Reaction Wheel Disturbance Model Extraction Software - RWDMES

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort

Structure of the cell envelope of Halobacterium halobium

The structure of the isolated cell envelope of Halobacterium halobium is studied by X-ray diffraction, electron microscopy, and biochemical analysis. The envelope consists of the cell membrane and two layers of protein outside. The outer layer of protein shows a regular arrangement of the protein or glycoprotein particles and is therefore identified as the cell wall. Just outside the cell membrane is a 20 A-thick layer of protein. It is a third structure in the envelope, the function of which may be distinct from that of the cell membrane and the cell wall. This inner layer of protein is separated from the outer protein layer by a 65 Å-wide space which has an electron density very close to that of the suspending medium, and which can be etched after freeze-fracture. The space is tentatively identified as the periplasmic space. At NaCl concentrations below 2.0 M, both protein layers of the envelope disintegrate. Gel filtration and analytical ultracentrifugation of the soluble components from the two protein layers reveal two major bands of protein with apparent mol wt of ~16,000 and 21,000. At the same time, the cell membrane stays essentially intact as long as the Mg++ concentration is kept at ≥ 20 mM. The cell membrane breaks into small fragments when treated with 0.1 M NaCl and EDTA, or with distilled water, and some soluble proteins, including flavins and cytochromes, are released. The cell membrane apparently has an asymmetric core of the lipid bilayer

Bis(1H-pyrazole-κN 2)bis­(2,4,6-tri­isopropyl­benzoato-κO)cobalt(II)

The title compound, [Co(C16H23O2)2(C3H4N2)2] or (C3H4N2)2Co(O2CC6H2 iPr3-2,4,6), is a rare example of a tetra­coordinate cobalt(II) carboxyl­ate stabilized by ancillary N-heterocyclic ligands. The Co(II) ion resides on a crystallographic twofold axis so that the asymmetric unit comprises one half-mol­ecule. Due to the steric bulk of the 2,4,6-triisopropyl­phenyl substituents, the carboxyl­ate ligands are both coordinated in a monodentate fashion despite the low coordination number. The coordination geometry around the central Co(II) ion is distorted tetra­hedral with angles at Co ranging from 92.27 (18)° to 121.08 (14)°

Reaction Wheel Disturbance Modeling, Jitter Analysis, and Validation Tests for Solar Dynamics Observatory

The Solar Dynamics Observatory (SDO) aims to study the Sun's influence on the Earth by understanding the source, storage, and release of the solar energy, and the interior structure of the Sun. During science observations, the jitter stability at the instrument focal plane must be maintained to less than a fraction of an arcsecond for two of the SDO instruments. To meet these stringent requirements, a significant amount of analysis and test effort has been devoted to predicting the jitter induced from various disturbance sources. One of the largest disturbance sources onboard is the reaction wheel. This paper presents the SDO approach on reaction wheel disturbance modeling and jitter analysis. It describes the verification and calibration of the disturbance model, and ground tests performed for validating the reaction wheel jitter analysis. To mitigate the reaction wheel disturbance effects, the wheels will be limited to operate at low wheel speeds based on the current analysis. An on-orbit jitter test algorithm is also presented in the paper which will identify the true wheel speed limits in order to ensure that the wheel jitter requirements are met

Dynamic analysis of TMT

Dynamic disturbance sources affecting the optical performance of the Thirty Meter Telescope (TMT) include unsteady wind forces inside the observatory enclosure acting directly on the telescope structure, unsteady wind forces acting on the enclosure itself and transmitted through the soil and pier to the telescope, equipment vibration either on the telescope itself (e.g. cooling of instruments) or transmitted through the soil and pier, and potentially acoustic forces. We estimate the characteristics of these disturbance sources using modeling anchored through data from existing observatories. Propagation of forces on the enclosure or in support buildings through the soil and pier to the telescope base are modeled separately, resulting in force estimates at the telescope pier. We analyze the resulting optical consequences using integrated modeling that includes the telescope structural dynamics, control systems, and a linear optical model. The dynamic performance is given as a probability distribution that includes the variation of the external wind speed and observing orientation with respect to the wind, which can then be combined with dome seeing and other time- or orientation-dependent components of the overall error budget. The modeling predicts acceptable dynamic performance of TMT