Design for a pipe network is traditionally a linear process. A piping system design is chosen, and then a pump is selected based off the system head. This process ignores the efficiency of the piping system, but quickly determines a pump required based on the design. Using modeling software gives the engineer the power to analyze multiple scenarios and address the efficiency of the process. As the engineer must iterate on the system design and pump choice sequentially, it is easy to miss intermediate solutions that could potentially achieve greater savings and efficiency. Designing with the pump and piping system in mind can lead to significant savings, especially when flow analysis software with automated sizing capabilities is used.
Why System Efficiency Is Important
The demand for a stronger and smarter water system has been a priority for several years as systems continue to age and breakdown. With finite resources available to handle increasing loads, it becomes clear how important efficiency is to account for the impact of aging components and changes to the system. It is not enough to design for the immediate system, as a rapidly changing market leads to rapidly changing design requirements. The question becomes how can a high system efficiency be maintained with varying demand?
There are limits to how much efficiency an engineer can achieve with hand calculations to determine the ideal sizing for a pipe system.
While the head required for a single pipeline may be simple to calculate, it becomes more complex for pipe networks. With a hydraulic solver to accurately model the system, this process becomes simpler. Various system configurations can be calculated quickly, particularly with software capable of containing multiple operating cases within one model.
For simple cases, such as sizing a control valve for the system, hydraulic software can be used to set the flow or pressure demand, then the software can report the necessary pressure drop needed from the component.
However, this process becomes more difficult as the sensitivity of the system to each component must be determined. The engineer must select different combinations to compare as design cases. With this iterative approach, the engineer is limited in the number of cases they can compare.
Image 1. Cooling system (Image courtesy of Applied Flow Technology)Consider the cooling system in Image 1. It includes four pumps, four heat exchangers and 34 pipes, which could be sized separately. If the pipes are the same size, the calculation can be simplified, but the system will require a larger pump and lose efficiency. Splitting the pipes into multiple groups and varying the size for each requires more time dedicated to modeling and comparative scenarios for the system. Savings may increase, but it becomes more difficult to determine which is the most efficient design. Since the system must be sized sequentially, rather than being sized in tandem, it is possible to miss intermediate combinations of system and pump configurations that are likely more efficient.
This process can be simplified by using automated sizing software to run potential cases and iterations. This is accomplished by entering necessary design requirements as inputs with the system sizing as outputs, rather than guessing the system design and then verifying the design requirements.
In a recent case, a consulting company used modeling software to analyze an existing petrochemical production facility with a hot oil network. The company created multiple scenarios to analyze sensitivity to various elements in the model. After several oversized elements were identified, the components were resized using the software. This allowed for nearly 1 megawatt (MW) reduction in power consumption by replacing eight components.
It is possible that additional savings over the life of the system could be found by resizing the pipes. However, the replacement costs might not justify the action. This highlights the importance of performing a comprehensive system design at the beginning, in order to minimize large costs down the road.
One concern with this sizing process may be that it is sizing for a specific case and will not take into account the possibility of system expansion.
However, a sophisticated sizing software will also have the ability to optimize for multiple conditions at once to consider the effects of operating at different points during seasons or with sections of the model temporarily isolated. It is also possible to account for a safety factor directly in the optimization process. This means the system can be designed for uncertainty in the current demand, as well as consider the difference in operation as demand is expanded.
As rising demands introduce new challenges, choosing the right tools will help account for variable demand to choose not only the best pump, but also to effectively size the piping system to further optimize the system.