Can I read Bayesian Deconvolution of Vessel Residence Time Distribution on EtoBox?

Bayesian Deconvolution of Vessel Residence Time Distribution by Thomas Huddle; Paul Langston; Edward Lester is a Engineering article available to read on EtoBox.

What is Bayesian Deconvolution of Vessel Residence Time Distribution about?

## Abstract Residence time distribution (RTD) within vessels is a critical aspect for the design and operation of continuous flow technologies, such as hydrothermal synthesis of nanomaterials. RTD affects product characteristics, such as particle size distribution. Tracer techniques allow measurement of RTD, but often cannot be used on an individual vessel in multiple vessel systems due to unsuitable exit flow conditions. However, RTD can be measured indirectly by removal of this vessel from the system and deconvoluting the resulting detected tracer profile from the original trace of the entire system. This paper presents three models for deconvolution of RTD: BAY an application of the Lucy-Richardson iterative algorithm using Bayes’ Theorem, LSQ an adaptation of a least squares error approach and FFT a Fast Fourier Transform. These techniques do not require any assumption about the form of the RTD. The three models are all accurate in theoretical tests with no simulated measurement error. For scenarios with simulated measurement error in the convoluted distribution, the FFT and BAY models are both very accurate. The LSQ model is the least suitable and the output is very noisy; smo

Who reads Bayesian Deconvolution of Vessel Residence Time Distribution?

Author

Thomas Huddle; Paul Langston; Edward Lester

Publisher

Walter de Gruyter GmbH

Published

2017

Language

EN

Field

Engineering (Physical Sciences)