def objective(fields, solver):
U, T, p = fields
mesh = solver.mesh.symMesh
def _meshArgs(start=0):
return [x[start] for x in mesh.getTensor()]
patch = mesh.boundary['obstacle']
startFace, nFaces = patch['startFace'], patch['nFaces']
meshArgs = _meshArgs(startFace)
test = tensor.Zeros((1, 1))
test = tensor.Kernel(objectiveTest)(nFaces, (test, ))(U, T, p, *meshArgs)
inputs = (test, )
outputs = tuple([tensor.Zeros(x.shape) for x in inputs])
(test, ) = tensor.ExternalFunctionOp('mpi_allreduce', inputs,
outputs).outputs
return test
def objective(fields, solver):
U, T, p = fields
mesh = solver.mesh.symMesh
def _meshArgs(start=0):
return [x[start] for x in mesh.getTensor()]
nPlaneCells, cells, areas = [x[0] for x in solver.extraArgs[:3]]
w = tensor.Zeros((1, 1))
w = tensor.Kernel(objectivePressureLossWeighting)(nPlaneCells,
(w, ))(U,
T,
p,
cells,
areas,
solver=solver)
weights = [x[0] for x in solver.extraArgs[3:]]
w2 = tensor.Zeros((1, 1))
_heatTransferWeighting = tensor.Kernel(objectiveHeatTransferWeighting)
for index, patchID in enumerate(patches):
patch = mesh.boundary[patchID]
startFace, nFaces = patch['startFace'], patch['nFaces']
meshArgs = _meshArgs(startFace)
weight = weights[index]
w2 = _heatTransferWeighting(nFaces, (w2, ))(weight, *meshArgs)
inputs = (w, w2)
outputs = tuple([tensor.Zeros(x.shape) for x in inputs])
w, w2 = tensor.ExternalFunctionOp('mpi_allreduce', inputs, outputs).outputs
pl = tensor.Zeros((1, 1))
pl = tensor.Kernel(objectivePressureLoss)(nPlaneCells,
(pl, ))(U,
T,
p,
cells,
areas,
w,
solver=solver)
_heatTransfer = tensor.Kernel(objectiveHeatTransfer)
ht = tensor.Zeros((1, 1))
for index, patchID in enumerate(patches):
patch = mesh.boundary[patchID]
startFace, nFaces = patch['startFace'], patch['nFaces']
meshArgs = _meshArgs(startFace)
weight = weights[index]
ht = _heatTransfer(nFaces, (ht, ))(U,
T,
p,
weight,
w2,
*meshArgs,
solver=solver)
k = solver.mu(300) * solver.Cp / solver.Pr
a = 0.4
#b = -0.71e-3/(120*k)/2000.
b = 0.
# MPI ALLREDUCE
#if not config.gpu:
# inputs = (pl, w, ht, w2)
# outputs = tuple([tensor.Zeros(x.shape) for x in inputs])
# pl, w, ht, w2 = tensor.ExternalFunctionOp('mpi_allreduce', inputs, outputs).outputs
inputs = (pl, ht)
outputs = tuple([tensor.Zeros(x.shape) for x in inputs])
pl, ht = tensor.ExternalFunctionOp('mpi_allreduce', inputs,
outputs).outputs
# then elemwise
def _combine(pl, ht):
pl = pl.scalar()
ht = ht.scalar()
obj = pl
obj2 = ht
return a * obj + b * obj2
return tensor.Kernel(_combine)(1)(pl, ht)