Conformal Mapping of Temperature Variation in Compost Heap

Abstract

Laboratory in vessel trapezoidal compost system was designed and constructed. Temperature variation in the compost heap was measured for five days at various depths. Mathematical model for the variation of temperature of the composting process was developed using Conformal Mapping Technique. One of the parameters in the model had two distinct roots, one a positive root and the other negative root. Prediction of temperature was done using both the positive and negative root. The prediction using positive root was named Predicted 1 while that using negative root was named Predicted 2. Four Polynomial functions were generated and considered as reasonable choice for fitting the Measured Surface Temperature (Ts) and Bottom Temperature (Tb) as a function of the predicted temperature. Predicted 1 showed a polynomial relationship with Ts and Tb. The R² values of these relationships with Ts and Tb were 0.165 and 0.379 respectively. The R² value of 0.165 is low and signifies poor estimate of temperature variation in compost heap. On the other hand, the R² value of 0.379 is adjudged moderately okay for prediction based on previous researchers. Predicted 2 also showed a polynomial relationship with Ts and Tb. The R² values of these relationships with Ts and Tb were 0.4226 and 0.688 respectively. The R² value of 0.688 is high while 0.4226 is moderate. The R² values suggested that predicted 2 had a better polynomial relationship with the measured data than predicted 1. Therefore, can be used as the best fit for the model. In terms of shape characteristics, the model simulated the typical temperature-time profile of previous works on compost temperature models in literature closely. The model like several other studies due to the short time frame precluded presentation of the overall shape of the profile. The T-test result (p<0.05) suggested that the model generally gave accurate estimates of the measured temperature while the standard deviation and coefficient of variability (C.V.%) Suggested that predicted 2 gave a more accurate estimate than predicted 1. The results showed also that the decomposition of the compost material used was dominated by the presence of mesophilic bacteria. Further work is suggested to investigate model performance over thermophilic composting time periods, provide further model sensitivity information and incorporate natural ventilation aeration expressions into the model.