Global Civil Engineering Awards

The construction industry is increasingly focused on sustainable materials that reduce environmental impact while maintaining high mechanical performance. One promising strategy involves incorporating industrial waste materials into concrete, such as high-volume fly ash (FA) as a cement substitute and recycled porcelain aggregate (PA) as fine aggregate. This study investigates a novel sustainable concrete system enhanced with multiscale fibers to overcome the strength limitations typically associated with high replacement levels. The goal is to develop an eco-friendly material capable of meeting structural performance requirements while promoting circular economy principles. Optimization of Fly Ash and Porcelain Aggregate Replacement A key objective of the research was to determine the optimal proportions of FA (0–50 %) and PA (0–100 %) required to achieve a target compressive strength of 45 MPa. Through experimental testing and numerical modeling, the study demonstrated that even at...

Accurate characterization of weathered geomaterials—comprising residual soils and weathered rocks—is essential for ensuring the stability and safety of civil engineering structures. These materials exhibit transitional behavior between soil and rock, making their mechanical properties difficult to assess using conventional techniques. Laboratory testing is often impractical because obtaining undisturbed samples from weathered layers is extremely challenging. Consequently, reliable in-situ testing methods are crucial for capturing true field conditions and improving geotechnical design accuracy. Limitations of Conventional Field Testing Methods Traditional field tests are typically developed either for soils or for intact rock masses, leading to significant shortcomings when applied to intermediate geomaterials. Weathered layers possess heterogeneous structures, variable stiffness, and complex failure mechanisms that standard tests cannot fully capture. As a result, existing technique...

Active structural control systems are among the most effective technologies for suppressing vibrations in civil engineering structures subjected to dynamic loads such as earthquakes and wind. However, conventional active control methods often suffer from performance degradation due to time delays, measurement noise, and changing operational conditions. To overcome these limitations, data-driven control strategies based on reinforcement learning have emerged as promising alternatives. This study introduces advanced soft actor-critic (SAC)– based control approaches designed to enhance adaptability and robustness in complex real-world environments. Challenges in Traditional Active Control Systems Traditional controllers, such as linear quadratic Gaussian (LQG) control, rely on predefined system models and fixed parameters. In practical applications, uncertainties such as sensor noise, communication delays, and environmental variability can significantly reduce their effectiveness. Thes...

Foamed glass aggregate (FGA) is an innovative lightweight geomaterial manufactured from recycled glass through a sinter-foaming process. As sustainability becomes a central priority in civil engineering, FGA has emerged as a promising alternative to conventional granular fills. Its highly porous cellular structure results in extremely low density, excellent thermal insulation, and efficient drainage performance. These characteristics make FGA particularly suitable for applications such as embankments, backfills, retaining structures, and foundation systems where weight reduction and environmental benefits are essential. Production Mechanisms and Microstructural Formation The engineering performance of FGA originates from its manufacturing process, in which glass particle size, sintering temperature, and foaming agent dosage interact to create a controlled cellular microstructure. During sintering, gas released from the foaming agent becomes trapped within softened glass particles, f...

Accurate estimation of soil unsaturated hydraulic conductivity is essential for understanding vadose zone flow, groundwater recharge, contaminant transport, and broader subsurface hydrological processes. Conventional point-scale measurements are typically invasive, labor-intensive, and limited in spatial and temporal coverage, making them inadequate for capturing natural field heterogeneity. To address these limitations, non-destructive geophysical techniques offer a promising alternative for continuous, large-scale monitoring of soil moisture dynamics and hydraulic behavior. Integrated Geophysical Framework This study introduces an innovative framework that integrates time-lapse ground penetrating radar (GPR) and electrical resistivity tomography (ERT) with an improved instantaneous profile (IIP) inversion approach. By combining electromagnetic and electrical measurements, the method captures changes in soil moisture and pore-water distribution over time. This integrated approach e...

Bridge digital twins represent a transformative approach in bridge engineering, enabling the creation of virtual replicas that mirror the physical structure throughout its lifecycle. Originating from advancements in other industries, digital twin technology integrates real-world data with computational models to support monitoring, analysis, and decision-making. In bridge applications, digital twins promise enhanced safety, predictive maintenance, and optimized asset management, making them a critical component of next-generation infrastructure systems. Concept of Digital Twins in Bridge Engineering A bridge digital twin combines geometric information, material properties, sensor data, and operational conditions into a unified virtual model. By linking physical bridges with Building Information Modeling (BIM) and Finite Element (FE) models, engineers can simulate structural behavior under varying loads and environmental influences. This integration enables continuous assessment of p...

 Bamboo scrimber (BS) is a high-performance engineered bamboo material gaining recognition as a sustainable alternative to conventional structural materials. Produced through the densification and resin impregnation of bamboo fibers, BS exhibits excellent strength, durability, and resource efficiency. Despite its promising mechanical properties, the anisotropic nature of bamboo—stemming from its fibrous structure—leads to direction-dependent behavior that is not yet fully understood, particularly under shear loading. This knowledge gap presents a critical challenge for the reliable structural design of BS components subjected to shear forces. Experimental Investigation of Shear Properties To address this challenge, the study conducted an extensive experimental program involving 250 shear tests performed under five distinct loading orientations. This comprehensive testing approach enabled the systematic evaluation of how fiber alignment and loading direction influence shear perfor...

Advanced cementitious composites are rapidly evolving beyond traditional load-bearing functions to incorporate multifunctional smart capabilities such as self-sensing and ambient energy harvesting. These next-generation materials are designed to support intelligent infrastructure systems capable of structural monitoring, data transmission, and autonomous energy supply. This study introduces triboelectric-functionalized cementitious composites reinforced with smart core–sheath braided yarns (APCY), aiming to enable large-scale deployment of energy-autonomous and self-powered civil infrastructure. Fabrication of Smart Core–Sheath Yarns via Braiding Technology The APCY yarns are manufactured using advanced braiding technology to produce a core–sheath configuration optimized for mechanical durability and functional performance. A surface roughening modification applied to the guide holes significantly enhances yarn hairiness, thereby increasing effective surface contact area for triboele...

Robot-aided inspection has emerged as a promising solution for enhancing safety, efficiency, and objectivity in infrastructure assessment. However, existing approaches often suffer from inconsistent mapping accuracy, unreliable defect measurements, and platform-specific system designs that limit scalability. This study investigates whether a SLAM-centric (Simultaneous Localization and Mapping) framework can overcome these limitations and enable precise, repeatable, and platform-agnostic visual inspections across diverse infrastructure environments. Integrated Lidar–Camera–Inertial SLAM Architecture The proposed framework integrates lidar, camera, and inertial measurement unit (IMU) data within a unified SLAM pipeline to ensure robust localization and mapping under real-world conditions. Multi-sensor fusion enhances pose estimation accuracy and resilience to environmental challenges such as lighting variation, occlusions, and geometric complexity. By centering the inspection workflow...

Sustainable water management has become a fundamental pillar of global environmental sustainability and resource conservation. Escalating water demand—driven by climate change, rapid urbanization, and population growth—has intensified pressure on existing water infrastructure systems. Civil engineering plays a decisive role in designing, upgrading, and managing water supply, wastewater, and stormwater systems to ensure long-term resilience and sustainability. This study provides a rigorous evaluation of how innovative engineering practices and emerging technologies are transforming water management toward more sustainable and equitable paradigms. Sustainable Water Supply Systems and Technological Innovations Modern water supply systems increasingly integrate advanced treatment technologies, smart monitoring networks, and decentralized distribution models to enhance efficiency and reduce resource losses. Innovations such as membrane filtration, smart metering, leak detection systems,...

Superhydrophobic coatings have gained increasing attention in structural engineering due to their ability to provide water repellency, anti-fouling performance, and surface protection against environmental degradation. However, achieving both high hydrophobicity and long-term durability remains a significant challenge. This study presents a novel fluorinated silane-modified organic polysilazane coating system designed to deliver superior water repellency, mechanical robustness, and environmental stability through a scalable and cost-effective fabrication approach. Synthesis of Fluorinated Silane Coupling Agent A fluorinated silane coupling agent was synthesized via hydrosilylation between 2-(perfluorohexyl)ethyl methacrylate and trimethoxysilane. The incorporation of perfluoroalkyl functional groups provides low surface energy, which is essential for achieving superhydrophobic behavior. This synthesized coupling agent was subsequently integrated into an organic polysilazane matrix, e...

  Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, durability, and serviceability of civil infrastructure such as bridges, buildings, and transportation systems. Conventional monitoring systems often depend on external power supplies and wired data transmission, limiting their scalability and long-term reliability. This study introduces a Novel Self-Powered Sensor (NSPS) specifically designed for civil structures, integrating self-energy harvesting, low-power wireless communication, and intelligent sensing capabilities. The proposed system addresses the limitations of traditional SHM by enabling sustainable, long-term, and autonomous infrastructure monitoring. System Architecture and Core Technologies The NSPS integrates three major technological components: environmental energy harvesting, ultra-low-power wireless data transmission, and intelligent sensing modules. The energy harvesting unit captures ambient environmental energy—such as vibration...

Waterproofing remains a critical challenge in the durability and service life of concrete infrastructure, particularly in environments exposed to moisture ingress and shrinkage-induced cracking. Conventional bentonite-based systems, while effective, often require high material consumption and may exhibit limitations in performance consistency. This study explores the development of nano-Na-bentonite derived from Egyptian bentonitic clay through solvothermal (NBS) and precipitation (NBP) synthesis routes. By leveraging nano-scale engineering, the research aims to enhance swelling behavior, hydrophobicity, and crack-sealing efficiency, ultimately offering a sustainable and high-performance alternative for waterproofing civil structures. Material Preparation and Nano-Modification Techniques The starting Egyptian bentonite was subjected to activation and purification processes to ensure the removal of impurities and optimization of montmorillonite content prior to nano-modification. Two s...

Ride quality and flight safety are critical performance indicators for flexible civil aircraft, particularly under atmospheric disturbances such as gusts and turbulence. Normal overload tracking must satisfy stringent comfort and safety standards defined by ISO 2631-1 and MIL-F-9490D. This paper proposes a neural backstepping output-constrained control strategy to ensure accurate overload tracking while strictly respecting ride quality constraints. Normal Overload Constraints and Control Objectives The normal overload constraint arises from the need to limit excessive accelerations that degrade passenger comfort and structural integrity. To explicitly address these constraints, the control design incorporates an integral barrier Lyapunov function (IBLF), which guarantees that the overload response remains within a predefined safe interval throughout system operation. Neural Backstepping Control Framework A backstepping-based control architecture is developed for the flexible aircr...

  Infrastructure surface crack detection is a vital task in structural health monitoring, directly influencing the safety, durability, and serviceability of civil engineering assets. Although deep learning methods have achieved notable success in automated crack detection, their performance is often constrained by inefficient hyperparameter tuning, susceptibility to local optima, and suboptimal feature extraction. This study addresses these limitations by proposing an intelligent optimization-driven crack detection framework. Limitations of Conventional Deep Learning-Based Crack Detection Traditional deep learning models rely heavily on manual or heuristic-based hyperparameter selection, which can lead to unstable training outcomes and reduced generalization performance. Moreover, commonly used optimization techniques may become trapped in local optima, resulting in inaccurate crack localization and increased false positive rates, particularly when dealing with complex backgroun...