Building Science is a field of study that focuses on the technical performance of buildings, building materials and building systems. This broad discipline includes elements of construction technology, material science, architecture, meteorology, sustainable building, and heat and mass transport physics. BSRC focuses on effectively using Information Technology (IT) for sustainable buildings. Some of the major research projects of BSRC are Center for Building Energy Research and Development funded by DST and US DOE, Cool Roof Calculator funded by Climate Works Foundation, Earth Cooling System Monitoring in Pantanagar and Nanital funded by US DOE, Cool Roof Monitoring in Satyam Learning Center Hyderabad funded by US DOE, Smart Classrooms by NOKIA, and Monitoring of Distributed Transformers funded by Central Power Research Institute.

An Early Stage Design Decision Tool for Building Energy Efficiency

Research Area
Energy Efficient Buildings
Keyword
Building Energy Simulation, Energy Efficiency, Machine Learning, Sensitivity Analysis, Visualization
Technology Description
Building energy efficiency and life cycle cost is important considerations when designing a building. The early design phase provides more opportunities and flexibility as there are fewer constraints. In typical practice, design teams use energy simulation tools to estimate energy consumption/cost using consider several parameters and their combinations. Many tools consider only a small set of combinations of parameters for energy efficiency/life cycle cost. Furthermore, building professionals lack an easy-to-use tool that is available to all related professions and facilitates the discussion between architects and engineers. To fill this gap, a tool called early Design Optimization Tool (eDOT) has been developed to help the design team visualize the spectrum of building design solutions for energy efficiency. eDOT performs annual energy simulation of a five zones simplified model using EnergyPlus. eDOT performs a sensitivity analysis that helps a designer understand the impact of key parameters on energy performance.Parameters such as Azimuth, Aspect Ratio, Overhang, Window to Wall Ratio (WWR), Roof Insulation thickness, Wall Insulation thickness and Glass Type are considered in the tool. The tool uses cloud computing and machine learning algorithms to speedup the simulation process.
Type of Work
Idea, Algorithm, Software system, Data set
Current State of work
Technology designed, but not yet implemented
Potential Applications
1. This technology can be used in early stage of building design for energy efficiency. Beneficial for architects, building owner, and design team.
Related Publications
1. WinOpt - An Early Stage Design Tool for Optimizing Window Parameters, 30th International PLEA Conference 2014, Vol12