Generative design pipeline for urban and neighborhood planning
US-12147737-B2 · Nov 19, 2024 · US
US10628535B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10628535-B2 |
| Application number | US-201615091321-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 5, 2016 |
| Priority date | Feb 1, 2007 |
| Publication date | Apr 21, 2020 |
| Grant date | Apr 21, 2020 |
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A method and system provide a complete energy analytical model. An input model is acquired and consists of a combination of architectural building elements (ABEs) and conceptual massing elements (CMEs). The input model is pre-processed by extracting information from both the ABEs and the CMEs, and constructing virtual elements that encapsulate the extracted information. A discrete set of points in three-dimensional (3D) space that is distributed over boundary faces of the ABEs or CMEs is determined. The discrete set of points is used to provide a representation of the input model that is used in combination with a 3D cubical grid (a voxel grid) to analyze a spatial structure of the input model. A two-dimensional (2D) discrete approximation of the geometry of the input model is used to determine surfaces of the energy analytical model which is then output.
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What is claimed is: 1. A computer implemented method for providing a complete energy analytical model comprising: (a) acquiring an input model, wherein the input model comprises a combination of one or more architectural building elements (ABEs) and one or more conceptual massing elements (CMEs), wherein: (1) the ABEs comprise individual objects that represent individual physical components of a building without explicitly modeling 3D spaces for the input model; (2) the individual physical components comprise walls, floors, windows, and roofs; (3) the ABEs represent characteristics of physical and geometric forms of architectural elements of the building; and (4) inaccuracies between ABEs exist in the input model; (5) the CME comprises a representation of the input model as a single composite 3D solid; (b) pre-processing the input model, wherein the pre-processing: (1) extracts information from both the ABEs and the CMEs in the input model; and (2) constructs a virtual element that encapsulates the extracted information; (c) determining a discrete set of points in three-dimensional (3D) space, distributed over boundary faces of the ABEs or CMEs; (d) providing, using the discrete set of points, a representation of the input model that is used to analyze a spatial structure of the input model; (e) approximating a geometry of the input model utilizing a two-dimensional (2d) discrete approach; (f) based on the spatial structure and the approximated geometry of the input model, determining surfaces of the energy analytical model wherein the energy analytical model is not a precisely accurate airtight energy analytical model, wherein in a precisely accurate airtight energy analytical model analytic faces meet without any gaps to bound 3D spaces; (f) outputting the energy analytical model comprised of the spatial structure and the surfaces; and (g) simulating energy usage of a building represented by the energy analytical model. 2. The computer-implemented method of claim 1 , wherein: the information comprises a surface and a material/thermal property. 3. The computer-implemented method of claim 1 , wherein: the surface comprises a face of one or more of the CMEs or the ABEs. 4. The computer-implemented method of claim 1 , wherein: the information comprises a category of one of the CMEs or one of the ABEs. 5. The computer-implemented method of claim 1 , wherein: the information comprises a level associated with one of the CMEs or one of the ABEs. 6. The computer-implemented method of claim 1 , wherein: the virtual element comprises a list of faces defining a three-dimensional (3D) shape and a separate list of faces used to construct surfaces. 7. The computer-implemented method of claim 1 , wherein: the discrete set of points comprises a point cloud. 8. The computer-implemented method of claim 1 , wherein the providing the discrete set of points further comprises: determining the spatial structure of the input model using a 3D voxel grid. 9. The computer-implemented method of claim 8 , further comprising: utilizing the 3D voxel grid to discretize the spaces and surfaces of the energy analytical model at a perimeter of the input model to represent differences in heat loss and gain. 10. The computer-implemented method of claim 1 , wherein the determining surfaces comprises: defining a rectangular grid in a 2D coordinate plane for a representative face of one of the ABEs or one of the CMEs; for each cell in the rectangular grid, moving to a side of the representative face, examining 3D voxels until a voxelized space is reached, while tracking the ABEs and CMEs passed through; deciding if a current cell should be part of a surface; if the current cell should not be part of the surface, process a next cell in the rectangular grid; if the current cell should be part of the surface, encoding information needed to determine which surface the current cell will be part of; and determining connected sets of cells having a same encoding, wherein connected sets of cells approximate the surfaces associated to a portion of one of the ABEs or CMEs. 11. The computer-implemented method of claim 1 , further comprising: utilizing a building information model (BIM) representation of the energy analytical model within a building design software application; querying the energy analytical model, within the building design software application; and updating the BIM representation before running an energy simulation.
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