Sensitivity Analysis of Simulation Models

This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial metamodels, resolution-IV and resolution-V designs for metamodels augmented with two-factor interactions, and designs for second-degree polynomial metamodels including central composite designs. It also reviews factor screening for simulation models with very many factors, focusing on the so-called "sequential bifurcation" method. Furthermore, it reviews Kriging metamodels and their designs. It mentions that sensitivity analysis may also aim at the optimization of the simulated system, allowing multiple random simulation outputs.simulation;sensitivity analysis;gradients;screening;Kriging;optimization;Response SurfaceMethodology;Taguchi

An Experimental and Theoretical Investigation of Novel Aircraft Drag Reduction

Air transportation is an important part of the world’s economic and indispensable transportation system. The major institutions in the world and the aviation authorities are well aware of the demanding expectations of the public for cheaper transportation cost and at the same time the need to reduce the negative impact of aircraft or air-transportation system on the atmosphere which include noise around airports and global warming to attain sustainability, reduction in the emission of green-house gases such Nitrogen oxides (x) and Carbon di-oxide. In order to achieve such a balance in the future, a strategy is required to match competitive excellence dedicated to meeting the demands of society while at the same time being cost effective for the airline companies and operating aviation authorities. Such a vision or concept cannot be realised without making further technological breakthroughs in engineering fields such as Aerodynamics and other discipline including materials and structures. Improving aircraft aerodynamic performance will have a direct impact on helping to implement these goals. Improving aircraft drag capabilities remains one of the big challenges faced by manufacturers of transport aircraft. It is known that for a typical transport aircraft drag, the induced drag amounts to about 40% of the total drag at cruise flight conditions and about 80 –90 percent of the total drag during aircraft take off. The skin friction drag constitute approximately one half of the total Aircraft drag at cruise flight configuration making up most of the remaining percentage of drag at cruise condition. The use of winglets or other wing-tip devices as a drag reduction device play a significant role in improving aircraft performance by acting as passive devices to reduce drag and enhance aircraft performance. In this thesis, four novel spiroid drag reduction devices are presented which were designed and optimised using STAR-CCM+ Optimate + which uses the SHERPA search algorithm as its optimisation tool. The objective of the optimisation process was set to maximise the lift-to-drag ratio. A low fidelity mesh model was used during the optimisation and the results were verified by using high-fidelity physics and mesh model. The developed devices showed an improve CL/CD ratio of up to 11 percent and improved CL by up to 7 percent while reducing CD by up to 4 percent with an 18 - 24 percent reduction in induced drag observed as well. The devices showed consistency in performance at several Mach numbers and angles of attacks. Thus, suggesting that such devices could be used over a wide range of flight regimes on aircraft or UAVs. The study also successfully demonstrated the capability to using this optimisation process in the design and development of such devices. Furthermore, a numerical investigation and wind tunnel verification study was performed on a wing tip turbine to ascertain the aerodynamic performance modification of using such a device at several Mach numbers, angles of attack, propeller rpms and sensitivity of propeller nacelle positions at the wing tip. The obtained results revealed a trend on the nacelle position to achieve the most improved aerodynamic performance. A CL/CD ratio improvement of up to 7 percent, CL modification of approximate 4 percent and CD reduction of up to 4 percent were achieved. In addition to demonstrate an appreciation of some of the wider implication of installing wing tip devices, a flutter analysis on a rectangular clean wing with added variable mass at the wing tip was performed. The result showed that the added masses had no significant implication on the flutter characteristics of the wing

Structured Sub-Nyquist Sampling with Applications in Compressive Toeplitz Covariance Estimation, Super-Resolution and Phase Retrieval

Sub-Nyquist sampling has received a huge amount of interest in the past decade. In classical compressed sensing theory, if the measurement procedure satisfies a particular condition known as Restricted Isometry Property (RIP), we can achieve stable recovery of signals of low-dimensional intrinsic structures with an order-wise optimal sample size. Such low-dimensional structures include sparse and low rank for both vector and matrix cases. The main drawback of conventional compressed sensing theory is that random measurements are required to ensure the RIP property. However, in many applications such as imaging and array signal processing, applying independent random measurements may not be practical as the systems are deterministic. Moreover, random measurements based compressed sensing always exploits convex programs for signal recovery even in the noiseless case, and solving those programs is computationally intensive if the ambient dimension is large, especially in the matrix case. The main contribution of this dissertation is that we propose a deterministic sub-Nyquist sampling framework for compressing the structured signal and come up with computationally efficient algorithms. Besides widely studied sparse and low-rank structures, we particularly focus on the cases that the signals of interest are stationary or the measurements are of Fourier type. The key difference between our work from classical compressed sensing theory is that we explicitly exploit the second-order statistics of the signals, and study the equivalent quadratic measurement model in the correlation domain. The essential observation made in this dissertation is that a difference/sum coarray structure will arise from the quadratic model if the measurements are of Fourier type. With these observations, we are able to achieve a better compression rate for covariance estimation, identify more sources in array signal processing or recover the signals of larger sparsity. In this dissertation, we will first study the problem of Toeplitz covariance estimation. In particular, we will show how to achieve an order-wise optimal compression rate using the idea of sparse arrays in both general and low-rank cases. Then, an analysis framework of super-resolution with positivity constraint is established. We will present fundamental robustness guarantees, efficient algorithms and applications in practices. Next, we will study the problem of phase-retrieval for which we successfully apply the sparse array ideas by fully exploiting the quadratic measurement model. We achieve near-optimal sample complexity for both sparse and general cases with practical Fourier measurements and provide efficient and deterministic recovery algorithms. In the end, we will further elaborate on the essential role of non-negative constraint in underdetermined inverse problems. In particular, we will analyze the nonlinear co-array interpolation problem and develop a universal upper bound of the interpolation error. Bilinear problem with non-negative constraint will be considered next and the exact characterization of the ambiguous solutions will be established for the first time in literature. At last, we will show how to apply the nested array idea to solve real problems such as Kriging. Using spatial correlation information, we are able to have a stable estimate of the field of interest with fewer sensors than classic methodologies. Extensive numerical experiments are implemented to demonstrate our theoretical claims

Surrogate Based Optimization of Helicopter Rotor Blades for Vibration Reduction in Forward Flight

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76201/1/AIAA-2006-1821-974.pd

Efficient Global Optimization of Helicopter Rotor Blades for Vibration Reduction in Forward Flight

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77207/1/AIAA-2006-6997-436.pd

Multiple-Surrogate Approach to Helicopter Rotor Blade Vibration Reduction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77383/1/AIAA-40291-933.pd