Energy harvesting technologies have been explored by researchers for more than two decades as an alternative to conventional power sources (e.g. batteries) for small-sized and low-power electronic devices. The limited life-time and necessity for periodic recharging or replacement of batteries has been a consistent issue in portable, remote, and implantable devices. Ambient energy can usually be found in the form of solar energy, thermal energy, and vibration energy. Amongst these energy sources, vibration energy presents a persistent presence in nature and manmade structures. Various materials and transduction mechanisms have the ability to convert vibratory energy to useful electrical energy, such as piezoelectric, electromagnetic, and electrostatic generators. Piezoelectric transducers, with their inherent electromechanical coupling and high power density compared to electromagnetic and electrostatic transducers, have been widely explored to generate power from vibration energy sources. A topical review of piezoelectric energy harvesting methods was carried out and published in this journal by the authors in 2007. Since 2007, countless researchers have introduced novel materials, transduction mechanisms, electrical circuits, and analytical models to improve various aspects of piezoelectric energy harvesting devices. Additionally, many researchers have also reported novel applications of piezoelectric energy harvesting technology in the past decade. While the body of literature in the field of piezoelectric energy harvesting has grown significantly since 2007, this paper presents an update to the authors' previous review paper by summarizing the notable developments in the field of piezoelectric energy harvesting through the past decade.

https://iopscience.iop.org/article/10.1088/1361-665X/ab36e4/pdf

A review of energy harvesting using piezoelectric materials: state-of-the-art a decade later (2008–2018)

Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

Fiber-reinforced asphalt-concrete – A review

A comprehensive laboratory evaluation of the geotechnical and geoenvironmental properties of five predominant types of construction and demolition (C&D) waste materials was undertaken in th...

https://researchbank.swinburne.edu.au/file/9bbb0fa6-5557-4c65-ada9-7a360c041032/1/PDF (Accepted manuscript).pdf

Geotechnical and geoenvironmental properties of recycled construction and demolition materials in pavement subbase applications

Energy harvesting technologies in roadway and bridge for different applications – A comprehensive review

Interpretation of geophysical data often requires the solution of an inverse problem or simply, inversion. Inverse problem is a problem where the observed data is used to infer the characteristics of the system under investigation. There are two general approaches to the solution of inverse problems, deterministic and probabilistic approaches. Traditionally, in engineering geophysics, inversion is carried out using a deterministic approach, where a single set of results is identified as the interpretation outcome. In complex inverse problems, the deterministic solution process is often guided by an interpreter, who uses his information, experience, or judgment to guide the process. The deterministic approach to the solution of inverse problems implicitly assumes that the uncertainties in data and quantitative models are negligible. However, this assumption is not valid in many applications and, consequently, obtaining a single set of results does not provide a complete picture in terms of quantifying the effects of data and/or theoretical uncertainties on the obtained solution. In this paper, a general probabilistic approach to the solution of inverse problems is introduced, which offers the framework required to obtain uncertainty measures and to include some a priori information in the solution process. A technique for the evaluation of the probabilistic solution using Monte Carlo Markov Chains (MCMC) with Neighborhood Algorithm (NA) approximation is introduced and explained. Finally, the application of the presented approach in the health monitoring of transportation infrastructure using non-destructive testing (NDT) is illustrated.

Application Of Probabilistic Approach To The Solution Of Inverse Problems In Nondestructive Testing And Engineering Geophysics

Multisensor and automated measurement of bridge deck condition

Assessing condition of concrete bridge decks by robotic platform RABIT for development of deterioration and predictive models

The performance of roadway pavement is significantly affected by the integrity of buried pipes underneath. It is important that these pipes remain structurally sound during the life of the roadway for a better performance and uninterrupted service. Damage or total loss of the pipe will result in structural damage to the pavement, excessive deflections, and roadway subsidence or collapse. In the event of a roadway subsidence or collapse, the roadway or sections of it will be fully or partially closed to traffic for repair. Road closure and detours would cost the traveling public (trucking industry and passenger vehicles) in travel delay and added vehicle operating costs. One-lane closures usually result in approximately 30-60 minutes of delay per vehicle, and would cost the public in gas costs and additional costs due to travel delays. The added cost of travel would cause loss of revenues for businesses in New Jersey.

Study of the Effects of Buried Pipe Integrity on Roadway Subsidence

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Ali Maher

Papers

Application Of Probabilistic Approach To The Solution Of Inverse Problems In Nondestructive Testing And Engineering Geophysics

Multisensor and automated measurement of bridge deck condition

Assessing condition of concrete bridge decks by robotic platform RABIT for development of deterioration and predictive models

Study of the Effects of Buried Pipe Integrity on Roadway Subsidence

Surface Waves in Evaluation of Damping in Layered Systems