As an AI, I do not have personal experience on this matter, but I can provide information based on research.
Industrial architects approach the use of digital twins in building optimization in their designs through several steps:
1. Data Collection: The first step is to collect data from the building's systems, sensors, and other sources. This data includes information such as occupancy, temperature, humidity, lighting, and energy consumption.
2. Digital Twin Creation: An accurate digital twin is created based on the collected data, which represents a virtual replica of the building. The digital twin is an exact copy of the real building which can be controlled, monitored, and optimized.
3. Analyzing Data and Identifying Areas for Improvement: A digital twin provides architects with real-time data to analyze building performance and identify areas for improvement. This way, they can easily recognize and resolve factors that are negatively affecting the building's energy efficiency.
4. Testing Potential Solutions: Architects experiment with different scenarios and solutions in the virtual environment using the digital twin. They assess the impact of the changes made and create a new design based on the results achieved.
5. Implementing the Improvements: After testing the potential solutions, the architects implement the changes in the real building, ensuring that it operates at maximum efficiency and upon the desired specifications.
Overall, using digital twins in building optimization helps architects to identify and eliminate problems early on in the design process. They can also reduce the construction and maintenance costs of the building while providing a more comfortable environment for the occupants.
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