Search Results (45)

The conversion of legacy missile engines into space propulsion systems represents a strategic opportunity to accelerate Europe’s access to orbit while advancing sustainability and circular-economy goals. Rather than discarding decommissioned hardware, repurposing missile propulsion can reduce development timelines, retain valuable materials, and leverage proven architectures for new applications. This perspective outlines the potential of the Soviet-era Isayev S2.720 engine as a representative case, drawing on historical precedents of missile-to-launcher conversions worldwide. A three-pillar methodology is proposed to frame such efforts: (i) the adoption of cleaner propellants such as LOX–LCH₄ in place of toxic hypergolics; (ii) remanufacturing and upgrading of key subsystems through additive manufacturing, AI-assisted inspection, and digital twin modelling; and (iii) validation supported by dedicated testing, life-cycle assessment (LCA), and life-cycle costing (LCC). Beyond the technical aspects, the paper discusses retrofit applicability, cost considerations, and the role of standardization in enabling future certification. By positioning the S2.720 as a model, this study highlights the broader strategic value of adapting decommissioned propulsion systems for modern orbital use, providing insight into how Europe might integrate legacy assets into a more sustainable and resilient space transportation framework. Full article

Building renovation is widely recognised as a critical strategy for improving energy performance, reducing greenhouse gas emissions, and meeting decarbonisation targets. Although numerous studies have explored retrofit interventions, the existing literature tends to focus on either specific climates or particular building types, lacking a consolidated perspective that links interventions to both climatic context and typological characteristics. This study addresses this gap through a structured literature review of recent scientific publications, aiming to map and categorise climate-sensitive retrofit strategies across different building typologies. The methodological approach involves a qualitative synthesis of peer-reviewed studies, with interventions classified based on climate zone and building use. The results highlight the prevalence of envelope-related measures—such as thermal insulation and high-performance glazing—in residential and educational buildings, particularly in colder climates. Conversely, HVAC upgrades and passive solutions dominate in hot and mixed zones. The findings provide an evidence-based reference for stakeholders involved in designing renovation strategies, while also identifying the need for more context-aware, integrative frameworks that account for climate, building use, and socio-economic factors in retrofit decision-making. Full article

The residential building sector is a major contributor to global energy consumption and carbon emissions, making retrofit strategies essential for meeting climate targets. While many studies focus on reducing operational energy, few comprehensively evaluate the trade-offs between operational savings and the embodied carbon introduced by retrofit measures. This study addresses this gap by developing an integrated, novel scenario-based assessment framework that combines dynamic energy simulation and life cycle assessment (LCA) to quantify whole life carbon impacts. Applied to representative Irish housing typologies, the framework evaluates thirty retrofit scenarios across three intervention levels: original fabric, shallow retrofit, and deep retrofit incorporating multiple HVAC technologies and envelope upgrades. Results reveal that while deep retrofits deliver up to 80.2% operational carbon reductions, they also carry the highest embodied emissions. In contrast, shallow retrofits with high-efficiency air-source heat pumps offer near-comparable energy savings with significantly lower embodied impacts. Comparative analysis confirms that reducing heating setpoints has a greater effect on energy demand than increasing system efficiency, especially in low-performance buildings. Over a 25-year lifespan, shallow retrofits outperform deep retrofits in overall carbon efficiency, achieving up to 76% total emissions reduction versus 74% for deep scenarios. Also, as buildings approach near-zero energy standards, the embodied carbon share increases, highlighting the importance of LCA in design decision-making. This study provides a scalable, evidence-based methodology for evaluating retrofit options and offers practical guidance to engineers, researchers, and policymakers aiming to maximize carbon savings across residential building stocks. Full article

This study applies the Integrated Modification Methodology (IMM) to assess how morphology-driven, nature-based solutions reduce urban heat island (UHI) effects and flooding in Rio de Janeiro’s Cidade Nova. Multi-scale GIS diagnostics identify green continuity and vertical permeability as critical weaknesses. Simulations (Ladybug/Dragonfly) and hydrological modelling (rational method) quantify the intervention’s impact, including greening, material retrofits, and drainage upgrades. Results show a 38% increase in albedo, a 13% reduction in volumetric heat capacity, and a 30% drop in thermal conductivity. These changes reduce the peak UHI by 0.2 °C hourly, narrowing the urban–rural temperature gap to 3.5 °C (summer) and 4.3 °C (winter). Hydrologically, impervious cover decreases from 22% to 15%, permeable surfaces rise from 9% to 29%, and peak runoff volume drops by 27% (16,062 to 11,753 m³/h), mitigating flood risks. Green space expands from 7.8% to 21%, improving connectivity by 50% and improving park access. These findings demonstrate that IMM-guided interventions effectively enhance thermal and hydrological resilience in dense tropical cities, aligning with climate adaptation and the Sustainable Development Goals. Full article

Urban building energy retrofit (UBER) is a critical strategy for advancing the low-carbon and climate-resilience transformation of cities. The integration of machine learning (ML), data-driven clustering, and multi-objective optimization (MOO) is a key aspect of artificial intelligence (AI) that is transforming the process of retrofit decision-making. This integration enables the development of scalable, cost-effective, and robust solutions on an urban scale. This systematic review synthesizes recent advances in AI-driven MOO frameworks for UBER, focusing on how state-of-the-art methods can help to identify and prioritize retrofit targets, balance energy, cost, and environmental objectives, and develop transparent, stakeholder-oriented decision-making processes. Key advances highlighted in this review include the following: (1) the application of ML-based surrogate models for efficient evaluation of retrofit design alternatives; (2) data-driven clustering and classification to identify high-impact interventions across complex urban fabrics; (3) MOO algorithms that support trade-off analysis under real-world constraints; and (4) the emerging integration of explainable AI (XAI) for enhanced transparency and stakeholder engagement in retrofit planning. Representative case studies demonstrate the practical impact of these approaches in optimizing envelope upgrades, active system retrofits, and prioritization schemes. Notwithstanding these advancements, considerable challenges persist, encompassing data heterogeneity, the transferability of models across disparate urban contexts, fragmented digital toolchains, and the paucity of real-world validation of AI-based solutions. The subsequent discussion encompasses prospective research directions, with particular emphasis on the potential of deep learning (DL), spatiotemporal forecasting, generative models, and digital twins to further advance scalable and adaptive urban retrofit. Full article

Sustainability in the construction and building sector with the use of greener and more eco-friendly building materials can minimize carbon footprint, which is one of the prime goals of the twenty-first century. The use of natural fibers in ancient and traditional buildings and structures is not new, but in the last fifty years, only man-made fibers have predominantly occupied the market for structural retrofitting or upgrading. This research investigated the potential of utilizing natural fibers, particularly jute fiber products, to enhance masonry’s thermal and structural characteristics. The study meticulously investigated the utilization of materials such as jute net (with a mesh size of 2.5 cm × 1.25 cm), jute fiber diatons, and jute fiber composite mortar (with 1% jute fiber with respect to the dry mortar mass) in the context of masonry upgrading. The research evaluated the structural and thermal performance of these upgraded walls. Notably, the implementation of natural fiber textile-reinforced mortar (NFTRM) resulted in an astounding increase of over 500% in the load-bearing capacity of the walls, while simultaneously enhancing insulation by more than 36%. Furthermore, the study involved a meticulous analysis of crack patterns during in-plane cyclic testing utilizing the advanced Digital Image Correlation (DIC) tool. The upgraded/retrofitted wall exhibited a maximum crack width of approximately 7.84 mm, primarily along the diagonal region. Full article

Urban building energy prediction is a critical challenge for sustainable city planning and large-scale retrofit prioritization. However, traditional data-driven models struggle to capture real urban environments’ spatial and morphological complexity. In this study, we systematically benchmark a range of graph-based neural networks (GNNs)—including graph convolutional network (GCN), GraphSAGE, and several physics-informed graph attention network (GAT) variants—against conventional artificial neural network (ANN) baselines, using both shape coefficient and energy use intensity (EUI) stratification across three distinct residential districts. Extensive ablation and cross-district generalization experiments reveal that models explicitly incorporating interpretable physical edge features, such as inter-building distance and angular relation, achieve significantly improved prediction accuracy and robustness over standard approaches. Among all models, GraphSAGE demonstrates the best overall performance and generalization capability. At the same time, the effectiveness of specific GAT edge features is found to be district-dependent, reflecting variations in local morphology and spatial logic. Furthermore, explainability analysis shows that the integration of domain-relevant spatial features enhances model interpretability and provides actionable insight for urban retrofit and policy intervention. The results highlight the value of physics-informed GNNs (PINN) as a scalable, transferable, and transparent tool for urban energy modeling, supporting evidence-based decision making in the context of aging residential building upgrades and sustainable urban transformation. Full article

The retrofitting of legacy systems enables upgrades that extend the lifespan of outdated equipment, improve efficiency, and reduce environmental impacts. This manuscript builds on existing approaches to retrofitting legacy systems using Industry 4.0 technologies. Therefore, it explores how the proposed modernization envisions the transition from Industry 4.0 to Industry 5.0, which emphasizes human-centric approaches, sustainability, and resilience. Tools such as RAMI 4.0 (a reference architecture model for Industry 4.0), Lean Six Sigma (a methodology for process improvement), and Big Data analytics are highlighted throughout the text as essential for optimizing processes and ensuring alignment with global challenges, including resource efficiency and environmental sustainability. This work addresses both conceptual and technical aspects of system modernization. It provides a comprehensive framework for retrofitting systems and integrating advanced technologies such as digital twins. These efforts ensure that industries are prepared for the evolving demands of Industry 4.0 and beyond. Full article

Nearly zero-energy buildings (nZEBs) are central to global carbon reduction strategies, and Taiwan is actively promoting their adoption through building energy performance labeling, particularly in the retrofit of existing buildings. Under Taiwan’s nZEB framework, qualification requires both an A⁺ energy performance label and over 50% energy savings from retrofit technologies. This study proposes an integrated assessment framework for retrofitting small- to medium-sized office buildings into nZEBs, incorporating diagnostics, technical evaluation, policy alignment, and resource integration. A case study of a bank branch in Kaohsiung involved on-site energy monitoring and EnergyPlus V22.2 simulations to calibrate and assess the retrofit impacts. Lighting improvements and two HVAC scenarios—upgrading the existing fan coil unit (FCU) system and adopting a completely new variable refrigerant flow (VRF) system—were evaluated. The FCU and VRF scenarios reduced the energy use intensity from 141.3 to 82.9 and 72.9 kWh/m²·yr, respectively. Combined with rooftop photovoltaics and green power procurement, both scenarios met Taiwan’s nZEB criteria. The proposed framework demonstrates practical and scalable strategies for decarbonizing existing office buildings, supporting Taiwan’s 2050 net-zero target. Full article

This study explores modernization strategies for existing district heating (DH) networks to enhance their efficiency and sustainability, focusing on achieving net-zero emissions in urban heating systems. Building upon a literature review and expert interviews, we developed a strategic decision-support framework that outlines distinct strategies for retrofitting district heating grids and includes a portfolio analysis. This framework serves as a tool to guide DH operators and stakeholders in selecting well-founded modernization pathways by considering technical, economic, and social dimensions. The review identifies several promising measures, such as reducing operational temperatures at substations, implementing optimized substations, integrating renewable and waste heat sources, implementing thermal energy storage (TES), deploying smart metering and monitoring infrastructure, and expanding networks while addressing public concerns. Additionally, the review highlights the importance of stakeholder engagement and policy support in successfully implementing these strategies. The developed strategic decision-support framework helps practitioners select a tailored modernization strategy aligned with the local context. Furthermore, the findings show the necessity of adopting a comprehensive approach that combines technical upgrades with robust stakeholder involvement and supportive policy measures to facilitate the transition to sustainable urban heating solutions. For example, the development of decision-support tools enables stakeholders to systematically evaluate and select grid modernization strategies, directly helping to reduce transmission losses and lower greenhouse gas (GHG) emissions contributing to climate goals and enhancing energy security. Indeed, as shown in the reviewed literature, retrofitting high-temperature district heating networks with low-temperature distribution and integrating renewables can lead to near-complete decarbonization of the supplied heat. Additionally, integrating advanced digital technologies, such as smart grid systems, can enhance grid efficiency and enable a greater share of variable renewable energy thus supporting national decarbonization targets. Further investigation could point to the most determining context factors for best choices to improve the sustainability and efficiency of existing DH systems. Full article

Achieving both indoor environmental quality (IEQ) and energy efficiency in school buildings remains a challenge, particularly in older structures where renovation strategies often lack site-specific validation. This study evaluates the impact of energy retrofits on a 1970s primary school in France by integrating in situ measurements with a validated numerical model for forecasting energy demand and IEQ. Temperature, humidity, and CO₂ levels were recorded before and after renovations, which included insulation upgrades and an air handling unit replacement. Results indicate significant improvements in winter thermal comfort (PPD < 20%) with a reduced heating water temperature (65 °C to 55 °C) and stable indoor air quality (CO₂ < 800 ppm), without the need for window ventilation. Night-flushing ventilation proved effective in mitigating overheating by shifting peak temperatures outside school hours, contributing to enhanced thermal regulation. Long-term energy consumption analysis (2019–2022) revealed substantial reductions in gas and electricity use, 15% and 29% of energy saving for electricity and gas, supporting the effectiveness of the applied renovation strategies. However, summer overheating (up to 30 °C) persisted, particularly in south-facing upper floors with extensive glazing, underscoring the need for additional optimization in solar gain management and heating control. By providing empirical validation of renovation outcomes, this study bridges the gap between theoretical predictions and real-world effectiveness, offering a data-driven framework for enhancing IEQ and energy performance in aging school infrastructure. Full article

Decades of migration and refugee influxes have driven Amman’s rapid urban growth, yet newer neighborhoods increasingly grapple with fragmented social cohesion. This study examines whether walkable design can strengthen community bonds, focusing on Deir Ghbar, a car-centric district in West Amman. Using GIS and mixed-methods analysis, we assess how walkability metrics (residential density, street connectivity, land-use mix, and retail density) correlate with sense of community. The results reveal that street connectivity and residential density enhance social cohesion, while land-use mix exhibits no significant effect. High-density, compact neighborhoods foster neighborly interactions, but major roads disrupt these connections. A critical mismatch emerges between quantitative land-use metrics and resident experiences, highlighting the need to integrate spatial data with community insights. Amman’s zoning policies, particularly the stark contrast between affluent low-density Zones A/B and underserved high-density Zones C/D, perpetuate socio-spatial segregation—a central critique of this study. We urge the Greater Amman Municipality’s 2025 Master Plan to prioritize mixed-density zoning, pedestrian retrofits (e.g., traffic calming and sidewalk upgrades), and equitable access to amenities. This study provides a replicable GIS and survey-based framework to address urban socio-spatial divides, aligning with SDG 11 for inclusive cities. It advocates for mixed-density zoning and pedestrian-first interventions in Amman’s Master Plan. By integrating a GIS with social surveys, this study offers a replicable model for addressing socio-spatial divides in cities facing displacement and inequality. Full article

This study investigates the significant energy optimization gaps in hotel retrofits in a subtropical climate, quantifying the missed energy-saving opportunities through advanced simulation techniques. Utilizing Design Builder software, the energy consumption of a hotel in Cienfuegos (Cuba) was assessed both before and after renovation, focusing on passive strategies (e.g., replacing single-glazed windows with double glazing) and active interventions (e.g., upgrading the air conditioning system). The results reveal that current retrofit strategies fail to reduce energy consumption substantially. Replacing single-glazed windows with double glazing could reduce annual energy use by 42%. Additionally, upgrading the existing chiller system or implementing a Variable Refrigerant Flow (VRF) system could result in 40% and 59.5% energy savings, respectively. The most significant energy reduction, 71%, is achieved when both interventions—upgrading the chiller and installing double-glazed windows—are implemented, reducing the energy consumption index (ECI) to a quarter of its current value. The life cycle cost (LCC) analysis demonstrates that energy-efficient investments offer considerable economic returns. For instance, an investment of USD 508,600 in a modern chiller system would generate net savings of USD 1,373,500 over its operational lifespan. This study underscores substantial economic and environmental losses from omitting energy efficiency considerations in hotel renovations. It calls for integrating comprehensive energy optimization strategies in retrofit planning, with each dollar invested in energy-saving measures potentially yielding USD 2.5 in life cycle savings. This approach is crucial for global hotel markets facing energy challenges. Full article

This study presents a comprehensive review of various advanced methodologies that have been used to enhance the structural and thermal performance of masonry walls through innovative and sustainable retrofitting/upgrading techniques. Focusing on three primary approaches—mechanical/structural retrofitting, thermal retrofitting, and integrated (structural and thermal) retrofitting, this paper critically examines various masonry-strengthening strategies. Retrofitting techniques are categorized by material use and objectives. Fiber-based solutions include insulation materials, fiber composite mortar for strength, FRP for high-strength reinforcement, and TRM for durability. According to the relevant objectives, retrofitting can enhance structural stability (FRP, TRM), improve thermal insulation, or combine both for integrated performance. Particular emphasis is placed on the effectiveness of TRM systems, with a comparative analysis of man-made (glass, steel textile) and natural fiber-based TRM solutions. Regarding integrating natural fibers into TRM systems, this study highlights their potential as eco-friendly alternatives that reduce environmental impact while maintaining or improving structural integrity. Furthermore, it highlights and examines techniques for testing masonry walls. In this context, this review highlights the applicability of natural fiber as a sustainable building material in various retrofitting/upgrading solutions. Full article

Streets, as critical public space nexuses, require synergistic quality–utilization alignment—where quality without use signifies institutional inefficiency, and use without quality denotes operational ineffectiveness. Focusing on high-frequency pedestrian commuting streets (HFPCSs) that not only crucially mediate metropolitan mobility patterns but also shape citizens’ daily urban experiences and satisfaction, this study proposes a data-driven diagnostic framework for street quality–utilization assessment, integrating multi-source urban big data through a case study of Shenzhen. By integrating multi-source urban big data, we identify HFPCSs using LBS data and develop a multi-dimensional evaluation system that incorporates 1.07 million Points of Interest (POIs) for assessing convenience, utilizes DeepLabv3+ for the semantic segmentation of street view imagery to evaluate comfort, and leverages 15,374 km of road network data for accessibility analysis. The results expose dual mismatches: merely 2.15% of HFPCSs achieve balanced comfort–convenience–accessibility benchmarks, while over 70% of these are clustered in northern districts, exhibiting systematically inferior quality metrics across dimensions. Diagnostic analysis reveals specific planning and spatial configurations contributing to these disparities, informing targeted retrofitting strategies for priority street typologies. This approach establishes a replicable model for megacity street renewal, deploying supply–demand diagnostics to synchronize infrastructure upgrades with pedestrian flow realities. By bridging data insights with human-centric urban improvements, this framework demonstrates how smart city technologies can concretely address the quality–utilization paradox—advancing sustainable urbanism through evidence-based street transformations. Full article