Adam Bruce

Using high-fidelity Monte Carlo simulations, we analyze the statistical characteristics of three common spacecraft attitude determination algorithms using two input vectors convolved with zero-mean, uncorrelated Gaussian measurement noise. Our results suggest the attitude error distributions associated with a spherical-noise sampling model are robustly non-Gaussian but highly structured. By inspecting attitude error histograms corresponding to a variety of input variance noise distributions, we isolate two driving factors, the relative measurement noise variance and relative true measurement geometry, which appear to correlate with observable morphological variability between error histograms. For practical measurement conditions we find calculated error histograms can be parameterized by generalized Gamma distributions, and for at least one significant class of measurement conditions these distributions are entirely described by a single scale parameter which is a linear function of the input variance. We furthermore find that both geometric estimates of the attitude via TRIAD and quaternion solutions to Wahba's problem are largely similar both in accuracy and distributional morphology, converging at the distributional level for relative input noise variance ratios as low as 25:1.

Nitin Dhamankar

Increasingly stringent airport noise regulations and health concerns for people living or working in the vicinity of aircraft have made prediction and attenuation of jet noise an active research topic. Manipulating turbulent flow structures within a jet by suitably modifying the engine nozzle geometry has shown promise to reduce noise levels. However, trial-and-error based experimental tests of novel nozzle designs are expensive and are currently unable to provide comprehensive flow-field measurements which are crucial to gain a better understanding of the noise generation processes. Computer simulations using the large eddy simulation (LES) approach have the potential to be an accurate and efficient research tool for jet noise. A petascalable noise prediction tool-set based on high-order LES and computational aeroacoustics (CAA) is designed and implemented in the current work. The work emphasizes improving the fidelity of simulations while maintaining reasonable computational costs. A wall-modeled immersed boundary method has been implemented and validated to this end. The wealth of flow-field information obtainable from this tool-set will help shed light on the noise generation mechanisms in a jet.

Parth Shah

Defending against ballistic missile attacks requires a complex array of systems that work cohesively yet independently to provide defensive capabilities for the US and her allies. Traditional system evaluation and selection of missile defense architecture assets involves exhaustively evaluating all design options to understand the performance any given architecture. This approach becomes computationally intractable as the number of design options increases. This research provides decision-support methods for evaluating and selecting missile defense assets early in the design process by treating architectures as a collection of nodes. A combined portfolio optimization-regression approach is presented using Least Absolute Shrinkage and Selection Operator (LASSO) regression, artificial neural networks (ANNs), and Conditional Value-at-Risk (CVaR). LASSO strives to isolate salient predictors of performance, leveraged in a neural network to produce a nonlinear regression model that captures some of the complex interactions to enable predictive modeling and effective SoS level decision-making. CVaR leverages risk mitigation strategies that further approximate the highly complex operational interactions to enable efficient portfolio selection of systems based on desired performance metrics. This approach offers a pathway to quickly identify new, viable architecture options early in the design process without conducting an exhaustive search of the design space.

What is the Research Symposium Series?

The Research Symposium Series is a department-sponsored forum for graduate students and advanced-level undergraduates to present their research to a general audience.

The Research Symposium Series is designed to: 

• Facilitate the exchange of ideas and knowledge among faculty and graduate students.
• Provide opportunities for students to develop their technical presentation skills.
• Promote the research activities of the department to undergraduates and other interested individuals.

2016 Prizes

• $500, $300, $200 for best three presentations
• $150 for best undergraduate presentation
• $150 for best abstract

Questions about the Research Symposium Series may be directed to:
aaerss@ecn.purdue.edu
https://engineering.purdue.edu/AAE/Academics/StudentOrgs/aaerss
*Winners in the presentation category cannot compete in that category the following year. The same applies for winners in the abstract category.