of 3D images on a rendering device. The imaging device includes a focal plane detector array (FPA) for obtaining the optical images of the ROI, and processing circuits behind the FPA. The processing circuits convert the optical images into the video signals. The imaging device includes right and left pupil for receiving a right and left images through a right and left conjugated multi-band pass filters. Illuminators illuminate the ROI through a multi-band pass filter having three right and three left pass bands that are matched to the right and left conjugated multi-band pass filters. A full color image is collected after three or six sequential illuminations with the red, green and blue lights.

Shahinian, Hrayr Karnig↗
NASA NTRS2017

Immersive Simulations and Engineering Environment (iSEE)

In January 2017, the Immersive Simulations and Engineering Environment (iSEE), formally known as the Human Factor Tool (HFT), was brought back online. Since August, the lab had been operating at a nominal status, but with dated hardware. An evaluation was done on the present system so that the improvements and capabilities brought about by the upgrades can be quantified. Immediately following the analysis, evaluations with human factor engineers were performed and some upgrades were implemented. Due to a malfunction with a crucial piece of hardware, the lab was reconfigured temporarily. This allowed easy analysis and integration of various other components which improved the laboratories overall performance. Soon after, work began on creating a video to showcase the capabilities of the lab. This video not only served to show the actual functions of the lab, but also show the expanded capabilities the new hardware and software made available. Skills were acquired throughout the renovation process in various fields, all of which were crucial to not only implementing the updates to the lab, but understanding how they will improve it.

Motion Capture↗
NASA NTRS2018

The History & Evolution of Spacesuits and Spacewalks - Walking in Space

The presentation and videos that will be included in this technology talk will summarize the basic functions of spacesuits, the evolution of spacesuit design, and the development plans for future exploration spacesuits. The videos will run in a loop with no audio. The speakers will generally follow the slide presentation. There will be a 5-minute intro on basic suit functions, followed by a 7-10 minute discussion on suit history and evolution, then 7-10 minutes to cover the current ISS (International Space Station) suit and the development of the next generation exploration spacesuits. That will leave around 5-10 minutes for questions and answers.

Hughes, David↗
NASA NTRS2018

Automated Pneumothorax Diagnosis using Deep Neural Networks

Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.

US Army collaboration↗
NASA NTRS2019

BioBot: Innovative Offloading of Astronauts for More Effective Exploration

The BioBot concept consists of a robotic rover which is capable of traversing the same terrain as a spacesuited human. It carries the primary life support system for the astronaut, including consumables, atmosphere revitalization systems (e.g., CO2 scrubbing, humidity and temperature management, ventilation fan), power system (e.g., battery, power management and distribution),and thermal control system (e.g., water sublimator, cooling water pump), along with umbilical lines to connect to the supported astronaut. Although not technically part of life support, it would be logical for the BioBot to also provide long-range communications, video monitoring, tool and sample transport, and other functions to enable and enhance EVA productivity in planetary surface exploration.The design reference scenario for this concept is that astronauts involved in future lunar or Mars exploration will be on the surface for weeks or months rather than days, and will be involved in regular EVA operations. It is not unreasonable to think of geologists spending several days inEVA exploration each week over a prolonged mission duration, with far more ambitious operational objectives than were typical of Apollo. In this scenario, each astronaut will be accompanied by a "BioBot", which will transport their life support system and consumables, an extended umbilical and umbilical reel, and robotic systems capable of controlling the position and motion of the umbilical. The astronaut will be connected to the robot via the umbilical, carrying only a small emergency open-loop life support system similar to those contained in every PLSS. The robotic mobility base will be designed to be capable of traveling anywhere the astronaut can walk, and will also be useful as a transport for the EVA tools, science instrumentation, and collected samples. In addition, the BioBot can potentially carry the astronaut on traverses as well. Such a system will also be a significant enhancement to public engagement in these future exploration missions, as the robotic vehicles can also support high-resolution cameras and high bandwidth communications gear to providehigh-definition video coverage of each crew throughout each EVA sortie.

Akin, David L.↗
NASA NTRS2019

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan-stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet bulb temperature thresholds were applicable for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applicable to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions.

Veres, Joseph P.↗
NASA NTRS2019

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan- stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet bulb temperature thresholds were applicable for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applicable to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions.

Veres, Joseph P.↗
NASA NTRS2019

NASA KSC Intern Final Report - Virtual Reality in STEM Engagement

For this internship, I was a part of the multi-center NextGen STEM (Science, Technology, Engineering, and Mathematics) pilot. Specifically, I worked with the Developing Commercial Crew Program (CCP) Capabilities team that focuses on human spaceflight to the space station with NASA’s commercial partners. Composed of NASA employees and contractors (who are connected to KSC, JSC, and LaRC), they work to ensure that students will experience traditional classroom content and be immersed in emerging technologies in order to explore Commercial Crew missions and launch facilities. This group is in the process of creating educational products and resources to inspire the next generation to pursue STEM and to allow educators to have access to unique and enticing STEM activities. These products include: age-appropriate classroom lessons (including activity sheets and challenges) for kindergarten through twelfth grade; a CCP app and corresponding guide; learning experiences for students as well as educators; and virtual field trips and tours using NASA-created Virtual Reality (VR) videos and a custom VR app. My particular assignment was managing the VR equipment, developing an understanding of how to maximize the use of the equipment, creating documents that explain and convey the operations and procedures concerning the equipment (including lessons learned from equipment use), and training others to utilize the equipment effectively and correctly for conference events and group demonstrations. Over the course of this internship, I helped my team outline and learn essential procedures of operation for the VR equipment, solved technology problems that arose (due to the nature of creating unique products), and encouraged audiences at KSC and various conferences to consider using the CCP VR videos in their classrooms as an opportunity to engage and challenge the next generation to pursue STEM careers.

STEM↗
NASA NTRS2019

Using Science Operations Tools and Methods from NASA for Remote Presence Ocean Exploration on Earth: E/V Nautilus Cruise NA108

NASA Ames' Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade.In the last two years, we have participated in SUBSEA, a multi-institution collaborative project. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC). In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule.The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team's ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA's Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island's Graduate School of Oceanography (GSO). ISC is GSO's telepresence operations facility.

Lees, David S.↗
NASA NTRS2020

Astrobee "Bumble Bee" 1st On-Orbit Activities

Video highlights of first Astrobee free flyer, Bumble, on-orbit commissioning activities. Includes: unpacking, first wake up, nozzle stress test, JEM mapping, IMU calibration, first flight, first autonomous undock, disturbance rejection test, first autonomous docking, crew tumbling alongside the robot, first long (3m) flight, first autonomous flight, and first autonomous survey. (3 minutes and 57 seconds long video).

Maria G Bualat↗
NASA NTRS2020

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗
NASA NTRS2020

Analysis of the Honeywell Uncertified Research Engine with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to provide operating conditions such that ice would accrete in either the fan-stator through the inlet guide vane region of the compression system or within the first stator of the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDESMELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan-stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet-bulb temperature thresholds were applied for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applied to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions. The goal of this study is to show that the computational process developed on earlier engine icing tests can be used to provide an icing risk assessment in adiabatic regions for other engines.

Turbofan engine↗
NASA NTRSDate not supplied

Measurement of material recession and shock standoff in plasma windtunnel using neural nets

Arcjets are plasma wind tunnels used to test the performance of heatshield materials for spacecraft atmospheric entry. These facilities present an extremely harsh flow environment with heat fluxes up to 10^9 W/m^2 for up to 30 minutes. The plasma is low-temperature (~1 eV) but high pressure (> 10 kPa) creating high-enthalpy supersonic flows similar to atmospheric entry conditions. Typically, material samples are measured before and after a test to characterize the total recession. However, this does not capture time-dependent effects such as material expansion and non-linear recession. This work will present new analysis of arcjet test videos which measure both the time-dependent 2D recession of the material samples and the shock standoff distance. New results showing non-linear material erosion rates will be highlighted. The material and shock edges are extracted from the videos by training and applying a convolutional neural network. Due to the consistent camera settings, the machine learning model achieves high accuracy (~99%) on new data with only a small number of training frames (~80). The new results will be discussed in the context of temperature dependent plasma-surface interaction.

Magnus A Haw↗
NASA NTRS2020

Multibody Based Digital Astronaut Dynamics Simulation

BACKGROUND: This study provides the Software, Robotics, & Simulation Division at the NASA Johnson Space Center with a verification tool for multibody dynamics simulation requiring human motion. The motivation stems from current studies of several Vibration Isolation & Stabilization(VIS)system designs that attenuate the moments and forces which would be transmitted to a spacecraft during an exercise. A multibody dynamics model for a proposed VIS was available previously[1], therefore modeling of the VIS was not needed for this work. The interest here is in creating the multibody dynamics model of an astronaut in motion which may be utilized independently or while attached to a mechanism. An existing simulation [2] that utilizes OpenSim [3,4] and an in-house multibody dynamics package (MBDyn) [5] is used in order to verify the astronaut model. The main advantage this model will have over the existing simulation is that everything will be processed in one tool. METHODS AND RESULTS: Creating the simulation required; estimation of Body Segment Inertial Parameters (BSIP),a multibody model of the human-VIS system, joint acceleration profiles, and input files for MBDyn, which is used for this analysis. The scaling factors provided by Dumas et al. [6] are utilized in estimating the BSIP. Anthropometric data are used for estimating these parameters, the Anthropometric Survey of US Army Personnel (ANSUR II) [7] was the source. The astronaut model consists of 15 bodies, 14 joints and 32 degrees of freedom, with the dynamics topology generated using the center of mass locations and anthropometric data. MBDyn has an option for prescribed joint motion (PJM), which requires joint acceleration data as input. The joint angle data is first obtained from a motion capture system and then processed through code that has been created to generate approximate joint acceleration profiles. The topology tree for the astronaut model begins at the right foot up to the pelvis where there is one branch for going down the left leg and another for the torso. The torso branch leads to branches for the arms and a leaf body for the head/neck segment. For attachment to the VIS, the heel of the right foot is connected to the VIS platform through a fixed joint, resembling a foot restraint. The left foot does not attach to the platform in order to prevent a system with a closed loop. Topology and symmetry of the astronaut model were verified through kinematic analysis. Further verification of the forces and moments transmitted to the VIS were verified against the existing simulation. There was a satisfactory level of agreement when testing a simple motion, for example, rocking back and forth. Full exercise motions are to be tested soon. The main outcome has been a novel application of MBDyn for biomechanics modeling that is now available for dynamic simulations involving human motion. The estimation of BSIP was another useful result of this study, requiring only 15 inputs for generating mass properties of a theoretical astronaut model. Expansion on this work is possible by going through an alternative route in obtaining the joint motion data. Instead of high-tech and often expensive motion capture systems, an individual may watch videos with high focus and at a slow motion for each individual segment in order to determine the initial and final time and angle for that specific degree of freedom. Synthetic trajectories may also be created if there is no video reference available.

F N Matari↗
NASA NTRS2020

Electric Six Degree of Freedom Installation Timelapse (Six Degree of Freedom Dynamic Test System)

The Six-degree-of-freedom Dynamic Test System (SDTS) is a short-range real-time motion based testing platform. Its primary use at NASA/JSC has been for development and qualification testing of docking systems, robotic assisted berthing mechanisms, and dynamic attachment systems. The SDTS is a closed-loop force feedback system that can simulate on-orbit contact dynamics between two vehicles utilizing the actual mechanical interfaces for testing. The facility is controlled by interconnected computers running real-time simulation software that takes measured contact forces, integrates the equations of motion in real time, and provide those states back into the motion table. This infrastructure can also be used for non-mating applications such as relative position sensor testing/evaluations. The SDTS facility provides a superstructure for mounting test articles, multiple test sensors, an intercom network for voice communications, and a synchronized timing system for data acquisition that includes HD video. This time-lapse video shows the buildup and testing of a modern electric actuation system created by Mikrolar, Inc. at the Johnson Space Center. This motion base will replace the current hydraulic actuator system, which is been in use since the 1970s, for all-future NASA testing. Once the system goes through customization to provide JSC’s unique closed-loop environment, the facility will help certify docking system and attach mechanisms on the ground before we send the first woman and the next man to the lunar surface

hexapod↗
NASA NTRSDate not supplied

Measurement of Material Recession and Shock Standoff in Plasma Windtunnel using Neural Nets

Arcjets are plasma wind tunnels used to test the performance of heatshield materials for spacecraft atmospheric entry. These facilities present an extremely harsh flow environment with heat fluxes up to 109 W/m2 for up to 30 minutes. The plasma is low-temperature (∼1 eV) but high pressure (> 10 kPa) creating high-enthalpy supersonic flows similar to atmospheric entry conditions. Typically, material samples are measured before and after a test to characterize the total recession. However, this does not capture time-dependent effects such as material expansion and non-linear recession. This work will present new analysis of arcjet test videos which measure both the time-dependent 2D recession of the material samples and the shock standoff distance. The results show non-linear time-dependent effects are present for some conditions. The material and shock edges are extracted from the videos by training and applying a convolutional neural network. Due to the consistent camera settings, the machine learning model achieves high accuracy (± 2 px) relative to manually segmented images with only a small number of training frames (80).

Neural network↗
NASA NTRS2020

Evaluation of Computational Fluid Dynamics for Testing at High Supersonic Speeds

Video is an overview of the AETC Capability Challenge: Evaluation of Computational Fluid Dynamics (CFD) for Testing at High Supersonic Speeds. Featuring assessments of a series of wind tunnel tests and CFD analysis conducted with a focus on air flow and the potential of optimizing future testing. This video is beneficial for sharing with other organizations that operate or test in wind tunnels.

CFD Studies↗
NASA NTRSDate not supplied

Motion Magnification to Visualize the Modes of Space Structures

Traditional structural testing involves using accelerometers and strain gages to measure the motion. While this traditional instrumentation suite has proven accurate, it is limited to capture data only in the discrete locations where the transducers are placed. Additionally, applying the instrumentation can be a difficult and labor intensive task. By using video cameras, the motion of the test article – such as a launch vehicle or launch vehicle payload – can be easily captured at any location in the field of view and easily visualized using a post-processing technique called Motion Magnification. It is also much easier to place video cameras to measure motion rather than having to place contact sensors, especially when placement locations can be limited on final flight hardware. Recently, a team of MIT Lincoln Laboratory (MITLL) and NASA Marshall Space Flight Center (MSFC) have been collaborating to use Motion Magnification to measure the dynamics of large space structures. This presentation will detail some of the results of this collaboration.

Eric Colby Stewart↗