Search Results (298)

This study addresses the challenge of rapid identification and assessment of localized damage to building envelopes under resource-constrained conditions—specifically, the absence of specialized inspection equipment—with a particular focus on the detrimental effects of such damage on thermal performance and energy efficiency. An efficient detection methodology tailored to small-scale maintenance scenarios is proposed, leveraging the YOLOv11 object detection architecture to develop an intelligent system capable of recognizing common envelope defects in contemporary residential buildings, including cracks, spalling, and sealant failure. The system prioritizes the detection of anomalies that may induce thermal bridging, reduced airtightness, or insulation degradation. Defects are classified according to severity and their potential impact on thermal behavior, enabling a graded, integrated repair strategy that holistically balances structural safety, thermal restoration, and façade aesthetics. By explicitly incorporating energy performance recovery as a core objective, the proposed approach not only enhances the automation of spatial data processing but also actively supports the green operation and low-carbon retrofitting of existing urban building stock. Characterized by low cost, high efficiency, and ease of deployment, this method offers a practical and scalable technical pathway for the intelligent diagnosis of thermal anomalies and the enhancement of building energy performance. It aligns with the principles of high-quality architectural development and sustainable building governance, while concretely advancing operational energy reduction in the built environment and contributing meaningfully to energy conservation goals. Full article

The UK’s net-zero by 2050 commitment necessitates urgent housing sector decarbonisation, as residential buildings contribute approximately 17% of national emissions. Post-1950 construction prioritised speed over efficiency, creating energy-deficient housing stock that challenges climate objectives. Current retrofit policies focus primarily on technological solutions—insulation and heating upgrades—while neglecting broader sustainability considerations. This research advocates systematically integrating Circular Economy (CE) principles into residential retrofit practices. CE approaches emphasise material circularity, waste minimisation, adaptive design, and a lifecycle assessment, delivering superior environmental and economic outcomes compared to conventional methods. The investigation employs mixed-methods research combining a systematic literature analysis, policy review, stakeholder engagement, and a retrofit implementation evaluation across diverse UK contexts. Key barriers identified include regulatory constraints, workforce capability gaps, and supply chain fragmentation, alongside critical transition enablers. An evidence-based decision-making framework emerges from this analysis, aligning retrofit interventions with CE principles. This framework guides policymakers, industry professionals, and researchers in the development of strategies that simultaneously improve energy-efficiency, maximise material reuse, reduce embodied emissions, and enhance environmental and economic sustainability. The findings advance a holistic, systems-oriented approach, positioning housing as a pivotal catalyst in the UK’s transition toward a circular, low-carbon built environment, moving beyond isolated technological fixes toward a comprehensive sustainability transformation. Full article

The assessment of buildings’ energy performance plays a critical role in achieving global sustainability goals, particularly in reducing carbon emissions and improving energy efficiency. In this context, various modelling approaches have been developed to evaluate building energy performance. Among them, data-driven models, such as machine learning (ML) algorithms, have gained significant attention in recent years due to their scalability, fast development process, and high predictive accuracy. However, a key limitation of these models is their limited interpretability, which can negatively affect their application particularly in decision-making and retrofit planning processes. To address this issue, SHapley Additive exPlanations (SHAP) has emerged as a promising approach for interpreting complex ML models by quantifying the contribution of each input feature to the model’s predictions. As a result, this study developed an XGBoost ML model that predicts energy performance of residential buildings in the UK with an R² value of more than 0.98. After that, SHAP method was applied to explore and explain the effect of individual features on model outcomes, which highlighted that SHAP framework can be a strong complementary approach for enhancing the interpretability and practical applicability of black-box models in building energy performance analysis. Full article

This study presents an integrated ex-post evaluation of a municipal window-retrofit program in Goyang, Republic of Korea (heating-dominated, Dwa). Using field surveys and pre- and post-utility bills for 36 dwellings, mainly pre-2000 low-rise reinforced-concrete buildings, we normalize climate with HDD and CDD and prices with CPI-deflated tariffs to isolate the intrinsic effect of window replacement. Area-normalized indicators ($∆e$, $\eta$, DPB, NPV, AC) were computed. Average annual savings were 30.2 kWh per m² per year ($\eta$ ≈ 16 percent), consisting of 10.6 kWh per m² per year of gas and 19.6 kWh per m² per year of electricity (n = 36). The median discounted payback was 7.0 years. Under a 50 percent subsidy, about 80 percent of projects recovered private investment within 15 years and showed positive NPV with a median of about USD 4944. The electricity-tariff multiplier had the largest influence on cash flows and payback. The median abatement cost was about USD 352 per tCO₂-eq. A portfolio view indicates that prioritizing low-cost cases maximizes total abatement, and that higher-cost cases merit design or cost review. Using the first post-retrofit year 2023, portfolio abatement is about 623 tCO₂-eq per year. The framework jointly normalizes climate and price effects and yields policy-relevant estimates for heating-dominated contexts. Full article

In recent decades, energy efficiency policies have increasingly focused on reducing buildings’ energy use and improving their performance. However, by overlooking the entire life cycle of a building, a considerable portion of its environmental impact has indeed been kept out of the process. As a result, even leading buildings that have advanced toward Zero-Energy status may not that as innocent as promised by evaluating environmental impacts during their whole life. Consequently, a logical method for achieving nearly Zero Energy Buildings (nZEBs) involves implementing energy-efficient measures and proper materials throughout the entire life cycle of buildings. This paper is one of its first kinds that includes all building systems and materials embodied energy and cost to explore the possibility of creating nearly zero residential buildings through their life cycle. Life-cycle energy consumptions, life-cycle CO₂ emissions and life-cycle cost of nZEB retrofit packages for a five-storey, 20-apartment residential building in Ankara, Turkey were evaluated. The methodology couples dynamic simulation (DesignBuilder/EnergyPlus) with an EN 15978-aligned boundary (A1–A5, B, C). The study highlights the critical role of both operational and embodied energy and carbon emissions in the pursuit of nZEBs. The best nZEB package reduces primary energy by ~55% and life-cycle CO₂ by ~45% relative to the reference building over 50 years, while cost-optimal packages deliver 6–7% lower global cost. These findings demonstrate the effectiveness of life cycle assessment in measuring building environmental impact, the utilization of renewable energy, and the optimization of building materials in reducing energy consumption and emissions, providing a sustainable and cost-efficient approach to residential building design. Full article

Reducing energy demand and carbon emissions in residential buildings requires more than technological upgrades; it demands a nuanced understanding of occupant behaviour. Residential energy use is shaped by both physical design and human actions, yet behavioural factors remain underexplored, contributing to the energy performance gap. This study addresses this issue by developing and validating a behavioural framework grounded in the Theory of Planned Behaviour (TPB) to examine how attitudes, social norms, perceived control, and environmental awareness influence energy-related decisions. Data were collected through an online survey of 310 households in metropolitan Sydney and analysed using Stata v17 software employing principal component analysis and regression modelling. Results reveal that environmental awareness is the most significant predictor of pro-environmental intention, which strongly correlates with actual behavioural outcomes. While attitudes and perceived control were generally positive, subjective norms and awareness remained moderate, limiting behavioural change. The proposed framework demonstrates strong validity and reliability, offering a practical tool for policymakers, designers, and educators to integrate behavioural insights into sustainable building strategies. By prioritising awareness campaigns and normative interventions, stakeholders can complement technical retrofits with behavioural measures, accelerating progress towards low-carbon housing and benefiting both households and the broader community. Full article

This study investigates the architectural design factors that influence the adoption of eco-friendly solar energy technologies for the partial retrofitting of older residential buildings in densely populated urban areas in a developed country. This research study employs a mixed-method approach, combining quantitative and qualitative frameworks along with comparative analysis and utilizing standard fact-finding procedures to examine the adoption of eco-friendly energy systems and their integration into existing infrastructures. The feasibility study, complemented by a detailed technical investigation, identifies several significant factors affecting the intention to undertake sustainable solar retrofitting. These factors include performance expectations, facilitating conditions, motivation, price/value perceptions, and environmental knowledge. This study highlights key constraints and tipping points that influence households’ decisions to implement light retrofitting and explores three distinct system configurations to enhance cost-effectiveness. The insights gained from this research study are valuable for a range of stakeholders, including homeowners, designers, technology developers and manufacturers, real estate developers, builders, and government entities. The findings guide effective strategies to encourage eco-friendly retrofits through both passive and active systems, contributing to future environmental sustainability goals. This research study addresses a gap in the literature regarding the environmental sustainability of solar retrofitting in densely populated urban settings in developed countries. Addressing the pressing issue of global warming contributes to advancing sustainable solar housing technologies and provides a comprehensive foundation for the early stages of the design process. Full article

This study presents the design and implementation of a prototype dual-function photovoltaic window system that integrates flexible solar panels for dynamic shading and a compact lithium battery for local energy storage. The methodology involves developing an experimental setup where translucent, flexible photovoltaic panels are retrofitted onto a standard residential window. The system is connected to a charge controller and a small-capacity lithium-ion battery pack. Key performance metrics, including solar irradiance, power generation efficiency, reduction in thermal transmittance, and battery state of charge, are continuously monitored under varying real-world environmental conditions. The integrated panels can significantly reduce solar heat gain, thereby lowering indoor ambient temperature and reducing the building’s cooling load. Simultaneously, the system will generate sufficient electricity to be stored in the lithium battery, providing a self-contained power source for low-draw applications such as lighting or charging personal devices. This research highlights the viability of developing cost-effective, multi-functional building components that transform passive architectural elements into active energy-saving and power-generating systems in terms of green environment goals. Full article

Conventional approaches to building energy retrofit decision-making struggle to generalize across diverse building characteristics, climate conditions, and occupant behaviors, and often lack interpretability. Generative AI, particularly Large Language Models (LLMs), offers a promising solution because they learn from extensive, heterogeneous data and can articulate inferences in transparent natural language. However, their capabilities in retrofit decision-making remain underexplored. This study evaluates six widely used LLMs on two objectives: determining the retrofit measure that maximizes CO₂ reduction (a technical task) and minimizes the payback period (a sociotechnical task). We assessed performance across accuracy, consistency, sensitivity, and reasoning. The evaluation used 400 residential buildings from a nationwide, simulation-based database. The results reveal that LLMs vary across cases, with consistently strong technical-task performance but notably weaker performance on the sociotechnical one, highlighting limitations in handling complex economic and contextual trade-offs. The models consistently identify a near-optimal solution for the technical task (Top-5 accuracy reaching 92.8%), although their ability to pinpoint the single best option is limited (Top-1 accuracy reaching 54.5%). While models approximate engineering logic by prioritizing location and geometry, their reasoning processes are oversimplified. These findings suggest LLMs are promising for technical advisory tools but not yet reliable for standalone retrofit decision-making. Full article

Power outages during extreme heat events threaten occupant safety by exposing buildings to rapid indoor overheating. However, current building thermal resilience assessments rely mainly on physics-based simulations or IoT sensor data, which are computationally expensive and slow to scale. This study develops an Artificial Intelligence (AI)-driven workflow that integrates Building Information Modeling (BIM)-based residential models, automated EnergyPlus simulations, and supervised Machine Learning (ML) algorithms to predict indoor thermal trajectories and calculate thermal resilience against power failure events in hot seasons. Four representative U.S. residential building typologies were simulated across fourteen ASHRAE climate zones to generate 16,856 scenarios over 45.8 h of runtime. The resulting dataset spans diverse climates and envelopes and enables systematic AI training for energy performance and resilience assessment. It included both time-series of indoor thermal conditions and static thermal resilience metrics such as Passive Survivability Index (PSI) and Weighted Unmet Thermal Performance (WUMTP). Trained on this dataset, ensemble boosting models, notably XGBoost, achieved near-perfect accuracy with an average R² of 0.9994 and nMAE of 1.10% across time-series (indoor temperature, humidity, and cooling energy) recorded every 3 min for a 5-day simulation period with 72 h of outage. It also showed strong performance for predicting static resilience metrics, including WUMTP (R² = 0.9521) and PSI (R² = 0.9375), and required only 1148 s for training. Feature importance analysis revealed that windows contribute 74.3% of the envelope-related influence on passive thermal response. This study demonstrates that the novelty lies not in the algorithm itself, but in applying the model to resilience context of power outages, to reduce computations from days to seconds. The proposed workflow serves as a scalable and accurate tool not only to support resilience planning, but also to guide retrofit prioritization and inform building codes. Full article

Kinetic façades represent a climate-responsive design solution that improves building adaptability by responding to seasonal needs such as daylighting and shading. They offer an attractive retrofit strategy that improves both the esthetics and environmental performance of buildings. This study investigated the integration of an origami-inspired kinetic façade into a student dormitory building located in Dhahran, Saudi Arabia. Using numerical simulations, 35 façade configurations were analyzed under varying conditions of façade orientations, closure ratios (from 5% to 95%), and cavity depths (from 20 cm to 100 cm). The findings highlight the critical impact of kinetic façade design characteristics on daylight availability and solar exposure and the required trade-off between these two variables. In this context, this study observed that at higher façade closure ratios, increasing cavity depth could effectively mitigate daylight reduction by promoting reflected daylight penetration inside the cavity. As for heat gains and cooling load reduction, mid-range façade closure, 50 cm in this study, achieved balanced performance across the three examined orientations. However, the southern façade showed slightly higher efficiency compared to the eastern and western façades, which achieved lower cooling reductions and showed a similar UDI compromise. Thus, a dynamic façade operation is recommended, where higher closure ratios could be applied during peak solar hours on the east in the morning and the west in the afternoon to maximize cooling savings, while moderate closure ratios can be maintained on the south to preserve daylight. Future work should incorporate real-time climatic data and smart control technologies to further optimize kinetic façade performance. Full article

In recent years, European and national policies on energy efficiency and sustainable construction have promoted a profound rethinking of building practices and strategies for upgrading the existing building stock. With the conversion of Law Decree No. 34 of 19 May 2020 (Decreto Rilancio) into Law No. 77 of 17 July 2020, and of Law Decree No. 76 of 16 July 2020 (Decreto Semplificazioni) into Law No. 120 of 11 September 2020, the tax deduction rate was increased to 110% for expenses related to specific interventions such as seismic risk reduction, energy retrofit, installation of photovoltaic systems, and charging infrastructures for electric vehicles in buildings—commonly known as the Superbonus 110%. Furthermore, the category of “building renovation,” as defined in Presidential Decree No. 380 of 6 June 2001 (art. 3, paragraph 1, letter d), was expanded with specific reference to demolition and reconstruction of existing buildings, allowing—under certain conditions—interventions that do not comply with the original footprint, façades, site layout, volumetric features, or typological characteristics. These measures were designed not only to positively affect household investment levels, thereby significantly contributing to national income growth, but also to support the broader objective of decarbonising the building sector while improving seismic safety. Within this regulatory and policy framework, instruments such as the Superbonus 110% have acted as a driving force for the diffusion of renovation projects aimed at enhancing energy performance and reducing greenhouse gas emissions, in line with the objectives of the European Green Deal and the Energy Performance of Buildings Directive (EPBD). This paper is situated within such a context and examines a real-world case of bio-based renovation admitted to fiscal incentives under the Superbonus 110%. The focus is placed on the procedural framework as well as on the technical, economic, and evaluative aspects, adopting a multidimensional perspective that combines regulatory, operational, and financial considerations. The case study concerns the demolition and reconstruction of a single-family residential chalet, designed according to near-Zero-Energy Building (nZEB) standards, located in the municipality of San Roberto, in the province of Reggio Calabria. The intervention is set within an environmentally and culturally sensitive area, being situated in the Aspromonte National Park and subject to landscape protection restrictions under Article 142 of Legislative Decree No. 42/2004. The aim of the study is to highlight, through the analysis of this case, both the opportunities and the challenges of applying the Superbonus 110% in protected contexts. By doing so, it seeks to contribute to the scientific debate on the interplay between incentive-based regulations, energy sustainability, and landscape–environmental protection requirements, while providing insights for academics, practitioners, and policymakers engaged in the ecological transition of the construction sector. Full article

China’s urbanisation has transitioned from an era of rapid, coarse expansion to one of refined and targeted development. In accordance with China’s “dual-carbon” strategy, the building sector—presently the third-largest source of domestic carbon emissions—is compelled to pursue emission optimisation in its forthcoming evolution. Photovoltaic-building technologies offer an effective response to this imperative. Within the context of accelerating high-rise residential construction, the architectural integration of scientifically configured photovoltaic façades has emerged as a critical challenge. Employing an integrated methodology of urban surveying and simulation, this study examines the façade characteristics of residential buildings in northern Chinese cities, selecting Xi’an as the representative case. Three PV-facade integration strategies for existing stock are presented: window retrofitting, wall retrofitting, and full-façade renovation. Utilising the EnergyPlus platform, the manuscript simulates the electrical demand profiles and clean-electricity generation of typical dwellings under varying photovoltaic materials and configuration schemes, while concurrently assessing economic performance. It demonstrates that a judicious determination of photovoltaic installation scale and layout strategy markedly amplifies energy-saving efficacy, diminishes aggregate energy consumption and carbon emissions, and simultaneously reduces the capital expenditure of photovoltaic systems. For multi-story buildings, a full façade retrofit yielded the highest annual electricity generation of 514,703.56 kWh and an annual carbon reduction of 15,521.50 kgCO₂. For high-rise buildings, installing PV modules only above the 20th floor increased the effective generation ratio from 45.24% to 87.17%, while the carbon reduction efficiency per unit investment improved from 0.05 to 0.22 kgCO₂/¥. Full article

The comprehensive renovation of existing buildings has become imperative and is recognized as a central priority within the European Union’s agenda (European Green Deal). The objectives of this initiative include reducing energy consumption, mitigating environmental pollution, and achieving long-term decarbonization targets. This research addresses the case of load-bearing masonry buildings constructed in the post-World War II period, characterized by specific geometric and volumetric features. Current regulations on seismic design and thermal protection reveal significant deficiencies in both the structural safety and the energy performance of these buildings. Recent seismic events and the increasing demand for electricity further highlight the urgency of integrated retrofitting measures that simultaneously enhance structural resistance and improve thermal protection. This research aims to develop an integrated retrofitting approach that simultaneously improves seismic resistance and energy efficiency. A review of strengthening techniques and thermal upgrades was carried out, followed by a critical assessment of their applicability. The proposed intervention combines two comparable seismic reinforcement schemes with thermal improvements, implemented through a one-sided reinforced cement mortar overlay coupled with external thermal insulation materials. Analyses demonstrate that the retrofit increases the structural resistance to a_gR = 0.10 g and upgrades the building envelope to current energy efficiency requirements. The results confirm that the method is both effective and feasible, offering a replicable solution for similar residential masonry buildings. This study concludes that integrated retrofitting can extend building service life, enhance occupant safety and comfort, and provide a practical framework for large-scale application in sustainable renovation practices, which is especially significant for Serbia and other Balkan countries, considering that the analyzed case study buildings are characteristic representatives for these regions. Full article