Rajasekar Elangovan’s research while affiliated with Indian Institute of Technology Roorkee and other places

This paper addresses the estimation of a residential building's embodied energy through real-time data and evaluates the influence of diverse infill wall materials on its embodied energy. The investigation centers on a 10storey residential structure situated in Roorkee, India's composite climate. The study encompasses initial embodied energy from the bill of quantities and recurring embodied energy from maintenance and replacement cycles. Calculated at 11630 MJ/m², the determined lifetime embodied energy comprises 98.6% initial and 1.4% recurrent energy. A comparative analysis is conducted against existing literature and extended to alternative building envelopes. Findings indicate that using fly ash lime brick for infill walls minimizes embodied energy, potentially saving around 515MJ/m² across the building's lifespan. This research provides valuable insights into estimating and comparing the embodied energy of residential buildings and highlights the potential energy efficiency benefits of specific building envelope choices.

This study investigates the effect of thermal mass and insulation position on the thermal performance of residential buildings in a cold climate. A combination of numerical simulations and field measurements is employed to assess the impact of different wall configurations on heating energy demands and comfort. Configurations with thermal mass placed on the interior side of walls exhibit better thermal performance, reducing temperature fluctuations and enhancing thermal comfort. The study also explores the influence of climate severities, changing the window-to-wall ratio and building orientation on energy savings and comfort for various wall configurations. Wall B (thermal mass inside and insulation outside) reduces HED by 4% and HDD by 3% across different locations. Wall B reduced HED by 9.8% and HDD by 1.4% for a south facing building, and reduced HED by 3.2% and HDD by 2.2% for 10% WWR.

Climate zoning plays a vital role in developing and implementing building energy regulations. India is classified into five climate zones based on which building energy efficiency strategies are recommended. The climate diversity across India's geography impacts the effectiveness of these strategies. Bioclimatic zoning is a building-centered approach that effectively enables the integration of climate-responsive strategies. In thiscontext, this paper discusses and presents the bioclimaticclassification of India based on Mahoney strategy groupsderived from high-resolution spatial climatic data. The study pertains to residential buildings and derives the classification based on the size of openings, opening protection, and thermal mass of the envelope. The study's objectives are to delineate bioclimatic zones and to validate them using energy simulations. The study uses 30-second resolution data from the WorldClim data repository and presents six bioclimatic zones. Buildingenergy simulations are carried out using a validatedenergy model developed in the Energy Plus tool at50kmx50km grid resolution covering 1135 locations. Climate-responsive design strategies are incorporated for each location. Cooling and heating indoor degree hours are computed using dynamic base temperature based on the running mean temperature for each location. Asignificant variation is established in the Cooling indoordegree hours performance of the building considering thedesign strategies deduced based on bioclimatic zoning. The bioclimatic zones are intended to serve as a design basis for residential buildings

Grey Wolf Optimization (GWO) is an emerging evolutionary metaheuristic technique capable of solving challenging engineering problems. Despite its growing popularity, GWO's suitability for building design problems remains unexplored. This paper presents a novel algorithmic framework using EnergyPlus, EPLauncher and Matlab to implement a single and bi-objective GWO for building energy optimization. The goal is to identify optimal wall and window type, orientation, air conditioner's operational profiles and cooling setpoints consistent with minimum annual and peak cooling energy demands for a residential apartment building in five Köppen-Geiger climate zones across India. In place of testing the entire parametric space involving 5,76,000 possibilities, GWO identifies the optimal solutions inside 1250 trials (∼99% run reduction). The single and bi-objective GWO produces (83-97)% and (75-95)% annual and peak cooling demand reductions than a typical construction and operation scenario in the five climate zones. The optimized solutions recommend low thermal transmittance-high capacitance wall sections, 10–15% window-to-wall ratios and double glazed windows with a low solar gain coefficient. Further, optimal air conditioner operational parameters (setpoint and duration) are identified. The presented algorithmic framework is highly robust and can integrate can incorporate upcoming metaheuristic algorithms to perform single and multiobjective building energy optimizations.

In this research work, results on optimization of parameters related to energy consumption for indoor climate control of a building enclosure are discussed. The analysis is carried out for a building unit maintained at comfort level using Mitsubishi 1.5 ton of refrigeration split air conditioner. A mathematical model based on energy balance and experimental trials were used to compute energy consumption for space cooling/heating conditions. For the purpose of optimization, six control variables at three levels have been chosen from environment, thermo-physical properties, and geometrical variables. Taguchi optimization was carried out using L27 orthogonal arrays to obtain an experimental test strategy for cooling and heating modes, which gives rise to two sets of parameters. With the implementation of utility concept, a single set of optimum level parameters were obtained for both heating and cooling mode operations. Taguchi technique predicted 1.606 kW and 1.252 kW as optimum energy consumption for space cooling and heating modes, respectively with 95% confidence level. Inside humidity ratio, overall heat transfer coefficient and wall to window ratio are predicted as the most influencing parameters for both cooling mode and heating mode operations by the Taguchi method and utility analysis.

Many countries in the Global South have hot and dry climates with large diurnal temperature variations, which leads to large demand for space cooling-which is likely to increase with climate change. A common approach to dampen the indoor temperature fluctuations and thus reduce cooling energy demand is the use of thermal mass. However, the use of lightweight structures in many cities (e.g., high-rise structures, or for earthquake protection) precludes the use of traditional forms of thermal mass. Therefore, phase change materials (PCMs) are being widely developed as thermal energy storage systems for building applications. However, challenges such as leakage of PCMs in liquid state and their low thermal conductivity, still limit their applications in buildings. In this paper, we review the potential of Form or Shape-Stabilized Phase Change Materials (SSPCMs), which are developed by incorporating the PCM into a supporting matrix to prevent leakage in liquid state whilst improving thermal conductivity. We review different methods of preparation and the resultant thermal properties and chemical stability. We find good evidence in the literature for SSPCMs to reduce PCM leakage in liquid state, dampen indoor temperature fluctuations, and potentially alleviate peak energy demand by shifting peak loads to off-peak periods.