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Computational Solid Mechanics Computational Plasticity C. Agelet de Saracibar ETS Ingenieros de Caminos, Canales y Puertos, Universidad Politécnica de Cataluña (UPC), Barcelona, Spain International Center for Numerical Methods in Engineering (CIMNE), Barcelona, Spain Chapter 2. 1D Plasticity Algorithms
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Chapter 2. 1D Plasticity Algorithms v1.0

Oct 02, 2015

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  • Computational Solid Mechanics Computational Plasticity

    C. Agelet de Saracibar ETS Ingenieros de Caminos, Canales y Puertos, Universidad Politcnica de Catalua (UPC), Barcelona, Spain

    International Center for Numerical Methods in Engineering (CIMNE), Barcelona, Spain

    Chapter 2. 1D Plasticity Algorithms

  • Contents 1. Introduction 2. 1D Rate independent plasticity models

    1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    3. 1D Rate dependent plasticity models 1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    4. 1D Computational plasticity assignment

    1D Plasticity Algorithms > Contents

    Contents

    April 1, 2015 Carlos Agelet de Saracibar 2

  • Contents 1. Introduction 2. 1D Rate independent plasticity models

    1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    3. 1D Rate dependent plasticity models 1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    4. 1D Computational plasticity assignment

    1D Plasticity Algorithms > Contents

    Contents

    April 1, 2015 Carlos Agelet de Saracibar 3

  • 1D Plasticity Algorithms > Introduction

    Time integration algorithm

    April 1, 2015 Carlos Agelet de Saracibar 4

    pnE 1

    pn+E

    1n+E

    Time integration algorithm

  • Contents 1. Introduction 2. 1D Rate independent plasticity models

    1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    3. 1D Rate dependent plasticity models 1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    4. 1D Computational plasticity assignment

    1D Plasticity Algorithms > Contents

    Contents

    April 1, 2015 Carlos Agelet de Saracibar 5

  • 1. Additive split of strains

    2. Constitutive equations

    3. Associative plastic flow rule

    4. Yield function

    5. Kuhn-Tucker loading/unloading conditions

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    1D Rate independent plasticity model

    April 1, 2015 Carlos Agelet de Saracibar 6

    ( ) { } { }, , , diag , ,e e e q q E K H = = =ES E CE S: , C :=

    { } { } { }: : ,0,0 , : , , , : , ,e p p p e e = + = = = E E E , E E E

    ( )p f= SE S

    ( ) Yf q q = +S

    ( ) ( )0, 0, 0f f =S S

  • Associative plastic flow rule: plastic strains at time n+1

    Using a Backward-Euler (BE) time integration scheme yields,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 7

    ( )p f= SE S

    ( )11 1 1n

    p pn n n nf ++ + += + SE E S

    ( )

    ( )

    1 1 1 1

    1 1

    1 1 1 1

    sgn

    sgn

    p pn n n n n

    n n n

    n n n n n

    q

    q

    + + + +

    + +

    + + + +

    = + = + =

  • Constitutive equations: stress state at time n+1

    The time-discrete constituve equation at time n+1 takes the form,

    Substituting the plastic strain variables at time n+1 yields,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 8

    ( ) ( ) { }, diag , ,e e e p E K H= = = ES E CE C E E C :=

    ( )1 1 1 1e pn n n n+ + + += = S CE C E E

    ( )( )( ) ( )

    1

    1

    1 1 1 1

    1 1 1

    n

    n

    pn n n n n

    pn n n n

    f

    f

    +

    +

    + + + +

    + + +

    =

    =

    S

    S

    S C E E S

    C E E C S

  • Trial state at time n+1 The trial state at time n+1 is defined by freezing the plastic behaviour at the time step, yielding

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 9

    ( ) ( )( )

    ,1

    , ,1 1 1

    , ,1 1 1 1 1

    1 1

    :

    :

    :

    :

    p trial pn ne trial p trialn n n

    trial e trial p trial pn n n n n n

    trial trialn nf f

    +

    + + +

    + + + + +

    + +

    =

    =

    = = =

    =

    E E

    E E E

    S CE C E E C E E

    S

  • Return mapping algorithm The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 10

    ( )11 1 1 1n

    trialn n n nf ++ + + += SS S C S

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    E q

    q q Kq q H q

    + + + + +

    + + +

    + + + + +

    = = = +

  • 1. Additive split of strains at time n+1

    2. Stresses at time n+1. Return mapping algorithm

    3. Plastic internal variables at time n+1

    4. Yield function at time n+1

    5. Kuhn-Tucker loading/unloading conditions at time n+1

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 11

    ( )1 1 1 1 1:n n n n Y nf f q q + + + + += = +S

    1 1 1 10, 0, 0n n n nf f + + + + =

    ( )11 1 1 1n

    trialn n n nf ++ + + += SS S C S

    1 1 1:e p

    n n n+ + += +E E E

    ( )11 1 1n

    p pn n n nf ++ + += + SE E S

  • Theorem 1. Elastic step/plastic step If the yield function is convex and the constitutive matrix is definite-positive, the following condition holds,

    and Kuhn-Tucker loading/unloading conditions can be decided just in terms of the trial yield function according to,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 12

    ( ) ( )1 1trialn nf f+ +S S

    ( )( )

    1 1

    1 1

    Elastic step

    Plastic s

    0 0

    0 t0 ep

    trialn n

    trialn n

    f

    f

    + +

    + +

    < =

    > >

    S

    S

  • Proof 1. Convexity of the yield function yields,

    Using the return mapping equation, yields,

    Definite-positiveness of the constitutive matrix yields,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 13

    ( ) ( ) ( ) ( )11 1 1 1 1n

    trial trialn n n n nf f f++ + + + + SS S S S S

    ( ) ( ) ( ) ( )1 11 1 1 1 1n n

    trialn n n n nf f f f + ++ + + + + S SS S S C S

    ( )11 1 1 1n

    trialn n n nf ++ + + += SS S C S

    ( ) ( ) ( ) ( )( ) ( )

    1 11 1 1 1 1

    1 1

    0n n

    trialn n n n n

    trialn n

    f f f f

    f f

    + ++ + + + +

    + +

    S SS S S C S

    S S

  • Proof 2. The trial yield function at time n+1 determines the discrete plastic loading/elastic unloading conditions according to,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 14

    ( )( ) ( )

    ( )( )

    ( )( ) ( )

    1

    1

    1 1

    1 1 1

    1

    1 1 1 1

    1 1 1 1

    if 0 then

    0

    0 Elastic step

    Plastic

    0

    else if 0 then

    0, 0 0 ste

    en if

    p

    d

    n

    trialn

    trialn n

    n n n

    trialn

    trialn n n n

    n n n n

    f

    f f

    f

    f

    f

    f f

    +

    +

    + +

    + + +

    +

    + + + +

    + + + +

    Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 15

    ( )1 1arg min trialn n + += S S S S E

    ( )( ) ( )

    1

    211 12

    1 11 12

    trial trialn n

    trial trialn n

    + +

    + +

    =

    = C

    S S S S

    S S C S S

  • Proof 1. The stress state at time n+1, the closest-point-projection of the trial stress state at n+1 onto the space of admissible stresses, is the solution of the following constrained minimization problem,

    Using the Lagrange multipliers method, the constrained minimization problem can be transformed into an unconstrained minimization problem defined as,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 16

    ( )1 1arg min trialn n + += S S S S E

    ( ) ( ) ( )1 1, :trial trialn n f + += +S S; S S SL( )1 1 1arg min ,trialn n n+ + += S S S; SL

  • The optimality conditions of the unconstrained minimization problem read, The return mapping algorithm arises as the solution of the unconstrained minimization problem yielding,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 17

    ( ) ( ) ( )( ) ( )

    1 1 1

    1

    1 1 1 1 1 1 1

    11 1 1 1

    , :

    : 0

    ;n n n

    n

    trial trialn n n n n n n

    trialn n n n

    f

    f

    + + +

    +

    + + + + + + +

    + + + +

    = +

    = + =

    S S S

    S

    S S S S S

    C S S S

    L

    ( ) ( )1 1 1 10, 0, 0n n n nf f + + + + =S S

    ( )11 1 1 1n

    trialn n n nf ++ + + += SS S C S

  • Return mapping algorithm The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 18

    ( )11 1 1 1n

    trialn n n nf ++ + + += SS S C S

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    E q

    q q Kq q H q

    + + + + +

    + + +

    + + + + +

    = = = +

  • The solution for the return mapping algorithm yields,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 19

    ( ) ( )1 1 1 1 1 1 1sgntrial trialn n n n n n nq q E H q + + + + + + + = +

    ( ) ( )( ) ( )

    1 1 1 1 1 1 1 1

    1 1 1

    sgn sgn

    sgn

    trial trial trial trialn n n n n n n n

    n n n

    q q q q

    E H q

    + + + + + + + +

    + + +

    =

    +

    ( )( ) ( )( )

    1 1 1 1 1

    1 1 1 1

    sgn

    sgnn n n n n

    trial trial trial trialn n n n

    q E H q

    q q

    + + + + +

    + + + +

    + + =

    =

    ( )( ) ( )

    1 1 1 1 1

    1 1 1 1sgn sgn

    trial trialn n n n n

    trial trialn n n n

    q E H q

    q q

    + + + + +

    + + + +

    + + =

    =

  • For the non-trivial case (plastic loading), using the discrete Kuhn-Tucker loading/unloading conditions, the discrete plastic multiplier (or discrete plastic consistency parameter) reads,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 20

    ( )1 1 1 1if 0 then , , 0n n n nf q q + + + +> =( )

    ( )( ) ( )

    1 1 1 1 1 1

    1 1 1 1

    1 1 1 1

    , ,

    , , 0

    n n n n n Y n

    trial trial trialn n n Y n

    trial trial trialn n n n

    f q q q q

    q E K H q

    f q q E K H

    + + + + + +

    + + + +

    + + + +

    = +

    = + + +

    = + + =

    ( ) ( )11 1 1 1, , 0trial trial trialn n n nE K H f q q + + + += + + >

    ( ) ( )1 1 1 1 1 1 1 10, , , 0, , , 0n n n n n n n nf q q f q q + + + + + + + + =

  • The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 21

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    E q

    q q Kq q H q

    + + + + +

    + + +

    + + + + +

    = = = +

    ( ) ( ) ( )( ) ( )( ) ( )

    11 1 1 1 1 1 1

    11 1 1 1 1

    11 1 1 1 1 1 1

    , , sgn

    : , ,

    : , , sgn

    trial trial trial trial trial trialn n n n n n n

    trial trial trial trialn n n n n

    trial trial trial trial trialn n n n n n n

    E K H f q q E q

    q q E K H f q q K

    q q E K H f q q H q

    + + + + + + +

    + + + + +

    + + + + + + +

    = + +

    = + +

    = + + + ( )trial

  • The update of the plastic internal variables takes the form,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 22

    ( )

    ( )

    1 1 1 1

    1 1

    1 1 1 1

    sgn

    sgn

    p pn n n n n

    n n n

    n n n n n

    q

    q

    + + + +

    + +

    + + + +

    = + = + =

    ( ) ( ) ( )( ) ( )( ) ( ) ( )

    11 1 1 1 1 1

    11 1 1 1

    11 1 1 1 1 1

    , , sgn

    , ,

    , , sgn

    p p trial trial trial trial trialn n n n n n n

    trial trial trialn n n n n

    trial trial trial trial trialn n n n n n n

    E K H f q q q

    E K H f q q

    E K H f q q q

    + + + + + +

    + + + +

    + + + + + +

    = + + + = + + +

    = + +

  • Consistent elastoplastic tangent modulus The consistent elastoplastic tangent modulus is computed taking the variation of the stress at time n+1, yielding, where

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Consistent elastoplastic tangent modulus

    April 1, 2015 Carlos Agelet de Saracibar 23

    ( ) ( )11 1 1 1 1sgntrial trial trial trialn n n n nE K H f E q + + + + += + + ( ) ( )11 1 1 1 1sgntrial trial trial trialn n n n nd d E K H df E q + + + + += + +

    ( )( ) ( )

    ( ) ( )

    ,1 1 1 1

    1 1 1 1 1 1 1

    1 1 1 1 1 1

    sgn

    sgn sgn

    trial e trial pn n n n n

    trial trial trial trial trial trial trialn n n n n n n

    trial trial trial trial trialn n n n n n

    d Ed E d E d

    df d q q d q

    q d q E d

    + + + +

    + + + + + + +

    + + + + + +

    = = =

    = =

    = =

  • The consistent elastoplastic tangent modulus takes the form,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Consistent elastoplastic tangent modulus

    April 1, 2015 Carlos Agelet de Saracibar 24

    ( ) ( )

    ( ) ( ) ( )( )( )

    11 1 1 1 1

    1 11

    1 1 1 1 1

    11 1

    sgn

    sgn sgn

    1

    trial trial trial trialn n n n n

    n n

    trial trial trial trialn n n n n

    n n

    d d E K H df E q

    d E d

    E K H q E d E q

    d E E E K H d

    + + + + +

    + +

    + + + + +

    + +

    = + +

    =

    + +

    = + +

    ( )( )11 1, : 1ep epn nd E d E E E E K H + += = + +

  • 1D Plasticity algorithm Step 1. Given the strain at time n+1 (strain driven problem), and the stored plastic internal variables at time n (plastic internal variables database) Step 2. Compute the trial state at time n+1

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 25

    ( ) ( )

    ,1

    , ,1 1 1

    , ,1 1 1 1 1

    1 1 1 1

    :

    :

    :

    :

    p trial pn ne trial p trialn n n

    trial e trial p trial pn n n n n n

    trial trial trial trialn n n Y nf q q

    +

    + + +

    + + + + +

    + + + +

    =

    =

    = = =

    = +

    E E

    E E E

    S CE C E E C E E

  • Step 3. Check the trial yield function at time n+1 Step 4. Compute discrete plastic multiplier at time n+1

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 26

    ( ) ( )1 1 1if 0 then set , and exittrialtrial ep

    n n nf E E+ + + = =

    ( ) 11 1trialn nE K H f

    + += + +

  • Step 5. Return mapping algorithm (closest-point-projection)

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 27

    ( ) ( )( )( ) ( )

    11 1 1 1 1

    11 1 1

    11 1 1 1 1

    sgn

    :

    : sgn

    trial trial trial trialn n n n n

    trial trialn n n

    trial trial trial trialn n n n n

    E K H f E q

    q q E K H f K

    q q E K H f H q

    + + + + +

    + + +

    + + + + +

    = + + = + +

    = + + +

    ( )1

    1 1 1 1trialn

    trial trialn n n nf

    ++ + + += SS S C S

  • Step 6. Update plastic internal variables database at time n+1 Step 7. Compute the consistent elastoplastic tangent modulus

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 28

    ( ) ( )( )( ) ( )

    11 1 1 1

    11 1

    11 1 1 1

    sgn

    sgn

    p p trial trial trialn n n n n

    trialn n n

    trial trial trialn n n n n

    E K H f q

    E K H f

    E K H f q

    + + + +

    + +

    + + + +

    = + + + = + + +

    = + +

    ( )( )1: 1epE E E E K H = + +

    ( )1

    1 1 1trialn

    p p trialn n n nf

    ++ + += + SE E S

  • Nonlinear isotropic hardening Exponential saturation law + linear hardening

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 29

    ( ) ( ):q = = =

    ( ) ( )( ): : 1 expYq K = = ( ) ( ) ( )( )1 expY K = +

  • Time discrete nonlinear isotropic hardening

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 30

    ( ) ( )( ) ( )

    ( ) ( )

    1 1 1

    1 1

    1 1 1

    :

    :

    :

    n n n n

    trial trialn n n n

    trialn n n n n

    q

    q q

    q q

    + + +

    + +

    + + +

    = = +

    = = =

    = + +

  • Plastic loading: Yield function at time n+1 Nonlinear residual scalar equation on the plastic multiplier at time n+1

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 31

    ( ) ( ) ( )( )1 1 1 1 0trialn n n n n nf f E H + + + + = + + =

    ( )( ) ( ) ( )( )

    1 1 1

    1 1 1 1

    : 0

    : 0n n n

    trialn n n n n n

    g g f

    g f E H

    + + +

    + + + +

    = = =

    = + + =

  • Newton-Raphson iterative solution algorithm Step 1. Initialize iteration counter and plastic multiplier Step 2. Compute the residual g at time n+1, iteration k Step 3. While the absolute value of the current residual at time n+1, iteration k, is greater than a tolerance Step 4. Solve the linarized equation Step 5. Update the plastic multiplier at time n+1, iteration k+1 Step 6. Compute the residual g at time n+1, iteration k+1 Step 7. Increment iteration counter k=k+1 and go to Step 3

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 32

    10, 0knk += =

    1 1 1 0k k kn n ng Dg + + ++ =

    11 1 1

    k k kn n n ++ + += +

  • Newton-Raphson iterative solution algorithm

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 33

    ( ) ( ) ( )( )( ) ( )

    ( )( )

    1 1 1 1

    1 1 1 1 1

    1 1

    11 1 1

    :

    :

    :

    :

    k trial k kn n n n n n

    k k k k kn n n n n n

    k kn n n

    k k kn n n

    g f E H

    Dg E H

    E H

    + + + +

    + + + + +

    + +

    ++ + +

    = + +

    = + +

    = + + +

    =

    1 1 1 0k k kn n ng Dg + + ++ =

  • Consistent elastoplastic tangent modulus The consistent elastoplastic tangent modulus is computed taking the variation of the stress at time n+1, yielding, where the variations of the trial stress tensor, and plastic multiplier, at time n+1, have to be computed.

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 34

    ( )( )

    1 1 1 1 1

    1 1 1 1 1

    sgn

    sgn

    trial trial trialn n n n n

    trial trial trialn n n n n

    E q

    d d d E q

    + + + + +

    + + + + +

    =

    =

  • The variation of the plastic multiplier at time n+1 is computed setting the variation of the residual at time n+1 equal to zero,

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 35

    ( ) ( ) ( )( )( ) ( )

    ( )( )( )( )

    1 1 1 1

    1 1 1 1 1

    1 1 1

    1

    1 1 1

    : 0

    :

    : 0

    trialn n n n n n

    trialn n n n n n

    trialn n n n

    trialn n n n

    g f E H

    dg df d E H d

    df d E H

    d E H df

    + + + +

    + + + + +

    + + +

    + + +

    = + + =

    = + +

    = + + + =

    = + + +

  • Substituting the variations shown before, the following discrete tangent constitutive equation is obtained, where the consistent elastoplastic tangent modulus at time n+1 is given by

    1D Plasticity Algorithms > Rate Independent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 36

    1 1 1ep

    n n nd E d + + +=

    ( )( )( )11 11epn n nE E E E H + += + + +

  • Contents 1. Introduction 2. 1D Rate independent plasticity models

    1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    3. 1D Rate dependent plasticity models 1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    4. 1D Computational plasticity assignment

    1D Plasticity Algorithms > Contents

    Contents

    April 1, 2015 Carlos Agelet de Saracibar 37

  • 1. Additive split of strains

    2. Constitutive equations

    3. Associative plastic flow rule

    4. Yield function

    5. Plastic multiplier

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    1D Rate dependent plasticity model

    April 1, 2015 Carlos Agelet de Saracibar 38

    ( ) { } { }, , , diag , ,e e e q q E K H = = =ES E CE S: , C :=

    { } { } { }: : ,0,0 , : , , , : , ,e p p p e e = + = = = E E E , E E E

    ( )p f= SE S

    ( ) Yf q q = +S

    ( )1 0f = S

  • Associative plastic flow rule: plastic strains at time n+1

    Using a Backward-Euler (BE) time integration scheme yields,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 39

    ( )p f= SE S

    ( )11 1 1n

    p pn n n nt f ++ + += + SE E S

  • Constitutive equations: stress state at time n+1

    The time-discrete constituve equation at time n+1 takes the form,

    Substituting the plastic strains at time n+1 yields,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 40

    ( ) ( ) { }, diag , ,e e e p E K H= = = ES E CE C E E C :=

    ( )1 1 1 1e pn n n n+ + + += = S CE C E E

    ( )( )( ) ( )

    1

    1

    1 1 1 1

    1 1 1

    n

    n

    pn n n n n

    pn n n n

    t f

    t f

    +

    +

    + + + +

    + + +

    =

    =

    S

    S

    S C E E S

    C E E C S

  • Trial state at time n+1 The trial state at time n+1 is defined by freezing the plastic behaviour at the time step, yielding

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 41

    ( ) ( )( )

    ,1

    , ,1 1 1

    , ,1 1 1 1 1

    1 1

    :

    :

    :

    :

    p trial pn ne trial p trialn n n

    trial e trial p trial pn n n n n n

    rial trialn nf f

    +

    + + +

    + + + + +

    + +

    =

    =

    = = =

    =

    E E

    E E E

    S CE C E E C E E

    S

  • Return mapping algorithm The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 42

    ( )11 1 1 1n

    trialn n n nt f ++ + + += SS S C S

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    t E q

    q q t Kq q t H q

    + + + + +

    + + +

    + + + + +

    = = = +

  • 1. Additive split of strains at time n+1

    2. Stresses at time n+1. Return mapping algorithm

    3. Plastic internal variables at time n+1

    4. Yield function at time n+1

    5. Plastic multiplier at time n+1

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 43

    ( )1 1 1 1 1:n n n n Y nf f q q + + + + += = +S

    ( )11 1 1 1n

    trialn n n nt f ++ + + += SS S C S

    1 1 1:e p

    n n n+ + += +E E E

    ( )11 1 1n

    p pn n n nt f ++ + += + SE E S

    ( )11 1 0n nf + += S

  • Return mapping algorithm The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 44

    ( )11 1 1 1n

    trialn n n nt f ++ + + += SS S C S

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    t E q

    q q t Kq q t H q

    + + + + +

    + + +

    + + + + +

    = = = +

  • The solution for the return mapping algorithm yields,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 45

    ( ) ( )1 1 1 1 1 1 1sgntrial trialn n n n n n nq q t E H q + + + + + + + = +

    ( ) ( )( ) ( )

    1 1 1 1 1 1 1 1

    1 1 1

    sgn sgn

    sgn

    trial trial trial trialn n n n n n n n

    n n n

    q q q q

    t E H q

    + + + + + + + +

    + + +

    =

    +

    ( )( ) ( )( )

    1 1 1 1 1

    1 1 1 1

    sgn

    sgnn n n n n

    trial trial trial trialn n n n

    q t E H q

    q q

    + + + + +

    + + + +

    + + =

    =

    ( )( ) ( )

    1 1 1 1 1

    1 1 1 1sgn sgn

    trial trialn n n n n

    trial trialn n n n

    q t E H q

    q q

    + + + + +

    + + + +

    + + =

    =

  • For the non-trivial case (plastic loading), the yield function and the discrete plastic multiplier are greater than zero, and the following expressions hold,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 46

    ( )1 1 1 1 1if 0 then , , 0n n n n nf q q + + + + +> = >( )

    ( )( ) ( )

    1 1 1 1 1 1

    1 1 1 1

    1 1 1 1 1

    , ,

    , ,

    n n n n n Y n

    trial trial trialn n n Y n

    trial trial trialn n n n n

    f q q q q

    q t E K H q

    f q q t E K H

    + + + + + +

    + + + +

    + + + + +

    = +

    = + + +

    = + + =

    ( )1

    1 1 1 1, , 0trial trial trial

    n n n nt E K H f q qt

    + + + + = + + + >

  • The return mapping algorithm takes the form,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 47

    ( )

    ( )

    1 1 1 1 1

    1 1 1

    1 1 1 1 1

    sgn

    :

    : sgn

    trialn n n n n

    trialn n n

    trialn n n n n

    t E q

    q q t Kq q t H q

    + + + + +

    + + +

    + + + + +

    = = = +

    ( ) ( )( )( ) ( )

    11 1 1 1 1

    11 1 1

    11 1 1 1 1

    sgn

    :

    : sgn

    trial trial trial trialn n n n n

    trial trialn n n

    trial trial trial trialn n n n n

    E K H t f E q

    q q E K H t f K

    q q E K H t f H q

    + + + + +

    + + +

    + + + + +

    = + + + = + + +

    = + + + +

  • The update of the plastic internal variables takes the form,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Return mapping algorithm

    April 1, 2015 Carlos Agelet de Saracibar 48

    ( )

    ( )

    1 1 1 1

    1 1

    1 1 1 1

    sgn

    :

    : sgn

    p pn n n n n

    n n n

    n n n n n

    t q

    tt q

    + + + +

    + +

    + + + +

    = + = + =

    ( ) ( )( )( ) ( )

    11 1 1 1

    11 1

    11 1 1 1

    sgn

    :

    : sgn

    p p trial trial trialn n n n n

    trialn n n

    trial trial trialn n n n n

    E K H t f q

    E K H t f

    E K H t f q

    + + + +

    + +

    + + + +

    = + + + + = + + + +

    = + + +

  • Consistent elastoplastic tangent modulus The consistent elastoplastic tangent modulus is computed taking the variation of the stress at time n+1, yielding, where

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Consistent elastoplastic tangent modulus

    April 1, 2015 Carlos Agelet de Saracibar 49

    ( ) ( )11 1 1 1 1sgntrial trial trial trialn n n n nE K H t f E q + + + + += + + + ( ) ( )11 1 1 1 1sgntrial trial trial trialn n n n nd d E K H t df E q + + + + += + + +

    ( )( ) ( )

    ( ) ( )

    ,1 1 1 1

    1 1 1 1 1 1 1

    1 1 1 1 1 1

    sgn

    sgn sgn

    trial e trial pn n n n n

    trial trial trial trial trial trial trialn n n n n n n

    trial trial trial trial trialn n n n n n

    d Ed E d E d

    df d q q d q

    q d q E d

    + + + +

    + + + + + + +

    + + + + + +

    = = =

    = =

    = =

  • The consistent elastoplastic tangent modulus takes the form,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Consistent elastoplastic tangent modulus

    April 1, 2015 Carlos Agelet de Saracibar 50

    ( ) ( )

    ( ) ( )( )( )

    11 1 1 1 1

    1 11 2

    1 1 1

    11 1

    sgn

    sgn

    1

    trial trial trial trialn n n n n

    n n

    trial trialn n n

    n n

    d d E K H t df E q

    d E d

    E K H t q E E d

    d E E E K H t d

    + + + + +

    + +

    + + +

    + +

    = + + +

    =

    + + +

    = + + +

    ( )( )11 1, : 1ep epn nd E d E E E E K H t + += = + + +

  • 1D Plasticity algorithm Step 1. Given the strain at time n+1 (strain driven problem), and the stored plastic internal variables at time n (plastic internal variables database) Step 2. Compute the trial state at time n+1

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 51

    ( ) ( )

    ,1

    , ,1 1 1

    , ,1 1 1 1 1

    1 1 1 1

    :

    :

    :

    :

    p trial pn ne trial p trialn n n

    trial e trial p trial pn n n n n n

    trial trial trial trialn n n Y nf q q

    +

    + + +

    + + + + +

    + + + +

    =

    =

    = = =

    = +

    E E

    E E E

    S CE C E E C E E

  • Step 3. Check the trial yield function at time n+1 Step 4. Compute discrete plastic multipliet at time n+1

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 52

    ( ) ( )1 1 1if 0 then set , and exittrialtrial ep

    n n nf E E+ + + = =

    ( ) 11 1trialn nE K H t f

    + += + + +

  • Step 5. Return mapping algorithm (closest-point-projection)

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 53

    ( ) ( )( )( ) ( )

    11 1 1 1 1

    11 1 1

    11 1 1 1 1

    sgn

    :

    : sgn

    trial trial trial trialn n n n n

    trial trialn n n

    trial trial trial trialn n n n n

    E K H t f E q

    q q E K H t f K

    q q E K H t f H q

    + + + + +

    + + +

    + + + + +

    = + + + = + + +

    = + + + +

    ( )1

    1 1 1 1trialn

    trial trialn n n nf

    ++ + + += SS S C S

  • Step 6. Update plastic internal variables database at time n+1 Step 7. Compute the consistent elastoplastic tangent modulus

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    1D Plasticity algorithm

    April 1, 2015 Carlos Agelet de Saracibar 54

    ( ) ( )( )( ) ( )

    11 1 1 1

    11 1

    11 1 1 1

    sgn

    sgn

    p p trial trial trialn n n n n

    trialn n n

    trial trial trialn n n n n

    E K H t f q

    E K H t f

    E K H t f q

    + + + +

    + +

    + + + +

    = + + + + = + + + +

    = + + +

    ( )( )1: 1epE E E E K H t = + + +

    ( )1

    1 1 1trialn

    p p trialn n n nf

    ++ + += + SE E S

  • Nonlinear isotropic hardening Exponential saturation law + linear hardening

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 55

    ( ) ( ):q = = =

    ( ) ( )( ): : 1 expYq K = = ( ) ( ) ( )( )1 expY K = +

  • Time discrete nonlinear isotropic hardening

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 56

    ( ) ( )( ) ( )

    ( ) ( )

    1 1 1

    1 1

    1 1 1

    :

    :

    :

    n n n n

    trial trialn n n n

    trialn n n n n

    q t

    q q

    q q t

    + + +

    + +

    + + +

    = = +

    = = =

    = + +

  • Plastic loading: Yield function at time n+1 Nonlinear residual scalar equation on the plastic multiplier at time n+1

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 57

    ( ) ( ) ( )( )1 1 1 1 1 0trialn n n n n n nf f t E H t + + + + + = + + = >

    ( )( ) ( )( )

    1 1 1 1

    1 1 1 1

    : 0

    : 0

    n n n n

    trialn n n n n n

    g g f

    g f t E H tt

    + + + +

    + + + +

    = = =

    = + + + =

  • Newton-Raphson iterative solution algorithm Step 1. Initialize iteration counter and plastic multiplier Step 2. Compute the residual g at time n+1, iteration k Step 3. While the absolute value of the current residual at time n+1, iteration k, is greater than a tolerance Step 4. Solve the linarized equation Step 5. Update the plastic multiplier at time n+1, iteration k+1 Step 6. Compute the residual g at time n+1, iteration k+1 Step 7. Increment iteration counter k=k+1 and go to Step 3

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 58

    10, 0knk += =

    1 1 1 0k k kn n ng Dg + + ++ =

    11 1 1

    k k kn n n ++ + += +

  • Newton-Raphson iterative solution algorithm

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 59

    ( ) ( )( )

    ( )

    ( )

    1 1 1 1

    1 1 1 1 1

    1 1

    11 1 1

    :

    :

    :

    :

    k trial k kn n n n n n

    k k k k kn n n n n n

    k kn n n

    k k kn n n

    g f t E H tt

    Dg E H t t tt

    E t H tt

    + + + +

    + + + + +

    + +

    ++ + +

    = + + + = + + + = + + + +

    =

    1 1 1 0k k kn n ng Dg + + ++ =

  • Consistent elastoplastic tangent modulus The consistent elastoplastic tangent modulus is computed taking the variation of the stress at time n+1, yielding, where the variations of the trial stress tensor, and plastic multiplier, at time n+1, have to be computed.

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 60

    ( )( )

    1 1 1 1 1

    1 1 1 1 1

    sgn

    sgn

    trial trial trialn n n n n

    trial trial trialn n n n n

    t E q

    d d d t E q

    + + + + +

    + + + + +

    =

    =

  • The variation of the plastic multiplier at time n+1 is computed setting the variation of the residual at time n+1 equal to zero,

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 61

    ( ) ( )( )

    ( )

    ( )

    ( )

    1 1 1 1

    1 1 1 1 1

    1 1 1

    1

    1 1

    : 0

    :

    : 0

    trialn n n n n n

    trialn n n n n n

    trialn n n n

    n n n n

    g f t E H tt

    dg df d t E H t d tt

    df d t E t Ht

    d t E t H dft

    + + + +

    + + + + +

    + + +

    + + +

    = + + + = = + + + = + + + + =

    = + + + + 1

    trial

  • Substituting the variations shown before, the following discrete tangent constitutive equation is obtained, where the consistent elastoplastic tangent modulus at time n+1 is given by

    1D Plasticity Algorithms > Rate Dependent Plasticity Models

    Nonlinear isotropic hardening

    April 1, 2015 Carlos Agelet de Saracibar 62

    1 1 1ep

    n n nd E d + + +=

    ( )1

    1 11epn n nE E E E t H t

    + +

    = + + + +

  • Contents 1. Introduction 2. 1D Rate independent plasticity models

    1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    3. 1D Rate dependent plasticity models 1. Return mapping algorithm 2. Consistent elastoplastic tangent modulus 3. Step by step algorithm 4. Nonlinear isotropic hardening

    4. 1D Computational plasticity assignment

    1D Plasticity Algorithms > Contents

    Contents

    April 1, 2015 Carlos Agelet de Saracibar 63

  • Implement in MATLAB the BE time-stepping algorithm for 1D rate-independent/rate-dependent hardening plasticity models, including linear and nonlinear isotropic hardening, and linear kinematic hardening

    Perform the numerical simulation of uniaxial cyclic plastic loading/elastic unloading examples for the following cases: o Rate-independent/rate-dependent perfect plasticity o Rate-independent/rate-dependent linear isotropic hardening plasticity o Rate-independent/rate-dependent nonlinear isotropic hardening

    plasticity, considering an exponential saturation law o Rate-independent/rate-dependent linear kinematic hardening

    plasticity o Rate-independent/rate-dependent nonlinear isotropic and linear

    kinematic hardening plasticity

    1D Plasticity Algorithms > 1D Computational Plasticity Assignment

    1D Computational plasticity assignment

    April 1, 2015 Carlos Agelet de Saracibar 64

  • For the perfect plasticity models, plot the stress-strain curves For the linear isotropic/linear kinematic hardening models,

    plot the stress-strain curves showing the influence of the isotropic/kinematic hardening parameters

    For the nonlinear isotropic hardening model, plot the stress-strain curves showing the influence of the exponential coefficient of the exponential saturation law on the stress-strain curves

    For the rate-dependent plasticity models, plot the stress-strain, and the stress-time curves showing the influence of the viscosity parameter and the loading rate.

    Show that the rate-independent response can be recovered from the rate-dependent results using very small values for the viscosity or the loading rate

    1D Plasticity Algorithms > 1D Computational Plasticity Assignment

    1D Computational plasticity assignment

    April 1, 2015 Carlos Agelet de Saracibar 65

  • Write a comprehensive deliverable report (10 pages) providing the data of the cyclic loading and material properties considered, the stress-strain curves, and the stress-time curves for the rate-dependent plasticity examples. Add suitable comments on the results, comparing the influence of the different material parameters and loading conditions.

    Add a printed copy of the subroutines as an Appendix

    1D Plasticity Algorithms > 1D Computational Plasticity Assignment

    1D Computational plasticity assignment

    April 1, 2015 Carlos Agelet de Saracibar 66

    Computational Solid MechanicsComputational PlasticityNmero de diapositiva 2Nmero de diapositiva 3Nmero de diapositiva 4Nmero de diapositiva 5Nmero de diapositiva 6Nmero de diapositiva 7Nmero de diapositiva 8Nmero de diapositiva 9Nmero de diapositiva 10Nmero de diapositiva 11Nmero de diapositiva 12Nmero de diapositiva 13Nmero de diapositiva 14Nmero de diapositiva 15Nmero de diapositiva 16Nmero de diapositiva 17Nmero de diapositiva 18Nmero de diapositiva 19Nmero de diapositiva 20Nmero de diapositiva 21Nmero de diapositiva 22Nmero de diapositiva 23Nmero de diapositiva 24Nmero de diapositiva 25Nmero de diapositiva 26Nmero de diapositiva 27Nmero de diapositiva 28Nmero de diapositiva 29Nmero de diapositiva 30Nmero de diapositiva 31Nmero de diapositiva 32Nmero de diapositiva 33Nmero de diapositiva 34Nmero de diapositiva 35Nmero de diapositiva 36Nmero de diapositiva 37Nmero de diapositiva 38Nmero de diapositiva 39Nmero de diapositiva 40Nmero de diapositiva 41Nmero de diapositiva 42Nmero de diapositiva 43Nmero de diapositiva 44Nmero de diapositiva 45Nmero de diapositiva 46Nmero de diapositiva 47Nmero de diapositiva 48Nmero de diapositiva 49Nmero de diapositiva 50Nmero de diapositiva 51Nmero de diapositiva 52Nmero de diapositiva 53Nmero de diapositiva 54Nmero de diapositiva 55Nmero de diapositiva 56Nmero de diapositiva 57Nmero de diapositiva 58Nmero de diapositiva 59Nmero de diapositiva 60Nmero de diapositiva 61Nmero de diapositiva 62Nmero de diapositiva 63Nmero de diapositiva 64Nmero de diapositiva 65Nmero de diapositiva 66