Pipeline hydraulics

[miyanui]

I am an EIT (mechanical) just starting out at a new job, I am looking to gather the best resources for getting up to speed in "pipeline hydraulics": pump selection, design, surge analysis,relief calcs, friction loss, hydraulic gradients etc. anyone have any ideas? would be nice to find a book that has lots of examples and sample problems, not just theory.

 

[21121956]

Hello everybody:

You can start with "Crane Fluid Flow Examples in MS" by Art Montemayor. It is a very good and handy technical paper.

Download it here

http://www.cheresources.com/invision/files/file/267-crane-fluid-flow-examples-in-ms-excel/

Good luck!

El que no puede andar, se sienta.

 

[Latexman]

Get Crane Technical Paper 410.

Crane Technical Paper No. 410 (TP-410) is the quintessential guide to understanding the flow of fluid through valves, pipes and fittings, enabling you to select the correct equipment for your piping system.

Originally developed in 1942, the latest edition of Crane TP-410 has been fully updated to reflect the latest knowledge and research in the fluid handling industry. The TP-410 has served as an indispensable technical resource for over 60 years to specifying engineers, designers and engineering students.

It can be ordered online here for US$60:

Crane TP-410

I've used Crane TP-410 for over 30 years.

Good luck,
Latexman

 

[zdas04]

Looking at the library that I've accumulated over 30+ years of doing this stuff, I would have:
[ul]
Crane Technical Paper #410
GPSA Field Engineering Data Book
Cameron Hydraulics
Marks handbook (least useful and most expensive of the list, but sometimes it is the only option)
[/ul]

There is also "Pipeline Rules of Thumb" which everyone eventually buys, but no one actually uses (worthless index, terrible organization, and some questionable calcs).

Those would do you well for a career.

David

David Simpson, PE
MuleShoe Engineering

"Belief" is the acceptance of an hypotheses in the absence of data.
"Prejudice" is having an opinion not supported by the preponderance of the data.
"Knowledge" is only found through the accumulation and analysis of data.