Carlos Paredes, profile picture
Uploaded byCarlos Paredes
PDF, PPTX273 views

Modelica-OpenModelica-slides para aprender.pdf

This document summarizes Peter Fritzson's presentation on modeling, simulation, and development of cyber-physical systems with OpenModelica and FMI. It discusses industrial challenges for complex cyber-physical systems and introduces OpenModelica as a free, open-source language and environment for modeling multi-domain systems. It provides examples of Modelica models for various applications like robotics, automotive, power plants, and more.

Embed presentation

Download as PDF, PPTX
1 / 108
2 / 108
3 / 108
4 / 108
5 / 108
6 / 108
7 / 108
8 / 108
9 / 108
10 / 108
11 / 108
12 / 108
13 / 108
14 / 108
15 / 108
16 / 108
17 / 108
18 / 108
19 / 108
20 / 108
21 / 108
22 / 108
23 / 108
24 / 108
25 / 108
26 / 108
27 / 108
28 / 108
29 / 108
30 / 108
31 / 108
32 / 108
33 / 108
34 / 108
35 / 108
36 / 108
37 / 108
38 / 108
39 / 108
40 / 108
41 / 108
42 / 108
43 / 108
44 / 108
45 / 108
46 / 108
47 / 108
48 / 108
49 / 108
50 / 108
51 / 108
52 / 108
53 / 108
54 / 108
55 / 108
56 / 108
57 / 108
58 / 108
59 / 108
60 / 108
61 / 108
62 / 108
63 / 108
64 / 108
65 / 108
66 / 108
67 / 108
68 / 108
69 / 108
70 / 108
71 / 108
72 / 108
73 / 108
74 / 108
75 / 108
76 / 108
77 / 108
78 / 108
79 / 108
80 / 108
81 / 108
82 / 108
83 / 108
84 / 108
85 / 108
86 / 108
87 / 108
88 / 108
89 / 108
90 / 108
91 / 108
92 / 108
93 / 108
94 / 108
95 / 108
96 / 108
97 / 108
98 / 108
99 / 108
100 / 108
101 / 108
102 / 108
103 / 108
104 / 108
105 / 108
106 / 108
107 / 108
108 / 108
Presentation at RISE SICS East, Sweden October 6, 2018 Peter Fritzson peter.fritzson@liu.se Full Professor at Linköping University Director Open Source Modelica Consortium Vice Chairman of Modelica Association Director of the MODPROD Center for model-based development Modeling, Simulation, and Development of Cyber- Physical Systems with OpenModelica and FMI
2 Industrial Challenges for Complex Cyber-Physical System Products of both Software and Hardware • Increased Software Fraction • Shorter Time-to-Market • Higher demands on effective strategic decision making • Cyber-Physical (CPS) – Cyber (software) Physical (hardware) products
3 Peter Fritzson Principles of Object Oriented Modeling and Simulation with Modelica 3.3 A Cyber-Physical Approach Can be ordered from Wiley or Amazon Wiley-IEEE Press, 2014, 1250 pages • OpenModelica • www.openmodelica.org • Modelica Association • www.modelica.org Big Book on Modelica and Technology, Dec 2014 Download Free OpenModelica Software
4 September 2011 232 pages Translations available in Chinese, Japanese, Spanish Wiley IEEE Press For Introductory Short Courses on Object Oriented Mathematical Modeling Introductory Modelica Book
5 Part I Introduction to Modelica
6 Modelica Background: Stored Knowledge Model knowledge is stored in books and human minds which computers cannot access “The change of motion is proportional to the motive force impressed “ – Newton
7 Modelica Background: The Form – Equations • Equations were used in the third millennium B.C. • Equality sign was introduced by Robert Recorde in 1557 Newton still wrote text (Principia, vol. 1, 1686) “The change of motion is proportional to the motive force impressed ” CSSL (1967) introduced a special form of “equation”: variable = expression v = INTEG(F)/m Programming languages usually do not allow equations!
8 What is Modelica? • Robotics • Automotive • Aircrafts • Satellites • Power plants • Systems biology A language for modeling of complex cyber-physical systems
9 What is Modelica? A language for modeling of complex cyber-physical systems Primary designed for simulation, but there are also other usages of models, e.g. optimization.
10 What is Modelica? A language for modeling of complex cyber-physical systems i.e., Modelica is not a tool Free, open language specification: There exist several free and commercial tools, for example: • OpenModelica from OSMC • Dymola from Dassault systems • Wolfram System Modeler fr Wolfram MathCore • SimulationX from ITI – ESI Group • MapleSim from MapleSoft • AMESIM from LMS • JModelica.org from Modelon • MWORKS from Tongyang Sw & Control • IDA Simulation Env, from Equa Available at: www.modelica.org Developed and standardized by Modelica Association
11 Declarative language Equations and mathematical functions allow acausal modeling, high level specification, increased correctness Multi-domain modeling Combine electrical, mechanical, thermodynamic, hydraulic, biological, control, event, real-time, etc... Everything is a class Strongly typed object-oriented language with a general class concept, Java & MATLAB-like syntax Visual component programming Hierarchical system architecture capabilities Efficient, non-proprietary Efficiency comparable to C; advanced equation compilation, e.g. 300 000 equations, ~150 000 lines on standard PC Modelica – The Next Generation Modeling Language
12 What is acausal modeling/design? Why does it increase reuse? The acausality makes Modelica library classes more reusable than traditional classes containing assignment statements where the input-output causality is fixed. Example: a resistor equation: R*i = v; can be used in three ways: i := v/R; v := R*i; R := v/i; Modelica Acausal Modeling
13 What is Special about Modelica? • Multi-Domain Modeling • Visual acausal hierarchical component modeling • Typed declarative equation-based textual language • Hybrid modeling and simulation
14 What is Special about Modelica? Multi-Domain Modeling Cyber-Physical Modeling Physical Cyber 3 domains - electric - mechanics - control
15 What is Special about Modelica? Multi-Domain Modeling Acausal model (Modelica) Causal block-based model (Simulink) Keeps the physical structure Visual Acausal Hierarchical Component Modeling
16 inertial x y axis1 axis2 axis3 axis4 axis5 axis6 r3Drive1 1 r3Motor r3Control qdRef 1 S qRef 1 S k2 i k1 i qddRef cut joint l qd tn Jmotor=J gear=i spring=c fric=Rv0 S rel joint=0 S Vs - + diff - + pow er emf La=(250/(2*D*wm)) Ra=250 Rd2=100 C=0.004*D/w m - + OpI Rd1=100 Ri=10 Rp1=200 Rp2=50 Rd4=100 hall2 Rd3=100 g1 g2 g3 hall1 g4 g5 r w qd q rate2 b(s) a(s) rate3 340.8 S rate1 b(s) a(s) tacho1 PT1 Kd 0.03 w Sum - sum +1 +1 pSum - Kv 0.3 tacho2 b(s) a(s) q qd iRef qRef qdRef What is Special about Modelica? Visual Acausal Hierarchical Component Modeling Multi-Domain Modeling Hierarchical system modeling Courtesy of Martin Otter Srel = n*transpose(n)+(identity(3)- n*transpose(n))*cos(q)- skew(n)*sin(q); wrela = n*qd; zrela = n*qdd; Sb = Sa*transpose(Srel); r0b = r0a; vb = Srel*va; wb = Srel*(wa + wrela); ab = Srel*aa; zb = Srel*(za + zrela + cross(wa, wrela));
17 What is Special about Modelica? Multi-Domain Modeling Typed Declarative Equation-based Textual Language A textual class-based language OO primary used for as a structuring concept Behaviour described declaratively using • Differential algebraic equations (DAE) (continuous-time) • Event triggers (discrete-time) class VanDerPol "Van der Pol oscillator model" Real x(start = 1) "Descriptive string for x”; Real y(start = 1) "y coordinate”; parameter Real lambda = 0.3; equation der(x) = y; der(y) = -x + lambda*(1 - x*x)*y; end VanDerPol; Differential equations Variable declarations Visual Acausal Hierarchical Component Modeling
18 What is Special about Modelica? Hybrid Modeling Visual Acausal Component Modeling Multi-Domain Modeling Typed Declarative Equation-based Textual Language time Continuous-time Discrete-time Hybrid modeling = continuous-time + discrete-time modeling Clocked discrete-time
19 Modelica vs Simulink Block Oriented Modeling Simple Electrical Model R1=10 C=0.01 L=0.1 R2=100 G AC=220 p n p p p p p n n n n -1 1 sum3 +1 -1 sum1 +1 +1 sum2 1 s l2 1 s l1 sinln 1/R1 Res1 1/C Cap 1/L Ind R2 Res2 Modelica: Physical model – easy to understand Simulink: Signal-flow model – hard to understand Keeps the physical structure
20 OpenModelica Tool Graphical Editor and Plotting Graphical Modeling Using Drag and Drop
21 Graphical Modeling with OpenModelica Environment
22 • A DC motor can be thought of as an electrical circuit which also contains an electromechanical component model DCMotor Resistor R(R=100); Inductor L(L=100); VsourceDC DC(f=10); Ground G; ElectroMechanicalElement EM(k=10,J=10, b=2); Inertia load; equation connect(DC.p,R.n); connect(R.p,L.n); connect(L.p, EM.n); connect(EM.p, DC.n); connect(DC.n,G.p); connect(EM.flange,load.flange); end DCMotor load EM DC G R L Multi-Domain (Electro-Mechanical) Modelica Model
23 Automatic transformation to ODE or DAE for simulation: (load component not included) Corresponding DCMotor Model Equations The following equations are automatically derived from the Modelica model:
24 Model Translation Process to Hybrid DAE to Code Modelica Model Flat model Hybrid DAE Sorted equations C Code Executable Optimized sorted equations Modelica Model Modelica Graphical Editor Modelica Source code Translator Analyzer Optimizer Code generator C Compiler Simulation Modelica Textual Editor Frontend Backend "Middle-end" Modeling Environment
25 Brief Modelica History • First Modelica design group meeting in fall 1996 • International group of people with expert knowledge in both language design and physical modeling • Industry and academia • Modelica Versions • 1.0 released September 1997 • 2.0 released March 2002 • 2.2 released March 2005 • 3.0 released September 2007 • 3.1 released May 2009 • 3.2 released March 2010 • 3.3 released May 2012 • 3.2 rev 2 released November 2013 • 3.3 rev 1 released July 2014 • 3.4 released May 2017 • Modelica Association established 2000 in Linköping • Open, non-profit organization
26 Modelica in Power Generation GTX Gas Turbine Power Cutoff Mechanism Hello Courtesy of Siemens Industrial Turbomachinery AB Developed by MathCore for Siemens
27 Modelica in Automotive Industry
28 Modelica in Avionics
29 Application of Modelica in Robotics Models Real-time Training Simulator for Flight, Driving Courtesy of Tobias Bellmann, DLR, Oberphaffenhofen, Germany • Using Modelica models generating real-time code • Different simulation environments (e.g. Flight, Car Driving, Helicopter) • Developed at DLR Munich, Germany • Dymola Modelica tool
30 Large Robotic Flight Simulator (Demo)
31 • GT unit, ST unit, Drum boilers unit and HRSG units, connected by thermo-fluid ports and by signal buses • Low-temperature parts (condenser, feedwater system, LP circuits) are represented by trivial boundary conditions. • GT model: simple law relating the electrical load request with the exhaust gas temperature and flow rate. Combined-Cycle Power Plant Plant model – system level Courtesy Francesco Casella, Politecnico di Milano – Italy and Francesco Pretolani, CESI SpA - Italy
32 Attitude control for satellites using magnetic coils as actuators Torque generation mechanism: interaction between coils and geomagnetic field Formation flying on elliptical orbits Control the relative motion of two or more spacecraft Modelica Spacecraft Dynamics Library Courtesy of Francesco Casella, Politecnico di Milano, Italy
33 Biggest Immediate Challenge for Humanity – Create a Sustainable Society – Avoid Global Collapse in 50 Years World System Dynamics Simulation with OpenModelica – World3 model, Meadows et al Sustainable, Scenario 9 4% improvement per year Collapse ca 2070, Scenario 2 Close to current developments Climate change, pollution, desertification, etc. www.openmodelica.org Download software from World population Year
34 World3 Model in Modelica, Meadows et al, Cellier Comprehensive model – 13 areas • Population dynamics • Human fertility • Human ecological footprint • Pollution dynamics • Industrial investment • Human welfare • Arable land • Labor utilization • Life expectancy • Food production • Land fertility • Non-recover resource • Service sector
35 Each Year New Record for Global Mean Temperature This is February 2016
36 World3 Simulations with Different Start Years for Sustainable Policies – Collapse if starting too late
37
How the world could be in 80-100 years at a global warming of 4 degrees See level rise 2 m flooding coastal cities Uninhabitable New Scientist, 28 february 2009 IPCC, business as usual scenario www.climate-lab-book.ac.uk www.atmosfair.de References Cities, agriculture Uninhabitable desert Uninhabitable due to extreme weather Flooded Business-as-usual scenario, IPCC Massive migration to to northern Europe, Russia, and Canada Example Emissions CO2e / person - Earth can handle 2 ton/yr - Flight Spain – 1 ton - Flight Canaryisl – 2 ton - Flight Thailand – 4 ton
39 Year 1750‐2000: • Mean temperature north hemisphere, • Population, • CO2‐concentration, • BNP, • Loss av rain forest, • Water usage • Paper consumption, • Exterminated species • Oil consumtion, • Motor vehicles • Destroyed fish populations • Destruction of ozon layer • Foreign investments A Unique Point in History – Exponential Trends Approaches Planet Earth Boundaries
40 Need Smart Systems to Support a Circular Economy for a Sustainable Society • Circular management of products, material, throughout the life-cycle • Optimize manufacturing and usage over the entire life cycle
41 What Can You Do? Need Global Sustainability Mass Movement • Develop smart Cyber-Physical systems for reduced energy and material footprint • Model-based circular economy for re-use of products and materials • Promote sustainable lifestyle and technology • Install electric solar PV panels • Buy shares in cooperative wind power 20 sqm solar panels on garage roof, Nov 2012 Generated 2700 W at noon March 10, 2013 Expanded to 93 sqm, 12 kW, March 2013 House produced 11600 kwh, used 9500 kwh Avoids 10 ton CO2 emission per year
42 Example Electric Cars Can be charged by electricity from own solar panels Renault ZOE; 5 seat; Range: 22kw (2014) vs 41 kw battery (2017) • Realistic Swedish drive cycle: • Summer: 165 km, now 300 km • Winter: 110 km, now 200 km Cheap fast AC chargers (22kw, 43kw) Tesla model S range 480 km DLR ROboMObil • experimental electric car • Modelica models
43 What Can You Do? More Train Travel – Less Air Travel • Air travel by Swedish Citizens – about the same emissions as all personal car traffic in Sweden! • By train from Linköping to Munich and back – saves almost 1 ton of CO2e emissions compared to flight • Leave Linköping 07.00 in Munich 23.14 More Examples, PF travel 2016: • Train Linköping-Paris, Dec 3- 6, EU project meeting • Train Linköping-Dresden, Dec 10-16, 1 week workshop Train travel Linköping - Munich
44 Small rectangles – surface needed for 100% solar energy for humanity
45 Part II Introduction to the OpenModelica Environment
The OpenModelica Environment www.openmodelica.org
47 OpenModelica – Free Open Source Tool Developed by the Open Source Modelica Consortium (OSMC) • Graphical editor • Model compiler and simulator • Debugger • Performance analyzer • Dynamic optimizer • Symbolic modeling • Parallelization • Electronic Notebook and OMWebbook for teaching • Spokentutorial for teaching EngineV6 11116 equation model
48 • Advanced Interactive Modelica compiler (OMC) • Supports most of the Modelica Language • Modelica and Python scripting • Basic environment for creating models • OMShell – an interactive command handler • OMNotebook – a literate programming notebook • MDT – an advanced textual environment in Eclipse 48 • OMEdit graphic Editor • OMDebugger for equations • OMOptim optimization tool • OM Dynamic optimizer collocation • ModelicaML UML Profile • MetaModelica extension • ParModelica extension • OMSimulator – FMI/TLM simulator The OpenModelica Open Source Environment www.openmodelica.org new
49 The OpenModelica Tool Architecture Simulation Execution OMEdit Graphic and Textual Model Editor OMNotebook Interactive Notebooks Debugger OMC Interactive Compiler Server ModelicaML UML/Modelica and requirement verification MDT Eclipse Plugin OMOptim Optimization 3D Visualization OMShell Modelica Scripting OMPython Python Scripting OMSimulator FMI Simulation OMJulia Julia Scripting OMWebbook Interactive Notebooks OMMatlab Matlab Scripting OMSens sensitivity analysis OMSysident
50 Industrial members • ABB AB, Sweden • Berger IT-Cosmos, Germany • Bosch Rexroth AG, Germany • Brainheart Energy AB, Sweden • CDAC Centre, Kerala, India • Creative Connections, Prague • DHI, Aarhus, Denmark • Dynamica s.r.l., Cremona, Italy • EDF, Paris, France • Equa Simulation AB, Sweden • Fraunhofer IWES, Bremerhaven • INRIA, Rennes, France • ISID Dentsu, Tokyo, Japan Open-source community services • Website and Support Forum • Version-controlled source base • Bug database • Development courses • www.openmodelica.org Code Statistics • FH Bielefeld, Bielefeld, Germany • University of Bolivar, Colombia • TU Braunschweig, Germany • University of Calabria, Italy • Univ California, Berkeley, USA • Chalmers Univ, Control,Sweden • Chalmers Univ, Machine, Sweden • TU Darmstadt, Germany • TU Delft, The Netherlands • TU Dresden, Germany • Université Laval, Canada • Georgia Inst of Technology, USA • Ghent University, Belgium • Halmstad University, Sweden University members OSMC – International Consortium for Open Source Model-based Development Tools, 53 members Febr 2018 Founded Dec 4, 2007 • Maplesoft, Canada • RTE France, Paris, France • Saab AB, Linköping, Sweden • Scilab Enterprises, France • SKF, Göteborg, Sweden • TLK Thermo, Germany • Siemens Turbo, Sweden • Sozhou Tongyuan, China • Talent Swarm, Spain • VTI, Linköping, Sweden • VTT, Finland • Wolfram MathCore, Sweden • Heidelberg University, Germany •TU Hamburg/Harburg Germany • IIT Bombay, Mumbai, India • KTH, Stockholm, Sweden • Linköping University, Sweden • Univ of Maryland, Syst Eng USA • Univ of Maryland, CEEE, USA • Politecnico di Milano, Italy • Ecoles des Mines, CEP, France • Mälardalen University, Sweden • Univ Pisa, Italy • Univ College SouthEast Norway • Tsinghua Univ, Beijing, China • Vanderbilt Univ, USA
51 OpenModelica Graphical Editor and Plotting
52 OpenModelica Simulation in Web Browser Client OpenModelica compiles to efficient Java Script code which is executed in web browser MultiBody RobotR3.FullRobot
53 Spoken-Tutorial step-by-step OpenModelica and Modelica Tutorial Using OMEdit. Link from www.openmodelica.org 1,600,000 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 2,011 2,012 2,013 2,014 2,015 2,016 Number of students/teachers trained in their colleges/schools
54 OMnotebook Interactive Electronic Notebook Here Used for Teaching Control Theory
55 OM Web Notebook Generated from OMNotebook Edit, Simulate, Plot Models on a Web Page http://omwebbook.openmodelica.org/ OMweb book OMNote book
56 OMPython – Python Scripting with OpenModelica • Interpretation of Modelica commands and expressions • Interactive Session handling • Library / Tool • Optimized Parser results • Helper functions • Deployable, Extensible and Distributable
57 General Tool Interoperability & Model Exchange Functional Mock-up Interface (FMI) • FMI development was started by ITEA2 MODELISAR project. FMI is a Modelica Association Project now • Version 1.0 • FMI for Model Exchange (released Jan 26,2010) • FMI for Co-Simulation (released Oct 12,2010) • Version 2.0 • FMI for Model Exchange and Co-Simulation (released July 25,2014) • > 80 tools supporting it (https://www.fmi-standard.org/tools) Engine with ECU Gearbox with ECU Thermal systems Automated cargo door Chassis components, roadway, ECU (e.g. ESP) etc. functional mockup interface for model exchange and tool coupling courtesy Daimler
58 Functional Mockup Units • Import and export of input/output blocks – Functional Mock-Up Units – FMUs, described by • differential-, algebraic-, discrete equations, • with time-, state, and step-events • An FMU consists of (compiled) C-code, + interface description in XML • An FMU can be large (e.g. 100 000 variables) • An FMU can be used in an embedded system (small overhead) • FMUs can be connected together
59 OpenModelica Functional Mockup Interface (FMI)
60 OMSimulator Composite Model Editor with 3D Viewer Combine External (FMI) Models into New Models • Composite model editor with 3D visualization of connected mechanical model components which can be FMUs, Modelica models, etc., or co-simulated components • 3D animation possible • Composite model saved as XML-file
61 OMSimulator – Integrated FMI and TLM-based Cosimulator/Simulator in OpenModelica OMSimulator Integrated TLM & FMI libOMSimulator Simulink wrapper Beast wrapper ADAMS wrapper TLM component C-API interface OMEdit Papyrus Scripting … OMC FMI component FMI component FMI FMU Modelica model Composite FMI component
62 Embedded System Support in OpenModelica • Code generation of real-time Controllers from Modelica models for small foot-print platforms
63 Single board heating system (IIT Bombay) • Use for teaching basic control theory • Usually controlled by serial port (set fan value, read temperature, etc) • OpenModelica can generate code targeting the ATmega16 on the board (AVR-ISP programmer in the lower left). Program size is 4090 bytes including LCD driver and PID-controller (out of 16 kB flash memory available). Use Case: SBHS (Single Board Heating System) Movie Demo!
64 Example – Code Generation to SHBS
65 Code Generator Comparison, Full vs Simple Full Source-code FMU targeting 8-bit AVR proc Simple code generator targeting 8-bit AVR proc Hello World (0 equations) 43 kB flash memory 23 kB variables (RAM) 130 B flash memory 0 B variables (RAM) SBHS Board (real-time PID controller, LCD, etc) 68 kB flash memory 25 kB variables (RAM) 4090 B flash memory 151 B variables (RAM) The largest 8-bit AVR processor MCUs (Micro Controller Units) have 16 kB SRAM. One of the more (ATmega328p; Arduino Uno) has 2 kB SRAM. The ATmega16 we target has 1 kB SRAM available (stack, heap, and global variable
66 • Free library for interfacing hardware drivers • Cross-platform (Windows and Linux) • UDP , SharedMemory, CAN, Keyboard, Joystick/Gamepad • DAQ cards for digital and analog IO (only Linux) • Developed for interactive real- time simulations Communication & I/O Devices: MODELICA_DEVICEDRIVERS Library
67 OMEdit 3D Visualization of Multi-Body Systems • Built-in feature of OMEdit to animate MSL-Multi-Body shapes • Visualization of simulation results • Animation of geometric primitives and CAD-Files New Animation Window Simulate with Animation
68 OpenModelica 3D Animation Demo
69 OpenModelica 3D Animation Demo – Excavator
70 Visualization using Third-Party Libraries: DLR Visualization Library • Advanced, model-integrated and vendor-unspecific visualization tool for Modelica models • Offline, online and real-time animation • Video-export function • Commercial library, feature reduced free Community Edition exists Courtesy of Dr. Tobias Bellmann (DLR)
71 Problems Solved problems Result plot Export result data .csv OMOptim – Parameter Sweep Design Optimization Here Pareto front optimiza- tion
72 Optimization of Dynamic Trajectories Using Multiple-Shooting and Collocation • Minimize a goal function subject to model equation constraints, useful e.g. for NMPC • Multiple Shooting/Collocation • Solve sub-problem in each sub-interval 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 1 2 4 8 16 MULTIPLE_COLLOCATION ipopt [scaled] jac_g [scaled] Example speedup, 16 cores: In OpenModelica 1.9.1 beta release Jan 2014.
73 OpenModelica Dynamic Optimization Collocation
74 Failure Mode and Effects Analysis (FMEA) in OM • Modelica models augmented with reliability properties can be used to generate reliability models in Figaro, which in turn can be used for static reliability analysis • Prototype in OpenModelica integrated with Figaro tool Modelica Library Application Modelica model Simulation Figaro Reliability Library Reliability model in Figaro FT generation FT processing Automated generation
75 OpenModelica Model Parallelization Faster Simulation on Multi-Core Automated parallelization of models Parallelizing numeric Jacobian computations in simulation 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 1 2 3 4 6 8 10 12 14 Speedup ScalableTestSuite N=39 nnz= 818 Sp… number of threads Speedup about 4 using 8 threads
76 Recent Large-scale ABB OpenModelica Application Generate code for controlling 7.5 to 10% of German Power Production ABB OPTIMAX PowerFit • Real-time optimizing control of large- scale virtual power plant for system integration • Software including OpenModelica now used in managing more than 2500 renewable plants, total up to 1.5 GW High scalability supporting growth • 2012: initial delivery (for 50 plants) • 2013: SW extension (500 plants) • 2014: HW+SW extension (> 2000) • 2015: HW+SW extension, incl. OpenModelica generating optimizing controller code in FMI 2.0 form Manage 7.5% - 10% of German Power • 2015, Aug: OpenModelica Exports FMUs for real-time optimizing control (seconds) of about 5.000 MW (7.5%) of power in Germany
77 Part III Equation-Based Model Dynamic Debugging and Performance Analysis
78 Need for Debugging Tools Map Low vs High Abstraction Level • A major part of the total cost of software projects is due to testing and debugging • US-Study 2002: Software errors cost the US economy annually~ 60 Billion $ • Problem: Large Gap in Abstraction Level from Equations to Executable Code • Example error message (hard to understand) Error solving nonlinear system 132 time = 0.002 residual[0] = 0.288956 x[0] = 1.105149 residual[1] = 17.000400 x[1] = 1.248448 ...
79 OpenModelica Equation Model Debugger 0 = y + der(x * time * z); z = 1.0; (1) substitution: y + der(x * (time * z)) => y + der(x * (time * 1.0)) (2) simplify: y + der(x * (time * 1.0)) => y + der(x * time) (3) expand derivative (symbolic diff): y + der(x * time) =>y + (x + der(x) * time) (4) solve: 0.0 = y + (x + der(x) * time) => der(x) = ((-y) - x) / time time <> 0 Example of equation transformations on a model:
80 Mapping dynamic run-time error to source model position Integrated Static-Dynamic OpenModelica Equation Model Debugger Showing equation transfor mations of a model: Efficient handling of Large Equation Systems
81 Transformations Browser – EngineV6 Overview (11 116 equations in model)
82 Performance Profiling (Here: Profiling all equations in MSL 3.2.1 DoublePendulum)
83 • ABB OPTIMAX® provides advanced model based control products for power generation and water utilities. • ABB: “OpenModelica provides outstanding debugging features that help to save a lot of time during model development.” ABB Commercial Application Use of Debugger
84 Equation Model Debugging on Siemens Model (used on Siemens Evaporator test model, 1100 equations) 84
85 Equation Model Debugger on Siemens Model (Siemens Evaporator test model, 1100 equations) Pointing out the buggy equation y = u1/u2; that gives division by zero
86 Performance Profiling for faster Simulation (Here: Profiling equations of Siemens Drum boiler model with evaporator • Measuring performance of equation blocks to find bottlenecks • Useful as input before model simplification for real-time applications • Integrated with the debugger to point out the slow equations • Suitable for real-time profiling (collect less information), or a complete view of all equation blocks and function calls Conclusion from the evaluation: “…the profiler makes the process of performance optimization radically shorter.”
87 Part IV Dynamic Verification/Testing of Requirements vs Usage Scenario Models Wladimir Schamai, Lena Buffoni, Peter Fritzson and contributions from MODRIO partners
88 OpenModelica and Papyrus Based Model-Based Development Environment to Cover Product-Design V Product models Requirements models Unified Modeling: Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models Specification Design Design Refinement Component verification Subsystem level integration and verification Subsystem level integration test calibration and verification Product verification and deployment Maintenance Realization Detailed feature design and implementation Architectural design and system functional design Preliminary feature design System requirements Level of Abstraction Documentation, Version and Configuration Management Verification Integration Calibration Experience Feedback
89 Business Process Control and Modeling Product models Requirements models Unified Modeling: Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models Metso Business model & simulation VTT Simantics Graphic Modeling Too OpenModelica based simulation Simulation of 3 strategies with outcomes VTT Simantics Business process modeler OpenModelica compiler & simulator
90 Requirement Capture Product models Requirements models Unified Modeling: Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models OpenModelica based simulation vVDR (virtual Verification of Designs against Requirements) in ModelicaML UML/Modelica Profile, part of OpenModelica Design Model Scenario Model Requirement Models Verification Model Binding Provider from design model Client from requirement model
91 OpenModelica – ModelicaML UML Profile Based on Open-Source Papyrus UML and OpenModelica • ModelicaML is a UML Profile for SW/HW modeling • Applicable to “pure” UML or to other UML profiles, e.g. SysML • Standardized Mapping UML/SysML to Modelica • Defines transformation/mapping for executable models • Being standardized by OMG • ModelicaML • Defines graphical concrete syntax (graphical notation for diagram) for representing Modelica constructs integrated with UML • Includes graphical formalisms (e.g. State Machines, Activities, Requirements) • Which do not yet exist in Modelica language (extension work ongoing) • Which are translated into executable Modelica code • Is defined towards generation of executable Modelica code • Current implementation based on the Papyrus UML tool + OpenModelica
92 Example: Simulation and Requirements Evaluation Req. 001 is instantiated 2 times (there are 2 tanks in the system) tank-height is 0.6m Req. 001 for the tank2 is violated Req. 001 for the tank1 is not violated
93 ModelicaML: Graphical Notation a Structure Behavior Requirements
94 Example: Representation of System Structure Interconnections Inheritance Components
95 Example: Representation of System Behavior State Machine of the Tank State Machine of the Controller Conditional Algorithm (Activity Diagram)
96 Example: Representation of System Requirements Textual Requirement Formalized Requirement
97 vVDR Method – virtual Verification of Designs vs Requirements Formalize Requirements Formalize Designs Formalize Scenarios Create Verification Models Execute and Create Report Analyze Results RMM Requirement Monitor Models Scenario Models SM Designs Alternative Models DAM VM Verification Models AUTOMATED Task Created Artifact Goal: Enable on-demand verification of designs against requirements using automated model composition at any time during development. AUTOMATED Actor Reports *
98 Challenge We want to verify different design alternatives against sets of requirements using different scenarios. Questions: 1) How to find valid combinations of design alternatives, scenarios and requirements in order to enable an automated composition of verification models? 2) Having found a valid combination: How to bind all components correctly? … Create Verification Models … RMM 1. Verification Model VM DAM SM 2. Verification Model VM … … Requirement Models Scenario Models Designs Alternative Models DAM SM DAM DAM SM SM SM SM SM RMM 1 RMM RMM RMM RMM SM RMM RMM RMM RMM … … n. Verification Model *
99 Composing Verification Models main idea • Collect all scenarios, requirements, import mediators • Generate/compose verification models automatically: • Select the system model to be verified • Find all scenarios that can stimulate the selected system model (i.e., for each mandatory client check whether the binding expression can be inferred) • Find requirements that are implemented in the selected system model (i.e., check whether for each requirement for all mandatory clients binding expressions can be inferred) • Present the list of scenarios and requirements to the user • The user can select only a subset or scenarios or requirements he/she wishes to consider
100 Generating/Composing Verification Models algorithm
101 Simulation and Report Generation in ModelicaML Verification models are simulated. The generated Verification Report is a prepared summary of: • Configuration, bindings • Violations of requirements • etc.
102 Continuous and Discrete Time Locators for Time-related Requirements • A Continuous Time Locator(CTL) specifies one or more time intervals • Time intervals have a duration • They usually have a position in time, but a sliding time window defines any time period of a given duration • A Discrete Time Locator (DTL) defines one or more positions in time and has no duration • An event is associated with a DTL that specifies when the event occurred • The difference between events and DTLs is that a DTL is not an object • That position may be relative to the initialisation of the system or to another DTL time time duration time
103 Time Locators Expressed in Modelica Special FORML-L syntax Standard Modelica syntax duringAny duration duringAny(duration) after event after(event) after event1 untilNext event2 afterUntil(event1, event2) after event for duration afterFor(event, duration) after event within duration afterWithin(event, duration) until event until(event) every duration1 for duration2 everyFor(duration1, duration2) when condition changes Maps to Modelica if
104 From Text to Simulated Requirement – Modelica Extended with new Operators model P2a extends Condition; input ConditionStatus bPSNeeded, sARequired, set1Powered; equation status = if afterWithin (bPSNeeded == notViolated and sARequired == notViolated, 20) then if set1Powered == notViolated then notViolated else violated else undefined; end P2a; BPS.Needed and SA.Required s20 s20 t = 0 time BPS.Needed and SA.Required Set1.Powered must become true within the timeframe s20 and remain true afterwards From a text requirement expressing a condition: A - In the absence of any Backup Power Supply (BPS) component failure or in the presence of a single sensor failure, when the BPS is not under maintenance, in case of loss of MPS, and if safety injection is required, Set1 must be powered within 20 s
105 From Text to Simulated Requirement – Requirement not Violated – OpenModelica Simulation Within 20s BPS Powered Requirement undefined outside the specified time window Requirement validated BPS.Needed and SA.Required s20 t = 0 time t = 10 t = 25 Set1.Powered 3-valued logic prototype: 1 – true 0 – false -1 – undefined
106 Outlook: New OpenModelica Frontend for Large-Scale models • Soon: New OMC Compiler frontend for fast compilation and large- scale models • Been under development the past 2-3 years • Now (sept 24) simulates 67% of MSL models, coverage increases about 6% per month • About 10-200 times faster than the old frontend, depending on model
107 OpenModelica DAEMode for Large-Scale models • Goal – to handle hundreds of thousands to millions of equations • Introduced sparse solvers in the solution chain: • KLU for linear algebraic equations, • Kinsol for nonlinear algebraic equations, and • IDA for causalized differential equations. • Largest system so far: electro-mechanical power system model with about 600.000 differential-algebraic equations • Under development for even larger systems
108 Summary and Questions Hybrid Modeling Visual Acausal Component Modeling Multi-Domain Modeling Typed Declarative Textual Language Thanks for listening! www.modelica.org – Language, Standard Library www.openmodelica.org – Open Source Tool Modelica® is a registered trademark of the Modelica Association

More Related Content

DOC
Diagrama de fases
byAna Perrone
 
PPTX
CIM 2 Modelica
byFrancisco José Gómez López
 
PPTX
CIM to Modelica Factory - Automated Equation-Based Cyber-Physical Power Syste...
byLuigi Vanfretti
 
PDF
Modelica Tutorial with PowerSystems: A tutorial for Modelica simulation
by智哉 今西
 
PPTX
Multi-core Real-time Simulation of High-Fidelity Vehicle Models using Open St...
byModelon
 
PPTX
It‘s Math That Drives Things – Simulink as Simulation and Modeling Environment
byJoachim Schlosser
 
PDF
modelling-and-simulation-made-easy-with-simulink.pdf
byGBBarrios
 
PPTX
Ford Modelon Vehicle Thermal Management 2014
byModelon
 
Diagrama de fases
byAna Perrone
 
CIM 2 Modelica
byFrancisco José Gómez López
 
CIM to Modelica Factory - Automated Equation-Based Cyber-Physical Power Syste...
byLuigi Vanfretti
 
Modelica Tutorial with PowerSystems: A tutorial for Modelica simulation
by智哉 今西
 
Multi-core Real-time Simulation of High-Fidelity Vehicle Models using Open St...
byModelon
 
It‘s Math That Drives Things – Simulink as Simulation and Modeling Environment
byJoachim Schlosser
 
modelling-and-simulation-made-easy-with-simulink.pdf
byGBBarrios
 
Ford Modelon Vehicle Thermal Management 2014
byModelon
 

Similar to Modelica-OpenModelica-slides para aprender.pdf

PPTX
Optimica Compiler Toolkit - Overview
byModelon
 
PDF
learn matlab for ease Lec5
byAmba Research
 
PPTX
Electrification Library - Overview
byModelon
 
PPTX
Mayank dhanariya power point presentation
bymayankdhanariya1234
 
PPTX
Akshat pareek power point presentation on basics
bymayankdhanariya1234
 
DOCX
simulink
byAditi Tiwari
 
PDF
Engineering the software of robotic systems - 1 - Introduction [ICSE 2017 - t...
byIvano Malavolta
 
PPTX
Automated Deployment of Modelica Models in Excel via Functional Mockup Interf...
byModelon
 
PPTX
Electric Power Library - Overview
byModelon
 
PPTX
Innovate with confidence – Functional Verification of Embedded Algorithms
byJoachim Schlosser
 
PDF
ADVANCED WORKSHOP IN MATLAB
bySaeed J. Almalowi,PhD
 
PPTX
10_Matlab Simulink for Electrical Engineering.pptx
byRomanusPeterLyanda
 
DOCX
Internship report
byVanam Bhanu Sai Simha
 
PDF
Fdmu pro step_2010_final
byFraunhofer IGD, Competence Center "Interactive Engineering Technologies"
 
PDF
SLIDES_Electrification__AI_and_the_Future_of_Engineering_Education.pdf.pdf
bySamuelNahum1
 
PPTX
minor project Electric Vehicle for simulation
byshatrughnasamal2
 
PPTX
Power System Simulation: History, State of the Art, and Challenges
byLuigi Vanfretti
 
PPTX
How to use SIMULINK a hands on training.pptx
bydoupeindia1
 
PPTX
College 2 18-2014
byAnand Ronald
 
PPTX
Modeling and Simulation of Electrical Power Systems using OpenIPSL.org and Gr...
byLuigi Vanfretti
 
Optimica Compiler Toolkit - Overview
byModelon
 
learn matlab for ease Lec5
byAmba Research
 
Electrification Library - Overview
byModelon
 
Mayank dhanariya power point presentation
bymayankdhanariya1234
 
Akshat pareek power point presentation on basics
bymayankdhanariya1234
 
simulink
byAditi Tiwari
 
Engineering the software of robotic systems - 1 - Introduction [ICSE 2017 - t...
byIvano Malavolta
 
Automated Deployment of Modelica Models in Excel via Functional Mockup Interf...
byModelon
 
Electric Power Library - Overview
byModelon
 
Innovate with confidence – Functional Verification of Embedded Algorithms
byJoachim Schlosser
 
ADVANCED WORKSHOP IN MATLAB
bySaeed J. Almalowi,PhD
 
10_Matlab Simulink for Electrical Engineering.pptx
byRomanusPeterLyanda
 
Internship report
byVanam Bhanu Sai Simha
 
Fdmu pro step_2010_final
byFraunhofer IGD, Competence Center "Interactive Engineering Technologies"
 
SLIDES_Electrification__AI_and_the_Future_of_Engineering_Education.pdf.pdf
bySamuelNahum1
 
minor project Electric Vehicle for simulation
byshatrughnasamal2
 
Power System Simulation: History, State of the Art, and Challenges
byLuigi Vanfretti
 
How to use SIMULINK a hands on training.pptx
bydoupeindia1
 
College 2 18-2014
byAnand Ronald
 
Modeling and Simulation of Electrical Power Systems using OpenIPSL.org and Gr...
byLuigi Vanfretti
 

More from Carlos Paredes

PPTX
presentacion de emgu para aprender emgu e
byCarlos Paredes
 
PPTX
gato bot propuesta para la enseñanza a distancia
byCarlos Paredes
 
PPTX
Módulo II-ED primera clase de ecuaciones diferenciales.pptx
byCarlos Paredes
 
PPTX
Integral de línea y terema de grenn (1).pptx
byCarlos Paredes
 
PPTX
Módulo II-ED-Clase 21 ecuaciones diferenciales.pptx
byCarlos Paredes
 
PPT
Introduction-to-Unity de la aplicacion.ppt
byCarlos Paredes
 
PPTX
Unity Rutinas para programar en el .pptx
byCarlos Paredes
 
PDF
LISTAS FORMA TE PARTE 2 segunda parte de verbos
byCarlos Paredes
 
PDF
LISTAS FORMA TE PARTE 1 de japones para aprender
byCarlos Paredes
 
PPTX
Algebra lineal para propedeutico enlinea
byCarlos Paredes
 
PPTX
descriptores en identificacion de ellos.pptx
byCarlos Paredes
 
PDF
Machine_Learning_with_MATLAB_Seminar_Latest.pdf
byCarlos Paredes
 
PDF
tecnicas_agrupamiento de datos para analisis
byCarlos Paredes
 
PPTX
Reglas y ejercicios de logica difusa para su comprencion
byCarlos Paredes
 
PPT
Metodo de montecarlo es un mentodo sencillo
byCarlos Paredes
 
PPT
Sistemas Expertos para el conocimieto de los mismos
byCarlos Paredes
 
PDF
Definición de simulación.pdf
byCarlos Paredes
 
PDF
Squim .pdf
byCarlos Paredes
 
PPTX
Módulo III CVV clase 1(resuelto).pptx
byCarlos Paredes
 
PDF
MAS1.pdf
byCarlos Paredes
 
presentacion de emgu para aprender emgu e
byCarlos Paredes
 
gato bot propuesta para la enseñanza a distancia
byCarlos Paredes
 
Módulo II-ED primera clase de ecuaciones diferenciales.pptx
byCarlos Paredes
 
Integral de línea y terema de grenn (1).pptx
byCarlos Paredes
 
Módulo II-ED-Clase 21 ecuaciones diferenciales.pptx
byCarlos Paredes
 
Introduction-to-Unity de la aplicacion.ppt
byCarlos Paredes
 
Unity Rutinas para programar en el .pptx
byCarlos Paredes
 
LISTAS FORMA TE PARTE 2 segunda parte de verbos
byCarlos Paredes
 
LISTAS FORMA TE PARTE 1 de japones para aprender
byCarlos Paredes
 
Algebra lineal para propedeutico enlinea
byCarlos Paredes
 
descriptores en identificacion de ellos.pptx
byCarlos Paredes
 
Machine_Learning_with_MATLAB_Seminar_Latest.pdf
byCarlos Paredes
 
tecnicas_agrupamiento de datos para analisis
byCarlos Paredes
 
Reglas y ejercicios de logica difusa para su comprencion
byCarlos Paredes
 
Metodo de montecarlo es un mentodo sencillo
byCarlos Paredes
 
Sistemas Expertos para el conocimieto de los mismos
byCarlos Paredes
 
Definición de simulación.pdf
byCarlos Paredes
 
Squim .pdf
byCarlos Paredes
 
Módulo III CVV clase 1(resuelto).pptx
byCarlos Paredes
 
MAS1.pdf
byCarlos Paredes
 

Recently uploaded

PPTX
EMR Software for Pulmonology Clinics Why EasyClinic Supports Accuracy, Contin...
byEasy Clinic
 
PDF
DSD-INT 2025 Groundwater table lowering due to surface water lowering - Reusen
byDeltares
 
PDF
Latest Courier Management Software 2026 | Complete Courier & Logistics Solution
byCourier Softwares
 
PPTX
Architectural Styles in Software Engineering
byM Munim
 
PPTX
Build Smarter with Google: A Workshop on MediaPipe, Firebase, Gemini and Anti...
byvanshikaprakash05
 
PDF
DSD-INT 2025 Large scale unsaturated zone modelling - Sequential Steady State...
byDeltares
 
PPTX
Free AI Paraphrasing Tool to Rewrite Sentences – SENTENCIFY
bySENTENCIFY
 
PDF
DSD-INT 2025 iMOD Parallel coupler development plan - Verkaik
byDeltares
 
PPTX
Testing Strategies for Agile Teams in 2026
byMatt Calder
 
PDF
Problem Solving_20241203_220045_0000.pdf
bythakurayush00991
 
PDF
Cloud Engineering Services | Infysion Technologies
bysolutioninginfysion
 
PPTX
UAE-Based Insurer Transforms Operations with InsureEdge
byInsurance Tech Services
 
PPTX
Aviation Fleet Management Software for Airlines & Operators
bySISGAIN
 
PPTX
Project System Presentation details process presentation
bytejpratappandey4
 
PDF
Hack&Verse Kick-off and infor session Event ppt
bysanidhyasahu1120
 
PDF
Inside An AI Powered ERP System for Process Manufacturers
byBatchMaster Software Pvt. Ltd.
 
PDF
CodeFulcrum Company Profile - Engineering Scalable Software for High-Growth E...
byCodeFulcrum
 
PDF
our environment ppt made by many people name rarang yadav
byrarang180
 
PPTX
Lect 1 Number systems and base conversions. [Autosaved].pptx
byzainiman8511
 
PDF
Python Core Interview Cheat Sheet for a Senior Interview
byStanislav Lazarenko
 
EMR Software for Pulmonology Clinics Why EasyClinic Supports Accuracy, Contin...
byEasy Clinic
 
DSD-INT 2025 Groundwater table lowering due to surface water lowering - Reusen
byDeltares
 
Latest Courier Management Software 2026 | Complete Courier & Logistics Solution
byCourier Softwares
 
Architectural Styles in Software Engineering
byM Munim
 
Build Smarter with Google: A Workshop on MediaPipe, Firebase, Gemini and Anti...
byvanshikaprakash05
 
DSD-INT 2025 Large scale unsaturated zone modelling - Sequential Steady State...
byDeltares
 
Free AI Paraphrasing Tool to Rewrite Sentences – SENTENCIFY
bySENTENCIFY
 
DSD-INT 2025 iMOD Parallel coupler development plan - Verkaik
byDeltares
 
Testing Strategies for Agile Teams in 2026
byMatt Calder
 
Problem Solving_20241203_220045_0000.pdf
bythakurayush00991
 
Cloud Engineering Services | Infysion Technologies
bysolutioninginfysion
 
UAE-Based Insurer Transforms Operations with InsureEdge
byInsurance Tech Services
 
Aviation Fleet Management Software for Airlines & Operators
bySISGAIN
 
Project System Presentation details process presentation
bytejpratappandey4
 
Hack&Verse Kick-off and infor session Event ppt
bysanidhyasahu1120
 
Inside An AI Powered ERP System for Process Manufacturers
byBatchMaster Software Pvt. Ltd.
 
CodeFulcrum Company Profile - Engineering Scalable Software for High-Growth E...
byCodeFulcrum
 
our environment ppt made by many people name rarang yadav
byrarang180
 
Lect 1 Number systems and base conversions. [Autosaved].pptx
byzainiman8511
 
Python Core Interview Cheat Sheet for a Senior Interview
byStanislav Lazarenko
 

Modelica-OpenModelica-slides para aprender.pdf

  • 1.
    Presentation at RISE SICSEast, Sweden October 6, 2018 Peter Fritzson peter.fritzson@liu.se Full Professor at Linköping University Director Open Source Modelica Consortium Vice Chairman of Modelica Association Director of the MODPROD Center for model-based development Modeling, Simulation, and Development of Cyber- Physical Systems with OpenModelica and FMI
  • 2.
    2 Industrial Challenges forComplex Cyber-Physical System Products of both Software and Hardware • Increased Software Fraction • Shorter Time-to-Market • Higher demands on effective strategic decision making • Cyber-Physical (CPS) – Cyber (software) Physical (hardware) products
  • 3.
    3 Peter Fritzson Principles ofObject Oriented Modeling and Simulation with Modelica 3.3 A Cyber-Physical Approach Can be ordered from Wiley or Amazon Wiley-IEEE Press, 2014, 1250 pages • OpenModelica • www.openmodelica.org • Modelica Association • www.modelica.org Big Book on Modelica and Technology, Dec 2014 Download Free OpenModelica Software
  • 4.
    4 September 2011 232 pages Translations availablein Chinese, Japanese, Spanish Wiley IEEE Press For Introductory Short Courses on Object Oriented Mathematical Modeling Introductory Modelica Book
  • 5.
  • 6.
    6 Modelica Background: StoredKnowledge Model knowledge is stored in books and human minds which computers cannot access “The change of motion is proportional to the motive force impressed “ – Newton
  • 7.
    7 Modelica Background: TheForm – Equations • Equations were used in the third millennium B.C. • Equality sign was introduced by Robert Recorde in 1557 Newton still wrote text (Principia, vol. 1, 1686) “The change of motion is proportional to the motive force impressed ” CSSL (1967) introduced a special form of “equation”: variable = expression v = INTEG(F)/m Programming languages usually do not allow equations!
  • 8.
    8 What is Modelica? •Robotics • Automotive • Aircrafts • Satellites • Power plants • Systems biology A language for modeling of complex cyber-physical systems
  • 9.
    9 What is Modelica? Alanguage for modeling of complex cyber-physical systems Primary designed for simulation, but there are also other usages of models, e.g. optimization.
  • 10.
    10 What is Modelica? Alanguage for modeling of complex cyber-physical systems i.e., Modelica is not a tool Free, open language specification: There exist several free and commercial tools, for example: • OpenModelica from OSMC • Dymola from Dassault systems • Wolfram System Modeler fr Wolfram MathCore • SimulationX from ITI – ESI Group • MapleSim from MapleSoft • AMESIM from LMS • JModelica.org from Modelon • MWORKS from Tongyang Sw & Control • IDA Simulation Env, from Equa Available at: www.modelica.org Developed and standardized by Modelica Association
  • 11.
    11 Declarative language Equations andmathematical functions allow acausal modeling, high level specification, increased correctness Multi-domain modeling Combine electrical, mechanical, thermodynamic, hydraulic, biological, control, event, real-time, etc... Everything is a class Strongly typed object-oriented language with a general class concept, Java & MATLAB-like syntax Visual component programming Hierarchical system architecture capabilities Efficient, non-proprietary Efficiency comparable to C; advanced equation compilation, e.g. 300 000 equations, ~150 000 lines on standard PC Modelica – The Next Generation Modeling Language
  • 12.
    12 What is acausalmodeling/design? Why does it increase reuse? The acausality makes Modelica library classes more reusable than traditional classes containing assignment statements where the input-output causality is fixed. Example: a resistor equation: R*i = v; can be used in three ways: i := v/R; v := R*i; R := v/i; Modelica Acausal Modeling
  • 13.
    13 What is Specialabout Modelica? • Multi-Domain Modeling • Visual acausal hierarchical component modeling • Typed declarative equation-based textual language • Hybrid modeling and simulation
  • 14.
    14 What is Specialabout Modelica? Multi-Domain Modeling Cyber-Physical Modeling Physical Cyber 3 domains - electric - mechanics - control
  • 15.
    15 What is Specialabout Modelica? Multi-Domain Modeling Acausal model (Modelica) Causal block-based model (Simulink) Keeps the physical structure Visual Acausal Hierarchical Component Modeling
  • 16.
    16 inertial x y axis1 axis2 axis3 axis4 axis5 axis6 r3Drive1 1 r3Motor r3Control qdRef 1 S qRef 1 S k2 i k1 i qddRef cut joint l qd tn Jmotor=J gear=i spring=c fric=Rv0 S rel joint=0 S Vs - + diff - + power emf La=(250/(2*D*wm)) Ra=250 Rd2=100 C=0.004*D/w m - + OpI Rd1=100 Ri=10 Rp1=200 Rp2=50 Rd4=100 hall2 Rd3=100 g1 g2 g3 hall1 g4 g5 r w qd q rate2 b(s) a(s) rate3 340.8 S rate1 b(s) a(s) tacho1 PT1 Kd 0.03 w Sum - sum +1 +1 pSum - Kv 0.3 tacho2 b(s) a(s) q qd iRef qRef qdRef What is Special about Modelica? Visual Acausal Hierarchical Component Modeling Multi-Domain Modeling Hierarchical system modeling Courtesy of Martin Otter Srel = n*transpose(n)+(identity(3)- n*transpose(n))*cos(q)- skew(n)*sin(q); wrela = n*qd; zrela = n*qdd; Sb = Sa*transpose(Srel); r0b = r0a; vb = Srel*va; wb = Srel*(wa + wrela); ab = Srel*aa; zb = Srel*(za + zrela + cross(wa, wrela));
  • 17.
    17 What is Specialabout Modelica? Multi-Domain Modeling Typed Declarative Equation-based Textual Language A textual class-based language OO primary used for as a structuring concept Behaviour described declaratively using • Differential algebraic equations (DAE) (continuous-time) • Event triggers (discrete-time) class VanDerPol "Van der Pol oscillator model" Real x(start = 1) "Descriptive string for x”; Real y(start = 1) "y coordinate”; parameter Real lambda = 0.3; equation der(x) = y; der(y) = -x + lambda*(1 - x*x)*y; end VanDerPol; Differential equations Variable declarations Visual Acausal Hierarchical Component Modeling
  • 18.
    18 What is Specialabout Modelica? Hybrid Modeling Visual Acausal Component Modeling Multi-Domain Modeling Typed Declarative Equation-based Textual Language time Continuous-time Discrete-time Hybrid modeling = continuous-time + discrete-time modeling Clocked discrete-time
  • 19.
    19 Modelica vs SimulinkBlock Oriented Modeling Simple Electrical Model R1=10 C=0.01 L=0.1 R2=100 G AC=220 p n p p p p p n n n n -1 1 sum3 +1 -1 sum1 +1 +1 sum2 1 s l2 1 s l1 sinln 1/R1 Res1 1/C Cap 1/L Ind R2 Res2 Modelica: Physical model – easy to understand Simulink: Signal-flow model – hard to understand Keeps the physical structure
  • 20.
    20 OpenModelica Tool GraphicalEditor and Plotting Graphical Modeling Using Drag and Drop
  • 21.
    21 Graphical Modeling withOpenModelica Environment
  • 22.
    22 • A DCmotor can be thought of as an electrical circuit which also contains an electromechanical component model DCMotor Resistor R(R=100); Inductor L(L=100); VsourceDC DC(f=10); Ground G; ElectroMechanicalElement EM(k=10,J=10, b=2); Inertia load; equation connect(DC.p,R.n); connect(R.p,L.n); connect(L.p, EM.n); connect(EM.p, DC.n); connect(DC.n,G.p); connect(EM.flange,load.flange); end DCMotor load EM DC G R L Multi-Domain (Electro-Mechanical) Modelica Model
  • 23.
    23 Automatic transformation toODE or DAE for simulation: (load component not included) Corresponding DCMotor Model Equations The following equations are automatically derived from the Modelica model:
  • 24.
    24 Model Translation Processto Hybrid DAE to Code Modelica Model Flat model Hybrid DAE Sorted equations C Code Executable Optimized sorted equations Modelica Model Modelica Graphical Editor Modelica Source code Translator Analyzer Optimizer Code generator C Compiler Simulation Modelica Textual Editor Frontend Backend "Middle-end" Modeling Environment
  • 25.
    25 Brief Modelica History •First Modelica design group meeting in fall 1996 • International group of people with expert knowledge in both language design and physical modeling • Industry and academia • Modelica Versions • 1.0 released September 1997 • 2.0 released March 2002 • 2.2 released March 2005 • 3.0 released September 2007 • 3.1 released May 2009 • 3.2 released March 2010 • 3.3 released May 2012 • 3.2 rev 2 released November 2013 • 3.3 rev 1 released July 2014 • 3.4 released May 2017 • Modelica Association established 2000 in Linköping • Open, non-profit organization
  • 26.
    26 Modelica in PowerGeneration GTX Gas Turbine Power Cutoff Mechanism Hello Courtesy of Siemens Industrial Turbomachinery AB Developed by MathCore for Siemens
  • 27.
  • 28.
  • 29.
    29 Application of Modelicain Robotics Models Real-time Training Simulator for Flight, Driving Courtesy of Tobias Bellmann, DLR, Oberphaffenhofen, Germany • Using Modelica models generating real-time code • Different simulation environments (e.g. Flight, Car Driving, Helicopter) • Developed at DLR Munich, Germany • Dymola Modelica tool
  • 30.
    30 Large Robotic FlightSimulator (Demo)
  • 31.
    31 • GT unit,ST unit, Drum boilers unit and HRSG units, connected by thermo-fluid ports and by signal buses • Low-temperature parts (condenser, feedwater system, LP circuits) are represented by trivial boundary conditions. • GT model: simple law relating the electrical load request with the exhaust gas temperature and flow rate. Combined-Cycle Power Plant Plant model – system level Courtesy Francesco Casella, Politecnico di Milano – Italy and Francesco Pretolani, CESI SpA - Italy
  • 32.
    32 Attitude control forsatellites using magnetic coils as actuators Torque generation mechanism: interaction between coils and geomagnetic field Formation flying on elliptical orbits Control the relative motion of two or more spacecraft Modelica Spacecraft Dynamics Library Courtesy of Francesco Casella, Politecnico di Milano, Italy
  • 33.
    33 Biggest Immediate Challengefor Humanity – Create a Sustainable Society – Avoid Global Collapse in 50 Years World System Dynamics Simulation with OpenModelica – World3 model, Meadows et al Sustainable, Scenario 9 4% improvement per year Collapse ca 2070, Scenario 2 Close to current developments Climate change, pollution, desertification, etc. www.openmodelica.org Download software from World population Year
  • 34.
    34 World3 Model inModelica, Meadows et al, Cellier Comprehensive model – 13 areas • Population dynamics • Human fertility • Human ecological footprint • Pollution dynamics • Industrial investment • Human welfare • Arable land • Labor utilization • Life expectancy • Food production • Land fertility • Non-recover resource • Service sector
  • 35.
    35 Each Year NewRecord for Global Mean Temperature This is February 2016
  • 36.
    36 World3 Simulations withDifferent Start Years for Sustainable Policies – Collapse if starting too late
  • 37.
  • 38.
    How the worldcould be in 80-100 years at a global warming of 4 degrees See level rise 2 m flooding coastal cities Uninhabitable New Scientist, 28 february 2009 IPCC, business as usual scenario www.climate-lab-book.ac.uk www.atmosfair.de References Cities, agriculture Uninhabitable desert Uninhabitable due to extreme weather Flooded Business-as-usual scenario, IPCC Massive migration to to northern Europe, Russia, and Canada Example Emissions CO2e / person - Earth can handle 2 ton/yr - Flight Spain – 1 ton - Flight Canaryisl – 2 ton - Flight Thailand – 4 ton
  • 39.
    39 Year 1750‐2000: • Meantemperature north hemisphere, • Population, • CO2‐concentration, • BNP, • Loss av rain forest, • Water usage • Paper consumption, • Exterminated species • Oil consumtion, • Motor vehicles • Destroyed fish populations • Destruction of ozon layer • Foreign investments A Unique Point in History – Exponential Trends Approaches Planet Earth Boundaries
  • 40.
    40 Need Smart Systemsto Support a Circular Economy for a Sustainable Society • Circular management of products, material, throughout the life-cycle • Optimize manufacturing and usage over the entire life cycle
  • 41.
    41 What Can YouDo? Need Global Sustainability Mass Movement • Develop smart Cyber-Physical systems for reduced energy and material footprint • Model-based circular economy for re-use of products and materials • Promote sustainable lifestyle and technology • Install electric solar PV panels • Buy shares in cooperative wind power 20 sqm solar panels on garage roof, Nov 2012 Generated 2700 W at noon March 10, 2013 Expanded to 93 sqm, 12 kW, March 2013 House produced 11600 kwh, used 9500 kwh Avoids 10 ton CO2 emission per year
  • 42.
    42 Example Electric Cars Canbe charged by electricity from own solar panels Renault ZOE; 5 seat; Range: 22kw (2014) vs 41 kw battery (2017) • Realistic Swedish drive cycle: • Summer: 165 km, now 300 km • Winter: 110 km, now 200 km Cheap fast AC chargers (22kw, 43kw) Tesla model S range 480 km DLR ROboMObil • experimental electric car • Modelica models
  • 43.
    43 What Can YouDo? More Train Travel – Less Air Travel • Air travel by Swedish Citizens – about the same emissions as all personal car traffic in Sweden! • By train from Linköping to Munich and back – saves almost 1 ton of CO2e emissions compared to flight • Leave Linköping 07.00 in Munich 23.14 More Examples, PF travel 2016: • Train Linköping-Paris, Dec 3- 6, EU project meeting • Train Linköping-Dresden, Dec 10-16, 1 week workshop Train travel Linköping - Munich
  • 44.
    44 Small rectangles –surface needed for 100% solar energy for humanity
  • 45.
    45 Part II Introduction tothe OpenModelica Environment
  • 46.
  • 47.
    47 OpenModelica – FreeOpen Source Tool Developed by the Open Source Modelica Consortium (OSMC) • Graphical editor • Model compiler and simulator • Debugger • Performance analyzer • Dynamic optimizer • Symbolic modeling • Parallelization • Electronic Notebook and OMWebbook for teaching • Spokentutorial for teaching EngineV6 11116 equation model
  • 48.
    48 • Advanced InteractiveModelica compiler (OMC) • Supports most of the Modelica Language • Modelica and Python scripting • Basic environment for creating models • OMShell – an interactive command handler • OMNotebook – a literate programming notebook • MDT – an advanced textual environment in Eclipse 48 • OMEdit graphic Editor • OMDebugger for equations • OMOptim optimization tool • OM Dynamic optimizer collocation • ModelicaML UML Profile • MetaModelica extension • ParModelica extension • OMSimulator – FMI/TLM simulator The OpenModelica Open Source Environment www.openmodelica.org new
  • 49.
    49 The OpenModelica ToolArchitecture Simulation Execution OMEdit Graphic and Textual Model Editor OMNotebook Interactive Notebooks Debugger OMC Interactive Compiler Server ModelicaML UML/Modelica and requirement verification MDT Eclipse Plugin OMOptim Optimization 3D Visualization OMShell Modelica Scripting OMPython Python Scripting OMSimulator FMI Simulation OMJulia Julia Scripting OMWebbook Interactive Notebooks OMMatlab Matlab Scripting OMSens sensitivity analysis OMSysident
  • 50.
    50 Industrial members • ABBAB, Sweden • Berger IT-Cosmos, Germany • Bosch Rexroth AG, Germany • Brainheart Energy AB, Sweden • CDAC Centre, Kerala, India • Creative Connections, Prague • DHI, Aarhus, Denmark • Dynamica s.r.l., Cremona, Italy • EDF, Paris, France • Equa Simulation AB, Sweden • Fraunhofer IWES, Bremerhaven • INRIA, Rennes, France • ISID Dentsu, Tokyo, Japan Open-source community services • Website and Support Forum • Version-controlled source base • Bug database • Development courses • www.openmodelica.org Code Statistics • FH Bielefeld, Bielefeld, Germany • University of Bolivar, Colombia • TU Braunschweig, Germany • University of Calabria, Italy • Univ California, Berkeley, USA • Chalmers Univ, Control,Sweden • Chalmers Univ, Machine, Sweden • TU Darmstadt, Germany • TU Delft, The Netherlands • TU Dresden, Germany • Université Laval, Canada • Georgia Inst of Technology, USA • Ghent University, Belgium • Halmstad University, Sweden University members OSMC – International Consortium for Open Source Model-based Development Tools, 53 members Febr 2018 Founded Dec 4, 2007 • Maplesoft, Canada • RTE France, Paris, France • Saab AB, Linköping, Sweden • Scilab Enterprises, France • SKF, Göteborg, Sweden • TLK Thermo, Germany • Siemens Turbo, Sweden • Sozhou Tongyuan, China • Talent Swarm, Spain • VTI, Linköping, Sweden • VTT, Finland • Wolfram MathCore, Sweden • Heidelberg University, Germany •TU Hamburg/Harburg Germany • IIT Bombay, Mumbai, India • KTH, Stockholm, Sweden • Linköping University, Sweden • Univ of Maryland, Syst Eng USA • Univ of Maryland, CEEE, USA • Politecnico di Milano, Italy • Ecoles des Mines, CEP, France • Mälardalen University, Sweden • Univ Pisa, Italy • Univ College SouthEast Norway • Tsinghua Univ, Beijing, China • Vanderbilt Univ, USA
  • 51.
  • 52.
    52 OpenModelica Simulation inWeb Browser Client OpenModelica compiles to efficient Java Script code which is executed in web browser MultiBody RobotR3.FullRobot
  • 53.
    53 Spoken-Tutorial step-by-step OpenModelicaand Modelica Tutorial Using OMEdit. Link from www.openmodelica.org 1,600,000 1,400,000 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 2,011 2,012 2,013 2,014 2,015 2,016 Number of students/teachers trained in their colleges/schools
  • 54.
    54 OMnotebook Interactive ElectronicNotebook Here Used for Teaching Control Theory
  • 55.
    55 OM Web NotebookGenerated from OMNotebook Edit, Simulate, Plot Models on a Web Page http://omwebbook.openmodelica.org/ OMweb book OMNote book
  • 56.
    56 OMPython – PythonScripting with OpenModelica • Interpretation of Modelica commands and expressions • Interactive Session handling • Library / Tool • Optimized Parser results • Helper functions • Deployable, Extensible and Distributable
  • 57.
    57 General Tool Interoperability& Model Exchange Functional Mock-up Interface (FMI) • FMI development was started by ITEA2 MODELISAR project. FMI is a Modelica Association Project now • Version 1.0 • FMI for Model Exchange (released Jan 26,2010) • FMI for Co-Simulation (released Oct 12,2010) • Version 2.0 • FMI for Model Exchange and Co-Simulation (released July 25,2014) • > 80 tools supporting it (https://www.fmi-standard.org/tools) Engine with ECU Gearbox with ECU Thermal systems Automated cargo door Chassis components, roadway, ECU (e.g. ESP) etc. functional mockup interface for model exchange and tool coupling courtesy Daimler
  • 58.
    58 Functional Mockup Units •Import and export of input/output blocks – Functional Mock-Up Units – FMUs, described by • differential-, algebraic-, discrete equations, • with time-, state, and step-events • An FMU consists of (compiled) C-code, + interface description in XML • An FMU can be large (e.g. 100 000 variables) • An FMU can be used in an embedded system (small overhead) • FMUs can be connected together
  • 59.
  • 60.
    60 OMSimulator Composite ModelEditor with 3D Viewer Combine External (FMI) Models into New Models • Composite model editor with 3D visualization of connected mechanical model components which can be FMUs, Modelica models, etc., or co-simulated components • 3D animation possible • Composite model saved as XML-file
  • 61.
    61 OMSimulator – IntegratedFMI and TLM-based Cosimulator/Simulator in OpenModelica OMSimulator Integrated TLM & FMI libOMSimulator Simulink wrapper Beast wrapper ADAMS wrapper TLM component C-API interface OMEdit Papyrus Scripting … OMC FMI component FMI component FMI FMU Modelica model Composite FMI component
  • 62.
    62 Embedded System Supportin OpenModelica • Code generation of real-time Controllers from Modelica models for small foot-print platforms
  • 63.
    63 Single board heatingsystem (IIT Bombay) • Use for teaching basic control theory • Usually controlled by serial port (set fan value, read temperature, etc) • OpenModelica can generate code targeting the ATmega16 on the board (AVR-ISP programmer in the lower left). Program size is 4090 bytes including LCD driver and PID-controller (out of 16 kB flash memory available). Use Case: SBHS (Single Board Heating System) Movie Demo!
  • 64.
    64 Example – CodeGeneration to SHBS
  • 65.
    65 Code Generator Comparison,Full vs Simple Full Source-code FMU targeting 8-bit AVR proc Simple code generator targeting 8-bit AVR proc Hello World (0 equations) 43 kB flash memory 23 kB variables (RAM) 130 B flash memory 0 B variables (RAM) SBHS Board (real-time PID controller, LCD, etc) 68 kB flash memory 25 kB variables (RAM) 4090 B flash memory 151 B variables (RAM) The largest 8-bit AVR processor MCUs (Micro Controller Units) have 16 kB SRAM. One of the more (ATmega328p; Arduino Uno) has 2 kB SRAM. The ATmega16 we target has 1 kB SRAM available (stack, heap, and global variable
  • 66.
    66 • Free libraryfor interfacing hardware drivers • Cross-platform (Windows and Linux) • UDP , SharedMemory, CAN, Keyboard, Joystick/Gamepad • DAQ cards for digital and analog IO (only Linux) • Developed for interactive real- time simulations Communication & I/O Devices: MODELICA_DEVICEDRIVERS Library
  • 67.
    67 OMEdit 3D Visualizationof Multi-Body Systems • Built-in feature of OMEdit to animate MSL-Multi-Body shapes • Visualization of simulation results • Animation of geometric primitives and CAD-Files New Animation Window Simulate with Animation
  • 68.
  • 69.
    69 OpenModelica 3D AnimationDemo – Excavator
  • 70.
    70 Visualization using Third-PartyLibraries: DLR Visualization Library • Advanced, model-integrated and vendor-unspecific visualization tool for Modelica models • Offline, online and real-time animation • Video-export function • Commercial library, feature reduced free Community Edition exists Courtesy of Dr. Tobias Bellmann (DLR)
  • 71.
    71 Problems Solved problems Resultplot Export result data .csv OMOptim – Parameter Sweep Design Optimization Here Pareto front optimiza- tion
  • 72.
    72 Optimization of DynamicTrajectories Using Multiple-Shooting and Collocation • Minimize a goal function subject to model equation constraints, useful e.g. for NMPC • Multiple Shooting/Collocation • Solve sub-problem in each sub-interval 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 1 2 4 8 16 MULTIPLE_COLLOCATION ipopt [scaled] jac_g [scaled] Example speedup, 16 cores: In OpenModelica 1.9.1 beta release Jan 2014.
  • 73.
  • 74.
    74 Failure Mode andEffects Analysis (FMEA) in OM • Modelica models augmented with reliability properties can be used to generate reliability models in Figaro, which in turn can be used for static reliability analysis • Prototype in OpenModelica integrated with Figaro tool Modelica Library Application Modelica model Simulation Figaro Reliability Library Reliability model in Figaro FT generation FT processing Automated generation
  • 75.
    75 OpenModelica Model Parallelization FasterSimulation on Multi-Core Automated parallelization of models Parallelizing numeric Jacobian computations in simulation 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 1 2 3 4 6 8 10 12 14 Speedup ScalableTestSuite N=39 nnz= 818 Sp… number of threads Speedup about 4 using 8 threads
  • 76.
    76 Recent Large-scale ABBOpenModelica Application Generate code for controlling 7.5 to 10% of German Power Production ABB OPTIMAX PowerFit • Real-time optimizing control of large- scale virtual power plant for system integration • Software including OpenModelica now used in managing more than 2500 renewable plants, total up to 1.5 GW High scalability supporting growth • 2012: initial delivery (for 50 plants) • 2013: SW extension (500 plants) • 2014: HW+SW extension (> 2000) • 2015: HW+SW extension, incl. OpenModelica generating optimizing controller code in FMI 2.0 form Manage 7.5% - 10% of German Power • 2015, Aug: OpenModelica Exports FMUs for real-time optimizing control (seconds) of about 5.000 MW (7.5%) of power in Germany
  • 77.
    77 Part III Equation-Based ModelDynamic Debugging and Performance Analysis
  • 78.
    78 Need for DebuggingTools Map Low vs High Abstraction Level • A major part of the total cost of software projects is due to testing and debugging • US-Study 2002: Software errors cost the US economy annually~ 60 Billion $ • Problem: Large Gap in Abstraction Level from Equations to Executable Code • Example error message (hard to understand) Error solving nonlinear system 132 time = 0.002 residual[0] = 0.288956 x[0] = 1.105149 residual[1] = 17.000400 x[1] = 1.248448 ...
  • 79.
    79 OpenModelica Equation ModelDebugger 0 = y + der(x * time * z); z = 1.0; (1) substitution: y + der(x * (time * z)) => y + der(x * (time * 1.0)) (2) simplify: y + der(x * (time * 1.0)) => y + der(x * time) (3) expand derivative (symbolic diff): y + der(x * time) =>y + (x + der(x) * time) (4) solve: 0.0 = y + (x + der(x) * time) => der(x) = ((-y) - x) / time time <> 0 Example of equation transformations on a model:
  • 80.
    80 Mapping dynamic run-timeerror to source model position Integrated Static-Dynamic OpenModelica Equation Model Debugger Showing equation transfor mations of a model: Efficient handling of Large Equation Systems
  • 81.
    81 Transformations Browser –EngineV6 Overview (11 116 equations in model)
  • 82.
    82 Performance Profiling (Here: Profilingall equations in MSL 3.2.1 DoublePendulum)
  • 83.
    83 • ABB OPTIMAX®provides advanced model based control products for power generation and water utilities. • ABB: “OpenModelica provides outstanding debugging features that help to save a lot of time during model development.” ABB Commercial Application Use of Debugger
  • 84.
    84 Equation Model Debuggingon Siemens Model (used on Siemens Evaporator test model, 1100 equations) 84
  • 85.
    85 Equation Model Debuggeron Siemens Model (Siemens Evaporator test model, 1100 equations) Pointing out the buggy equation y = u1/u2; that gives division by zero
  • 86.
    86 Performance Profiling forfaster Simulation (Here: Profiling equations of Siemens Drum boiler model with evaporator • Measuring performance of equation blocks to find bottlenecks • Useful as input before model simplification for real-time applications • Integrated with the debugger to point out the slow equations • Suitable for real-time profiling (collect less information), or a complete view of all equation blocks and function calls Conclusion from the evaluation: “…the profiler makes the process of performance optimization radically shorter.”
  • 87.
    87 Part IV Dynamic Verification/Testingof Requirements vs Usage Scenario Models Wladimir Schamai, Lena Buffoni, Peter Fritzson and contributions from MODRIO partners
  • 88.
    88 OpenModelica and PapyrusBased Model-Based Development Environment to Cover Product-Design V Product models Requirements models Unified Modeling: Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models Specification Design Design Refinement Component verification Subsystem level integration and verification Subsystem level integration test calibration and verification Product verification and deployment Maintenance Realization Detailed feature design and implementation Architectural design and system functional design Preliminary feature design System requirements Level of Abstraction Documentation, Version and Configuration Management Verification Integration Calibration Experience Feedback
  • 89.
    89 Business Process Controland Modeling Product models Requirements models Unified Modeling: Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models Metso Business model & simulation VTT Simantics Graphic Modeling Too OpenModelica based simulation Simulation of 3 strategies with outcomes VTT Simantics Business process modeler OpenModelica compiler & simulator
  • 90.
    90 Requirement Capture Product models Requirements models Unified Modeling:Meta -modeling& Modelica& UML& OWL Business Process Control Requirements Capture Model -Driven Design (PIM) Compilat ion & Code Gen (PSM) System Simulation Software & Syst Product Feedback Platform models Process models Product models Requirements models Unified Modeling: Meta -modeling& Modelica&UML Business Process Control Requirements Capture Model - Driven Design Compilation & Code Gen System Simulation Software & System Product Platform models Process models OpenModelica based simulation vVDR (virtual Verification of Designs against Requirements) in ModelicaML UML/Modelica Profile, part of OpenModelica Design Model Scenario Model Requirement Models Verification Model Binding Provider from design model Client from requirement model
  • 91.
    91 OpenModelica – ModelicaMLUML Profile Based on Open-Source Papyrus UML and OpenModelica • ModelicaML is a UML Profile for SW/HW modeling • Applicable to “pure” UML or to other UML profiles, e.g. SysML • Standardized Mapping UML/SysML to Modelica • Defines transformation/mapping for executable models • Being standardized by OMG • ModelicaML • Defines graphical concrete syntax (graphical notation for diagram) for representing Modelica constructs integrated with UML • Includes graphical formalisms (e.g. State Machines, Activities, Requirements) • Which do not yet exist in Modelica language (extension work ongoing) • Which are translated into executable Modelica code • Is defined towards generation of executable Modelica code • Current implementation based on the Papyrus UML tool + OpenModelica
  • 92.
    92 Example: Simulation andRequirements Evaluation Req. 001 is instantiated 2 times (there are 2 tanks in the system) tank-height is 0.6m Req. 001 for the tank2 is violated Req. 001 for the tank1 is not violated
  • 93.
  • 94.
    94 Example: Representation ofSystem Structure Interconnections Inheritance Components
  • 95.
    95 Example: Representation ofSystem Behavior State Machine of the Tank State Machine of the Controller Conditional Algorithm (Activity Diagram)
  • 96.
    96 Example: Representation ofSystem Requirements Textual Requirement Formalized Requirement
  • 97.
    97 vVDR Method – virtualVerification of Designs vs Requirements Formalize Requirements Formalize Designs Formalize Scenarios Create Verification Models Execute and Create Report Analyze Results RMM Requirement Monitor Models Scenario Models SM Designs Alternative Models DAM VM Verification Models AUTOMATED Task Created Artifact Goal: Enable on-demand verification of designs against requirements using automated model composition at any time during development. AUTOMATED Actor Reports *
  • 98.
    98 Challenge We want toverify different design alternatives against sets of requirements using different scenarios. Questions: 1) How to find valid combinations of design alternatives, scenarios and requirements in order to enable an automated composition of verification models? 2) Having found a valid combination: How to bind all components correctly? … Create Verification Models … RMM 1. Verification Model VM DAM SM 2. Verification Model VM … … Requirement Models Scenario Models Designs Alternative Models DAM SM DAM DAM SM SM SM SM SM RMM 1 RMM RMM RMM RMM SM RMM RMM RMM RMM … … n. Verification Model *
  • 99.
    99 Composing Verification Models mainidea • Collect all scenarios, requirements, import mediators • Generate/compose verification models automatically: • Select the system model to be verified • Find all scenarios that can stimulate the selected system model (i.e., for each mandatory client check whether the binding expression can be inferred) • Find requirements that are implemented in the selected system model (i.e., check whether for each requirement for all mandatory clients binding expressions can be inferred) • Present the list of scenarios and requirements to the user • The user can select only a subset or scenarios or requirements he/she wishes to consider
  • 100.
  • 101.
    101 Simulation and ReportGeneration in ModelicaML Verification models are simulated. The generated Verification Report is a prepared summary of: • Configuration, bindings • Violations of requirements • etc.
  • 102.
    102 Continuous and DiscreteTime Locators for Time-related Requirements • A Continuous Time Locator(CTL) specifies one or more time intervals • Time intervals have a duration • They usually have a position in time, but a sliding time window defines any time period of a given duration • A Discrete Time Locator (DTL) defines one or more positions in time and has no duration • An event is associated with a DTL that specifies when the event occurred • The difference between events and DTLs is that a DTL is not an object • That position may be relative to the initialisation of the system or to another DTL time time duration time
  • 103.
    103 Time Locators Expressedin Modelica Special FORML-L syntax Standard Modelica syntax duringAny duration duringAny(duration) after event after(event) after event1 untilNext event2 afterUntil(event1, event2) after event for duration afterFor(event, duration) after event within duration afterWithin(event, duration) until event until(event) every duration1 for duration2 everyFor(duration1, duration2) when condition changes Maps to Modelica if
  • 104.
    104 From Text toSimulated Requirement – Modelica Extended with new Operators model P2a extends Condition; input ConditionStatus bPSNeeded, sARequired, set1Powered; equation status = if afterWithin (bPSNeeded == notViolated and sARequired == notViolated, 20) then if set1Powered == notViolated then notViolated else violated else undefined; end P2a; BPS.Needed and SA.Required s20 s20 t = 0 time BPS.Needed and SA.Required Set1.Powered must become true within the timeframe s20 and remain true afterwards From a text requirement expressing a condition: A - In the absence of any Backup Power Supply (BPS) component failure or in the presence of a single sensor failure, when the BPS is not under maintenance, in case of loss of MPS, and if safety injection is required, Set1 must be powered within 20 s
  • 105.
    105 From Text toSimulated Requirement – Requirement not Violated – OpenModelica Simulation Within 20s BPS Powered Requirement undefined outside the specified time window Requirement validated BPS.Needed and SA.Required s20 t = 0 time t = 10 t = 25 Set1.Powered 3-valued logic prototype: 1 – true 0 – false -1 – undefined
  • 106.
    106 Outlook: New OpenModelica Frontendfor Large-Scale models • Soon: New OMC Compiler frontend for fast compilation and large- scale models • Been under development the past 2-3 years • Now (sept 24) simulates 67% of MSL models, coverage increases about 6% per month • About 10-200 times faster than the old frontend, depending on model
  • 107.
    107 OpenModelica DAEMode forLarge-Scale models • Goal – to handle hundreds of thousands to millions of equations • Introduced sparse solvers in the solution chain: • KLU for linear algebraic equations, • Kinsol for nonlinear algebraic equations, and • IDA for causalized differential equations. • Largest system so far: electro-mechanical power system model with about 600.000 differential-algebraic equations • Under development for even larger systems
  • 108.
    108 Summary and Questions Hybrid Modeling VisualAcausal Component Modeling Multi-Domain Modeling Typed Declarative Textual Language Thanks for listening! www.modelica.org – Language, Standard Library www.openmodelica.org – Open Source Tool Modelica® is a registered trademark of the Modelica Association