As engineers we like to think we optimize our designs, or at least when we’re provided the time to do so (when was the last time that happened?). The fact of the matter is, most real piping systems have simply too many variables for us to really evaluate to determine the optimum combination of pipe sizes that will yield the lowest cost system meeting the requirements. Take a simple system with 10 pipes that can range from 1” to 12” nominal size of standard weight. Each pipe thus has 11 possible sizes. This simple system therefore has 10^11 possible combinations of pipe sizes. Oh, and let’s throw in multiple operating cases and a variety of other requirements and limitations that engineers must contend with in the real world. With Intelliflow, Mercury applies very sophisticated optimization methods to evaluate the impact of each pipe on the overall cost of the system and the ability of the system to meet its performance requirements and limits. Using the artificial intelligence of Intelliflow, Mercury determines the optimum sizing to minimize system cost and meet the system requirements. Mercury’s ability to determine the optimum sizing is so far above what can otherwise be achieved that no other available method may be accurately referred to as optimizing.

Almost any type of system will benefit from Mercury’s optimization. Limited exceptions include extremely simple systems where the number of variables is so small that one can comprehensively analyze these to find an optimum using Fathom (though it will certainly take you longer to do so). Also, systems where there is no flexibility to change pipe sizes; e.g. replacing the pump on an existing system where pipe size changes are not being considered (though an optimization with Mercury may indicate such changes are well worth considering).

Yes, Mercury can optimally size systems over multiple cases. Indeed, this is a necessary capability for handling real world systems where multiple operating cases are the usual situation. Multiple cases may be of essentially any type, normal/standby, peak load/normal load, winter load/summer load and so on.

None to as much as you want. First, it’s important to know that you may select to have Mercury size your system on the basis of an engineering parameter optimization or a cost optimization. An engineering parameter optimization will size the piping for either minimum pipe weight, minimum pipe + fluid weight, minimum pipe volume or minimum pipe internal surface area. No cost data is needed for this since all of the information Mercury requires is contained in the engineering databases describing the pipe materials and fluids. Sizing on the basis of a cost optimization has two advantages. First, you’re sizing directly on what you are probably most interested in, minimum cost. Secondly, the sizing can now involve not only the pipes, but also pumps, control valves and other system components. How much cost data you provide Mercury is the same consideration traditionally used in estimating system cost. You can calculate every nut and bolt or provide minimal data such as cost per foot of pipe and simply apply multipliers to account for fittings, installation, etc. The point here is that Mercury allows you complete flexbility to work with cost at whatever level of detail you decide is appropriate.

Yes, Mercury will directly read Fathom models. What’s more, Mercury will generate a model scenario with input pipe sizes reflecting the optimum results, an Optimized Scenario. As with any scenario, this can be saved as a separate file that could then be opened and run in Fathom.

Most requirements are described through constraints. Mercury offers the user about 60 types of constraints. For pipes, for example, you may define constraints related to minimum and maximum values for pressures, velocity, flow and others. Pump constraints include min/max head, power, proximity to best efficiency point. Control valve constraints include pressure drop, open percentage and others. Any number of constraints may be defined and you have full control on which pipes, pumps, valves, etc. any constraint to which any constraint is applied. Constraints thus allow you define such requirements as; I need this minimum flow here at this minimum pressure, or don’t exceed this maximum pressure in this part of the system, or the pump(s) must operate within plus or minus this percentage of its best efficiency point.

Time variations may be readily defined. Further, if you wish, Mercury will size the system based on a present value cost objective using the interest and inflation rate you provide.

Just like Fathom, all of Mercury’s engineering databases describing fluids, piping materials and components (pumps, valve, etc.) may be modified. Further more, in Mercury, cost databases may be defined and modified at will. Importantly, these databases may be used across networks so that providing this information to Mercury makes it available to all users.

To answer this, first consider how you do it now. In the preliminary design stages you may only know requirements are going to be within a certain range. Ultimately, to size the system, you decide on a value or values to use as the design basis. This same consideration applies when you use Mercury, only now you can size your system more quickly and optimally for whatever design requirement you decide to use. Because Mercury lets you size systems quickly, you can readily investigate the effects of changing your requirements.