Abstract

Heterogeneous non-catalytic gas-solid reactors are commonly used in the production of chemicals, metals and metal oxides, for example, rotary drum reactor for producing quick lime; blast furnace, a moving bed reactor for producing iron, etc. Industrial processes involve multicomponent mixtures of solids as most of the naturally occurring materials such as minerals are multicomponent in nature. Generally the raw materials are heterogeneous and their physical and chemical characteristics vary from one source to another. The solid particles are also usually moist, the moisture content varying from season to season. The physico-chemical phenomena that take place in these reactors include flow of gases through porous media, heat transfer between the gases, solids, equipment and the environment, evaporation and condensation of moisture, reactions between gases and solids and within a single phase, melting and solidification depending on the temperatures inside the reactor, etc. The flow of particles is also of great importance especially in rotary drum and moving bed reactors. General features of the mathematical models for non-catalytic reactors are described along with models for the phenomena mentioned above. Case studies from the iron and steel industry on model-based optimization of production of direct reduced iron in a rotary kiln and induration of wet iron ore pellets on a moving packed bed reactor are discussed here.

Highlights

  • Production of many commodity chemicals, metals, ceramics and polymers involve reactions between gases and solid particles, which may act as catalysts in some cases and in other cases, participate in the reaction with the gases directly

  • Vertical shaft or rotary kilns are used for the production of quick or burnt lime in the soda ash, pulp and paper (Fernandes and Castro, 2000), and iron and steel industries (Watkinson and Brimacombe, 1982; Davis and Englund, 2003; D’Abreu et al, 2008)

  • Rotary kilns are used for producing sponge iron or direct reduced iron (Feinman and Mac Rae, 1999), cement (Peray, 1984; Mastorakos et al, 1999; Majumdar et al, 2007), for waste incineration (Marias, 2003; Yang et al, 2003), and for combustion or pyrolysis of coal (Patisson et al, 2000a, 2000b; Li et al, 2003), maize

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Summary

Introduction

Production of many commodity chemicals, metals, ceramics and polymers involve reactions between gases and solid particles, which may act as catalysts in some cases and in other cases, participate in the reaction with the gases directly. Vertical shaft or rotary kilns are used for the production of quick or burnt lime in the soda ash, pulp and paper (Fernandes and Castro, 2000), and iron and steel industries (Watkinson and Brimacombe, 1982; Davis and Englund, 2003; D’Abreu et al, 2008). Moving packed bed reactors are employed for sintering of iron or zinc ores (Chatterjee et al., 1993; Nakano et al, 2010; Ahn et al, 2013), for induration of iron ore pellets on a moving or traveling grate or strand (Thurlby et al, 1979; Barati, 2008; Sadrnezhaad et al., 2008), and for gasification of coal (Yoon et al, 1979; Hobbs et al, 1992). The reactors used for sintering of wet iron or zinc ore granules and for induration of wet iron ore pellets are rectangular in shape and have volumes in excess of. The main objectives of process optimization are enhancement of reactor productivity, efficient utilization of raw materials and fuels, product quality improvement, reduction of energy consumption, environmental compliance, maintaining the equipment in good health and ensuring its availability

Challenges faced in process optimization
Need for soft-sensors and data analytics
Mathematical modeling of gas-solid reactors
Charging and flow of solids
Fluid flow and heat transfer
Evaporation and condensation of moisture
Reaction kinetics
Melting and solidification
Numerical solution and tuning of models
Framework for optimization
Direct reduction of iron ore by coal in a rotary kiln
Brief process description
Iron ore direct reduction model
Induration of wet iron ore pellets on a traveling grate
Induration model
Findings
Concluding remarks and suggestions for future research

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