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Advanced Real-Time Simulation Laboratory by Prof. Gabriel A. Wainer

Explore innovative methodologies integrating real-time simulation with hardware, benefiting fields like defense, biology, and engineering. Develop advanced models for embedded systems and enhance collaboration through distributed techniques.

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Advanced Real-Time Simulation Laboratory by Prof. Gabriel A. Wainer

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  1. Advanced Real-Time Simulation Laboratory Prof. Gabriel A. Wainer Dept. of Systems and Computer Engineering http://www.sce.carleton.ca/faculty/wainer

  2. Engineering @ Carleton University Centre on Visualization and Simulation (V-Sim) • Interdisciplinary research • Defence and Emergency • Biology • Environmental Sciences • Mechanical Engineering • Aerospace Engineering • Cognitive Science • Systems and Computer Engineering • Architecture and City Planning • Traffic • Gaming

  3. Research areas • Defining advanced modelling and Simulation methodologies • Integrating techniques for development of simulations with hardware-in-the-loop • M&S as basis for development of embedded Real-Time systems • Improved performance and collaboration through parallel and distributed techniques • Open-Source model

  4. Layered View on M&S Visualization Applications Models Execution Engines (Simulators) (single/multi Proc/RT) Middleware/OS (Corba/HLA/P2P/MPI/WS…; Windows/Linux/RTOS…) Hardware (Workstations/Clusters/SBC…)

  5. Simulation Techniques

  6. Model-Based Development of Real-Time Systems • Integrate M&S in every step of the development of embedded RT systems. • M&S-based architecture: models used in simulation are the target for end products. • Rapid prototyping • Encourages reuse • Cost-effective • Prototype tools readily available

  7. Model-Based Development of Real-Time Systems Time Port Value 00:06:120 direction 1 00:06:130 activate 1 00:15:930 activate 0 00:56:800 direction 2 00:56:810 activate 1 01:01:130 activate 0 01:22:710 direction 2 Time Out-port Value 00:06:130 result 1 00:15:930 result 0 00:56:810 result 2 01:01:130 result 0 (…) components: eng@Engine in : activate_in direction_in out : result link : activate_in activate@eng link : direction_in direction@eng • Users develop simulated models • Move components to target • platform (no changes in model’s • coding)

  8. Model-Based Development of Real-Time Systems • Robot prototype • 6 man-hours to develop the whole • controller, test, modify, retest • Simulation-based solution (model • controls the robot) • Motor controller • Multi-motor controller

  9. Model-Based Development of Real-Time Systems • Model-based applications • Enhanced facilities for testing • Model execution: guaranteed to be • correct (formal specification) • Fully developed controller with sensor feedback • Remote control application

  10. Model-Based Distributed Simulation * see Notes

  11. Modelling and Simulation Methodologies and Tools

  12. Layered View on M&S Visualization Applications Models Execution Engines (Simulators) (single/multi Proc/RT) Middleware/OS (Corba/HLA/P2P/MPI/WS…; Windows/Linux/RTOS…) Hardware (Workstations/Clusters/SBC…)

  13. Main Goals • Reuse of simulation software in a different context? • Reuse of experiments carried out? • Changes/Updates in the model? • Engineering approach? • How do we validate the results?

  14. Varied methods for modelling - High level specifications translated into executable code * see Notes

  15. Varied methods for modelling

  16. High Level Specifications modelcircuit Modelica.Electrical.Analog.Sources.PulseVoltage V(V=10, width=50, period=2.5); Modelica.Electrical.Analog.Basic.Resistor R1(R=0.001); Modelica.Electrical.Analog.Basic.Inductor I1(L=500); Modelica.Electrical.Analog.Basic.Inductor I2(L=2000); Modelica.Electrical.Analog.Basic.Capacitor C(C=10); Modelica.Electrical.Analog.Basic.Resistor R2(R=1000); Modelica.Electrical.Analog.Basic.Ground Gnd; equation connect(V.p, R1.p); connect(R1.n, I1.p); connect(R1.n, I2.p); connect(I2.n, C.p); connect(I2.n, R2.p); connect(C.n, I1.n); connect(R2.n, C.n); connect(I1.n, V.n); connect(V.n, Gnd.p); endcircuit;

  17. Integrated Development Environment

  18. Applications

  19. Layered View on M&S Visualization Applications Models Execution Engines (Simulators) (single/multi Proc/RT) Middleware/OS (Corba/HLA/P2P/MPI/WS…; Windows/Linux/RTOS…) Hardware (Workstations/Clusters/SBC…)

  20. Current developments

  21. Applications Traffic Modelling

  22. High-level specification • language for traffic M&S • Automated simulation • generation • Integration with GIS • and Immersive • Environment • applications • Advanced 3D visualization • (work-in-progress)

  23. 3D visualization (being updated)

  24. Applications Biology and Medicine

  25. Molecular Biology Enzyme kinetics Ion channels Synapsin/Vesicle interactions Metabolic Pathways in human cells

  26. Biology Heart tissue Liver cells Encapsulated Cancer • - Ottawa Heart Institute • UC Berkeley/UCSF • Dept. of Biology, Carleton

  27. Physics and Chemistry Heat Spread Surface Tension • Binary solidification

  28. Flow Injection Analysis Model

  29. Applications Environmental Systems Analysis

  30. Landslides Pollution Forest Fires Flooding

  31. Fire Spread Modeling

  32. Applications Networking

  33. Network Performance Analysis

  34. Network Prototyping • Real time simulation on embedded microcontrollers • Rapid design and testing potential network devices

  35. Applications Defence and Emergency Planning

  36. SAT Building Evacuation: crowds + interoperability Collaboration with School of Architecture (CIMS)

  37. SAT Evacuation Visualization Maya (and other 3D visualization tools) integrated with simulation engine

  38. Summary • Well-established team • Expertise in M&S • Record of collaboration locally, Nationally and Internationally • Collaboration with Government, Industry and Academia • Truly interdisciplinary • The intersection of RCTI with V-SIM for a blend of: • real-time systems, virtual and live simulation • simulation interoperability • engineering methodology • military applications of M&S

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