SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid Class Reference

Inheritance diagram for SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid:

Public Member Functions
def	__defaults__ (self)
def	initialize (self, number_spanwise_vortices, number_chordwise_vortices, keep_files, save_regression_results, regression_flag, print_output, trim_aircraft, side_slip_angle, roll_rate_coefficient, pitch_rate_coefficient, lift_coefficient)
def	evaluate (self, state, settings, geometry)
def	sample_training (self)
def	build_surrogate (self)
def	evaluate_conditions (self, run_conditions, trim_aircraft)
Public Member Functions inherited from SUAVE.Analyses.Mission.Segments.Conditions.Conditions.Conditions
def	ones_row (self, cols)
def	ones_row_m1 (self, cols)
def	ones_row_m2 (self, cols)
def	expand_rows (self, rows, override=False)

Public Attributes
	tag
	current_status
	geometry
	settings
	training
	training_file
	surrogates
Public Attributes inherited from SUAVE.Analyses.Mission.Segments.Conditions.Aerodynamics.Aerodynamics
	tag
	freestream
	aerodynamics
	stability
	aero_derivatives
	propulsion
	noise
Public Attributes inherited from SUAVE.Analyses.Mission.Segments.Conditions.Basic.Basic
	tag
	frames
	weights
	energies
	noise

Detailed Description

This builds a surrogate and computes lift using AVL.

Assumptions:
None

Source:
None

Member Function Documentation

__defaults__()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.__defaults__

(

self

)

This sets the default values and methods for the analysis.

Assumptions:
None

Source:
N/A

Inputs:
None

Outputs:
None

Properties Used:
N/A

Reimplemented from SUAVE.Analyses.Mission.Segments.Conditions.Aerodynamics.Aerodynamics.

build_surrogate()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.build_surrogate

(

self

)

Builds a surrogate based on sample evalations using a Guassian process.
Assumptions:
None
Source:
N/A
Inputs:
self.training.
  coefficients             [-] CL and CD
  span efficiency factor   [-] e 
  grid_points              [radians,-] angles of attack and Mach numbers 
Outputs:
self.surrogates.
  lift_coefficient        
  drag_coefficient        
  span_efficiency_factor  
Properties Used:
No others

evaluate()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.evaluate	(		self,
			state,
			settings,
			geometry
	)

Evaluates lift and drag using available surrogates.

Assumptions:
Returned drag values are currently not meaningful.

Source:
N/A

Inputs:
state.conditions.
  mach_number      [-]
  angle_of_attack  [radians]

Outputs:
inviscid_lift      [-] CL
inviscid_drag      [-] CD
span_efficiency    [-] e

Properties Used:
self.surrogates.
  lift_coefficient       [-] CL
  drag_coefficient       [-] CD
  span_efficiency_factor [-] e

evaluate_conditions()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.evaluate_conditions	(		self,
			run_conditions,
			trim_aircraft
	)

Process vehicle to setup geometry, condititon, and configuration.

Assumptions:
None

Source:
N/A

Inputs:
run_conditions <SUAVE data type> aerodynamic conditions; until input
method is finalized, will assume mass_properties are always as 
defined in self.features

Outputs:
results        <SUAVE data type>

Properties Used:
self.settings.filenames.
  run_folder
  output_template
  batch_template
  deck_template
self.current_status.
  batch_index
  batch_file
  deck_file
  cases

initialize()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.initialize	(		self,
			number_spanwise_vortices,
			number_chordwise_vortices,
			keep_files,
			save_regression_results,
			regression_flag,
			print_output,
			trim_aircraft,
			side_slip_angle,
			roll_rate_coefficient,
			pitch_rate_coefficient,
			lift_coefficient
	)

Drives functions to get training samples and build a surrogate.

Assumptions:
None

Source:
N/A

Inputs:
None

Outputs:
self.tag = 'avl_analysis_of_{}'.format(geometry.tag)

Properties Used:
self.geometry.tag

sample_training()

def SUAVE.Analyses.Aerodynamics.AVL_Inviscid.AVL_Inviscid.sample_training

(

self

)

Call methods to run AVL for sample point evaluation.
Assumptions:
Returned drag values are not meaningful.
Source:
N/A
Inputs:
see properties used
Outputs:
self.training.
  coefficients     [-] CL and CD
  grid_points      [radians,-] angles of attack and Mach numbers 
Properties Used:
self.geometry.tag  <string>
self.training.     
  angle_of_attack  [radians]
  Mach             [-]
self.training_file (optional - file containing previous AVL data)

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The documentation for this class was generated from the following file:

• /Users/emiliobotero/Dropbox/SUAVE/SUAVE/trunk/SUAVE/Analyses/Aerodynamics/AVL_Inviscid.py