def set_eigenvalue_problem_type_2(self, Rayleigh, Prandtl, **kwargs):
self.problem = de.EVP(self.domain,
variables=self.variables,
eigenvalue='nu',
tolerance=1e-6)
self.problem.substitutions['dt(f)'] = "(0*f)"
self.set_equations(Rayleigh, Prandtl, EVP_2=True, **kwargs)
def test_wave_sparse_evp(benchmark, x_basis_class, Nx, dtype):
n_comp = 5
# Domain
x_basis = x_basis_class('x', Nx, interval=(-1, 1))
domain = de.Domain([x_basis], np.float64)
# Problem
problem = de.EVP(domain, variables=['u', 'ux'], eigenvalue='k2')
problem.add_equation("ux - dx(u) = 0")
problem.add_equation("dx(ux) + k2*u = 0")
problem.add_bc("left(u) = 0")
problem.add_bc("right(u) = 0")
# Solver
solver = problem.build_solver()
solver.solve_sparse(solver.pencils[0], n_comp, target=0)
# Filter infinite/nan eigenmodes
finite = np.isfinite(solver.eigenvalues)
solver.eigenvalues = solver.eigenvalues[finite]
solver.eigenvectors = solver.eigenvectors[:, finite]
# Sort eigenmodes by eigenvalue
order = np.argsort(solver.eigenvalues)
solver.eigenvalues = solver.eigenvalues[order]
solver.eigenvectors = solver.eigenvectors[:, order]
# Check solution
n = np.arange(n_comp)
exact_eigenvalues = ((1 + n) * np.pi / 2)**2
assert np.allclose(solver.eigenvalues[:n_comp], exact_eigenvalues)
def test_rbc_growth(Nz, sparse):
z = de.Chebyshev('z', Nz, interval=(0, 1))
d = de.Domain([z])
rayleigh_benard = de.EVP(d, ['p', 'b', 'u', 'w', 'bz', 'uz', 'wz'],
eigenvalue='omega')
rayleigh_benard.parameters['k'] = 3.117 #horizontal wavenumber
rayleigh_benard.parameters['Ra'] = 1708. #Rayleigh number, rigid-rigid
rayleigh_benard.parameters['Pr'] = 1 #Prandtl number
rayleigh_benard.parameters['dzT0'] = 1
rayleigh_benard.substitutions['dt(A)'] = 'omega*A'
rayleigh_benard.substitutions['dx(A)'] = '1j*k*A'
rayleigh_benard.add_equation("dx(u) + wz = 0")
rayleigh_benard.add_equation(
"dt(u) - Pr*(dx(dx(u)) + dz(uz)) + dx(p) = -u*dx(u) - w*uz")
rayleigh_benard.add_equation(
"dt(w) - Pr*(dx(dx(w)) + dz(wz)) + dz(p) - Ra*Pr*b = -u*dx(w) - w*wz")
rayleigh_benard.add_equation(
"dt(b) - w*dzT0 - (dx(dx(b)) + dz(bz)) = -u*dx(b) - w*bz")
rayleigh_benard.add_equation("dz(u) - uz = 0")
rayleigh_benard.add_equation("dz(w) - wz = 0")
rayleigh_benard.add_equation("dz(b) - bz = 0")
rayleigh_benard.add_bc('left(b) = 0')
rayleigh_benard.add_bc('right(b) = 0')
rayleigh_benard.add_bc('left(w) = 0')
rayleigh_benard.add_bc('right(w) = 0')
rayleigh_benard.add_bc('left(u) = 0')
rayleigh_benard.add_bc('right(u) = 0')
EP = eig.Eigenproblem(rayleigh_benard, sparse=sparse)
growth, index, freq = EP.growth_rate({})
assert np.allclose([growth, freq[0]], [0.0018125573647729994, 0.])
def build_solver(domain, domain_old, N, N_old, k):
# We have N >= N_old
# but N/2 < N_old
T_old = domain_old.new_field()
T_old.set_scales(512/N_old)
data = np.loadtxt(dir + '/T.dat')
T_old['g'] = data[1,:]
T0 = domain.new_field()
T0['c'][:int(N/2)] = T_old['c'][:int(N/2)]
T0['c'][int(N/2):int(N/2) + int(N_old/2)] = T_old['c'][N_old:]
# T0['c'][:N_old] = T_old['c'][:N_old]
# T0['c'][N:N+int(N_old/2)] = T_old['c'][N_old:]
rho = domain.new_field()
T0.set_scales(1)
rho.require_grid_space()
np.place(rho['g'], T0['g']>0, -1)
np.place(rho['g'], T0['g']<=0, S)
rho['g'] *= T0['g']
N2 = rho.differentiate(0)
z = domain.grid(0)
T0z = T0.differentiate(0)
T0z['g'][z<0.45] *= 0
T0z.require_coeff_space()
logger.info(k)
problem = de.EVP(domain, variables=['p','T','u','w','Tz','uz'], eigenvalue='om')
problem.parameters['nu'] = nu
problem.parameters['kappa'] = kappa
problem.parameters['T0z'] = T0z
problem.parameters['S'] = S
problem.substitutions['dt(A)'] = "-1j*om*A"
problem.parameters['kx'] = 2*np.pi*k
problem.substitutions['dx(A)'] = "1j*kx*A"
problem.add_equation("dx(u) + dz(w) = 0")
problem.add_equation("dt(T) - kappa*(dx(dx(T)) + dz(Tz)) + w*T0z = 0")
problem.add_equation("dt(u) - nu*(dx(dx(u)) + dz(uz)) + dx(p) = 0")
problem.add_equation("dt(w) - nu*(dx(dx(w)) - dz(dx(u))) + dz(p) + S*T = 0")
problem.add_equation("Tz - dz(T) = 0")
problem.add_equation("uz - dz(u) = 0")
problem.add_bc("left(uz) = 0")
problem.add_bc("left(w) = 0")
problem.add_bc("left(T) = 0")
problem.add_bc("right(uz) = 0")
problem.add_bc("right(w) = 0")
problem.add_bc("right(T) = 0")
solver = problem.build_solver()
return solver
def test_half_qho_dense_evp(benchmark, x_basis_class, Nx, dtype):
n_comp = 10
stretch = 0.1
# Domain
x_basis = x_basis_class('x', Nx, edge=0, stretch=stretch)
domain = de.Domain([x_basis], np.float64)
# Problem
problem = de.EVP(domain, variables=['ψ', 'ψx'], eigenvalue='E')
problem.substitutions["V"] = "x**2 / 2"
problem.substitutions["H(ψ,ψx)"] = "-dx(ψx)/2 + V*ψ"
problem.add_equation("ψx - dx(ψ) = 0", tau=True)
problem.add_equation("H(ψ,ψx) - E*ψ = 0", tau=False)
problem.add_bc("left(ψ) = 0")
# Solver
solver = problem.build_solver()
solver.solve_dense(solver.pencils[0])
# Filter infinite/nan eigenmodes
finite = np.isfinite(solver.eigenvalues)
solver.eigenvalues = solver.eigenvalues[finite]
solver.eigenvectors = solver.eigenvectors[:, finite]
# Sort eigenmodes by eigenvalue
order = np.argsort(solver.eigenvalues)
solver.eigenvalues = solver.eigenvalues[order]
solver.eigenvectors = solver.eigenvectors[:, order]
# Check solution
n = np.arange(n_comp)
exact_eigenvalues = 2 * n + 3 / 2
assert np.allclose(solver.eigenvalues[:n_comp], exact_eigenvalues)
def test_qho_stretch_dense_evp(benchmark, x_basis_class, Nx, dtype):
n_comp = 10
# Domain
x_basis = x_basis_class('x', Nx, center=0, stretch=1.0)
domain = de.Domain([x_basis], np.float64)
# Problem
sign_x = domain.new_field()
sign_x.meta['x']['envelope'] = False
sign_x['g'] = np.sign(domain.grid(0))
problem = de.EVP(domain, variables=['ψ', 'ψx'], eigenvalue='E')
problem.parameters['sign_x'] = sign_x
problem.substitutions["V"] = "abs(x) / 2"
problem.substitutions[
"H(ψ,ψx)"] = "-(4*sign_x*x*dx(ψx) + 2*sign_x*ψx)/2 + V*ψ"
problem.add_equation("ψx - dx(ψ) = 0", tau=False)
problem.add_equation("H(ψ,ψx) - E*ψ = 0", tau=False)
# Solver
solver = problem.build_solver()
solver.solve_dense(solver.pencils[0])
# Filter infinite/nan eigenmodes
finite = np.isfinite(solver.eigenvalues)
solver.eigenvalues = solver.eigenvalues[finite]
solver.eigenvectors = solver.eigenvectors[:, finite]
# Sort eigenmodes by eigenvalue
order = np.argsort(np.abs(solver.eigenvalues))
solver.eigenvalues = solver.eigenvalues[order]
solver.eigenvectors = solver.eigenvectors[:, order]
# Check solution
n = np.arange(n_comp)
exact_eigenvalues = n + 1 / 2
assert np.allclose(solver.eigenvalues[:n_comp], exact_eigenvalues)
def eigenmodes_inviscid_1d(param, kx, comm=MPI.COMM_SELF):
"""Solve normal modes for any kx in 1D."""
# Background BVP
domain, p_full, a_full = background.solve_hydrostatic_pressure(
param, np.complex128, comm=comm)
p_full, p_trunc, a_full, a_trunc, heq, N2 = background.truncate_background(
param, p_full, a_full)
# Adiabatic viscous fully-compressible hydrodynamics
problem = de.EVP(domain,
variables=['a1', 'p1', 'u', 'w', 'uz', 'wz'],
eigenvalue='σ',
ncc_cutoff=param.ivp_cutoff,
entry_cutoff=param.matrix_cutoff)
problem.meta[:]['z']['dirichlet'] = True
problem.parameters['a0'] = a_trunc
problem.parameters['p0'] = p_trunc
problem.parameters['a0z'] = a_trunc.differentiate('z')
problem.parameters['p0z'] = p_trunc.differentiate('z')
problem.substitutions['a0x'] = '0'
problem.substitutions['p0x'] = '0'
problem.parameters['U'] = 0 # Look at modes in local frame
problem.substitutions['μ'] = '0' # Solve for inviscid modes
problem.parameters['γ'] = param.γ
problem.parameters['kx'] = kx # Instead of k_tide
problem.parameters['Lx'] = param.Lx
problem.parameters['Lz'] = param.Lz
problem.substitutions['dt(A)'] = "σ*A"
problem.substitutions['dx(A)'] = "1j*kx*A"
problem.substitutions['ux'] = "dx(u)"
problem.substitutions['wx'] = "dx(w)"
problem.substitutions['div_u'] = "ux + wz"
problem.substitutions['txx'] = "μ*(2*ux - 2/3*div_u)"
problem.substitutions['txz'] = "μ*(wx + uz)"
problem.substitutions['tzz'] = "μ*(2*wz - 2/3*div_u)"
problem.substitutions['φ'] = "0"
problem.substitutions['cs20'] = "γ*p0*a0"
problem.add_equation(
"dt(u) + U*ux + a0*dx(p1) + a1*p0x - a0*(dx(txx) + dz(txz)) = - (u*ux + w*uz) - a1*dx(p1) + a1*(dx(txx) + dz(txz)) - dx(φ)"
)
problem.add_equation(
"dt(w) + U*wx + a0*dz(p1) + a1*p0z - a0*(dx(txz) + dz(tzz)) = - (u*wx + w*wz) - a1*dz(p1) + a1*(dx(txz) + dz(tzz)) - dz(φ)"
)
problem.add_equation(
"dt(a1) + U*dx(a1) + u*a0x + w*a0z - a0*div_u = - (U*a0x + u*dx(a1) + w*dz(a1)) + a1*div_u"
)
problem.add_equation(
"dt(p1) + U*dx(p1) + u*p0x + w*p0z + γ*p0*div_u = - (U*p0x + u*dx(p1) + w*dz(p1)) - γ*p1*div_u"
)
problem.add_equation("uz - dz(u) = 0")
problem.add_equation("wz - dz(w) = 0")
#problem.add_bc("left(txz) = 0")
#problem.add_bc("right(txz) = 0")
problem.add_bc("left(uz - dz(u)) = 0")
problem.add_bc("left(w) = 0")
problem.add_bc("right(w) = 0")
return domain, problem
def set_EVP(self, *args, ncc_cutoff=1e-10, tolerance=1e-10, **kwargs):
"""
Constructs an eigenvalue problem of the current objeect's equation set.
Note that dt(f) = omega * f, not i * omega * f, so real parts of omega
are growth / shrinking nodes, imaginary parts are oscillating.
"""
self.problem_type = 'EVP'
self.problem = de.EVP(self.domain, variables=self.variables, eigenvalue='omega', ncc_cutoff=ncc_cutoff, tolerance=tolerance)
self.problem.substitutions['dt(f)'] = "omega*f"
self.set_equations(*args, **kwargs)
def rotating_rbc_evp(Ek, Ra, k, Nz=24):
z = de.Chebyshev('z', Nz, interval=(0, 1))
d = de.Domain([z], comm=MPI.COMM_SELF)
variables = ['T', 'Tz', 'p', 'u', 'v', 'w', 'Ox', 'Oy']
problem = de.EVP(d, variables, eigenvalue='omega')
#Parameters
problem.parameters['kx'] = k / np.sqrt(2) #horizontal wavenumber (x)
problem.parameters['ky'] = k / np.sqrt(2) #horizontal wavenumber (y)
problem.parameters['Ra'] = Ra #Rayleigh number
problem.parameters['Pr'] = 1 #Prandtl number
problem.parameters['Pm'] = 1 #Magnetic Prandtl number
problem.parameters['E'] = Ek
problem.parameters['dzT0'] = -1
#Substitutions
problem.substitutions["dt(A)"] = "omega*A"
problem.substitutions["dx(A)"] = "1j*kx*A"
problem.substitutions["dy(A)"] = "1j*ky*A"
problem.substitutions['UdotGrad(A,A_z)'] = '(u*dx(A) + v*dy(A) + w*(A_z))'
problem.substitutions['Lap(A,A_z)'] = '(dx(dx(A)) + dy(dy(A)) + dz(A_z))'
problem.substitutions["Oz"] = "dx(v)-dy(u)"
problem.substitutions["Kz"] = "dx(Oy)-dy(Ox)"
problem.substitutions["Ky"] = "dz(Ox)-dx(Oz)"
problem.substitutions["Kx"] = "dy(Oz)-dz(Oy)"
#Dimensionless parameter substitutions
problem.substitutions["inv_Re_ff"] = "(Pr/Ra)**(1./2.)"
problem.substitutions["inv_Pe_ff"] = "(Ra*Pr)**(-1./2.)"
#Equations
problem.add_equation(
"dt(T) + w*dzT0 - inv_Pe_ff*Lap(T, Tz) = -UdotGrad(T, Tz)")
problem.add_equation(
"dt(u) + dx(p) + inv_Re_ff*(Kx - v/E) = v*Oz - w*Oy")
problem.add_equation(
"dt(v) + dy(p) + inv_Re_ff*(Ky + u/E) = w*Ox - u*Oz")
problem.add_equation(
"dt(w) + dz(p) + inv_Re_ff*(Kz) - T = u*Oy - v*Ox")
problem.add_equation("dx(u) + dy(v) + dz(w) = 0")
problem.add_equation("Ox - (dy(w) - dz(v)) = 0")
problem.add_equation("Oy - (dz(u) - dx(w)) = 0")
problem.add_equation("Tz - dz(T) = 0")
bcs = ['T', 'u', 'v', 'w']
for bc in bcs:
problem.add_bc(" left({}) = 0".format(bc))
problem.add_bc("right({}) = 0".format(bc))
return problem
def set_eigenvalue_problem(self,
*args,
ncc_cutoff=1e-10,
tol=1e-6,
**kwargs):
self.problem_type = 'EVP'
self.problem = de.EVP(self.domain,
variables=self.variables,
eigenvalue='omega',
ncc_cutoff=ncc_cutoff,
tolerance=tol)
self.problem.substitutions['dt(f)'] = "omega*f"
self.set_equations(*args, **kwargs)
def _build_hires(self):
"""builds a high-resolution EVP from the EVP passed in at
construction
"""
old_evp = self.EVP
old_x = old_evp.domain.bases[0]
x = tools.basis_from_basis(old_x, self.factor)
d = de.Domain([x], comm=old_evp.domain.dist.comm)
self.EVP_hires = de.EVP(d,
old_evp.variables,
old_evp.eigenvalue,
ncc_cutoff=old_evp.ncc_kw['cutoff'],
max_ncc_terms=old_evp.ncc_kw['max_terms'],
tolerance=self.EVP.tol)
for k, v in old_evp.substitutions.items():
self.EVP_hires.substitutions[k] = v
for k, v in old_evp.parameters.items():
if type(v) == Field: #NCCs
new_field = d.new_field()
v.set_scales(self.factor, keep_data=True)
new_field['g'] = v['g']
self.EVP_hires.parameters[k] = new_field
else: #scalars
self.EVP_hires.parameters[k] = v
for e in old_evp.equations:
self.EVP_hires.add_equation(e['raw_equation'])
try:
for b in old_evp.boundary_conditions:
self.EVP_hires.add_bc(b['raw_equation'])
except AttributeError:
# after version befc23584fea, Dedalus no longer
# distingishes BCs from other equations
pass
self.hires_solver = self.EVP_hires.build_solver()
def max_growth_rate(Nz, Prandtl, Rayleigh, kx):
"""Calculate maximum linear growth-rate for no-slip RBC."""
# Create bases and domain
# Use COMM_SELF so keep calculations independent between processes
z_basis = de.Chebyshev('z', Nz, interval=(-1/2, 1/2))
domain = de.Domain([z_basis], grid_dtype=np.complex128, comm=MPI.COMM_SELF)
# 2D Boussinesq hydrodynamics, with no-slip boundary conditions
# Use substitutions for x and t derivatives
problem = de.EVP(domain, variables=['p','b','u','w','bz','uz','wz'], eigenvalue='omega')
problem.parameters['P'] = (Rayleigh * Prandtl)**(-1/2)
problem.parameters['R'] = (Rayleigh / Prandtl)**(-1/2)
problem.parameters['F'] = F = 1
problem.parameters['kx'] = kx
problem.substitutions['dx(A)'] = "1j*kx*A"
problem.substitutions['dt(A)'] = "-1j*omega*A"
problem.add_equation("dx(u) + wz = 0")
problem.add_equation("dt(b) - P*(dx(dx(b)) + dz(bz)) - F*w = -(u*dx(b) + w*bz)")
problem.add_equation("dt(u) - R*(dx(dx(u)) + dz(uz)) + dx(p) = -(u*dx(u) + w*uz)")
problem.add_equation("dt(w) - R*(dx(dx(w)) + dz(wz)) + dz(p) - b = -(u*dx(w) + w*wz)")
problem.add_equation("bz - dz(b) = 0")
problem.add_equation("uz - dz(u) = 0")
problem.add_equation("wz - dz(w) = 0")
problem.add_bc("left(b) = 0")
problem.add_bc("left(u) = 0")
problem.add_bc("left(w) = 0")
problem.add_bc("right(b) = 0")
problem.add_bc("right(u) = 0")
problem.add_bc("integ(p, 'z') = 0")
# Solve for eigenvalues
solver = problem.build_solver()
solver.solve(solver.pencils[0])
# Return largest finite imaginary part
ev = solver.eigenvalues
ev = ev[np.isfinite(ev)]
return np.max(ev.imag)
def test_non_constant(Nx, sparse, ordinal):
x = de.Chebyshev('x', Nx, interval=(0, 5))
d = de.Domain([
x,
])
prob = de.EVP(d, ['y', 'yx', 'yxx', 'yxxx'], 'sigma')
prob.add_equation(
"dx(yxxx) -0.02*x*x*yxx -0.04*x*yx + (0.0001*x*x*x*x - 0.02)*y - sigma*y = 0"
)
prob.add_equation("dx(yxx) - yxxx = 0")
prob.add_equation("dx(yx) - yxx = 0")
prob.add_equation("dx(y) - yx = 0")
prob.add_bc("left(y) = 0")
prob.add_bc("right(y) = 0")
prob.add_bc("left(yx) = 0")
prob.add_bc("right(yx) = 0")
EP = Eigenproblem(prob, use_ordinal=ordinal)
EP.solve(sparse=sparse)
indx = EP.evalues_good.argsort()
five_evals = EP.evalues_good[indx][0:5]
print("First five good eigenvalues are: ")
print(five_evals)
print(five_evals[-1])
reference = np.array([
0.86690250239956 + 0j, 6.35768644786998 + 0j, 23.99274694653769 + 0j,
64.97869559403952 + 0j, 144.2841396045761 + 0j
])
assert np.allclose(reference, five_evals, rtol=1e-4)
nu['g'] = Nus[tind, :]
U = domain.new_field(name='U')
U['g'] = Us[tind, :]
Uz = domain.new_field(name='Uz')
Uz = U.differentiate(z_basis)
V = domain.new_field(name='V')
V['g'] = Vs[tind, :]
Vz = domain.new_field(name='Vz')
Vz['g'] = Vzs[tind, :]
Bz = domain.new_field(name='Bz')
B = domain.new_field(name='B')
B['g'] = Bs[tind, :]
Bz = B.differentiate(z_basis)
problem = de.EVP(domain,
variables=['u', 'v', 'w', 'b', 'p', 'uz', 'vz', 'wz', 'bz'],
eigenvalue='omg',
tolerance=1e-10)
problem.parameters['tht'] = tht
problem.parameters['U'] = U
problem.parameters['V'] = V
problem.parameters['B'] = B
problem.parameters['Uz'] = Uz
problem.parameters['Vz'] = Vz
problem.parameters['Bz'] = Bz
problem.parameters['N'] = 3.5e-3
problem.parameters['f'] = 1e-4
problem.parameters['kap'] = kap
problem.parameters['nu'] = nu
problem.parameters['k'] = 0.
problem.parameters['l'] = l
import dedalus.public as de
import numpy as np
import matplotlib.pyplot as plt
import logging
import time
logger = logging.getLogger(__name__)
# Domain
Nx = 128
x_basis = de.Chebyshev('x', Nx, interval=(-1, 1))
domain = de.Domain([x_basis], np.float64)
# Problem
problem = de.EVP(domain, variables=['u', 'u_x'],eigenvalue='l')
problem.meta[:]['x']['dirichlet'] = True
problem.add_equation("l*u + dx(u_x) = 0")
problem.add_equation("u_x - dx(u) = 0")
problem.add_bc("left(u) = 0")
problem.add_bc("right(u) = 0")
# Solver
solver = problem.build_solver()
t1 = time.time()
solver.solve_dense(solver.pencils[0])
t2 = time.time()
logger.info('Elapsed solve time: %f' %(t2-t1))
# Filter infinite/nan eigenmodes
finite = np.isfinite(solver.eigenvalues)
y(0) = y(5) = y'(0) = y'(5) = 0
NB: I corrected a typo
"""
import dedalus.public as de
from eigentools import Eigenproblem, CriticalFinder
x = de.Chebyshev('x', 50, interval=(0, 5))
d = de.Domain([
x,
])
prob = de.EVP(d, ['y', 'yx', 'yxx', 'yxxx'], 'sigma')
c3 = d.new_field(name='c3')
c1 = d.new_field(name='c1')
c01 = d.new_field(name='c01')
xx = x.grid()
# this is not a reasonable way to do this; it's just to test non-constant coefficients
c3['g'] = -0.02 * xx**2
c1['g'] = -0.04 * xx
c01['g'] = 0.0001 * xx**4
prob.parameters['c3'] = c3
prob.parameters['c1'] = c1
prob.parameters['c01'] = c01
prob.parameters['c02'] = -0.02
matplotlib.use('Agg')
from mpi4py import MPI
from eigentools import Eigenproblem, CriticalFinder
import time
import dedalus.public as de
import numpy as np
import matplotlib.pylab as plt
comm = MPI.COMM_WORLD
# Define the Orr-Somerfeld problem in Dedalus:
z = de.Chebyshev('z', 50)
d = de.Domain([z], comm=MPI.COMM_SELF)
orr_somerfeld = de.EVP(d, ['w', 'wz', 'wzz', 'wzzz'], 'sigma')
orr_somerfeld.parameters['alpha'] = 1.
orr_somerfeld.parameters['Re'] = 10000.
orr_somerfeld.add_equation(
'dz(wzzz) - 2*alpha**2*wzz + alpha**4*w - sigma*(wzz-alpha**2*w)-1j*alpha*(Re*(1-z**2)*(wzz-alpha**2*w) + 2*Re*w) = 0 '
)
orr_somerfeld.add_equation('dz(w)-wz = 0')
orr_somerfeld.add_equation('dz(wz)-wzz = 0')
orr_somerfeld.add_equation('dz(wzz)-wzzz = 0')
orr_somerfeld.add_bc('left(w) = 0')
orr_somerfeld.add_bc('right(w) = 0')
orr_somerfeld.add_bc('left(wz) = 0')
orr_somerfeld.add_bc('right(wz) = 0')
def set_eigenvalue_problem(self, *args, **kwargs):
self._set_domain()
self.problem = de.EVP(self.domain, variables=self.variables, eigenvalue='omega')
self.problem.substitutions['dt(f)'] = "omega*f"
self.set_equations(*args, **kwargs)
structure = heated_polytrope(nz, γ, ε, n_h)
h0 = d.Field(name='h0', bases=zb)
θ0 = d.Field(name='θ0', bases=zb)
Υ0 = d.Field(name='Υ0', bases=zb)
s0 = d.Field(name='s0', bases=zb)
h0['g'] = structure['h']['g']
θ0['g'] = structure['θ']['g']
Υ0['g'] = structure['Υ']['g']
s0['g'] = structure['s']['g']
logger.info(structure)
c = de.CartesianCoordinates('z')
R_inv = d.Field(name='R_inv')
ρ0 = np.exp(Υ0).evaluate()
# Υ = ln(ρ), θ = ln(h)
problem = de.EVP([u, Υ, θ, s, τ_u1, τ_u2, τ_s1, τ_s2], eigenvalue=R_inv)
problem.add_equation(
(ρ0 *
(1 / Ma2 * (h0 * grad(θ) + grad(h0) * θ) - 1 / Ma2 * s_c_over_c_P * h0 *
(grad(s) + θ * grad(s0))) - R_inv * viscous_terms + lift(τ_u1, -1) +
lift(τ_u2, -2), 0))
problem.add_equation(
(h0 * (div(u) + u @ grad(Υ0)) + R_inv * lift(τ_u2, -1) @ ez, 0))
problem.add_equation(
(θ - (γ - 1) * Υ - s_c_over_c_P * γ * s, 0)) #EOS, s_c/cP = scrS
#TO-DO:
#consider adding back in diffusive & source nonlinearities
problem.add_equation(
(ρ0 * u @ grad(s0) - R_inv / Pr * (lap(θ) + 2 * grad(θ0) @ grad(θ)) +
lift(τ_s1, -1) + lift(τ_s2, -2), 0))
if no_slip:
from mpi4py import MPI
from eigentools import Eigenproblem, CriticalFinder
import time
import dedalus.public as de
import numpy as np
import matplotlib.pylab as plt
comm = MPI.COMM_WORLD
# Define the MRI problem in Dedalus:
x = de.Chebyshev('x', 64)
d = de.Domain([x], comm=MPI.COMM_SELF)
mri = de.EVP(
d, ['psi', 'u', 'A', 'B', 'psix', 'psixx', 'psixxx', 'ux', 'Ax', 'Bx'],
'sigma')
Rm = 4.879
Pm = 0.001
mri.parameters['q'] = 1.5
mri.parameters['beta'] = 25.0
mri.parameters['iR'] = Pm / Rm
mri.parameters['iRm'] = 1. / Rm
mri.parameters['Q'] = 0.745
mri.add_equation(
"sigma*psixx - Q**2*sigma*psi - iR*dx(psixxx) + 2*iR*Q**2*psixx - iR*Q**4*psi - 2*1j*Q*u - (2/beta)*1j*Q*dx(Ax) + (2/beta)*Q**3*1j*A = 0"
)
mri.add_equation(
"sigma*u - iR*dx(ux) + iR*Q**2*u - (q - 2)*1j*Q*psi - (2/beta)*1j*Q*B = 0")
def linearStabilityAnalysisPar(f, tht, kappa, Pr, U, Uz, V, Vz, B, Bz, nz, H,
l, k, domain):
# Need to decide whether input variables are in rotated frame or not.
import sys
import numpy as np
import pdb
from mpi4py import MPI
from eigentools import Eigenproblem, CriticalFinder
# import matplotlib.pyplot as plt
# from pylab import *
# import scipy.integrate as integrate
from dedalus import public as de
# import logging
# logger = logging.getLogger(__name__)
# LOAD IN PARAMETERS
#f = parameters, tht, kappa, Pr, U, Uz, V, Vz, B, Bz, nz, H, ll, domain)
# f, tht, kappa, Pr, U, Uz, V, Vz, B, Bz, nz, H, ll, domain):
# pdb.set_trace()
# f = args[0]
# tht = args[1]
# kappa = args[2]
# Pr = args[3]
# U = args[4]
# Uz = args[5]
# V = args[6]
# Vz = args[7]
# B = args[8]
# Bz = args[9]
# nz = args[10]
# H = args[11]
# ll = args[12]
## domain = args[13]
# z_basis = de.Chebyshev('z', nz, interval=(0, H))
# domain = de.Domain([z_basis], np.complex128)
# non-constant coefficients
# kap = domain.new_field(name='kap')
# z = domain.grid(0)
# kap['g'] = kapi
# SETUP LINEAR STABILITY ANALYSIS
problem = de.EVP(
domain,
variables=['u', 'v', 'w', 'b', 'p', 'uz', 'vz', 'wz', 'bz'],
eigenvalue='omg',
tolerance=1e-3)
problem.parameters['U'] = U
problem.parameters['V'] = V
problem.parameters['B'] = B
problem.parameters['Uz'] = Uz
problem.parameters['Vz'] = Vz
problem.parameters['Bz'] = Bz
problem.parameters['f'] = f
problem.parameters['tht'] = tht
problem.parameters['kap'] = kappa
problem.parameters['Pr'] = Pr
problem.parameters['k'] = 0. # will be set in loop
problem.parameters['l'] = 0. # will be set in loop
problem.substitutions['dx(A)'] = "1j*k*A"
problem.substitutions['dy(A)'] = "1j*l*A"
problem.substitutions['dt(A)'] = "-1j*omg*A"
problem.add_equation(
('dt(u) + U*dx(u) + V*dy(u) + w*Uz - f*v*cos(tht) + dx(p)'
'- b*sin(tht) - Pr*(kap*dx(dx(u)) + kap*dy(dy(u)) + dz(kap)*uz'
'+ kap*dz(uz)) = 0'))
problem.add_equation(
('dt(v) + U*dx(v) + V*dy(v) + w*Vz + f*u*cos(tht)'
'- f*w*sin(tht) + dy(p) - Pr*(kap*dx(dx(v)) + kap*dy(dy(v))'
'+ dz(kap)*vz + kap*dz(vz)) = 0'))
# problem.add_equation(('dt(w) + U*dx(w) + V*dy(w) + f*v*sin(tht) + dz(p)'
# '- b*cos(tht) - Pr*(kap*dx(dx(w)) + kap*dy(dy(w)) + dz(kap)*wz'
# '+ kap*dz(wz)) = 0'))
problem.add_equation(
'0*(dt(w) + U*dx(w) + V*dy(w)) + f*v*sin(tht) + dz(p)'
'- b*cos(tht) - Pr*(kap*dx(dx(w)) + kap*dy(dy(w)) + dz(kap)*wz'
'+ kap*dz(wz)) = 0')
# problem.add_equation(('dt(b) + U*dx(b) + V*dy(b) + u*N**2*sin(tht)'
# '+ w*(N**2*cos(tht) + Bz) - kap*dx(dx(b)) - kap*dy(dy(b)) - dz(kap)*bz'
# '- kap*dz(bz) = 0'))
problem.add_equation(
('dt(b) + U*dx(b) + V*dy(b) + u*Vz*f'
'+ w*(Bz) - kap*dx(dx(b)) - kap*dy(dy(b)) - dz(kap)*bz'
'- kap*dz(bz) = 0'))
problem.add_equation('dx(u) + dy(v) + wz = 0')
problem.add_equation('uz - dz(u) = 0')
problem.add_equation('vz - dz(v) = 0')
problem.add_equation('wz - dz(w) = 0')
problem.add_equation('bz - dz(b) = 0')
problem.add_bc('left(u) = 0')
problem.add_bc('left(v) = 0')
problem.add_bc('left(w) = 0')
problem.add_bc('left(bz) = 0')
problem.add_bc('right(uz) = 0')
problem.add_bc('right(vz) = 0')
problem.add_bc('right(w) = 0')
problem.add_bc('right(bz) = 0')
problem.namespace['k'].value = k
problem.namespace['l'].value = l
# solve problem
EP = Eigenproblem(problem)
(gr, idx, freq) = EP.growth_rate({})
# print(str(np.max(idx)))
# print(str(idx[-1]))
# if idx[-1]>nz:
# grt = 0
gr = np.array([gr])
# #get full eigenvectors and eigenvalues for l with largest growth
## idx = sorted_eigen(0., ll[np.argmax(gr)])
# solver.set_state(idx[-1])
#
# # collect eigenvector
# u = solver.state['u']
# v = solver.state['v']
# w = solver.state['w']
# b = solver.state['b']
# shear production
# SP = -2*np.real(np.conj(w['g'])*(u['g']*Uz['g']+v['g']*Vz['g']))
#
# # buoyancy production
# BP = 2*np.real((u['g']*np.sin(tht)+w['g']*np.cos(tht))*np.conj(b['g']))
return (gr, 0, 0, 0, 0)
def mhd_rbc_evp(Q, Ra, k, Nz=24, variables_form=True):
z = de.Chebyshev('z', Nz, interval=(0, 1))
d = de.Domain([z], comm=MPI.COMM_SELF)
if variables_form:
variables = [
'T', 'Tz', 'u', 'w', 'phi', 'Ax', 'Ay', 'Az', 'Bx', 'By', 'Bz',
'Jx', 'Jy', 'Oy', 'p'
]
else:
variables = [
'T', 'Tz', 'u', 'w', 'Ax', 'Ay', 'Az', 'Bx', 'By', 'Oy', 'p', 'phi'
]
problem = de.EVP(d, variables, eigenvalue='omega')
#Parameters
problem.parameters['kx'] = k #horizontal wavenumber (x)
problem.parameters['ky'] = 0 #horizontal wavenumber (y)
problem.parameters['Ra'] = Ra #Rayleigh number
problem.parameters['Pr'] = 1 #Prandtl number
problem.parameters['Pm'] = 1 #Magnetic Prandtl number
problem.parameters['Q'] = Q
problem.parameters['dzT0'] = -1
#Substitutions
problem.substitutions['v'] = '0'
problem.substitutions['Ox'] = '0'
problem.substitutions["dt(A)"] = "omega*A"
problem.substitutions["dx(A)"] = "1j*kx*A"
problem.substitutions["dy(A)"] = "1j*ky*A"
problem.substitutions['UdotGrad(A,A_z)'] = '(u*dx(A) + v*dy(A) + w*(A_z))'
problem.substitutions['Lap(A,A_z)'] = '(dx(dx(A)) + dy(dy(A)) + dz(A_z))'
if not variables_form:
problem.substitutions["Bz"] = "dx(Ay)-dy(Ax)"
problem.substitutions["Jx"] = "dy(Bz)-dz(By)"
problem.substitutions["Jy"] = "dz(Bx)-dx(Bz)"
problem.substitutions["Jz"] = "dx(By)-dy(Bx)"
problem.substitutions["Kz"] = "dx(Oy)-dy(Ox)"
problem.substitutions["Oz"] = "dx(v)-dy(u)"
problem.substitutions["Ky"] = "dz(Ox)-dx(Oz)"
problem.substitutions["Kx"] = "dy(Oz)-dz(Oy)"
#Dimensionless parameter substitutions
problem.substitutions["inv_Re_ff"] = "(Pr/Ra)**(1./2.)"
problem.substitutions["inv_Rem_ff"] = "(inv_Re_ff / Pm)"
problem.substitutions["JxB_pre"] = "((Q*Pr)/(Ra*Pm))"
problem.substitutions["inv_Pe_ff"] = "(Ra*Pr)**(-1./2.)"
#Equations
problem.add_equation("Tz - dz(T) = 0")
problem.add_equation(
"dt(T) + w*dzT0 - inv_Pe_ff*Lap(T, Tz) = -UdotGrad(T, Tz)")
problem.add_equation(
"dt(u) + dx(p) + inv_Re_ff*Kx - JxB_pre*Jy = v*Oz - w*Oy + JxB_pre*(Jy*Bz - Jz*By)"
)
problem.add_equation(
"dt(w) + dz(p) + inv_Re_ff*Kz - T = u*Oy - v*Ox + JxB_pre*(Jx*By - Jy*Bx) "
)
problem.add_equation(
"dt(Ax) + dx(phi) + inv_Rem_ff*Jx - v = v*Bz - w*By")
problem.add_equation(
"dt(Ay) + dy(phi) + inv_Rem_ff*Jy + u = w*Bx - u*Bz")
problem.add_equation(
"dt(Az) + dz(phi) + inv_Rem_ff*Jz = u*By - v*Bx")
problem.add_equation("dx(u) + dy(v) + dz(w) = 0")
problem.add_equation("dx(Ax) + dy(Ay) + dz(Az) = 0") #do I need dy here??
problem.add_equation("Bx - (dy(Az) - dz(Ay)) = 0")
problem.add_equation("By - (dz(Ax) - dx(Az)) = 0")
if variables_form:
problem.add_equation("Bz - (dx(Ay) - dy(Ax)) = 0")
problem.add_equation("Jx - (dy(Bz) - dz(By)) = 0")
problem.add_equation("Jy - (dz(Bx) - dx(Bz)) = 0")
problem.add_equation("Oy - (dz(u) - dx(w)) = 0")
bcs = ['T', 'u', 'w', 'Jx', 'Jy', 'Bz']
for bc in bcs:
problem.add_bc(" left({}) = 0".format(bc))
problem.add_bc("right({}) = 0".format(bc))
return problem
def Rayleigh_Benard_onset(Prandtl=1,
nz=32,
nx=128,
aspect=64,
data_dir='./',
multiplier=1.5,
no_slip=False,
stress_free=False,
no_lid=False):
if not no_slip and not stress_free and not no_lid:
no_slip = True
# input parameters
logger.info(" Pr = {}".format(Prandtl))
# Parameters
Lz = 1.
Lx = aspect * Lz
logger.info("resolution: [{}x{}]".format(nx, nz))
# Create bases and domain
x_basis = de.Fourier('x', nx, interval=(0, Lx), dealias=3 / 2)
z_basis_set = []
nz_set = [nz, int(nz * multiplier)]
for nz_solve in nz_set:
z_basis_set.append(
de.Chebyshev('z', nz_solve, interval=(0, Lz), dealias=3 / 2))
domain_set = []
for z_basis in z_basis_set:
domain_set.append(de.Domain([x_basis, z_basis], grid_dtype=np.float64))
solver_set = []
# 2D Boussinesq hydrodynamics
for domain in domain_set:
problem = de.EVP(domain,
variables=['p', 'b', 'u', 'w', 'bz', 'uz', 'wz'],
eigenvalue='Ra')
problem.meta['p', 'b', 'u', 'w']['z']['dirichlet'] = True
problem.parameters['F'] = F = 1
problem.parameters['Pr'] = np.sqrt(Prandtl)
problem.parameters['Lx'] = Lx
problem.parameters['Lz'] = Lz
problem.substitutions['plane_avg(A)'] = 'integ(A, "x")/Lx'
problem.substitutions['vol_avg(A)'] = 'integ(A)/Lx/Lz'
# for eq_type_1 = False; not working
problem.substitutions['dt(f)'] = '(0*f)'
problem.substitutions['P'] = '(1/sqrt(Ra)*1/sqrt(Pr))'
problem.substitutions['R'] = '(1/sqrt(Ra)*sqrt(Pr))'
#problem.substitutions['scale'] = 'sqrt(Ra)'
eq_type_1 = True
problem.add_equation("dx(u) + wz = 0")
if eq_type_1:
problem.add_equation(" - (dx(dx(b)) + dz(bz)) - F*w = 0")
problem.add_equation(" - (dx(dx(u)) + dz(uz)) + dx(p) = 0")
problem.add_equation(" - (dx(dx(w)) + dz(wz)) + dz(p) - Ra*b = 0")
else:
# not working
problem.add_equation(
"(dt(b) - P*(dx(dx(b)) + dz(bz)) - F*w ) = -(u*dx(b) + w*bz)"
)
problem.add_equation(
"(dt(u) - R*(dx(dx(u)) + dz(uz)) + dx(p) ) = -(u*dx(u) + w*uz)"
)
problem.add_equation(
"(dt(w) - R*(dx(dx(w)) + dz(wz)) + dz(p) - b ) = -(u*dx(w) + w*wz)"
)
problem.add_equation("bz - dz(b) = 0")
problem.add_equation("uz - dz(u) = 0")
problem.add_equation("wz - dz(w) = 0")
problem.add_bc("left(b) = 0")
if no_slip:
problem.add_bc("left(u) = 0")
problem.add_bc("right(u) = 0")
logger.info("using no_slip BCs")
elif stress_free:
problem.add_bc("left(uz) = 0")
problem.add_bc("right(uz) = 0")
logger.info("using stress_free BCs")
elif no_lid:
problem.add_bc("left(u) = 0")
problem.add_bc("right(uz) = 0")
logger.info("using stress_free BCs")
problem.add_bc("left(w) = 0")
problem.add_bc("right(b) = 0")
problem.add_bc("right(w) = 0", condition="(nx != 0)")
problem.add_bc("integ(p, 'z') = 0", condition="(nx == 0)")
solver_set.append(problem.build_solver())
logger.info('Solver built')
# Main loop
try:
logger.info('Starting loop')
start_time = time.time()
crit_Ra_set = []
min_wavenumber = 1
max_wavenumber = int(nx / 2)
first_output = True
for wave in np.arange(min_wavenumber, max_wavenumber):
low_e_val_set = []
for solver in solver_set:
solver.solve(solver.pencils[wave])
eigenvalue_indices = np.argsort(np.abs(solver.eigenvalues))
eigenvalues = np.copy(solver.eigenvalues[eigenvalue_indices])
low_e_val_set.append(eigenvalues[0])
x_grid = solver.domain.grid(0)
if np.isfinite(low_e_val_set[0]):
if first_output:
print(
"k_h Ra_1 Ra_2 relative error"
)
print(
" (nz={:4d}) (nz={:4d}) |Ra_1 - Ra_2|/|Ra_1|"
.format(nz_set[0], nz_set[1]))
first_output = False
print(
"{:4d}:{:12.4g} {:>12.4g} {:>12.4g} {:8.3g}".format(
wave, wave / Lx, low_e_val_set[0], low_e_val_set[1],
np.abs(
np.abs(low_e_val_set[0] - low_e_val_set[1]) /
low_e_val_set[0])))
crit_Ra_set.append(low_e_val_set[1])
else:
print(wave, "no finite values")
except:
logger.error('Exception raised, triggering end of main loop.')
raise
finally:
i_min_Ra = np.argmin(crit_Ra_set)
logger.info("Minimum Ra = {:g} at wavenumber={:g} (# {:d})".format(
crit_Ra_set[i_min_Ra], (i_min_Ra + min_wavenumber) / Lx,
i_min_Ra + min_wavenumber))
end_time = time.time()
logger.info('Run time: %.2f sec' % (end_time - start_time))
def solve_hires(self, tol=1e-10):
old_evp = self.EVP
old_d = old_evp.domain
old_x = old_d.bases[0]
old_x_grid = old_d.grid(0, scales=old_d.dealias)
if type(old_x) == de.Compound:
bases = []
for basis in old_x.subbases:
old_x_type = basis.__class__.__name__
n_hi = int(basis.base_grid_size * self.factor)
if old_x_type == "Chebyshev":
x = de.Chebyshev(basis.name, n_hi, interval=basis.interval)
elif old_x_type == "Fourier":
x = de.Fourier(basis.name, n_hi, interval=basis.interval)
else:
raise ValueError(
"Don't know how to make a basis of type {}".format(
old_x_type))
bases.append(x)
x = de.Compound(old_x.name, tuple(bases))
else:
old_x_type = old_x.__class__.__name__
n_hi = int(old_x.coeff_size * self.factor)
if old_x_type == "Chebyshev":
x = de.Chebyshev(old_x.name, n_hi, interval=old_x.interval)
elif old_x_type == "Fourier":
x = de.Fourier(old_x.name, n_hi, interval=old_x.interval)
else:
raise ValueError(
"Don't know how to make a basis of type {}".format(
old_x_type))
d = de.Domain([x], comm=old_d.dist.comm)
self.EVP_hires = de.EVP(d,
old_evp.variables,
old_evp.eigenvalue,
tolerance=tol)
x_grid = d.grid(0, scales=d.dealias)
for k, v in old_evp.substitutions.items():
self.EVP_hires.substitutions[k] = v
for k, v in old_evp.parameters.items():
if type(v) == Field: #NCCs
new_field = d.new_field()
v.set_scales(self.factor, keep_data=True)
new_field['g'] = v['g']
self.EVP_hires.parameters[k] = new_field
else: #scalars
self.EVP_hires.parameters[k] = v
for e in old_evp.equations:
self.EVP_hires.add_equation(e['raw_equation'])
try:
for b in old_evp.boundary_conditions:
self.EVP_hires.add_bc(b['raw_equation'])
except AttributeError:
# after version befc23584fea, Dedalus no longer
# distingishes BCs from other equations
pass
solver = self.EVP_hires.build_solver()
if self.sparse:
solver.solve_sparse(solver.pencils[self.pencil],
N=10,
target=0,
rebuild_coeffs=True)
else:
solver.solve_dense(solver.pencils[self.pencil],
rebuild_coeffs=True)
self.evalues_hires = solver.eigenvalues
def run(subs):
print("\n\nBegin Linearized Pure Hydro, Const/Static Background\n")
print("Using substitutions: ", subs)
print()
# set lowest level of all loggers to INFO, i.e. dont follow DEBUG stuff
root = logging.root
for h in root.handlers:
h.setLevel("INFO")
# name logger using the module name
logger = logging.getLogger(__name__)
# Input parameters
gamma = 1.4
kappa = 1.e-4
c_v = 1.
k_z = 3.13 # vertical wavenumber
R_in = 1.
R_out = 3.
# background is const
rho0 = 5.
T0 = 10.
p0 = (gamma - 1) * c_v * rho0 * T0
height = 2. * numpy.pi / k_z
# Problem Domain
r_basis = de.Chebyshev('r', 32, interval=(R_in, R_out), dealias=3 / 2)
z_basis = de.Fourier('z', 32, interval=(0., height), dealias=3 / 2)
th_basis = de.Fourier('th',
32,
interval=(0., 2. * numpy.pi),
dealias=3 / 2)
domain = de.Domain([r_basis, th_basis, z_basis], grid_dtype=numpy.float64)
# alias the grids
z = domain.grid(2, scales=domain.dealias)
th = domain.grid(1, scales=domain.dealias)
r = domain.grid(0, scales=domain.dealias)
# Equations
# incompressible, axisymmetric, Navier-Stokes in Cylindrical
# expand the non-constant-coefficients (NCC) to precision of 1.e-8
TC = de.EVP(domain,
variables=['rho', 'p', 'T', 'u', 'v', 'w', 'Tr'],
ncc_cutoff=1.e-8,
eigenvalue='omega')
TC.parameters['gamma'] = gamma
TC.parameters['kappa'] = kappa
TC.parameters['p0'] = p0
TC.parameters['T0'] = T0
TC.parameters['rho0'] = rho0
# multiply equations through by r**2 or r to avoid 1/r**2 & 1/r terms
if (subs):
# substitute for dt()
TC.substitutions['dt(A)'] = '-1.j*omega*A'
# r*div(U)
TC.substitutions['r_div(A,B,C)'] = 'A + r*dr(A) + dth(B) + r*dz(C)'
# r-component of gradient
TC.substitutions['grad_1(A)'] = 'dr(A)'
# th-component of gradient
TC.substitutions['r_grad_2(A)'] = 'r*dth(A)'
# z-component of gradient
TC.substitutions['grad_3(A)'] = 'dz(A)'
# r*r*Laplacian(scalar)
TC.substitutions['r2_Lap(f, fr)'] = \
'r*r*dr(fr) + r*dr(f) + dth(f) + r*r*dz(dz(f))'
# equations using substituions
TC.add_equation("p/p0 - rho/rho0 - T/T0 = 0")
TC.add_equation("r*r*dt(p) + gamma*p0*r*r_div(u,v,w) - " + \
"(gamma-1)*kappa*r2_Lap(T, Tr) = 0")
TC.add_equation("r*dt(rho) + rho0*r_div(u,v,w) = 0")
TC.add_equation("rho0*dt(u) + grad_1(p) = 0")
TC.add_equation("r*rho0*dt(v) + r_grad_2(p) = 0")
TC.add_equation("rho0*dt(w) + grad_3(p) = 0")
TC.add_equation("Tr - dr(T) = 0")
else:
print("\nNon-Substitutions Version is not coded up\n")
sys.exit(2)
# Boundary Conditions
TC.add_bc("left(u) = 0")
TC.add_bc("left(v) = 0")
TC.add_bc("left(w) = 0")
TC.add_bc("right(u) = 0", condition="nz != 0")
TC.add_bc("right(v) = 0")
TC.add_bc("right(w) = 0")
TC.add_bc("integ(p,'r') = 0", condition="nz == 0")
###############################################################
# Force break since the following has not been edited yet...
###############################################################
print("\nThe rest of the script needs to be changed still\n")
sys.exit(2)
# Timestepper
dt = max_dt = 1.
Omega_1 = TC.parameters['V_l'] / R_in
period = 2. * numpy.pi / Omega_1
logger.info('Period: %f' % (period))
ts = de.timesteppers.RK443
IVP = TC.build_solver(ts)
IVP.stop_sim_time = 15. * period
IVP.stop_wall_time = numpy.inf
IVP.stop_iteration = 10000000
# alias the state variables
p = IVP.state['p']
u = IVP.state['u']
v = IVP.state['v']
w = IVP.state['w']
ur = IVP.state['ur']
vr = IVP.state['vr']
wr = IVP.state['wr']
# new field
phi = Field(domain, name='phi')
for f in [phi, p, u, v, w, ur, vr, wr]:
f.set_scales(domain.dealias, keep_data=False)
v['g'] = v_analytic
#p['g'] = p_analytic
v.differentiate(1, vr)
# incompressible perturbation, arbitrary vorticity
phi['g'] = 1.e-3 * numpy.random.randn(*v['g'].shape)
phi.differentiate(1, u)
u['g'] *= -1. * numpy.sin(numpy.pi * (r - R_in))
phi.differentiate(0, w)
w['g'] *= numpy.sin(numpy.pi * (r - R_in))
u.differentiate(1, ur)
w.differentiate(1, wr)
# Time step size
CFL = flow_tools.CFL(IVP,
initial_dt=1.e-3,
cadence=5,
safety=0.3,
max_change=1.5,
min_change=0.5)
CFL.add_velocities(('u', 'w'))
# Analysis
# integrated energy every 10 steps
analysis1 = IVP.evaluator.add_file_handler("scalar_data", iter=10)
analysis1.add_task("integ(0.5 * (u*u + v*v + w*w))", name="total KE")
analysis1.add_task("integ(0.5 * (u*u + w*w))", name="meridional KE")
analysis1.add_task("integ((u*u)**0.5)", name="u_rms")
analysis1.add_task("integ((w*w)**0.5)", name="w_rms")
# Snapshots every half inner rotation period
analysis2 = IVP.evaluator.add_file_handler('snapshots',
sim_dt=0.5 * period,
max_size=2**30)
analysis2.add_system(IVP.state, layout='g')
# Radial profiles every 100 steps
analysis3 = IVP.evaluator.add_file_handler("radial_profiles", iter=100)
analysis3.add_task("integ(r*v, 'z')", name="Angular Momentum")
# MAIN LOOP
dt = CFL.compute_dt()
start_time = time.time()
while IVP.ok:
IVP.step(dt)
if (IVP.iteration % 10 == 0):
logger.info('Iteration: %i, Time: %e, dt: %e' % \
(IVP.iteration, IVP.sim_time, dt))
dt = CFL.compute_dt()
end_time = time.time()
logger.info('Total time: %f' % (end_time - start_time))
logger.info('Iterations: %i' % (IVP.iteration))
logger.info('Average timestep: %f' % (IVP.sim_time / IVP.iteration))
logger.info('Period: %f' % (period))
logger.info('\n\tSimulation Complete\n')
return
#k = np.pi/10
#Rm = 4.052
R = Rm/Pm
iR = 1.0/R
c1 = (Omega2*R2**2 - Omega1*R1**2)/(R2**2 - R1**2)
c2 = (R1**2*R2**2*(Omega1 - Omega2))/(R2**2 - R1**2)
zeta_mean = 2*(R2**2*Omega2 - R1**2*Omega1)/((R2**2 - R1**2)*np.sqrt(Omega1*Omega2))
print("mean zeta is {}, meaning q = 2 - zeta = {}".format(zeta_mean, 2 - zeta_mean))
r = de.Chebyshev('r', nr, interval = (R1, R2))
d = de.Domain([r],comm=MPI.COMM_SELF)
widegap = de.EVP(d,['psi','u', 'A', 'B', 'psir', 'psirr', 'psirrr', 'ur', 'Ar', 'Br'],'sigma')
widegap.parameters['k'] = k
widegap.parameters['iR'] = iR
widegap.parameters['Rm'] = Rm # Rm rather than iRm so search options are more intuitive
widegap.parameters['c1'] = c1
widegap.parameters['c2'] = c2
widegap.parameters['beta'] = beta
widegap.parameters['B0'] = 1
widegap.parameters['xi'] = 0
widegap.substitutions['ru0'] = '(r*r*c1 + c2)' # u0 = r Omega(r) = Ar + B/r
widegap.substitutions['rrdu0'] = '(c1*r*r-c2)' # du0/dr = A - B/r^2
widegap.substitutions['twooverbeta'] = '(2.0/beta)'
widegap.substitutions['psivisc'] = '(2*r**2*k**2*psir - 2*r**3*k**2*psirr + r**3*k**4*psi + r**3*dr(psirrr) - 3*psir + 3*r*psirr - 2*r**2*psirrr)'
widegap.substitutions['uvisc'] = '(-r**3*k**2*u + r**3*dr(ur) + r**2*ur - r*u)'
Re = 0.
Pr = 1
Ra = 25
use_Laguerre = False
find_crit = True
if use_Laguerre:
logger.info("Running with Laguerre z-basis")
z_basis = de.Laguerre('z', nz, dealias=3 / 2)
else:
z_basis = de.Chebyshev('z', nz, interval=(0, Lz), dealias=3 / 2)
domain = de.Domain([z_basis], comm=MPI.COMM_SELF)
problem = de.EVP(domain,
variables=['p', 'θ', 'u', 'v', 'w', 'θz', 'uz', 'vz', 'wz'],
eigenvalue='sigma')
problem.parameters['Ra'] = Ra
problem.parameters['Re'] = Re
problem.parameters['Pr'] = Pr
problem.parameters['kx'] = kx
problem.parameters['ky'] = ky
problem.substitutions['Uz'] = '-Pr'
problem.substitutions['dt(A)'] = 'sigma*A'
problem.substitutions['dx(A)'] = '-1j*kx*A'
problem.substitutions['dy(A)'] = '-1j*ky*A'
if use_Laguerre:
problem.substitutions['Ux'] = 'Pr*Re*(1-exp(-z))'
problem.substitutions['Uxz'] = 'Pr*Re*exp(-z)'
#problem.substitutions['Ux'] = '-Pr*Re*exp(-z)'
#problem.substitutions['Uxz'] = 'Pr*Re*exp(-z)'
if case == 3:
velocity_bc = "no-slip"
temperature_bc = "FT"
kc = 2.55
kx_global = np.linspace(kc * (1 - zoom), kc * (1 + zoom), Nk)
# Create bases and domain
# Use COMM_SELF so keep calculations independent between processes
z_basis = de.Chebyshev('z', Nz, interval=(-1 / 2, 1 / 2))
domain = de.Domain([z_basis], grid_dtype=np.complex128, comm=MPI.COMM_SELF)
# 2D Boussinesq hydrodynamics, with various boundary conditions
# Use substitutions for x derivatives
problem = de.EVP(domain,
variables=['p', 'T', 'u', 'w', 'F', 'ω'],
eigenvalue='Ra')
problem.parameters['kx'] = 1
problem.substitutions['dx(A)'] = "1j*kx*A"
problem.add_equation(" dx(u) + dz(w) = 0")
problem.add_equation(" dx(dx(T)) - dz(F) + w = 0")
problem.add_equation(" dz(ω) + dx(p) = 0")
problem.add_equation(" - dx(ω) + dz(p) - Ra*T = 0")
problem.add_equation("F + dz(T) = 0")
problem.add_equation("ω - dx(w) + dz(u) = 0")
problem.add_bc("left(w) = 0")
problem.add_bc("right(w) = 0")
if velocity_bc == "no-slip":
if __name__ == '__main__':
'''
setup domain and calculate derivatives of vertical profiles as needed
'''
z_basis = de.Chebyshev('z', nz_waves, interval=(zmin * Hgas, zmax * Hgas))
domain_EVP = de.Domain([z_basis], comm=MPI.COMM_SELF)
'''
notation: W = delta_P/P = delta_ln_rhog, Q=delta_eps/eps = delta_ln_eps, U = velocities
W_p = W_primed (dW/dz)...etc
'''
if (diffusion == True) and (tstop == True): #full problem
waves = de.EVP(domain_EVP, ['W', 'W_p', 'Q', 'Q_p', 'Ux', 'Uy', 'Uz'],
eigenvalue='sigma',
tolerance=tol)
if (diffusion == False) and (tstop == True):
waves = de.EVP(domain_EVP, ['W', 'W_p', 'Q', 'Ux', 'Uy', 'Uz'],
eigenvalue='sigma',
tolerance=tol)
if (diffusion == False) and (tstop == False):
waves = de.EVP(domain_EVP, ['W', 'Q', 'Ux', 'Uy', 'Uz'],
eigenvalue='sigma',
tolerance=tol)
'''
set up required vertical profiles as non-constant coefficients
'''
z = domain_EVP.grid(0)
def weakfield_hydro(Ra, k, Nz=24, noHorizB_BCs=True, kx=True):
z = de.Chebyshev('z', Nz, interval=(0, 1))
d = de.Domain([z], comm=MPI.COMM_SELF)
variables = ['p', 'u', 'v', 'w', 'Ox', 'Oy', 'Bx', 'By', 'Bz', 'Jz_z']
problem = de.EVP(d, variables, eigenvalue='omega')
#Parameters
if kx:
problem.parameters['kx'] = k
problem.parameters['ky'] = 0
else:
problem.parameters['kx'] = 0
problem.parameters['ky'] = k
problem.parameters['Ra'] = Ra #Rayleigh number
problem.parameters['Pm'] = 1 #Magnetic Prandtl number
problem.parameters['dzT0'] = -1
#Substitutions
problem.substitutions["dt(A)"] = "omega*A"
problem.substitutions["dx(A)"] = "1j*kx*A"
problem.substitutions["dy(A)"] = "1j*ky*A"
problem.substitutions['UdotGrad(A,A_z)'] = '(u*dx(A) + v*dy(A) + w*(A_z))'
problem.substitutions['Lap(A,A_z)'] = '(dx(dx(A)) + dy(dy(A)) + dz(A_z))'
problem.substitutions["Jx"] = "dy(Bz)-dz(By)"
problem.substitutions["Jy"] = "dz(Bx)-dx(Bz)"
problem.substitutions["Jz"] = "dx(By)-dy(Bx)"
problem.substitutions["Oz"] = "dx(v)-dy(u)"
problem.substitutions["Kz"] = "dx(Oy)-dy(Ox)"
problem.substitutions["Ky"] = "dz(Ox)-dx(Oz)"
problem.substitutions["Kx"] = "dy(Oz)-dz(Oy)"
#Dimensionless parameter substitutions
problem.substitutions["inv_Re_ff"] = "(Pr/Ra)**(1./2.)"
problem.substitutions["inv_Rem_ff"] = "(inv_Re_ff / Pm)"
problem.substitutions['B0'] = '0'
problem.substitutions['T'] = '0'
#Equations
problem.add_equation("dx(u) + dy(v) + dz(w) = 0")
problem.add_equation("dt(u) + dx(p) + inv_Re_ff*(dy(Oz)-dz(Oy)) = 0 ")
problem.add_equation("dt(v) + dy(p) + inv_Re_ff*(dz(Ox)-dx(Oz)) = 0 ")
problem.add_equation("dt(w) + dz(p) + inv_Re_ff*(dx(Oy)-dy(Ox)) = 0 ")
problem.add_equation("Ox - (dy(w) - dz(v)) = 0")
problem.add_equation("Oy - (dz(u) - dx(w)) = 0")
problem.add_equation("dx(Bx) + dy(By) + dz(Bz) = 0")
problem.add_equation(
"dt(Bz) + inv_Rem_ff*(dx(Jy) - dy(Jx)) = 0"
) #need to figure out nonliner terms
problem.add_equation(
"dt(Jz) - inv_Rem_ff*(dx(dx(Jz)) + dy(dy(Jz)) + dz(Jz_z)) = 0")
problem.add_equation("Jz_z - dz(Jz) = 0")
if noHorizB_BCs:
bcs = ['Oy', 'Ox', 'w', 'Bx', 'By']
else:
bcs = ['Oy', 'Ox', 'w', 'Bz', 'Jz_z']
for bc in bcs:
problem.add_bc(" left({}) = 0".format(bc))
problem.add_bc("right({}) = 0".format(bc))
return problem
