Evaluating Architectural Design by Using BIM and Virtual Reality
Virtual Reality Experience
Coupling capabilities of BIM with VR and game engines can create a highly interactive environment with a digital geometry model derived from the BIM software. This provides a powerful tool that helps the designers better understand different design options and provide a decision-making framework to choose the best solution.
In this project, the team focuses on evaluating daylighting and different types of windows in the early design phases of a building, which should satisfy additional requirements and stakeholders’ needs. The team utilizes a combination of BIM and VR in the CAVE lab.
Project Overview
Product: An Immersive Virtual Model of a commercial building with two design options
Project Duration: February 2018- April 2018
My Role: Virtual 3D model Designer, Researcher
Responsibilities: In a team of three, I was in both the design and research teams.
The Problem: Complexity of the architectural design review process and issues related to evaluating different design options using conventional tools
The Goal: Investigate the applicability of the integrated system of the game engine, VR, and BIM in the CAVE lab for assessing Architectural design options, evaluate BIM-CAVE as a tool for assessment of different design options, and propose a framework as a decision-making system that can help project stakeholders to choose the best design option for the projects.
LSU CAVE Lab
Process of Proposed Approach
As a case study, we made the architectural model of two concept restaurants with different designs of openings and used the CAVE lab to evaluate occupants' feedback about the two designs. The first design uses traditional and normal windows and the second one uses curtain wall windows.
We used Autodesk Revit, Autodesk 3D Max, Unreal Engine, and the CAVE lab at LSU for this project.
Proposed framework for an architectural design decision-making model
Implementation
Create 3D BIM models in Revit
3D modeling of two prototypes of restaurants was performed in Autodesk Revit. The BIM model contains architectural details and components, geometric and non-geometric information of components furniture, and materials.
3D model of the first design option (Normal window)
3D model of the second design option (Curtain wall window)
Adjust the model in 3D MAX
The models were imported and adjusted in Autodesk 3D MAX to be prepared for importing to Unreal Engine software and then exported to FBX format.
Import the model into Game Engine (Unreal Engine software) and adjust the model for CAVE
Prepared FBX files imported to the Unreal engine. In this step, the required adjustments were performed, including assigning materials, adding lighting, and coding for required actions.
There are different options available in Unreal software for gaming scenarios such as first-person, third-person, etc. We used the first-person for a better sense of presence when we run the model in the CAVE.
Run in the CAVE and evaluation
In this step, two alternatives were prepared for execution on the CAVE. The cluster system of the CAVE needs several processes to run the VR model.
We conducted a short survey with 10 participants after a simple subjective test. Participants were asked to go through both alternatives and evaluate the building design and daylighting as restaurant customers. After evaluation, they answered a short questionnaire with two distinct sets of questions (1) design-related questions and (2) CAVE-related questions.
Evaluating Architectural design options in the CAVE
CONCLUSION AND LIMITATIONS
Our study showed that CAVE is a very user-friendly and effective tool for design evaluation. The CAVE was successful to visualize two distinct design options for participants so that they had different feelings about the alternatives, which was reflected in the survey. However, the results also illustrated that some participants moderately agreed that they had a complete sense of presence. This might be because of model-related issues, CAVE-related issues, or a combination of them. Further studies might help to find out the main reasons.
It should be considered that our sample was small because of time limitations. For more reliable results this study can be replicated with more participants.
Because of the limited time we narrowed down the scope of the project only to the visualization part of our framework. Considering the complete process of the proposed framework and developing a comprehensive decision-making model can be an interesting topic for future study.