Optimization based feasibility study for filler slabs as a response towards the ECBC roof compliance with respect to thermal transmittance for five climatic zones of India

Ramya R. Acharya, Pranav Kishore, M. Raghuprem, Pradeep Kini, Stuthi Shetty, Anupam Raj

Research output: Contribution to journalConference articlepeer-review

Abstract

The Energy Conservation Building Code (ECBC) will soon be made mandatory pan India and the building designs must comply with the criteria for energy efficiency. One of the major components of ECBC is the building envelope. The roof assembly U-factor requirements is mentioned in section 4, clause 4.3.1. This research talks about filler slabs as a possible solution for roofing in buildings for ECBC compliance. A framework is developed that selects the optimum combination of the materials based on different parameters like u value for different commercial building typologies in five climatic zones of India. This research considers various filler materials that are tested for their thermal conductivity (k -value) in the Indian context. The list of materials formulates the range for selected variables, that are used for the optimization in the mathematical model. This mathematical model generates the result for six building typologies (two special case for level ECBC), five climatic zones, three levels of ECBC, two grades of steel and concrete each and six slab thickness, a total of 2208 cases. This optimization model produces the optimum choice for filler material in different cases based upon the variables and associated constraints. In the cases where the solution cannot be derived, it is deduced that filler slabs alone are not feasible to be used as a solution for the ECBC compliance.

Original languageEnglish
Pages (from-to)213-220
Number of pages8
JournalProcedia Manufacturing
Volume44
DOIs
Publication statusPublished - 2020
Event1st International Conference on Optimization-Driven Architectural Design, OPTARCH 2019 - Amman, Jordan
Duration: 05-11-201907-11-2019

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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