summaery2018: Projects
Parametric Modeling in BIM
Project information
Martha Castillo, Fabian Hartung, Syed Nafifur Rahman, Umar Arif Shaik, Anees Vellattuchola
Co-Authors MentorsJenny Rütz
Faculty / Section:
Civil Engineering
Degree programme:
Management [Construction Real Estate Infrastructure] (Master of Science (M.Sc.)),
Natural Hazards and Risks in Structural Engineering (NHRE) (englischsprachig) (Master of Science (M.Sc.))
Presentation
SemesterSummer semester 2018
Exhibition Location / Event Location- Marienstraße 15 - Mensa am Park
(Foyer der Mensa im EG (am 12.07. von 18.00 Uhr bis 18.45 Uhr))
Project description online
This project is a close cooperation with the solid construction company Town & Country Haus which specializes in typified single and two-unit houses. With the ongoing digitization in the building sector planning processes can be optimized through automation. This saves effort, costs and the error rate can be reduced significantly. The focus of this work was the automated quantity and mass determination of several building models with subsequent price calculation. For achieving this, building components were linked to prices through Dynamo which is a visual programming application in the BIM-software Revit. The students created a parametric algorithm for exporting quantity and mass data into an Excel spreadsheet where the total price was calculated according to Town & Country company-specific requirements. Another part of the project was the automated construction plan output which allows easy plan creation by using templates and stack export by only one mouse-click. Furthermore the building models were used for demonstrating the construction process. By importing them into the Navisworks software, all building components were linked to the construction schedule. For visualization purposes animations which show the individual stages of construction were produced. The results of this project confirm that parametric algorithms are of great use for automating certain tasks and therefore, for the optimization of planning processes.