Citation
Mahar Rasool Bux, . and Sahito Abdul Razaque, . and Siddiqui Zuhaib, . and Brohi Khan Muhammad, . Estimating calorific values of lignocellulosic biomass from volatile and fixed solids. pp. 1-6. ISSN 2289-1692
Abstract
The gross calorific value (GCV) is the most important property of any fuel which shows its energy content. The experimental determination of GCV of solid fuels is a cost intensive process as it requires exceptional equipment and high skills. To streamline the task many equations were developed in past for determining GCV from proximate and ultimate analysis of solid fuels. In present study two empirical equations were developed to predict the GCV of lignocellulosic biomass using their volatile solids (VS) and fixed solids (FS) with and without ash contents in specified range of VS (60.84“82.64 ) FS (17.36“39.16 ) and ash (1.59“21.76 ) as percentage dry mass basis. The experimental data was analyzed through multiple regression analysis and least square method. The empirical equations were developed and their mean errors were determined. The developed empirical equations are simpler economical less time consuming and are more accurate compare to the equations based on the proximate analysis.
Download File
Full text available from:
Official URL: http://ijbr.utp.edu.my/uploads/26_104_cpg2q13-07-2...
|
Abstract
The gross calorific value (GCV) is the most important property of any fuel which shows its energy content. The experimental determination of GCV of solid fuels is a cost intensive process as it requires exceptional equipment and high skills. To streamline the task many equations were developed in past for determining GCV from proximate and ultimate analysis of solid fuels. In present study two empirical equations were developed to predict the GCV of lignocellulosic biomass using their volatile solids (VS) and fixed solids (FS) with and without ash contents in specified range of VS (60.84“82.64 ) FS (17.36“39.16 ) and ash (1.59“21.76 ) as percentage dry mass basis. The experimental data was analyzed through multiple regression analysis and least square method. The empirical equations were developed and their mean errors were determined. The developed empirical equations are simpler economical less time consuming and are more accurate compare to the equations based on the proximate analysis.
Additional Metadata
| Item Type: | Article |
|---|---|
| AGROVOC Term: | Biomass |
| AGROVOC Term: | Lignocellulose |
| AGROVOC Term: | Calorific value |
| AGROVOC Term: | Solids |
| AGROVOC Term: | Heating |
| AGROVOC Term: | Proximate analysis |
| AGROVOC Term: | Multiple regression analysis |
| AGROVOC Term: | Statistical analysis |
| AGROVOC Term: | Ash content |
| AGROVOC Term: | Energy content |
| Depositing User: | Ms. Suzila Mohamad Kasim |
| Last Modified: | 24 Apr 2025 06:28 |
| URI: | http://webagris.upm.edu.my/id/eprint/24063 |
Actions (login required)
 |
View Item |
