Date of Graduation
2014
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Mechanical and Aerospace Engineering
Committee Chair
David S Mebane
Committee Co-Chair
Ever Barbero
Committee Member
Xingbo Liu
Abstract
In this work, data from isotope exchange - secondary ion mass spectrometry (IE-SIMS) and electrical conductivity relaxation (ECR) experiments are analyzed using a purely Bayesian approach. The new technique allows quantification of the uncertainty associated with fitting two parameters (the surface exchange coefficient, k, and the bulk diffusion coefficient, D) to a single reaction-diffusion model. The behavior and reliability of the technique is analyzed by considering an idealized data set, where the parameters of interest are pre-defined. The associated MCMC routine finds the parameter location in less than 5,000 samples, despite the starting point being 8 orders of magnitude away. Real experimental data from two experiments conducted on the same material at the same temperature and very similar partial pressures are analyzed and compared and yield vastly differing results from those obtained in the original studies.
Recommended Citation
Blair, Joshua, "A Bayesian Approach to Electrical Conductivity Relaxation and Isotope ExchangeSecondary Ion Mass Spectrometry" (2014). Graduate Theses, Dissertations, and Problem Reports. 5220.
https://researchrepository.wvu.edu/etd/5220