Techniques for Modeling Discrete Controllers for the Optimization of Hybrid Plants: a Case Study
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Techniques for Modeling Discrete Controllers for the Optimization of Hybrid Plants: a Case Study. Dynamics of Mechanical Systems. E. Seabra 1 | J. Machado 1 | C. Leão 2 | L. F. Silva 1. Universidade do Minho - Escola de Engenharia 1 Departamento de Engenharia Mecânica

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Universidade do minho escola de engenharia

Techniques for Modeling Discrete Controllers for the Optimization of Hybrid Plants: a Case Study

Dynamics of Mechanical Systems

E. Seabra1 | J. Machado1 | C. Leão2 | L. F. Silva1

Universidade do Minho - Escola de Engenharia

1 Departamento de Engenharia Mecânica

2 Departamento de Produção e Sistemas

Campus de Azurém

4800-058 Guimarães

Portugal

Universidade do Minho

Escola de Engenharia


Outline

Outline

  • Context of the work

  • Contribution of this work

  • The case study

  • Plant modeling for simulation purposes

  • Controller modeling for simulation purposes

  • Simulation results

  • Conclusions and perspectives


Support

Support

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • SCAPS Project

    • “Safety Control of Automated Production Systems”

    • Simulation and Formal Verification of Real-Time Systems

      • taking into account the plant modeling

  • Supported by FCT

    • the Portuguese Foundation for Science and Technology, and FEDER, the European Regional Development Fund


Automated system static point of view

Program

Scan cycle

Automated system – Static point of view

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

Plant

Controller

Inputs

Outputs

Does the program is correct ?

(in accordance with the expected behavior?)


Automated system dynamic point of view

Automated system – Dynamic point of view

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • How to create the plant model for:

  • Simulation purposes?

  • and/or

  • Formal verification purposes?

  • Taking the time into account …


State of the art

State of the art

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Analysis Techniques of Industrial Controllers:

    • Not exhaustive (Simulation) [Barton 1992] [Baresi et al. 1998] [Amerongen 2003] [Mattsson et al. 1998] [Lebrun 2003]

    • Exhaustive (Formal Verification)

      • Model-Checking [Clarke et al. 1986] [Moon et al. 1992]

      • Theorem-proving [Volker & Kramer, 1999] [Roussel & Denis, 2002]

      • Reachability analysis [Kowalewski & Preuig,1996] [Frey & Litz, 2000]


State of the art1

  • For Real-Time Hybrid systems (tools and formalisms):

    • Dymola software and programming language Modelica [Elmqvist and Mattson, 1997];

      • with the library for hierarchical state machines StateGraph [Otter, 2005]

State of the art

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Analysis Techniques of Industrial Controllers:

    • Not exhaustive (Simulation) [Barton 1992] [Baresi et al. 1998] [Amerongen 2003] [Mattsson et al. 1998] [Lebrun 2003]


Our goal

Our Goal

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

To show as Modelica modeling language can be used for:

  • Safety behavior of the system (Controller + Plant)

  • Optimization of hybrid plant behavior parameters

  • Analysis of discrete controllers for hybrid plants


Case study normal behavior

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1, if the valve V18 be opened.


Case study normal behavior1

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1, if the valve V18 be opened.


Case study normal behavior2

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1, if the valve V18 be opened.


Case study normal behavior3

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1, if the valve V18 be opened.


Case study normal behavior4

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1,


Case study normal behavior5

Case Study (Normal Behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Tank1 is filled with an aqueous solution by opening valve V12.

  • When the level becomes high, the valve is closed and the heating system is switch on and also, in simultaneous, the cooling system of the condenser by opening valve V13.

  • When the concentration desired in the tank1 is reached, there are switch off the heating system and the cooling system of the condenser.

  • Continuously the solution flows from tank1 into tank2, and it must be guaranteed that the tank2 is empty.

  • When the first tank is empty the solution in tank2 stays for post‑processing operation where the solution is heated to avoid possible crystallization, using two approaches: heat until the temperature sensor TIS2 indicates that the desired temperature was reached; or heat for a certain time.

  • Finally, the tank2 is emptied by the pump P1, if the valve V18 be opened.


Case study failure behavior

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to ensure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior1

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to ensure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior2

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to assure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior3

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to assure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior4

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to assure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior5

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to assure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Case study failure behavior6

Case Study (Failure behavior)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The condenser may fail: the steam can not be cooled and the pressure inside the condenser rises.

    • The heater must be switched off to avoid the condenser explosion

  • The temperature of tank1 decreases and the solution may become solid and can not be drained in tank2.

    • Valve V15 must be opened early enough for preventing tank2 overflow, but after opening first valve V18

  • In the case of a condenser malfunction, it is also necessary to assure some response times of the controller program

    • whenever a condenser malfunction starts, the condenser can explode if steam is produced during 22 time units

    • if the heating device is switched off, the steam production stops after 12 time units

    • If no steam is produced in tank 1, the solution may solidify after 19 time units

    • emptying tank 2 takes between 0 and 26 time units

    • filling tank 1 takes 6 time units, at most


Controller specification for the system behavior

Controller specification for the system behavior

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

SFC (IEC 60848) Specification

Normal operation


Controller specification for the system behavior1

Controller specification for the system behavior

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

SFC (IEC 60848) Specification

Failure operation


Controller specification for the system behavior2

Controller specification for the system behavior

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

SFC (IEC 60848) Specification

Translation

StateGraphs (Otter, 2005)

Simulation with Dymola


Modelica system modeling

Modelica System Modeling

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives


Plant modeling simulation

Plant modeling - Simulation

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Modelica model for tank1 (Evaporator)


Plant modeling simulation1

Plant modeling - Simulation

  • Modelica model for tank1 (Evaporator)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Takes into account the functioning constraints indicated before;

  • There were modelled, also, the other system physical devices.


Plant modeling simulation2

Plant modeling - Simulation

  • Modelica model for tank1 (Evaporator)

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • Takes into account the functioning constraints indicated before;

  • There were modelled, also, the other system physical devices


Controller modeling simulation

Controller modeling - Simulation

  • StateGraph model for normal operation

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives


Controller modeling simulation1

Controller modeling - Simulation

  • StateGraph model for failure operation

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives


Simulation methodology

Simulation Methodology

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

1 – Simulation of system behavior using a discrete controller(operation and failure modes)

2 – Increasing the productivity of the system(number of batches in the evaporator system)


Simulation of system behavior using a discrete controller normal behavior tanks levels

Simulation of system behavior using a discrete controllerNormal behavior –Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

The two main properties are confirmed, the drainage of the solution present in the tank 1 only to happen when the tank2 is empty and also the filling of the tank1 to happen soon after this to be empty.


Universidade do minho escola de engenharia

Simulation of system behavior using a discrete controller Failure behavior (condenser malfunction) –Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

It can be concluded that the failure operation mode is properly simulated, given that is proven that the tank1 is drained through the safety valve (V16) because it is seen that the tank2 remains empty.


Increasing the productivity of the system

Increasing the productivity of the system

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

The batches number optimization depends on the best synchronism that happens among the time in that the solution present in the tank1 is prepared to be drained and the time in that the tank2 finishes its emptying, because it implicates lesser wastes of time in the process.

Among of several physical variables of the process it was chosen the heat supply rate (QHeat) because it is the most relevant variable that determine the rate of the steam formation (this condenses in the condenser C) and correspondingly, the time in that the solution present in the evaporator (tank1) is prepared to be drained (desired concentration reached).

In addition, in all of the performed simulations, it was assumed a time of 200s for the solution powder-processing operation fulfill in the tank2.


Increasing the productivity of the system1

Increasing the productivity of the system

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

The batches number optimization depends on the best synchronism that happens among the time in that the solution present in the tank1 is prepared to be drained and the time in that the tank2 finishes its emptying, because it implicates lesser wastes of time in the process.

Among of several physical variables of the process it was chosen the heat supply rate (QHeat) because it is the most relevant variable that determine the rate of the steam formation (this condenses in the condenser C) and correspondingly, the time in that the solution present in the evaporator (tank1) is prepared to be drained (desired concentration reached).

In addition, in all of the performed simulations, it was assumed a time of 200s for the solution powder-processing operation fulfill in the tank2.


Increasing the productivity of the system2

Increasing the productivity of the system

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

The batches number optimization depends on the best synchronism that happens among the time in that the solution present in the tank1 is prepared to be drained and the time in that the tank2 finishes its emptying, because it implicates lesser wastes of time in the process.

Among of several physical variables of the process it was chosen the heat supply rate (QHeat) because it is the most relevant variable that determine the rate of the steam formation (this condenses in the condenser C) and correspondingly, the time in that the solution present in the evaporator (tank1) is prepared to be drained (desired concentration reached).

In addition, in all of the performed simulations, it was assumed a time of 200s for the solution powder-processing operation fulfill in the tank2.


Increasing the productivity of the system heat supply rate of 2500 w tanks levels

Increasing the productivity of the system Heat supply rate of 2500 W– Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

It happens a great synchronism lack between the time in that the solution present in the tank1 is prepared to be drained and the time in that the tank2 finishes its emptying (waste of time of about 300 s).


Increasing the productivity of the system heat supply rate of 3170 w tanks levels

Increasing the productivity of the system Heat supply rate of 3170 W– Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

It can be verified the synchronism that occurs among the time in that the solution present in the tank1 is prepared to be drained and the time in that the tank2 finishes its emptying.


Increasing the productivity of the system heat supply rate of 3170 w tanks levels1

Increasing the productivity of the system Heat supply rate of 3170 W– Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

An excellent synchronization can be confirmed by the simulation results for the time period that take places the transfer of the solution between tank1 and tank2, because wastes of time don't exist.


Increasing the productivity of the system simulations with different heat supply rates tanks levels

Increasing the productivity of the system Simulations with different heat supply rates – Tanks’ levels

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives


Conclusions

Conclusions

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • The presented approach (to increase the Systems Safety) is useful because:

    • In Simulation:

      • we can avoid, using simulation, a set of program errors in reduced time intervals;

      • some functioning delays may be obtained by simulation;

        • these delays are important to create the plant models for formal verification purposes;

    • In Formal Verification

      • the verification of complex hybrid systems is limited due to the number of states involved, this way the simulation is the best solution for obtaining safety hybrid systems.


Perspectives

Perspectives

Context of the work

Contribution of this work

The case study

Plant modeling for simulation purposes

Controller modeling for simulation purposes

Simulation results

Conclusions and perspectives

  • To use Simulation to:

    • Evaluate and optimization of different parameters of the plant functioning

    • to find critical delays of the plant functioning

      • to see if a property, for different considered delays, is still true or if different delays imply that a property that is true, for a delay, will become false for another

  • To apply the results indicated before:

    • In order to apply on the formal verification of hybrid systems


Universidade do minho escola de engenharia

Techniques for Modeling Discrete Controllers for the Optimization of Hybrid Plants: a Case Study

Dynamics of Mechanical Systems

Thank you for your attention

Questions?

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  • +351 253 510 227 

  • +351 253 516 007

Universidade do Minho

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