physics based simulation driven by monitoring data · • physics based simulation driven by...
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Physics Based Simulation Driven by Monitoring Data
Nils Ipsen
Senior Technical Consultant
EDRMedeso AS
Introduction
• Hi-fidelity simulations running in real-time where the input data is sensor data
• Component modelling and solving in real-time
• Incorporate physics based simulation into system simulation
• Two way data exchange and data transfer
• Typical applications and reference projects
Real-Time Simulation using Reduced Order Modelling or Co-Simulation
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0 5 10
Seco
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Inle
tTe
mp
erat
ure
(K)
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0 5 10
Seco
nd
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Inle
tTe
mp
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(K)
Time (s)
Fluent
Dynarom
DynaROM
Response Surface
Fluent
Dynarom
State Space Model Co-Simulation
Incorporating ROMs Into System Simulation
XX BARXX °C
PI SYSTEM
Socket
C++ ProgramC# Program
AF SDK
Socket
Ansys Twin BuilderReal-time Simulation
(ROM)
Asset with pressures sensors
P1
P2
P3
Ansys Twin BuilderReal-time Simulation
(ROM)
One PC
One Program
PTC ThingWorx running on Microsoft Azure
Typical applications and reference projects
• High volume products
– Added value to the product
– Product as a service
• Failure critical products
– Maximize uptime
– Maintain safety
• Production optimization
– Control over a complete process
Grundfos SYSMON digital twins - harness the power of IoT to optimize your life.Grundfos, a global leader in design and manufacturing of pumps and water systems, brings advanced simulation and prediction capabilities to real-time in collaboration with simulation-powerhouse ANSYS and elite channel partner EDRMedeso. Grundfos will use digital twins to better serve its customers through improved product quality and performance, enhanced development productivity, optimized maintenance and reduced overall costs and risks associated with unplanned downtime.
”We want to deliver best-in-class products and solutions to our customers, and digitalization opens new ways to capitalize on this.
We chose EDR&Medeso as our partner for this journey, because of their leading position in the market and their ability to deliver an end-to-end IIoT solution for predictive analytics and maintenance”
Olli Rantanen, CEO, Rolls-Royce Oy AbJoni Keski-Rahkonen, Manager, Rolls-Royce Oy Ab
Courtesy: Rolls-Royce
Digital Twin at Rolls-Royce
Summary
• Physics based simulation driven by monitoring data is a good way to obtain virtual sensor data.
• Is can replace the historical data that machine learning and AI need for predictive analysis.
• Reduced order modelling techniques are utilized to solve problems in real time.
• The reduced order models can be built in to a system simulation.
• Commercial tools are available and ready today.
• Questions?
