Experiments were performed in a pilot scale rotary kiln with coal and coke particles to study their mean residence time, residence time distribution, bed depth profile and time spent at the bed surface. The influence of filling ratio on residence time was studied with a uniform bed depth in the kiln. Residence time distribution and bed depth profile measurements were performed in a kiln without end constriction, at different rotational speeds and different solid inputs. The residence time fraction corresponding to the passage of the particles at the bed surface was measured with a photographic study of the movement of a coloured particle. Various equations were tested to represent the experimental results. The equations of Kramers and Croockewit (1952) and Ronco (1965) were adequate to calculate mean residence times, while only the former could represent correctly the bed depth profile. An equation is proposed which turns out to be quite accurate in predicting the fraction of the residence time spent in the upper layer of the bed.

In order to simulate coal pyrolysis in a rotary kiln in the steady-state regime, a mathematical model has been developed which calculates the temperature profiles in the charge, the gas, and the furnace walls, together with the gas composition and the degree of removal of volatile species. The model takes into account the principal physicochemical and thermal phenomena involved, including the complex movements of the charge; the gas flow; heat transfer between the charge, the gas phase, and the furnace walls; drying and pyrolysis of the coal; the cracking of tars; the combustion of volatile species; and the combustion and extinction of the coke. The data necessary for the model were obtained by specific experiments or from the literature. The model has been validated by comparing its predictions to measurements performed on an industrial rotary kiln. The model has been used to study the influence of operating parameters such as the furnace rotation speed, in order to optimize the process. It is shown how a modification to the extinction zone leads to an increase in coke yield of 0.75 pct.

A mathematical model is presented which describes the pyrolysis of a single grain of coal and is designed to be incorporated into an overall model simulating the rotary kiln coal pyrolysis process. The grain model takes into account the principal physical phenomena occurring during the conversion of coal to coke, namely, heat transfer toward and within the grain, drying of the coal, and the evolution of volatile species. Particular care has been taken in the determination of the thermophysical and kinetic parameters necessary for the model. Thus, the drying kinetics for Lorraine coal were measured by thermogravimetry. The kinetics of pyrolysis were determined by both thermogravimetry and gasphase chromatography, in order to separately monitor the evolution of the nine gaseous species considered. The true specific heat and the thermal conductivity of the solid were also mesured as a function of temperature. The numerical model, based on the finite-volume method, calculates the temperature, composition, and mass flow rates for the different gases evolved at each point in the grain at any instant of time. The model was, finally, validated by comparing the calculated and measured values of the overall conversion of the pyrolysis reaction and the temperature at the center of the grain.

Goal, scope and background Integrating environmental issues into the traditional product design process, for powerful eco-efficiency, is now one of the major priorities for steelmakers. Life cycle assessment (LCA) is currently undertaken as the most holistic approach for assessing environmental impact and selecting new technologies to reduce emissions for steel industry. However, in order to identify new ways for environmental friendly production of steel, it is essential to carry out the process Life cycle inventory (LCI) which is the core part of LCA. According to LCA practitioners, the quality and the availability of data are the main important limiting factors when applying this methodology for new steelmaking processes without large industrial application. In this paper, we propose a new approach of LCIA of steelmaking, based on the simulation of traditional processes which guarantees the quality of data, the mass and the energy balances. This approach is validated for an existing integrated plant and will be used to assess the inventory for breakthrough steelmaking technologies. MethodsThe proposed methodological framework combines physicochemical modelling approach with LCA thinking, in order to carry out the LCI of steelmaking process. Using Aspen Plus commercial flow-sheeting software, physicochemical models have been developed for each steelmaking unit: coke plant, sinter plant, blast furnace, basic oxygen furnace and hot-rolling. The association of the five separately developed modules builds the complete flow sheet of the integrated steelmaking plant. Based on chemical reactions, thermodynamics laws and mathematical equations, the model calculates the mass of each pollutant released by the process, the masses and the chemical compositions of products and by-products simultaneously. For a better understanding of this approach, a brief description of the module developed for coke-making plant is given in the current paper. Results Thanks to the developed model, the LCI of an existing European integrated steelmaking plant has been calculated and inserted into GaBi software for environmental impacts assessment. In order to check the maturity of the developed approach, simulations of the model have been carried out for virtual cases describing an integrated steelmaking plant, characterised by the best available technology. Comparisons between inventories calculated with the model for "virtual" cases and for existing European plant showed good consistency of results and allowed us to validate the proposed approach. Discussions The new approach proposed for LCI calculation offers some important benefits that cannot be obtained when the inventory is carried out in the traditional way. First of all, the model allows us to control the mass and energy balances, something that is basically impossible to assure when only data from industry and/or literature are used. Secondly, calculating emissions based on physicochemical and mathematical considerations gives a strong credibility to the inventory. Predictive mode...

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