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A unified semi-empirical model for estimating the higher heating value of coals based on proximate analysis

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Mathematical models for estimating the higher heating value of coals have constantly been developed and verified. Recently, models based on proximate analysis have gained much attention because of the relative ease in acquiring of such data. However, most models reported are focused solely in improving the accuracy of the estimates and oftentimes the realistic physical explanation and assumptions of the model are not looked into. Furthermore, most models found in literature are generated from coals of specific origin and thus limiting its applicability. In this work, a simple linear additive model with moisture, fixed carbon, volatile matter and ash as parameters was generated. In the generation of the model, proximate data sets (n > 8000) of coals form various origins was taken into consideration having higher heating values ranging from 0.09 to 36.26 MJ/kg. A plausible derivation of a model based on energy and material balance is also provided. The proposed improved model outperforms similar models reported in literature and has a comparable accuracy when compared to complex model previously established.

Abbreviations: ar: as received db: dry basis daf: dry-ash-free basis FC: fixed-carbon HHV: higher heating value VM: volatile matter
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Keywords: Coal; Higher Heating Value; Proximate Analysis; Semi-Empirical Model

Document Type: Research Article

Affiliations: Department of Chemical Engineering, University of San Carlos- Talamban Campus, Cebu City, Philippines

Publication date: December 2, 2018

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