modeling tool for stiff heterogeneous systems

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Modeling Tool for Stiff Heterogeneous Systems. 1 Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia, shornikov@inbox.ru. Yury Shornikov 1 , Eugeny Novikov 2. 2 Institute of Computational Modeling SB RAS, Krasnoyarsk, Russia, novikov@icm.krasn.ru. - PowerPoint PPT Presentation

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Modeling Tool for Stiff Heterogeneous Modeling Tool for Stiff Heterogeneous SystemsSystems

Yury Shornikov1, Eugeny Novikov2

1 Design Technological Institute of Digital Techniques SB RAS,Novosibirsk, Russia, shornikov@inbox.ru

2 Institute of Computational Modeling SB RAS,Krasnoyarsk, Russia, novikov@icm.krasn.ru

2

Class of SystemsClass of Systems

;

;

Discrete-continuous systems. For example, the constrained pendulum.

Classes of HS Continuous BehaviorClasses of HS Continuous Behavior

3

Systems Models of Continuous Modes

Electromechanical ODE

Automation ODE having retarded arguments

Chemical kinetics ODE

Biological ODE, PDE

Electrical DAE

Chemical-engineering PDE

Mechanical PDE

Others ODE, DAE, PDE

4

Class of SystemsClass of Systems

5

Traction Electric DriveTraction Electric Drive

Block diagram of traction electric drive of electric loader

Structural specification (visual model)

Data ImportData Import

6

Changing of the motor torque in time

7

Solving Direct Problems of Solving Direct Problems of Chemical KineticsChemical Kinetics

s

N

1iiij

N

1i

k

iij N,1j,ccrr j

ri N,1i,c – reactants

sj N,1j,k – rate constants of stages

αij и βij – stoichiometric coefficients

8

Unification of ISMA SoftwareUnification of ISMA Software::Integrated PreprocessorIntegrated Preprocessor

LISMALISMA GG

;S S

C SC S

S E aE

ida

cidO

T*OOT

ETTE SS

:LISMAG C

9

Ethane PyrolysisEthane Pyrolysis

2 6 3 3

3 2 6 4 2 5

2 5 2 4

2 6 2 2 5

2 5 2 5 4 10

,

,

,

,

.

C H CH CH

CH C H CH C H

C H C H H

H C H H C H

C H C H C H

8,1j,y j - concentrations of reactants

10

Biliary SystemBiliary System

Reception Ejection

 Daily bile secretion

11

Biliary SystemBiliary SystemOutput intensity of the bile in 12

duodenum Output intensity of the bile into

the bile duct

Mode «reception»

Mode «ejection»

Class of SystemsClass of SystemsSystem of differential-algebraic equations (DAE) with constraints:

12

0 0 0 0 0

, , ,

, , ,

: , , 0,

, , , ,

where , , ,

: ,

: ,

: .

yx

y yx

yx

yx

k

NN

N NN

NN Nx

NN S

y f x y t

x x y t

pr g x y t

t t t x t x y t y

x R y R t R

f R R R R

R R R R

g R R R R

13

Ring Modulator*Ring Modulator*

*Kampowski W., Rentrop P., Schmidt W. Classication and numerical simulation of electric circuits // Surveys on Mathematics for Industry, 2(1):23 65, 1992

14

Ring Modulator:Ring Modulator:Program Model in ISMAProgram Model in ISMA

15

Practical Modeling of HSPractical Modeling of HSRing modulator: comparative evaluation

Characteristics ISMAMK22*

DLSODE

MVS AnyLogic

Simulink

Number of computing the right side

474213 496073 _ _ _

Number of returns 496073 16946 _ _ _

*Novikov А.Е., Novikov Е.А., Shornikov Y.V. Approximation of Jacobi matrix in (2,2)-method of solving hybrid systems // Report of Academy of Science of Higher School of Russian Federation, 2008, #1(10). – P. 31-44.

Original Explicit, Semi-Explicit and Adaptive Integration Original Explicit, Semi-Explicit and Adaptive Integration Algorithms in the ISMAAlgorithms in the ISMA**

* Instrumental tools of computerized analysis (ISMA) / Yu.V. Shornikov, V.S. Druzhinin, N.А. Makarov, K.V. Omelchenko, and I.N. Tomilov // Official registration license for computers No. 2005610126, Мoscow, Rospatent, 2005.

16

17

High-Dimensional ModelsHigh-Dimensional ModelsModel of penetration of radioactive labeled antibodies in a tumor affected tissue of a

living oragnism (Akzo Nobel Central Research)

20t0,Ry,g0y,y,tfdt

dy N2

,ykyf

,ykyyy2y

2

yyf

1j2j2j2

j21j221j21j23j2

j3j21j2

j1j2

.v,0,...,v,0,v,0g,Rg

,yy,tty,N

1

,Nj1,c1j,c1j2

T000

N2

1N21N21

24j

23j

18

Text Model in ISMAText Model in ISMA

19

Dependency of Calculation Time Dependency of Calculation Time From System DimensionFrom System Dimension

Simulation results from:http://www.dm.uniba.it/~testset/report/medakzo.pdf

20

Comparison of Solutions Obtained Comparison of Solutions Obtained by Explicit and Implicit Methodsby Explicit and Implicit Methods

RADAU5

RADAU5, RKF78ST

Extending a Class of SystemsExtending a Class of Systems

DAE systems with constraints unresolved for the derivative:

21

0 0 0 0 0

, , , 0,

, , ,

: , , 0,

, , , ,

where , , ,

: ,

: ,

: .

yx

y y yx

yx

yx

k

NN

N N NN

NN Nx

NN S

F x y y t

x x y t

pr g x y t

t t t x t x y t y

x R y R t R

F R R R R R

R R R R

g R R R R

Instrumental Simulation of EPSInstrumental Simulation of EPS

22

Dostovalov D.N. Program of graphical sheme editor for electro-power systems ISMA EPS (ISMA Electric Power Systems) / Yu.V. Shornikov, A.N. Komarichev, D.N. Dostovalov // Certificate of state registration of computer programs #2013617771. M.:  Federal Service for Intellectual Property. - 2013.

Algorithm for Analysis of Implicit ProblemsAlgorithm for Analysis of Implicit Problems**

• Problem definition:

23

* Novikov E.A., Yumatova L.A. A few methods for solving of ordinary differential equations unresolved for the derivative // Reports of the Academy of Sciences of the USSR, vol.295, №4, 1987. – pp.809-812.

0 0 0 0

, 0,

where ,

, .

F x y

y x

x t x y t y

• Numerical scheme:

1 1 1 1 1 1

1 1 1

, ,

,

1( ), ,

where , , , ,

1, 1.

x yn n n n

n ny nx

x y xn ny n n n

nx n n ny n n

x x p k y y p k

D F ahF

D k h F y F k k hyah

F F x y x F F x y y

a p

Event Detection in HSEvent Detection in HS**

24

* 1. Novikov E.A., Shornikov Yu.V. Computer simulation of stiff hybrid systems: monograph / Novosibirsk: Publishing house of the NSTU, 2012, 451p. 2. Esposito J., Kumar V., Pappas, G.J.: Accurate event detection for simulating hybrid systems. In: Hybrid Systems: Computation and Control (HSCC). Volume LNCS 2034, Springer–Verlag, 1998.

Event Detection AlgorithmEvent Detection Algorithm

25

Test of Event Detection AlgorithmTest of Event Detection Algorithm

26

a) – without taking into account the dynamics of an event function, .b) – using the event-detection algorithm, .

Movement

Rebound:

: 0,

.

pr y

v v

Modal behavior:

0,

0.

y v

v a

a b

1 0 75. 2 0 06.

Extending a Class of SystemsExtending a Class of SystemsContinuous behavior of HS is determined by the systems differential-algebraic equations and PDEs.

27

2

2

0 0 0 0

0 0

2

, , , , , ,

, ,

: , 0,

, , , ,

, , , ,

,

, , , ,

: ,

: ,

: ,

px z

x x

p px z z

x

k m

p

NN N

N N

N NN N N

N S

z z zx z t p

t p p

x x t

pr g x t

x t p x z t p z

t t t p p p

zz p

n

x R z R t R p R

R R R

R R R R R R

g R R R

Thank you for your attentionThank you for your attention!!

28

Yury Shornikov1, Eugeny Novikov2

1 Design Technological Institute of Digital Techniques SB RAS,Novosibirsk, Russia, shornikov@inbox.ru

2 Institute of Computational Modeling SB RAS,Krasnoyarsk, Russia, novikov@icm.krasn.ru

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