# A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
## 3 Materials and Methods
\begin{table}
\begin{tabular}{c c c c} \hline
**Phase** & **Treatment** & **Strengths** & **Limitations** \\ \hline \multicolumn{4}{c}{Low investment costs.} \\ Phase 3 & & Low employment of highly specialized workers. & High usage of area of land. \\ Dewatering (Dw\({}_{i}\)) & (Dw\({}_{1}\)) & Low energy and chemical reagents consumption. & The sludge must be previously stabilized. \\  & & Low sensitivity to sludge characteristics. & Climatic factors must be considered for \\  & & Low energy consumption. & the sizing of the system. \\ \hline \multicolumn{4}{c}{Low sensitivity to sludge characteristics.} \\ \hline \multicolumn{4}{c}{Low energy consumption.} \\ Belt press dewatering & Low investment and management costs. & High sensitivity to sludge characteristics. \\  & (Dw\({}_{2}\)) & Simplicity of construction & Automatic management is not \\  & & and maintenance. & recommended. \\  & & Good dry content of the treated sludge. & Dimensional reduction of the \\  & & & influent sludge. \\ \hline \multicolumn{4}{c}{Discontinuous functioning.} \\ Filter press dewatering (Dw\({}_{3}\)) & High dry content of the treated sludge. & High investment and management costs. \\  & Moderate solid concentration in & Special support structures are required. \\  & & the filtered. & High usage of space. \\  & & Highly specialized workers are required. \\ \hline \multicolumn{4}{c}{Specific maintenance required.} \\ \multicolumn{4}{c}{Good containment of bad odor emissions.} \\ Centrifugation & Quick start and stop. & Sand removal and sludge size \\  & (Dw\({}_{4}\)) & Quick start and stop. & reduction required. \\  & & High dry content of the & Need for highly qualified workers. \\  & & dewatered sludge. & High investment costs for \\  & & medium-small plants. \\ \hline \end{tabular}
\end{table} 
Table 4: Strengths and limitations of all considered alternatives to carry out the dewatering treatments of the modeled SSTS. \begin{table}
\begin{tabular}{c c c} \hline
**Phase** & **Treatment** & **Strengths** & **Limitations** \\ \hline \multicolumn{4}{c}{Good correction and fertilization capacity of} \\ Phase 4 & the compost. & Need to use a filler. \\ Composting & Good level of stabilization. & In some cases, high management costs. \\ (Co) & Compos can be stored better than sludge. & Production of bad odors. \\  & Material recovery. & \\ \hline Phase 5 & Very high dry content of the sludge. & \\ Thermal drying & Very high reduction of volume and weight of & Need to dewater sludge before treating it. \\ (Td) & sludge. & \\ \hline \end{tabular}
\end{table} 
Table 5: Strengths and limitations of all considered alternatives to carry out the composting and thermal drying treatments of the modeled SSTS. The PC is an input that mainly evaluates the economic feasibility of treatment for a specific plant. For small-medium plants, the choice of treatments with high management and investment costs is not economically sustainable; thus, a more convenient solution is provided. The St parameter allows us to consider the chemical-physical characteristics of the SS. The type of secondary treatment of the WW in the water line determines the features of the sludge produced that will be subjected to treatment. If St = 1, the SS derives from activated sludge secondary treatment and has physic-chemical characteristics that make it suitable for biological treatments. On the contrary, if St = 0, the SS derives from secondary chemical treatment, which uses lime as the primary reagent, and it is not suitable for biological treatments. Consistent with CSp parameters, two kinds of configurations of the treatment plant were evaluated: the first one was on a \"single line\", which means that the primary and the secondary SS were processed together on the same plant. The second one was identified as \"separated line\"; in this case, two different plants were adapted to treat the primary and secondary SS.