11

EVALUATING INTELLIGENT FLUID AUTOMATION SYSTEMS USING A

FLUID NETWORK SIMULATION ENVIRONMENT

Ron Esmao - Sr. Applications Engineer, Flowmaster USA

22

Importance of Fluid System AutomationImportance of Fluid System Automation

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

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

Disadvantages– Time consuming– Puts crew in harms way– Difficult to determine alternate flow

paths

33

Intelligent Fluid Automation SystemsIntelligent Fluid Automation Systems

Intelligent Fluid Automation Systems can perform automated damage control even in the event the control system is damaged along with the fluid system.

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

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.

44

HardwareInterfaceModule

Testing Fluid Automation SystemsTesting Fluid Automation Systems

Testing smart valve based fluid automation systems in the laboratory – without the need for the physical piping system

This involves connecting the physical automation system to a computer simulation of the fluid system.

Automation System

Components

FluidNetwork

Simulation

I/O Signals

55

Selecting a Simulation ToolSelecting a Simulation Tool

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.

Simulation Tool Selected – FLOWMASTER2®

66

Proof of ConceptProof of Concept

M M

A B AB

Smart valve Zone Rupture Location

Smart valves

77

Proof of ConceptProof of Concept

Smart Valve Node 1

Fluid NetworkSimulation

AutomationSystem HMIApplication

NetworkInterface

Card

HardwareInterface

(DAQ Board)

HardwareInterface

Application

Simulation Manager

Smart ValveNode 2

Test & Simulation Workstation

Distributed Control Network

Architecture of the smart valve

demonstration system

88

Proof of ConceptProof 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

99

Proof of ConceptProof 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

1010

Proof of ConceptProof 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

1111

Proof of ConceptProof of Concept

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

The initial tests were successful – demonstrated the simulation could run in real-time

1212

Validating the Fluid Network Simulation ToolValidating the Fluid Network Simulation Tool

This is an ongoing effort

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

Validation is proving difficult due to the limited amount of data available on both

of these systems

However, preliminary results indicate that the simulated data sufficiently

matches operational data

1313

The Next StepThe Next Step

Database

Scheduler

SimulationInterface

DamageModels

PlantModels

HardwareInterface

Actual Control System

Actual Control System

I/O Signals

e.g., Flowmaster2 fluid system modelsSoftware Component

Hardware Component

Laboratory Test and Development Platform Architecture

1414

ConclusionsConclusions

Upon 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.

We 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.

1515

Questions?