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Minimax failure detection and identification in redundant gyro and accelerometer systems.

Minimax algorithms for failure detection and identification for redundant noncolinear arrays of single-degree-of-freedom gyros and accelerometers are described. These algorithms are optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible estimation error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.

Potter, J. E.↗

Lunar Dust Mitigation: A Guide and Reference: First Edition (2021)

On the surface of the Moon, lunar dust specifically presents unique challenges to operations long-term due to regolith particles’ ubiquitous presence in the lunar environment, potential to electrostatically charge and possible chemical reactivity. Whether to avoid exposure, try to remove or simply to tolerate lunar dust infiltrating a system becomes a complex question involving length of required service life, dust effects and critical risks, mass and complexity trades for the entire system. This publication provides a snapshot of advice from topical experts for specific areas of concern to systems targeted for deployment on the lunar surface. Following introductory overview commentary, dust mitigation approaches appropriate to the lunar surface are first addressed for typically static structures such as optical surfaces, radiators, and other thermal control surfaces, followed by regolith exposure concerns for communications equipment and non-optical sensors. The broad topic of mechanisms and mechanical assemblies is broken down to address relevant component level concerns, such as for bearings and for seals. “Soft goods” components of space suits (fabric) specific concerns are discussed, followed finally by brief coverage of human health issues and concerns, though the emphasis of this publication remains with components directly exposed to the harsh lunar surface environment. A description of some lunar surface hazard details, in particular characteristics of lunar surface dust, follows in Appendix A, and more detailed explanations of quantification issues for particulates are in Appendix B. The simple inertial removal of particles from a surface is discussed in Appendix C, followed by a summary of terrestrial best practices for dust mitigation recommended within select industries in Appendix D. The aggregated bibliography of references, while extensive and very useful, should not be construed to be exhaustive and can serve as a constructive start.

dust↗

Nature of the requirements for reference coordinate systems /Review paper/

The current need for more precisely defined reference coordinate systems arises for geodynamics because the earth can certainly not be treated as a rigid body when measurement uncertainties reach the few-centimeter scale or its angular equivalent. At least two coordinate systems seem to be required. The first is a system defined in space relative to appropriate astronomical objects, suitable for ultimately expressing the dynamical equations of motion for the earth. The second coordinate system must be associated with the nonrigid earth in some well defined way so that the rotational motions of the whole earth are represented by the transformation parameters relating the earth system to the space-inertial system. The earth system should be defined so that the dynamical equations for relative motions of the various internal mechanical components of the earth and accurate measurements of these motions are conveniently expressed in this system.

Lundquist, C. A.↗

A Study of the Positions and Velocities of a Space Station and a Ferry Vehicle During Rendezvous and Return

A study is made of the families of non-thrusting ascent trajectories of a ferry vehicle during rendezvous with an orbiting body, referred to as a space station. It is shown that these trajectories may also be interpreted as descent trajectories of the ferry from the station to the earth. The rendezvous trajectories start at the end of the boost period (assumed to be 60 miles) and terminate at the station. The equations of motion are derived and results are shown for two typical orbits of the station: a 300-mile cir­cular orbit and a 100-to-500-mile elliptical orbit. Trajectories are described in terms of a rotating co­ordinate system fixed in the station and launch con­ditions are tabulated in terms of non-rotating inertial coordinates. Boundaries are given in terms of launch (at time of booster burnout) and rendezvous conditions for the example cases. The considerations used to calculate these boundaries and the significance of some of the trends are discussed.

TRAJECTORY↗

Magellan Prelaunch Mission Operations Report

The Magellan spacecraft will be launched from Kennedy Space Center (KSC) within a 31-day overall launch period extending from April 28 to May 28, 1989. The launch will use the Shuttle Orbiter Atlantis to lift an Inertial Upper Stage (IUS) and the Magellan Spacecraft into low Earth orbit. After the Shuttle achieves its parking orbit, the IUS and attached Magellan spacecraft are deployed from the payload bay. After a short coast time, the two-stage IUS is fired to inject the Magellan spacecraft into an Earth-Venus transfer trajectory. The Magellan spacecraft is powered by single degree of freedom, sun-tracking, solar panels charging a set of nickel-cadmium batteries. The spacecraft is three-axis stabilized by reaction wheels using gyros and a star sensor for attitude reference. The spacecraft carries a solid rocket motor for Venus Orbit Insertion (VOI). A hydrazine propulsion system allows trajectory correction and prevents saturation of the reaction wheels. Communication with Earth through the Deep Space Network (DSN) is provided by S- and X-band telemetry channels, through alternatively a low, medium, or 3.7 m high-gain parabolic antenna rigidly attached to the spacecraft. The high-gain antenna also serves as the radar and radiometer antenna during orbit around Venus.

Source record↗

Mission Summary of Cassini Spacecraft Guidance and Control Hardware Health and Performance

The Cassini-Huygens mission ended on September 15, 2017, after nearly two decades in ight. The well-designed Cassini spacecraft had robust hardware that permitted two extended missions, lasting nine years longer than the expected prime mission. At the end of the mission, the Attitude and Articulation Control Subsystem (AACS) was using two pieces of redundant back-up of hardware, one reaction wheel and the hydrazine thruster branch, due to hardware anomalies earlier in the mission. The back-up hardware performed nominally through the rest of mission. The prime reaction wheels at the end of the mission had reached more than 130% of the consumable limit for number of revolutions. No thruster on either thruster branch accumulated more than 45% of the consumable limits. The inertial reference unit slightly exceeded the pre-launch requirements on bias error, but as the software continuously estimated this value in ight, the attitude estimation was not adversely a ected. The star trackers performed nominally, and though there was a spacecraft anomaly in 1998 related to the star trackers, the origin was not in hardware itself. The Sun sensors and accelerometer both performed as expected and met all requirements throughout the mission. Ultimately, the lifetime of the Cassini spacecraft was not limited by hardware performance. Planetary protection requirements necessitated the end of the mission as the spacecraft's propellant reserves depleted, and Cassini plunged into Saturn's atmosphere with a healthy attitude control system.

Stupik, Joan↗

Comparing Theoretically Scaled Biomechanical Models

BACKGROUND An investigation into incorporating space suit aspects required a 50th-percentile male model which was not part of the existing dataset of models. Previously, theoretical models for 5th-percentile female and 95th-percentile male were created utilizing a scaled test subject as close as possible to the target height and weight. Scaling factors were created by taking the height ratio and applying it uniformly to the model body segments, then fine tuning to ensure the theoretical model’s height is as expected. This study was initiated to examine the existing method of isometrically scaling in OpenSim [1,2] and to create alternative methods which do not rely on an existing subject being close in height and weight to the theoretical model of interest. Generating a theoretical biomechanical model provides additional abilities without the reliance on available OpenSim models or real subjects. Gained abilities include creating different percentile models and attaining representative anthropometry for any target height/weight, such as targeting specific crew populations or gaps within the current dataset. METHODS AND RESULTS This study includes 3 methods for generating the theoretical model; utilizing the modified unscaled OpenSim Full Body Rajagopal Model (FBRM) [3,4], a dataset of scaled OpenSim models, and existing scaling factors from Dumas et al. [5]. All methods use the Anthropometric Survey of US Army Personnel (ANSUR II) [6] as an input of necessary anthropometric measurements. The following measurements are retrieved from the ANSUR II collection: mass, stature, cervicale height, acromial height, axilla height, waist height, trochanterion height, lateral femoral epicondyle height, lateral malleolus height, acromion-radiale length, radiale-stylion length, palm length, ball of foot length, bicristal breadth, bimalleolar breadth. Some of the measurements are direct segment lengths and others are utilized to derive segment lengths. Height, weight, and age ranges are the required inputs to parse the collection for a mean value of the measurements. A simple iterative process may be necessary for the output of mean mass and stature consistent with the theoretical model of interest. In some cases, one may specify exact values instead of a range but that is dependent upon whether those exact values pertain to a single subject from the ANSUR II collection. Equations from Dumas et al. were used to calculate scaling factors for the two methods that utilize OpenSim scaled and unscaled models. In the third method, Dumas’ scaling factors were used directly instead of generating our own. After scaling factors are achieved, they are applied along with the mass and segment lengths retrieved from ANSUR II in order to calculate the segment mass, Center of Mass (CoM), mass Moment of Inertia (MoI), and the joint location in the parent frame. The theoretical models from the different methods were compared to the previous existing method of isometrically scaling in OpenSim, as well as the standards found in NASA STD-3000 [7] and the NASA Human Integration Design Handbook [8]. The whole-body center of mass is the main comparison performed between the models and the standards. The body segment mass properties were also compared when possible. In some cases, the standards do not provide complete data, or the center of mass location is not provided with respect to the appropriate joint coordinate system. For a 50th-percentile male subject, results from isometric scaling in OpenSim and the method utilizing the unscaled FBRM were compared to the standards in NASA STD-3000. According to the standard, the whole-body vertical CoM location was taken from the head vertex to the CoM. The standards provide 80.2 cm for the CoM vertical component whereas isometric scaling in OpenSim and utilizing the unscaled FBRM provide 82.2 and 82.3 cm, respectively. Through definition, the whole-body CoM in the medial/lateral direction agreed across the models. Investigation is on-going to clearly identify the reference point pertaining to dorsal/ventral whole-body CoM position in standards and relate that to the theoretical models. REFERENCES [1] Delp, S.L., et al., “OpenSim: Open-source Software to Create and Analyze Dynamic Simulations of Movement”, IEEE Transactions on Biomedical Engineering, (2007). [2] Seth, A., Hicks J.L., Uchida, T.K., Habib, A., Dembia, C.L., Dunne, J.J., Ong, C.F., DeMers, M.S., Rajagopal, A., Millard, M., Hamner, S.R., Arnold, E.M., Yong, J.R., Lakshmikanth, S.K., Sherman,n M.A., Delp, S.L. OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement. Plos Computational Biology, 14(7). (2018) [3] R. K. Huffman, W. K. Thompson, C. A. Gallo, L. J. Quiocho, “Improvement of Scaling and Inverse Kinematic Results with Additional Upper Body Joints Added to Opensim Rajagopal Model”, NASA Human Research Program Investigator’s Workshop, (2019). [4] Huffman R.K., Thompson W., Gallo C., “Modified OpenSim Rajagopal Full Body Model”, New Technology Report, MSC-26872-1. (August 2020). [5] Dumas R., Cheze L. and Verriest J., 2007. “Adjustments to McConville et al. and Young et al. body segment inertial parameters”. Journal of Biomechanics 40, pp. 543-553 [6] Gordon C.C., 2012 “Anthropometric Survey of U.S. Army Personnel: Methods and Summary Statistics”, US Army Natick Soldier RD&E Center. [7] NASA STD-3000/REV-B, 1995. “The Man-System Integration Standards” [8] NASA/SP-2010-3407/REV-1, 2014. “The Human Integration Design Handbook (HIDH)”

F N Matari↗

TRMM On Orbit Attitude Control System Performance

This paper presents an overview of the Tropical Rainfall Measuring Mission (TRMM) Attitude Control System (ACS) along with detailed in-flight performance results for each operational mode. The TRMM spacecraft is an Earth-pointed, zero momentum bias satellite launched on November 27, 1997 from Tanegashima Space Center, Japan. TRMM is a joint mission between NASA and the National Space Development Agency (NASDA) of Japan designed to monitor and study tropical rainfall and the associated release of energy. Launched to provide a validation for poorly known rainfall data sets generated by global climate models, TRMM has demonstrated its utility by reducing uncertainties in global rainfall measurements by a factor of two. The ACS is comprised of Attitude Control Electronics (ACE), an Earth Sensor Assembly (ESA), Digital Sun Sensors (DSS), Inertial Reference Units (IRU), Three Axis Magnetometers (TAM), Coarse Sun Sensors (CSS), Magnetic Torquer Bars (MTB), Reaction Wheel Assemblies (RWA), Engine Valve Drivers (EVD) and thrusters. While in Mission Mode, the ESA provides roll and pitch axis attitude error measurements and the DSS provide yaw updates twice per orbit. In addition, the TAM in combination with the IRU and DSS can be used to provide pointing in a contingency attitude determination mode which does not rely on the ESA. Although the ACS performance to date has been highly successful, lessons were learned during checkout and initial on-orbit operation. This paper describes the design, on-orbit checkout, performance and lessons learned for the TRMM ACS.

Robertson, Brent↗

Optical Displacement Sensor (ODS), a LISA's inertial reference sensor candidate.

We propose here an optical displacement sensor (ODS) as a supplemental or backup sensor for the LISA inertial reference sensor concept. This simple ODS consists of a laser diode and a quad-cell photodiode (both commercially available). The inertial mass’ reflective surface directs the laser beam onto the quad-cell photodiode. Changes in the inertial mass’ position and orientation are then extracted from ratios of the differences and sums of the quad-cell photodiode outputs. A simpler proto-type using a 200 microns wide slit has demonstrated a resolution of 10 nm/√Hz at 1 mHz and 1 nm/√Hz above 5 mHz. The electronics noise was 1 nm/√Hz at and above 1 mHz with simple and off the shelf electronics components. Although this ODs’ current performance does not meet the LISA’s system requirement’ of 1 nm/ at 1 mHz, we think that is achievable in the near future

Abramocivi, Alex↗

Range filtering for sequential GPS receivers with external sensor augmentation

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver.

Paielli, Russell↗

Decentralized control experiments on NASA's flexible grid

Methods arising from the area of decentralized control are emerging for analysis and control synthesis for large flexible structures. In this paper the control strategy involves a decentralized model reference adaptive approach using a variable structure control. Local models are formulated based on desired damping and response time in a model-following scheme for various modal configurations. Variable structure controllers are then designed employing co-located angular rate and position feedback. In this scheme local control forces the system to move on a local sliding mode in some local error space. An important feature of this approach is that the local subsystem is made insensitive to dynamical interactions with other subsystems once the sliding surface is reached. Experiments based on the above have been performed for NASA's flexible grid experimental apparatus. The grid is designed to admit appreciable low-frequency structural dynamics, and allows for implementation of distributed computing components, inertial sensors, and actuation devices. A finite-element analysis of the grid provides the model for control system design and simulation; results of several simulations are reported on here, and a discussion of application experiments on the apparatus is presented.

Ozguner, U.↗

Range filtering for sequential GPS receivers

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver.

Paielli, Russell↗

Firmware Architecture of the ARMADAS Bolting Robot

The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project, under development at NASA Ames Research Center, has demonstrated on-ground autonomous robotic assembly of extensive digital structures, and it is now moving forward towards in-space demonstration. The ARMADAS system comprises of the operation software, the operation user interface (opsUI), and a swarm of robots. The robotic system consists of a multitude of collaborative agents specifically designed to transport, place and bolt the building blocks, called voxels (volumetric pixels). This paper focuses on the bolting robot, referred to as Mobile Metamaterial Internal Co-Integrator (MMIC-I). MMIC-I is a battery-powered crawling robot. It navigates the structure through extension, contraction and gripping. Two distinct controller boards operate the robot's two symmetric modules, referred to as module A and B. Board A is the master board: it coordinates motion planning and motion primitives execution, hosts the WiFi client, performs periodic self-assessment and system idle check and triggers faults if anomalies are detected. Board B periodically sends a heartbeat to board A, through a wired communication channel that uses the Serial protocol. Additionally, board A's WiFi client receives heartbeat packet requests or motion/bolting commands from a dedicated server board, and acknowledges reception sending back a response heartbeat packet containing information about the overall robot status, e. g. electrical current and voltage values, target and actual angles, operating mode, fault status. Whenever a motion command is sent, the motion planning section of the firmware determines the current robot configuration, using Inertial Measurement Unit readings and the motors Pulse Width Modulation values. Afterwards, it calculates the list of primitives needed to reach the target state, and controls their execution in the proper order. MMIC-I can receive and execute motion and bolting commands only when it is in operational mode. MMIC-I has three operating modes: standby, operational and safed. Standby mode is automatically entered upon startup. While in standby mode, all motors are powered off, and the only accepted commands are the ones relative to a change of mode and heartbeat packet request. Fault detection causes the robot to automatically enter safed or standby mode. Whenever the detected fault occurs within a motion and requires immediate intervention, e. g. an over-current situation, the robot enters safed mode. Safed mode powers off all motors except for the locomotion module, thus preventing the robot from collapsing. Conversely, when the detected fault doesn't require immediate intervention (low battery warning, for instance), the robot enters standby mode after completing the ongoing motion. This paper provides a detailed discussion of MMIC-I's firmware architecture. It accurately describes the implementation approach for each module: sensor data reading, motor control and actuation, WiFi server-client communication, intra-boards Serial communication, operating modes and autonomous fault detection, motion planning, coordination and execution, etc. Moreover, in support of the software description, this paper includes a thorough characterization of MMIC-I's hardware and avionics.

In-space assembly↗

Extending the ICRF to Higher Radio Frequencies

The ICRF forms the basis for all astrometry including use as the inertial coordinate system for navigating deep space missions. This frame was defined using S/X-band observations over the past 20+ years. In January 2002, the VLBA approved our proposal for observing time to extend the ICRF to K-band (24 GHz) and Q-band (43 GHz). The first step will be observations at K- and Q-bands on a subset of ICRF sources. Eventually, K- and Q-band multi-epoch observations will be used to estimate positions, flux density and source structure for a large fraction of the current S/X-band ICRF source list. This work will benefit the radio astronomy community by extending the VLBA calibrator list at these bands. In the longer term, we would also like to extend the ICRF to Ka-band (32 GHz). A celestial reference frame will be needed at this frequency to support deep space navigation. A navigation demonstration is being considered for NASA's Mars 2005 mission. The initial K- and Q-band work will serve to identify candidate sources at Ka-band for use with that mission.

Jacobs, C. S.↗

Control and dynamics of a flexible spacecraft during stationkeeping maneuvers

A case study of a spacecraft having flexible solar arrays is presented. A stationkeeping attitude control mode using both earth and rate gyro reference signals and a flexible vehicle dynamics modeling and implementation is discussed. The control system is designed to achieve both pointing accuracy and structural mode stability during stationkeeping maneuvers. Reduction of structural mode interactions over the entire mode duration is presented. The control mode using a discrete time observer structure is described to show the convergence of the spacecraft attitude transients during Delta-V thrusting maneuvers without preloading thrusting bias to the onboard control processor. The simulation performance using the three axis, body stabilized nonlinear dynamics is provided. The details of a five body dynamics model are discussed. The spacecraft is modeled as a central rigid body having cantilevered flexible antennas, a pair of flexible articulated solar arrays, and to gimballed momentum wheels. The vehicle is free to undergo unrestricted rotations and translations relative to inertial space. A direct implementation of the equations of motion is compared to an indirect implementation that uses a symbolic manipulation software to generate rigid body equations.

Liu, D.↗

The attitude accuracy consequences of on-orbit calibration of the Extreme Ultraviolet Explorer attitude sensors by the Flight Dynamics Facility at Goddard Space Flight Center

The science mission of the Extreme Ultraviolet Explorer (EUVE) requires attitude solutions with uncertainties of 27, 16.7, 16.7 arcseconds (3 sigma) around the roll, pitch, and yaw axes, respectively. The primary input to the attitude determination process is provided by two NASA standard fixed-head star trackers (FHSTs) and a Teledyne dry rotor inertial reference unit (DRIRU) 2. The attitude determination requirements approach the limits attainable with the FHSTs and DRIRU. The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) designed and executed calibration procedures that far exceeded the extent and the data volume of any other FDF-supported mission. The techniques and results of this attempt to obtain attitude accuracies at the limit of sensor capability and the results of analysis of the factors that limit the attitude accuracy are the primary subjects of this paper. The success of the calibration effort is judged by the resulting measurement residuals and comparisons between ground- and onboard-determined attitudes. The FHST star position residuals have been reduced to less tha 4 arcsec per axis -- a value that appears to be limited by the sensor capabilities. The FDF ground system uses a batch least-squares estimator to determine attitude. The EUVE onboard computer (OBC) uses an extended Kalman filter. Currently, there are systematic differences between the two attitude solutions that occasionally exceed the mission requirements for 3 sigma attitude uncertainty. Attempts to understand and reduce these differences are continuing.

Hashmall, J.↗

Backup Attitude Control Algorithms for the MAP Spacecraft

The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE) spacecraft. The MAP spacecraft will perform its mission, studying the early origins of the universe, in a Lissajous orbit around the Earth-Sun L(sub 2) Lagrange point. Due to limited mass, power, and financial resources, a traditional reliability concept involving fully redundant components was not feasible. This paper will discuss the redundancy philosophy used on MAP, describe the hardware redundancy selected (and why), and present backup modes and algorithms that were designed in lieu of additional attitude control hardware redundancy to improve the odds of mission success. Three of these modes have been implemented in the spacecraft flight software. The first onboard mode allows the MAP Kalman filter to be used with digital sun sensor (DSS) derived rates, in case of the failure of one of MAP's two two-axis inertial reference units. Similarly, the second onboard mode allows a star tracker only mode, using attitude and derived rate from one or both of MAP's star trackers for onboard attitude determination and control. The last backup mode onboard allows a sun-line angle offset to be commanded that will allow solar radiation pressure to be used for momentum management and orbit stationkeeping. In addition to the backup modes implemented on the spacecraft, two backup algorithms have been developed in the event of less likely contingencies. One of these is an algorithm for implementing an alternative scan pattern to MAP's nominal dual-spin science mode using only one or two reaction wheels and thrusters. Finally, an algorithm has been developed that uses thruster one shots while in science mode for momentum management. This algorithm has been developed in case system momentum builds up faster than anticipated, to allow adequate momentum management while minimizing interruptions to science. In this paper, each mode and algorithm will be discussed, and simulation results presented.

ODonnell, James R., Jr.↗

Comparison of Orion Flywheel to Commercially Available Flywheel Device

INTRODUCTION: The chosen exercise device for the Orion Multi-purpose Crew Vehicle (MPCV) for Artemis missions is the Orion Flywheel (OFW), which was selected in 2017 from a pool of exercise devices. The Orion Flywheel is to be installed in the MPCV for its first use during the Artemis II mission and will be utilized for subsequent Artemis missions. The OFW provides the capability to perform both resistive and aerobic exercises while taking up a small volume and not requiring power. Aerobic exercise consists of rowing while resistive exercise includes the deadlift, harness squat, and deadlift high pull among others. The efficacy of the OFW as an exercise countermeasure to spaceflight deconditioning has not yet been fully evaluated. A future HRP-funded study using head-down tilt bed rest is planned to evaluate the efficacy of the OFW to mitigate aerobic and muscular deconditioning. The OFW, made by KBR, is a specialized device that poses high costs for purchase and maintenance. The aim of the study is to determine if a commercially available alternative could be used as a backup for the OFW during the bed rest study or as an alternative in other studies. This study seeks to compare the loading profile and mechanics of a commercial flywheel device (kBox Pro) with the three resistance settings of the OFW using a controlled, instrumented setup to validate its acceptability as a backup. METHODS: An experimental setup was designed to simulate human use of the OFW. Flywheel devices can have varied actuated inertial mass and strap length. The inertial mass refers to the flywheel itself or the object that spins as the result of the movement of the strap. The OFW has three gears actuated with a lever, with the low gear used for aerobic rowing and the medium and high gears used for resistance exercises. These gears correspond to increasing flywheel inertia, which corresponds to a certain number and sizes of inertial plates on a commercial flywheel. The kBox Pro has varied sizes of inertial discs that are installed to the external shaft of the device and can be configured to roughly match the inertia seen in the OFW per gear setting. The strap length can be adjusted to allow for different ranges of motion. The experimental setup allows for the simulation of rowing, harness squats, and deadlift high pulls with corresponding exercise strap lengths. All three OFW gears are to be tested, as well as multiple combinations of kBox discs. The setup was created using a system of pulleys and cables to minimize friction loss. The system is actuated through the dropping of a connected mass which, through the pulley system, pulls the strap of the exercise device upwards as if a human was exercising. A string potentiometer and tensile force transducer are used to measure strap displacement and strap force, respectively. The masses dropped are exercise chains that simulate the decrease in force observed throughout a typical exercise. As the chains are lowered to the ground, they begin to spool and therefore are no longer subjecting the exercise device’s strap to their load. This setup was designed to provide realistic loads and protect the OFW from damage, an important precaution because it’s the only available unit for research and ground operations. Data is to be collected across simulated exercises and with different strap lengths, with the same conditions collected on both the OFW and the kBox Pro. RESULTS: Data collection is ongoing for the kBox and the Orion Flywheel. CONCLUSIONS: Study results will inform if the OFW and a kBox Pro device can be deemed mechanically similar. Depending on the results, additional data collection may be required to assess the user experience between the devices. A key result of this study is a mechanical characterization of the OFW device, demonstrating the load and force profile using a repeatable test method. This data will guide next steps on potential kBox Pro modifications needed to produce a comparable exercise experience to the OFW.

Exercise↗