Abstract: The topology optimization of reinforced concrete (RC) building frames is relatively underexplored compared to steel structures, partly due to the lack of a systematic approach to generate and select ground structures (GS). Existing methods often use less systematic GS strategies, limiting efficient exploration of the vast and sparse design space shaped by large bay widths and story heights. This work addresses this gap by providing a comprehensive and systematic pipeline tailored for RC frames. The key contributions are: (1) development of a GS generation framework that systematically enumerates all feasible RC frame configurations within user-defined constraints, (2) introduction of a candidate GS selection map, a surrogate-based tool employing graph-based Latin Hypercube Sampling (LHS) and sparse Gaussian Process (GP) models, which predicts compliance early and strategically guides candidate selection, significantly reducing computational cost while serving as a reference for understanding design parameter influences; and (3) implementation of an integrated topology optimization pipeline applying particle swarm optimization (PSO) to selected candidates, achieving efficient compliance minimization with reduced computational effort. The complete workflow - which spans GS generation, surrogate-based candidate selection, and iterative optimization - is implemented and validated in two design domains with width-to-height aspect ratios of 1:1 and 1:1.5 and generates 438,984 and 104,032 different frame configurations respectively. The selected candidates undergo PSO-based optimization, yielding designs with volume fractions below 0.55 and preserving critical floor beams, demonstrating the framework’s ability to enable the design of structurally efficient RC frames. The framework is designed to be extensible, with direct applicability to broader RC design scenarios including three-dimensional frames and nonlinear analysis in future work.

Abstract: Climate change poses significant challenges to the operation and safety of dam and reservoir (D&R) systems, particularly in regions characterized by water scarcity and high climate variability. This study presents a structured methodology for climate risk assessment that integrates regional climate projections, system-specific thresholds, and a semi-quantitative risk matrix approach. A key innovation is the explicit linkage between climate indicators and system performance through physically based thresholds, combined with empirically derived exceedance probabilities from high-resolution climate projections. The methodology is applied to the Almopeos D&R system in Northern Greece using an ensemble of statistically downscaled CMIP6 simulations under two emission scenarios (SSP2-4.5 and SSP5-8.5) and two future periods (2041–2060 and 2081–2100). Three climate indicators are analyzed: TX35 (temperature extremes), CDD (consecutive dry days), and Rx1day (extreme precipitation). Results indicate that temperature increase is the dominant climate risk hazard, leading to increased irrigation demand and reduced system reliability, with risks classified as high to very high. Drought conditions represent a secondary but important risk, becoming critical during prolonged dry periods affecting reservoir storage, while extreme precipitation events exhibit low likelihood but potentially high consequences for dam safety. Adaptation measures are prioritized using a qualitative multi-criteria approach, highlighting the effectiveness of operational measures, while structural and monitoring interventions remain essential for ensuring system safety. The proposed methodology provides a transparent and transferable framework for climate-resilient planning of water infrastructure systems.

Abstract: Laminated Veneer Lumber (LVL) is engineered product produced by adhesively bonding fast growing Poplar veneers. Comparing dimensional lumber, LVL provides better use rate and fulfills structural wood requirement for wood structure building. And have proven this thing about the lateral mechanical properties for LVL shear walls, also have done investigations into what the hold downs and the loads of those that get put into it do to them when trying out these types of things in an effort to study their lateral mechanical workings. Comparisons with different types of wooden shear wall structures were carried out for this reason. According to the research data obtained through experiments and analyses, suggestions were proposed to designers regarding how they might go about designing hold-down devices in cases wherein these were employed with respect to particular kinds of shear walls which themselves had their own particular features and attributes.

Abstract: This study develops a comparative screening framework for evaluating the feasibility of low-temperature clinker production using waste-derived raw meals under melt-phase and Fe-in-liquid constraints. The work addresses the need to connect two strategies for lower-emission cement manufacture that are often discussed separately: partial substitution of conventional raw materials with waste-derived inputs and reduction of clinker burning temperature through mineralized processing. A secondary-data analysis was conducted using selected open-access case studies and an open-access spreadsheet dataset, from which quantitative variables related to composition, process conditions, clinker formation, and cement performance were extracted and compared. The results show that feasibility depends not only on burning temperature, but also on major-oxide compatibility, minor-element constraints, burnability, clinker phase balance, melt-related indicators, and final cement performance. In the waste-substitution benchmark, MSWI bottom ash was compositionally feasible only within a limited substitution range controlled by Fe2O3 content. In the mineralizer benchmark, a reduction in burning temperature from 1450 ∘C to 1350 ∘C was found to be a practical benchmark for reduced-temperature clinker production, whereas further reduction to 1300 ∘C required stronger chemical assistance and led to performance penalties. Overall, the proposed framework distinguishes favorable, conditionally feasible, and constrained pathways and provides a basis for screening candidate systems before experimental validation.

Abstract: The construction industry remains one of the largest contributors to global carbon emissions, with ordinary Portland cement (OPC) production accounting for a significant share due to high energy consumption and carbon intensive clinker manufacturing processes. As infrastructure development accelerates worldwide, particularly in rapidly urbanizing regions, the demand for sustainable construction materials has become urgent. In recent decades, alternative cementitious materials (ACMs), including fly ash, ground granulated blast furnace slag (GGBS), silica fume, and rice husk ash, have gained attention as partial replacements for OPC in concrete mixes. This research paper investigates the geotechnical and environmental impacts associated with the use of alternative cementitious materials in concrete, emphasizing real world construction conditions and performance requirements. The study evaluates the influence of ACMs on parameters such as soil–structure interaction, compressive and long term strength development, durability under aggressive environmental exposure, permeability characteristics, and resistance to chemical attack. Environmental performance indicators including carbon footprint reduction, energy savings, industrial waste utilization, and lifecycle sustainability are also assessed. Experimental findings and recent literature indicate that ACM based concrete exhibits reduced permeability, enhanced resistance to sulfate and chloride ingress, and improved long term mechanical performance compared to conventional OPC concrete. These contribute to improved geotechnical behavior in foundations exposed to adverse soil conditions. Furthermore, adopting alternative cementitious materials can reduce greenhouse gas emissions while supporting circular economy principles. The study concludes that integrating ACMs into concrete production is an approach for construction without compromising geotechnical performance or structural reliability.

Abstract: Structural reanalysis involves repeated evaluation of structural responses under iterative design changes. It is a major computational burden in structural optimization, sensitivity analysis, and health monitoring. The three-layer architecture, which comprises the stiffness, displacement, and force layers, is motivated by the governing structural mechanics relationship F=K·U, which establishes stiffness and displacement as natural intermediate quantities for predicting internal forces. This physics-informed hierarchy reduces dependence on large training datasets while preserving predictive accuracy across all response quantities. The framework predicts member-level stiffness statistics, nodal displacements, and internal forces through three sequential layers: stiffness, displacement, and force. Each layer enriches the feature set of the layer above. Sensitivity-based secondary inputs are derived analytically from closed-form expressions relating cross-sectional dimensions to stiffness and displacement changes. This embeds structural mechanics knowledge directly into the feature engineering process without additional analyses. Member stiffness matrices are recovered as submatrices of the global stiffness matrix, encoding inter-member structural context into each member’s representation. The framework is implemented on a six-floor, three-bay reinforced concrete frame of 42 members. Training uses 1,890 data points from 45 finite element iterations. The Random Forest model achieves R² scores of 0.99, 0.98, and 0.91 for axial force, shear force, and bending moment respectively on unseen validation data. Once trained, the framework predicts any number of design iterations in a single inference pass. This substantially reduces the computational cost of reanalysis-based workflows. The proposed framework offers a scalable, interpretable, and physics-consistent alternative to both classical reanalysis methods and purely data-driven surrogate models, with direct applicability to structural size optimization and structural health monitoring workflows.

Abstract: Reliable assessment of small-strain soil stiffness is essential for geotechnical site characterization and for analysing the behaviour of embankments and other earth structures. Surface-wave methods provide an efficient non-destructive means of estimating shear-wave velocity profiles; however, their application is limited by the non-uniqueness of the inversion process. This paper presents a multimodal inversion procedure for Rayleigh-wave dispersion curves based on the particle swarm optimization algorithm. The procedure involves the calculation of theoretical dispersion curves for a horizontally layered medium and their matching with experimental data through a global search scheme. The proposed procedure was first verified using two synthetic soil profiles, and its robustness was further assessed by considering perturbations of the theoretical dispersion curve of up to 10%. Particular attention was given to the influence of higher modes on the inversion results. The results show that including higher modes leads to a more accurate and reliable determination of shear-wave velocity profiles than an inversion based solely on the fundamental mode. The procedure was subsequently validated on a transverse embankment profile using an experimental MASW dispersion curve and comparison with SCPT results. Good agreement was obtained, and the eight-layer model proved to be a good compromise between accuracy and model complexity. The proposed multimodal approach therefore represents a reliable tool for the geotechnical characterization of layered soil profiles.

Abstract: The aerodynamic behaviour of buildings equipped with porous outer envelopes is governed by the interaction between millimetre-scale geometric features and building-scale flow structures. Explicitly resolving these scales in numerical simulations is computationally prohibitive, making homogenised porous-medium formulations a practical alternative. Among them, the Darcy–Forchheimer (D–F) model is widely adopted; however, the reliability of building-scale predictions critically depends on how its resistance coefficients are identified and validated. This study proposes and assesses a consistent procedure for the determination and application of D–F coefficients for porous screens used in double-skin façade systems. Porous elements are first characterised at element scale through an analytical derivation based on aerodynamic force coefficients, from fully resolved CFD simulations of representative periodic modules. The resulting D–F coefficients are cross-compared and validated against available wind tunnel data. Secondly, the calibrated homogenised model is applied to a building-scale double-skin façade configuration. The porous layer is represented as a finite-thickness porous region governed by the identified D–F parameters and analysed through unsteady Reynolds-averaged Navier–Stokes simulations. The model’s capability to reproduce global aerodynamic loads, local pressure distributions, and wake characteristics is evaluated against experimental data. The results demonstrate that a properly calibrated D–F formulation provides an accurate and computationally efficient representation of porous façade systems, bridging element-scale characterisation and structural-scale aerodynamic performance.

Abstract: Leaks in pipe systems result in significant economic losses, environmental hazards, and public health risks. Transient-based leak detection methods, which exploit the dynamics of pressure waves in response to system anomalies, have emerged as efficient techniques for identifying and characterizing leaks in pressurized pipelines. These methods offer dis-tinct advantages, including minimal data requirements, high sensitivity to low-pressure anomalies, and resilience to the ill-posed conditions often affecting steady-state models. This paper reviews transient-based leak detection, synthesizing findings from over 138 peer-reviewed publications spanning the past three decades. The review categorizes tran-sient-based methods into transient damping, transient reflection, system response, and inverse transient methods, analyzing the prevalence, evolution, and research rate of each category over time. By structuring the review around key aspects such as simulation do-main type, analysis approach, system response, solver strategies, adaptability to noise, viscoelasticity, and network complexity, this paper identifies significant trends and shifts in research focus. A comprehensive tabular dataset of 138 studies captures how research activity in various areas has accelerated, slowed, or reached stability, offering insights into the evolving priorities within the field. This review highlights areas for further develop-ment, particularly in addressing AI-enhanced applications, transient excitation and measurement sites design, noise resilience, comprehensive leak characterization, valida-tion approaches, and scalability for complex network applications, providing a resource to guide future research in transient-based leak detection.

Abstract: This paper presents an interpretable machine-learning framework for predicting the splitting strength (ST) of asphalt concrete and supporting data-driven mixture design. A database consisting of 296 samples was established, and 14 input variables related to asphalt properties, aggregate gradation, and fiber characteristics were selected for modeling. Six machine-learning models, namely TabPFN, ANN, SVR, RF, XGBoost, and LightGBM, were developed and compared. Hyperparameter optimization was performed for five models using NSGA-II, while TabPFN was directly applied with its default configuration. The results show that all six models achieved satisfactory predictive capability, whereas TabPFN delivered the best overall performance on the testing set, with the lowest RMSE of 0.28, MAE of 0.21, MAPE of 18.01%, MAD of 0.14, the highest R² of 0.88, and the highest composite score of 0.91. SHAP analysis further revealed that nine dominant variables accounted for 92.0% of the total average contribution, among which Ag9.5, FT, Ag4.75, AC, and Du were the most influential. In addition, favorable parameter ranges for improving ST were quantified, such as Ag9.5 < 66.8%, Ag4.75 < 45.0%, AC < 5.4 wt.%, AV < 3.6%, and Du > 134.7 cm. Finally, a GUI platform integrating prediction and SHAP-based explanation was developed to improve the accessibility and practical applicability of the proposed framework.

Abstract: Plain 3D printed concrete (3DPC) suffers from inherent brittleness and anisotropic behavior that limit its structural applications. This study aims to investigate sprayed strain-hardening cementitious composite (SHCC) as a thin overlay to reinforce 3DPC. In particular, this paper investigated the effects of sprayed SHCC overlay thickness (10, 20, and 30 mm) on the flexural performance of reinforced 3DPC. Four-point bending tests were conducted on specimens with two cutting orientations, namely parallel (H) and perpendicular (V) to printing direction, and three loading directions (X, Y, and Z). The digital image correlation (DIC) technique was used to monitor strain distributions and interfacial behavior. The 3DPC reinforced with the 10 mm-thick overlay still showed brittle behavior but with reduced anisotropy. For reinforced 3DPC with a 20 mm-thick overlay, the flexural capacity increased by 35%–970% depending on loading direction, with the ultimate deflection enhanced by over 400% in all directions. The 30 mm-thick overlay further improved flexural strength by 155%–1200% and ultimate deflection by 350%–533% relative to plain 3DPC. DIC analysis revealed brittle fracture via a single crack in the composite with the 10mm-thick overlay, while the specimens with thicker overlays exhibited multiple cracks, and no shear slip was observed at the interface between the 3DPC substrate and S-SHCC overlay. An anisotropy-modified plane-section model was developed to predict structural behavior, with elastic stage deviations within 28% in the X-direction and 30% in the Y- and Z-directions. The peak load predictions showed 30% deviation in the X-direction and less than 15% spread in the Y- and Z-directions. These findings provide guidelines for designing 3DPC structures reinforced with sprayed SHCC overlay.

Abstract: Small streams exhibit rapid and nonlinear flood responses due to steep slopes, short flow paths, and limited storage capacity, making real-time flood prediction challenging under both computational and data constraints. This study proposes an integrated, measurement-based flood prediction framework that enables real-time estimation of flood dis-charge and flood depth in small-stream basins. Unlike conventional approaches that rely on either computationally intensive hydrodynamic models or standalone data-driven methods, the proposed framework combines high-frequency monitoring data, rainfall nowcasting, and nonlinear regression-based hydraulic relationships into a unified system. Rainfall–discharge nomographs and depth–discharge rating curves were developed using a nonlinear four-parameter logistic (4PL) regression model based on long-term observations from twelve representative basins in Korea. Forecast rainfall from the Korea Meteorological Administration MAPLE nowcasting system was used to estimate discharge, which was subsequently transformed into flood depth through calibrated rating curves. To extend prediction capability beyond monitoring locations, additional depth–discharge relationships were derived for ungauged reaches using hybrid approaches based on HEC-RAS scenario simulations and the Manning equation. Validation against major flood events showed strong agreement between observed and predicted values, with mean prediction accuracies of approximately 89% for discharge and 90% for flood depth. The proposed framework effectively captures nonlinear rainfall–runoff behavior while significantly reducing computational complexity compared with conventional hydrodynamic models. These results demonstrate that the framework provides a practical and scalable solution for real-time flood prediction and early warning in small-stream environments, particularly by enabling spatially continuous flood-depth estimation across both gauged and ungauged reaches.

Abstract: Slope displacements (δ) have been shown to correlate uniquely with the earthquake energy (Eₑq) contributing to slope sliding, regardless of input motion characteristics. Based on this principle, this study applies the Energy-Based Newmark Method to infinitely long slopes subjected to diverse ten earthquake records with incrementally scaled amplitudes. As the earthquake wave energy (Eᵤ) increases, the energy ratio (Eₑq/Eᵤ) exhibits a distinct peak followed by a monotonic decrease. These peak values and corresponding Eᵤ levels strongly depend on the predominant frequencies (fₚ) of the motions, consistent with results from harmonic wave analyses. A unified design diagram is developed to correlate Eₑq/Eᵤ with Eᵤ incorporating fₚ and slope parameters. Since both Eᵤ and fₚ can be estimated from design motions or empirically predicted using earthquake magnitude and source distance, the slope displacement δ can be directly obtained from the diagram, eliminating the need for time-domain numerical simulations used in the conventional Newmark approaches. This method is recommended for seismic zonation and hazard mapping in mountainous and hilly regions by regional authorities and infrastructure planners.

Abstract: Since the mid-20th century, reservoir construction has increased rapidly, and the number of mega-reservoirs has risen. Consequently, the impact of earthquakes on the safety of reservoir dams has attracted growing attention. This study employed the Particle Flow Code (PFC) to conduct a dynamic damage and failure analysis of the Koyna concrete gravity dam under strong seismic loading and to investigate the influence of seismic waves and inertial effects on the dam’s failure characteristics. A damage accumulation and failure index based on PFC, accounting for damage paths and the number of cracks, was proposed. When the dam was subjected to horizontal seismic waves lasting 0.82 s and vertical seismic waves lasting 0.018 s, cracks penetrated the dam. Horizontal and vertical seismic waves caused failure resulting from horizontal and vertical displacement differences, respectively. The horizontal displacement difference exhibited two peaks. The dam was more sensitive to horizontal seismic waves. The greater the inertial force, the faster the rate of damage accumulation and failure, and the greater the number of damage cracks. The inertial force of vertical seismic waves negligibly influenced the damage accumulation rate, crack initiation time, and failure mode.

Abstract: The seismic performance evaluation of concrete dams is a critical task in dam safety engineering, given the catastrophic consequences that dam failure can produce. Over the past two decades, the demand–capacity ratio (DCR) and cumulative inelastic duration (CID) framework, codified in USACE EM 1110-2-6051 and proposed by Ghanaat, has become the standard methodology for linear-elastic performance assessment. However, this framework intentionally uses static tensile strength as the capacity measure, introducing conservatism by neglecting the well-documented strain-rate enhancement of concrete tensile strength under seismic loading. This paper presents a comprehensive review of the current state of knowledge on seismic performance evaluation of concrete dams, synthesizing findings from gravity, arch, and buttress dam studies. It covers the DCR/CID framework, near-fault versus far-fault ground motion effects, dam–reservoir–foundation interaction modeling, nonlinear analysis methods, and emerging capacity-based approaches such as incremental dynamic analysis (IDA) and endurance time analysis (ETA). The paper then proposes an enhanced DCR formulation that incorporates strain-rate-dependent dynamic tensile strength using the CEB-FIP and Malvar–Ross dynamic increase factor (DIF) models. This rate-dependent DCR provides a more physically accurate capacity estimate for seismic strain rates (10⁻⁴ to 10⁻¹ s⁻¹), potentially reducing unnecessary conservatism while maintaining safety. The implications for performance level classification and the triggering of onlinear analysis are discussed.

Abstract: Pavements are essential elements of transportation networks and are instrumental to the growth and development of a country. To harness the full potential of this infrastructure, it is necessary to maintain it in proper structural and functional conditions. Conventional techniques, such as manual inspection can be used to determine the functional conditions of the pavement. However, these techniques have different shortcomings, including high monitoring costs, time consumption and requirement of traffic control during pavement surveying. These shortcomings can be mitigated by utilizing various Artificial Intelligence (AI) techniques such as machine learning and deep learning, for pavement surface inspection. This study aims to systematically review state-of-the-art deep learning techniques such as You Only Look Once (YOLO), Convolutional Neural Networks (CNNs), and vision transformer architectures for pavement distress detection. Deep learning techniques can autonomously detect various types of pavement distress including longitudinal and transverse cracks, rutting, faulting, patching, shoving, raveling and potholes from the pavement surface. The findings from the review indicate that YOLO and CNN were extensively employed by researchers, however in recent times, vision transformers gained popularity among researchers and pavement engineers. Overall, this study highlights the critical role played by different deep learning techniques in transforming pavement monitoring, leading to safer, more resilient, and sustainable transportation infrastructure.

Abstract: Factors such as asset aging, climate change affecting hydrological events and the growing demand in electricity are placing huge pressure on hydroelectric infrastructures, including dams, whose most important and critical component is the spillway, which operates through a system of discharge gates. This research aims to present the technical, environmental and functional parameters and issues affecting this system, highlighting the causes of their degradation and proposing solutions to improve their service life and their reliability. A literature review has been made to identify the challenges related to reliability and durability of the system. In addition, a case study based on real-world data was made to support and reveal the problems related to the spillway gates system. What sets this research apart is its integration of theoretical studies with a practical case study, supporting the proposed theories and uncovering potential hidden factors. Following the identification of key challenges, new updated and adaptable solutions explored world widely will be recommended to develop in future research.

Abstract: Hardfill dams represent a recent and cost-effective construction method in which locally available materials such as alluvial deposits, riverbed gravel, and excavation spoil are mixed with a low cement content to form the dam body. Compared with conventional roller-compacted concrete (RCC) gravity dams, hardfill dams require less rigorous material specifications and quality control, resulting in lower stresses within both the dam body and its foundation. Their symmetrical trapezoidal cross-section also provides favorable seismic performance. This paper presents a parametric sensitivity analysis of a 30 m high hardfill dam, examining the combined influence of horizontal seismic acceleration (0.1 g, 0.2 g, and 0.3 g) and foundation allowable bearing capacity (0.4, 0.6, and 0.8 MPa) on the required upstream and downstream slope inclinations. Nine models were first pre-dimensioned through rigid-body stability analysis following USACE criteria and then verified using plane-strain finite element models in SAP2000, with pseudo-static seismic loading. Results show that foundation bearing capacity is the governing parameter for the dam geometry, while seismic acceleration produces a proportional but less dominant effect on slope steepness. Gentler slopes consistently yield better stress distributions along the foundation, and significant discrepancies between rigid-body and elastic analyses arise when the foundation-to-dam stiffness ratio is low.

Abstract: Crumb Rubber Asphalt (CRA) is among the most established high-value pathways for recycling end-of-life tires in transport infrastructure. However, despite decades of research and field application, the literature remains dispersed across binder modification, mixture performance, incorporation technologies, long-term durability, environmental implications and circularity. This study presents a systematic review of peer-reviewed journal articles indexed in Scopus and Web of Science (WoS) that address the use of crumb rubber in asphalt binders and mixtures. The review is structured around four interrelated questions: how incorporation route governs rubber-bitumen interaction; how crumb rubber affects rutting, fatigue, low-temperature cracking and moisture susceptibility; how aging, emissions and life-cycle impacts shape the sustainability case for CRA; and which unresolved methodological limitations still restrict broader implementation. The evidence shows that crumb rubber generally improves rutting resistance, elastic recovery, fracture tolerance, and, in several surface applications, acoustic performance. These benefits, however, are not intrinsic to rubber addition alone. They depend on a process-sensitive design window involving rubber gradation, rubber content, base-binder chemistry, digestion temperature, interaction time, blending energy, storage conditions, and the use of complementary technologies such as warm-mix additives, rejuvenators, pre-swelling treatments or hybrid modifiers. Wet-process systems remain the most mature and technically reliable route, whereas dry-process technologies offer implementation simplicity but exhibit greater variability in material response. Terminal-blend technologies improve workability and storage stability, although, in some cases, they partially reduce the elastomeric contribution associated with intact rubber particles. From a sustainability perspective, CRA clearly contributes to waste-tire valorization and may reduce life-cycle burdens when durability gains are realized and production conditions are optimized. Nevertheless, these environmental advantages are conditional rather than universal. Future research should prioritize standardized reporting, multi-scale mechanism-to-performance integration, realistic weathering and aging protocols, harmonized life-cycle assessment and credible end-of-life recycling pathways for rubberized asphalt systems.

Abstract: With the acceleration of urbanization, numerous deep and large foundation pit projects have been emerging. This paper proposes a new type of support structure for deep foundation pits, namely vertical-inclined-piles wall (VIPW). Six sets of large-scale model tests of foundation pit excavation under 1-g condition were carried out, among which one set was supported by soldier pile wall (SPW) and the other five by VIPW. By monitoring and analyzing the distribution and variation characteristics of vertical pile deformation, surface settlement, pile bending moment, and inclined pile top axial force during the excavation process, the action mechanism of VIPW was revealed, and it was verified that VIPW exhibits better support performance than SPW. Furthermore, four key parameters, including the embedded depth of inclined piles, the inclination angle of inclined piles, the support position of inclined piles, and the embedded depth of vertical piles, were changed respectively to study their influences on the deformation and force characteristics of VIPW, providing a theoretical basis for structural optimization design. Moreover, by comparing the instability and failure characteristics of the foundation pit, it is proved that VIPW can effectively ensure the stability of the foundation pit.