MS thesis abstract - Bourgault, Frederic
| Author: | Bourgault, Frederic |
| Degree: | Masters of Science |
| SERC #: | 5-00 |
| File type: | PDF, 3341 kB |
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Model Uncertainty and Performance Analysis for Precision Controlled Space Structures
The purpose of this thesis is to provide confidence for the designer that a concept of a future space-based telescope will meet its very stringent requirements. More specifically, our goal is to predict the amount of uncertainty in the performance prediction made through out the design process. Also, given a statistical database for structural uncertainty, the methodology presented will establish the probability of success of a particular architecture. The traditional design process starts by evaluating and comparing the performance of different concepts by using simplified structural and disturbance models. As the process progresses the different solutions are evaluated and the most promising concept is retained and refined. Later on, some preliminary structural testing is performed, and the finite element model is updated to reflect the reality more accurately. Eventually, when the design process approach completion and is moving toward production, most of the structural elements have been tested, and the performance predictions of the model should converge to the actual system performance.
Large flexible space structures present a problem in using this approach because they are often too flexible to support their own weight and/or too large to fit inside any laboratory facilities to be tested fully assembled. For example, it would be impractical to test the whole assembly of the International Space Station or SIM on the ground. Also, during the preliminary design phase, no test data are available to update the models. Nevertheless, even when the model is very mature and has been updated after experimental testing, a discrepancy remains between the predicted and actual performance of the system. These uncertainties are due to various sources of variability in the system: variable noises (sources and levels), testing conditions and environmental factors, assembly/reassembly, shipset, disturbance levels, and others. How then, can we have confidence that a particular concept will meet the requirements if the only tool we have are finite element models that may not be accurate? The solution is to try to estimate the range of uncertainty around our nominal model performances. Since in the early design phase no test data are available, our best bet will be to use past experience to predict the expected uncertainty range on the performances of a new design.
Using sensitivity information and statistical uncertainties from the literature (i.e.: modal mass and stiffness parameters uncertainties [Hasselman & Chrostowski, 1991], as well as modal damping ratios uncertainties [Simonian, 1987]), we demonstrate with different techniques how to obtain estimates of the performance predictions uncertainty ranges. We also obtain the probability distribution function of the performance of the system and use it to deduce its "probability of success" (i.e. the probability that once built the actual structure will satisfy the performance requirements). This last result, which can be obtained without too much computation, has a great useful potential and might become an integral design step for high performance controlled structures as it promises to help build confidence in the model predictions and could be used in the so called error budgeting phase. The techniques are demonstrated on a 2 degree-of-freedom sample case and on a more realistic system: the Space Interferometer Mission (SIM) Calssic model.