An integrated approach of BIM-enabled LCA and energy simulation: The optimized solution towards sustainable development

Passive design strategies such as orientation, shading, sealing, glazing, and insulation can significantly reduce the necessity of an artificial heating-cooling system, accounting for 40% of total energy usage in the residential building. However, none of the previous studies have quantified the energy reduction and their environmental impacts simultaneously for these passive design parameters to achieve the national standard requirements for house rating. Hence, this study focuses on the use of Building Information Modeling (BIM-Autodesk Revit), energy rating tool (FirstRate5), and BIM-enabled life cycle assessment (LCA-Tally) to quantify, compare, and improve the building design options to reduce carbon footprint and energy consumptions in residential dwellings. Sensitivity analysis has been performed with the @Risk Palisade decision tool for optimizing operational energy efficiency. The sensitivity indices show the ceiling (0.84-0.96) and the wall (0.22-0.37) are the most influential predictors for passive design strategies to reduce energy consumption. A moderate correlation exists with windows, floors, and orientations (0.13-0.29), where the relationship with eave projection, air infiltrations is relatively weak. BIM has been used as a platform of interconnectivity between optimized operational energy of @Risk optimizer and consequent embodied phases. A comparative study of insulation performance identifies that 95% of the ceiling's total operational energy consumption can be minimized using R3 rather than R6 of the national thermal code. For the wall, 90% of energy minimization can occur using R2 rather than R4 of the national thermal code. The study reveals that while insulation is only 1% of the total building mass, and the corresponding carbon footprint and primary energy demand are 4% and 7%, respectively, LCA explains a significant amount of energy, about 76% reduction at its operational stage. In this paper, an evidence-based analytical framework provides a BIM based optimization platform to validate and justify the impact categories of environment-friendly, energy-efficient design of houses. (c) 2020 Elsevier Ltd. All rights reserved.