Efficient solar drying requires that the drying rate is quantitatively known as a function of the environment and the control. To develop a drying-rate model for wastewater sludge, data were collected at a solar drying installation in Fussen, Germany. In this solar dryer, wet sludge is uniformly spread over a concrete floor under a greenhouse-like transparent cover. The sludge is mixed mechanically several times a day by an autonomous robot (electric mole®), the structure is fan-ventilated horizontally, and the indoor air is mixed by electric fans. Data of evaporation rate, environmental conditions, and control operations were collected over three drying cycles. Evaporation rate via sludge sampling and via vapor balance across the structure compared favorably, justifying the use of hourly vapor-balance data. Four types of prediction models were considered: physical, additive, multiplicative, and neural network. The multiplicative model has been selected for potential implementation. The most important predictors of evaporation rate, for the conditions under consideration, were (1) solar radiation, (2) outdoor temperature, (3) ventilation rate, and (4) dry solids content of the sludge. Air mixing is an order of magnitude less effective (per unit of air discharge) than ventilation.
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