Optimizing Pumping Systems to Minimize First or Life-cycle Cost
AFT Fathom™ Technical Paper
Authors: Judy Hodgson, DuPont Company; Trey Walters, P.E., Applied Flow Technology
Presented at the 19th International Pump Users Symposium, February 2002
ABSTRACT
Numerical optimization methods offer a powerful new technology for pump users when combined with pumping system analysis software. Whether the design goal is to reduce first costs or life-cycle costs, this technology promises to significantly reduce pumping system costs and energy usage.
Optimization methods work by automatically selecting pipe and pump sizes to minimize cost. Design engineers define the constraints for the system, such as flowrate, NPSH margin, or fluid velocity. The optimization software then finds the combination of pipe and pump sizes to minimize the cost while satisfying the constraints.
A new design concept is introduced called the optimal pumping system operating point (OPSOP). In simple terms, the OPSOP uses cost data to identify the optimum tradeoff in pipe, pump, and (optionally) energy costs for a system that may have one or more duty points. Using this information, a new and improved method of pump sizing is described.
To establish benchmark comparisons for typical petrochemical pumping systems, these optimization methods were applied to four previously designed systems. With a modest amount of effort, first cost reductions were as much as 17 percent, and life-cycle cost reductions were as much as 72 percent (based on 10 years), with savings of over $100,000 in several cases.
*The IntelliFlow® technology featured in this paper has since migrated from AFT Mercury and AFT Titan to become the Automated Network Sizing (ANS) Module for AFT Fathom™ and AFT Arrow™. This module utilizes similar methods to provide the cost minimization as presented in this paper.
The potential cost and energy savings from pumping systems is great. Recent studies have found that pumping systems account for about 20 percent of world energy usage (Frenning, et al., 2001). Efforts that minimize wasted energy in these systems would not only have substantial economic savings, but an equally important environmental impact, as well. Although savings can be made by optimizing existing systems, the greatest opportunities are in systems yet to be built. The reason is that in new designs the piping can be included as one of the variables that the engineer can modify to optimize the system. In large existing systems, it would be cost-prohibitive to make a piping change.
Unfortunately, pumping system design engineers work in an environment where budget and schedule constraints limit their ability to optimize their designs using traditional methods. The number of variables in complex pumping systems makes such optimization impractical, even with modern hydraulic analysis software. Most of the design engineer’s effort is focused on ensuring the system will merely function properly. With the abundant opportunity for cost and energy reduction in new pumping systems, the need exists for technologies that will allow engineers to optimize pumping system designs to minimize cost and energy usage. The commercial software, AFT Mercury* (now the Automated Network Sizing Module), addresses this need.
Conclusion
Installing a properly sized pump for this application would have
saved the project $73,692, or 70 percent in LCC with a five-year
life cycle. For a 10-year life cycle, the savings would have been
$123,401, or 72 percent. Although the original pump was
undersized, the optimum pump actually had a smaller casing than
the original and therefore was less expensive than the original. This
resulted in a small savings in first cost. The savings was $653 or
seven percent.
- Numerical optimization technology is a proven technology that
has been successfully applied in other design arenas that, until now, have not been utilized in pumping system design. - Based on real-world systems as the benchmark, using
optimization software in place of traditional design techniques
results in significant cost savings for both first cost and LCC. - Besides being easy to use, the software proved to be versatile
enough to manage different design issues commonly found in the petrochemical industry. - This software has the potential to be a powerful tool in the effort
to move from first-cost-focused design to LCC-focused because no additional work is required to compare the two different designs and their respective monetary tradeoffs.
Below is an excerpt from the paper. Use the link above to view the full paper.
INTRODUCTION
The potential cost and energy savings from pumping systems is great. Recent studies have found that pumping systems account for about 20 percent of world energy usage (Frenning, et al., 2001). Efforts that minimize wasted energy in these systems would not only have substantial economic savings, but an equally important environmental impact, as well.
Although savings can be made by optimizing existing systems, the greatest opportunities are in systems yet to be built. The reason is that in new designs the piping can be included as one of the variables that the engineer can modify to optimize the system. In large existing systems, it would be cost-prohibitive to make a piping change.
Unfortunately, pumping system design engineers work in an environment where budget and schedule constraints limit their ability to optimize their designs using traditional methods. The number of variables in complex pumping systems makes such optimization impractical, even with modern hydraulic analysis software. Most of the design engineer’s effort is focused on ensuring the system will merely function properly.
With the abundant opportunity for cost and energy reduction in new pumping systems, the need exists for technologies that will allow engineers to optimize pumping system designs to minimize cost and energy usage. The commercial software, AFT Mercury, addresses this need.
ANALYSIS VERSUS DESIGN
Before discussing the potential of modern optimization technology for the pumping industry, it is worth pausing to underscore the difference between engineering analysis and engineering design. Engineering analysis involves the application of engineering formulas and calculation methods to predict the behavior of a given system. The calculation methods might be applied in hand calculations, spreadsheets, or modeling software. Such methods are satisfactory for evaluating the performance of an existing system or design.
However, applying engineering analysis to a new design is problematic in that it cannot answer the real question asked by the designer, “What design will best achieve the project goals?” There are numerous possible design goals, among which are to minimize cost, energy, or risk, or to maximize performance, safety, or reliability.
With engineering analysis, the engineer must propose a design, and then use analysis to evaluate the proposed design. Good designs are typically defined as designs that function properly.
In contrast, true engineering design answers the real question being asked. Rather than evaluating a proposed design, a design based method’s output will be the design itself. The input data will be the design requirement to be satisfied.