Master’s in Multiphysics Co-Simulation & FMI/FMU
Online master's programme of 1,900 hours in multiphysics co-simulation and FMI/FMU: 1D/3D coupling, orchestration and HIL/SIL. 12 modules covering coupled multiphysics systems, Modelica modelling, the FMI standard, co-simulation algorithms, 3D coupling, SSP and DCP, real-time and XiL simulation, model verification and validation, digital twins, sector applications and MBSE, with an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Model multiphysics systems with acausal languages.
Create, verify and integrate FMUs in line with the FMI standard.
Design stable, accurate co-simulation algorithms.
Couple 3D simulation with system models.
Deploy co-simulation in real-time and XiL environments.
Verify and validate models against credibility criteria.
Apply co-simulation to digital twins and systems engineering.
Who it's for
- System simulation engineers.
- Co-simulation specialists.
- Modelica modelling engineers.
- XiL validation engineers.
- Digital twin engineers.
- MBSE engineers.
- Engineering or science graduates looking to enter the automotive sector.
What you'll work with
- FMI 3.0 (Modelica Association) (Functional Mock-up Interface)
- SSP 1.0 (Modelica Association) (System Structure and Parameterization)
- DCP (Modelica Association) (Distributed Co-Simulation Protocol)
- Modelica Language Specification 3.6 (Modelica modelling language)
- ASAM XIL (test bench interface standard)
- ISO 26262 (road vehicle functional safety)
- ASME V&V 10 (verification and validation in computational solid mechanics)
- OpenModelica
- Dymola
- Simulink
- preCICE
- Simcenter Amesim
12 modules
1.1Thermal, mechanical and electrical coupling1.2Fluid-structure interaction1.3Strong and weak coupling1.4Time scales and stiffness1.5Modelling cyber-physical systems1.6System simulation versus 3D simulation1.7Examples in automotive and energy1.8Numerical errors in coupling1.9Toolchains in systems engineering1.10Case study: coupling analysis of an electric vehicle
2.1The Modelica language and acausal modelling2.2Modelica Standard Library2.3Electrical, mechanical and thermal components2.4Differential-algebraic equations2.5DAE index and index reduction2.6Inheritance and model reuse2.7Parameterisation and records2.8DASSL and IDA solvers2.9Model initialisation2.10Lab: electric motor model in Modelica
3.1History and governance of the Modelica Association3.2FMI for model exchange3.3FMI for co-simulation3.4FMI 3.0: clocks and terminals3.5XML model description3.6FMU C API3.7Variables, causality and variability3.8Export from commercial tools3.9Validation with the FMU Compliance Checker3.10Practical exercise: creating and verifying an FMU
4.1The co-simulation master4.2Jacobi and Gauss-Seidel schemes4.3Fixed and variable communication step4.4Input extrapolation and correction4.5Coupling stability4.6Energy conservation between subsystems4.7Rollback and step restart4.8Algebraic loops between FMUs4.9Coupling error analysis4.10Lab: co-simulation master in Python
5.1CFD co-simulation with system models5.2Structural FEM and control5.3MpCCI and preCICE interfaces5.4Mapping between non-matching meshes5.5Order reduction of 3D models5.6Reduced-order models exported as FMUs5.7Performance and parallelism5.8Validation of 3D-1D coupling5.9Thermal management cases5.10Case study: battery cooling with coupled CFD-system simulation
6.1System Structure and Parameterization6.2Connecting and parameterising FMUs6.3Distributed Co-Simulation Protocol6.4Networked distributed co-simulation6.5Integration with ASAM XIL6.6System variant management6.7Exchange between suppliers and OEMs6.8Intellectual property protection6.9Configuration traceability6.10Workshop: SSP architecture for a multi-supplier system
7.1MiL, SiL, HiL and ViL7.2Real-time simulators7.3Determinism and fixed step7.4Integrating FMUs into HiL7.5I/O interfaces and CAN buses7.6Testing control units7.7Latency and jitter7.8Test automation7.9Test bench management7.10Practical exercise: SiL test of a controller with an FMU
8.1Credibility of models and simulations8.2Code and solution verification8.3Validation with experimental data8.4Uncertainty quantification8.5Sensitivity analysis8.6Parameter calibration8.7Traceability to requirements8.8Credibility documentation8.9Independent reviews8.10Case study: validation plan for a system model
9.1FMU-based digital twins9.2Deploying FMUs at the edge and in the cloud9.3Updating models with data9.4State estimation with Kalman filters9.5Model-based predictive maintenance9.6Optimisation in operation9.7Integration with IoT platforms9.8Scaling simulations in the cloud9.9Digital twin life-cycle management9.10Lab: pump twin with FMU and data
10.1Full vehicle and powertrain10.2More-electric aircraft10.3Power grids and power electronics10.4Buildings and HVAC10.5Industrial hydraulic systems10.6Railways and traction10.7Renewable energy and hydrogen10.8Robotics and mechatronics10.9Lessons from multi-tool projects10.10Workshop: choosing a strategy for a sector case
11.1MBSE and SysML v211.2Linking architecture and simulation11.3Requirements verifiable by simulation11.4Model configuration management11.5CI workflows for simulation models11.6Corporate libraries and governance11.7Collaboration across disciplines11.8Simulation return metrics11.9Organisational maturity in simulation11.10Practical exercise: integrating SysML with co-simulation
12.1System definition and objectives12.2Co-simulation architecture12.3Model and FMU development12.4Master configuration12.5Coupling verification12.6Validation with data12.7Analysis of results12.8Conclusions and proposals12.9Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
The programme is delivered 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is OpenModelica, Dymola, Simulink, preCICE and Simcenter Amesim, in free, academic or evaluation versions. Exercises are based on real procedures: cross-tool co-simulation tests, model validation with test-bench data and software-in-the-loop testing. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: FMI 3.0 (Modelica Association), SSP 1.0 (Modelica Association), DCP (Modelica Association), Modelica Language Specification 3.6, ASAM XIL, ISO 26262, ASME V&V 10.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with OpenModelica, Dymola, Simulink, preCICE and Simcenter Amesim, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a suitable computer and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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