Link to Galaxy/RCAS

All functions below are in the module msgd.ms.rcas.

Read the OML data (readRcasOml)

import msgd.ms.rcas as mmr
oml = mmr.readRcasOml('oml.dat')

Returned value of this function is a Python dictionary having the following data layout.

oml = {
    'fenode': fe_nodes,
    'aeronode': aero_nodes,
    'aeroseg': aero_segs,
    'airfoilinterp': airfoil_interp
}

oml['fenode']

Data block “FENODE”. A dictionary of structural nodal ID and coordinates: {id1: [x1, y1, z1], id2: [x2, y2, z2], ...}.

oml['aeronode']

Data block “AERONODE”. A dictionary of aerodynamic nodal ID and coordinates: {id1: [x1, y1, z1], id2: [x2, y2, z2], ...}.

oml['aeroseg']

Data block “AEROSEG”. A dictionary of aerodynamic segments.

{
    seg1_id: {
        'aero_nodes': [pnode_id, cnode_id],
        'chord': c,
        'airfoil': 'airfoil_name',
        'twist': t,
        'shear': s
    },
    seg2_id: {...},
    ...
}

oml['airfoilinterp']

Data block “AIRFOILINTERP”. A dictionary of radial location and airfoil name: {'r': [r1, r2, ...], 'airfoil': ['name1', 'name2', ...]}.

Read the property data (readRcasProp)

import msgd.ms.rcas as mmr
prop = mmr.readRcasProp('prop.dat')

Returned value of this function is a Python dictionary having the following data layout.

prop = {
    'prop1_name': value,
    'prop2_name': {'x': [], 'y': []},
    'prop3_name': [],
    ...
}

Each key in this dictionary is the property name in the file (without the leading “!M “ characters), such as “BEA”, “BGJ”, etc. For the values, there are three types:

Scalar (prop['prop1_name']). There is only a single value corresponding to the property, such as ‘REFLENGTH’.

Mapping list (prop['prop2_name']). Most properties belong to this type. There are two columns in the data file. Key x stores the list of spanwise locations (first column), while y stores the list of property values (second column).

Others (prop['prop3_name']). The rest data blocks that do not belong to the previous two types, such as ‘BMISC’.

Read the load data (readRcasLoad)

import msgd.ms.rcas as mmr
force, moment = mmr.readRcasLoad('force.csv', 'moment.csv')

Returned values of this function are Python dictionaries having the following data layout.

Note

force and moment have the same layout.

force = {
    'node_id': [],
    'case_1': {
        'x': [
            [a1, xn1, xn2, xn3, ...],
            [a2, xn1, xn2, xn3, ...],
            ...
        ],
        'y': [],
        'z': []
    },
    'case_2': {...},
    ...
}

node_id

This is a list of nodal IDs. They are parsed from the header of the file. ID is the number after the keyword ‘NODE’.

case_1, case_2, …

Case ID (first column) in the file.

x, y, z

Component (second column in the file) of the load. Each of them is a list of loads for all nodes but one azimuth angle. In other words, each item in the list corresponds to a row in the file.

For example, force['case_1']['x'][0] is [a1, xn1, xn2, xn3, ...], which means Fx at node 1 (xn), node 2 (xn2), node 3 (xn3) and so on for the first azimuth angle (a1), say 15 degrees.