DEPARTMENT OF MATHEMATICAL SCIENCES

APPLIED AND COMPUTATIONAL MATHEMATICS SEMINAR

**Speaker:** Susan Minkoff, Mathematics, UMBC

**Title: ***
Sniffing for Leakage: Trace Gas Sensors and Carbon Sequestration
*

**Abstract:**
If society elects to reduce anthropogenic emissions of CO2, geologic storage
will be one of the key technologies. In the
standard approach to storage, CO2 is captured from fixed sources such as
coal-fired power plants, compressed and injected at supercritical conditions
into a target formation. To have
a noticeable impact, large quantities of CO2 will need to be stored.
One of the open questions that will define the success of this technology
include leakage of CO2 and
migration into drinking water and other formations.
In the first half of my talk
I will develop a quasi-1D model for migration of buoyant fluid from a reservoir.
I present a series of examples that illustrate the controlling mechanisms for
leakage rate from the reservoir and its attenuation by flux into shallower
layers.

In the second half of my talk I will discuss trace gas sensors which are compact and portable and are being employed more and more in a variety of applications including disease diagnosis via breath analysis, monitoring of atmospheric pollutants and greenhouse gas emissions, and early warning systems for homeland security applications. One such sensor is based on optothermal detection and uses a modulated laser source and a quartz tuning fork amplifier to detect trace gases. Modeling and design optimization can reduce the cost associated with trying to maximize the performance of novel trace gas sensors. We introduce the first mathematical model of a resonant optothermoacoustic sensor. The model is solved via the finite element method and couples heat transfer and thermoelastic deformation to determine the strength of the generated signal. Determining an optimally-designed sensor requires maximizing the signal as a function of the geometry of the quartz tuning fork (length and width of the tines, etc). An optimal tuning fork constrained to resonate at a frequency close to the standard 32.8 kHz tuning fork leads to a signal that is 3 times larger than the one obtained with the current experimental design. Moreover, the optimal tuning fork found when we drop the resonance frequency constraint produces a signal that is 24 times greater than that produced by the current sensor.

The first half of this talk is joint work with Steve Bryant at the University
of Texas at Austin. The second half of the talk is joint work with John Zweck
(UMBC), Noemi Petra (formerly at UMBC, currently at UT Austin), and Anatoliy
Kosterev (formerly at Rice University).

**Time:** Friday, Nov. 19, 2010, 1:30-2:30 p.m.

**Place:** Science and Tech I, Room 242

Department of Mathematical Sciences

George Mason University

4400 University Drive, MS 3F2

Fairfax, VA 22030-4444

http://math.gmu.edu/

Tel. 703-993-1460, Fax. 703-993-1491