Abstract

A new model for predicting the specific chemical exergy of municipal solid waste (MSW) is presented, the model is based on the content of carbon, hydrogen, oxygen, nitrogen, sulfur, and chlorine on a dry ash-free basis (daf). The proposed model was obtained from estimations of the higher heating value (HHV) and standard entropy of MSW using statistical analysis. The ultimate analysis of 56 different parts of MSW was used for the derivation of the HHV expression. In addition, 30 extra parts were used for validation. One hundred and seventeen relevant organic substances that represented the main constituents in MSW were used for derivation of the standard entropy of solid waste. The substances were divided into different waste fractions, and the standard entropies of each waste fraction and for the complete mixture were calculated. The specific chemical exergy of inorganic matter in the waste was also investigated by considering the inorganic compounds in the ash. However, as a result of the extremely low value calculated, the exergy of inorganic matter was ignored. The results obtained from the HHV model show a good correlation with the measured values and are comparable with other recent and previous models. The correlation of the standard entropy of the complete waste mixture is less accurate than the correlations of each individual waste fraction. However, the correlations give similar results for the specific chemical exergy, indicating that HHV has a greater impact when estimating the specific exergy of solid waste than entropy.

Abstract

The paper presents the possibilities of geostatistical analysis of geotechnical data using cluster analysis. As a result of the analysis, geological data from boreholes were replaced by digital data corresponding to parameters measured during CPTU static sounding. A unified database with a depth resolution of 2 cm was obtained, allowing it to be used to build geostatistical geotechnical models, e.g. using kriging. Techniques providing statistical control of the homogeneity of geotechnical separations, based only on measured data and not on interpolated or correlated data, were used to create the model. The technique used makes it possible to create an integrated geo-engineering model of the subsoil even for small sites with limited data.