AnnuOWL is our Annual simulation workflow based on Radiance grid-based simulation approach. Supported by 64 original Grasshopper Python components, AnnuOWL can support lighting and facade designers by providing an annual understanding of the entire space's lighting performance, for visual and non-visual aspects. Occupant-centered metrics are visualised via an intuitive visualisation proposed to be called as OVNI (Occupant Visual and Non-visual Illumination) diagrams, which are designed to look like UFOs. For each OVNI, the hemisphere indicates performance for daylight provision, and surrounding rings indicate 1) non-visual/circadian potential, 2) protection from discomfort glare, and 3) satisfaction via view quality (not yet incorporated).
This part of the tutorial series presents the installaton procedure (Python, Radance, Ladybug tools, GH_Cpython) required by AnnuOWL to function. It also presents a background setting in Rhino for exporting OBJ files, as required by one component for function appropriately.
1. Python 2.7 can be downloaded here..
2. Using Pip, install: numpy, scipy, and matplotlib...
3. Radiance is available here., needs to be added to Path.
4. Latest Ladybug 1.x can be downloaded here (latest is 1.6 as of this day).
5. GH_Cpython component can be downloaded in a zip file from here.
6. Settings in rhino for exporting OBJs by unchecking the remapping function.
This part of the tutorial series presents the structure of the zip file available for download, along with an overview of the grasshopper workflow.
In this part, a pre-simulated case (of the 4 cases provided in the zip file) is used to demonstrate the functioning of the workflow. A basic overview of sliders is presented.
An in-depth run-through of grid-based space-centered analysis is presented, while using pre-simulated case data. Use of panel and slider inputs is demonstrated.
A detailed run-through pf OVNI-based occupant-centered analysis is presented, using pre-simulated case data. The logical flow used in the evaluation of OVNI-visualised metrics is also presented.
For OVNI- and grid-based metrics, the use of panels and sliders for modifying user-inputs and customising the evaluation criteria is demonstrated. This could be useful while evaluating standards other than default EN17037, and may also be useful while evaluating future updates of the standards.
Previous parts of the tutorial series used pre-simulated (cached) data for demonstrating various possibilities of AnnuOWL. Performing live simulations (by changing the "Cached?" in section 1.1.2 of the workflow, to False) is demonstrated in this part. Grid- and OVNI-based evaluations are discussed for various grid positions and for different occupant viewing positions.
In the previous video demonstrating live simulation, a template geometry provided with the workflow is used for the evaluation. In this part, the process for incorporating original geometry layers is demonstrated.