The design of biological wastewater treatment systems is typically an iterative process. There are two reasons for this: (1) the definition of the problem to be solved evolves throughout the design, and (2) the database upon which the design is based improves as additional investigations are completed. Nevertheless, a "freeze" point must be reached during any project where the solution to the problem is fixed and then implemented. The steps which lead to this point are evolutionary in nature, with the problem statement continuously being redefined and potential solutions being evaluated and discarded until the best solution is selected. Most designs begin with an initial concept that is rather general in nature. For example, during early discus sions for a design, a decision may be made to treat a particular wastewater in an activated sludge system, even though the size of the system, its specific configuration, and the nature of any special features are unknown. Those questions, and many more, are addressed as the design proceeds, resulting in an ever more refined estimate of the required facilities. The increasing database that develops during the design process also allows refinement of the design. Typically the designer's understanding of the strength and nature of the wastewater, the characteristics of the treatment system, the effluent discharge standards, and the needs and desires of the treatment system owner and operator evolve as the project progresses.
Figure 9.1 illustrates this iterative nature of process design. The first step is to define the project objectives and requirements, allowing identification of the most reasonable potential solutions based on the current state of knowledge. The costs and scope of those potential solutions are then estimated using rough calculations of bioreactor size, oxygen requirements, solids wastage, etc. Next, the potential advantages and disadvantages of the alternative solutions are considered and a decision is made whether to more fully evaluate each one. When the potential advantages of a particular alternative solution are not sufficient to warrant further consideration, it is dropped and more study is devoted to those remaining. Each iteration around the loop results in more refined information, which allows better estimates to be made of the sizes and costs of the alternatives. Consequently, the use of more refined techniques is called for. This same logic can be applied to the refinement of a selected alternative. Additional studies to refine a given alternative are conducted only as long as the benefits derived from them outweigh their costs.
The iterative nature of process design and evaluation makes it clear that several levels of refinement are required. To begin the design process, a preliminary assessment must be made based on limited data. In spite of its preliminary nature, this assessment must be conceptually sound because important decisions will be based on it. In some instances, the preliminary assessment may be sufficiently precise to allow the project to proceed directly to implementation. This will usually occur for smaller projects where the cost of a conservative design is small compared to the cost of refining the estimates of facility requirements. It also occurs frequently for applications where significant experience already exists upon which to base the selection of the preliminary process design parameters. In other instances, little experience may exist with the subject wastewater or proposed treatment system, making the initial preliminary assessment quite uncertain. In that case, treatability studies as outlined in Chapter 8 must be performed, leading to parameters that may be used in models. In some cases, particularly for the activated sludge process, it may be possible to base design decisions on the simple stoichiometric model of Chapter 5 by incorporating a few broadening assumptions, such as grouping together slowly and readily biodegradable substrate. In other cases, such as large nutrient removal projects, even a small amount of uncertainty can result in significant over-expenditures. In those situations, additional testing to quantify the parameters in activated sludge model (ASM) No. 1 or No. 2 may be merited, allowing alternative designs to be considered by simulation, thereby reducing uncertainty. In the next section, we will consider the decisions that must be made in any design situation, regardless of its level. Then, in Section 9.4 we will consider the approaches used in the various levels of design.
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