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At least 163 records · Page 9

A comparison between bright points in a coronal hole and a quiet-sun region

A comparison is made of the morphological structure and temporal behavior of the emission from coronal bright points in a coronal hole and a quiet region, using data from the Harvard EUV experiment on Skylab. It is found that, in both regions, coronal bright points are located at network boundaries and cover a range of sizes from 10 to 40 in in linear extent. In a given bright pint, the peaks of emission in the six different lines, measured simultaneously through the same instrument slit, are not always cospatial, implying that bright points consist of a complex of small-scale loops at different temperatures. The intensity of bright points in both regions is also characterized by a significant temporal variability in all the wavelengths measured. This variability exhibits no regular periodicity. Yet the ratio of the varying (ac) to the constant (dc) components of the emission, in all the bright points studied, has a local maximum at 1-2 x 10 to the 5th k which coincides with the peak of the radiative loss function, and another local maximum at Mg x (1.4 x 10 to the 6th K). It is found that coronal bright points in a coronal hole or a quiet region are indistinguishable structures, and, therefore, conclude that they are independent of the overlying background corona.

Habbal, Shadia Rifai↗

Attitude determination and parameter estimation using vector observations - Application

This paper presents tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and earth-pointing attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. In the majority of tests performed, the two methods converge to the same estimates in the same number of iterations, but the new algorithm requires about 60 percent more computational effort. Some cases were found in which the new method converges in fewer iterations than the differential correction, and some for which the differential correction requires fewer iterations.

Markley, F. Landis↗

The effects of nonequilibrium ionization on the radiative losses of the solar corona

The emissivity of the ions of carbon and oxygen has been recalculated for a set of solar coronal loop models with a steady state siphon flow. The ion densities were calculated from the plasma velocities, temperatures, and densities of the models, and large departures from equilibrium were found. For purposes of comparison, the emissivity was calculated with and without the approximation of ionization equilibrium. Considerable differences in the radiative loss function Lambda(T) curve between equilibrium and nonequilibrium conditions were found. The nonequilibrium Lambda(T) function was then used to solve again the steady state flow equations of the loop models. The differences in the structure of these models with respect to the models calculated adopting the Lambda(T) curve in equilibrium are discussed.

Spadaro, D.↗

k-out-of-n:G systems - Some cost considerations

The authors provide a tool that an engineer designing a subsystem can use to decide between one subsystem and a more reliable but more costly one. The authors provide methods for selecting redundancy levels in k-out-of-n:G systems in order to minimize particular cost considerations where the k-out-of-n:G system is a subsystem of a major system. The n and k are chosen to minimize the total cost of the subsystem plus the average loss due to subsystem failure. A BASIC program is available to determine the n and k which find this minimum. Five loss functions are considered, and illustrations are given.

Suich, Ronald C.↗

Control of Complex Dynamic Systems by Neural Networks

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

Spall, James C.↗

Taguchi method of experimental design in materials education

Some of the advantages and disadvantages of the Taguchi Method of experimental design as applied to Materials Science will be discussed. This is a fractional factorial method that employs the minimum number of experimental trials for the information obtained. The analysis is also very simple to use and teach, which is quite advantageous in the classroom. In addition, the Taguchi loss function can be easily incorporated to emphasize that improvements in reproducibility are often at least as important as optimization of the response. The disadvantages of the Taguchi Method include the fact that factor interactions are normally not accounted for, there are zero degrees of freedom if all of the possible factors are used, and randomization is normally not used to prevent environmental biasing. In spite of these disadvantages it is felt that the Taguchi Method is extremely useful for both teaching experimental design and as a research tool, as will be shown with a number of brief examples.

Weiser, Martin W.↗

A simple suboptimal least-squares algorithm for attitude determination with multiple sensors

Three-axis attitude determination is equivalent to finding a coordinate transformation matrix which transforms a set of reference vectors fixed in inertial space to a set of measurement vectors fixed in the spacecraft. The attitude determination problem can be expressed as a constrained optimization problem. The constraint is that a coordinate transformation matrix must be proper, real, and orthogonal. A transformation matrix can be thought of as optimal in the least-squares sense if it maps the measurement vectors to the reference vectors with minimal 2-norm errors and meets the above constraint. This constrained optimization problem is known as Wahba's problem. Several algorithms which solve Wahba's problem exactly have been developed and used. These algorithms, while steadily improving, are all rather complicated. Furthermore, they involve such numerically unstable or sensitive operations as matrix determinant, matrix adjoint, and Newton-Raphson iterations. This paper describes an algorithm which minimizes Wahba's loss function, but without the constraint. When the constraint is ignored, the problem can be solved by a straightforward, numerically stable least-squares algorithm such as QR decomposition. Even though the algorithm does not explicitly take the constraint into account, it still yields a nearly orthogonal matrix for most practical cases; orthogonality only becomes corrupted when the sensor measurements are very noisy, on the same order of magnitude as the attitude rotations. The algorithm can be simplified if the attitude rotations are small enough so that the approximation sin(theta) approximately equals theta holds. We then compare the computational requirements for several well-known algorithms. For the general large-angle case, the QR least-squares algorithm is competitive with all other know algorithms and faster than most. If attitude rotations are small, the least-squares algorithm can be modified to run faster, and this modified algorithm is faster than all but a similarly specialized version of the QUEST algorithm. We also introduce a novel measurement averaging technique which reduces the n-measurement case to the two measurement case for our particular application, a star tracker and earth sensor mounted on an earth-pointed geosynchronous communications satellite. Using this technique, many n-measurement problems reduce to less than or equal to 3 measurements; this reduces the amount of required calculation without significant degradation in accuracy. Finally, we present the results of some tests which compare the least-squares algorithm with the QUEST and FOAM algorithms in the two-measurement case. For our example case, all three algorithms performed with similar accuracy.

Brozenec, Thomas F.↗

Kalman filter estimation of attitude and gyro bias with the QUEST observation model

The loss function for the Wahba attitude estimation problem employs unit vector observations with scalar weights. It is usually associated with the QUEST observation model, where the actual sensor noise is assumed the same for all components of the observed vector, regardless of the position in the field of view. The QUEST model has the great advantage of being sensor-independent except for the scalar parameter that characterizes the sensor errors. Although efficient algorithms for solving the Wahba problem exist, extending these algorithms to estimate gyro biases or sensor alignments has had mixed success. However, it is straightforward to estimate bias and alignment parameters with a Kalman filter. This paper investigates the use of an extended Kalman filter for the attitude and gyro bias that incorporates the QUEST observation model, to be referred to as the Unit Vector Filter (UVF). The UVF results are compared with those from a more conventional filter, the Real-Time Sequential Filter (RTSF), for which the residual is the two-dimensional projection of the unit vector onto the plane perpendicular to the sensor boresight. The RTSF is similar in design to that used by Multimission Modular Spacecraft for onboard attitude determination. An apparent obstacle to the use of unit vectors as measurements is their singular noise covariance matrix. Shuster has shown that this problem should not affect filter performance. The UVF and RTSF are tested using actual flight data from the Extreme Ultraviolet Explorer (EUVE). It is found that these filters generate nearly identical attitude and gyro bias estimates, thus validating the use of unit vectors and the QUEST noise model.

Sedlak, J.↗

Turbines For Optomechanical Energy Conversion

Class of proposed optomechanical energy-conversion machines exploit multiple reflections from precise, high-reflectivity mirrors, some of which fixed to turbinelike rotors that spin at high speeds. Basic idea to increase frequencies of photons (and thus energy of light) by repeated Doppler-shifting reflections from moving mirrors. Gain in optical energy in such reflection proportional to speed of mirror, while loss function of imperfections of mirror.

Dick, G. John↗

Fast Integer Ambiguity Resolution for GPS Attitude Determination

In this paper, a new algorithm for GPS (Global Positioning System) integer ambiguity resolution is shown. The algorithm first incorporates an instantaneous (static) integer search to significantly reduce the search space using a geometric inequality. Then a batch-type loss function is used to check the remaining integers in order to determine the optimal integer. This batch function represents the GPS sightline vectors in the body frame as the sum of two vectors, one depending on the phase measurements and the other on the unknown integers. The new algorithm has several advantages: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can resolve the integers even when coplanar baselines exist. The performance of the new algorithm is tested on a dynamic hardware simulator.

Lightsey, E. Glenn↗

30 Years of Wahba's Problem

This article discusses a problem proposed by Grace Wahba: Find the orthogonal matrix A with determinant +1 that minimizes the loss function L(A) is identical with the 1/2(summation from i( a(sub i) * absolute value of (b(sub i)- Ar(sub i))squared). where {b(sub i)} is a set of unit vectors measured in a spacecraft's body frame, {r(sub i)} e the corresponding unit vectors in a reference frame and {a(sub i) are non-negative weights). The orthogonal Procrustes problem is to find the orthogonal matrix A that is closest to B in the sense of the Fobenius norm, so that Wahba's Problem is equivalent to the orthogonal Procrustes problem with the provision that the determinant of A must be +1. The article reviews various solutions to this problem and the implementations of the various solutions.

Markley, F. Landis↗

How to Estimate Attitude from Vector Observations

In many spacecraft attitude systems, the attitude observations are naturally represented as unit vectors. Typical examples are the unit vectors giving the direction to the sun or a star and the unit vector in the direction of the Earth's magnetic field. In 1965, Grace Wahba, proposed the following problem: Find the orthogonal matrix A with determinant +1 that minimizes the loss function L(A) is identity with 1/2(Sum from i a(sub i) (absolute value of b(sub i - A(r(sub i))(exp 2))) where the set of b(sub i) is a set of unit vectors measured in a spacecraft's body frame, the set of r(sub i) are the corresponding unit vectors in a reference frame, and the set of a(sub i) are non-negative weights. Wahba's problem can be related to Maximum Likelihood Estimation if the weights are chosen to be inverse variances, a(sub i) = sigma((sub -2). Wahba didn't assume this, but it will be convenient to assume it in this paper. Wahba'soptimality condition has provided the basis for many attitude determination algorithms. The purpose of this paper is to give an overview of the most popular and most promising algorithm and to provide accuracy and speed comparisons.

Markley,F. Landis↗

How to Estimate Attitude from Vector Observations

The most robust estimators minimizing Wahba's loss function are Davenport's q method and the Singular Value Decomposition (SVD) method. The q method is faster than the SVD method with three or more measurements. The other algorithms are less robust since they solve the characteristic polynomial equation to find the maximum eigenvalue of Davenport's K matrix. They are only preferable when speed or processor power is an important consideration. Of these, Fast Optimal Attitude Matrix (FOAM) is the most robust and faster than the q method. Robustness is only an issue for measurements with widely differing accuracies, so the fastest algorithms, Quaternion ESTimator (QUEST), EStimator of the Optimal Quaternion (ESOQ), and ESOQ2, are well suited to star sensor applications.

Markley, F. Landis↗

New Developments in Quaternion Estimation from Vector Observations

This paper contains a critical comparison of estimators minimizing Wahba's loss function. Some new results are presented for the QUaternion ESTimator (QUEST) and EStimators of the Optimal Quaternion (ESOQ and ESOQ2) to avoid the computational burden of sequential rotations in these algorithms. None of these methods is as robust in principle as Davenport's q method or the Singular Value Decomposition (SVD) method, which are significantly slower. Robustness is only an issue for measurements with widely differing accuracies, so the fastest estimators, the modified ESOQ and ESOQ2, are well suited to sensors that track multiple stars with comparable accuracies. More robust forms of ESOQ and ESOQ2 are developed that are intermediate in speed.

Markley, F. Landis↗

New Attitude Sensor Alignment Calibration Algorithms

Accurate spacecraft attitudes may only be obtained if the primary attitude sensors are well calibrated. Launch shock, relaxation of gravitational stresses and similar effects often produce large enough alignment shifts so that on-orbit alignment calibration is necessary if attitude accuracy requirements are to be met. A variety of attitude sensor alignment algorithms have been developed to meet the need for on-orbit calibration. Two new algorithms are presented here: ALICAL and ALIQUEST. Each of these has advantages in particular circumstances. ALICAL is an attitude independent algorithm that uses near simultaneous measurements from two or more sensors to produce accurate sensor alignments. For each set of simultaneous observations the attitude is overdetermined. The information content of the extra degrees of freedom can be combined over numerous sets to provide the sensor alignments. ALIQUEST is an attitude dependent algorithm that combines sensor and attitude data into a loss function that has the same mathematical form as the Wahba problem. Alignments can then be determined using any of the algorithms (such as the QUEST quaternion estimator) that have been developed to solve the Wahba problem for attitude. Results from the use of these methods on active missions are presented.

Hashmall, Joseph A.↗

Surrogate-based Analysis and Optimization

A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.

Queipo, Nestor V.↗

Predictive Game Theory

Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

Wolpert, David H.↗

Translational Cellular Research on the International Space Station

The emerging field of Translational Research aims to coalesce interdisciplinary findings from basic science for biomedical applications. To complement spaceflight research using human subjects, translational studies can be designed to address aspects of space-related human health risks and help develop countermeasures to prevent or mitigate them, with therapeutical benefits for analogous conditions experienced on Earth. Translational research with cells and model organisms is being conducted onboard the International Space Station (ISS) in connection with various human systems impacted by spaceflight, such as the cardiovascular, musculoskeletal, and immune systems. Examples of recent cell-based translational investigations on the ISS include the following. The JAXA investigation Cell Mechanosensing seeks to identify gravity sensors in skeletal muscle cells to develop muscle atrophy countermeasures by analyzing tension fluctuations in the plasma membrane, which changes the expression of key proteins and genes. Earth applications of this study include therapeutic approaches for some forms of muscular dystrophy, which appear to parallel aspects of muscle wasting in space. Spheroids is an ESA investigation examining the system of endothelial cells lining the inner surface of all blood vessels in terms of vessel formation, cellular proliferation, and programmed cell death, because injury to the endothelium has been implicated as underpinning various cardiovascular and musculoskeletal problems arising during spaceflight. Since endothelial cells are involved in the functional integrity of the vascular wall, this research has applications to Earth diseases such as atherosclerosis, diabetes, and hypertension. The goal of the T-Cell Activation in Aging NASA investigation is to understand human immune system depression in microgravity by identifying gene expression patterns of candidate molecular regulators, which will provide further insight into factors that may play a critical role in immune function loss during aging. In addition, Omics investigations with cells have synergistic applications ranging from the evaluation of pharmacological countermeasures to drug discovery. Thus, cell-based translational research onboard the ISS is bidirectionally bridging cutting-edge cellular and molecular approaches with space bioastronautics and human health methodologies on Earth.

Love, John↗