<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chilka, A. G.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Ranade, V. V.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Drying of almonds II: multiple particles</style></title><secondary-title><style face="normal" font="default" size="100%">Indian Chemical Engineer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Almonds</style></keyword><keyword><style  face="normal" font="default" size="100%">CFD</style></keyword><keyword><style  face="normal" font="default" size="100%">Drying</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">1-18</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Computational modelling is an efficient and effective tool for modelling the drying process for food products. Developing validated computational models for drying processes is essential to build energy-efficient drying units, producing uniform quality of dried products. This work presents drying behaviour of almonds with a specific focus on understanding interaction among multiple almonds. Eight (2 × 2 × 2) particles and twenty seven (3 × 3 × 3) particles arranged in the shape of a cuboid were used to conduct drying experiments in a Mettler Toledo Moisture Analyzer unit. Experiments were conducted to measure the moisture loss data with respect to drying time using almond kernels. Experimental data were used to understand drying kinetics as well as variation in moisture content with respect to their positions in a cuboid. Computational fluid dynamics based simulations were carried out for the flow, heat transfer and drying of particles in the unit. Actual geometry of individual particles was considered in simulations to predict the variation in velocity, heat and mass transfer coefficients for all the particles. Simulations predicted moisture loss data that matches well with the experimentally measured values. Average moisture for each layer was also compared for various intermediate drying times. Simulation results captured the overall drying process for multiple particles system adequately. The results are compared with the results obtained with drying of a single almond. The approach, models and presented results will be useful for designing large-scale drying units for almonds. © 2017 Indian Institute of Chemical Engineers&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Indian&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">0.145</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nimbalkar, Pranhita R.</style></author><author><style face="normal" font="default" size="100%">Khedkar, Manisha A.</style></author><author><style face="normal" font="default" size="100%">Gaikwad, S. G.</style></author><author><style face="normal" font="default" size="100%">Chavan, Pramod V.</style></author><author><style face="normal" font="default" size="100%">Bankar, Sandip B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">New insight into sugarcane industry waste utilization (press mud) for cleaner biobutanol production by using c. acetobutylicum nrrl b-527</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Biochemistry and Biotechnology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acetone</style></keyword><keyword><style  face="normal" font="default" size="100%">Acetone butanol ethanols</style></keyword><keyword><style  face="normal" font="default" size="100%">Acidic pre treatments</style></keyword><keyword><style  face="normal" font="default" size="100%">Agriculture</style></keyword><keyword><style  face="normal" font="default" size="100%">Biobutanol</style></keyword><keyword><style  face="normal" font="default" size="100%">cellulose</style></keyword><keyword><style  face="normal" font="default" size="100%">Clostridium acetobutylicum</style></keyword><keyword><style  face="normal" font="default" size="100%">Detoxification</style></keyword><keyword><style  face="normal" font="default" size="100%">Drying</style></keyword><keyword><style  face="normal" font="default" size="100%">Drying Fermentation</style></keyword><keyword><style  face="normal" font="default" size="100%">FermentationSpoilage</style></keyword><keyword><style  face="normal" font="default" size="100%">Fermentative production</style></keyword><keyword><style  face="normal" font="default" size="100%">Pre-treatment</style></keyword><keyword><style  face="normal" font="default" size="100%">Press mud</style></keyword><keyword><style  face="normal" font="default" size="100%">Press mud Pretreatment</style></keyword><keyword><style  face="normal" font="default" size="100%">Response surface methodology</style></keyword><keyword><style  face="normal" font="default" size="100%">Sugar industry</style></keyword><keyword><style  face="normal" font="default" size="100%">Sulfur determination</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAY</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In the present study, press mud, a sugar industry waste, was explored for biobutanol production to strengthen agricultural economy. The fermentative production of biobutanol was investigated via series of steps, viz. characterization, drying, acid hydrolysis, detoxification, and fermentation. Press mud contains an adequate amount of cellulose (22.3%) and hemicellulose (21.67%) on dry basis, and hence, it can be utilized for further acetone-butanol-ethanol (ABE) production. Drying experiments were conducted in the temperature range of 60–120 °C to circumvent microbial spoilage and enhance storability of press mud. Furthermore, acidic pretreatment variables, viz. sulfuric acid concentration, solid to liquid ratio, and time, were optimized using response surface methodology. The corresponding values were found to be 1.5% (v/v), 1:5 g/mL, and 15 min, respectively. In addition, detoxification studies were also conducted using activated charcoal, which removed almost 93–97% phenolics and around 98% furans, which are toxic to microorganisms during fermentation. Finally, the batch fermentation of detoxified press mud slurry (the sample dried at 100 °C and pretreated) using Clostridium acetobutylicum NRRL B-527 resulted in a higher butanol production of 4.43 g/L with a total ABE of 6.69 g/L. © 2017 Springer Science+Business Media New York Author keywords&lt;/p&gt;</style></abstract><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.429 </style></custom4><section><style face="normal" font="default" size="100%">1-18</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chilka, Amarvir G.</style></author><author><style face="normal" font="default" size="100%">Ranade, Vivek V.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CFD modelling of almond drying in a tray dryer</style></title><secondary-title><style face="normal" font="default" size="100%">Canadian Journal of Chemical Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Almonds</style></keyword><keyword><style  face="normal" font="default" size="100%">CFD</style></keyword><keyword><style  face="normal" font="default" size="100%">Drying</style></keyword><keyword><style  face="normal" font="default" size="100%">scale-up</style></keyword><keyword><style  face="normal" font="default" size="100%">tray dryer</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">97</style></volume><pages><style face="normal" font="default" size="100%">560-572</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Drying is important in many food processing applications, and particularly so in the dry fruits industry. This work is focused on developing computational models for simulating the drying of almonds in a tray dryer. It is important to quantitatively understand heat and mass transfer within and around a single almond particle as well as the particle-particle interactions and their implications for dryer design. In this work, we have developed a systematic CFD modelling framework for modelling almond drying in a tray dryer. A single tray filled with almonds (similar to 2 kg) were dried at three set temperatures viz., 55, 65, and 75 degrees C. Air relative humidity at the inlet and outlet locations, and the weight of almonds were measured during drying for each experiment. An additional set of experiments were conducted in which almonds were filled only in the half section of the tray, keeping the other half empty. The same amount of almonds were used, to have multiple layers of almonds in the tray, and the set temperature for the experiment was 75 degrees C. Flow, heat, and mass transfer in the tray dryer were simulated using commercial CFD software Ansys Fluent. The validated computational model was used to simulate various cases including larger and more trays. The developed approach and models will be useful to select the appropriate dryer configuration and optimize its design. The developed models will also be useful to identify suitable operation conditions for the drying of almonds as well as other food products.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.265</style></custom4></record></records></xml>