Systematic generation of insulation materials via DEA and Building modelling

Policies are encouraging to reduce emissions in all sectors, due to the high energy demand during the life cycle of the processes. Constructions are not an exception and policies are encouraging to reduce energy demand in buildings. Although new constructions are reducing their energy demand according to new directives, without interventions in the actual building stock, the European goals proposed for 2050 cannot be achieved. Insulation is known to achieve an important reduction in the energy demand in the operation phase of the buildings. Despite that, this implementation carries out an initial investment in both, cost and impact, which suggest that using low embodied materials, such us bio-based materials, could improve this solution. Despite their good thermal properties, these new materials are not arriving at the actual market for insulators. In order to improve this scalability, an evaluation of the efficiency of different materials is carried out, with a following combination of the efficient materials in order to generate new hybrid solutions. These hybrid materials cope to simplify the applicability of bio-based materials, generating sandwich panels or combined mats to generate materials similar to the commercialized ones which have an increasing market nowadays. The methodology presented combines Data Envelopment Analysis (DEA) and Building modelling simulation. Using thermal simulations of EnergyPlus and the evaluation of efficiency and further projections of DEA. Seven bio-based materials and polyurethane for comparison have been studied, with a thickness that varies from 1 cm and 26 cm in increments of 5 cm. DEA analysis is used to quantify the efficiency score of the different thicknesses of the materials. The non-efficient materials are projected to this frontier, achieving a combination of materials. Those combinations have been analysed in order to model only the feasible solutions, which have proved to achieve efficiency in all the combinations proposed.