462296 Using FBRM for Online Monitoring of Particle Size in Radioactive Tank Waste

Monday, November 14, 2016: 5:09 PM
Peninsula (Hotel Nikko San Francisco)
Tristan J. Kernick1, Martha Grover2, Yoshiaki Kawajiri3 and Ronald W. Rousseau3, (1)School of Chemical and Biomolecular Engineering, Georgia Inst. of Technology, Atlanta, GA, (2)School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, (3)School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA

Focused-beam reflectance measurement (FBRM) is a popular qualitative tool for crystallization control and monitoring. Nevertheless, applying its data quantitatively is non-trivial – an FBRM chord length histogram depends on the size distribution of the scanned particles as well as their shape, surface roughness, and opacity. First-principles modeling of these light reflectance properties has proven to be effective, yet cumbersome to apply due to the quantity of parameters that need to be considered[1].

In this talk, we will examine the application of a previously-developed empirical framework[2]to a six-part mixture designed to simulate the particle sizes and densities seen in radioactive waste. FBRM is advantageous for nuclear waste processing because of its ability to carry out online in-situ measurement for a wide range of particle sizes with a short measurement time. Empirical modeling is useful for this application because particle shapes and surface characteristics are not uniform in tank waste. The model considered here takes in FBRM measurements obtained offline of a wide range of particle sizes, then approximates an online chord length histogram via an optimized linear combination of these signatures.

We will demonstrate the model’s ability to estimate the composition of a mixture containing six differently shaped particles with varied mass fractions. The online monitoring technique developed previously for a single crystal geometry in batch crystallization is extended to mixtures with multiple particle shapes.

[1] Kail, N., Marquardt, W., Briesen, H. 2009. Estimation of particle size distributions from focused beam reflectance measurements based on an optical model. Chemical Engineering Science 64, 984-1000.

[2] Li, H., Kawajiri, Y., Grover, M. A., Rousseau, R. W. 2014. Application of an empirical FBRM model to estimate crystal size distributions in batch crystallization. Crystal Growth & Design 14, 607-616.


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See more of this Session: Characterization and Measurement in Powder Processing
See more of this Group/Topical: Particle Technology Forum