Steel is the worlds most used metal and 2016 the produced amount of steel was measured to a total1630 MT where the Blast Furnace (BF) - Basic Oxygen Steelmaking (BOS) process, which is the mostcommon steel process, stands for 75% of the world’s current crude steel production.The BOS process works by blowing oxygen at high velocity through a hot metal bath consisting of hotmetal from the blast furnace mixed with fluxing agents as slag formers and up to 30 weights% scrap.Due to the high focus on environmental aspects throughout the world, the importance of utilizing andrecycling scrap and by-products such as slag and dust has increased. But when byproducts are recycled,the risk of impurities in the refined hot metal increases. To be able to control the impurities and reducethe risk of getting off-specification end product, it is important to understand when and where theimpurities end up.Zinc and chromium are two of these impurities that may cause issues to the process. To prevent thisfrom happening BlueScope Steel, a steel plant based in Wollongong, Australia, with a productioncapacity of 3 million tons of crude steel, wants to find out where these elements come from and howthey partition. For zinc, it is observed that most of it will end up in the offgas, while for chromium it isnoted that the majority exits with the steel and slag. It is assumed for both elements that the missingamount enters with the shredded steel scrap (shred) to meet the required mass balance using industrialdata. Results showed that the shred needs to contain between 0.312% and 0.515% zinc in order tosatisfy the zinc balance for year 2014 to 2019. For chromium, the range is from 0.315% to 0.371%.Data analyses carried out using SIMCA UMETRICS, which is a multivariate program used to performPrincipal Component Analysis (PCA) and Partial Least Squares (PLS) regression, and normal regressionsdone in Excel showed that zinc in the crude steel cannot be used to calculate or predict the partitioningfactors for zinc between slag, melt and off gases, due to a R2 (Goodness of fit) of 0.144, where the highera R2 value is the better the fit to the model. Slag showed better results with an R2 of 0.473 This regressionwas only done for heats with Zn contents above the detection limit, so it will most likely only beapplicable to heats where relatively high amounts of zinc are expected to end up in the slag. The amountof zinc that ends up in the offgas was above 95% for all the heats modelled.For chromium, results for predicting the partitioning between slag and melt showed greater promise,an R2 of 0.663 was obtained for regression of chromium in crude steel, and an R2 of 0.566 was obtainedfor regression of chromia in the slag. Both values are considered acceptable when analyzing plant data.When comparing the two, using the regression from chromium in the crude steel gives a slightly moreaccurate result, with a partitioning difference of only +/- 0.03 and a 97-99% accuracy, compared to +/-0.05 for chromia in the slag with a 95-98% accuracy.The model is used to compare how different amounts of shred will impact the partitioning of the twoelements analyzed. It also looks at how newer generations of filter cake, containing higher amounts ofzinc will impact the partitioning of zinc between the phases, especially the concentration of zinc thatreports to the dust.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-95383 |
| Date | January 2019 |
| Creators | Persson, Andreas |
| Publisher | Luleå tekniska universitet, Industriell miljö- och processteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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