def les_update(u_ab, nut_, nut_form, dt, CG1, tstep, DynamicSmagorinsky, Cs,
               u_CG1, u_filtered, Lij, Mij, JLM, JMM, dim, tensdim, G_matr,
               G_under, ll, dummy, uiuj_pairs, Sijmats, Sijcomps, Sijfcomps,
               delta_CG1_sq, Qij, Nij, JNN, JQN, **NS_namespace):

    # Check if Cs is to be computed, if not update nut_ and break
    if tstep % DynamicSmagorinsky["Cs_comp_step"] != 0:
        # Update nut_
        nut_()
        # Break function
        return

    # All velocity components must be interpolated to CG1 then filtered
    for i in xrange(dim):
        # Interpolate to CG1
        ll.interpolate(u_CG1[i], u_ab[i])
        # Filter
        tophatfilter(unfiltered=u_CG1[i], filtered=u_filtered[i], **vars())

    # Compute Lij from dynamic modules function
    compute_Lij(u=u_CG1, uf=u_filtered, **vars())

    # Compute Mij from dynamic modules function
    alpha = 2.
    magS = compute_Mij(alphaval=alpha, u_nf=u_CG1, u_f=u_filtered, **vars())

    # Lagrange average Lij and Mij
    lagrange_average(J1=JLM, J2=JMM, Aij=Lij, Bij=Mij, **vars())

    # Now u needs to be filtered once more
    for i in xrange(dim):
        # Filter
        tophatfilter(unfiltered=u_filtered[i],
                     filtered=u_filtered[i],
                     weight=1,
                     **vars())

    # Compute Qij from dynamic modules function
    compute_Qij(uf=u_filtered, **vars())

    # Compute Nij from dynamic modules function
    alpha = 4.
    compute_Nij(alphaval=alpha, u_f=u_filtered, **vars())

    # Lagrange average Qij and Nij
    lagrange_average(J1=JQN, J2=JNN, Aij=Qij, Bij=Nij, **vars())

    # UPDATE Cs**2 = (JLM*JMM)/beta, beta = JQN/JNN
    beta = (JQN.vector().array() / JNN.vector().array()).clip(min=0.5)
    Cs.vector().set_local((np.sqrt(
        (JLM.vector().array() / JMM.vector().array()) / beta)))
    Cs.vector().apply("insert")
    tophatfilter(unfiltered=Cs, filtered=Cs, N=2, weight=1, **vars())
    Cs.vector().set_local(Cs.vector().array().clip(max=0.3))
    Cs.vector().apply("insert")

    # Update nut_
    nut_.vector().set_local(Cs.vector().array()**2 *
                            delta_CG1_sq.vector().array() * magS)
    nut_.vector().apply("insert")
def les_update(u_ab, nut_, nut_form, dt, CG1, tstep, 
            DynamicSmagorinsky, Cs, u_CG1, u_filtered, Lij, Mij,
            JLM, JMM, dim, tensdim, G_matr, G_under, ll,
            dummy, uiuj_pairs, Sijmats, Sijcomps, Sijfcomps, delta_CG1_sq, 
            Qij, Nij, JNN, JQN, **NS_namespace): 

    # Check if Cs is to be computed, if not update nut_ and break
    if tstep%DynamicSmagorinsky["Cs_comp_step"] != 0:
        # Update nut_
        nut_()
        # Break function
        return

    # All velocity components must be interpolated to CG1 then filtered
    for i in xrange(dim):
        # Interpolate to CG1
        ll.interpolate(u_CG1[i], u_ab[i])
        # Filter
        tophatfilter(unfiltered=u_CG1[i], filtered=u_filtered[i], **vars())

    # Compute Lij from dynamic modules function
    compute_Lij(u=u_CG1, uf=u_filtered, **vars())

    # Compute Mij from dynamic modules function
    alpha = 2.
    magS = compute_Mij(alphaval=alpha, u_nf=u_CG1, u_f=u_filtered, **vars())

    # Lagrange average Lij and Mij
    lagrange_average(J1=JLM, J2=JMM, Aij=Lij, Bij=Mij, **vars())

    # Now u needs to be filtered once more
    for i in xrange(dim):
        # Filter
        tophatfilter(unfiltered=u_filtered[i], filtered=u_filtered[i],
                weight=1, **vars())

    # Compute Qij from dynamic modules function
    compute_Qij(uf=u_filtered, **vars())

    # Compute Nij from dynamic modules function
    alpha = 4.
    compute_Nij(alphaval=alpha, u_f=u_filtered, **vars())

    # Lagrange average Qij and Nij
    lagrange_average(J1=JQN, J2=JNN, Aij=Qij, Bij=Nij, **vars())

    # UPDATE Cs**2 = (JLM*JMM)/beta, beta = JQN/JNN
    beta = (JQN.vector().array()/JNN.vector().array()).clip(min=0.5)
    Cs.vector().set_local((np.sqrt((JLM.vector().array()/JMM.vector().array())/beta)))
    Cs.vector().apply("insert")
    tophatfilter(unfiltered=Cs, filtered=Cs, N=2, weight=1, **vars())
    Cs.vector().set_local(Cs.vector().array().clip(max=0.3))
    Cs.vector().apply("insert")

    # Update nut_
    nut_.vector().set_local(Cs.vector().array()**2 * delta_CG1_sq.vector().array() * magS)
    nut_.vector().apply("insert")
示例#3
0
def les_update(u_ab, nut_, nut_form, dt, CG1, delta, tstep, 
            DynamicSmagorinsky, Cs, u_CG1, u_filtered, Lij, Mij,
            JLM, JMM, dim, tensdim, G_matr, G_under, ll,
            dummy, uiuj_pairs, Sijmats, Sijcomps, Sijfcomps, delta_CG1_sq, 
            **NS_namespace):

    # Check if Cs is to be computed, if not update nut_ and break
    if tstep%DynamicSmagorinsky["Cs_comp_step"] != 0:
        # Update nut_
        nut_()
        # Break function
        return
    
    # All velocity components must be interpolated to CG1 then filtered
    for i in xrange(dim):
        # Interpolate to CG1
        ll.interpolate(u_CG1[i], u_ab[i])
        # Filter
        tophatfilter(unfiltered=u_CG1[i], filtered=u_filtered[i], **vars())

    # Compute Lij applying dynamic modules function
    compute_Lij(u=u_CG1, uf=u_filtered, **vars())

    # Compute Mij applying dynamic modules function
    alpha = 2.0
    magS = compute_Mij(alphaval=alpha, u_nf=u_CG1, u_f=u_filtered, **vars())
    
    # Lagrange average Lij and Mij
    lagrange_average(J1=JLM, J2=JMM, Aij=Lij, Bij=Mij, **vars())

    # Update Cs = sqrt(JLM/JMM) and filter/smooth Cs, then clip at 0.3. 
    """
    Important that the term in nut_form is Cs**2 and not Cs
    since Cs here is stored as sqrt(JLM/JMM).
    """
    Cs.vector().set_local(np.sqrt(JLM.vector().array()/JMM.vector().array()))
    Cs.vector().apply("insert")
    tophatfilter(unfiltered=Cs, filtered=Cs, N=2, weight=1., **vars())
    Cs.vector().set_local(Cs.vector().array().clip(max=0.3))
    Cs.vector().apply("insert")

    # Update nut_
    nut_.vector().set_local(Cs.vector().array()**2 * delta_CG1_sq.vector().array() * magS)
    nut_.vector().apply("insert")
示例#4
0
def les_update(u_ab, nut_, nut_form, dt, CG1, delta, tstep, DynamicSmagorinsky,
               Cs, u_CG1, u_filtered, Lij, Mij, JLM, JMM, dim, tensdim, G_matr,
               G_under, ll, dummy, uiuj_pairs, Sijmats, Sijcomps, Sijfcomps,
               delta_CG1_sq, **NS_namespace):

    # Check if Cs is to be computed, if not update nut_ and break
    if tstep % DynamicSmagorinsky["Cs_comp_step"] != 0:
        # Update nut_
        nut_()
        # Break function
        return

    # All velocity components must be interpolated to CG1 then filtered
    for i in xrange(dim):
        # Interpolate to CG1
        ll.interpolate(u_CG1[i], u_ab[i])
        # Filter
        tophatfilter(unfiltered=u_CG1[i], filtered=u_filtered[i], **vars())

    # Compute Lij applying dynamic modules function
    compute_Lij(u=u_CG1, uf=u_filtered, **vars())

    # Compute Mij applying dynamic modules function
    alpha = 2.0
    magS = compute_Mij(alphaval=alpha, u_nf=u_CG1, u_f=u_filtered, **vars())

    # Lagrange average Lij and Mij
    lagrange_average(J1=JLM, J2=JMM, Aij=Lij, Bij=Mij, **vars())

    # Update Cs = sqrt(JLM/JMM) and filter/smooth Cs, then clip at 0.3.
    """
    Important that the term in nut_form is Cs**2 and not Cs
    since Cs here is stored as sqrt(JLM/JMM).
    """
    Cs.vector().set_local(np.sqrt(JLM.vector().array() / JMM.vector().array()))
    Cs.vector().apply("insert")
    tophatfilter(unfiltered=Cs, filtered=Cs, N=2, weight=1., **vars())
    Cs.vector().set_local(Cs.vector().array().clip(max=0.3))
    Cs.vector().apply("insert")

    # Update nut_
    nut_.vector().set_local(Cs.vector().array()**2 *
                            delta_CG1_sq.vector().array() * magS)
    nut_.vector().apply("insert")