Development of In Situ Monitoring and Data-Driven Modeling for Complex Systems: Case Study on Simulant Mixtures of Nuclear Waste

Kocevska, Stefani

Title:

Development of In Situ Monitoring and Data-Driven Modeling for Complex Systems: Case Study on Simulant Mixtures of Nuclear Waste

dc.contributor.advisor	Grover, Martha A.
dc.contributor.advisor	Rousseau, Ronald W.
dc.contributor.author	Kocevska, Stefani
dc.contributor.committeeMember	Brettmann, Blair
dc.contributor.committeeMember	Erickson, Anna S.
dc.contributor.committeeMember	Filler, Michael A.
dc.contributor.department	Chemical and Biomolecular Engineering
dc.date.accessioned	2022-05-18T19:38:33Z
dc.date.available	2022-05-18T19:38:33Z
dc.date.created	2022-05
dc.date.issued	2022-05-03
dc.date.submitted	May 2022
dc.date.updated	2022-05-18T19:38:33Z
dc.description.abstract	Approximately 90 million gallons of nuclear and chemical waste are stored at the Hanford and Savannah River Sites in the United States. One of the main challenges associated with nuclear waste treatment and stabilization is the complexity of the waste, which calls for extensive sampling during processing. In this thesis, the use of Process Analytical Technology (PAT), including in-situ infrared and Raman spectroscopy, is demonstrated for Real-Time In-Line Monitoring (RTIM) of simulated nuclear waste. In-situ monitoring will facilitate the continuous operation of the waste treatment facility and help reduce employee exposure to hazardous working conditions. The work in this thesis bridges the gap between spectroscopy data and concentration outputs. A flexible spectra-to-composition modeling framework is developed to address the varying complexity in the simulated waste mixtures. The initial work incorporates linear multivariate regression models to quantify the concentrations of process-relevant (target) species in the waste system. As the complexity of the waste system increases, advanced signal separation preprocessing techniques are incorporated in the modeling framework. The goal of the additional steps is to identify the contributions of the target species in complex systems, which allows for increased robustness of the spectra-to-composition model. Another aspect of the thesis work is the analysis of non-linear phenomena occurring in Raman spectra, centered around the nitrate peak which exhibits peak shifting during certain conditions. The overall work in this thesis enables robust and efficient concentration quantification of target chemical species in complex mixtures, enabling real-time monitoring of nuclear waste.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/66654
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Raman spectroscopy
dc.subject	Infrared spectroscopy
dc.subject	Process analytical technology
dc.subject	Nuclear waste
dc.subject	Blind source separation
dc.subject	Chemometrics
dc.subject	Partial least squares regression
dc.subject	Ion pairing
dc.subject	Complex systems.
dc.title	Development of In Situ Monitoring and Data-Driven Modeling for Complex Systems: Case Study on Simulant Mixtures of Nuclear Waste
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Rousseau, Ronald W.
local.contributor.advisor	Grover, Martha A.
local.contributor.corporatename	School of Chemical and Biomolecular Engineering
local.contributor.corporatename	College of Engineering
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relation.isAdvisorOfPublication	d6e9a407-2031-4864-8232-15ac32d56de3
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thesis.degree.level	Doctoral