Search Results (22,670)

A dam deformation prediction method based on interpretable component decomposition and integration is proposed to address the problems of weak interpretability, difficult identification of key factors, and insufficient accuracy in the prediction model of deformation monitoring values of concrete dams due to multiple factors such as environmental loads and time factors. This method first strips the temporal component from the original sequence to obtain the castration sequence. Furthermore, complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose and reconstruct it into environmental load components and residual terms. In the process of deformation prediction, based on the characteristics of each deformation component, logarithmic functions, bidirectional long short-term memory (BiLSTM) networks optimized by The Black-Winged Kite Algorithm (BKA), and cloud models are used to fit and predict the temporal components, environmental load components, and residual terms, and the final prediction results are obtained through integration. At the same time, the SHAP (SHapley Additive exPlanations) method is introduced to quantify the contribution of input factors to enhance the interpretability of the model. Case study shows that the model outperforms the comparison model in both prediction accuracy and trend tracking ability, effectively improving the reliability of prediction results and significantly increasing the interpretability of deformation prediction, providing a more reliable analysis technique for dam deformation safety monitoring. Full article

To address the challenges of complex wiring, limited external power supply, and difficult maintenance in temperature monitoring during the construction of mass concrete, this study proposes a formwork-integrated self-powered temperature monitoring system based on hydration heat recovery. The system incorporates temperature sensing, thermal energy harvesting, energy storage and management, and wireless data transmission. Its heat-transfer performance, power-generation capability, and operational reliability are evaluated through experimental testing and seasonal condition analysis. The results show that interface optimization can substantially improve heat-transfer efficiency, enabling stable power generation and system operation even under low temperature-gradient conditions. The system exhibits a considerable energy surplus in summer and autumn, satisfies monitoring demands in spring, and is capable of achieving energy-neutral operation even in winter. Without requiring embedment within the concrete or reliance on an external power supply, the proposed system offers a convenient and efficient new solution for temperature monitoring during construction. Full article

Early-age shrinkage is a critical factor governing the dimensional stability and cracking susceptibility of ultra-high-performance concrete (UHPC). However, accurate prediction of UHPC shrinkage remains challenging due to the strong nonlinear interactions among mixture parameters, curing conditions, and hydration-induced internal moisture evolution, particularly when only limited experimental data are available. In this study, a systematic experimental program was conducted to investigate the influence of the binder-to-sand ratio, water-to-binder ratio, polypropylene fiber dosage, and curing environment on both early drying shrinkage and autogenous shrinkage of UHPC. Based on the experimental results, a structured dataset covering all shrinkage test data was constructed to support data-driven modeling. To improve prediction reliability under small-sample conditions, a Bayesian-optimized Extreme Gradient Boosting (BO-XGBoost) framework was developed and benchmarked against several conventional machine learning models, including Backpropagation Neural Networks (BPNNs), Random Forest (RF), and Support Vector Machines (SVMs). Shrinkage test data from other literature validated the prediction accuracy of this model, demonstrating its rationality and practicality. In addition, the Shapley Additive Explanations (SHAP) method was employed to quantitatively interpret the contribution and interaction mechanisms of key variables affecting shrinkage behavior. The results show that the BO-XGBoost model achieves the highest prediction accuracy and stability among the evaluated algorithms. SHAP analysis further reveals that curing age and curing environment dominate drying shrinkage, whereas autogenous shrinkage is primarily governed by the curing age and water-to-binder ratio. The interaction analysis also identifies the coupled effects between low water-to-binder ratio and extended curing age. The proposed framework not only improves prediction robustness for UHPC shrinkage under limited data conditions but also provides interpretable insights into the mechanisms governing early-age deformation. These findings offer a data-driven basis for optimizing UHPC mixture design and mitigating early-age cracking risks in engineering applications. Full article

The urgent global need for sustainable infrastructure drives the demand for high-value buildings and waste removal. This paper studies the feasibility of using recycled foam concrete aggregate (FCA) as a substitute for natural coarse aggregate (NCA) in concrete and studies its impact on rheology, mechanical degradation, shear resistance, and the full-range replacement ratio (0–100). The experimental results show that the monotonic change in the workability of fresh concrete determines the lubrication threshold at 60% replacement, which is driven by the volume proportion effect. Beyond this value, capillary suction dominates, and the viscosity rises rapidly. From a mechanical perspective, the porous structure of FCA is conducive to “internal curing” so that moisture is released from the drying interface, but it also becomes a source of defects that change the fault topology. Specifically, the critical transition of the shear failure mode shifts from the debonding of the interface to the crushing of the cross-particle aggregate. At this time, the shear capacity decreases substantially, experiencing a reduction of 71.8% when completely replaced. There is a strong correlation between ultrasonic pulse velocity (UPV), rebound number, and compressive strength, and a multivariate nonlinear regression model (R² > 0.85) with non-destructive strength prediction is ultimately obtained. Based on the balance between mechanical capacity and resource cyclability, an optimal alternative zone of 20% to 40% is proposed. This work not only provides a mechanism for multi-scale coupling between pore structure and structural properties but also provides a data-driven method for the safety assessment of lightweight recycled aggregate concrete (RAC). Full article

The construction industry is one of the primary global contributors to carbon emissions, with both construction materials and operational energy recognized as critical factors in achieving net-zero goals. Given that structural systems are embodied carbon-intensive, significant early-stage carbon reductions are possible. This paper introduces the dual-layer sustainable optimization framework (DLSOF), a methodology that integrates system-level substitution with span-level optimization and a single life-cycle assessment (LCA) approach focused on embodied carbon (EC) that is applicable to various construction types and climate regions. To validate DLSOF, two representative models of reinforced concrete buildings were selected for analysis: one focused on alternate structural systems and the other on span optimization for a standard slab configuration. The results indicate that, in most cases, span optimization achieves a reduction in embodied carbon of 33%, whilst system-level substitution, in most cases, achieves a reduction of approximately 30%. The dual-layer approach, in comparison to conventional baseline designs, achieves approximately a 52% reduction in embodied carbon. Uncertainty analysis indicates variability in design and data inputs, but the overall trend of embodied carbon reduction remains consistent. The results highlight the critical nature of the early structural design stage. For engineers, the DLSOF provides a practical design pathway, and it offers flexibility to accommodate diverse sustainability goals across varying geographical contexts. This study establishes a replicable and transferable model for low-carbon structural design by systematically integrating design optimization with embodied carbon assessment. Full article

Flexural stiffness identification of prestressed concrete beams plays an important role in evaluating the mechanical performance and damage condition of bridge structures and has become a critical research direction in bridge health monitoring. Accordingly, this paper presented a Physics-Informed Neural Network (PINN)-based method for flexural stiffness identification. In the physical modeling framework, point source forces in the beam-column equation (BCE) were represented by approximating the Dirac delta function with Gaussian functions. This strategy alleviated the convergence issue of the loss function caused by singular behavior and enabled the formulation of a unified governing equation for multi-point loading scenarios. To eliminate the long-term deflection caused by non-load-related factors and self-weight, the BCE was expressed in incremental form. The resulting nondimensional equation was adopted as the target constraint for PINN training to alleviate multi-scale challenges. Furthermore, the residual-based adaptive refinement (RAR) strategy was incorporated during network training to improve computational efficiency and identification accuracy. The proposed method was validated through nine numerical cases without linear relationships and three experimental cases. The results indicate that, even with limited measurement data and under the tested noise levels, the proposed framework can achieve satisfactory flexural stiffness identification under the tested loading conditions. This suggests that the proposed method has promising potential for flexural stiffness identification and may be useful in bridge structural health monitoring under sparse-data conditions. Full article

Modular integrated construction (MiC) is an innovative construction method that shifts on-site activities to a controlled factory environment, thereby offering sustainability benefits. However, current carbon management relies on labor-intensive manual data collection, causing delayed and inaccurate carbon accounting that increases greenwashing risks. Existing approaches lack real-time, automated, and trustworthy carbon tracking capabilities across fragmented supply chains. This study develops and validates the Blockchain-enabled IoT-BIM Platform (BIBP), which combines Internet of Things (IoT), Building Information Modeling (BIM), and blockchain for real-time carbon monitoring. IoT sensors automate data capture from construction equipment and BIM provides spatial visualization of carbon at the module and building levels. A Hyperledger Fabric blockchain ensures the authenticity, immutability, and traceability of carbon records. Validated on a 15-story MiC project in Hong Kong, BIBP established a cradle-to-end-of-construction baseline of 949.84 kgCO_2e/m², identifying steel and concrete as the primary hotspots (80% of material emissions). Real-time analytics demonstrated that combining high-volume ground granulated blast furnace slag (GGBS) concrete substitution, new energy sea–land multimodal transport, and 10% steel waste reduction achieves over 20% carbon savings. Furthermore, the BIBP automated data acquisition and calculation, improving assessment efficiency by 92.4%. The platform demonstrates the potential to transform carbon management from a static, retrospective evaluation into a proactive, data-driven monitoring process, equipping stakeholders with a tool to dynamically track emissions and make timely interventions toward carbon reduction targets. Full article

This study investigates the synergistic mechanism between composite activators (NaOH and Na₂SiO₃ blend) and the microstructure–macroperformance relationship of foam concrete, focusing on the influence of different activator dosages on foam concrete stability, compressive strength, and drying shrinkage behavior. Experimental results indicate that excessively high activator dosages impair foam concrete stability, reduce compressive strength, and accelerate drying shrinkage. However, an appropriate amount of composite activator effectively improves the stability of freshly mixed foam concrete, significantly reducing settlement rates. During the hardening stage, it optimizes pore size distribution, promotes the formation of denser hydration products, and enhances the mechanical properties of the pore framework, thereby synergistically improving the mechanical performance of foam concrete. Full article

As social robots are increasingly deployed in domains such as healthcare, education, and entertainment, there is growing demand for affective agents that can interpret users’ affective states and respond in contextually appropriate ways. Existing work has established strong foundations for emotion generation and appraisal, but the step that connects generated emotion to behavioral execution still relies heavily on model-specific rules or implicit links. We frame this issue as a Mechanism Gap and propose an Emotional BDI framework that introduces Frijda’s action tendency as an intermediate representation layer between the Affective Core and the Belief–Desire–Intention (BDI) Executor. Rather than mapping emotion directly to concrete behavior, the framework first transforms affective state into a directional action tendency and then lets BDI reasoning realize that tendency according to role and context. This creates an explicit emotion-to-behavior mediation structure through which the same emotion can be expressed differently across situations and roles. In an exploratory user evaluation with 26 participants, the proposed model received more favorable ratings than an Emotion-Driven Agent in satisfaction ($p=0.010$) and appropriateness ($p=0.002$). Compared with a Cooperative Agent, the proposed model showed a significant advantage only in satisfaction ($p=0.030$). These findings suggest that the proposed framework offers a useful architectural direction for affective decision making beyond direct mapping or unconditional compliance. Full article

To address the shortage of natural aggregates and freshwater, and promote the recycling of construction and demolition waste and localized construction materials for marine engineering, this study explores the electrochemical corrosion characteristics and deterioration mechanism of steel bars in recycled concrete aggregate (RCA)–seawater sea-sand concrete (SSC) concrete. Using RCA replacement rates (0%, 50%, 100%) as the core variable, specimens were prepared. Vacuum water saturation, open-circuit potential (OCP) monitoring, Tafel polarization scanning and electrochemical impedance spectroscopy (EIS) were adopted to study steel corrosion evolution within 180 days. The results show that RCA incorporation accelerates OCP negative drift and reduces passivation film stability, with more severe corrosion at higher replacement rates: the RCA100 group showed obvious corrosion after 60 days, while the RCA50 and RCA0 groups initiated corrosion at 90 days (RCA50 corroded faster). The surface mortar and internal microcracks of RCA enhance the water absorption and ion permeability of concrete, which, coupled with chloride ions, accelerates steel corrosion. This study clarifies the correlation between RCA replacement rate and corrosion parameters, providing data support for mix ratio optimization and marine engineering applications. Full article

Asphalt pavements are essential to modern transport infrastructure but remain highly dependent on virgin aggregates and petroleum-based binders, resulting in high energy demand and significant greenhouse gas emissions. In response, research has advanced recycled-material solutions and low-temperature asphalt technologies. However, sustainability is still often inferred from isolated environmental indicators, without consistent consideration of mechanical durability or economic feasibility throughout the life cycle. This review provides an integrated synthesis of sustainable asphalt mixtures by jointly examining recycling strategies, temperature-reduction processes (warm-mix, half-warm-mix, and cold-mix asphalt technologies), and their combined applications through an integrated performance–cost–environment perspective. The literature reveals substantial methodological fragmentation, with limited harmonisation of functional units, system boundaries, and allocation rules, which constrains cross-study comparability. Evidence indicates that reclaimed asphalt, recycled concrete aggregates, and steel slag can maintain or improve rutting resistance, stiffness, and moisture durability while enabling material cost savings of approximately 5–68%. Temperature-reduction technologies further achieve significant energy and GHG reductions in the production phase (20–70%), with integrated recycling–temperature-reduction systems showing the most consistent combined benefits. Overall, this review demonstrates that asphalt sustainability cannot be established through single-dimensional assessments but requires harmonised life-cycle frameworks that explicitly link environmental gains to mechanical performance, durability, and economic viability. Full article

Natural pumice can reduce the self-weight of concrete, but its high porosity, high water absorption, and weak interfacial bonding tend to limit the strength and durability of lightweight aggregate concrete. To address this issue, this study proposes a method for preparing and applying reinforced pumice lightweight aggregates, namely, using nano-SiO₂-modified fly ash to construct a nanocomposite material at the micro-interface for the reinforcement treatment of natural pumice aggregates, and reveals the mechanism by which this treatment enhances the performance of lightweight aggregate concrete. Through aggregate performance tests, compressive strength tests, XRD, SEM, and freeze–thaw cycle tests, the effects of the reinforced pumice aggregate on the performance of lightweight concrete were systematically investigated. The results show that after the reinforcement treatment, the water absorption of the pumice aggregate decreases by 17.6%, and the cylinder compressive strength increases by 34.3%. As the replacement ratio of reinforced pumice increases, both the early-age and later-age compressive strengths of the concrete continuously improve. When all the pumice aggregate is reinforced, the 3 d and 28 d compressive strengths increase by 35.1% and 33.44%, respectively. Meanwhile, the reinforced pumice effectively improves the interfacial bonding between the aggregate and the cement paste, reducing the width of the interfacial transition zone by 32%, enhancing the matrix compactness, and delaying crack propagation. The study demonstrates that the reinforced pumice aggregate possesses favorable characteristics, not only effectively improving the mechanical properties and freeze–thaw resistance of lightweight concrete but also providing a new technical pathway for the high-performance utilization of porous lightweight aggregates, offering a reference for the resource utilization of industrial solid waste and engineering applications in cold regions. Full article

The literature identifies concrete and steel as the primary contributors to embodied carbon in building structures and highlights a strong relationship between sustainability and structural system geometry. However, existing studies predominantly focus on one-way systems and flat slabs, while research on two-way joist slabs remains limited and often centred on strength optimisation. In particular, there is a lack of systematic life cycle comparisons of alternative beam configurations within this system. This gap is critical, as early-stage design decisions largely determine the environmental impact of structural systems. This study presents a comprehensive, span-dependent evaluation of four beam configurations, namely Without Beam, Internal Beam, Perimeter Beam, and Full Beam, for reinforced concrete two-way joist slabs used in office buildings. A parametric framework was developed using Eurocode-compliant structural design and nonlinear finite element modelling to assess 36 span combinations ranging from 4 × 4 m to 14 × 14 m. Material quantities were extracted from the final designs and converted into embodied carbon values using cradle-to-gate (A1–A3) emission factors derived from the ICE database. The results demonstrate that beam configuration has a significant influence on embodied carbon and construction cost. For spans below approximately 8 m, beamless systems provide the most material-efficient solution. For spans exceeding approximately 10 m, full-beam configurations offer improved structural efficiency and reduced embodied carbon due to enhanced stiffness and load distribution. Full article

The study focuses on the attempt to produce structural concrete, class C25/30 with exposure class XC3, using recycled aggregates derived from Excavation, Construction and Demolition Waste (ECDW) management. All the necessary properties of the recycled aggregates used were determined and four concrete mix compositions were made with recycled aggregate percentages ranging from 25% to 100%, while two more mix compositions were made with natural aggregates (NAs) to compare the results. A total of 78 cubic specimens, 13 from each mix, were obtained and their compressive strength, dynamic modulus of elasticity, rebound number, maximum deformation and maximum mass loss due to evaporation were determined at ages of 3, 7, 14, 28 and 90 days. The results show that 25–50% replacement with mixed recycled aggregates can satisfy the C25/30 strength class, whereas 100% replacement leads to significant strength and stiffness reductions. Overall, the study demonstrates that structural-grade recycled aggregate concrete is feasible up to moderate replacement levels, provided that the high water absorption and increased deformability associated with recycled aggregates are explicitly accounted for in mix design, curing and serviceability checks. Full article

In this paper, the uniform approximation of continuous functions on $[0,1]$ by rational functions with prescribed poles and bounded multiplicities is studied. A classical theorem of Fichera characterizes density in $C\left(\right[0,1\left]\right)$ through the divergence of a conformally invariant series involving the pole distribution. A modern reformulation of this result is developed and it is given an operator-theoretic interpretation in which the approximation property is equivalent to cyclicity and to the absence of nontrivial invariant subspaces in an associated Hardy-space model. In this framework, the classical Blaschke condition emerges as the fundamental obstruction to density, linking rational approximation to the structure of model spaces and non-selfadjoint operator algebras. The density criterion is interpreted in terms of symmetry: divergence corresponds to a balanced distribution of poles compatible with the conformal geometry of the slit domain, while convergence induces symmetry breaking and the emergence of invariant structures. Numerical models illustrate the sharpness of the criterion and provide a concrete manifestation of the Blaschke obstruction and cyclicity mechanism. This new approach places Fichera’s theorem within a broader operator-theoretic and spectral framework, connecting classical approximation theory with Hardy spaces, invariant subspace theory, and modern rational approximation methods. Full article