pyts.profModels package

Submodules

pyts.profModels.api module

PyTurbSim mean velocity ‘profile models’ package.

Available profile models

log_models.nwtc (alias: log)
The nwtc logarithmic mean wind-speed profile.
log_models.H2O (alias: h2l)
The hydro (water) logarithmic mean velocity profile.
power_models.nwtc (alias: pl)
The nwtc 1/7 power-law mean wind-speed profile.
iec_models.main (alias: iec)
The IEC mean wind-speed profile.
profModelBase
This is the base class for profile models. To create a new profile model, subclass this class or subclass and modify an existing profile model.
profObj
This is the ‘profile object’ class. All profile model __call__ methods must take a tsrun as input and return this class.

Example usage

>>> import pyts.profModels.api as pm

Create a logarithmic mean wind-speed ‘profile model’ with 18m/s wind at 80m, and surface roughness length of 1m:

>>> my_prof_model=pm.log(18,80,1)

# Now set ‘tsrun’ to use this profile model:

>>> tsrun.prof=my_prof_model(tsrun)

Creating a new profile model

Creating new profile models in PyTurbSim is simple. Simply subclass profModelBase, then:

1) write an __init__ method that takes inputs that define the profile model in general (i.e. irrespective of the spatial grid or other statistics of the flow), and

2) write a __call__ method that takes tsrun as input and returns a profObj, which

For example:

import pyts.profModels.api as pm # import the profModels api
from numpy import polyval # Import helper functions.

class my_new_model(pm.profModelBase):
    """
    A polynomial mean-velocity profile, where coefficients can be
    specified at initialization.
    """

    def __init__(self,Uref,Zref,poly_coefs=[1.,0.]):
        # All units should be in meters and seconds.
        self.Uref=Uref
        self.Zref=Zref
        self.poly_coefs=poly_coefs

    def __call__(self,tsrun):
        out=pm.profObj(tsrun)
        # Note here that tsrun contains the 'grid information', and
        # we can use that information to construct the profObj.
        out[0]=self.Uref*numpy.polyval(self.poly_coefs,tsrun.grid.z/Zref)
        # Here we have set the u-component (index 0) to follow the
        # polynomial, and we leave the other components to be zero.
        return out

That’s all that is required to define a new profile model! Now, assuming you have already created a tsrun instance (e.g. tsr) you set that tsrun to use your new model by simply doing, for example:

>>> tsr.prof = my_new_model(3.,20,[.5,0])

Now your PyTurbSim run will utilize your newly defined model!

Notes

For a description of the difference between ‘profile models’ (e.g. ‘my_prof_model’ in example above) and the profile they output (tsrun.prof), see the Code Framework section of the PyTurbSim documentation.

pyts.profModels.base module

This is the velocity profile package’s base module.

class pyts.profModels.base.profModelBase[source]

Bases: pyts.base.modelBase

A base class for TurbSim profile models.

class pyts.profModels.base.profObj(tsrun)[source]

Bases: pyts.base.gridProps, pyts.base.calcObj

Profile objects contain the array (self.array) of mean-velocity values for a specific PyTurbSim run.

Profile objects are created with/for a specific PyTurbSim run.

Parameters:

tsrun : tsrun

The PyTurbSim run object in which the profile will be used.

See also

profModelBase
The abstract base class for classes that create this class.
dudz

The vertical derivative of the u-component of the mean velocity field. (Centered difference)

dvdz

The vertical derivative of the v-component of the mean velocity field. (Centered difference)

dwdz

The vertical derivative of the w-component of the mean velocity field. (Centered difference)

u

The w-component of the mean velocity field.

uhub

The u-component hub-height wind speed.

v

The w-component of the mean velocity field.

w

The w-component of the mean velocity field.

pyts.profModels.iec module

This module contains the power-law mean-velocity profiles:
main - The IEC mean wind speed profile.
class pyts.profModels.iec.main(URef, RefHt, Z0, PLexp=0.2, turbmodel=None)[source]

Bases: pyts.profModels.power.nwtc, pyts.profModels.log.nwtc

IEC wind profile model.

This profile is a power-law across the rotor disk and logarithmic elsewhere.

Parameters:

grid : tsGrid

The TurbSim grid object for this simulation.

URef : float

Reference velocity for the wind profile [m/s].

RefHt : float

Reference height of the reference velocity [m].

PLexp : float,optional (0.2)

The power-law exponent to be utilized for this simulation [non-dimensional], default=0.2 (per IEC specification).

Z0 : float

Surface roughness length [m].

Ri : float

The Richardon number [non-dimensional].

turbmodel : str

the name of the turbulence model in this simulationm, optional.

See also

power.nwtc
The iec model is this law over the rotor disk
log.nwtc
The iec model is this law outside the rotor disk
__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A iec wind-speed profile for the grid in tsrun.

pyts.profModels.jet module

class pyts.profModels.jet.main(URef, ZRef, UStar, Ri, zjet_max=None)[source]

Bases: pyts.profModels.base.profModelBase

Low-level jet wind profile model.

Parameters:

URef : float

Reference velocity for the wind profile [m/s].

ZRef : float

Reference height of the reference velocity [m].

UStar : float

The bottom-boundary friction velocity [m/s].

Ri : float

The Richardson number stability parameter.

zjet_max : float, optional

The maximum height of the jet. If a value is not specified, the zjet_max property provides a default.
__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A jet wind-speed profile for the grid in tsrun.
zjet_max

The value of the jet height.

This property calculates a default value if one is not specified.

pyts.profModels.log module

This module contains the log-law mean-velocity profiles:
nwtc - The NWTC logarithmic mean wind speed profile. H2O - The hydro-logarithmic mean velocity profile.
class pyts.profModels.log.H2O(Uref, Zref, ustar)[source]

Bases: pyts.profModels.base.profModelBase

Logarithmic water velocity profile model.

Parameters:

URef : float

Reference velocity for the wind profile [m/s].

ZRef : float

Reference height of the reference velocity [m].

ustar : float

Surface friction veclocity [m/s].

Notes

The precise form of this model is,

\[Ubar(z) = U_*/\kappa * \mathrm{Ln}( z / Z_{ref}) + U_{ref}\]
__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A logarithmic mean-velocity profile object for the spatial grid in tsrun.
class pyts.profModels.log.nwtc(URef, ZRef, Z0, Ri=0, turbmodel=None)[source]

Bases: pyts.profModels.base.profModelBase

NWTC logarithmic wind-speed profile model.

Parameters:

URef : float

Reference velocity for the wind profile [m/s].

ZRef : float

Reference height of the reference velocity [m].

Z0 : float

Surface roughness length [m].

Ri : float

The Richardon number [non-dimensional].

turbmodel : str, optional

The name of the turbulence model in this simulationm.

Notes

The exact form of this model is,

\[\bar{U}(z) = U_{Ref}\frac{ln( z / Z0 ) - \psi_M}{ln( Z_{Ref} / Z0) - \psi_M}\]

Where psi_M is a function of Ri, the Richardson number (psi_M=0 for Ri=0), and the turbulence model.

__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A logarithmic wind-speed profile for the grid in tsrun.
model(z)[source]

Calculate the log profile for heights z.

Parameters:

z : array_like(dtype=float)

Height above the ground [m].
Returns:

u : array_like(dtype=float)

The mean velocity array [m/s].
psiM

The psi_M parameter for this profile model.

See the pyts.misc.psiM() function for details.

pyts.profModels.power module

The NWTC power-law profile model.

class pyts.profModels.power.nwtc(Uref, Zref, PLexp=0.14285714285714285)[source]

Bases: pyts.profModels.base.profModelBase

Power-law wind profile model.

\[\bar{U}(z) = U_{ref} * ( z / Z_{ref} )^{PLexp}\]
Parameters:

URef : float

Reference velocity for the wind profile [m/s].

Zref : float

Reference height of the reference velocity [m].

PLexp : float

The power-law exponent to be utilized for this simulation [non-dimensional], default=1/7.
__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A power-law wind-speed profile for the grid in tsrun.
model(z)[source]

The function for calculating the mean velocity profile.

pyts.profModels.simple module

This module contains the log-law mean-velocity profiles:
linear - A linear wind speed profile uniform - A uniform mean wind speed.
class pyts.profModels.simple.linear(URef, ZRef, URef2=0.0, ZRef2=0.0)[source]

Bases: pyts.profModels.base.profModelBase

A ‘linear’ mean wind-speed ‘profile’.

Parameters:

URef : float

The mean velocity you wish to produce [m/s].

ZRef : float

Reference height of URef [m].

URef2 : float (default = 0)

Second velocity point [m/s].

ZRef2 : float (default = 0)

Reference height of second velocity point [m]

Notes

The u-component is set to a linear profile through the points (URef,Zref) and (URef2,ZRef2). v- and w-components are zero.

__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A uniform wind-speed profile for the grid in tsrun.
class pyts.profModels.simple.uniform(URef)[source]

Bases: pyts.profModels.base.profModelBase

Uniform wind-speed ‘profile’ model.

Parameters:URef : The mean velocity you wish to produce.

Notes

This wind-speed ‘profile’ actually just sets the mean u-component wind-speed to be spatially uniform. The v- and w-components are zero.

__call__(tsrun)[source]

Create and calculate the mean-profile object for a tsrun instance.

Parameters:

tsrun : tsrun

A TurbSim run object.
Returns:

out : profObj

A uniform wind-speed profile for the grid in tsrun.

Module contents

This is the PyTurbSim mean velocity ‘profile models’ package. This package contains pre-defined profile models that can be implemented in a PyTurbSim run.

For more information and to use this module import the profModels.api package, e.g.

>>>    import pyts.profModels.api as pm