Plugin WindLab - Revision history

LabRPS at 20:02, 9 February 2025

2025-02-09T20:02:52Z

← Older revision		Revision as of 13:02, 9 February 2025
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	\|Version=1.0		\|Version=1.0
	\|Date=2024-04-15		\|Date=2024-04-15
	\|Features= [[#Horizontal_Uniform_Distribution\|Horizontal Uniform Distribution]], [[#Vertical_Uniform_Distribution\|Vertical Uniform Distribution]], [[#Uniform_Distribution\|Uniform Distribution]], [[#Grid_Points\|Grid Points]], [[#General_Distribution\|General Distribution]], [[#Import_Simulation_Points_from_File\|Import Simulation Points from File]], [[#Power_Law_Profile\|Power Law Profile]], [[#Logarithmic_Law_Profile\|Logarithmic Law Profile]], [[#Deaves_and_Harris_Profile\|Deaves and Harris Profile]], [[#Sine_Modulation_Function\|Sine Modulation Function]], [[#Three_Parameter_Modulation_Function\|Three Parameter Modulation Function]], [[#Exponential_Modulation_Function\|Exponential Modulation Function]], [[#Davenport_Coherence_Function\|Davenport Coherence Function]], [[#Krenk_Coherence_Function\|Krenk Coherence Function]], [[#Davenport_Along_Wind_Spectrum\|Davenport Along Wind Spectrum]], [[#Harris_Along_Wind_Spectrum\|Harris Along Wind Spectrum]], [[#Kaimal_Along_Wind_Spectrum\|Kaimal Along Wind Spectrum]], [[#Kaimal_Across_Wind_Spectrum\|Kaimal Across Wind Spectrum]], [[#Kaimal_Vertical_Wind_Spectrum\|Kaimal Vertical Wind Spectrum]], [[#Simiu_Along_Wind_Spectrum\|Simiu Along Wind Spectrum]], [[#Simiu_Across_Wind_Spectrum\|Simiu Across Wind Spectrum]], [[#Simiu_Vertical_Wind_Spectrum\|Simiu Vertical Wind Spectrum]], [[#von_Karman_Along_Wind_Spectrum\|von Karman Along Wind Spectrum]], [[#Uniform_Random_Phases\|Uniform Random Phases]], [[#Uniform_Random_Phases_Import\|Uniform Random Phases Import]], [[#Double_Index_Frequency_Discretization\|Double Index Frequency Discretization]], [[#Single_Index_Frequency_Discretization\|Single Index Frequency Discretization]], [[#Zerva_Frequency_Discretization\|Zerva Frequency Discretization]], [[#George_Deodatis_Simulation_Method_1996\|George Deodatis Simulation Method(1996)]], [[#Cholesky_Decomposition\|Cholesky Decomposition]]		\|Features= [[#Horizontal_Uniform_Distribution\|Horizontal Uniform Distribution]], [[#Vertical_Uniform_Distribution\|Vertical Uniform Distribution]], [[#Uniform_Distribution\|Uniform Distribution]], [[#Grid_Points\|Grid Points]], [[#General_Distribution\|General Distribution]], [[#Import_Simulation_Points_from_File\|Import Simulation Points from File]], [[#Power_Law_Profile\|Power Law Profile]], [[#Logarithmic_Law_Profile\|Logarithmic Law Profile]], [[#Deaves_and_Harris_Profile\|Deaves and Harris Profile]], [[#Sine_Modulation_Function\|Sine Modulation Function]], [[#Three_Parameter_Modulation_Function\|Three Parameter Modulation Function]], [[#Exponential_Modulation_Function\|Exponential Modulation Function]], [[#Davenport_Coherence_Function\|Davenport Coherence Function]], [[#Krenk_Coherence_Function\|Krenk Coherence Function]], [[#Davenport_Along_Wind_Spectrum\|Davenport Along Wind Spectrum]], [[#Harris_Along_Wind_Spectrum\|Harris Along Wind Spectrum]], [[#Kaimal_Along_Wind_Spectrum\|Kaimal Along Wind Spectrum]], [[#Kaimal_Across_Wind_Spectrum\|Kaimal Across Wind Spectrum]], [[#Kaimal_Vertical_Wind_Spectrum\|Kaimal Vertical Wind Spectrum]], [[#Simiu_Along_Wind_Spectrum\|Simiu Along Wind Spectrum]], [[#Simiu_Across_Wind_Spectrum\|Simiu Across Wind Spectrum]], [[#Simiu_Vertical_Wind_Spectrum\|Simiu Vertical Wind Spectrum]], [[#von_Karman_Along_Wind_Spectrum\|von Karman Along Wind Spectrum]], [[#Uniform_Random_Phases\|Uniform Random Phases]], [[#Uniform_Random_Phases_Import\|Uniform Random Phases Import]], [[#Double_Index_Frequency_Discretization\|Double Index Frequency Discretization]], [[#Single_Index_Frequency_Discretization\|Single Index Frequency Discretization]], [[#Zerva_Frequency_Discretization\|Zerva Frequency Discretization]], [[#George_Deodatis_Simulation_Method_1996\|George Deodatis Simulation Method(1996)]], [[#Cholesky_Decomposition\|Cholesky Decomposition]], [[#Exponential_Wave_Passage_Effect\|Exponential Wave Passage effect]]


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	[[#top\| Back to the Top ]]		[[#top\| Back to the Top ]]

	== Exponential Wave Passage ~~effect~~ ==		== Exponential Wave Passage Effect ==

	The wave passage effect is a measure of the wave passage delay due to the apparent velocity of waves, which is one of spatially varying properties of multivariate random processes. The exponential Wave Passage effect is expressed as follows:		The wave passage effect is a measure of the wave passage delay due to the apparent velocity of waves, which is one of spatially varying properties of multivariate random processes. The exponential Wave Passage effect is expressed as follows:

LabRPS: /* Exponential Wave Passage effect */

2025-02-09T20:01:09Z

Exponential Wave Passage effect

← Older revision		Revision as of 13:01, 9 February 2025
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	The wave passage effect is a measure of the wave passage delay due to the apparent velocity of waves, which is one of spatially varying properties of multivariate random processes. The exponential Wave Passage effect is expressed as follows:		The wave passage effect is a measure of the wave passage delay due to the apparent velocity of waves, which is one of spatially varying properties of multivariate random processes. The exponential Wave Passage effect is expressed as follows:

	<math>\gamma_{jk}(\omega) = \mbox{exp}\left ( -i\frac{\omega \xi_{jk}}{v_{app}} \right )</math>		<math>\gamma_{jk}(\omega) = \mbox{exp}\left ( -i\frac{\omega \times \xi_{jk}}{v_{app}} \right )</math>

	where:		where:
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	{{Code\|code=		{{Code\|code=
	import WindLab		import WindLab
			import GeneralToolsGui
	import WindLabObjects		import WindLabObjects
	from LabRPS import Vector as vec		from LabRPS import Vector as vec
			import LabRPS
	import numpy		import numpy

	# get an existing ~~WindLab~~ simulation called "Simulation"		def compute():
	sim = WindLab.getSimulation("Simulation")		installResuslt = WindLab.installPlugin("WindLabPlugin")

	# check if the simulation ~~does really exist~~		# get an existing SeaLab simulation called "Simulation"
	if not sim:		sim = WindLab.getSimulation("Simulation")
	LabRPS.Console.PrintError("The simulation does not exist.\n")
	~~# abord the computation~~		# check if the simulation sucessfully created
			if not sim:
			LabRPS.Console.PrintError("The simulation does not exist.\n")
			return None

	featureType = "Exponential Wave Passage ~~effect~~"		featureType = "Exponential Wave Passage Effect"
	featureGroup = "Wave Passage ~~effect~~"		featureGroup = "Wave Passage Effect"

	# create the feature ~~and add it to the existing simulation (you may refer to the WindLab Workbench page in~~		# create the feature
	~~# case you don't understand the next line)~~		decomposedPSD = WindLabObjects.makeFeature("MyNewFeature", sim.Name, featureType, featureGroup)
	~~coherence~~ = WindLabObjects.makeFeature("MyNewFeature", sim.Name, featureType, featureGroup)

	# check if the created feature is good		# check if the created feature is good
	if not ~~coherence~~:		if not decomposedPSD :
	LabRPS.Console.PrintError("Error on creating the ~~coherence function~~ feature.\n")		LabRPS.Console.PrintError("Error on creating the the feature.\n")
	# ~~abord~~ the ~~computation~~		return None

			# set simulation parameters
			sim.NumberOfFrequency = 2048
			sim.MaxFrequency = "0.64 Hz" # 4 rad/s;
			sim.FrequencyIncrement = "0.00031 Hz" # 0.00195 rad/s;

			# get the active simulation points feature and compute the simulation points coordinates
			simPoints = sim.computeLocationCoordinateMatrixP3()

			if not simPoints :
			LabRPS.Console.PrintError("Make sure you have an active location disttribution in the simulation with at least 3 simulation points.\n")
			return None

			# use a vector to represent a simulation point based on its coordinates
			v1 = vec(simPoints[0][1], simPoints[0][2], simPoints[0][3])
			v2 = vec(simPoints[1][1], simPoints[1][2], simPoints[1][3])
			v3 = vec(simPoints[2][1], simPoints[2][2], simPoints[2][3])

	~~coherence~~.~~ExponentialDecayCx = 10.0~~		# This feature is used to compute the wave passage effect which may vary in time. Let's assume that
	~~coherence~~.~~ExponentialDecayCy = 7~~.0		# the active wave passage effect in this example is stationary. Meanning it is not varying in time.
	~~coherence.ExponentialDecayCz~~ = 6.0		#Then, we use time instant of 0 second.
			time = 0.0

	# ~~In WindLab~~, ~~coherence function can vary with~~ time~~. In case the user desires a time dependent coherence function,~~		# compute the wave passage effect between points 1 and 3, at time instant of 0 second and for all frequency
	# ~~a modulation function can be used for this purpose. The feature account for this~~. ~~When~~ the ~~Stationarity property of~~ the ~~parent~~		# increments. Note that when the following code is run, WindLab will try to identify the active frequency distribution,
	# ~~simulation of this~~ feature ~~is false~~, ~~the feature identify the active modulation function~~ and ~~use it~~ to ~~produce non-stationary~~		# the active wave passage effect feature, and others. If WindLab fails to find any of these dependency features,
	# ~~coherence function by transforming~~ the the ~~mean wind speeds into time dependent mean wind speeds. But for this example we shall use time instant of 0 second~~.		# the computation will fails and specific error messages will be sent to the report view.
	~~time~~ = 0.0		effect13 = sim.computeWavePassageEffectVectorF(v1, v3, time)
	~~frequency = 0.25~~

	# ~~compute~~ the ~~coherence matrix at time instant of 0 second and frequency of 0~~.~~24 rad/s~~		# show the results
	~~# Note that when the following code is run~~, ~~WindLab will try to identify the active locations distribution~~,		GeneralToolsGui.GeneralToolsPyTool.showArray(len(effect13), len(effect13[0]), effect13)
	~~# it will also try to identity the active modulation function in case the parent simulation is non-stationary~~.		LabRPS.ActiveDocument.recompute()
	~~# If WindLab fails to find these dependency features, the computation will fails and specific error messages will be sent to the report view~~.
	~~coherences = sim.computeCrossCoherenceMatrixPP~~(~~frequency, time~~)

	~~# now you can convert the coordinate matrix to numpy array and use it for any other purposes~~		compute()
	~~arr = numpy.asarray~~(~~coherences~~)

	}}		}}
	[[#top\| Back to the Top ]]		[[#top\| Back to the Top ]]

LabRPS at 19:11, 9 February 2025

2025-02-09T19:11:20Z

@@ Line 2,243: / Line 2,243: @@
 compute()
 }}
 [[#top| Back to the Top ]]

LabRPS: /* Davenport Coherence Function */

2025-01-28T13:31:19Z

Davenport Coherence Function

← Older revision		Revision as of 06:31, 28 January 2025
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	<math>\~~gamma_jk~~(\omega) = exp\left[-\frac{\omega}{2 \pi}\left( \frac{\sqrt{C_{x}^2 \left( x_{j}-x_{k} \right)^2 + C_{y}^2 \left( y_{j}-y_{k} \right)^2 + C_{z}^2 \left( z_{j}-z_{k} \right)^2}}{\frac{U_{j}\left( z_{j} \right)+U_{k}\left( z_{k} \right)}{2}} \right)\right]</math>		<math>\gamma_{jk}(\omega) = exp\left[-\frac{\omega}{2 \pi}\left( \frac{\sqrt{C_{x}^2 \left( x_{j}-x_{k} \right)^2 + C_{y}^2 \left( y_{j}-y_{k} \right)^2 + C_{z}^2 \left( z_{j}-z_{k} \right)^2}}{\frac{U_{j}\left( z_{j} \right)+U_{k}\left( z_{k} \right)}{2}} \right)\right]</math>


	where:		where:
	* <math>\~~gamma~~(\omega)</math> is the coherence ~~function for~~ two points <math>P_{j}\left( x_{j},y_{j},z_{j} \right)</math> and <math>P_{k}\left( x_{k},y_{k},z_{k} \right)</math> ~~value for~~ frequency <math>\omega</math>,		* <math>\gamma_{jk}(\omega)</math> is the coherence value between two points <math>P_{j}\left( x_{j},y_{j},z_{j} \right)</math> and <math>P_{k}\left( x_{k},y_{k},z_{k} \right)</math> at frequency <math>\omega</math>,
	* <math>C_{x}</math> is the decay coefficient along x,		* <math>C_{x}</math> is the decay coefficient along x,
	* <math>C_{y}</math> is the decay coefficient along y,		* <math>C_{y}</math> is the decay coefficient along y,

LabRPS: /* Davenport Coherence Function */

2025-01-28T13:28:30Z

Davenport Coherence Function

← Older revision		Revision as of 06:28, 28 January 2025
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	<math>\~~gamma~~(\omega) = exp\left[-\frac{\omega}{2 \pi}\left( \frac{\sqrt{C_{x}^2 \left( x_{j}-x_{k} \right)^2 + C_{y}^2 \left( y_{j}-y_{k} \right)^2 + C_{z}^2 \left( z_{j}-z_{k} \right)^2}}{\frac{U_{j}\left( z_{j} \right)+U_{k}\left( z_{k} \right)}{2}} \right)\right]</math>		<math>\gamma_jk(\omega) = exp\left[-\frac{\omega}{2 \pi}\left( \frac{\sqrt{C_{x}^2 \left( x_{j}-x_{k} \right)^2 + C_{y}^2 \left( y_{j}-y_{k} \right)^2 + C_{z}^2 \left( z_{j}-z_{k} \right)^2}}{\frac{U_{j}\left( z_{j} \right)+U_{k}\left( z_{k} \right)}{2}} \right)\right]</math>

LabRPS at 20:49, 27 January 2025

2025-01-27T20:49:20Z

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LabRPS at 00:28, 19 January 2025

2025-01-19T00:28:56Z

← Older revision		Revision as of 17:28, 18 January 2025
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	{{Plugin		{{Plugin
	\|Name=Plugin ~~WindLab~~		\|Name=WindLab Plugin
	\|Description=This plugin implement various WindLab features.		\|Description=This plugin implement various WindLab features.
	\|Author=Koffi Daniel		\|Author=Koffi Daniel

LabRPS: /* Scripting */

2025-01-18T02:42:24Z

Scripting

← Older revision		Revision as of 19:42, 17 January 2025
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	import LabRPS		import LabRPS
	import numpy		import numpy
			import matplotlib.pyplot as plt
			from mpl_toolkits.mplot3d import Axes3D

	def compute():		def compute():
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	compute()		compute()


	}}		}}

LabRPS: /* Scripting */

2025-01-17T23:52:01Z

Scripting

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      # now you can convert the coordinate matrix to numpy array and use it for any other purposes
      arr = numpy.asarray(simPoints)
      # you can also show the result in a table, pass False as last argument to the function to ask
      # LabRPS to only show the data without plotting them
      GeneralToolsGui.GeneralToolsPyTool.showArray(sim.getSimulationData().numberOfSpatialPosition, 4, simPoints, False)
 compute()

LabRPS at 15:50, 17 January 2025

2025-01-17T15:50:05Z

Show changes