def addKernels(db, kernels, dofMatrixName):
# Kernels
for i in range(0, 4):
godunovStatePlus = db['nP{}'.format(
i + 1)] * db[dofMatrixName] * db['godunovMatrix']
kernels.append(
Kernel.Prototype('godunovState[{}]'.format(i * 4),
godunovStatePlus,
beta=0,
prefetch=godunovStatePlus))
flux = db['pP{}'.format(i + 1)] * db['godunovState'] * db['fluxSolver']
kernels.append(
Kernel.Prototype('nodalFlux[{}]'.format(i * 4),
flux,
prefetch=db['godunovState']))
for h in range(1, 4):
godunovStateMinus = db['nM{}{}'.format(
i + 1, h)] * db[dofMatrixName] * db['godunovMatrix']
kernels.append(
Kernel.Prototype('godunovState[{}]'.format(i * 4 + h),
godunovStateMinus,
beta=1,
prefetch=godunovStateMinus))
flux = db['pM{}{}'.format(
i + 1, h)] * db['godunovState'] * db['fluxSolver']
kernels.append(
Kernel.Prototype('nodalFlux[{}]'.format(i * 4 + h),
flux,
prefetch=db['godunovState']))
def addKernels(db, kernels):
evaluateAtNodes = db['v'] * db['stressDOFS']
db.insert(evaluateAtNodes.flat('interpolationDOFS'))
kernels.append(Kernel.Prototype('evaluateAtNodes', evaluateAtNodes, beta=0))
convertToModal = db['vInv'] * db['interpolationDOFS']
kernels.append(Kernel.Prototype('convertToModal', convertToModal, beta=0))
def addKernels(db, kernels):
for depth in range(0, maxDepth + 1):
subTriangleProjection = db['subTriangleProjectionMatrix{}'.format(
depth)] * db['velocityDOFS']
kernels.append(
Kernel.Prototype('subTriangleProjection[{}]'.format(depth),
subTriangleProjection,
beta=0))
(r'^fP(\d{1})$', lambda x: 18 + (int(x[0])-1))
]
DB.determineGlobalMatrixIds(globalMatrixIdRules, db)
# Kernels
kernels = list()
db.insert(DB.MatrixInfo('reducedTimeIntegratedDofs', numberOfBasisFunctions, numberOfReducedQuantities))
db.insert(DB.MatrixInfo('reducedDofs', numberOfBasisFunctions, numberOfReducedQuantities))
db.insert(DB.MatrixInfo('mechanism', numberOfBasisFunctions, numberOfMechanismQuantities))
db.insert(DB.MatrixInfo('timeDerivative0_elastic', numberOfBasisFunctions, numberOfElasticQuantities))
volume = db['kXiDivM'] * db['reducedTimeIntegratedDofs'] * db['AstarT'] \
+ db['kEtaDivM'] * db['reducedTimeIntegratedDofs'] * db['BstarT'] \
+ db['kZetaDivM'] * db['reducedTimeIntegratedDofs'] * db['CstarT']
kernels.append(Kernel.Prototype('volume', volume, beta=0))
for i in range(0, 4):
localFlux = db['r{}DivM'.format(i+1)] * db['fMrT{}'.format(i+1)] * db['reducedTimeIntegratedDofs'] * db['AplusT']
prefetch = None
if i == 0:
prefetch = db['reducedTimeIntegratedDofs']
elif i == 1:
prefetch = localFlux
else:
prefetch = Kernel.DummyPrefetch()
kernels.append(Kernel.Prototype('localFlux[{}]'.format(i), localFlux, prefetch=prefetch))
for i in range(0, 4):
for j in range(0, 4):
for h in range(0, 3):
DB.determineGlobalMatrixIds(globalMatrixIdRules, db)
# Kernels
kernels = list()
db.insert(
DB.MatrixInfo('timeIntegrated', numberOfBasisFunctions,
numberOfQuantities))
db.insert(
DB.MatrixInfo('timeDerivative0', numberOfBasisFunctions,
numberOfQuantities))
volume = db['kXiDivM'] * db['timeIntegrated'] * db['AstarT'] \
+ db['kEtaDivM'] * db['timeIntegrated'] * db['BstarT'] \
+ db['kZetaDivM'] * db['timeIntegrated'] * db['CstarT']
kernels.append(Kernel.Prototype('volume', volume))
for i in range(0, 4):
localFlux = db['r{}DivM'.format(i + 1)] * db['fMrT{}'.format(
i + 1)] * db['timeIntegrated'] * db['AplusT']
prefetch = None
if i == 0:
prefetch = db['timeIntegrated']
elif i == 1:
prefetch = localFlux
else:
prefetch = Kernel.DummyPrefetch()
kernels.append(
Kernel.Prototype('localFlux[{}]'.format(i),
localFlux,
prefetch=prefetch))