Data Driven Assembly of Procedurally Modeled Facilities
| dc.contributor.author | Bishop, M. Scott | en_US |
| dc.contributor.author | Ferrer, Josè | en_US |
| dc.contributor.author | Max, Nelson | en_US |
| dc.contributor.editor | Eric Galin and Michael Wand | en_US |
| dc.date.accessioned | 2014-12-16T07:11:26Z | |
| dc.date.available | 2014-12-16T07:11:26Z | |
| dc.date.issued | 2014 | en_US |
| dc.description.abstract | We present a method to arrange components of industrial facilities in a constrained site footprint. We use a probabilistic graphical model of industrial sites and existing procedural modeling methods to automate the assembly and 3D modeling of wastewater treatment plants. A knowledge engineered approach produces a combination of components that inherently contains domain specific information like process dependencies and facility size. The inferred combination is laid out using mathematical optimization or via a physics-based simulation resulting in an arrangement that respects the industrial process and design plausibility. | en_US |
| dc.description.seriesinformation | Eurographics 2014 - Short Papers | en_US |
| dc.identifier.issn | 1017-4656 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/egsh.20141009 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | I.3.2 [Computer Graphics] | en_US |
| dc.subject | Graphics Systems Stand | en_US |
| dc.subject | alone Systems | en_US |
| dc.subject | G.3 [Probability and Statistics] | en_US |
| dc.subject | Probabilistic Algorithms Bayesian Networks | en_US |
| dc.subject | I.2.6 [Computing Methodologies] | en_US |
| dc.subject | Learning Knowledge Acquisition. | en_US |
| dc.title | Data Driven Assembly of Procedurally Modeled Facilities | en_US |
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