dnv-bladed-models 0.8.0

An API for working with Bladed Next Gen models.

Bladed Next Gen Python Models API

dnv_bladed_models=0.8.0

A Python package to create and edit JSON input models for Bladed Next Generation.

Visit https://mysoftware.dnv.com/knowledge-centre/bladed-5 for more information.

Prerequisites

• Requires Python 3.9 or above

Usage

Add import

import dnv_bladed_models as models

There are a large number of model classes (500+) in the Bladed NG input API.

The root model is BladedAnalysis; a JSON file input to the calculation engine must have this model as the root object.

However the same capabilities are available for every model/class; each one can be read and written to JSON individually, as demonstrated below.

Load a full Bladed NG JSON analysis model from file

analysis = models.BladedAnalysis.from_file('/path/to/analysis.json')

This will perform some validation of the input to ensure the structure adheres to the input schema.

Save a model to a JSON file

analysis.to_file('/path/to/file.json')

The JSON file can then be opened in VS Code, and will automatically receive validation, doc-string and auto-complete support against the Bladed NG JSON Schema.

Load a model from a JSON string

analysis = models.BladedAnalysis.from_json(json_str)

This will perform some validation of the input to ensure the structure adheres to the input schema.

Render a model as a JSON string

json_str = analysis.to_json()

Create a new model object in code

Create a new instance of the BladedAnalysis model object:

analysis = models.BladedAnalysis()

A model object can be created with an empty initialiser as shown above, or by specifying some or all of the child models as keyword arguments:

beam = models.LidarBeam(
    MountingPosition=models.LidarMountingPosition(
        X=1,
        Y=2,
        Z=3
    )
)

Modify a model object in code

If a model object is already loaded, properties can be modified as required:

analysis.Constants.AirCharacteristics.Density = 1.23

Manipulate the turbine assembly

Access existing component definitions:

# Access a known existing component by it's key, ensuring the correct type
blade = analysis.Turbine.ComponentLibrary.Component_as_Blade('blade')

# Iterate over all component entries...
for key, component in analysis.Turbine.ComponentLibrary.items():
    print(f"Component key: {key}, Component type: {component.ComponentType}")

Access existing nodes in the Assembly tree using string and integer accessors:

blade_node = analysis.Turbine.Assembly['Hub']['PitchSystem_1'][0]

# or
blade_node = analysis.Turbine.Assembly['Hub']['PitchSystem_1']['Blade']

# or
blade_nodes = [ps_node[0] for node_name, ps_node in analysis.Turbine.Assembly['Hub'].items()]

Add new nodes and component definitions:

analysis.Turbine.ComponentLibrary['MyHub'] = models.IndependentPitchHub()
analysis.Turbine.ComponentLibrary['MyPitchSystem'] = models.PitchSystem()
analysis.Turbine.ComponentLibrary['MyBlade'] = models.Blade()

hub_node = models.AssemblyNode(
    Definition = "ComponentLibrary.MyHub"
)
for i in range(1, 4):
    blade_node = models.AssemblyNode(
        Definition = "ComponentLibrary.MyBlade"
    )
    ps_node = models.AssemblyNode(
        Definition = "ComponentLibrary.MyPitchSystem"
    )
    ps_node[f'Blade'] = blade_node
    hub_node[f'PitchSystem_{i}'] = ps_node

analysis.Turbine.Assembly['Hub'] = hub_node

Change a model to an alternative choice

Some model properties can be set to one of a number of different model types, to allow a choice between different options available in the calculation.

The property must simply be set to an object of one of the valid types. The valid types available are included in the doc strings, and the schema documentation available on the Bladed Next Gen website.

The example below is for dynamic stall. The detail of setting the specific properties on each model is omitted for brevity:

analysis.Settings.Aerodynamics.DynamicStall = models.OyeModel()

# or
analysis.Settings.Aerodynamics.DynamicStall = models.IAGModel()

# or
analysis.Settings.Aerodynamics.DynamicStall = models.CompressibleBeddoesLeishmanModel()

# or
analysis.Settings.Aerodynamics.DynamicStall = models.IncompressibleBeddoesLeishmanModel()

Working with type checking tooling

If using type checking development tooling, there are helper methods available to access typed references to values that could be one of several types.

For example, to obtain a reference to the DynamicStall value, the following method can be used. An error will be raised at run time if the type specifier cannot be honoured by actual objects.

The oye variable will receive a type of 'OyeModel' by the type engine, and at runtime is assured to receive an object of that type, or an error is raised.

oye = analysis.Settings.Aerodynamics.DynamicStall_as_OyeModel

Additionally, a reference to the union of all possible types can be obtained using the 'as' methods (this raises an error if the object is specified with an 'insert'):

dynamic_stall = analysis.Settings.Aerodynamics.DynamicStall_as_inline

Similar methods are available for libraries and arrays.

# Get the tower object as a specific reference from the library
tower = analysis.Turbine.ComponentLibrary.Component_as_Tower('tower')

# Get a Tower Can by index, as a reference to a specific type
first_simple_can = tower.Cans_element_as_SimpleTowerCan(0)

# or process tower cans using a union of all possible types
for i, can in enumerate(tower.Cans_as_inline):
    can.CanHeight = i * 10

Working with distributed files ($insert)

The Models API can be used to separate out a JSON file into multiple distributed files, and can read in individual files that have been distributed.

This package cannot resolve multiple distributed files into a single file or object. This capability is available via the Bladed Next Gen CLI, and equivalent capabilities will be made available natively in Python in a future release.

Given the following JSON:

{
    "SteadyCalculation": {
        "SteadyCalculationType": "AerodynamicInformation",
        ...
    },
    "Constants": {
        "AccelerationDueToGravity": 9.8100004196167,
        ...
    }
}

1. Read in the document from a file:

   analysis = models.BladedAnalysis.from_file(analysis_file)
   

2. Extract objects to separate files, and record the path reference in the owning object:

   analysis.SteadyCalculation_as_inline.extract_to_insert_from_file('steady-calc/aero_info.json', analysis_file)
   
   assert analysis.SteadyCalculation.is_insert == True
   
   analysis.Constants.extract_to_insert_from_file('constants.json', analysis_file)
   
   assert analysis.Constants.is_insert = True
   

   These operations will write new JSON files relative to the directory of analysis_file, containing the JSON representation of the respective object.

   i.e.

   In the directory of analysis_file:

   • steady-calc/aero_info.json : Will contain the full JSON representation of the AerodynamicInformationCalculation model object.

   • constants.json : Will contain the full JSON representation of the Constants model object.

3. Write out the updated analysis object to file, that now contains '$insert' references:

   analysis.to_file(analysis_file)
   

   The following JSON will be written:

   {
       "SteadyCalculation": {
           "$insert": "steady-calc/aero-info.json"
       },
       "Constants": {
           "$insert": "constants.json"
       }
   }
   

4. Read in a JSON document that contains inserts

   distributed_analysis = models.BladedAnalysis.from_file(analysis_file)
   
   # Test and inspect
   assert distributed_analysis.SteadyCalculation.is_insert == True
   print(distributed_analysis.SteadyCalculation.insert)
   
   # Attempting to treat the now distributed model object as 'in-line', will yield an error
   try:
       steady_calc = distributed_analysis.SteadyCalculation_as_inline
   except ValueError as e:
       print(e)
   
   # Update the insert location
   distributed_analysis.SteadyCalculation.insert = 'new-dir/aero-info.json'