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Title: Energy-Harvesting Smart Pavements Utilizing Piezoelectric Transducers

Author: Chianng Chan et al.

Abstract: This research investigates the integration of piezoelectric transducers within civil transportation infrastructure to harvest kinetic energy from vehicular traffic. Urban roadways are continuously subjected to high mechanical loads, which generally dissipate as wasted vibrational energy. By embedding optimized piezoelectric modules beneath the asphalt surface layer, this mechanical stress can be converted directly into electrical energy. The study focuses on the mechanical packaging of these sensors to withstand cyclic heavy traffic loading without causing premature structural failure or cracking in the pavement matrix. Advanced finite element modeling is used to evaluate the stress distribution at the material interface between the rigid transducer housing and the flexible asphalt concrete. Additionally, a prototype scale-model is subjected to accelerated pavement testing to evaluate long-term durability and electrical power output efficiency under varying vehicular speeds and axle weights. Preliminary findings indicate that optimal placement strategy can generate sufficient continuous power to operate localized civil systems, such as LED traffic signals, wireless structural health monitoring sensors, and smart streetlighting networks. Ultimately, this interdisciplinary approach bridges mechanical energy conversion principles with traditional civil infrastructure design, offering a sustainable pathway toward self-powered, smart urban transportation systems that reduce reliance on the main electrical grid.

Keywords: Energy Harvesting, Piezoelectric Transducers, Smart Pavements, Infrastructure Sustainability, Finite Element Analysis

Title: Autonomous Robotic Systems for Post-Disaster Structural Health Inspection

Author: Zainul Abidin et al.

Abstract: Ensuring the safety of civil infrastructure following catastrophic events like earthquakes or severe floods requires rapid, precise structural health monitoring (SHM). This project develops an integrated autonomous robotic system—combining unmanned aerial vehicles (UAVs) and tracked ground rovers—engineered specifically for inspecting compromised concrete and steel structures. From a mechanical perspective, the research focuses on designing robust, adaptive stabilization mechanisms and specialized end-effectors capable of maintaining steady contact with uneven vertical walls to deploy non-destructive testing (NDT) probes, such as ultrasonic and impact-echo sensors. From a civil engineering standpoint, the focus centers on interpreting the gathered kinematic and sensor data to accurately categorize structural degradation. Advanced computer vision algorithms are integrated to map surface cracks, while machine learning models estimate structural residual capacity in real-time. By automating this process, the system mitigates the immense safety risks faced by human inspectors entering unstable zones. The research evaluates system performance across multiple simulated disaster environments, analyzing navigation accuracy in GPS-denied concrete canyons and the fidelity of the generated 3D structural damage maps. The final output provides municipal engineers with an actionable, automated triage tool that significantly accelerates post-disaster infrastructure assessment and recovery timelines.

Keywords: Structural Health Monitoring, Autonomous Robots, Non-Destructive Testing, Disaster Recovery, Infrastructure Inspection

Title: Mechanical Metamaterials for Advanced Seismic Isolation in High-Rise Structures

Author: M. Z. Cohen et al.

Abstract: Traditional seismic protection systems, such as base isolators and tuned mass dampers, often feature significant bulk, complex maintenance requirements, and limited effectiveness against multi-directional or broadband seismic waves. This research explores the application of mechanical metamaterials—engineered cellular structures possessing unique wave-filtering properties—as a novel seismic isolation strategy for high-rise civil structures. By designing periodic sub-wavelength geometries, these metamaterials can create acoustic and elastic “bandgaps” that completely block or redirect dangerous seismic shear waves away from the building’s foundation. The investigation utilizes mechanical topology optimization to synthesize auxetic and chiral unit cells capable of extreme energy dissipation under high-strain cyclic compression. These optimized mechanical units are then scaled and modeled as foundational sub-structures within a finite element representation of a multi-story civil building. Seismic time-history analyses, utilizing historical earthquake data, are conducted to evaluate the metamaterial foundation’s capacity to minimize top-floor lateral drift and structural acceleration. Results demonstrate that metamaterial-based foundations can drastically reduce the seismic energy transmitted into the superstructure compared to standard elastomeric bearings. This study bridges the gap between micro-scale mechanical material physics and macro-scale structural engineering, providing a highly customizable, passive shield against devastating seismic events.

Keywords: Seismic Isolation, Mechanical Metamaterials, Wave Bandgaps, Topology Optimization, Structural Dynamics