Prove system behaviour before live operation.
A realistic dynamic model gives the real control application a safe environment in which to respond, fail, recover and improve. TURNER ECS uses that closed loop to validate complete-system behaviour before commissioning.
A safe place to challenge a critical system.
Simulation lets engineers explore the responses that matter without exposing a live plant, vessel or machine to unnecessary test risk. The model and control application are developed together, then challenged with operating and fault scenarios.
Dynamic modelling
We represent the prime mover, driven equipment, electrical network and relevant process dynamics at a level appropriate to the project. I/O lists, design data and historical trends help define and calibrate the model.
The model can reproduce starts, load changes, trips, disturbances and recovery so the control system receives meaningful feedback.
Digital Twin validation
The control application interacts with the dynamic model in a closed loop. Engineers test sequences, protections, alarms, communications and operator interfaces against representative behaviour before deployment.
Where applicable, Woodward GAP and NetSim can execute the control code in the simulation environment with its intended timing.
From physical behaviour to control decisions.
The simplified view below replaces a dense wiring diagram with the four elements that make the test useful. The control acts on the model; the model responds; the operator interfaces show what happened.
Closed loop: the control output changes the model and the model returns realistic inputs. This exposes interactions that isolated component tests can miss.
A model that becomes useful engineering evidence.
Each stage adds confidence to the next. The scope and fidelity are agreed around the decisions, operating modes and risks the project needs to address.
- 01
Define the critical behaviour
Agree the operating envelope, success criteria, interfaces and credible disturbances to test.
- 02
Build the system model
Represent the machine and connected equipment using available engineering data, I/O and plant history.
- 03
Fit it to the real plant
Compare simulated and historical trends, then tune the model to the behaviours that matter.
- 04
Connect and challenge the control
Run the application, alarms, fallback logic and operator interfaces through normal and fault scenarios.
- 05
Review, refine and retain evidence
Use trends, event records and repeatable scenarios to improve the design and support FAT, commissioning and training.
Watch a disturbance unfold, then inspect the evidence.
These frames come from the supplied easYgen demonstration. Select any frame to enlarge the actual control and simulator screens. The example shows a mains failure followed by emergency generation, restoration and trend review.
01 / BASELINEEstablish the operating stateVerify normal indications and the starting conditions.
02 / DISTURBANCEIntroduce a mains failureObserve detection, alarms and the first control response.
03 / FALLBACKStart emergency generationCheck start logic and the transition toward a supported load.
04 / RECOVERYPrepare to return to the gridValidate synchronisation conditions and operating sequence.
05 / TRANSFERManage the load transferInspect the control response as supply conditions change.
06 / EVIDENCEReview event trendsCompare the recorded response with the agreed test criteria.
See the complete 36-second sequence, including the transitions between these six frames.
The interactions that decide whether the system is ready.
Test scope is shaped around the asset and its operating risk. A model can support development, design review, FAT preparation, issue diagnosis and operator training.
Prime mover response
Starts, shutdowns, speed and load transients, and protection limits.
Power management
Generator coordination, PMS/LSS logic, supply loss and recovery.
Fault and fallback
Credible equipment failures, alarms, trips and controlled fallback strategies.
System integration
Control communications and HMI, SCADA and DCS interfaces through protocol emulation where applicable.
Operator scenarios
Repeatable start-up, shutdown, disturbance and recovery exercises.
Evidence and tuning
Trend comparison, event review and controlled refinement before site activity.
Use the offline test to make live work more predictable.
Find integration issues earlier. See how the control, machine, electrical network and operator interface interact before site constraints dominate the schedule.
Prepare stronger acceptance tests. Repeat the same operating cases and retain the trends and event records needed for review.
Support commissioning and training. Rehearse normal and abnormal situations in a controlled environment, then carry the learning into the live phase.
What behaviour do you need to prove?
Tell us about the asset, control platform, available plant data and the scenarios that matter. We can help define the right model and test approach.