def test_LinearADR_Sine():
logEvent("LinearADR_Sine")
sol = AnalyticalSolutions.LinearADR_Sine()
u = [sol.uOfX(x) for x in X]
assert u[midpoint_x_index] == 0.22471248696198207
Du = [sol.duOfX(x)[0] for x in X]
assert Du[midpoint_x_index] == 6.122493544431436
aflux = [sol.advectiveFluxOfX(x)[0] for x in X]
assert aflux[midpoint_x_index] == 0.22471248696198207
dflux = [sol.diffusiveFluxOfX(x)[0] for x in X]
assert dflux[midpoint_x_index] == -0.061224935444314364
tflux = [sol.totalFluxOfX(x)[0] for x in X]
assert tflux[midpoint_x_index] == 0.1634875515176677
r = [sol.rOfUX(sol.uOfX(x), x) for x in X]
assert r[midpoint_x_index] == -6.211206478443425
if save_plots:
fig = plt.figure()
plt.title("LinearADR_Sine")
plt.plot(Xx, u, label='Solution')
plt.plot(Xx, Du, label='Gradient')
plt.plot(Xx, aflux, label='Advective Flux')
plt.plot(Xx, dflux, label='Diffusive Flux')
plt.plot(Xx, tflux, label='Total Flux')
plt.plot(Xx, r, label='reaction')
plt.legend()
plt.savefig("LinearADR_Sine.png")
def test_NonlinearAD_SteadyState():
logEvent("NonlinearAD_SteadyState")
sol = AnalyticalSolutions.NonlinearAD_SteadyState(q=2, r=1)
y = [sol.uOfX(x) for x in X]
assert y[midpoint_x_index] == 0.9948469998751492
if save_plots:
fig = plt.figure()
plt.plot(Xx, y, label='Solution,q=2,r=1')
sol = AnalyticalSolutions.NonlinearAD_SteadyState(q=1, r=2)
y = [sol.uOfX(x) for x in X]
assert y[midpoint_x_index] == 0.990588835252627
if save_plots:
fig = plt.figure()
plt.plot(Xx, [sol.uOfX(x) for x in X], label='Solution,q=1,r=2')
plt.legend()
plt.title("NonlinearAD_SteadyState")
plt.savefig("NonlinearAD_SteadyState.png")
def test_NonlinearADR_Decay_DiracIC():
logEvent("NonlinearADR_Decay_DiracIC")
sol = AnalyticalSolutions.NonlinearADR_Decay_DiracIC()
up25 = [sol.uOfXT(x, T=0.25) for x in X]
assert up25[midpoint_x_index] == 0.0058003017280384575
up75 = [sol.uOfXT(x, T=0.75) for x in X]
assert up75[midpoint_x_index] == 1.3623941337338921e-08
Dup25 = [sol.duOfXT(x, T=0.25)[0] for x in X]
assert Dup25[midpoint_x_index] == -0.248169222231705570
Dup75 = [sol.duOfXT(x, T=0.75)[0] for x in X]
assert Dup75[midpoint_x_index] == -6.484340816869727e-07
afluxp25 = [sol.advectiveFluxOfXT(x, T=0.25)[0] for x in X]
assert afluxp25[midpoint_x_index] == 0.0058003017280384575
afluxp75 = [sol.advectiveFluxOfXT(x, T=0.75)[0] for x in X]
assert afluxp75[midpoint_x_index] == 1.3623941337338921e-08
dfluxp25 = [sol.diffusiveFluxOfXT(x, T=0.25)[0] for x in X]
assert dfluxp25[midpoint_x_index] == 0.0024816922223170556
dfluxp75 = [sol.diffusiveFluxOfXT(x, T=0.75)[0] for x in X]
assert dfluxp75[midpoint_x_index] == 6.484340816869727e-09
tfluxp25 = [sol.totalFluxOfXT(x, T=0.25)[0] for x in X]
assert tfluxp25[midpoint_x_index] == 0.008281993950355513
tfluxp75 = [sol.totalFluxOfXT(x, T=0.75)[0] for x in X]
assert tfluxp75[midpoint_x_index] == 2.010828215420865e-08
if save_plots:
fig = plt.figure()
plt.plot(Xx,
up25,
label='Solution,t=0.25')
plt.plot(Xx,
up75,
label='Solution,t=0.75')
plt.plot(Xx,
Dup25,
label='Gradient,t=0.25')
plt.plot(Xx,
Dup75,
label='Gradient,t=0.75')
plt.plot(Xx,
afluxp25,
label='Advective Flux,t=0.25')
plt.plot(Xx,
afluxp75,
label='Advective Flux,t=0.75')
plt.plot(Xx,
dfluxp25,
label='Diffusive Flux,t=0.25')
plt.plot(Xx,
dfluxp75,
label='Diffusive Flux,t=0.75')
plt.plot(Xx,
tfluxp25,
label='Total Flux,t=0.25')
plt.plot(Xx,
tfluxp75,
label='Total Flux,t=0.75')
plt.legend()
plt.title("NonlinearADR_Decay_DiracIC.png")
plt.savefig("NonlinearADR_Decay_DiracIC.png")
def test_LinearADR_Decay_DiracIC():
logEvent("LinearADR_Decay_DiracIC")
sol = AnalyticalSolutions.LinearADR_Decay_DiracIC()
up25 = [sol.uOfXT(x, T=0.25) for x in X]
assert up25[midpoint_x_index] == 0.0045216528018377404
up75 = [sol.uOfXT(x, T=0.75) for x in X]
assert up75[midpoint_x_index] == 6.435494248102993e-09
Dup25 = [sol.duOfXT(x, T=0.25)[0] for x in X]
assert Dup25[midpoint_x_index] == -0.19346149763373902
Dup75 = [sol.duOfXT(x, T=0.75)[0] for x in X]
assert Dup75[midpoint_x_index] == -3.062985739327577e-07
afluxp25 = [sol.advectiveFluxOfXT(x, T=0.25)[0] for x in X]
assert afluxp25[midpoint_x_index] == 0.0045216528018377404
afluxp75 = [sol.advectiveFluxOfXT(x, T=0.75)[0] for x in X]
assert afluxp75[midpoint_x_index] == 6.435494248102993e-09
dfluxp25 = [sol.diffusiveFluxOfXT(x, T=0.25)[0] for x in X]
assert dfluxp25[midpoint_x_index] == 0.0019346149763373901
dfluxp75 = [sol.diffusiveFluxOfXT(x, T=0.75)[0] for x in X]
assert dfluxp75[midpoint_x_index] == 3.062985739327577e-09
tfluxp25 = [sol.totalFluxOfXT(x, T=0.25)[0] for x in X]
assert tfluxp25[midpoint_x_index] == 0.00645626777817513
tfluxp75 = [sol.totalFluxOfXT(x, T=0.75)[0] for x in X]
assert tfluxp75[midpoint_x_index] == 9.498479987430571e-09
if save_plots:
fig = plt.figure()
plt.plot(Xx,
up25,
label='Solution,t=0.25')
plt.plot(Xx,
up75,
label='Solution,t=0.75')
plt.plot(Xx,
Dup25,
label='Gradient,t=0.25')
plt.plot(Xx,
Dup75,
label='Gradient,t=0.75')
plt.plot(Xx,
afluxp25,
label='Advective Flux,t=0.25')
plt.plot(Xx,
afluxp75,
label='Advective Flux,t=0.75')
plt.plot(Xx,
dfluxp25,
label='Diffusive Flux,t=0.25')
plt.plot(Xx,
dfluxp75,
label='Diffusive Flux,t=0.75')
plt.plot(Xx,
tfluxp25,
label='Total Flux,t=0.25')
plt.plot(Xx,
tfluxp75,
label='Total Flux,t=0.75')
plt.legend()
plt.title("LinearADR_Decay_DiracIC.png")
plt.savefig("LinearADR_Decay_DiracIC.png")
def test_LinearAD_DiracIC():
logEvent("LinearAD_DiracIC")
sol = AnalyticalSolutions.LinearAD_DiracIC()
up25 = [sol.uOfXT(x, T=0.25) for x in X]
assert up25[midpoint_x_index] == 0.005805917122996999
up75 = [sol.uOfXT(x, T=0.75) for x in X]
assert up75[midpoint_x_index] == 1.362394143014481e-08
Dup25 = [sol.duOfXT(x, T=0.25)[0] for x in X]
assert Dup25[midpoint_x_index] == -0.24840948011219627
Dup75 = [sol.duOfXT(x, T=0.75)[0] for x in X]
assert Dup75[midpoint_x_index] == -6.484340861040867e-07
afluxp25 = [sol.advectiveFluxOfXT(x, T=0.25)[0] for x in X]
assert afluxp25[midpoint_x_index] == 0.005805917122996999
afluxp75 = [sol.advectiveFluxOfXT(x, T=0.75)[0] for x in X]
assert afluxp75[midpoint_x_index] == 1.362394143014481e-08
dfluxp25 = [sol.diffusiveFluxOfXT(x, T=0.25)[0] for x in X]
assert dfluxp25[midpoint_x_index] == 0.0024840948011219627
dfluxp75 = [sol.diffusiveFluxOfXT(x, T=0.75)[0] for x in X]
assert dfluxp75[midpoint_x_index] == 6.484340861040867e-09
tfluxp25 = [sol.totalFluxOfXT(x, T=0.25)[0] for x in X]
assert tfluxp25[midpoint_x_index] == 0.008290011924118962
tfluxp75 = [sol.totalFluxOfXT(x, T=0.75)[0] for x in X]
assert tfluxp75[midpoint_x_index] == 2.0108282291185675e-08
if save_plots:
fig = plt.figure()
plt.plot(Xx,
up25,
label='Solution,t=0.25')
plt.plot(Xx,
up75,
label='Solution,t=0.75')
plt.plot(Xx,
Dup25,
label='Gradient,t=0.25')
plt.plot(Xx,
Dup75,
label='Gradient,t=0.75')
plt.plot(Xx,
afluxp25,
label='Advective Flux,t=0.25')
plt.plot(Xx,
afluxp75,
label='Advective Flux,t=0.75')
plt.plot(Xx,
dfluxp25,
label='Diffusive Flux,t=0.25')
plt.plot(Xx,
dfluxp75,
label='Diffusive Flux,t=0.75')
plt.plot(Xx,
tfluxp25,
label='Total Flux,t=0.25')
plt.plot(Xx,
tfluxp75,
label='Total Flux,t=0.75')
plt.legend()
plt.title("LinearAD_DiracIC.png")
plt.savefig("LinearAD_DiracIC.png")
def test_LinearAD_SteadyState():
logEvent("AD_SteadyState")
sol = AnalyticalSolutions.LinearAD_SteadyState()
y = [sol.uOfX(x) for x in X]
assert y[midpoint_x_index] == 0.9882908500750013
if save_plots:
fig = plt.figure()
plt.plot(Xx, y, label='Solution,q=1,r=1')
plt.legend()
plt.title("LinearAD_SteadyStage")
plt.savefig("LinearAD_SteadyState.png")
return np.array([0.0, 0.0, round(x[2], 5)])
elif (x[1] < eps) or (x[1] > p.L[1] - eps): #on front or back
return np.array([round(x[0], 5), 0.0, round(x[2], 5)])
elif (x[0] < eps) or (
x[0] > p.L[0] - eps): #on inflow or outflow (left/right)
return np.array([0.0, round(x[1], 5), round(x[2], 5)])
p.periodicDirichletConditions = {
0: getPDBC,
1: getPDBC,
2: getPDBC,
3: getPDBC
}
pSol2 = AnalyticalSolutions.PlanePoiseuilleFlow_p(plateSeperation=h,
mu=mu,
grad_p=-G)
uSol2 = AnalyticalSolutions.PlanePoiseuilleFlow_u(plateSeperation=h,
mu=mu,
grad_p=-G)
vSol2 = AnalyticalSolutions.PlanePoiseuilleFlow_v(plateSeperation=h,
mu=mu,
grad_p=-G)
class pRot(AnalyticalSolutions.SteadyState):
def __init__(self):
pass
def uOfX(self, x):
if p.nd == 3:
self.val = val
self.ztop = ztop
self.zbot = zbot
self.delta_z = delta_z
def uOfX(self, x):
fact = exp(-(x[2] - self.zbot) * (self.ztop - x[2]) / self.delta_z)
return self.val * (1.0 - fact)
if use_PlanePoiseuille:
uProfile = AnalyticalSolutions.PlanePoiseuilleFlow_u2(
plane_theta=0.0,
plane_phi=0.0,
v_theta=0.0,
v_phi=math.pi / 2.0,
v_norm=0.0,
mu=mu_0,
grad_p=grad_p,
L=[1.0, 1.0, upstream_height])
else:
uProfile = u_flat(val=inflow)
def velRamp(t):
if t < residence_time:
return 1.0 - exp(-25.0 * t / residence_time)
else:
return 1.0
