Advanced methods to calculation of pressure drop during aeration in composting process

Robert Sidełko; Beata Janowska; Kazimierz Szymański; Natalia Mostowik; Anna Głowacka

doi:10.1016/j.scitotenv.2019.04.155

Advanced methods to calculation of pressure drop during aeration in composting process

Sci Total Environ. 2019 Jul 15:674:19-25. doi: 10.1016/j.scitotenv.2019.04.155. Epub 2019 Apr 11.

Authors

Robert Sidełko¹, Beata Janowska², Kazimierz Szymański², Natalia Mostowik², Anna Głowacka³

Affiliations

¹ Koszalin University of Technology, Poland. Electronic address: robert.sidelko@tu.koszalin.pl.
² Koszalin University of Technology, Poland.
³ West Pomeranian University of Technology Szczecin, Poland.

PMID: 31003083
DOI: 10.1016/j.scitotenv.2019.04.155

Abstract

The objective of our research work was to develop a model that could be used to determine resistance of air flow through a bed of organic material processed in composting operation. The raw material used for testing was organic fraction below 80mm separated from municipal waste. The range of process parameters values treated as independent variables was: for hydraulic load 8.49÷50.96m³·m^-2·h^-1, thickening coefficient 0.69÷0.94 and airflow direction from the bottom upwards and vice versa. The research work lasting 19÷25days was performed in three independent series varying in the bed height. Material humidity was maintained at a constant level of approx. 45%. Analysis of simulation results allowed for selection of MLP/5-9-1 neural network. High quality of such obtained neural network was confirmed by statistical evaluation indicators represented by a coefficient of correlation between the forecast and real values (0.906) and the range of standardized rests of the forecast results (4.082÷5.453).

Keywords: Airflow; Composting; Neural network; Pressure drop.