Effect of material properties on the residence time distribution (RTD) characterization of powder blending unit operations. Part II of II: Application of models

• Published in: Powder technology Vol. 344; pp. 525 - 544
• Main Authors: Escotet-Espinoza, M. Sebastian, Moghtadernejad, Sara, Oka, Sarang, Wang, Zilong, Wang, Yifan, Roman-Ospino, Andres, Schäfer, Elisabeth, Cappuyns, Philippe, Van Assche, Ivo, Futran, Mauricio, Muzzio, Fernando, Ierapetritou, Marianthi
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 15.02.2019; Elsevier BV
• Subjects: Axial dispersion; Continuous manufacturing; Convolution; Experimental data; Material properties; Mathematical models; Mixing; Modeling; Multivariate analysis; Parameters; Powder; Powder blending; powders; process design; Regression analysis; Residence time distribution; tanks; Tanks-in-series; Variance analysis; Continuous manufacturing; Mixing; Tanks-in-series; Modeling; Axial dispersion; Powder blending
• ISSN: 0032-5910; 1873-328X
• DOI: 10.1016/j.powtec.2018.12.051

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. [Display omitted] •Two residence time distribution (RTD) models used for powder blending are reviewed.•Parametric regression methods are discussed for RTD model parameter estimation.•The three parameters for each of the RTD models were regressed for each pulse curve.•Statistical analysis on parameters was performed relating material properties to RTD.•RTD models and parameters were used to establish disturbance dissipation regimes.