Research Experience

7/96 - 8/2001

Spray Modeling with Adaptive Mesh Refinement

One of the primary difficulties encountered when using computational methods to model complex flows is the need for a prohibitive amount of memory in order to resolve small scale behavior. Adaptive Mesh Refinement (AMR) has proven to be a powerful and effective numerical technique for addressing this problem. By adaptively identifying and focusing on key areas, AMR is able to resolve the desired small scale behavior of flows without the additional memory overhead of refining the mesh over the entire domain. The effectiveness of this technique has been demonstrated in its application to fluids encountering shockwaves, for example.

In collaboration with researchers in the Center for Computational Sciences and Engineering at the Lawrence Berkeley National Labs, the capability of an existing AMR fluid code was expanded to handle flows with properties common to engine combustion problems. This work involved introducing parcels of droplets into an ambient gaseous flow in order to model fuel sprays found within fuel-injected diesel engines.

To read more, my dissertation can be viewed here.

6/93 - 7/94

Programmed data analysis routines and analyzed data from solar magnetograms in research that lead to my senior thesis in physics and a paper (see abstract) in Solar Physics.

Summer '91

Designed, built, and tested a model system of optical fibers to be implemented as a part of the mirror calibration system of the HiRes Fly's Eye.
Co-worker: Zhen Liu

Summer '92

Designed and constructed a "moon scope" - a portable calibrated instrument that would allow a comparison of the atmosphere's ability to transmit light at different sites using a common light source (the moon).