Search Results (3,311)

Improving the thermal, daylighting, and energy performance of rural dwellings in cold regions is important for low-carbon rural construction. This study evaluated a composite on-top sunspace roof window (OSRW) for narrow-deep Guanzhong rural dwellings in Shaanxi Province, China. A field-informed benchmark model, supported by field surveys and short-term hygrothermal measurements, was simulated using an EnergyPlus–Radiance framework within Rhino–Grasshopper. Performance was assessed using useful daylight illuminance (UDI_100–2000), PMV-based annual comfort hours, and annual total load. Single-variable parametric simulations, feasibility-band screening, and a combined-variable consistency check were used to identify practical design ranges. The recommended configuration included a side roof WRR of 0.7–0.8, central roof WRR of 0.5–0.7, OSRW cavity height of 0.4–0.8 m, story height of 3.2–3.6 m, south facade WWR of 0.3, and R-type inner-window configuration. In the combined-variable check, annual load reductions remained positive across all retained cases (10.97–65.37%), UDI generally improved (mean 4.46%), and thermal comfort showed clearer trade-offs (−9.58–6.70%), mainly controlled by side roof WRR. These findings provide construction-oriented OSRW parameter guidance for similar narrow-deep Guanzhong rural dwellings under comparable benchmark, weather, and operational-control assumptions. Full article

Artificial intelligence (AI) offers new opportunities for evidence retrieval, data interpretation, experimentation, feedback, and evidence-based problem solving in engineering education. This study developed a theoretically grounded “One Core, Two Channels, and Four-Dimensional Drivers” model to align AI, research-informed teaching, and New Agricultural Science within an undergraduate Building Materials course, and examined preliminary between-cohort outcome differences. A 32-teaching-hour nonequivalent comparison-group study involving 123 students was conducted. The intervention integrated research-informed cases, rural and green-construction contexts, purpose-specific AI-supported tasks, laboratory work, staged projects, and multidimensional assessment. The intervention cohort scored higher on the final examination (mean difference 8.00 points; Hedges’ g = 1.19), experimental grade (4.67; g = 1.28), continuous-assessment score (35.56; g = 3.34), and course evaluation (1.63 on a 70-point scale; g = 0.58). Project innovation data were highly sparse. The continuous-assessment difference should not be interpreted as a standalone AI literacy effect because structured AI-learning opportunities differed by condition, and equivalence of non-examination scoring was not independently established. Given nonrandomized allocation, the absence of participant-level baseline measures, and unequal measurement strength across outcomes, the findings represent preliminary between-cohort evidence rather than causal treatment effects. Full article

This paper presents the design and development of a laboratory-scale 3D printing platform intended for research on sustainable construction materials. The growing interest in low-carbon and locally available materials, including clay, geopolymers, recycled aggregates, and bio-based composites, has increased the need for flexible experimental printing systems. However, most existing construction 3D printers are designed for industrial applications and remain costly, bulky, or limited to specific material categories. The proposed platform was developed using a Model-Based Systems Engineering approach in order to structure the design process and establish links between user needs, system requirements, functions, and physical components. The platform is based on modular Cartesian architecture and includes interchangeable extrusion systems. A syringe extruder is used for relatively fluid materials such as clay slurries, ceramic pastes, gypsum-based mixtures, and fluid geopolymers, while a screw extruder is designed for more viscous materials such as mortars, cement-based mixtures, and dense geopolymer pastes. The system also integrates motion-control components, material feeding devices, monitoring elements, and safety functions to ensure stable and repeatable printing conditions. The platform is intended to support the evaluation of printability, material flow, layer deposition, dimensional stability, and interlayer bonding. By combining a flexible hardware configuration with an MBSE-based design methodology, the proposed system provides a practical research tool for the development and validation of sustainable construction materials. It also creates opportunities for future work on multi-material printing, automated process control, and digital manufacturing applications. Full article

Improving the separation efficiency between methyldichlorosilane (CH₃SiHCl₂) and trichlorosilane (SiHCl₃) is one of the key urgent problems to be solved for the quality improvement and consumption reduction in high-purity polysilicon. In this work, three types of porous supported catalysts were prepared via an in situ reaction method, taking aluminum chloride (AlCl₃) as the active component and activated carbon, silica gel and activated alumina as support; the catalytic reaction mechanisms of CH₃SiHCl₂ and silicon tetrachloride (SiCl₄) over the as-prepared porous supported catalysts were investigated, based on density functional theory (DFT). The results reveal that among the three supported catalysts, the activated carbon-supported aluminum chloride catalyst (C@AlCl₃) possesses the maximum binding energy (−3.20 eV) between the active component and support. CH₃SiHCl₂ and SiCl₄ possess the lowest co-adsorption energy (−1.8 eV) and the minimum reaction energy barrier (0.8 eV) on C@AlCl₃, accompanied by the maximum charge transfer to the catalyst surface (−2.65 e and −2.80 e), thus exhibiting the highest catalytic activity, with the maximum single-pass conversion of CH₃SiHCl₂ exceeding 90%. This work provides material basis and theoretical guidance for constructing a reactive distillation strategy for high-efficiency and low-energy separation of CH₃SiHCl₂ from SiHCl₃. Full article

Urban form profoundly influences the effectiveness of coordinated management of carbon emissions and air pollution, which is of great significance for sustainable urban development. This study took 336 Chinese cities as research samples and used carbon emissions, PM_2.5, and nighttime light datasets from 2000 to 2020 to investigate the contribution of urban form to the degree of coordination between urban carbon emissions and PM_2.5. We constructed a multi-dimensional indicator system for urban form and adopted the coupling coordination degree (CCD) model to quantify the coordinated development of these two variables. A novel analytical framework was established using the stacking ensemble learning model. Combined with the SHAP method, this framework provided nonlinear associations of various urban morphological factors with the CCD. The results are as follows: (1) The stacking ensemble model performs best in capturing high-dimensional nonlinear relationships, with test set R², RMSE, and RPD values of 0.75, 0.082, and 1.98, respectively. (2) Urban form exhibits nonlinear threshold effects on the carbon-pollution coordination degree. The top predictors contributing to the model output are the class area (CA), the landscape shape index (LSI), the percentage of like adjacencies (PLADJ), and the number of patches (NP). Among them, CA exhibits a monotonically increasing asymptotic saturation response, while the LSI presents an inverted U-shaped response. (3) The contribution of urban form to the CCD exhibits significant spatial heterogeneity. The developed regions of eastern China constitute the high-sensitivity zone of the CCD, and are mainly constrained by scale expansion, land fragmentation, and excessive agglomeration, while the central and western regions show the low-sensitivity zone of the CCD. These results offer a scientific reference for designing pollution control and carbon mitigation strategies. Full article

Background: Corporate energy transition can create efficiency, financing, and valuation benefits, but it also exposes firms to implementation, information, and transition risks. This study examines whether digital transformation helps firms convert energy-transition strategies into financial value. Unlike prior studies that mainly treated digitalization or sustainability as broad direct predictors, this study examines an implementation-based, multidimensional digital capability as a boundary condition across three distinct energy-transition strategies and both accounting- and market-based financial outcomes. Methods: Using an unbalanced panel of 30 firms associated with Indonesia’s LQ45 Low Carbon Leaders Index (120 firm years, 2020–2025), we construct a 30-item implementation-based Digital Transformation Index and estimate two-way fixed-effects models with firm-level wild-cluster-bootstrap inference, conditional marginal effects, false-discovery-rate adjustment, and prespecified robustness checks. Results: Clean energy use is positively associated with return on assets, return on equity, and Tobin’s Q. Low-carbon operational efficiency is most clearly associated with return on assets, whereas renewable energy use is primarily reflected in Tobin’s Q. Digital transformation is positively associated with all three outcomes and selectively strengthens the financial effects of the three transition strategies. Conclusions: Digital transformation is not a universal performance amplifier. It functions as a strategy- and outcome-specific value-conversion and risk-management capability that improves the monitoring, coordination, financing, verification, and communication of energy-transition investments. Full article

Corporate net-zero pledges have proliferated across the Middle East, yet whether capital markets distinguish credible decarbonization strategies from symbolic ones remains unexamined in energy-exporting emerging markets, a gap this study addresses. This omission matters because the six Gulf Cooperation Council (GCC) economies in our sample face acute stranded-asset exposure amid national diversification programmes such as Saudi Arabia’s Vision 2030 and the UAE’s Operation 300bn. We test whether net-zero credibility is associated with firm valuation among 167 listed firms across seven Middle Eastern countries (2020–2025, 1002 firm-year observations), constructing a five-dimension Credibility Index (pathway specificity, capex alignment, verification, policy compliance, and track record) and applying event-study, pooled panel regression, mediation, moderation, and firm/year fixed-effects analysis. The index is internally consistent (Cronbach’s α = 0.92) and its estimated valuation association is invariant to equal, alternative and leave-one-out weighting schemes. Credibility is positively associated with all four valuation multiples (p < 0.001, firm-clustered standard errors); a one-standard-deviation increase corresponds to a 0.133 increase in Tobin’s Q (95% CI [0.116, 0.149]). High-credibility announcements earn cumulative abnormal returns 5.95 percentage points above low-credibility announcements over (−5, +5) trading days (95% CI [4.79, 7.11]), a gap robust to nonparametric tests, placebo dates and strictly pre-announcement credibility scoring. The association survives firm and year fixed effects (within-firm β = 0.119 per SD, p < 0.001). No moderator—foreign ESG fund, domestic institutional or sovereign wealth fund ownership, regulatory stringency, carbon intensity or financial health—reaches significance after correction for multiple testing, so we find no evidence of investor-type or jurisdictional heterogeneity in this sample. To the authors’ knowledge, this is the first Middle East-calibrated, capex-verified credibility index and the first evidence on the pricing of transition authenticity across GCC markets and Egypt, informing regulators, boards, and ESG investors. Full article

The Monolithic Precast Concrete Shear Wall System (MPCSWS) has become an important structural form for industrialized and sustainable construction, but its broader application is still constrained by the reliability, seismic behavior, and long-term performance of connection regions. Existing studies are abundant but remain insufficiently systematized, especially regarding the relationship among technological evolution, code-based design requirements, and engineering applicability. This review systematically examines MPCSWS connection technologies using literature retrieved from the Web of Science database and analyzed through bibliometric mapping, regulatory comparison, and engineering-oriented synthesis. Wet, dry, and hybrid connections are classified and compared in terms of load-transfer mechanisms, seismic performance, failure modes, durability concerns, and practical limitations. The review shows that wet connections remain the most mature route for achieving emulative cast-in-place behavior, whereas dry and hybrid systems provide advantages in constructability, inspectability, damage control, and potential repairability. However, unified performance evaluation criteria, durability-informed seismic assessment, and full-scale validation remain insufficient. This review provides a structured knowledge framework for MPCSWS connection technologies and discusses potential future developments in resilience-based design, intelligent monitoring, low-carbon materials, and system-level verification. Full article

High renewable energy penetration and surging electrical demand challenge the operation of integrated electricity–gas systems (IEGS) due to source and load uncertainties. This paper proposes a multi-objective optimal scheduling framework that harnesses flexible resources within the IEGS to balance economic, environmental, and energy efficiency goals. First, a liquid storage tank is introduced to reform the traditional carbon capture, utilization, and storage system. Additionally, a hydrogen energy multi-utilization structure—integrating two-stage power-to-gas, hydrogen fuel cells, and hydrogen storage—is developed to improve operational flexibility under renewable fluctuations and carbon constraints. Second, electric vehicles (EVs) schedulability is quantitatively evaluated across different charging scenarios, defining carbon quotas and profit calculation methods to incentivize EV participation. To address source-load uncertainties, a two-stage robust optimization model utilizing a box uncertainty set and budget constraints is constructed to secure the optimal scheduling solution under worst-case scenarios. Finally, by introducing penalty factors for carbon emissions and energy loss, the multi-objective function is transformed into a single-objective problem to minimize operation costs, emissions, and energy wastage. The results show that the coupled CCUS–HEMU configuration reduces the total and environmental costs by 15.50% and 77.13%. Under the worst-case source–load scenario, bidirectional EV charging further reduces the total cost by 22.10%, increases renewable-energy utilization from 87.34% to 94.34%, and decreases load fluctuation and the maximum peak–valley difference by 68.95% and 14.85%, respectively, thereby enhancing the system’s low-carbon flexibility and robustness against operational uncertainties. Full article

The need to enhance both the mechanical and the thermal insulation performance of alkali-activated mortars has stimulated interest in natural fiber-based reinforcement strategies, particularly for sustainability-driven design and low-carbon construction. This study explores the combined effect of natural kapok fiber, petroleum coke (PC) and waste tire rubber powder (WTRP) on the mechanical, thermal, microstructural, mineralogical, and pore structure characteristics of alkali-activated slag-based mortars. While the beneficial effects of each of these bio-based and waste-derived materials have been widely reported, little attention has been paid to their combined use and the potential for them to work together in a way that is more effective than the sum of their parts. For this purpose, 20 different mortar mixtures were produced, incorporating kapok fibers at ratios of 0%, 0.5%, 0.75% and 1%. The beneficial effect of WTRP was investigated for the case of a 3% cement additive where natural sand was substituted by PC at ratios of 0%, 10% and 20%. The results indicated that the synergistic interaction enabled the development of a sustainable mortar with enhanced thermal insulation performance of up to 37% while maintaining flexural performance compared to the control case. Microstructural, mineralogical, pore structure and thermal analyses revealed that the bio-based and waste-derived contents significantly influenced the pore network, phase evolution and fiber–matrix interactions. Overall, the results highlight the potential of the proposed sustainable material system to produce mortars with enhanced thermal insulation, sufficient mechanical performance, and lowered environmental footprint. Full article

The cement industry accounts for approximately 7% of global anthropogenic CO₂ emissions, making clinker reduction, alternative binders, and carbon use and capture technologies essential mitigation strategies. However, decarbonization based on the replacement of clinkers with supplementary cementitious materials or alternative binders generally adjusts the materials’ physicochemical properties and reactivity. As these actions may have implications for durability and performance throughout the life cycle, this paper presents a systematic review, based on the Methodi Ordinatio approach, of studies published in the last decade in indexed databases that examine the relationship between low-emission cements, durability, and service life. Of 48 selected articles, most focused on quantifying CO₂ avoidance through clinker reduction, without comprehensively addressing the use phase. When present in the literature, durability is found in studies of chloride penetration and carbonation resistance. However, no integrative chain studies or long-term studies focused on the durability of less emissive cement-based materials were identified. Across the reviewed studies, durability was mainly associated with changes in pore structure, hydration products, transport properties, and matrix alkalinity. Fine and reactive additions may promote pore refinement and restrict the ingress of aggressive agents, whereas extensive clinker replacement and portlandite consumption may reduce the alkaline reserve and increase carbonation susceptibility. However, these relationships are strongly dependent on binder composition, replacement level, and curing conditions, and were rarely evaluated together over sufficiently long periods. Full article

During the floating transportation and installation of immersed tube tunnels, the mechanical stability of the mooring system is a key factor governing construction safety. Current conditions and mooring-line arrangements are two major factors controlling the magnitude and distribution of mooring-line tensions. However, their coupled effects and the applicability of different calculation methods remain insufficiently understood. Based on a large-cross-section immersed tube tunnel project, this study employed a semi-empirical method specified in the Chinese Code for Loads on Port Engineering and a three-dimensional floating-body-mooring numerical model established in ANSYS AQWA. Multiple combinations of current velocity and direction were considered to compare the mooring-line responses under five typical arrangements corresponding to different construction stages. The effects of current conditions and mooring configurations on the magnitude, distribution, and transfer of mooring-line loads were systematically examined. The results show that current velocity is the dominant factor controlling the magnitude of mooring-line tensions, which generally increase with the square of the current velocity. Changes in current direction directly alter the principal load-bearing mooring-line group, and a current velocity of 1.5 m/s during the falling tide represents the most unfavorable current condition throughout the construction process. The mooring-line arrangement governs the spatial distribution and concentration of the line loads. During the floating transportation and mooring stages with multi-line constraints, the maximum mooring-line tensions calculated using China’s code-based method are 18.5–25.2% higher than those obtained from the numerical simulations, indicating relatively conservative predictions. In contrast, during stages with weakened constraints, such as line release and positioning in the foundation trench, the numerical model captures more pronounced local load concentration, yielding maximum tensions 19.4–28.8% higher than those predicted by the code-based method. Across all operating conditions, the maximum mooring-line tensions calculated by the code-based method and numerical model are 924 and 750 kN, respectively. This study clarifies the coupled effects of current conditions and mooring-line arrangements on mooring-load transfer and identifies the applicable scenarios of the two calculation methods. The findings provide a quantitative basis for calculation-method selection, mooring-force assessment, and construction-safety management during immersed tube tunnel installation. Full article

The modern energy transition has outpaced the control and optimization frameworks built to govern it. As power and energy systems fragment into webs of renewable generators, storage operators, flexible loads, and carbon-constrained firms, the deterministic, single-optimizer models that once sufficed buckle against nonlinearity, bounded rationality, and strategic conflict among parties who learn and revise as they go. Evolutionary game theory (EGT), which traces how strategies propagate through populations by imitation and selection rather than instantaneous optimization, offers a route through this difficulty—one this review develops across three scales of low-carbon coordination central to cleaner production: enterprise-level industrial symbiosis, system-level smart energy operation, and market-level carbon governance. We synthesize three decades of theory alongside the recent fusion of EGT with artificial intelligence, where deep reinforcement learning approximates high-dimensional payoffs, federated learning lets rival firms co-train models without surrendering proprietary data, and blockchain underwrites decentralized mechanism execution. The synthesis is accompanied by two illustrative numerical case studies, constructed for this review rather than drawn from the surveyed literature, whose quantitative outputs are reported below as demonstrations of modeled behavior rather than as empirical measurements. In the first of these, cooperative emergence in industrial symbiosis hinges on critical thresholds that travel from 0.15 to 0.75 as subsidies and transaction costs vary, with anchor-enterprise targeting accelerating cooperation 2.4-fold while cutting outcome variance 3-fold. In smart energy coordination, AI-enhanced learning buys 32 to 41% faster convergence, yet pays 25 to 39% larger oscillations—a speed–stability tension whose resolution lives in a narrow learning-rate band near 0.08 to 0.12, outside which either sluggishness or instability takes hold. Carbon-market behavior turns on price thresholds: emitters switch abruptly from buying quotas toward investing in abatement once the clearing price clears firm-specific triggers, a discrete state switch that smooth equilibrium analysis misses entirely. Across all three domains, fragmented data, path dependence, and regime-switching dynamics recur as the binding constraints on modeling and on governance alike. Four mechanisms prove invariant to scale—the decisive weight of initial conditions, the catalytic leverage of well-positioned anchor agents, the equilibrium-shaping force of institutional design, and the computational reach added by AI integration—which suggests that insight earned in one domain transfers to the others. We close by mapping open problems in heterogeneity modeling, verification under deep uncertainty, and the still-unrealized coupling of digital twins with privacy-preserving learning. EGT emerges not as retrospective description but as prospective guidance for the cooperative transitions on which credible decarbonization depends. Full article

Yellow River sediment is a promising resource for use in construction materials. However, the effects of Yellow River silt and sand in different applications remain unclear. This review examines the physicochemical properties of these two forms, their engineering applications, and the underlying mechanisms governing material performance. Yellow River sand is mainly used as a fine aggregate in conventional concrete, engineered cementitious composites (ECC), and cement mortar, whereas Yellow River silt is commonly used in subgrade fills, concretes incorporating multiple solid wastes, and building products. Across these applications, the behavior of Yellow River sediment in construction materials reflects both physical packing and chemical reactivity. Their relative contributions depend on sediment form, material system, processing condition, and sediment content. Chemical reactivity is observed mainly in systems containing Yellow River silt, although the contribution of the silt itself has not been isolated. In conventional concrete, the highest compressive strengths are generally observed when Yellow River sand replaces 10–30% of natural sand, but the exact level depends on mixture design. Regional differences in sediment composition further limit the direct transfer of this range and require evaluation based on target performance. Future research should develop predictive models linking sediment characteristics, content, and target performance, establish low-carbon activation methods, and clarify long-term durability under complex service conditions. Full article

Hybridizing concentrated solar power (CSP) with residual biomass allows supercritical CO₂ (sCO₂) power cycles to deliver dispatchable low-carbon electricity, but it is unclear whether the extra equipment of the more efficient layouts adds a life-cycle burden that offsets their thermodynamic gain. This work reports what is, to the authors’ knowledge, the first unified energy, exergy, environmental and exergoenvironmental comparison of two combined sCO₂–organic Rankine cycle (ORC) configurations—a simple and a recompression Brayton layout, both with reheating, regeneration and a toluene bottoming ORC—driven by a solar tower and a coconut-shell-biomass furnace. Life-cycle impacts are quantified with Eco-indicator 99, a damage-oriented method that scores construction, operation and decommissioning damage in milli-points (mPts), and are allocated to the exergy streams through the exergoenvironmental balance. Both cycles are modelled in Python with CoolProp properties and validated against published sCO₂ analyses (efficiency deviation below 7.3%). The recompression layout reaches 54.3% thermal and 32.0% second-law efficiency and cuts the exergy destruction from 173 to 128 kW. Its larger construction impact (22.6 vs. 20.1 mPts/h) is negligible against the shared biomass reheater (429.4 mPts/h), so it is also marginally cleaner overall (459 vs. 472 mPts/h). Efficiency-oriented layout selection is therefore environmentally safe, and the remaining leverage lies in the biomass supply chain. Full article