It is difficult to optimize the process parameters of directly preparing carbonaceous mesophase (CMs) by solvothermal method using coal tar as raw material. To solve this problem, a Decision Tree model for CMs preparation (DTC) was established based on the relationship between the process parameters and the yields of CMs. Then, the importance of variables in the preparation process for CMs was predicted, the relationship between experimental conditions and yields was revealed, and the preparation process conditions were also optimized by the DTC. The prediction results showed that the importance of the variables was raw material type, solvothermal temperature, solvothermal time, solvent amount, and additive type in order. And the optimized reaction conditions were as follows: coal tar was pretreated by decompress distillation and centrifugation, the solvent amount was 50.0 ml, the solvothermal temperature was 230 °C, and the reaction time was 5 h. These prediction results were consistent with the actual experimental results, and the error between the predicted yields and the actual yields was about − 1.1%. Furthermore, the prediction error of DTC method was within the acceptable range when the data sample sets were reduced to 100 sets. These results proved that the established DTC for chemical process optimization can effectively lessen the experimental workload and has high application value.

A coagulation-flocculation (CF) process using aluminum sulfate as a coagulant was employed to treat highly suspended solids in tunnel wastewater. Response surface methodology (RSM) based on a Box-Behnken design was applied to evaluate the effects of three factors (coagulant dosage, pH and temperature) on total suspended solids (TSS) removal efficiency as well as to identify optimal values of those factors to maximize removal of TSS. Optimal conditions of coagulant dosage and pH for maximum TSS removal changed depending on the temperature (4 ~ 24°C). As temperature increased, the amount of coagulant dosage and pH level decreased for maximum TSS removal efficiency during the CF process. Proper adjustment of optimal pH and coagulant dosage to accommodate temperature fluctuations can improve TSS removal performance of the CF process.