NONLINEAR DYNAMIC FINITE ELEMENT ANALYSIS IN ZSOIL : with application to geomechanics & structures Th.Zimmermann copyright zace services ltd
Far-field BC needed 2-phase medium Ground motion
For time being in Z_Soil: limited structural dynamics a, or d t
with some extensions analysis by geomod
STATICS RECALL
STATIC EQUILIBRIUM STATEMENT, 1-PHASE Boundary value problem displacement imposed on u Equilibrium 12 +(12 /x2)dx2 12 f1 traction imposed on 11 11+(11/x1)dx1 x2 x1 dx1 direction 1: (11/x1)dx1dx2+(12 /x2) dx1dx2+ f1dx1dx2=0 L(u)= ij/xj + fi=0 (Differential equation of equilibrium)
FORMAL DIFFERENTIAL PROBLEM STATEMENT 1-phase,linear or nonlinear) (equilibrium) (displ.boundary cond.) (traction bound. cond.) Incremental elasto-plastic constitutive equation: NB: Time is steps
Kd=F MATRIX FORM -DISCRETIZATION LEADS TO THE MATRIX FORM…. FOR LINEAR STATICS Kd=F ( K=stiffness matrix, F=vector of nodal forces d=vector of nodal displacements)
DYNAMICS
DYNAMIC EQUILIBRIUM STATEMENT, 1-PHASE Boundary value problem displacement imposed on u Equilibrium traction imposed on 12 +(12 /x2)dx2 12 f1 11 11+(11/x1)dx1 x2 x1 dx1 direction 1: (11/x1)dx1dx2+(12 /x2) dx1dx2+ f1dx1dx2=0 L(u)= ij/xj + fi=0
FORMAL DIFFERENTIAL PROBLEM STATEMENT Deformation(1-phase): (equilibrium) (displ.boundary cond.) (traction bound. cond.) (initial conditions) Incremental elasto-plastic constitutive equation: NB: Time is real
Kd=F Ma(t)+[Cv(t)]+Kd(t) =F(t) COMPARING MATRIX FORMS STATICS (linear case) Kd=F We obtain (Linear system size: Ndofs=Nnodes x NspaceDim, -d=nodal displacements -F=nodal forces) DYNAMICS (linear case) Ma(t)+[Cv(t)]+Kd(t) =F(t) where We obtain (Linear system size: Ndofs=Nnodes x NspaceDim, But 3xNdofs unknowns) optional
SOLUTION TECHNIQUES -MODAL ANALYSIS -FREQUENCY DOMAIN ANALYSIS both essentially restricted to linear problems -DIRECT TIME INTEGRATION appropriate for a fully nonlinear analysis
DIRECT TIME INTEGRATION (linear case)…a) Using Newmark’s algorithm : At each time step, solve:
DIRECT TIME INTEGRATION (linear case)…b)
Ma(t)+Cv(t)+Kd(t)=F(t) >>>> MATRIX FORMS STATICS (linear case) Kd=F DYNAMICS (linear case) Ma(t)+Cv(t)+Kd(t)=F(t) >>>> at any tn+1 we have an equivalent static problem K*dn+1=F*n+1 an+1=………… vn+1=…………
NEWMARK IS A 1-STEP ALGORITHM All information to compute solution at time tn+1, is in solution at time tn , restart is easy
NUMERICAL ( ALGORITHMIC) DAMPING CAN EXIST and varies with parameters (γ ,β) ● ● Newmark(0.6,0.3025) ● ● HHT ● ● ● ● Newmark(0.5,0.25) ● ● ● ● ● ● ● IT MAY BE WANTED OR NOT
DISCRETIZATION APPROXIMATES HIGH FREQUENCIES Exact sol.: Filtering of high frequencies may be desirable
HHT Hilber-Hughes-Taylor α method HHT filters high frequencies without damping low frequencies
NUMERICAL ( ALGORITHMIC) DAMPING CAN EXIST and varies with parameters (γ ,β) ● ● ● ● HHT(-0.3) ● ● ● ● ● ● ● ● ● ● ● IT MAY BE WANTED OR NOT
Algorithmic data for Newmark …or HHT(under CONTROL/AN..
Mass can be CONSISTENT (as obtained by FEM) or LUMPED (concentrated at (some) nodes) Only lumped masses are available in ZSOIL Lumped masses tend to lead to underestimate frequencies
Lumped masses tend to lead to underestimate frequencies: ILLUSTRATION
C=αM+βK is RAYLEIGH DAMPING RAYLEIGH DAMPING a) Recall: Ma(t)+Cv(t)+Kd(t)=F(t) C=αM+βK is RAYLEIGH DAMPING α,β:constants This form of damping is not representative of physical reality, in general. Its success is due to the fact that it maintains mode decoupling in modal analysis
RAYLEIGH DAMPING b): PARENTHESIS ON MODAL ANALYSIS
RAYLEIGH DAMPING d) COMPARING THE MODAL EQUATION WITH THE 1DOF VISCOUSLY DAMPED OSCILLATOR YIELDS:
RAYLEIGH DAMPING e)
RAYLEIGH DAMPING f) this can be plotted
2 (ω,ξ) pairs are used to define α0,β0 in ZSOIL
NONLINEAR DYNAMICS
CONSTITUTIVE MODEL: ELASTIC-PERFECTLY PLASTIC 1- dimensional E y this problem is non-linear
FROM LOCAL TO GLOBAL NONLINEAR RESPONSE
SOLUTION OF LINEARIZED PROBLEM, static case Nonlinear problem to solve d Linearize at , w. Taylor exp. hence the following algorithm: i: iteration n: step
THE PROBLEM IS NONLINEAR & THEREFORE NEEDS ITERATIONS tends to 0 Fn+1 Fn i: iteration n: step d
d Fn Fn+1 NEWTON- RAPHSON & al. ITERATIVES SCHEMES d Fn Fn+1 KTo 2.Constant stiffness,use KTo till i: iteration n: step 3.Modified NR, update KT opportunistically, each step e.g.,till 1.Full NR, update KT at each step & iteration, till 4. BFGS, “optimal”secant scheme
TOLERANCES ITERATIVE ALGORITHMS
Ma(t)+Cv(t)+N(d(t))=F(t) MATRIX FORMS STATICS (nonlinear case) N(d)=F DYNAMICS (nonlinear case) Ma(t)+Cv(t)+N(d(t))=F(t) >>>> (e.g.)
DIRECT TIME INTEGRATION (nonlinear case) Using Newmark’s algorithm (or Hilber’s): At each time step, solve:
Ma(t)+Cv(t)+N(d(t))=F(t) or Ma(t)+N(d,v)=F(t) MATRIX FORMS STATICS (nonlinear case) N(d)=F DYNAMICS (nonlinear case) Ma(t)+Cv(t)+N(d(t))=F(t) or Ma(t)+N(d,v)=F(t) >>>>at any tn+1, we have an equivalent static problem N*(dn+1)=F*n+1 an+1=………… vn+1=………… Like for linear case
SEISMIC INPUT a >>> equilibrium >>Fin+Fdamp+Fel = Fext
SEISMIC INPUT b yields
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