pyADflow API

class adflow.pyADflow.ADFLOW(*args, **kwargs)[source]

Create the ADflow object.

Parameters
commMPI intra comm

The communicator on which to create ADflow. If not given, defaults to MPI.COMM_WORLD.

optionsdict

The list of options to use with ADflow. This keyword argument is NOT OPTIONAL. It must always be provided. It must contain, at least the ‘gridFile’ entry for the filename of the grid to load

debugbool

Set this flag to true when debugging with a symbolic debugger. The MExt module deletes the copied .so file when not required which causes issues debugging.

dtypestr

String type for float: ‘d’ or ‘D’. Not needed to be used by user.

addActuatorRegion(fileName, axis1, axis2, familyName, thrust=0.0, torque=0.0, heat=0.0, relaxStart=None, relaxEnd=None, coordXfer=None)[source]

Add an actuator disk zone defined by the supplied closed surface in the plot3d file “fileName”. This surface defines the physical extent of the region over which to apply the source terms. Internally, we find all of the CFD volume cells that are inside this closed surface and apply the source terms over these cells. This surface is only used with the original mesh coordinates to mark the internal CFD cells, and we keep using these cells even if the geometric design and the mesh coordinates change. For example, the marked cells can lie outside of the original closed surface after a large design change, but we will still use the cells that were inside the surface with the baseline design.

axis1 and axis2 define the vector that we use to determine the direction of the thrust addition. Internally, we compute a vector by $axisVec = axis2-axis1$ and then we normalize this vector. When adding the thrust terms, the direction of the thrust is obtained by multiplying the thrust magnitude by this vector.

Optionally, the source terms in the actuator zone can be gradually ramped up as the solution converges. This continuation approach can be more robust but the users should be careful with the side effects of partially converged solutions. This behavior can be controlled by relaxStart and relaxEnd parameters. By default, the full magnitude of the source terms are added. relaxStart controls when the continuation starts ramping up. The value represents the relative convergence in a log10 basis. So relaxStart = 2 means the source terms will be inactive until the residual is decreased by a factor of 100 compared to free stream conditions. The source terms are ramped to the full magnitude at relaxEnd. E.g., a relaxEnd value of 4 would result in the full source terms after a relative reduction of 1e4 in the total residuals. If relaxStart is not provided, but relaxEnd is provided, then the relaxStart is assumed to be 0. If both are not provided, we do not do ramping and just activate the full source terms from the beginning. When this continuation is used, we internally ramp up the magnitude of the source terms monotonically to prevent oscillations; i.e., decrease in the total residuals increase the source term magnitudes, but an increase in the residuals do not reduce the source terms back down.

Parameters
fileNamestr

Surface Plot 3D file (multiblock ascii) defining the closed region over which the integration is to be applied.

axis1numpy array, length 3

The physical location of the start of the axis

axis2numpy array, length 4

The physical location of the end of the axis

familyNamestr

The name to be associated with the functions defined on this region.

thrustscalar, float

The total amount of axial force to apply to this region, in the direction of axis1 -> axis2

torquescalar, float

The total amount of torque to apply to the region, about the specified axis.

heatscalar, float

The total amount of head added in the actuator zone with source terms

relaxStartscalar, float

The start of the relaxation in terms of orders of magnitude of relative convergence

relaxEndscalar, float

The end of the relaxation in terms of orders of magnitude of relative convergence

coordXferfunction

A callback function that performs a coordinate transformation between the original reference frame and any other reference frame relevant to the current CFD case. This allows user to apply arbitrary modifications to the loaded plot3d surface. The call signature is documented in DVGeometry’s addPointset method.

addArbitrarySlices(normals, points, sliceType='relative', groupName=None, sliceDir=None)[source]

Add slices that vary arbitrarily in space. This is a generalization of the addSlices routine, where we have the user specify a list of “normals” and “points” that define slice planes. Rest of the code is the same. This way users can add slices that follow the dihedral of a wing for example.

Parameters
normals3-d array or ndarray (nSlice, 3)

The normals of the slice directions. If an array of size 3 is passed, we use the same normal for all slices. if an array of multiple normals are passed, we use the individual normals for each point. in this case, the numbers of points and normals must match.

pointsndarray (nSlice, 3)

Point coordinates that define a slicing plane along with the normals

sliceDirndarray (nSlice, 3)

If this is provided, only the intersections that is in this direction starting from the normal is kept. This is useful if you are slicing a closed geometry and only want to keep one side of it. It is similar to the functionality provided in addCylindricalSlices.

sliceTypestr {‘relative’, ‘absolute’}

Relative slices are ‘sliced’ at the beginning and then parametrically move as the geometry deforms. As a result, the slice through the geometry may not remain planar. An absolute slice is re-sliced for every output so is always exactly planar and always at the initial position the user indicated.

groupNamestr

The family to use for the slices. Default is None corresponding to all wall groups.

addCylindricalSlices(pt1, pt2, nSlice=25, sliceBeg=0.0, sliceEnd=360.0, sliceType='relative', groupName=None)[source]

Add cylindrical projection slices. The cylindrical projection axis is defined from pt1 to pt2. Then we start from the lift direction and rotate around this axis until we are back at the beginning. The rotation direction follows the right hand rule; we rotate the plane in the direction of vectors from pt1 to pt2 crossed with the lift direction. This routine will not work as is if the cylinder axis is exactly aligned with the lift direction. If that use case is needed, consider using addArbitrarySlices.

Parameters
pt1numpy array, length 3

beginning point of the vector that defines the rotation axis

pt2numpy array, length 3

end point of the vector that defines the rotation axis

nSliceint

number of slices around a 360 degree full rotation.

sliceBegfloat

beginning of the slices in the rotation direction in degrees

sliceEndfloat

end of the slices in the rotation direction in degrees

sliceTypestr {‘relative’, ‘absolute’}

Relative slices are ‘sliced’ at the beginning and then parametrically move as the geometry deforms. As a result, the slice through the geometry may not remain planar. An absolute slice is re-sliced for every output so is always exactly planar and always at the initial position the user indicated.

groupNamestr

The family to use for the slices. Default is None corresponding to all wall groups.

addFunction(funcName, groupName, name=None)[source]

Add a “new” function to ADflow by restricting the integration of an existing ADflow function by a section of the mesh defined by ‘groupName’. The function will be named ‘funcName_groupName’ provided that the ‘name’ keyword argument is not given. It is is, the function will be use that name. If necessary, this routine may be used to “change the name” of a function. For example,

>>> addFunction('cd', None, 'super_cd')

will add a function that is the same as ‘cd’, but called ‘super_cd’.

Parameters
funcNamestr or list

The name of the built-in adflow function

groupNamestr or list

The family or group of families to use for the function

Namestr or list

An overwrite name.

Returns
nameslist

The names if the functions that were added

addFunctions(funcNames, groupNames, names=None)[source]

Add a series of new functions to ADflow. This is a vector version of the addFunction() routine. See that routine for more documentation.

addIntegrationSurface(fileName, familyName, isInflow=True, coordXfer=None)[source]

Add a specific integration surface for performing massflow-like computations.

Parameters
fileNamestr

Surface Plot 3D file (may have multiple zones) defining integration surface.

familyNamestr

User supplied name to use for this family. It should not already be a name that is defined by the surfaces of the CGNS file.

isInflowbool

Flag to treat momentum forces as if it is an inflow or outflow face. Default is True

coordXferfunction

A callback function that performs a coordinate transformation between the original reference frame and any other reference frame relevant to the current CFD case. This allows user to apply arbitrary modifications to the loaded plot3d surface. The call signature is documented in DVGeometry’s addPointset method.

addLiftDistribution(nSegments, direction, groupName=None)[source]

Add a lift distribution to the surface output.

Parameters
nSegmentsint

Number of slices to use for the distribution. Typically 150-250 is sufficient

directionstr {‘x’, ‘y’, ‘z’}

The normal of the slice direction. If you have z-axis ‘out the wing’ you would use ‘z’

groupName: str

The family group to use for the lift distribution. Default of None corresponds to all wall surfaces.

addSlices(direction, positions, sliceType='relative', groupName=None)[source]

Add parametric slice positions. Slices are taken of the wing at time addParaSlices() is called and the parametric positions of the intersections on the surface mesh are stored. On subsequent output, the position of the slice moves as the mesh moves/deforms. This effectively tracks the same location on the wing.

Parameters
directionstr {‘x’, ‘y’, ‘z’}

The normal of the slice direction. If you have z-axis ‘out the wing’ you would use ‘z’

positionsfloat or array

The list of slice positions along the axis given by direction.

sliceTypestr {‘relative’, ‘absolute’}

Relative slices are ‘sliced’ at the beginning and then parametrically move as the geometry deforms. As a result, the slice through the geometry may not remain planar. An absolute slice is re-sliced for every output so is always exactly planar and always at the initial position the user indicated.

groupNamestr

The family to use for the slices. Default is None corresponding to all wall groups.

addUserFunction(funcName, functions, callBack)[source]

Add a new function to ADflow by combining existing functions in a user-supplied way. The allows the user to define a function such as L/D while only requiring a single adjoint solution.

Parameters
funcNamestr

The name of user-supplied function

functionslist of strings

The exisitng function strings which are the input to the callBack function

callBackpython function handle

The user supplied function that will produce the user function. This routine must be complex-step safe for the purpose of computing sensitivities.

Examples

>>> ap = AeroProblem(....,evalFuncs=['L/D'])
>>> CFDSolver = ADFLOW(options=....)
>>> def LoverD(funcs):
        funcs['L/D'] = funcs['cl']/funcs['cd']
        return funcs
>>> CFDSolver.addUserFunction('L/D', ['cl','cd'], LoverD)
advanceTimeStepCounter()[source]

Advance one unit of timestep and physical time.

checkPartitioning(nprocs)[source]

This function determines the potential load balancing for nprocs. The intent is this function can be run in serial to determine the best number of procs for load balancing. The grid is never actually loaded so this function can be run with VERY large grids without issue.

Parameters
nProcsint

The number of procs check partitioning on

Returns
loadInbalancefloat

The fraction of inbalance for cells. 0 is good. 1.0 is really bad

faceInbalancefloat

The fraction of inbalance for faces. This gives an idea of communication code. 0 is god. 1.0 is really bad.

computeJacobianVectorProductBwd(resBar=None, funcsBar=None, fBar=None, wDeriv=None, xVDeriv=None, xSDeriv=None, xDvDeriv=None, xDvDerivAero=None)[source]

This the main python gateway for producing reverse mode jacobian vector products. It is not generally called by the user by rather internally or from another solver. A mesh object must be present for the xSDeriv=True flag and a mesh and DVGeo object must be present for xDvDeriv=True flag. Note that more than one of the specified return flags may be spcified. If more than one return is specified, the order of return is : (wDeriv, xVDeriv, XsDeriv, xDvDeriv, dXdvDerivAero).

Parameters
resBarnumpy array

Seed for the residuals (dwb in adflow)

funcsBardict

Dictionary of functions with reverse seeds. Only nonzero seeds need to be provided. All other seeds will be taken as zero.

fBarnumpy array

Seed for the forces (or tractions depending on the option value) to use in reverse mode.

wDerivbool

Flag specifiying if the state (w) derivative (wb) should be returned

xVDerivbool

Flag specifiying if the volume node (xV) derivative should be returned

xSDerivbool

Flag specifiying if the surface node (xS) derivative should be returned.

xDvDerivbool

Flag specifiying if the design variable (xDv) derviatives should be returned. This will include both geometric and aerodynamic derivatives

xDvDerivAerobool

Flag to return just the aerodynamic derivatives. If this is True and xDvDeriv is False,*just* the aerodynamic derivatives are returned.

Returns
wbar, xvbar, xsbar, xdvbar, xdvaerobararray, array, array, dict, dict

One or more of these are returned depending on the *Deriv flags provided.

computeJacobianVectorProductBwdFast(resBar=None)[source]

This fast routine computes only the derivatives of the residuals with respect to the states. This is the operator used for the matrix-free solution of the adjoint system.

Parameters
resBarnumpy array

Seed for the residuals (dwb in adflow)

Returns
wbar: array

state derivative seeds

computeJacobianVectorProductFwd(xDvDot=None, xSDot=None, xVDot=None, wDot=None, residualDeriv=False, funcDeriv=False, fDeriv=False, groupName=None, mode='AD', h=None, evalFuncs=None)[source]

This the main python gateway for producing forward mode jacobian vector products. It is not generally called by the user by rather internally or from another solver. A DVGeo object and a mesh object must both be set for this routine. Parameters ———- xDvDot : dict

Perturbation on the geometric design variables defined in DVGeo.

xSDotnumpy array

Perturbation on the surface

xVDotnumpy array

Perturbation on the volume

wDotnumpy array

Perturbation the state variables

residualDerivbool

Flag specifiying if the residualDerivative (dwDot) should be returned

funcDerivbool

Flag specifiying if the derviative of the cost functions (as defined in the current aeroproblem) should be returned.

fderivbool

Flag specifiying if the derviative of the surface forces (tractions) should be returned

groupNamestr

Optional group name to use for evaluating functions. Defaults to all surfaces.

modestr [“AD”, “FD”, or “CS”]

Specifies how the jacobian vector products will be computed.

hfloat

Step sized used when the mode is “FD” or “CS

Returns

dwdot, funcsdot, fDotarray, dict, array

One or more of the these are return depending on the *Deriv flags

computeStabilityParameters()[source]

run the stability derivative driver to compute the stability parameters from the time spectral solution

evalFunctions(aeroProblem, funcs, evalFuncs=None, ignoreMissing=False)[source]

Evaluate the desired functions given in iterable object, ‘evalFuncs’ and add them to the dictionary ‘funcs’. The keys in the funcs dictionary will be have an <ap.name>_ prepended to them.

Parameters
aeroProblempyAero_problem class

The aerodynamic problem to to get the solution for

funcsdict

Dictionary into which the functions are saved.

evalFuncsiterable object containing strings

If not None, use these functions to evaluate.

ignoreMissingbool

Flag to suppress checking for a valid function. Please use this option with caution.

Examples

>>> funcs = {}
>>> CFDsolver(ap)
>>> CFDsolver.evalFunctions(ap1, funcs, ['cl', 'cd'])
>>> funcs
>>> # Result will look like (if aeroProblem, ap1, has name of 'wing'):
>>> # {'wing_cl':0.501, 'wing_cd':0.02750}
evalFunctionsSens(aeroProblem, funcsSens, evalFuncs=None)[source]

Evaluate the sensitivity of the desired functions given in iterable object, ‘evalFuncs’ and add them to the dictionary ‘funcSens’. The keys in the ‘funcsSens’ dictionary will be have an <ap.name>_ prepended to them.

Parameters
funcSensdict

Dictionary into which the function derivatives are saved.

evalFuncsiterable object containing strings

The additional functions the user wants returned that are not already defined in the aeroProblem

Examples

>>> funcSens = {}
>>> CFDsolver.evalFunctionsSens(ap1, funcSens, ['cl', 'cd'])
getAdjoint(objective)[source]

Return the adjoint values for objective if they exist. Otherwise just return zeros

getAdjointResNorms()[source]

Return the following adjoint residual norms: initRes Norm: Norm the adjoint RHS startRes Norm: Norm at the start of adjoint call (with possible non-zero restart) finalCFD Norm: Norm at the end of adjoint solve

getAdjointStateSize()[source]

Return the number of ADJOINT degrees of freedom (states) that are on this processor. The reason this is different from getStateSize() is that if frozenTurbulence is used for RANS, the nonlinear system has 5+neq turb states per cell, while the adjoint still has 5.

getConvergenceHistory(workUnitTime=None)[source]

Retrieve the convergence history from the fortran level.

This information is printed to the terminal during a run. It is iterTot, IterType, CFL, Step, Linear Res, and CPU time (if added as a monitor variable) and the data for each monitor variable.

Parameters
workUnitTimefloat

The scaling factor specific to the processor. If provided and CPU time is a monitor variable (showcpu is true), the work units (a processor independent time unit) ~will be added to the returned dict too.

Returns
convergeDictdict

A dictionary of arrays and lists. The keys are the data types. The indices of the arrays are the major iteration numbers.

Examples

>>> CFDsolver(ap)
>>> CFDsolver.evalFunctions(ap1, funcs, ['cl', 'cd'])
>>> hist = CFDSolver.getConvergenceHistory()
>>> if MPI.COMM_WORLD.rank == 0:
>>>     with open(os.path.join(output_dir, "convergence_history.pkl"), "wb") as f:
>>>         pickle.dump(hist, f)
getForces(groupName=None, TS=0)[source]

Return the forces on this processor on the families defined by groupName.

Parameters
groupNamestr

Group identifier to get only forces cooresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

TSint

Spectral instance for which to get the forces

Returns
forcesarray (N,3)

Forces (or tractions depending on that forceAsTractions options) on this processor. Note that N may be 0, and an empty array of shape (0, 3) can be returned.

getHeatFluxes(groupName=None, TS=0)[source]

Return the heat fluxes for isothermal walls on the families defined by group name on this processor.

Parameters
groupNamestr

Group identifier to get only heat fluxes cooresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

TSint

Spectral instance for which to get the fluxes.

Returns
heatFluxesarray (N)

HeatFluxes on this processor. Note that N may be 0, and an empty array of shape (0) can be returned.

getPointSetName(apName)[source]

Take the apName and return the mangled point set name.

getResNorms()[source]

Return the initial, starting and final Res Norms. Typically used by an external solver.

getResidual(aeroProblem, res=None, releaseAdjointMemory=True)[source]

Return the residual on this processor. Used in aerostructural analysis

getSolution(groupName=None)[source]

Retrieve the basic solution variables from the solver. This will return all variables defined in basicCostFunctions for the specified group. This is a lower level function than evalFunctions() which should be used for optimization.

Parameters
groupNamestr

The family group on which to evaluate the functions.

getSolverMeshIndices()[source]

Get the list of indices to pass to the mesh object for the volume mesh mapping

getSpatialPerturbation(seed=314)[source]

This is is a debugging routine only. It is used only in regression tests when it is necessary to compute a consistent random spatial vector seed that is independent of per-processor block distribution.

Parameters
seedinteger

Seed to use for random number. Only significant on root processor

getSpatialSize()[source]

Return the number of degrees of spatial degrees of freedom on this processor. This is (number of nodes)*(number of spectral instances)*3

getStatePerturbation(seed=314)[source]

This is is a debugging routine only. It is used only in regression tests when it is necessary to compute a consistent random state vector seed that is independent of per-processor block distribution. This routine is not memory scalable as a complete state vector is generated on each process.

Parameters
seedinteger

Seed to use for random number. Only significant on root processor

getStateSize()[source]

Return the number of degrees of freedom (states) that are on this processor. This is (number of states)*(number of cells)*(number of spectral instances)

getStates()[source]

Return the states on this processor. Used in aerostructural analysis

getSurfaceConnectivity(groupName=None, includeZipper=True, includeCGNS=False)[source]

Return the connectivity dinates at which the forces (or tractions) are defined. This is the complement of getForces() which returns the forces at the locations returned in this routine.

Parameters
groupNamestr

Group identifier to get only forces cooresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

includeCGNSbool

Whether or not this function should return the indices of the CGNS blocks that each face patch belongs to. Zipper mesh patches will have cgnsBlockID = -1.

getSurfacePerturbation(seed=314)[source]

This is is a debugging routine only. It is used only in regression tests when it is necessary to compute a consistent random surface perturbation seed that is independent of per-processor block distribution.

Parameters
seedinteger

Seed to use for random number. Only significant on root processor

getSurfacePoints(groupName=None, includeZipper=True, TS=0)[source]

Return the coordinates for the surfaces defined by groupName.

Parameters
groupNamestr

Group identifier to get only coordinates cooresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

TSint

The time spectral instance to use for the forces.

getUniqueSpatialPerturbationNorm(dXv)[source]

This is is a debugging routine only. It is used only in regression tests when it is necessary to compute the norm of a spatial perturbuation on meshes that are split. This will unique-ify the nodes and accumulate onto the unique nodes thus giving the same norm independent of the block splits. Again, this routine is not memory scalable and should only be used for debugging purposes.

Parameters
dXvnumpy vector

Spatial perturbation of size getSpatialSize()

globalAdjointPreCon(inVec, outVec)[source]

This function is ONLY used as a preconditioner to the global Aero-Structural ADJOINT system. This computes outVec = M^(-1)*inVec where M^(-1) is the approximate inverse application of the preconditing matrix.

Parameters
inVecarray

inVec must be size self.getAdjointStateSize()

Returns
outVecarray

Preconditioned vector

globalNKPreCon(inVec, outVec)[source]

This function is ONLY used as a preconditioner to the global Aero-Structural system. This computes outVec = M^(-1)*inVec where M^(-1) is the approximate inverse application of the preconditing matrix.

Parameters
inVecarray

inVec must be size self.getStateSize()

Returns
outVecarray

Preconditioned vector

mapVector(vec1, groupName1, groupName2, vec2=None, includeZipper=True)[source]

This is the main workhorse routine of everything that deals with families in ADflow. The purpose of this routine is to convert a vector ‘vec1’ (of size Nx3) that was evaluated with ‘groupName1’ and expand or contract it (and adjust the ordering) to produce ‘vec2’ evaluated on groupName2.

A little ascii art might help. Consider the following “mesh” . Family ‘fam1’ has 9 points, ‘fam2’ has 10 pts and ‘fam3’ has 5 points. Consider that we have also also added two additional groups: ‘f12’ containing ‘fam1’ and ‘fam2’ and a group ‘f23’ that contains families ‘fam2’ and ‘fam3’. The vector we want to map is ‘vec1’. It is length 9+10. All the ‘x’s are significant values.

The call: mapVector(vec1, ‘f12’, ‘f23’)

will produce the “returned vec” array, containing the significant values from ‘fam2’, where the two groups overlap, and the new values from ‘fam3’ set to zero. The values from fam1 are lost. The returned vec has size 15.

    fam1     fam2      fam3
|---------+----------+------|

|xxxxxxxxx xxxxxxxxxx|        <- vec1
          |xxxxxxxxxx 000000| <- returned vec (vec2)

It is also possible to pass in vec2 into this routine. For that case, the existing values in the array will not be kept. In the previous examples, the values corresponding to fam3 will retain their original values.

Parameters
vec1Numpy array

Array of size Nx3 that will be mapped to a different family set.

groupName1str

The family group where the vector vec1 is currently defined

groupName2str

The family group where we want to the vector to mapped into

vec2Numpy array or None

Array containing existing values in the output vector we want to keep. If this vector is not given, the values will be filled with zeros.

Returns
vec2Numpy array

The input vector maped to the families defined in groupName2.

propagateUncertainty(aeroProblem, evalFuncs=None, UQDict=None)[source]

Use the first order second moment method to predict output uncertainties for the current solution.

Parameters
aeroProblempyAero_problem class

The aerodynamic problem to solve

evalFuncsiterable object containing strings

The functions the user wants the uncertainty of

UQDictdict

Dictionary containing the mean and std dev. of the input parameters that are providing the uncertain input.

releaseAdjointMemory()[source]

release the PETSc Memory that have been allocated

resetAdjoint(obj)[source]

Reset an adjoint ‘obj’ that is stored in the current aeroProblem. If the adjoint does not yet exist, nothing is done

Parameters
objstr

String identifing the objective.

resetFlow(aeroProblem, releaseAdjointMemory=True)[source]

Reset the flow after a failure or for a complex step derivative operation.

Parameters
aeroProblempyAero_problem object

The aeroproblem with the flow information we would like to reset the flow to.

saveAdjointMatrix(baseFileName)[source]

Save the adjoint matrix to a binary petsc file for possible future external testing

Parameters
basefileNamestr

Filename to use. The Adjoint matrix, PC matrix(if it exists) and RHS will be written

setAdjoint(adjoint, objective=None)[source]

Sets the adjoint vector externally. Used in coupled solver

setAeroProblem(aeroProblem, releaseAdjointMemory=True)[source]

Set the supplied aeroProblem to be used in ADflow

setDisplacements(aeroProblem, dispFile)[source]

This function allows the user to perform aerodynamic analysis/optimization while using a fixed set of displacements computed from a previous structural analysis. Essentially this allows the jig shape to designed, but performing analysis on the flying shape.

Parameters
aeroProblemaeroProblem class

The AP object that the displacements should be applied to.

dispFilestr

The file contaning the displacements. This file should have been obtained from TACS

Notes

The fixed set of displacements do not affect the sensitivities, since they are fixed and not affected by any DVs.

Also, in the case where the current surface mesh was not used to generate the displacements file, a nearest neighbor search is used to apply the displacements.

setMesh(mesh)[source]

Set the mesh object to the aero_solver to do geometric deformations

Parameters
meshMBMesh or USMesh object

The mesh object for doing the warping

setOption(name, value)[source]

Set Solver Option Value

setResNorms(initNorm=None, startNorm=None, finalNorm=None)[source]

Set one of these norms if not None. Typlically used by an external solver

setRotationRate(rotCenter, rotRate, cgnsBlocks=None)[source]

Set the rotational rate for the grid:

rotCenter: 3-vectorThe center of rotation for steady motion rotRate: 3-vector or aeroProblem: If it is a 3-vector, take the rotations to about x-y-z, if it is an aeroProblem with p,q,r, defined, use that to compute rotations. cgnsBlocks: The list of blocks to set. NOTE: This must be in 1-based ordering!

setStates(states)[source]

Set the states on this processor. Used in aerostructural analysis and for switching aeroproblems

setSurfaceCoordinates(coordinates, groupName=None)[source]

Set the updated surface coordinates for a particular group.

Parameters
coordinatesnumpy array

Numpy array of size Nx3, where N is the number of coordinates on this processor. This array must have the same shape as the array obtained with getSurfaceCoordinates()

groupNamestr

Name of family or group of families for which to return coordinates for.

setTargetCp(CpTargets, groupName=None, TS=0)[source]

Set the CpTarget distribution for am inverse design problem.

Parameters
CpSurfnumpy array

Array of CP targets to set for the surface. This size must correpsond to the size of the surface obtained using the same groupName.

groupNamestr

Group identifier to set only CPtargets corresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

TSint

Time spectral instance to set.

setWallTemperature(temperature, groupName=None, TS=0)[source]

Set the temperature of the isothermal walls.

Parameters
temperaturenumpy array

Dimensional temperature to set for wall. This size must correpsond to the size of the heat flux obtained using the same groupName.

groupNamestr

Group identifier to set only temperatures corresponding to the desired group. The group must be a family or a user-supplied group of families. The default is None which corresponds to all wall-type surfaces.

TSint

Time spectral instance to set.

solveAdjointForRHS(inVec, relTol=None)[source]

Solve the adjoint system with an arbitary RHS vector.

Parameters
inVecnumpy array

Array of size w

Returns
outVecnumpy array

Solution vector of size w

solveCL(aeroProblem, CLStar, alpha0=None, delta=0.5, tol=0.001, autoReset=True, CLalphaGuess=None, maxIter=20, nReset=25)[source]

This is a simple secant method search for solving for a fixed CL. This really should only be used to determine the starting alpha for a lift constraint in an optimization.

Parameters
aeroProblempyAero_problem class

The aerodynamic problem to solve

CLStarfloat

The desired target CL

alpha0angle (deg)

Initial guess for secant search (deg). If None, use the value in the aeroProblem

deltaangle (deg)

Initial step direction for secant search

tolfloat

Desired tolerance for CL

autoResetbool

Flag to reset flow between solves. The Euler NK method has issues when only the alpha is changed (Martois effect we think). This will reset the flow after each solve which solves this problem. Not necessary (or desired) when using the RK solver.

CLalphaGuessfloat or None

The user can provide an estimate for the lift curve slope in order to accelerate convergence. If the user supply a value to this option, it will not use the delta value anymore to select the angle of attack of the second run. The value should be in 1/deg.

Returns
None, but the correct alpha is stored in the aeroProblem
solveDirectForRHS(inVec, relTol=None)[source]

Solve the direct system with an arbitary RHS vector.

Parameters
inVecnumpy array

Array of size w

Returns
outVecnumpy array

Solution vector of size w

solveErrorEstimate(aeroProblem, funcError, evalFuncs=None)[source]

Evaluate the desired function errors given in iterable object ‘evalFuncs’, and add them to the dictionary ‘funcError’. The keys in the funcError dictionary will be have an <ap.name>_ prepended to them.

Parameters
aeroProblempyAero_problem class

The aerodynamic problem to get the error for

funcErrordict

Dictionary into which the function errors are saved. We define error to be \(\epsilon = f^\ast - f\), where \(f^\ast\) is the converged solution and \(f\) is the unconverged solution.

evalFuncsiterable object containing strings

If not None, use these functions to evaluate.

Examples

>>> CFDsolver(ap)
>>> funcsSens = {}
>>> CFDSolver.evalFunctionsSens(ap, funcsSens)
>>> funcError = {}
>>> CFDsolver.solveErrorEstimate(ap, funcError)
>>> # Result will look like (if aeroProblem, ap, has name of 'wing'):
>>> print(funcError)
>>> # {'wing_cl':0.00085, 'wing_cd':0.000021}
solveSep(aeroProblem, sepStar, nIter=10, alpha0=None, delta=0.1, tol=0.001, expansionRatio=1.2, sepName=None)[source]

This is a safe-guarded secant search method to determine the alpha that yields a specified value of the separation sensor. Since this function is highly nonlinear we use a linear search to get the bounding range first.

Parameters
aeroProblempyAero_problem class

The aerodynamic problem to solve

sepStarfloat

The desired target separation sensor value

nIterint

Maximum number of iterations

alpha0angle (deg) or None

Initial guess. If none, use what is in aeroProblem.

deltaangle (deg)

Initial step. Only the magnitude is significant

tolfloat

Desired tolerance for sepSensor

sepNamestr or None

User supplied function to use for sep sensor. May be a user-added group function.

Returns
None, but the correct alpha is stored in the aeroProblem
solveTargetFuncs(aeroProblem, funcDict, tol=0.0001, nIter=10, Jac0=None)[source]

Solve the an arbitrary set of function-dv sets using a Broyden method.

Parameters
AeroProblemAeroProblem instance

The aerodynamic problem to be solved

funcDictdict

Dictionary of function DV pairs to solve: {‘func’:{‘dv’:str, ‘dvIdx’:idx,’target’:val,’initVal’:val,’initStep’:val}} func : Name of function that is being solved for dv : design variable that has dominant control of this function value dvIdx : index into dv array if dv is not scalar target : target function value initVal : initial design variable value initStep : initial step for this dv in when generating finite difference starting jacobian

tolfloat

Tolerance for the L2 norm of function error from target values

nIterint

Maximum number of iterations.

Jac0nxn numpy array

Initial guess for the func-dv Jacobian. Usually obtained from a previous analysis and saves n function evaluations to produce the initial Jacobian.

solveTimeStep()[source]

Solve the current time step, and write solutions if necessary

solveTrimCL(aeroProblem, trimFunc, trimDV, dvIndex, CLStar, trimStar=0.0, alpha0=None, trim0=None, da=0.001, deta=0.01, tol=0.0001, nIter=10, Jac0=None, liftFunc='cl')[source]

Solve the trim-Cl problem using a Broyden method.

Parameters
ASProblemASProblem instance

The aerostructural problem to be solved

trimFuncstr

Solution variable to use for trim. Usually ‘cmy’ or ‘cmz’

trimDVstr

Dame of DVGeo design variable to control trim

dvIndexint

Index of the trimDV function to use for trim

CLStarfloat

Desired CL value

trimStarfloat

Desired trimFunc value

alpha0float or None

Starting alpha. If None, use what is in the aeroProblem

trim0float or None

Starting trim value. If None, use what is in the DVGeo object

dafloat

Initial alpha step for Jacobian

detafloat

Initial stet in the ‘eta’ or trim dv function

tolfloat

Tolerance for trimCL solve solution

nIterint

Maximum number of iterations.

Jac02x2 numpy array

Initial guess for the trim-cl Jacobian. Usually obtained from a previous analysis and saves two function evaluations to produce the initial Jacobian.

liftFuncstr

Solution variable to use for lift. Usually ‘cl’ or a custom function created from cl.

updateGeometryInfo(warpMesh=True)[source]

Update the ADflow internal geometry info.

writeActuatorRegions(fileName, outputDir=None)[source]

Debug method that writes the cells included in actuator regions to a tecplot file. This routine should be called on all of the procs in self.comm. The output can then be used to verify that the actuator zones are defined correctly.

Parameters
fileNamestr

Name of the output file

outputDirstr

output directory. If not provided, defaults to the output directory defined with the aero_options

writeForceFile(fileName, TS=0, groupName=None, cfdForcePts=None)[source]

This function collects all the forces and locations and writes them to a file with each line having: X Y Z Fx Fy Fz. This can then be used to set a set of structural loads in TACS for structural only optimization

Like the getForces() routine, an external set of forces may be passed in on which to evaluate the forces. This is only typically used in an aerostructural case.

writeLiftDistributionFile(fileName)[source]

Evaluate and write the lift distibution to a tecplot file.

Parameters
fileNamestr

File of lift distribution. Should have .dat extension.

writeMeshFile(fileName)[source]

Write the current mesh to a CGNS file. This call isn’t used normally since the volume solution usually contains the grid

Parameters
fileNamestr

Name of the mesh file

writeSlicesFile(fileName)[source]

Evaluate and write the defined slice information to a tecplot file.

Parameters
fileNamestr

Slice file. Should have .dat extension.

writeSolution(outputDir=None, baseName=None, number=None, writeSlices=True, writeLift=True)[source]

This is a generic shell function that potentially writes the various output files. The intent is that the user or calling program can call this file and ADflow write all the files that the user has defined. It is recommended that this function is used along with the associated logical flags in the options to determine the desired writing procedure

Parameters
outputDirstr

Use the supplied output directory

baseNamestr

Use this supplied string for the base filename. Typically only used from an external solver.

numberint

Use the user supplied number to index solution. Again, only typically used from an external solver.

writeSlicesbool

Flag to determine if the slice files are written, if we have any slices added.

writeLiftbool

Flag to determine if the lift files are written, if we have any lift distributions added.

writeSurfaceSensitivity(fileName, func, groupName=None)[source]

Write a tecplot file of the surface sensitivity. It is up to the use to make sure the adjoint already computed before calling this function.

Parameters
fileNamestr

String for output filename. Should end in .dat for tecplot.

funcstr

ADFlow objective string for the objective to write.

groupNamestr

Family group to use. Default to all walls if not given (None)

writeSurfaceSolutionFile(fileName)[source]

Write the current state of the surface flow solution to a CGNS file. Keyword arguments:

Parameters
fileNamestr

Name of the file. Should have .cgns extension.

writeSurfaceSolutionFileTecplot(fileName)[source]

Write the current state of the surface flow solution to a teclot file.

Parameters
fileNamestr

Name of the file. Should have .plt extension.

writeVolumeSolutionFile(fileName, writeGrid=True)[source]

Write the current state of the volume flow solution to a CGNS file. This is a lower level routine; Normally one should call writeSolution().

Parameters
fileNamestr

Name of the file. Should have .cgns extension.

writeGridbool

Flag specifying whether the grid should be included or if links should be used. Always writing the grid is recommended even in cases when it is not strictly necessary. Note that if writeGrid = False the volume files do not contain any grid coordinates rendering the file useless if a separate grid file was written out and is linked to it.