Search Results (3)

The building and construction sector significantly impacts CO₂ emissions and atmospheric pollutants, contributing to climate change. Improving energy efficiency in buildings is essential to achieving carbon neutrality by 2050, as outlined in the European Green Deal. This study presents a decision-support tool for energy retrofit interventions in existing residential buildings. The methodological approach begins with the identification and classification of common roof and wall types in the national residential building stock, segmented by construction period, followed by defining optimized, pre-calculated standardized solutions. The performance evaluations of proposed solutions resulted in a matrix designed to guide practitioners in selecting pre-calculated, efficient, and sustainable prefabricated solutions based on energy performance criteria. The tool developed from this matrix enables preliminary energy assessment, offering an overview of potential retrofit interventions. It assists designers in identifying specific cases based on construction period, building type, and climate zone, allowing for the selection of standardized solutions, energy pre-analyses, energy and cost-saving simulations, and access to detailed performance sheets. Unlike other tools requiring extensive input on opaque envelope components and thermo-physical calculations, this tool streamlines the selection process of vertical and roof closures based on construction age and building type. Additionally, the tool estimates potential economic savings and the Net Present Value (NPV) of proposed insulation solutions, identifying available incentives for the intervention. Full article

Existing reinforced concrete building structures have low lateral resistance capacities due to seismically deficient details. Since these building structures suffer an increase in axial loads to the main structural elements due to green retrofits (e.g., installation of energy equipment/devices, roof gardens) as one of the sustainable building solutions and/or vertical extensions, their capacities can be reduced. This paper aims to propose a rapid estimation method incorporating a previously developed machine-learning model to find an allowable range of axial loads for reinforced concrete columns using simple structural details for enhancement in the sustainability performance of existing buildings in structural and energy fields. The methodology consists of two steps: (1) a machine-learning-based failure detection model, and (2) column damage limits proposed by previous researchers. To demonstrate this proposed method, an existing building structure built in the 1990s was selected, and the allowable range for the target structure was computed for both exterior and interior columns. A machine-learning-based method showed that axial loading could be increased by a factor of 1.35. Additionally, nonlinear time-history analysis for the target structure was performed to compare the seismic responses before and after applying the maximum allowable axial load. Based on the dynamic responses, the increased axial loads from green retrofits and/or vertical extensions could degrade structural performance and change its failure mode. The proposed methodology can rapidly estimate the allowable axial load range for existing reinforced concrete buildings without repeated modeling and computing processes. In addition, nonlinear time-history analysis is needed to accurately evaluate the impact of the increased axial loads from green retrofits/vertical extensions on structural performance. Full article

Türkiye’s earthquake zone, primarily located along the North Anatolian Fault, is one of the world’s most seismically active regions, frequently experiencing devastating earthquakes, such as the one in Hatay in 2023. Therefore, reconstructing energy-efficient buildings after major earthquakes enhances disaster resilience and promotes energy efficiency through retrofitting, renovation, or demolition and reconstruction. To this end, this study proposes implementing energy-efficient design solutions in dwelling units to minimize energy consumption in new buildings in Hatay, Southern Turkiye, an area affected by the 2023 earthquake. This research focused on a five-story residential building in the district of Kurtlusarımazı, incorporating small-scale Vertical-Axis Wind Turbines (VAWTs) with thin-film photovoltaic (PV) panels, along with the application of a green wall surrounding the building. ANSYS Fluent v.R2 Software was used for a numerical investigation of the small-scale IceWind turbine, and DesignBuilder Software v.6.1.0.006 was employed to simulate the baseline model and three energy-efficient design strategies. The results demonstrated that small-scale VAWTs, PV panels, and the application of a green wall reduced overall energy use by 8.5%, 18%, and 4.1%, respectively. When all strategies were combined, total energy consumption was reduced by up to 28.5%. The results of this study could guide designers in constructing innovative energy-efficient buildings following extensive demolition such as during the 2023 earthquake in Hatay, Türkiye. Full article