AE Brown Bag Seminar

 

Aidan Bedwell

Ryan MacGinnitie

Harrison Ryan

Hiroshi Wang

 

Friday, October 10

11:00 a.m. - 12:20 p.m.

Guggenheim 442

 

Pizza Served

 

Aidan Bedwell

Title: 

Coanda Effect Micro Air Vehicle Thrust Optimization

Abstract:

The objective of this project was to optimize the shape of a Coanda Effect Micro Air Vehicle (CEMAV) to produce the maximum amount of thrust for the lowest required rotor torque. The aircraft used as the baseline for CEMAV is EMBLA, an aircraft developed by AESIR between 2008 and 2013, and this project was conducted in support of Lee Whitcher’s PhD thesis. Coanda Effect vehicles of this type are not common, and there exists little literature on the optimization of these designs.

This project involved creating and simulating simplified CFD models to determine a more optimal geometry for the vehicle. The geometry of the CFD models were varied with simulations being run for more than 100 geometric variations before the highest-performing design was selected for testing. A physical model of the optimized CEMAV geometry was created and tested alongside identical testing of the original EMBLA. The results of these tests represented a notable improvement to the overall thrust and efficiency of the CEMAV.

Faculty advisor:

Research Engineer Lee Whitcher

 

Ryan MacGinnitie

Title:

Large-Eddy Simulations of Non-Reacting Flow in a Rich Quench Lean Burner

Abstract:

This study presents a numerical investigation of the non-reacting flow field in a Rich-Quench-Lean (RQL) burner using Large-Eddy Simulation (LES). The objective is to evaluate the accuracy and predictive capability of LES in reproducing important flow structures found in experimental data obtained from a Cambridge RQL combustor configuration. A second order accurate LES solver (LESLIE) was used, with simulations conducted on a grid of 6.3 million points and parallelized across 720 processors. The numerical results were compared against experimental observations from El Helou et al., focusing on the qualitative features of the instantaneous flow field, time-averaged velocity profiles, and turbulence intensity distributions. Overall, the LES approach captured the essential features of the swirling flow and quenching dynamics, providing a validated baseline for future soot formation studies in reacting configurations. Advisor Name: Dr. Suresh Menon

 

Harrison Ryan

Title:

Implementation of Stochastic Spatial Turbulence Fields for Real-time Reduced Order Urban Modeling

Abstract:

The Mann Model for turbulence has been selected to generate turbulence fields for an Advanced Air Mobility (AAM) vehicle’s flight path and is implemented within Python. The Mann Model is based on a model of the spectral tensor for atmospheric surface-layer turbulence, allowing for turbulence generation over a wide range of velocity perturbations, while requiring few inputs and efficiently generating turbulence boxes. While spatially-variant, a time-varying sigmoidal interpolation was added between two different turbulence boxes. This stochastic turbulence model was implemented within a larger Representative Environment Model (REM) that efficiently models and evaluates the atmospheric boundary layer, building wakes and wildfire updrafts for an AAM vehicle flight path fully in Python, accurately capturing turbulence disturbances of interest on an AAM vehicle scale. 

Faculty Advisor:

Professor Marilyn Smith

 

Hiroshi Wang

Title:

Experimental Analysis of Electrodynamic Dust Shields for Lunar Dust Mitigation

Abstract:

Lunar regolith presents significant challenges for exploration, as it can degrade hardware and pose health risks to astronauts. Electrodynamic Dust Shields (EDS) are an active dust mitigation approach that employ high-voltage AC signals to mobilize and repel particles. This research analyzes EDS performance under varying parameters such as frequency and voltage, along with different configurations including 2- and 3-phase systems, electrode geometry, and substrate material. Experiments are conducted in vacuum chambers using high-voltage transformers and UV lamps to mobilize dust, while optical microscopy and cameras are used to evaluate its removal on EDS surfaces. Key performance metrics include cleaning efficiency and particle size distribution. This presentation will highlight the experimental methodology, covering EDS design, testing procedures, and observed trends in dust removal performance.

Faculty advisor: 

Professor Álvaro Romero-Calvo