An analysis of the optimization of a beam rider missile system
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An identification procedure proposed by Shen and Taylor to determine the crack characteristics (location and size of the crack) from dynamic measurements is tested. This procedure was based on minimization of either the 'mean-square' measure of difference between measurement data (natural frequencies and mode shapes) and the corresponding predictions obtained from the computational model. The procedure is tested for simulated damage in the form of symmetric cracks in a simply-supported Bernoulli-Euler beam. The sensitivity of the solution of damage identification problems to the values of parameters that characterize damage is discussed. A sensitivity formula is derived.
The straightforward automatic-differentiation and the hand-differentiated incremental iterative methods are interwoven to produce a hybrid scheme that captures some of the strengths of each strategy. With this compromise, discrete aerodynamic sensitivity derivatives are calculated with the efficient incremental iterative solution algorithm of the original flow code. Moreover, the principal advantage of automatic differentiation is retained (i.e., all complicated source code for the derivative calculations is constructed quickly with accuracy). The basic equations for second-order sensitivity derivatives are presented; four methods are compared. Each scheme requires that large systems are solved first for the first-order derivatives and, in all but one method, for the first-order adjoint variables. Of these latter three schemes, two require no solutions of large systems thereafter. For the other two for which additional systems are solved, the equations and solution procedures are analogous to those for the first order derivatives. From a practical viewpoint, implementation of the second-order methods is feasible only with software tools such as automatic differentiation, because of the extreme complexity and large number of terms. First- and second-order sensitivities are calculated accurately for two airfoil problems, including a turbulent flow example; both geometric-shape and flow-condition design variables are considered. Several methods are tested; results are compared on the basis of accuracy, computational time, and computer memory. For first-order derivatives, the hybrid incremental iterative scheme obtained with automatic differentiation is competitive with the best hand-differentiated method; for six independent variables, it is at least two to four times faster than central finite differences and requires only 60 percent more memory than the original code; the performance is expected to improve further in the future.
Contractor shall perform a complete analysis of the potential of the solid state laser in the very long pulse mode (100 ns pulse width, 10-30 hz rep-rate) and in the very short pulse mode (100 ps pulse width 10-30 hz rep rate) concentrating on the operation of the device in the 'hot-rod' mode, where no active cooling the laser operation is attempted. Contractor's calculations shall be made of the phase aberrations which develop during the repped-pulse train, and the results shall feed into the adaptive optics analyses. The contractor shall devise solutions to work around ORION track issues. A final report shall be furnished to the MSFC COTR including all calculations and analysis of estimates of bulk phase and intensity aberration distribution in the laser output beam as a function of time during the repped-pulse train for both wave forms (high-energy/long-pulse, as well as low-energy/short-pulse). Recommendations shall be made for mitigating the aberrations by laser re-design and/or changes in operating parameters of optical pump sources and/or designs.
A new structural modeling and analysis method, the Distributed Transfer Function Method (DTFM), is presented for the applications of space gossamer structures.
To maximize reliability of a spacecraft which performs long-life (over 10-year), deep-space mission (to outer planet), a fault-tolerant environment incorporating automatic on-board preventive maintenance is highly desirable.
Recent developments in gas foil bearing technology have led to numerous advanced high-speed rotating system concepts, many of which have become either commercial products or experimental test articles. Examples include Oil-Free microturbines, motors, generators and turbochargers. The driving forces for integrating gas foil bearings into these high-speed systems are the benefits promised by removing the oil lubrication system. Elimination of the oil system leads to reduced emissions, increased reliability, and decreased maintenance costs. Another benefit is reduced power plant weight. For rotorcraft applications, this would be a major advantage, as every pound removed from the propulsion system results in a payload benefit. Implementing foil gas bearings throughout a rotorcraft gas turbine engine is an important long-term goal that requires overcoming numerous technological hurdles. Adequate thrust bearing load capacity and potentially large gearbox applied radial loads are among them. However, by replacing the turbine end, or hot section, rolling element bearing with a gas foil bearing many of the above benefits can be realized. To this end, engine manufacturers are beginning to explore the possibilities of hot section gas foil bearings in propulsion engines. This paper presents a logical follow-on activity by analyzing a conceptual rotorcraft engine to determine the feasibility of a foil bearing supported core. Using a combination of rotordynamic analyses and a load capacity model, it is shown to be reasonable to consider a gas foil bearing core section.
A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.
This summer internship is focused on using CFD and fluid mechanics to optimize the SRL-ADEPT geometry in an attempt to increase drag and area-effectiveness, and reduce flow separation.
An analysis is presented which integrates the results of specific studies in the areas of photovoltaic structural design optimization, optimization of array series/parallel circuit design, thermal design optimization, and optimization of environmental protection features. The analysis is based on minimizing the total photovoltaic system life-cycle energy cost including repair and replacement of failed cells and modules. This approach is shown to be a useful technique for array optimization, particularly when time-dependent parameters such as array degradation and maintenance are involved.
Failure analysis of adjoint systems method for determining optimal trajectories
The rise of electron microscopy has expanded our ability to acquire nanometer and atomically resolved images of complex materials. The resulting vast datasets are typically analyzed by human operators, an intrinsically challenging process due to the multiple possible analysis steps and the corresponding need to build and optimize complex analysis workflows. We present a methodology based on the concept of a Reward Function coupled with Bayesian Optimization, to optimize image analysis workflows dynamically. The Reward Function is engineered to closely align with the experimental objectives and broader context and is quantifiable upon completion of the analysis. Here, cross-section, high-angle annular dark field (HAADF) images of ion-irradiated (Y, Dy)Ba 2 Cu 3 O 7–δ thin-films were used as a model system. The reward functions were formed based on the expected materials density and atomic spacings and used to drive multi-objective optimization of the classical Laplacian-of-Gaussian (LoG) method. These results can be benchmarked against the DCNN segmentation. This optimized LoG* compares favorably against DCNN in the presence of the additional noise. We further extend the reward function approach towards the identification of partially-disordered regions, creating a physics-driven reward function and action space of high-dimensional clustering. We pose that with correct definition, the reward function approach allows real-time optimization of complex analysis workflows at much higher speeds and lower computational costs than classical DCNN-based inference, ensuring the attainment of results that are both precise and aligned with the human-defined objectives.
Midcourse guidance analysis and optimization with discrete measurements for mission logic development
An approach for reducing the number of variables and constraints, which is combined with System Analysis Equations (SAE), for multiobjective optimization-based design is presented. In order to develop a simplified analysis model, the SAE is computed outside an optimization loop and then approximated for use by an operator. Two examples are presented to demonstrate the approach.
To reduce oscillatory hub loads in forward flight, a structural optimization analysis of a hingeless helicopter rotor has been developed and applied. The aeroelastic analysis of the rotor is based on a finite element method in space and time, and linked with automated optimization algorithms. For the optimization analysis two types of structural representation are used: a generic stiffness-distribution and a single-cell thin-walled beam. For the first type, the design variables are nonstructural mass and its placement, chordwise center of gravity offset from the elastic axis, and stiffness. For the second type, width, height and thickness of spar are used as design variables. For the behavior constraints, frequency placement, autorotational inertia and aeroelastic stability of the blade are included. The required sensitivity derivatives are obtained using a direct analytical approach. An optimum oscillatory hub load shows a 25-77 percent reduction for the generic blade, and 30-50 percent reduction for the box-beam.
The main purpose of this paper is to introduce a risk management approach that allows planners to quantify the risk and efficiency tradeoff in the presence of uncertainties, and to make forward-looking choices in the development and execution of the plan. Demonstrate a planning and risk analysis framework that tightly integrates mathematical optimization, empirical simulation, and theoretical analysis techniques to solve complex problems.
Cost analysis for optimized cost orbital space transportation system