@article{MAKHILLIJSSCEA202114128827,
    title = {Improvement of Radiotracer Residence Time Distribution Analysis in Industrial Applications},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {14},
    number = {1},
    pages = {1-17},
    year = {2021},
    issn = {1997-5422},
    doi = {ijssceapp.2021.1.17},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2021.1.17},
    author = {Elsayed,Mohamed,H. and},
    keywords = {residence time distributions,axial dispersion flow model,Radiotracer,tanks in series flow model},
    abstract = {This study is concerned with the
characterization and assessment of Residence Time
Distribution (RTD) using signal processing algorithms.
Besides, implicit and explicit models of the RTD signals
are proposed. The experimental system of captured
signals includes <sup>99</sup>Mo radiotracer, scintillator detector and
DAS. Various algorithms are implemented for the
analysis of the acquired signal. These algorithms are
baseline restoration, background correction, statistical
error computation, radioactive decay correction, signal denoising
and dead time correction methods. A quantitative
and qualitative measure of the proposed algorithms is
conducted. Analytical treatment of RTD is investigated
that validated through comparison with introduced block
diagram models by MATLAB Simulink environment.
Additionally, the activity of used radiotracer activity is
experimentally measured using Axial Dispersion Flow
Model (ADFM) and Tanks in Series Flow Model
(TSFM). The total amount of calculated tracer output is
found to be of 112018 CPS. The proposed algorithms are
observed to achieve a notable precision in the analysis of
radiotracer applications.}
    }