Chemical and Biological Engineering ETDs

Publication Date

Summer 7-30-2024

Abstract

There is a need for a low-cost robust sensor accurately detecting leaks from oil and gas infrastructure. This work presents the development of an electrochemical sensor based on an yttria stabilized zirconia (YSZ) electrolyte with La0.87Sr0.13CrO3, Indium Tin Oxide (In2O3 90 wt%, SnO2 10 wt%), Au, Pt electrodes. Selectivity to target gasses of the three sensing electrodes in conjunction with machine learning allows for the accurate discrimination between possible methane sources as well as the quantification of methane concentration. Sensor sensitivity is improved through a low-ionic conductivity substrate of magnesia stabilized zirconia. Field testing is performed with the improved prototype sensor, where it is shown that the device is capable of detecting leaks at various rates from a simulated buried pipeline. Finally, multiphysics finite element analysis (FEA) is used to guide the design process for a self-heated stick sensor manufactured via typical manufactured high temperature cofired ceramic manufacturing methods.

Keywords

mixed potential sensor, natural gas leak detection, multiphysics FEA, machine learning, electrochemistry

Document Type

Dissertation

Language

English

Degree Name

Chemical Engineering

Level of Degree

Doctoral

Department Name

Chemical and Biological Engineering

First Committee Member (Chair)

Fernando Garzon

Second Committee Member

Lok-kun Tsui

Third Committee Member

Shuya Wei

Fourth Committee Member

Jose M. Cerrato

Fifth Committee Member

Eric Brosha

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