1. Virtual testing of a severe service control valve Mark A. Lobo, P.E. Lobo Engineering, P.L.C.

2.  Where have you been all my life?  Valentines Day 1969  1984 – The HP Portable and 1-2-3  The Microsoft Windows Workstation  The UberCloud CAE Experiment

3. CAE Server CAE Cloud 3 options to use technical compute power

4. ◦ CAE Software as a Service  The Cloud computing model ◦ rapidly provisioned and released with minimal management effort or service provider interaction.  The CAE in the Cloud model ◦ on remote high-performance Cloud computers ◦ over the Internet to your workstation. ◦ ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources

5.  Provides a restriction to fluid flow  Restriction is adjustable  Restriction varies with control signal  Applied in fluid process systems that must adapt to variable inputs or disturbances  Valve design fits application Courtesy of Badger Meter, Inc. Milwaukee, WI Flowserve Corporation Image DeZURIK Image

6.  Accuracy ◦ Hysteresis ◦ Linearity ◦ Repeatability

7.  Inherent Characteristic  Valve flow coefficient, C V  Liquid pressure recovery factors, F L and F LP  Reynolds Number factor, F R  Liquid critical pressure ratio factor, F F  Piping geometry factor, F P  Pressure drop ratio factor, x T and x TP ANSI/ISA-75.02.01-2008 Control Valve Capacity Test Procedures

8.  In-house or Out-house ◦ Usage frequency ◦ Location ◦ Cost Courtesy of Emerson Process Management

9. In-house ◦ Fire hydrant ◦ Flow meter ◦ Stopwatch ◦ Sewer ◦ Pressure gauges ◦ Isolation valves ◦ Pencil and paper ◦ Boots ◦ Rain suit Test Data ◦ Eleven control points 5%, 10%, …, 100% ◦ Ten differential pressure settings per control points, with upstream pressure constant ◦ 3-5 upstream pressure settings ◦ 300 to 500 data points

10.  Fluid process requirements ◦ Environment ◦ Fluid composition ◦ Range of conditions ◦ Accuracy ◦ Response time ◦ Reliability  Control Valve Specification ◦ Physical characteristics ◦ Flow Characteristic ◦ Ratings

11.  Resistance vs. control range  Flow Coefficient vs. Travel C V = Flow Coefficient Q = Flow rate, gpm F P = Piping geometry factor ρ 1 = Density of fluid at P & T ρ 0 = Standard density of fluid ΔP = differential pressure, psi G f = Specific gravity

13.  Static vs. dynamic pressure  Phase change  Valve acts smaller C V = Flow Coefficient Q = Flow rate, gpm F L = Liquid pressure recovery factor F LP = F L + piping geometry ρ 1 = Density of fluid at P & T ρ 0 = Standard density of fluid P 1 = Upstream pressure, psig F F = Pressure drop ratio factor P v = Vapor pressure, psig

15. Liquid Pressure Recovery Factor F L =.88

16. Courtesy of George E King Engineering * 24927 N Point Pl * Katy, TX * USA * 77494 Phone: (281) 851-8095 Gekengineering.com

17.  The valve model  Mechanical simulation  Heat transfer simulation  Fluid dynamics simulation ◦ Fully developed turbulent flow ◦ Flow path evaluation ◦ Data output mirrors physical test data ◦ Quick scenario setup ◦ Extensive control of solution settings ◦ Phase change challenges convergence

18.  ASME B16.34 compliant  Class 1500  5000 psig rating per API 6A  2” line size  C V above 60  F L above.95  Actuation torque below 3000 lb-in  Autodesk Inventor and Simulation Mechanical  Autodesk Simulation CFD 360

19.  Explore applying CAE in the cloud for simulation to drive product design  Educate the end user  Experience the software provider as cloud resource provider  Extensive trial (over 200 solution runs) to compare local vs. cloud solutions  Evaluate the investment in software Jon den Hartog, P.E., Autodesk ® Sr. Product Line Manager Heath Houghton, Autodesk ® Simulation CFD Product Manager

20.  Ideal flow path ◦ Straight body ◦ Simple Inlet/outlet transition ◦ Gradual velocity changes ◦ Minimize direction changes ◦ High F L  Actuation requirements ◦ Rotary to linear drive ◦ Efficient ◦ Transparent to flow path

25.  Volume flow rate ◦ Average velocity at inlet ◦ Area of inlet  Boundary conditions ◦ Upstream pressure ◦ Downstream pressure  Solution Settings  Convergence  Expectations

26. Results –Believe!

28. Liquid Pressure Recovery Factor F L =.97

29. Results –Believe! Liquid Pressure Recovery Factor F L =.97

32.  a pool of Amazon EC2 M2.4x large instances, each with 8 physical cores and 64.8 GB RAM  HP Z800 Dual 2.4GHz Quad Core E5620 Workstation, 24GB RAM  Local solves ◦ 1 scenario - 1 hour with dedicated workstation ◦ 3-4 hours running modeler in parallel  Cloud solves ◦ 10 scenarios – 3 hours

33. Simulation Solving Approach Approx Time to Complete Investment Required Single Desktop Machine + Local Computing 800 hours (1 month) Engineering Workstation + Simulation SW License Single Desktop Machine + Private HPC Cluster + Multiple Solver Licenses 24 hours (1 day) Engineering Workstation + Simulation SW License + 30 Node Compute Cluster + 30 Simulation Solver Licenses Single Desktop Machine + Cloud Computing 24 hours (1 day) Engineering Workstation + Simulation SW License + $1200 Cloud Compute Fee Cloud vs. local solution

34. Discover! Try! Buy!

35.  Started August 2012: today 1200+ participating organizations from 68 countries  144 teams formed in Rounds 1-5  HPC Experiment registration at: http://www.theubercloud.com/hpc- experiment/ http://www.theubercloud.com/hpc- experiment/  HPCwire Readers Choice Award 2013:

36. - UberCloud website: http://www.TheUberCloud.comhttp://www.TheUberCloud.com - Request UberCloud Promo Code: http://www.theubercloud.com/request-ubercloud-promo- code/?pc=hm-openfoam http://www.theubercloud.com/request-ubercloud-promo- code/?pc=hm-openfoam - HPC Experiment registration: http://www.theubercloud.com/hpc-experiment/ http://www.theubercloud.com/hpc-experiment/ - HPC Magazine cover story: http://www.hpcmagazine.com/cover-stories/an-inside-look- at-the-ubercloud-hpc-experiment/ http://www.hpcmagazine.com/cover-stories/an-inside-look- at-the-ubercloud-hpc-experiment/ - Compendium, case studies: http://www.hpcwire.com/whitepapers/2013-06- 25/the_ubercloud_hpc_experiment:_compendium_of_case_studi es.html http://www.hpcwire.com/whitepapers/2013-06- 25/the_ubercloud_hpc_experiment:_compendium_of_case_studi es.html - HPCwire Award: http://www.hpcwire.com/off-the-wire/ubercloud- receives-top-honors-2013-hpcwire-readers-choice-awards/ http://www.hpcwire.com/off-the-wire/ubercloud- receives-top-honors-2013-hpcwire-readers-choice-awards/