KEYWORDS: Structural health monitoring, Ferroelectric materials, Sensors, Renewable energy, Metamaterials, Finite element methods, Epoxies, Energy harvesting, Chemical elements
Interest in blue energy harvesting systems is rapidly growing and becoming widespread given its promise as a renewable and clean energy source. Blue energy harvesting from raindrop impact would allow low-power systems to operate in remote areas without the need for battery replacement and related maintenance. Insufficient power output is the most critical limitation that makes the conventional types of rain energy harvester (REH) typically unusable or/and infeasible. To overcome this limitation, a bio-inspired metasurface skin is proposed in this paper to serve as the membrane for a piezoelectric type of REHs. The proposed metasurface membrane is comprised of a system of biaxial-cuts inspired by snake scale. The power enhancement of the bio-inspired harvester with a metamembrane was studied and compared to its equivalent conventional harvester with a plain membrane when the substrate was under raindrop pressure. The Finite Element Model (FEM) results showed that the metamembrane could transfer more stress deformation to the piezo-element layer, thus enhancing power output. This is attributable to the metasurface membrane polarizing the PVDF better than a conventional plain membrane because of its higher ability to stretch the PVDF. The proposed bio-inspired harvester could be used for different public facilities such as tents, umbrellas, awnings, temporary roofs, coverings, and tarps to provide power for sensing, lighting, signage, digital displays, etc., especially in heavy-rain regions.
There is a higher necessity for a safe and intelligent railway transportation system as an important foundation for the smart city concept. The need to develop real-time condition monitoring technology for limited access parts of high-speed trains, such as wheels, is an important challenge. This paper develops an Internet of Things (IoT) based nondestructive evaluation (NDE 4.0) platform for autonomous inspection of in-service train wheels. The proposed NDE 4.0 platform consists of a wireless transmission module (WTM) which is used to remotely transfer power from the bogie to its surrounded wheels and also to receive back the data from sensors installed on the axle box of the wheels. The WTM’s circuits were designed and simulated in LTSpice software. This paper reveals the great potential of using cyber-physical systems to intelligently manage big data and autonomously control National Railway Networks (NRN).
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.