This paper presents an experimental evaluation of the thermal performance of a wood–aluminum window installed in a timber building exposed to real climatic conditions. The assessment is based on long-term in situ measurements of heat flux and temperature variations. The aim of the research was to determine the thermal transmittance of individual parts of the window assembly, analyze their dynamic thermal behavior, and identify critical areas in terms of heat losses. The results revealed a spatially heterogeneous distribution of heat fluxes through the window structure. The center of the glazing achieved values close to the declared Ug parameter, whereas the edge regions of the glazing and the window frame exhibited a significant increase compared with the declared values. The time-dependent analysis confirmed a distinct diurnal cycle of heat flux and a phase shift between the glazing and frame components. Furthermore, it was demonstrated that the accuracy of local U-value determination is significantly affected by the magnitude of the temperature difference, with the stability and repeatability of the calculated U-values improved at higher ΔT values, particularly above approximately 10–15 K. The findings highlight the need for detailed, spatially resolved assessment of window structures and emphasize the importance of experimental verification of their thermal performance under real conditions.
Accurate prediction of retaining-pile displacement is important for deformation control during staged deep-excavation construction, where monitoring series often exhibit pronounced nonstationarity and multiscale temporal variation. To account for the distinct temporal characteristics of the trend and fluctuation components, this study proposes a CEEMDAN–SVR–PSO-LSTM hybrid framework, termed CSPL. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is first used to decompose the monitored displacement series into a slowly varying residual and oscillatory intrinsic mode functions (IMFs). Support vector regression (SVR) is employed to predict the trend component, whereas particle swarm optimization (PSO)-optimized long short-term memory (LSTM) is used to predict the fluctuation components. The component-wise predictions are then reconstructed to obtain the final displacement prediction. The proposed model is validated using monitoring data from two Zhengzhou Metro projects. For Case 1, the model achieves average R2, RMSE, and MAPE values of approximately 0.94, 0.33 mm, and 2.8%, respectively, across different monitoring depths, showing better overall predictive performance than BP, EMD-LSTM, and VMD-GRU. For Case 2, external validation using 90 depth-wise monitoring points over six construction stages yields millimeter-level errors, supporting stable predictive performance under different geological and support-system conditions. The results further indicate that the late construction stages and the upper pile segments deserve particular attention in deformation control. The proposed model provides a data-driven tool for construction-stage displacement prediction and deformation control in underground geotechnical engineering.
Moon and Mars mission architectures are shifting from short stays to longer surface stays in isolated, confined and extreme (ICE) conditions, where small crews live almost entirely inside pressurized habitats. As transit durations increase and lunar outposts evolve into more permanent bases, crews are exposed for longer periods to environmental hazards and non-terrestrial gravity that disrupt usual sensorimotor patterns. In this context, the habitat becomes the primary interface between human bodies and extreme environments, shaping how inhabitants perceive, move, orient themselves and sustain everyday routines away from Earth. This article develops a neuroarchitecture integrative model for indoor living in lunar and Martian habitats, treating space habitat resilience as a cognitive and experiential property of the human–habitat system. The model connects advances in space architecture and planetary science research with person–environment theories to show how interior form and indoor environmental quality (IEQ) influence attention, emotional regulation and social functioning under confinement. It distinguishes a macro scale, where planetary constraints compress human experience into Built Environments in Extreme Environments (BEXEs), from a micro scale, where habitability is organized into four functional clusters (somatic, operational, psychosocial and ludic-recreational). Conventional IEQ assessment addresses a small set of generic dimensions applicable to any building; here, these are reorganized into twelve cluster-specific dimensions, three per cluster, calibrated for confinement and for the absence of an accessible exterior. Focusing on room shape and proportions, degrees of enclosure and visual order as key interior variables, the model positions the habitat as an active co-regulator of cognition and argues for design agendas that move beyond minimum safety and volume standards toward evidence-informed cognitive habitability in emerging off-Earth settlements.
Built heritage environments are increasingly recognized as important components of the built environment that shape human experiences beyond their cultural and historical values. However, how heritage-related experiences are associated with restorative perceptions through cultural interpretations and human–place relationships remains insufficiently understood. This study examines the mechanisms underlying perceived restorativeness in built heritage environments by integrating heritage identity and place attachment. Using the built heritage of the Macao Peninsula as a case study, an exploratory sequential mixed-methods approach was adopted, combining large-scale social media semantic analysis with questionnaire-based structural modeling. Analysis of 23,838 user-generated reviews identified key dimensions of public experiences associated with heritage environments, which informed the development of the measurement framework. Survey data from 234 visitors were subsequently analyzed using structural equation modeling and mediation analysis. The results reveal that restorative experiences in built heritage environments are shaped through a cognitive–identity–place pathway. Cultural cognition is associated with heritage identity formation, which is further associated with place attachment and perceived restorativeness. Place identity plays a significant mediating role in linking heritage identity with restorative experiences. These findings highlight that the value of built heritage environments lies not only in their physical characteristics but also in the cultural meanings and emotional connections they foster. This study provides implications for heritage conservation, adaptive reuse, and human-centered design and management of historic environments.
Lean Construction (LC) has evolved from an emerging adaptation of production principles into a mature academic domain, yet a comprehensive assessment of its global structure and development remains needed. This study presents a rigorous bibliometric and scoping review of LC research using a sample of 484 highly refined, peer-reviewed documents retrieved from the Scopus database up to 2025. Following the PRISMA-ScR guidelines and utilizing VOSviewer, the co-occurrence networks of keywords, countries, and co-authorships were systematically analyzed. The results reveal a structurally centralized research landscape historically led by the United States and the United Kingdom, though accompanied by an increasing globalization driven by emerging clusters in Asia and South America. Keyword analysis indicates growing research attention to Building Information Modeling (BIM), information management, agile approaches, and environmental sustainability within the analyzed Lean Construction literature alongside traditional operational and planning concerns. However, the literature exhibits persistent fragmentation, with over 70% of identified journals publishing two or fewer articles on the subject within specialized thematic niches. This study concludes that opportunities exist to further explore the relationship between Lean Construction and emerging digital technologies while strengthening cross-regional and interdisciplinary collaborations. These efforts may contribute to a more cohesive and globally representative understanding of the discipline and its role in improving efficiency and sustainability within the built environment.
The building industry is the largest consumer of energy and the largest source of carbon emissions, and the sustainable development of building envelopes is thus inevitable. Among the facade systems, metal cladding materials offer a number of benefits such as high durability, architectural freedom, and recyclability; however, the choice of these materials needs to be based on several performance aspects. This research presents a novel comprehensive approach for analyzing metal cladding options in a health care building through the integration of building energy simulation and multi-attribute decision analysis (MADA) techniques. A primary health care facility in Istanbul, Türkiye, was used as a case example. Eight metal cladding materials—steel, aluminum, copper, zinc, titanium, stainless steel, Corten steel, and magnesium alloy—were evaluated against various wall and insulation combinations. The assessment combined energy with physical–mechanical, thermal, acoustic, and sustainability indicators such as density, thermal conductivity, Young’s modulus, damping capacity, traffic noise insulation, service life, and recyclability. A series of building energy simulations was performed to estimate the effect of facade design options on yearly energy consumption, and the resulting data set was analyzed based on the CRITIC, LOPCOW and ALPAS methods. This method allows the comprehensive evaluation of metal cladding material on energy efficiency, structural strength, acoustic performance, durability, and circularity simultaneously. The results provide a practical decision support framework for sustainable facade material selection in health care and other energy-intensive buildings. Titanium emerged as the optimal metal cladding material, distinguished by its superior combination of low thermal conductivity, damping capacity, and recyclability under both CRITIC and LOPCOW weighting schemes. Comparative analysis across nine MADA methods (ρ = 0.932) and sensitivity analysis over 70 scenarios confirmed the robustness of this finding, with titanium retaining first place in 64 out of 70 perturbation scenarios. These outcomes provide materials engineering insight into how the mechanical, thermal, and durability characteristics of structural metals and alloys translate into differentiated in-service performance, offering evidence-based guidance for metal selection in facade applications. The outcomes reported relate to one health care facility located in Istanbul and demonstrate the potential of the novel framework for the specific investigated case but are not intended to be generalized across all building types and climatic zones or to provide universally applicable material rankings.
Remote island buildings often operate under isolated environmental conditions where conventional water supply infrastructures are unavailable or unreliable. However, the lack of theoretical frameworks and integrated technologies for building-scale autonomous water supply remains a critical challenge in sustainable construction and resilient building development. Existing atmospheric water harvesting technologies mainly focus on material-level adsorption capacity or short-term water production performance, while systematic principles for integrating sorption materials, heat transfer structures, and renewable energy subsystems into autonomous building water systems remain insufficiently established. This study develops and validates an active, continuous atmospheric water harvesting (AWH) system utilizing MIL-101(Cr) coated on finned tubes. The system alternates cold water (25 °C) and hot water (50–70 °C during actual experiments; 50–80 °C in simulations) through the piping, allowing the two parallel modules to independently undergo adsorption and desorption phases-thereby breaking away from the traditional daily single-cycle mode. A coupled heat and mass transfer model is developed and validated using experimental measurements obtained from the MIL-101(Cr)-coated finned tube component, with root-mean-square deviations below 8.5% for all key parameters. Under simulated coastal island conditions (75–87% RH, 29–32 °C), the dual-module system achieves a water productivity up to 1.989 kg·m−2·day−1 at a desorption temperature of 80 °C, with cycling frequencies reaching 9 cycles per module over 48 h. Parametric analysis reveals that synergy between desorption temperature (50–80 °C) and desorption extent (50–80%) governs daily water yield, while the per-cycle adsorption capacity remains stable at ≈0.91 g/g. Energy and economic analysis shows that the auxiliary electricity required ranges from 0.38 (50 °C) to 6.36 kWh·m−3 (80 °C), with a preliminary levelized cost of water of 1.85–3.2 USD·m−3 competitive with conventional island supply methods.
Traditional dwellings in humid subtropical China contain climate-adaptive spatial elements, yet their outdoor thermal-comfort performance and passive optimization potential remain insufficiently quantified. This study examined three traditional Minnan mansions in Quanzhou, Fujian Province, to evaluate how courtyards, alleyways, recessed entrance spaces, and peripheral vegetation regulate summer outdoor thermal environments. Field microclimate monitoring, UAV photogrammetry, and ENVI-met/BioMet simulations were combined, and baseline models were validated using measured air temperature and relative humidity data. Single-element scenarios were developed for ground albedo adjustment, courtyard shading, alleyway green pergolas, recessed entrance shading, increased fengshui woodland density, and optimized woodland layout, followed by multi-element combined strategies. The results indicate that shading and vegetation-related measures reduced daytime heat stress primarily by limiting solar radiation exposure, improving near-ground thermal and humidity conditions, and modifying local wind fields. Combined strategies produced more stable UTCI improvements than individual interventions, with a maximum UTCI reduction of 7.5 °C. In contrast, high-albedo paving reduced local air temperature but could worsen UTCI by increasing reflected short-wave radiation. These findings provide quantitative support for low-intervention thermal environment optimization and climate-adaptive renewal of traditional dwellings in humid–hot regions.
Raw mix-design variables used to predict ultra-high-performance concrete (UHPC) properties cannot fully represent internal proportions and structural compatibility. This study develops mechanism-informed proxy-core features based on particle packing, water film thickness, and rheology, and evaluates four feature systems using literature-derived datasets for compressive strength (924 samples), flexural strength (406 samples), and slump flow (192 samples). Eight regression models were compared using five-fold cross-validation, Bayesian optimization, SHAP, and ablation analysis. Proxy-W achieved an R2 of 0.918 for compressive strength, only 0.005 higher than baseline-W on the original split. For flexural strength, baseline-WB achieved the highest R2 (0.906), whereas proxy-W yielded the lowest MAE (2.140 MPa). The largest single-split difference occurred for slump flow (R2: 0.740 to 0.838 for W-based systems), but 30 repeated splits yielded mean R2 values of 0.667 ± 0.169 and 0.738 ± 0.101 for baseline-W and proxy-W, respectively, while proxy-WB showed no average improvement over baseline-WB. Repeated and source-group validation further indicated that the predictive effects of proxy-core features were property-, representation-, partition-, and source-dependent. Overall, proxy-core features are best interpreted as physically informed relational representations rather than universally accuracy-enhancing features.
Designing new buildings in historical environments remains a critical challenge in balancing architectural innovation with the preservation of cultural heritage values. Four fundamental design approaches have been identified in the literature: imitation, emulation, respectful integration, and contrast. Despite extensive research on new architectural interventions in historical contexts, a conceptual gap remains regarding the relationship between architectural differentiation and contextual integration. This study addresses this gap by conceptualizing contrast not as the antithesis of contextual integration, but as a design strategy whose contribution can be evaluated across different dimensions of context. It investigates the conditions under which contrast can function as a context-responsive design strategy. A narrative literature review was conducted to thematically classify design approaches based on recurring concepts. The methodological contribution of the study lies in transforming a single case into a transferable analytical tool for theoretical testing. Qualitative evaluation techniques, including spatial, perceptual, and theoretical readings, were employed to assess the case against established criteria using architectural evidence such as plans, sections, elevations, and photographs. The analysis also considered the historical-cultural, social, and environmental dimensions of context. In this respect, the proposed model contributes to ongoing debates in architectural heritage conservation by offering an alternative evaluative tool for contemporary interventions in historic settings.
Meeting growing construction demand with materials that can be emissions-free in the near future is a critical part of decarbonisation, but given the finite nature of land and biomass, this requires careful planning of resources and land use. Straw is a promising example of this, since it is an agricultural co-product, can be used in load-bearing strawbale and prefabricated straw construction, avoids competition with arable land, and is compatible with zero-emissions production. However, the resource availability and implications of scaling-up the use of straw for construction in the UK have not been quantified. Here, we estimate the quantities of straw currently produced and used in different applications. Scenario and sensitivity analysis show that it is feasible to supply 300,000 low-rise dwellings with straw for load-bearing construction demand in the UK, meeting house-building targets with little impact on other sectors. UK straw supply and demand vary spatially and temporally, with surpluses in eastern regions and deficits in urban centres, alongside year-to-year production fluctuations. Even at the lower bound of these variations, the results indicate that the key limitation is not resource availability, but rather the need for improved supply chain coordination, certification and regulatory acceptance, greater economic efficiency of strawbale construction comparable to prefabricated systems, and alignment with land use and agricultural policy. This study provides a framework that can be applied to other materials to assess resource availability.
Archaeological sites with limited surface visibility and low spatial legibility often depend on presentation systems to communicate historical functions and heritage meaning. Using the Site of Xuanquan Posthouse as a case study, this study examined how visual attention and visitor perceptions jointly inform the interpretive effectiveness of such low-visibility archaeological sites. A complementary two-stage quantitative design was adopted. First, 20 adults viewed 12 static presentation images, and visual attention was compared across eight categories of information. Second, 252 valid questionnaires were analyzed using partial least squares structural equation modeling (PLS-SEM) and importance–performance map analysis (IPMA). Archaeological remains, reconstructed architecture or models, and digital media generally showed shorter time-to-first-fixation values and greater cumulative visual attention, whereas explanatory text, diagrams and maps, and bamboo and wooden slip documents were less visually prominent. Interpretation quality, perceived authenticity, and exhibition experience quality were all positively associated with perceived heritage understanding and perceived interpretation effectiveness, with heritage understanding playing a central mediating role. The findings indicate that effective presentation should connect visually prominent entry points with explanatory, spatial, and evidentiary information so that visitors can progress from recognizing physical remains to understanding their historical functions and heritage significance.
Automated personal protective equipment (PPE) monitoring can support construction-site safety, but practical deployment requires reproducible performance, reliable confidence estimates, and robustness across varying field acquisition conditions. This study evaluates a modular two-stage framework comprising YOLO26s person detection and MobileNetV3-based multi-label classification of six PPE attributes: helmets, high-visibility vests, gloves, safety boots, goggles, and face masks. The dataset contained 1807 construction-site images and 7580 person crops, partitioned by video recording to prevent temporal and location-based leakage. The same MobileNetV3 architecture was trained in three independent runs using different random seeds. Attribute-specific thresholds were selected on the validation set, and probability calibration was assessed using temperature scaling and Expected Calibration Error. On the test set, Average Precision was highest for vests (0.995) and boots (0.979), followed by gloves (0.908), helmets (0.892), goggles (0.715), and masks (0.695). Calibration improved substantially for boots and vests, slightly for goggles, negligibly for helmets, and unfavourably for gloves and masks. Distance effects were strongly attribute-dependent, with goggles degrading markedly at 30 m, while worker-density effects were non-monotonic. The findings demonstrate the importance of reproducibility, calibration, and operational robustness when evaluating construction-site PPE classifiers.
The construction sector contributes significantly to global carbon emissions, prompting a shift toward sustainable engineered timber. However, European hardwood species remain underutilised because current design standards are largely based on research conducted on softwood species. This paper outlines the fundamental principles for designing mechanical timber connections, specifically dowel-type fasteners, by reviewing the European Yield Model and fracture-mechanics approaches for ductile and brittle failure. Through a synthesis of recent experimental investigations on species like European beech, the work identifies critical gaps in current Eurocode 5 (EC5) provisions. The findings demonstrate that EC5 tends to underestimate the load-carrying capacity of many hardwood connections by 33% to 46% and does not explicitly account for brittle mechanisms such as splitting and row shear. Furthermore, the results highlight that connection performance may be significantly increased by factors like dowel-surface roughness, the “rope effect,” and specific assembly requirements such as precise predrilling diameters. This study concludes that existing design frameworks require calibration with hardwood-specific data and improved predictive models to differentiate failure modes. Such adjustments are essential to fully exploit the superior mechanical potential of hardwood species in modern timber construction.
Public geopolymer concrete (GPC) databases can support retrospective screening of records with lower reported CO2 emissions under strength constraints, but reliable ranking also requires correct response matching and stable threshold-based eligibility. Using 274 records, this study reconstructed the strength–CO2 correspondence from 19 mix proportion and preparation fields, yielding 273 mix design identifiers (MixIDs). Eight regression algorithms were evaluated under MixID-grouped validation, and CatBoost with derived descriptors was retained as the primary model. It achieved R2 = 0.969 and RMSE = 2.096 MPa on the fixed test set; across 30 repeated holdouts, mean RMSE was 2.390 ± 0.234 MPa. Because observed strength was available for every record, the model served as an internal consistency filter rather than a predictor of untested formulations. At 40, 50, and 60 MPa, 176, 65, and four records met the observed strength and mean prediction criteria, while 174, 62, and three records also satisfied the empirical fifth-percentile (Q05) criterion. Q05 was treated as a descriptive measure of partition sensitivity, and the 60 MPa result was regarded as exploratory. A CO2 assignment negative control showed weak agreement between row-wise and key-matched values (Pearson r = 0.065) and low Pareto-set overlap (Jaccard = 0.045–0.105). Thus, prediction accuracy alone does not ensure valid lower-CO2 ranking. The workflow provides an auditable basis for screening observed records within the database domain.
To address the limitations of conventional temporary steel platforms, a novel lightweight temporary steel platform (LTSP) system was developed based on an inland river high-pile wharf project. The proposed system utilizes permanent rock-socketed steel tubular piles of the wharf structure as the primary load-bearing foundation and consists of welded corbels, twin I-beam main girders, secondary I-section distribution beams, and steel deck plates. A construction method integrating permanent and temporary structural components was proposed. Field measurements were conducted to investigate the vibration response characteristics of the LTSP. The results indicate that the platform exhibits relatively high natural frequencies, with all identified fundamental frequencies exceeding 14 Hz, suggesting a low risk of resonance under human-induced excitations. The lateral stiffness of the platform was found to be greater than its vertical stiffness. Pedestrian-induced vibrations were mainly concentrated near excitation locations, whereas vehicle-induced vibrations were more uniformly distributed across the platform. The permanent steel tubular piles provided effective local restraint and enhanced structural stiffness, thereby reducing vibration transmission to adjacent areas. Construction machinery generated the most significant vibration responses, particularly during simultaneous multi-equipment operations. Therefore, to ensure the safety and operational performance of the temporary steel platform, it is recommended to avoid the simultaneous operation of heavy equipment, such as rotary drilling rigs, fully loaded tanker trucks, and truck cranes. Furthermore, as the current findings are based on a single field application case, future studies should incorporate long-term monitoring and numerical modeling to further evaluate the platform’s applicability to other practical engineering projects.
This study develops a probabilistic carbon-aware optimization framework for residential 24/7 carbon-free electricity (CFE) under uncertain load, PV generation and dynamic grid carbon intensity. Historical half-hourly monitoring data are represented through KDE-Copula scenario generation, while grid carbon factors are described by time-series decomposition and ARMA-based residual scenarios. A two-stage mixed-integer linear program jointly sizes and dispatches battery energy storage (BESS) and thermal energy storage (TES) by minimizing annualized lifecycle CO2 emissions. The results show that coordinated BESS–TES operation improves PV utilization and avoids carbon-intensive grid imports, especially in winter. In the examined capacity range, increasing BESS capacity from 0 to 100 kWh reduces annual lifecycle emissions from approximately 8600 to 6000 kg CO2 yr−1, corresponding to about a 30% reduction, whereas the marginal benefit of additional TES is constrained by DHW demand and its embodied emissions. Electrical storage is therefore the principal carbon-shifting resource, while a moderately sized TES complements it by moving heat-pump operation toward low-carbon and PV-rich periods. The framework provides a practical basis for carbon-aware design of residential electrification systems.
Heating, ventilation and air conditioning (HVAC) accounts for an overwhelmingly large proportion of building energy consumption. Mass low-grade cold and heat energy dissipates during system operation, endowing pulsating heat pipes (PHPs) with promising application prospects in building energy systems. Combining experimental tests and the phase-space reconstruction method, this paper investigates the intrinsic correlation between the flow behavior of working fluids and chaotic characteristics under varied working fluids, heating powers and liquid filling ratios. The working fluid type dominates the oscillation characteristics of pulsating heat pipes. When distilled water serves as the working fluid, the attractor presents a scattered distribution. In contrast, the PHP charged with HFE-7100 achieves stable unidirectional circulation with high-frequency, small-amplitude pulsation, forming a densely distributed attractor. Increasing the flow velocity of the working fluid drives the attractor distribution to evolve from scattered to concentrated. Intermittent flow of the working fluid induces a multi-temperature-zone distribution on the tube wall, and the attractor takes on a multi-region spiral morphology. A low liquid filling ratio triggers working fluid dry-out, and the attractor trajectory maintains a continuous unidirectional upward trend; by comparison, the attractor shows a multi-region spiral distribution under high filling ratio conditions. Research on chaotic dynamic characteristic identification, evolutionary law analysis and stable domain regulation of pulsating heat pipes can lay a theoretical foundation for structural optimization and operating condition adjustment of high-performance pulsating heat pipe devices for building waste heat recovery.
Subsurface thermo-hydro-mechanical (THM) coupled processes are fundamental to geomechanics, yet conventional mesh-based methods face high computational costs and limited efficiency in strongly nonlinear simulations and inverse problems. This review examines two representative physics-informed machine learning paradigms for THM modeling: physics-informed neural networks (PINNs) and neural operators (NOs). Relevant studies were identified through iterative keyword-based searches and citation tracking and were comparatively analyzed in terms of physical embedding, data dependence, computational efficiency, inverse capability, generalization, and engineering applications. The analysis shows that PINNs are well suited to physics-constrained simulation and parameter inversion from sparse data but are limited by training instability and loss imbalance. NOs enable rapid repeated forward predictions but depend strongly on representative training data and may perform poorly under out-of-distribution conditions. This review clarifies the complementary roles, trade-offs, and application boundaries of PINNs and NOs and highlights their hybrid integration as a promising route toward efficient and physically consistent subsurface THM simulation.
This article presents laboratory experiments examining the potential benefits of the synergistic effects of ground granulated blast furnace slag (GGBS) and metakaolin (MK) on lime (L) stabilisation of synthetic sulfate-bearing soil. The different soil–binder mixtures considered in this study were prepared by partially replacing lime with GGBS, metakaolin, or a combination of both, at substitution levels ranging from 25% to 75% by mass. The engineering performance of the mixtures was characterised through physico-mechanical analyses (unconfined compressive strength and linear expansion) and microstructural analyses (X-ray diffraction and scanning electron microscopy). Among the binary binders examined in this study, the GGBS-rich binder demonstrated the highest strength, while the metakaolin-rich binder exhibited the lowest swelling behaviour. This difference in performance was balanced by the ternary L–GGBS–MK blend, particularly at a blending ratio of 5L–12.5GGBS–2.5MK. This optimal blend produced a near-zero linear expansion of 0.04%, with only a negligible reduction in strength compared with the binary blend 5L–15GGBS. By replacing a substantial proportion of lime with industrial by-products, the proposed stabilisation strategy reduces reliance on high-carbon conventional binders, supporting the development of green, low-carbon, and resource-efficient construction materials. The findings demonstrate the potential of circular material utilisation to mitigate sulfate-induced heaving while enhancing the durability and sustainability of ground improvement practices. This innovative approach addresses geo-environmental challenges associated with lime stabilisation and aligns with the broader transition towards net-zero construction, promoting the beneficial reuse of industrial by-products, reducing embodied carbon, conserving natural resources, and advancing environmentally responsible geotechnical engineering solutions for sustainable infrastructure development.
