TY - JOUR
T1 - Effect of material properties on the residence time distribution (RTD) characterization of powder blending unit operations. Part II of II
T2 - Application of models
AU - Escotet-Espinoza, M. Sebastian
AU - Moghtadernejad, Sara
AU - Oka, Sarang
AU - Wang, Zilong
AU - Wang, Yifan
AU - Roman-Ospino, Andres
AU - Schäfer, Elisabeth
AU - Cappuyns, Philippe
AU - Van Assche, Ivo
AU - Futran, Mauricio
AU - Muzzio, Fernando
AU - Ierapetritou, Marianthi
N1 - Funding Information:
The authors would like to acknowledge the funding provided by Janssen Pharmaceutical (P.Is Fernando Muzzio and Marianthi Ierapetritou), the support provided by Rutgers University through the University and Louis Bevier Doctoral Fellowship awarded to M. Sebastian Escotet-Espinoza, and the financial support from FDA ( DHHS - FDA - 1 U01 FD005295-01 ).
Funding Information:
The authors would like to acknowledge the funding provided by Janssen Pharmaceutical (P.Is Fernando Muzzio and Marianthi Ierapetritou), the support provided by Rutgers University through the University and Louis Bevier Doctoral Fellowship awarded to M. Sebastian Escotet-Espinoza, and the financial support from FDA (DHHS - FDA - 1 U01 FD005295-01).
PY - 2019/2/15
Y1 - 2019/2/15
N2 - Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclét number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.
AB - Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclét number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.
KW - Axial dispersion
KW - Continuous manufacturing.
KW - Mixing
KW - Modeling
KW - Powder blending
KW - Tanks-in-series
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U2 - 10.1016/j.powtec.2018.12.051
DO - 10.1016/j.powtec.2018.12.051
M3 - Article
AN - SCOPUS:85058566715
VL - 344
SP - 525
EP - 544
JO - Powder Technology
JF - Powder Technology
SN - 0032-5910
ER -