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NASA NTRSDate not supplied

Autonomous Lunar PNT Simulator (ALPS)

In this paper we present a simulation tool that has been used to develop an architecture for a low-cost Position, Navigation and Time (PNT) system to provide PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities. Over the next few decades there is expected to be a substantial increase in Lunar missions supporting and inspired by NASA’s Artemis Program. It is expected that a large fraction of these missions will be low cost, utilizing rideshares and CubeSats, just as has seen in Earth orbit over the past decade. Many of these missions will need navigation capabilities but may be unable to support the large power, mass and weight that a weak GNSS or DSN based navigation solution would entail. As Lunar PNT service demand is not likely to be needed over the entire lunar surface 24/7, the creation of a dedicated Lunar GNSS constellation cannot be justified. Hence, our proposed architecture envisions utilizing existing Lunar science and exploration assets to create ad hoc and on demand Lunar PNT swarms capable of providing PNT services to low cost missions. The simulation reflects the two distinct parts of the architecture: the creation of a Lunar PNT swarm using non-dedicated existing assets, and the quantitative modeling of the quality of the PNT services that this swarm provides. To support the former, the simulation supports various swarm localization techniques, including centralized and distributed EKFs both of which support pluggable dynamics models. In modeling the PNT service performance the simulation adopts standard techniques from the GNSS community, including providing degree of precision (DOP) estimates for theoretical end users. Crucially, all asset capabilities, including clock accuracy, independent location self-knowledge and timing measurement precision can be set independently for each asset, reflecting the key concept of utilizing non-dedicated assets. The simulation is predominantly implemented in MATLAB, with GMAT being used for the propagation of orbital assets. The paper will present results from the simulation reflecting the tool’s flexibility and focusing on scenarios that match real-world proposed missions, including scenarios designed to provide PNT support to lunar surface missions similar to NASA Ames' forthcoming VIPER mission. The performance of centralized and decentralized swarm configuration and localization techniques will be compared. Finally, performance of the PNT service provided by an autonomous Lunar PNT swarm will be compared to existing radiometric and weak GNSS methods.

Kelley Elizabeth Hashemi↗
NASA NTRS2020

Modeling and Control for a Flexible Inverted Pendulum Robot

This report describes the tasks accomplished during Fall 2020 at the Kennedy Space Center under the scope of the Robotic Control System Design internship project. These tasks primarily supported development of an augmented adaptive control system for an inverted pendulum (IP) robotic system on a 4-wheel mobile base (Penny). This system serves as an analogue to the control problems in the flight of rockets in the initial and latter stages of launch, and methods developed as part of this research can later be applied to more complex IP systems, such as launch vehicles. To more accurately model launch vehicles, a flexible aluminum pendulum is used both on the hardware and in the simulated models. In order to capture the flexible dynamics of the system, hardware modifications were made to Penny (including installation of a rate gyro at the tip of the pendulum). Simulink models were created to control and model the hardware system, and Simscape models were created/updated to model the system in simulation. MATLAB programs were created throughout the internship to analyze data generated from hardware and simulation runs. Linear fixed-gain controllers have been applied to the simulated and hardware system, and work continues with augmenting these controllers using sensor blending and direct output adaptive control methods to improve stabilization of system states and cancel flex dynamics. In addition to describing the work done to support these modeling efforts, an Independent Research and Technology Development (IR&TD) proposal for a lunar simulation with soil deformation modeling developed during the internship is briefly described.

Nashir A Janmohamed↗
NASA NTRSDate not supplied

Developing a Multi-Lingual Autocoding Interface for the MAVERIC-II Dynamics Simulator

Simulation model development in certain high-level languages such as Python, MATLAB, or Simulink are unparalleled by their convenience and rapid turnover time. However, legacy simulation engines often depend on more traditional languages such as FORTRAN or C/C++. The NASA Marshall Aerospace Vehicle Representation in C version II (MAVERIC-II) is a modular, legacy-derived computer program used for high-fidelity, 6 degree-of-freedom (6dof) simulation for aerospace vehicle flights and analyses of guidance and control performance with built-in mathematical modeling of environmental effects such as wind, atmosphere, and gravity as well as dispersion capability for Monte Carlo analysis. MAVERIC-II is modular in the sense that each component software element of the simulation engine may be supplanted for a higher or lower fidelity version. The design flow of the development of these models is often performed in high-level languages as mentioned previously, which must then be translated into C or C++ code to be integrated into MAVERIC-II. We propose a unified method of autocoding and interfacing between several languages and MAVERIC-II, which may be generalized further to any type of 6dof simulation engine.

Mason Nixon↗
NASA NTRS2004

Mars Exploration Rovers landing dispersion analysis

Landing dispersion estimates for the Mars Exploration Rover missions were key elements in the site targeting process and in the evaluation of landing risk. This paper addresses the process and results of the landing dispersion analyses performed for both Spirit and Opportunity. The several contributors to landing dispersions (navigation and atmospheric uncertainties, spacecraft modeling, winds, and margins) are discussed, as are the analysis tools used. The JPL MarsLS program, a MATLAB-based landing dispersion visualization and statistical analysis tool, was used to calculate the probability of landing within hazardous areas. By convolving this with the probability of landing within flight system limits (in-spec landing) for each hazard area, a single overall measure of landing risk was calculated for each landing ellipse. In-spec probability contours were also generated, allowing a more synoptic view of site risks, illustrating the sensitivity to changes in landing location, and quantifying the possible consequences of anomalies such as incomplete maneuvers. Data and products required to support these analyses are described, including the landing footprints calculated by NASA Langley's POST program and the JPL AEPL program, cartographically registered base maps and hazard maps, and flight system estimates of in-spec landing probabilities for each hazard terrain type. Various factors encountered during operations, including evolving navigation estimates and changing atmospheric models, are discussed and final landing points are compared with approach estimates.

Desai, Prasun N.↗
NASA NTRS2012

Testing and characterization of an IR CBIRD FPA

High performance IR cameras are in great demand for a variety of applications, including defense (e.g. night vision, missile detection) and space (e.g. imaging at IR wavelengths). IR focal plane arrays (FPAs) are an essential component of IR cameras. An FPA is a collection of detectors at the focal plane of an imaging device, where each detector can be thought of a pixel in the image it is detecting. The FPA in this study is based on Complimentary Barrier Infrared Detectors (CBIRDs). The CBIRD FPA was tested by imaging flat black body targets at three different temperatures, 20ºC, 25ºC, and 30ºC, with images captured using SEIR software. The important figures of merit for an IR FPA, Noise Equivalent Difference Temperature (NEDT), Noise Equivalent Irradiance (NEI), detectivity (D*), responsivity, and quantum Efficiency (QE), were extracted from the image data for each individual detector using a MATLAB program, as was the array Modulation Transfer Function MTF. The test results show a mean NEDT of 16.98mK and an MTF of about 0.34 at the Nyquist frequency. Overall, the array performs well in the MWIR range and takes quality IR images.

Das, Tanya↗
NASA NTRS2017

WFIRST coronagraph optical modeling

End-to-end numerical optical modeling of the WFIRST coronagraph incorporating wavefront sensing and control is used to determine the performance of the coronagraph with realistic errors, including pointing jitter and polarization. We present the performance estimates of the current flight designs as predicted by modeling. We also describe the release of a new version of the PROPER optical propagation library, our primary modeling tool, which is now available for Python and Matlab in addition to IDL.

Zhou, Hanying↗
NASA NTRS2018

Fast Linearized Coronagraph Optimizer (FALCO) I: A Software Toolbox for Rapid Coronagraphic Design and Wavefront Correction

The Fast Linearized Coronagraph Optimizer (FALCO) is an open-source toolbox of routines for coronagraphic focal plane wavefront correction. The goal of FALCO is to provide a free, modular framework for the simulation or testbed operation of several common types of coronagraphs. FALCO includes routines for pair-wise probing estimation of the complex electric field and Electric Field Conjugation (EFC) control, and we ask the community to contribute other wavefront correction algorithms. FALCO utilizes and builds upon PROPER, an established optical propagation library. The key innovation in FALCO is the rapid computation of the linearized response matrix for each deformable mirror (DM), which facilitates re-linearization after each control step for faster DM-integrated coronagraph design and wavefront correction experiments. FALCO is freely available as source code in MATLAB at github.com/ajeldorado/falco-matlab and will be available later this year in Python 3 at github.com/ajeldorado/falco-python.

Shaklan, Stuart B.↗
NASA NTRSDate not supplied

Streamlining GNC Architecture Development and FSW Integration forthe Mars Ascent Vehicle

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface ofanother atmospheric planetary body outside of the Earth-Moon system. Significant light-time delayrequires complete autonomy of flight throughout ascent, and naturally a high level of reliability isdesired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls(GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiencyof algorithm integration onto the MAV flight processor, and to increase confidence that said integrationis successful and without human error. An interface architecture is proposed for the GNC suite thatallows both the guidance and navigation subsystems to provide code algorithms directly in C++, and thecontrols subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code fromthe GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendlywrapper which abstracts the integration of the GNC algorithm code into an interface-level API that iscompatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSWteam’s partnership, and this strong interface between these two teams have allowed the GNC/FSWteams to greatly increase confidence of efficient and error-free implementation of the GNC code ontoMAV for a successful flight.

GNC↗
NASA NTRS2020

Julia Language 1.1 Ephemeris Reader and Gravitational Modeling Program for Solar System Bodies

This paper analyzes the advancements to the Julia Language 1.1 Ephemeris and Physical constants Reader including the addition of gravitational modeling. Originally written in MATLAB, this Julia Language program is intended to be used in for trajectory design. Written in an open-source coding language, this ephemeris reader can output the state of planetary bodies including asteroids as well as other constants such as gravitational parameters. Two primary methods were chosen to calculate the gravitational potentials which include polyhedral modeling and spherical harmonics.

Gray, Brennan↗
NASA NTRSDate not supplied

Streamlining GNC Architecture Development and FSW Integration for the Mars Ascent Vehicle

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface of another atmospheric planetary body outside of the Earth-Moon system. Significant light-time delay requires complete autonomy of flight throughout ascent, and naturally a high level of reliability is desired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls (GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiency of algorithm integration onto the MAV flight processor, and to increase confidence that said integration is successful and without human error. An interface architecture is proposed for the GNC suite that allows both the guidance and navigation subsystems to provide code algorithms directly in C++, and the controls subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code from the GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendly wrapper which abstracts the integration of the GNC algorithm code into an interface-level API that is compatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSW team’s partnership, and this strong interface between these two teams have allowed the GNC/FSW teams to greatly increase confidence of efficient and error-free implementation of the GNC code onto MAV for a successful flight.

Engineering↗
NASA NTRSDate not supplied

Developing a Multilingual Auto-coding Interface Control for the MAVERIC-II Dynamics Simulator

Simulation model development in certain high-level languages such as Python, MATLAB, or Simulink are unparalleled by their convenience and rapid turnover time. However, legacy simulation engines often depend on more traditional languages such as FORTRAN or C/C++. The NASA Marshall Aerospace Vehicle Representation in C version II (MAVERIC-II) is a modular, legacy-derived computer program used for high-fidelity, 6 degree-of-freedom (6DOF) simulation for aerospace vehicle flights and analyses of guidance and control performance with built-in mathematical modeling of environmental effects such as wind, atmosphere, and gravity as well as dispersion capability for Monte Carlo analysis. MAVERIC-II is modular in the sense that each component software element of the simulation engine may be supplanted for a higher or lower fidelity version. The design flow of the development of these models is often performed in high-level languages as mentioned previously, which must then be translated into C or C++ code to be integrated into MAVERIC-II. Using principles of model-based design, we propose a unified method of auto-coding and interfacing between several languages and MAVERIC-II, which may be generalized further to any type of 6DOF simulation engine.

Mason Nixon↗
NASA NTRSDate not supplied

Scheduling Position, Navigation and Time Service Requests from Non-dedicated Lunar Constellations

This paper presents a centralized scheduler that satisfies user requests for Position, Navigation, and Time (PNT) services from an ad-hoc, non-dedicated orbital constellation around the Moon. Traditional, dedicated GNSS networks provide service 24/7, which allows users to acquire localization services at-will. For ad-hoc networks, a coordinated schedule is needed to ensure Quality of Service (QoS) guarantees for user localization, while satisfying non-dedicated assets’ usage constraints. This scheduler bridges this coordination gap by leveraging Mixed Integer-Linear Programming (MILP) to schedule this “as-needed” localization service while respecting the constraints on each asset. In upcoming decades there is expected to be a substantial increase in Lunar missions. Many of these missions will feature low-cost surface assets near the moon’s polar regions and small-sat science missions in orbit. Most missions need PNT capabilities to ensure safe operations and meet their science objectives, but low-cost missions may not be able to support the large power, mass, and weight that a weak GNSS or DSN based navigation solution would entail. Asset localization has been demonstrated using a decentralized extended Kalman Filter (DEKF) in the previously presented Lunar Autonomous PNT System (LAPS). Within the LAPS simulation environment, a module has been developed to generate the coordinated user-asset schedules described above; this Service Scheduler Module (SSM) allows for complete end-to-end testing of the entire system. Within SSM, a user service request consists of a location on the Lunar surface, a cumulative service duration, and a window in which service must occur. SSM takes as input these requests and the LAPS-predicted positional degree of precision as the QoS for each available set of orbital assets. A simple, baseline MILP model is formulated to provide the highest-precision service balanced across all requests. To reflect the non-dedicated nature of the constellation, this baseline model is augmented with additional asset-specific load capacity constraints or availability constraints. The load capacity constraints limit total time spent providing service, and the availability constraints reflect blockout times or availability windows when the assets are not otherwise occupied. SSM outputs two schedules: the user schedule to indicate their service times and expected QoS, and a satellite schedule to be transmitted to the orbiting constellation, describing when each non-dedicated asset provides PNT service. SSM is predominantly implemented in MATLAB and allows the use of any MILP solver to generate the resulting schedules. This paper describes the SSM - LAPS interface, how the output of LAPS is used to construct the MILP, and how SSM provides user localization service while satisfying constraints. It will also demonstrate the tool’s flexibility for formulating schedules for the end user and the constellation, focusing on scenarios that match real-world proposed missions. It will detail how SSM can be used to compare the addition of load capacity constraints, satellite availability constraints, and QoS guarantees for the users. Finally, we describe how SSM can be used to support the design of the ad-hoc constellation itself. The resulting integrated capability will support the design of future ad-hoc Lunar PNT networks, enabling high-quality, low-cost Lunar exploration

Swarm↗
NASA NTRS2021

Powder River Basin Water Resources: Mapping Russian Olive in the Powder River Basin to Inform Invasive Species Management

Since its introduction in the late 1800s, Elaeagnus augustifolia (Russian olive) has become a widespread invasive shrub that poses a threat to native riparian species in the United States by competing with native riparian plants for space and resources. To date, limited information on the distribution of Russian olive in the Powder River Basin of Montana and Wyoming have hampered management efforts and decision making. Here, we detect and model the distribution of Russian Olive using field surveys, ocular sampling, and variables from Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Shuttle Radar Topography Mission (SRTM) using the Random Forest algorithm. We derived topographic, spectral, and hydrological variables from Landsat 8 OLI, Sentinel-2 MSI, and SRTM to utilize as model inputs. The team was able to successfully create a spectral Russian olive detection map for the Powder River Basin (RMSE =15.44%, R2 = 0.6482). The team also examined change in stream channel geomorphology from 1984-2020 in a time-series analysis using Landsat visible imagery and the RivMap MATLAB package and found little change. Our results will help our partners at the Powder River County Weed Board, Gay Ranch, United States Geological Survey, and University of Northern Colorado to locate and prioritize areas for riparian habitat restoration and to understand the region’s hydrology and geomorphology.

Catherine Buczek↗
NASA NTRSDate not supplied

Emulation of Core Flight System Applications for Flight Software Development and Validation

The Mars Sample Return (MSR) campaign is an unprecedented attempt in the return of Martian samples back to Earth. The ascent from the surface will be performed by the Mars Ascent Vehicle (MAV), a critical element in the mission that National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is developing. To this end, innovations in flight software development, verification, and validation are occurring. The MAV flight computer will run Core Flight System (cFS), an open-source software environment developed by NASA Goddard Space Flight Center (GSFC). NASA Marshall’s MAV Mission and Fault Management (M&FM) Team has implemented an emulation of two applications of this architecture: Limit Checker and Stored Command. Using an emulation of the functionalities of these applications allows for rapid prototyping of table-based algorithms. Further, M&FM is leveraging an in-house, low-fidelity but high-throughput State Analysis Model (SAM), an integrated MATLAB Stateflow Plant and Software model. This model is run in parallel with the cFS emulation for full flyout testing of the M&FM algorithms, verification of intent of these algorithms, and for future auto-generation of application-ingestible M&FM tables. The tables can then be delivered to the MAV Flight Software (FSW) team in a seamless process, reducing the cost of traditional FSW development and the risk of starting M&FM FSW development at later points in the NASA program life cycle.

Cody Wheeler↗
NASA NTRSDate not supplied

Correlated Electromagnetic Levitation Actuator: A Reaction Sphere Based Attitude Control System

To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at NASA’s Marshall Space Flight Center have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. The probe also includes the ability to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL Finite Element Analysis and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller thatmitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.

controls↗
NASA NTRSDate not supplied

Correlated Electromagnetic Levitation Actuator: A Reaction Sphere-Based Attitude Control System

To address problems experienced by current reaction wheels and control moment gyroscopebased attitude control systems (ACS), researchers at National Aeronautics and Space Administration’s (NASA’s) Marshall Space Flight Center (MSFC) have begun developing a reaction sphere actuator based on correlated electromagnetic levitation that will be immune to destructive bearing friction, momentum saturation, and gimbal lock. The Correlated Electromagnetic Levitation Actuator (CELA) advances the state of the art of reaction sphere ACSs by employing the concept of correlated magnetics. It is a frictionless, direct-drive reaction sphere that harnesses a unique technology with an array of applications across multiple disciplines. Correlated electromagnets function in a manner that is analogous to a matched filter; the convolution of two signals is peaked at the index representing the greatest match. For CELA, the signals are the patterns of magnetic flux density as a function of position. The magnitude of the convolution equates to an attractive or repulsive force, and these forces can be azimuthal or radial. The development of CELA is based in four distinct disciplines: Advanced Manufacturing, Prototype Development, Electromagnetic Modeling, and Controls. We are developing novel manufacturing techniques required to build arrays of permanent and electromagnet dipoles on curved surfaces. To print the permanent magnetic array, we have developed a probe with pyramidal magnets that will reside on a robotic arm to induce localized magnetic fields on a surface. We have also used high temperature ovens to erase dipole patterns from a permanent magnet by heating the surface to its Curie temperature. A number of test articles and prototypes have been developed using additive manufacturing methods. These prototypes have included hemispherical motors to test the drive algorithm, and a levitation test bed that demonstrates a magnetic bearing method based on attractive magnetic forces and ratiometric Hall effect sensors. We developed an array of electromagnetic dipoles on a printed circuit board (PCB) with individual H-bridges controlling each coil. This device created various flux density patterns and we measured their magnetic fields using a custom Hall effect 3-D probe and a LabVIEW virtual instrument. These data will serve as a benchmark for characterizing the accuracy of future models. Current work is focused on modeling the magnetic fields of our prototype arrays using COMSOL finite element analysis (FEA) and verifying the model against our test data. Accurate modeling will allow us to quickly test new patterns of electromagnets and their macro behavior. Eventually, the magnetic field models will be implemented in our controls simulations to facilitate precise control of the reaction sphere. Initial model results agree with field measurements to within 1 G (5% of measured flux density). Currently, we are testing different material properties of the electromagnets and their magnetic fields and thermal effects. These results will be used to refine the design of the electromagnetic dipoles. Our control efforts have centered on developing commutation, levitation, and field pattern shaping hardware in the form of breadboards and PCBs with software running on a local microcontroller. In addition, our partners developed MATLAB Simulink models to demonstrate a PID controller that mitigates disturbance forces resulting from the interaction of drive and levitation magnetics. Finally, we have designed a three-axis test stand that will be used in future work to demonstrate CELA’s orientation control capability.

reaction sphere↗
NASA NTRSDate not supplied

The Instrumented Walking and Turning Test to Evaluate Suited Gait Dynamics and Performance in Extravehicular Activity Training Environments

Background and aims: Walking will be required for many exploration tasks on the Moon during the Artemis program. Walking in a straight line on the confined floorspace of a testing area, and repetitive treadmill walking that requires no change in direction may not adequately reflect the balance and coordination required during ambulation. Also, performance of turning maneuvers may be affected differently in different extravehicular activity (EVA) training facilities that simulate partial gravity. For example, the Neutral Buoyancy Lab (NBL) simulates lunar gravity by adding weight to underwater subjects to alter buoyancy and achieve the equivalent ground reaction force of 1/6 of Earth’s gravity (1/6G), whereas the Active Response Gravity Offload System (ARGOS) uses a computer controlled overhead suspension system programmed to continuously offload a percentage of a subject’s weight to simulate 1/6G. The degree to which dynamic movements such as turning are comparable across these EVA training facilities has not yet been evaluated. The instrumented gait test helps NASA scientists and engineers evaluate gait dynamics and performance in suited conditions, and this test demonstrates the unique characteristics and limitations of EVA training facilities. We developed an instrumented walking and turning test using inertial measurement units (IMUs) and conducted the test at NASA’s EVA training facilities. Results were used to compare suited walking and turning characteristics in the ARGOS and the NBL. Methods: Subjects donned the Mark III space suit during offloading with the ARGOS spreader bar gimbal and donned the Z2.5 space suit while underwater in the NBL with weights and floatation added to achieve realistic suit center of gravity. The test team securely attached three Opal (APDM, OR, USA) wireless IMUs on the space suit for each test run: one on the middle of the hard upper torso, and one on the left and on the right ankle bearings. During the NBL tests, the IMUs were encased in a waterproof housing (GoPro) with foam added to create a tighter fit. At both testing facilities, 6.3 m x 1.0 m (LxW) walking lines were marked, and a cone for turning or walking around was located at the end of the walking path with another line on the other side of the cone to indicate the stopping point after walking around the cone. Under simulated 1/6G, subjects began by standing at the marked line with their arms folded across the chest, they then walked at a preferred speed along the straight walking path until they reached the end, turned 180 degrees around the cone, and finally stopped at the marked stopping point. All IMU data recorded during testing were automatically saved to the internal memory. Then, raw IMU signals were processed using custom MATLAB (Mathworks, MA, USA) code to compare gait parameters during both the walking and the turning components of the task. These parameters included time (s), speed (m/s for walking and rad/s for turning), step number (n) and walk:turn time ratio (% time spent straight walking versus turning). Results: Less time, faster gait, fewer steps, and higher walk:turn ratio during both walking and turning components were exhibited during tests performed at the ARGOS versus those performed at the NBL. During the NBL tests, the slower walking speed continued at the same rate throughout a U-shape turn. During the ARGOS tests, the subjects performed shorter and tighter turns at 4 times the speed of the NBL turns because they walked 30% faster and the vertical offloading system gave them more support. Conclusion: Our data show that the differences in walking and turning parameters during the NBL tests may be due to the high viscosity in the water environment where the motion of the lower limbs was slow and did not reach full flexion and extension. These tests improve the current knowledge of testing environments in preparation for EVAs on the lunar surface.

Kyoung Jae Kim↗
NASA NTRSDate not supplied

Proof Testing Aluminum and Titanium Thin-Walled Tubes for Aerospace Applications

Proof testing aerospace components aids in verifying the structural integrity of flight hardware. This process is often an important step in the certification process for critical parts. Though proof testing is a common practice at NASA and in industry, there is often a need to understand better the effectiveness of proof testing pressure systems discovering cracklike flaws or defects. Often proof tests are used in requirements and in practice as technical rationale for screening critical defects in a part in lieu of performing a non-destructive inspection. The intent of this work is to define proof test failure envelopes for thin-walled tubes composed of two materials: aluminum and titanium. Both materials are common in aerospace thin-walled tubing applications which is why these were the materials chosen for this study. The fracture mechanics software NASGRO was used to perform a parametric study on the effect of defects in thin-walled tubes subjected to proof testing. For both materials, the parameters varied in the NASGRO analyses were aspect ratio, proof test pressure, thickness, diameter, and flaw multiplier. With each case defined as a through crack or failure, the results were then pulled into MATLAB in order to parse through the data and produce failure envelope plots. Failure envelopes were created by meshing a surface in between the minimum proof pressure failing data points. As expected, based on material properties, the plots indicated the aluminum material would fail at much lower proof tests than the titanium. The parametric data and failure envelopes may be used as general qualitative insight on the effectiveness of proof testing thin-walled tubes of similar alloys.

Leah B Davis↗