[vc_empty_space][vc_empty_space]
A kinetic model approach for predicting coke reactivity index from coal and coal blend properties
Kurniawan T.a,b, Irawan A.a,b, Alwan H.a,b, Hernanto R.c, Wahyudi W.c, Kodarif A.R.c, Bindar Y.b,d
a Chemical Engineering Department, Sultan Ageng Tirtayasa University, Serang, Indonesia
b RT Aksiatama Foundation, Cilegon, Indonesia
c PT Krakatau Steel, Cilegon, Indonesia
d Institut Teknologi Bandung, Chemical Engineering, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020, © 2020 Taylor & Francis Group, LLC.A novel method has been developed to estimate coke reactivity index (CRI) from coal properties through a kinetic approach. The model was derived from mass balance with a kinetic model of batch reactor CRI test. The parameters of kinetic model were optimized using non-linear least squared method. Three main properties of coals, i.e., Fe2O3 content, volatile matter, and coal rank were selected to predict the CRI. The predicted CRI value was in a good agreement with the CRI data. The standard error was less than 5. Coke strength after reaction (CSR) was predicted using linear regression of the CSR and CRI data. The estimated CSR was in good agreement with the CSR data. The sensitivity analysis of coal properties to CRI was also performed using the developed kinetic model. The model was successfully applied for coal blending to predict CRI of the produced coke with standard error 3.7. This model can explain well the catalytic effect of coal and coal blend properties to coke reactivity during the CRI test.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]catalytic,Catalytic effects,Coal blending,Coal properties,Kinetic approach,Kinetic modeling,Standard errors,Volatile matters[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]catalytic,coal blending,Coal properties,CRI,CSR,kinetic model[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1080/19392699.2019.1710498[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]