Recently, there has been a growing interest in deploying smart materials as sensing components of structural health monitoring systems. In this arena, piezoelectric materials offer great promise for researchers to rapidly expand their many potential applications. The main goal of this study is to review the state-of-the-art piezoelectric-based sensing techniques that are currently used in the structural health monitoring area. These techniques range from piezoelectric electromechanical impedance and ultrasonic Lamb wave methods to a class of cutting-edge self-powered sensing systems. We present the principle of the piezoelectric effect and the underlying mechanisms used by the piezoelectric sensing methods to detect the structural response. Furthermore, the pros and cons of the current methodologies are discussed. In the end, we envision a role of the piezoelectric-based techniques in developing the next-generation self-monitoring and self-powering health monitoring systems.

With recent advancements in technology, energy storage for gadgets and sensors has become a challenging task. Among several alternatives, the triboelectric nanogenerators (TENG) have been recognized as one of the most reliable methods to cure conventional battery innovation’s inadequacies. A TENG transfers mechanical energy from the surrounding environment into power. Natural energy resources can empower TENGs to create a clean and conveyed energy network, which can finally facilitate the development of different remote gadgets. In this review paper, TENGs targeting various environmental energy resources are systematically summarized. First, a brief introduction is given to the ocean waves’ principles, as well as the conventional energy harvesting devices. Next, different TENG systems are discussed in details. Furthermore, hybridization of TENGs with other energy innovations such as solar cells, electromagnetic generators, piezoelectric nanogenerators and magnetic intensity are investigated as an efficient technique to improve their performance. Advantages and disadvantages of different TENG structures are explored. A high level overview is provided on the connection of TENGs with structural health monitoring, artificial intelligence and the path forward.

Triboelectric nanogenerators have received significant research attention in recent years. Structural design plays a critical role in improving the energy harvesting performance of triboelectric nanogenerators. Here, we develop the magnetic capsulate triboelectric nanogenerators (MC-TENG) for energy harvesting under undesirable mechanical excitations. The capsulate TENG are designed to be driven by an oscillation-triggered magnetic force in a holding frame to generate electrical power due to the principle of the freestanding triboelectrification. Experimental and numerical studies are conducted to investigate the electrical performance of MC-TENG under cyclic loading in three energy harvesting modes. The results indicate that the energy harvesting performance of the MC-TENG is significantly affected by the structure of the capsulate TENG. The copper MC-TENG systems are found to be the most effective design that generates the maximum mode of the voltage range is 4 V in the closed-circuit with the resistance of 10 GΩ. The proposed MC-TENG concept provides an effective method to harvest electrical energy from low-frequency and low-amplitude oscillations such as ocean wave.

In this paper, a new structural damage detection approach is proposed, based on monitoring of the magnetic field intensity variations using smartphones. Experimental and numerical studies are conducted on steel plates to verify the efficiency of the proposed approach. Various damage scenarios are introduced to the steel plates. Then, a smartphone magnetometer sensor is deployed to measure the changes of the magnetic flux due to damage progression. The experimental and numerical results agree well with each other. Based on the results, the magnetic field intensity increases as the damage progresses. Furthermore, the damage detection accuracy declines as the distance of the smartphone increases from the steel plate surface. The proposed method can be considered as a promising, cost-effective and crowdsourcing sensing platform empowered by citizens for structural health monitoring of civil infrastructure systems.

3D concrete printing has gained tremendous popularity as a promising technique with the potential to remarkably push the boundaries of conventional concrete technology. Enormous research efforts have been directed towards improving the material properties and structural safety of 3D printed concrete (3DPC) over the last decade. In contrast, little attention has been accorded to its sustainability performance in the built environment. This study compares the energy efficiency, operational carbon emission, and thermal comfort of air cavity 3DPC building envelopes against insulated models. Four insulations, namely expanded polystyrene (EPS), extruded polystyrene (XPS), polyurethane foam (PUF), and fiberglass (FG), are iteratively paired with three different 3DPC mix designs, and their resulting performances are reported. A numerical optimization analysis is performed to obtain combinations of 3DPC building models and insulation with the least energy expenditure, carbon production, and thermal efficiency. The results indicate that insulation considerably enhances the overall environmental performance of 3DPC structures. The optimization process also demonstrates the potential of using 3D printable fiber reinforced engineered cementitious concrete (3DPFRECC) with polyurethane infill for amplified sustainable performance in modern construction.