1. 1 EVALUATING INTELLIGENT FLUID AUTOMATION SYSTEMS USING A FLUID NETWORK SIMULATION ENVIRONMENT Ron Esmao - Sr. Applications Engineer, Flowmaster USA

2. 2 Importance of Fluid System Automation l l USS Stark – May 1987 – – Struck by 2 Iraqi missiles – – 35 men killed / mainly due to fire – – Fire protection system failed – – Defense systems shut down / Chilled water system failed l l Current Damage Control Scenarios – – Send crew to locate and isolate pipe damage – – Determine alternate flow path through redundant piping – – Reroute fluid by opening or closing appropriate valves l l Disadvantages – – Time consuming – – Puts crew in harms way – – Difficult to determine alternate flow paths

3. 3 Intelligent Fluid Automation Systems l l Intelligent Fluid Automation Systems can perform automated damage control even in the event the control system is damaged along with the fluid system. l l The challenge in the development of these systems is testing – – Past efforts centered on full and reduced scale physical testing – – Involved simulating a combat damage event and observing the system response l l Disadvantages – – The cost to fully equip, maintain and operate the physical system – – The cost of acquiring and recording the trajectories of the fluid system states during the test event – – Only a limited number of test scenarios can be practically orchestrated.

4. 4 Hardware Interface Module Testing Fluid Automation Systems l l Testing smart valve based fluid automation systems in the laboratory – without the need for the physical piping system l lThis involves connecting the physical automation system to a computer simulation of the fluid system. Automation System Components Fluid Network Simulation I/O Signals

5. 5 Selecting a Simulation Tool l l Requirements – – Must be able to compute the states of the fluid network (pressures, flows, etc.) in real-time. » » The real-time requirement is satisfied if the time to compute the next system state is less than the simulated time increment. » » If system state at time t is x(t) → x(t+Δt) must be computed in less than Δt – – The simulation tool must compute the states at each simulation time step using mathematical models that describe the transient behavior of the system. (Ex. Waterhamer effects due to rapid system change such as a pump tripping or a rapid opening or closing of a fluid service) – – Must be able to interact or interoperate with other software applications while the simulation is running. l l Simulation Tool Selected – FLOWMASTER2 ®

6. 6 Proof of Concept M M ABAB Smart valve Zone Rupture Location Smart valves

7. 7 Proof of Concept Smart Valve Node 1 Fluid Network Simulation Automation System HMI Application Network Interface Card Hardware Interface (DAQ Board) Hardware Interface Application Simulation Manager Smart Valve Node 2 Test & Simulation Workstation Distributed Control Network Architecture of the smart valve demonstration system

8. 8 Proof of Concept Monitor sensor values sent to smart valve node Specify actuator faults and sensor noise Initiate leak or rupture Monitor fluid network states Demonstration systems graphical interface

9. 9 Proof of Concept Fluid component libraries COM enabled gauges and controllers Specify component properties Add components to construct fluid network FLOWMASTER2 ® model of the demonstration fluid network

10. 10 Proof of Concept Monitor status information via the control network Command smart valve via the control network Monitor pressure and estimated flow information via the control network Demonstration systems graphical interface

11. 11 Proof of Concept l l Initial tests – – Set a simulation time step equal to 100 milliseconds – – Adjusted the flow through the simulation GUI – – Verified the hardware interface generated signals proportional to the state variables (i.e., pressure values) computed by FLOWMASTER2 ® – – Initiated a rupture – – Observed that the smart valve nodes detected the rupture and commanded the simulated valves to isolate the damaged piping zone – – Added white noise to the pressure signal and observed how the signal to noise ratio affected the accuracy of the flow estimates and flow balance at the nodes l l The initial tests were successful – demonstrated the simulation could run in real-time

12. 12 Validating the Fluid Network Simulation Tool l l This is an ongoing effort l l Involves modeling existing fluid system test facilities using FLOWMASTER2 and comparing simulation results to data obtained from operation of these fluid systems – – Chilled Water, Reduced Scale Advanced Demonstrator (CW-RSAD) » » Small scale replica of DDG 51 class chilled water system operated by NSWC » » This system is used to investigate the use of component-level intelligent distributed control system technology – – The modified firemain onboard the ex-USS Shadwell l l Validation is proving difficult due to the limited amount of data available on both of these systems l l However, preliminary results indicate that the simulated data sufficiently matches operational data

13. 13 The Next Step Database Scheduler Simulation Interface Damage Models Plant Models Hardware Interface Actual Control System I/O Signals e.g., Flowmaster2 fluid system models Software Component Hardware Component Laboratory Test and Development Platform Architecture

14. 14Conclusions l lUpon completion, this laboratory platform will allow automation system designers to test the performance of any intelligent fluid automation system under normal conditions and simulated damage scenarios. l lWe envision this laboratory environment will provide a necessary capability to Navy and industry design teams currently developing automated damage control systems for fluid systems onboard in-service and future surface combatants.

15. 15 Questions?