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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

An Exploratory Exercise in Taguchi Analysis of Design Parameters: Application to a Shuttle-to-space Station Automated Approach Control System

The chief goals of the summer project have been twofold - first, for my host group and myself to learn as much of the working details of Taguchi analysis as possible in the time allotted, and, secondly, to apply the methodology to a design problem with the intention of establishing a preliminary set of near-optimal (in the sense of producing a desired response) design parameter values from among a large number of candidate factor combinations. The selected problem is concerned with determining design factor settings for an automated approach program which is to have the capability of guiding the Shuttle into the docking port of the Space Station under controlled conditions so as to meet and/or optimize certain target criteria. The candidate design parameters under study were glide path (i.e., approach) angle, path intercept and approach gains, and minimum impulse bit mode (a parameter which defines how Shuttle jets shall be fired). Several performance criteria were of concern: terminal relative velocity at the instant the two spacecraft are mated; docking offset; number of Shuttle jet firings in certain specified directions (of interest due to possible plume impingement on the Station's solar arrays), and total RCS (a measure of the energy expended in performing the approach/docking maneuver). In the material discussed here, we have focused on single performance criteria - total RCS. An analysis of the possibility of employing a multiobjective function composed of a weighted sum of the various individual criteria has been undertaken, but is, at this writing, incomplete. Results from the Taguchi statistical analysis indicate that only three of the original four posited factors are significant in affecting RCS response. A comparison of model simulation output (via Monte Carlo) with predictions based on estimated factor effects inferred through the Taguchi experiment array data suggested acceptable or close agreement between the two except at the predicted optimum point, where a difference outside a rule-of-thumb bound was observed. We have concluded that there is most likely an interaction effect not provided for in the original orthogonal array selected as the basis for our experimental design. However, we feel that the data indicates that this interaction is a mild one and that inclusion of its effect will not alter the location of the optimum.

Deal, Don E.↗
NASA NTRS1995

Supporting technology for the development of Controlled Ecological Life Support Systems (CELSS)

To support the development of Controlled Ecological Life Support Systems (CELSS) in the space program, a metabolic simulator has been selected for use in a closed chamber to test functions of the CELSS. This metabolic simulator is a catalytic reactor which oxidizes the methyl acetate to produce carbon dioxide and water vapor. In this project, kinetic studies of catalytic oxidation of methyl acetate were conducted using monolithic and pellet catalysts with 0.5% (by weight) platinum (Pt) on aluminum oxide (Al2O3). The reaction was studied at a pressure of one atmosphere and at temperatures varying from 160 C to 420 C. By-products were identified at the exit of the preheater and reactor. For the kinetic study with the monolithic catalyst, a linear regression method was used to correlate the kinetic data with zero-order, first-order and Langmuir-Hinshelwood models. Results indicate that the first-order model represents the data adequately at low concentrations of methyl acetate. For higher concentrations of methyl acetate, the Langmuir-Hinshelwood model best represents the kinetic data. Both rate constant and adsorption equilibrium constants were estimated from the regression. A Taguchi orthogonal array (L(sub 9)) was used to investigate the effects of temperature, flow rate, and concentration on the catalytic oxidation of methyl acetate. For the monolithic catalyst, temperature exerts the most significant effect, followed by concentration of methyl acetate. For the pellet catalyst, reaction temperature is the most significant factor, followed by gas flow rate and methyl acetate concentration. Concentrations of either carbon dioxide or oxygen were seen to have insignificant effect on the methyl acetate conversion process. Experimental results indicate that the preheater with glass beads can accomplish thermal cracking and catalytic reaction of methyl acetate to produce acetic acid, methanol, methyl formate, and 1-propanol. The concentration of all by-products was measured in ppmv (parts per million by volume). At higher temperatures, greater amounts of these products are produced, as expected. In all cases, methanol was the predominant concentration detected, followed by methyl formate. At temperatures lower than 320 C for the P-type monolithic catalyst, methanol, acetic acid, and acetone were detected, whereas, for the E-type monolithic catalyst, only methanol was detected at 160 C. Both P and E types of the monolithic catalyst were specified with the same substrates (ceramic), washcoat (Al2O3), and promoter (Pt). However, the manufacturing and treatment procedures were quite different. It was therefore concluded that the performance of the E-type monolithic catalyst is superior to that of the P-type for oxidation of methyl acetate. At higher reaction temperatures, e.g., above 420 C, all reactants and byproducts were completely oxidized using these two types of monolithic catalyst to produce carbon dioxide and water vapor. A complex heterogenous catalytic reaction mechanism was proposed to explain the formation of the byproducts (methanol, acetic acid, and methyl formate) as the methyl acetate traveled through the preheater packed with glass beads. The by-product, 1-propanol, may be formed only through a homogeneous reaction, since it is difficult to develop a reasonable sequence of heterogeneous reaction steps to explain its formation. The homogeneous thermal decomposition of methyl acetate to form free radicals was proposed to explain the formation of 1-propanol, and also methanol, in the preheater. A dual-site catalytic reaction mechanism was proposed for the oxidation of methyl acetate over Pt/Al2O3 monolithic catalyst. The dual-site mechanism describes the chemisorption of oxygen molecules as well as a physical adsorption of methyl acetate on the active sites. On the active sites, methyl acetate is oxidized rapidly to form carbon dioxide and water vapor. A rate equation derived from this mechanism gives the Langmuir-Hinshelwood rate formula which has been observed from the experimental data obtained in this project for high methyl acetate concentration (greater than 1000 ppmv) over a monolithic catalyst. If the oxygen concentration is very high and methyl acetate concentration is very low, the reaction rate equation is then reduced to a first-order with respect to methyl acetate concentration. The first-order model has also been observed from the experimental data obtained in this project for low methyl acetate concentration (less than 1000 ppmv).

Li, Ku-Yen↗
DOE OSTI2023

Explaining machine-learning models for gamma-ray detection and identification

As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray spectroscopy, including the introduction of gradient-based methods like saliency mapping and Gradient-weighted Class Activation Mapping (Grad-CAM), and black box methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). In addition, new sources of synthetic radiological data are becoming available, and these new data sets present opportunities to train models using more data than ever before. In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify modifications that need to be applied to adapt the methods to gamma-ray spectral data. We find that the black box methods LIME and SHAP are especially accurate in their results, and recommend SHAP since it requires little hyperparameter tuning. We also propose and demonstrate a technique for generating counterfactual explanations using orthogonal projections of LIME and SHAP explanations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A Classification of G -invariant Shallow Neural Networks

When trying to fit a deep neural network (DNN) to a G-invariant target function with G a group, it only makes sense to constrain the DNN to be G-invariant as well. However, there can be many different ways to do this, thus raising the problem of “G-invariant neural architecture design”: What is the optimal Ginvariant architecture for a given problem? Before we can consider the optimization problem itself, we must understand the search space, the architectures in it, and how they relate to one another. In this paper, we take a first step towards this goal; we prove a theorem that gives a classification of all G-invariant single-hidden-layer or “shallow” neural network (G-SNN) architectures with ReLU activation for any finite orthogonal group G, and we prove a second theorem that characterizes the inclusion maps or “network morphisms” between the architectures that can be leveraged during neural architecture search (NAS). The proof is based on a correspondence of every G-SNN to a signed permutation representation of G acting on the hidden neurons; the classification is equivalently given in terms of the first cohomology classes of G, thus admitting a topological interpretation. The G-SNN architectures corresponding to nontrivial cohomology classes have, to our knowledge, never been explicitly identified in the literature previously. Using a code implementation, we enumerate the G-SNN architectures for some example groups G and visualize their structure. Lastly, we prove that architectures corresponding to inequivalent cohomology classes coincide in function space only when their weight matrices are zero, and we discuss the implications of this for NAS.

Agrawal, Devanshu↗
DOE OSTI2021

Rodeo Algorithm for Quantum Computing

We present a stochastic quantum computing algorithm that can prepare any eigenvector of a quantum Hamiltonian within a selected energy interval $\ [E-\epsilon, E+\epsilon]$. In order to reduce the spectral weight of all other eigenvectors by a suppression factor δ, the required computational effort scales as $\ O[|\log \delta|/(p \epsilon)]$, where p s the squared overlap of the initial state with the target eigenvector. The method, which we call the rodeo algorithm, uses auxiliary qubits to control the time evolution of the Hamiltonian minus some tunable parameter E . In this manner, we converge to the target eigenvector with exponential accuracy in the number of measurements. In addition to preparing eigenvectors, the method can also compute the full spectrum of the Hamiltonian. We illustrate the performance with several examples. For energy eigenvalue determination with error $\epsilon$, the computational scaling is $\ O[(\log \epsilon)^2/(p \epsilon)]$. For eigenstate preparation, the computational scaling is $\ O(\log \Delta/p)$, where $\Delta$ is the magnitude of the orthogonal component of the residual vector. The speed for eigenstate preparation is exponentially faster than that for phase estimation or adiabatic evolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Towards Reconstruction of Complex Flow Fields Using Unit Flows

Many complex turbulent flows in nature and engineering can be qualitatively regarded as being constituted of multiple simpler unit flows. The objective of this work is to characterize the coherent structures in such complex flows as a combination of constituent unitary flow structures for the purpose of reduced-order representation. While turbulence is clearly a non-linear phenomenon, we aim to establish the degree to which the optimally weighted superposition of unitary flow structures can represent the complex flow structures. The rationale for investigating such superposition stems from the fact that the large-scale coherent structures are generated by underlying flow instabilities that may be reasonably described using linear analysis. Clearly, the degree of validity of superposition will depend on the flow under consideration. In this work, we take the first step toward establishing a procedure for investigating superposition. Experimental data of single and triple tandem jets in crossflow are used to demonstrate the procedure. A composite triple tandem jet flow field is generated from optimal superposition of single jet data and compared against ‘true’ triple jet data. Direct comparisons between the true and composite fields are made for spatial, temporal, and kinetic energy content. The large-scale features (obtained from proper orthogonal decomposition or POD) of true and composite tandem jet wakes exhibit nearly 70% agreement in terms of modal eigenvector correlation. Corresponding eigenvalues reveal that the kinetic energy of the flow is also emulated with only a slight overprediction. Temporal frequency features are also examined in an effort to completely characterize POD modes. The proposed method serves as a foundation for more rigorous and robust dimensional reduction in complex flows based on unit flow modes.

Kristo, Paul J.↗
DOE OSTI2020

Online adaptive basis refinement and compression for reduced-order models via vector-space sieving

In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dimensional trial basis to represent the FOM solution. As a result, ROMs can generate inaccurate approximate solutions, e.g., when the FOM solution at the online prediction point is not well represented by training data used to construct the trial basis. To address this fundamental deficiency of standard model-reduction approaches, this work proposes a novel online-adaptive mechanism for efficiently enriching the trial basis in a manner that ensures convergence of the ROM to the FOM, yet does not incur any FOM solves. The mechanism is based on the previously proposed adaptive $h$-refinement method for ROMs, but improves upon this work in two crucial ways. First, the proposed method enables basis refinement with respect to any orthogonal basis (not just the Kronecker basis), thereby generalizing the refinement mechanism and enabling it to be tailored to the physics characterizing the problem at hand. Second, the proposed method provides a fast online algorithm for periodically compressing the enriched basis via an efficient proper orthogonal decomposition (POD) method, which does not incur any operations that scale with the FOM dimension. We report these two features allow the proposed method to serve as (1) a failsafe mechanism for ROMs, as the method enables the ROM to satisfy any prescribed error tolerance online (even in the case of inadequate training), and (2) an efficient online basis-adaptation mechanism, as the combination of basis enrichment and compression enables the basis to adapt online while controlling its dimension.

42 ENGINEERING↗
NASA NTRS2001

Status of the Direct Data Distribution (D(exp 3)) Experiment

NASA Glenn Research Center's Direct Data Distribution (D3) project will demonstrate an advanced, high-performance communications system that transmits information from an advanced technology payload carried by a NASA spacecraft in low Earth orbit (LEO) to a small receiving terminal on Earth. The space-based communications package will utilize a solid-state, K-band phased-array antenna that electronically steers the radiated energy beam toward a low-cost, tracking ground terminal, thereby providing agile, vibration-free, electronic steering at reduced size and weight with increased reliability. The array-based link will also demonstrate new digital processing technology that will allow the transmission of substantially increased amounts of latency-tolerant data collected from the LEO spacecraft directly to NASA field centers, principal investigators, or into the commercial terrestrial communications network. The technologies demonstrated by D3 will facilitate NASA's transition from using Government-owned communication assets to using commercial communication services. The hardware for D3 will incorporate advanced technology components developed under the High Rate Data Delivery (HRDD) Thrust Area of NASA's Office of Aerospace Technology Space Base Program at Glenn's Communications Technology Division. The flight segment components will include the electrically steerable phased-array antenna, which is being built by the Raytheon System Corporation and utilizes monolithic microwave integrated circuit (MMIC) technology operating at 19.05 GHz; and the digital encoder/modulator chipset, which uses four-channel orthogonal frequency division multiplexing (OFDM). The encoder/modulator will use a chipset developed by SICOM, Inc., which is both bandwidth and power efficient. The ground segment components will include a low-cost, open-loop tracking ground terminal incorporating a cryoreceiver to minimize terminal size without compromising receiver capability. The project is planning to hold a critical design review in the second quarter of fiscal year 2002.

Wald, Lawrence↗
DOE OSTI2023

EI_MS_ML

The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation. Substructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit. Determining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.

Mitchell, Joshua↗
NASA NTRS2011

Fiber-Optic Magnetic-Field-Strength Measurement System for Lightning Detection

A fiber-optic sensor system is designed to measure magnetic fields associated with a lightning stroke. Field vector magnitudes are detected and processed for multiple locations. Since physical limitations prevent the sensor elements from being located in close proximity to highly conductive materials such as aluminum, the copper wire sensor elements (3) are located inside a 4-cubic-in. (.66-cubic-cm) plastic housing sensor head and connected to a fiber-optic conversion module by shielded cabling, which is limited to the shortest length feasible. The signal path between the conversion module and the avionics unit which processes the signals are fiber optic, providing enhanced immunity from electromagnetic radiation incident in the vicinity of the measurements. The sensors are passive, lightweight, and much smaller than commercial B-dot sensors in the configuration which measures a three-dimensional magnetic field. The system is expandable, and provides a standard-format output signal for downstream processing. Inside of the sensor head, three small search coils, each having a few turns on a circular form, are mounted orthogonally inside the non-metallic housing. The fiber-optic conversion module comprises three interferometers, one for each search coil. Each interferometer has a high bandwidth optical phase modulator that impresses the signal received from its search coil onto its output. The output of each interferometer travels by fiber optic cable to the avionics unit, and the search coil signal is recovered by an optical phase demodulator. The output of each demodulator is fed to an analog-to-digital converter, whose sampling rate is determined by the maximum expected rate of rise and peak signal magnitude. The output of the digital processor is a faithful reproduction of the coil response to the incident magnetic field. This information is provided in a standard output format on a 50-ohm port that can be connected to any number of data collection and processing instruments and/or systems. The measurement of magnetic fields using fiber-optic signal processing is novel because it eliminates limitations of a traditional B-dot system. These limitations include the distance from the sensor to the measurement device, the potential for the signal to degrade or be corrupted by EMI from lightning, and the size and weight of the sensor and associated plate.

Gurecki, Jay↗
NASA NTRS2024

Development of a Data Fusion Methodology for Lineload Aerodynamic Databases for a Launch Vehicle during Liftoff and Transition

The need for databases for the distributed loading on launch vehicles during the early portion of flight necessitates the use of expensive computational flows in regimes where wake effects dominate. While also being expensive, this is a regime that computational tools tend to historically have problems simulating accurately. To help tackle this problem, a method of data fusion to combine computational results to wind tunnel derived force and moment data is developed. Using this method, significant reduction in computational costs and increases in confidence of the final product is possible and has been used to generate several databases for the Space Launch System (SLS) at NASA. While the full details of database generation are not part of this work, the crucial method at its core is developed here. Two SLS geometries are used throughout the work to demonstrate the techniques. These are two of the larger geometries and represent both planned crewed missions to the Moon as well as potential cargo missions to deep space. The method uses principal component analysis (PCA) to generate a reduced ordered model (ROM) to help fill in the full parameter space. Other similar techniques are explored, but were not found to have a significant result on the predictions of the ROM. Because the full number of components are kept to generate the model, this lack of difference is expected. This method is then extended to ensure that predicted surfaces match trusted force and moment data derived from wind tunnel testing. This extension is done by setting up a constrained optimization problem in order to minimize the deviation from the surface resolved computational data while still integrating to the desired values. When generating the constrained optimization problem, a weighting factor to balance these competing needs is introduced. The work compares previously introduced weighting terms from similar work to the proposed terms and shows that the previously used terms do not have as desirable behavior in this flow regime. This method is then expanded by developing a technique to incorporate uncertainty quantification into the developed data fusion methodology. This expansion takes a two pronged approach. One examines transferring the uncertainties in the force and moment database and characterizes how those adjustments change the predicted lineloads. The second looks at model form error and looks how rebuilding the model using slightly different data changes the predictions. These two terms are then combined in order to create an uncertainty model that takes both effects into account. The limitations of the proposed methods is then discussed as well as possible techniques to address these shortcomings.

Launch Vehicles↗
NASA NTRS1993

Introduction to magnetic bearings

Multi-axis suspension has several advantages over single axis system, in that it provides control of an object with precision in two or three orthogonal axes. In this report, we discuss the primary use of magnetic-bearing suspension and it's relevance to what was formally known as NASA's Annular Suspension and Pointing System (ASPS). This system is an experimental pointing system with applications for the space shuttle and the space station programs. The objectives behind this magnetic suspension research project are to provide insight to the use of the ASPS configuration, to control the solar panels of the space station. This is important to maintain the correct position of the panels in relation to the sun and orbiting space station for the continuous supply of solar energy. Since the panels are suspended, they can be aligned with minimum outside interference. The approach of using magnetic suspension technology guarantees mechanical isolation since there are no contacting surfaces. This isolation reduces vibration transmission and mechanical wear which in turn extends the life of the payload and of the carrier. It should be noted that ASPS has a high pointing accuracy along the line of 0.01 arc-second. This research will be done in a laboratory setting by incorporating five bearing stations and one motion control station. We will attempt to suspend an object of dead weight similar to that of a solar panel. The long term applications may include deep-space navigation, fire control in weapon systems, and an improved mass transit system.

Skowronski, Lori↗
DOE OSTI2021

Regional Moment Tensor Inversion Using Rotational Observations

There are benefits from the addition of rotational motions to translational displacements for moment tensor (MT) inversions. The rotational radiation pattern is orthogonal to the shear radiation pattern, thus incorporating rotations is equivalent to gaining another observation point on the focal sphere. We demonstrated this by simulating curl and displacement wavefields for a regional distance station. Thus, one 6-C station (3-Component translational + 3-Component rotational) gathers the same information on radiation pattern as two 3-C stations at 90° azimuth from one another along the focal plane axis, which is sometimes difficult to obtain when restricted to surface sensors. We added rotational Green's functions to a regional MT inversion scheme (long-period, time-domain, and linear inversion) by computing spatial gradients from f-κ reflectivity synthetics. For rotational data, we used Array Derived Rotations (ADR) from Piñon Flats Observatory Array and Golay array deployed during IRIS Community Wavefield Demonstration Experiment. The hope is to ultimately use compact and field deployable broadband rotational seismometers instead of ADRs. Rotational motions were predicted from well-constrained deviatoric MT solutions of nine earthquakes recorded by the arrays and other seismic networks. Additionally, we formed three station sparse datasets with (3-C and 6-C) and without rotational ground motions (3-C only) for eight earthquakes testing the benefits of including rotational waveforms in MT inversions when they are equally weighted with translational waveforms. Adding rotational motions improved the double-couple components and reduced compensated-linear-vector-dipole and isotropic components in full-MT solutions using sparse datasets with poor coverage.

58 GEOSCIENCES↗
NASA NTRS2001

On-Orbit Calibration of Redundant Spacecraft Gyros by Optimal Reduction to Three Axes

The Aqua spacecraft will carry four single-axis gyros configured with three orthogonal axes and one skew axis. This redundancy presents a challenge for batch methods of on-orbit gyro calibration that use a spacecraft rotation model deterministically related to gyro data, in that sensor data can respond to at most three angular velocity components. When the number of gyros, N, is greater than 3, the 3xN matrix, G, that reduces the N gyro measurements to three body-frame angular-velocity components cannot be fully determined by such methods; there are many such matrices that produce essentially the same angular velocity history. In such a case, spacecraft operators require information about the Nx3 gyro linear response matrix, R, that relates gyro outputs to the body-frame angular velocities causing them. This matrix provides sufficient information to determine multiple reduced-dimension G-matrices for use in case of failure or degradation of one or more gyros, as well as to determine an optimal 3xN G for the fully-functional configuration. A viable proposal is to apply a 3xN pre-filter matrix, F, to the N gyro outputs before carrying out a conventional gyro calibration procedure. The angular-velocity history emerging from conventional calibration may then be used as input data, together with the same gyro data that generated it, to fit the alignment, scale-factor, and bias parameters of each gyro axis in turn. A difficulty of such a proposal is the arbitrariness in the choice of F. Due to gyro noise, different pre-filter matrices produce different calibrations. This paper presents a method of choosing F that is based on optimizing gyro consistency in the limit of infinite weight on gyro data, as compared to sensor data. The choice of F is independent of a priori alignment and is based on the gyro data alone. The method is applicable to any N of three or more, but reduces to conventional batch-estimation methodologies when N = 3. Results of computational comparison among calibration simulations using various choices of F will be presented for the Aqua gyro configuration with N = 4.

Radomski, M. S.↗
NASA NTRS2004

Foot-ground reaction force during resistive exercise in parabolic flight

INTRODUCTION: An interim resistance exercise device (iRED) was designed to provide resistive exercise as a countermeasure to spaceflight-induced loss of muscle strength and endurance as well as decreased bone mineral density. The purpose of this project was to compare foot-ground reaction force during iRED exercise in normal gravity (1 G) vs. microgravity (0 G) achieved during parabolic flight. METHODS: There were four subjects who performed three exercises (squat, heel raise, and deadlift) using the iRED during 1 G and 0 G at a moderate intensity (60% of maximum strength during deadlift exercise). Foot-ground reaction force was measured in the three orthogonal axes (x, y, z) using a force plate, and the magnitude of the resultant force vector was calculated (r = square root(x2 + y2 + z2)). Linear displacement (LD) was measured using a linear transducer. Peak force (Fpeak) and an index of total work (TWi) were calculated using a customized computer program. Paired t-tests were used to test if significant differences (p < or = 0.05) were observed between 1 G and 0 G exercise. RESULTS: Fpeak and TWi measured in the resultant axis were significantly less in 0 G for each of the exercises tested. During 0 G, Fpeak was 42-46% and TWi was 33-37% of that measured during 1 G. LD and average time to complete each repetition were not different from 1 G to 0 G. CONCLUSIONS: Crewmembers who perform resistive exercises during spaceflight that include the movement of a large portion of their body mass will require much greater external resistive force during 0 G than 1 G exercise to provide a sufficient stimulus to maintain muscle and bone mass.

Physical Education and Training↗