Industrial mixers for powders and granular materials operate with no effective control of mixture quality and lack scientific design. The last twenty years have seen growth in understanding of mixing and mixers. Howev...Industrial mixers for powders and granular materials operate with no effective control of mixture quality and lack scientific design. The last twenty years have seen growth in understanding of mixing and mixers. However, research falls far short of what is needed for on-line characterisation of mixture quality. Secondly, although theoretical descriptions of a few mixer types have been reported, these fall far short of what is needed for equipment design. Two thrusts could revolutionise this situation. One is a scientific characterisation of mixer structure applicable to industrial scale as well as laboratory scale equipment; this is now within our grasp using digital imaging. The other is the development of ideas to overcome the restricted number of particles that can be used in the Distinct Element Method （DEM） for mixers. The goal should be to take the designer through a sequence of steps to the most appropriate mixer size, configuration and operating conditions for a given process duty.展开更多
The objective of this study is to examine several optimization problems in the batch mixing of segregating particulate solids that can be set up and solved using Markov chain models. To improve the adequacy of such mo...The objective of this study is to examine several optimization problems in the batch mixing of segregating particulate solids that can be set up and solved using Markov chain models. To improve the adequacy of such models and exclude some physical contradictions that arise in the linear form, a non-linear Markov chain model for the mixing of segregating components is proposed. Optimal solutions are obtained by controlling the particle flow outside the mixing operating volume while the components are being loaded, modifying particle circulation inside the mixing zone during the process, and by structuring the load in the mixing zone. Solutions are found that not only reduce the negative influence of segregation, but also exclude it altogether. The gain resulting from optimization grows with the rate of segregation. The optimal solutions presented here can be used to improve the design of mixers.展开更多
文摘Industrial mixers for powders and granular materials operate with no effective control of mixture quality and lack scientific design. The last twenty years have seen growth in understanding of mixing and mixers. However, research falls far short of what is needed for on-line characterisation of mixture quality. Secondly, although theoretical descriptions of a few mixer types have been reported, these fall far short of what is needed for equipment design. Two thrusts could revolutionise this situation. One is a scientific characterisation of mixer structure applicable to industrial scale as well as laboratory scale equipment; this is now within our grasp using digital imaging. The other is the development of ideas to overcome the restricted number of particles that can be used in the Distinct Element Method （DEM） for mixers. The goal should be to take the designer through a sequence of steps to the most appropriate mixer size, configuration and operating conditions for a given process duty.
文摘The objective of this study is to examine several optimization problems in the batch mixing of segregating particulate solids that can be set up and solved using Markov chain models. To improve the adequacy of such models and exclude some physical contradictions that arise in the linear form, a non-linear Markov chain model for the mixing of segregating components is proposed. Optimal solutions are obtained by controlling the particle flow outside the mixing operating volume while the components are being loaded, modifying particle circulation inside the mixing zone during the process, and by structuring the load in the mixing zone. Solutions are found that not only reduce the negative influence of segregation, but also exclude it altogether. The gain resulting from optimization grows with the rate of segregation. The optimal solutions presented here can be used to improve the design of mixers.
