Ehsan Asadi
Refurbishment Decision Support System (RDSS) for building renovation strategies
Buildings are energy gluttons and have a large impact on the global climate change and other energy-related environmental issues. In Portugal, building sector consume about 29% of the total energy consumption. As a direct result, it is responsible for nearly 29% of CO2 equivalent greenhouse gas emissions.
Most European countries have succeeded in reducing energy consumption of new dwellings by more than 50% without increasing their building cost, and therefore, energy efficiency has achieved great acceptance among building owners. These buildings represent about 20% of the building stock but consume only 5% of energy. Concentration on improving the energetically poor building stock has great potential. Besides, the cyclical nature of the construction industry, the fact that the built environment is aging at a fast rate, the overall reduction in new building construction and the increasing awareness for sustainability, open new opportunities for expanding the refurbishment and reconstruction of buildings.
However, refurbishment work is usually characterized by complex and heterogeneous natures that require various specialties to integrate in highly variable conditions. Therefore stakeholders involved in building refurbishment projects may want to utilize neural networks, genetic algorithms, knowledge based decision support system, etc. for performing complex analysis in various ways and selection of the most suitable refurbishment actions.
Accordingly, in exploring the questions of building refurbishment, the aim of this project is to propose a concept for developing user friendly building condition assessment and refurbishment decision support system (DSS), more focusing on the organizations responsible for school buildings refurbishment facing refurbishment decisions, two dimensional trade-off between cost and quality, and physical and functional states of building in conducting condition assessment. This decision support system enable these organizations easily conduct the building condition assessment and offers optimal refurbishment actions considering the trade-off between cost and quality.
