Numerical modelling of superheated steam drying of distillers’ spent grain pellet-a single element approach
Puthukulangara Ramachandran, Rani
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Superheated steam (SS) drying has been proven to be a suitable choice for drying biological materials especially in the cases where the use of air drying has its limitations, such as oxidative reactions and chances of combustion. Distillers spent grain (DSG), a byproduct of ethanol production (from cereal grains), is in the form of a wet paste with 75-80% wet basis (wb) moisture. It is dried to safe storage moisture of about 10% (wb) to overcome the challenges associated with its transportation and storage. The present research focuses on development of a drying model for SS drying of DSG. The wet DSG has two components - coarse grain fraction and distillers’ solubles. To mimic the industrial drying process, compacted pellets of the coarse grain fraction (with and without solubles) were coated with solubles to increase the surface area for drying and then dried in SS. The experimental values of density, thermal conductivity, and specific heat of DSG with various levels (0, 10, 30, and 50% w/w) of solubles concentrations and different moisture contents (25, 35, and 45% wb) were in the range of 898.8–1136.7 kg/m3, 0.17–0.42 W/(mK) and 1.76–3.47 kJ/(kgK), respectively. The effect of the SS temperatures and velocities on the effective moisture diffusivity of DSG pellets with various levels of solubles (0, 10, 30% w/w) was also modelled using the drying characteristics. The initial condensation of SS on a DSG pellet for the selected SS operating conditions was modelled using the energy and mass balance at the surface of the pellet. The three-dimensional modelling of SS drying of a single DSG pellet was performed using a computational fluid dynamics software package (ANSYS CFX). Model parameters were tested for sensitivity by varying mesh configuration and initial conditions of SS and the pellet (coated with solubles and uncoated). The validation results show an agreement with a maximum mean relative percentage error of 9.1 and 7.8%, for the temperature and moisture predictions, respectively. Overall, the developed model could be used as a tool for designing the SS drying process for high moisture solids dried with inert material.