What is a pipe?
Easy question? Not really. Like many answers “It depends”. I would like to answer in the context of; 1) failure analytics, 2) asset management principles, and 3) hydraulic modeling.
A failed pipe
Consider the classic Herz Deterioration formula used in calculating Remaining Useful Life:
Lower case “a” is the aging factor. A large value for “a” means a slow start to aging which is a good thing. Upper case “B” is the failure factor. A large value for “B” means a fast-aging process, influenced by corrosive soils for example. Lower case “c” is resistance, measured by the time to first failure. As “c” is in the denominator and it is an exponent, a lot is riding on “c”.
The question is, first failure of what? Well, the pipe. But that always leads to so many more questions.
A water main break is obviously a failure. But where did the break occur? How do you know it is the first failure of that specific pipe? Failure analytics is all about trending failure. The more data, the statistically accurate the prediction can be. Yet no one fixes pipe to collect failure data points, so the key is deciding how many times you are going to fix the “pipe” with Operations & Maintenance (O&M) point repairs before you decide to replace the whole “pipe” with a capital project.
Asset management principles remind us that a pipe can fail in other ways such as a failure in meeting capacity requirements and even water quality violating secondary MCLs such as taste or odor, but that’s for another blog.
A pipe asset
I have been in countless conversations defining “pipes” in CCTV inspection, GIS, and CMMS solutions. It’s kind of like television sets; high def vs low def. From bottom to top, the illustration below shows the concept of CCTV segments vs GIS features vs CMMS assets.
By NASSCO, WRc, and WSA standards, every pipe segment must be declared in the inspection record.
Therefore, in Vitreous Clay Pipe (VCP) sewer mains, every 10 foot / 3m pipe segment is noted in the system. In larger pipe systems this is known as the Lay Schedule; every manufactured pipe segment is identified.
Of course, every tap, defect, Change in Material (from a point repair), etc is also defined. That is inherent in the inspection standard. The “pipe” ID in a CCTV inspection record simply has a system identifier attached from the GIS or CMMS solution, along with session and observation headers. This high definition can be too complicated for many GIS or CMMS solutions.
GIS solutions abstract this one level up. Historically many GIS data conversions simply connected the dots, i.e. a straight line digitized between two water valves or sewer manholes. This initially created a one segment to one GIS feature to one asset record as a GIS pipe.
Material is a very common attribute, so over time when a point repair is made of differing material, many GIS professionals digitize the new material type, e.g. a PVC point repair in a VCP sewer main. This creates a higher fidelity than one pipe segment but is nowhere near as detailed as a CCTV inspection record. Very few GIS linear feature layers contain fittings given the number of resources to maintain such a high-fidelity dataset.
As many CMMS solutions are tabular only, a pipe is usually a named entity with some form of linear referencing built-in. Turning to asset management principles, one must consider the maintenance methods of linear assets. The pipe itself cannot be operated or controlled; it is the terminating devices to the pipe that operate it. A potable water pipe is typically bounded by valves that are opened or closed. Sewer gravity mains are cleaned or inspected by going through the manholes on either end of the pipe. This is the definition of a pipe in an asset management context. As shown in the illustration above, the pipe Maintenance Management Unit (MMU) has a singular asset ID. Whether to use sequential numbers or coded human intelligence is the subject of great debate and I will leave that for yet another blog, or white paper.
The hydraulic behavior of a pipe
Above we defined a water pipe as an MMU, a linear asset terminated by two isolation valves. Operationally these valves are usually open so water can flow. Given the same diameter, same material, same installation/construction methodology, same soil base; a series of connected pipes with open valves hydraulically behave the same.
We also noted that a pipe failure prediction is more accurate with more data. A short pipe physically can only have a few breaks before you have to replace the whole segment. These failures are linked to the structural and hydraulic behavior of the physical pipe.
So, if we extend our definition of a “super pipe” as a collection of pipes with the same attribution noted above, we can collect more failures to feed a more accurate failure analysis.
This failure behavior can then be applied to individual segments for specific failure prediction. Like hydraulic modeling, care needs to be taken in applying various assumptions that combine science and art. Given enough characterizations of failure through these “super pipes”, calibration patterns come to light across the entire system.
So, what is a pipe?
A pipe is an MMU such as a gravity sewer main terminated by two manholes or a potable water main terminated by two operable valves. Similar properties and maintenance strategy lead to the behavior of the pipe. Predicting its specific useful life can be extrapolated to the whole system. This is the fundamental building block for data analytics.