Energy-Efficient & Passive Strategies for Thermal Comfort in Indoor Spaces

Speaker :
Mr. Nikhilesh Ghanta
Computation for Design & Optimization, Building Technology Lab
Massachusetts Institute of Technology, USA
Date : 22 Jan 2019 (Tue)
Time : 11:00 am
Venue : Room 5562, HKUST (5/F., Lift #27/28)


With increased risks of climate change and global warming, it becomes imperative to focus on energy efficient solutions. 10% of the world’s energy consumption is attributed to the indoor space heating and cooling, and this number increases to 35% when it comes to Hong Kong. This brings in the need for new cooling systems like chilled beams and also increases the importance of passive thermal strategies like thermal mass and natural ventilation. A low hanging fruit is the implementation of Internet of Things (IoT) and Artificial Intelligence (AI) to optimize the controls and monitoring of the HVAC systems in building spaces. For any improvements of such nature, simulations of the physics involved prove quintessential for understanding the processes going on and Computational Fluid Dynamics (CFD) is one such very popular tool. Current research at the Building Technology lab in MIT looks into understanding the local temperature stratification in indoor spaces using CFD so that optimum thermal comfort is achieved with minimal energy usage. Experimental results also prove necessary to completely validate such CFD models. Design strategies of passive systems are also incorporated into new building models and energy usage predicted through software such as Energy Plus. These results can be modeled using simpler Machine Learning algorithms like RBNN and Kriging and checked for global optimality.


Nikhilesh Ghanta is a graduate student in the inter-disciplinary Computation for Design & Optimization program and a researcher in the Building Technology lab at MIT. He is focused on indoor thermal comfort and energy-efficient cooling & heating strategies, while being sensitive to climate change. Through Computational Fluid Dynamics and other simulation methods, he is very keen on applying modeling and optimization techniques to the domain of energy and heat transfer. He has an undergraduate degree in Mechanical Engineering from IIT Madras and an M. Tech in Energy Technology. Prior to his research at MIT, he worked on operations and thermal-related problems during his two-year professional stint at Wipro Infrastructure Engineering in India. He has contributed to multiple international journal publications and presented at various conferences.