Optimal use of condensed parameters of ultimate analysis to predict the calorific value of biomass


Ozyuguran A., Akturk A., Yaman S.

Fuel, vol.214, pp.640-646, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 214
  • Publication Date: 2018
  • Doi Number: 10.1016/j.fuel.2017.10.082
  • Journal Name: Fuel
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.640-646
  • Keywords: Biomass, Calorific value prediction, Elemental analysis, Ultimate analysis, HEATING VALUES, PROXIMATE ANALYSES, FUEL, HHV
  • Istanbul Technical University Affiliated: Yes

Abstract

© 2017 Elsevier LtdHigher heating value (HHV) and lower heating value (LHV) of 39 biomass species that include woody samples, herbaceous materials, agricultural residues, juice pulps, nut shells, etc. were predicted based on elemental analysis results. Simple linear equations were developed in which C, H, N, S, and O contents exist and the prediction performance of these empirical equations was evaluated comparing the experimental and the predicted values of calorific values according to the criteria of mean absolute error (MAE), average absolute error (AAE), and average bias error (ABE). For this purpose, equations that include parameters changing from only C to sum of C, H, N, S, and O were tested to compare the prediction performance of each additional parameter. It was concluded that, the use of only two parameters including carbon and extra one element either nitrogen or oxygen is optimal to predict the calorific value. These condensed forms of ultimate analysis-based equations gave r2 values changing in the range of 0.9219–0.9572. Improving effects of additional parameters are rather limited and the addition of H and S contents did not lead so significant improvement in prediction performance.