In this paper, an analytical solution describing the deflection of a cracked beam repaired with piezoelectric patch is introduced. The solution is derived using perturbation method. A novel analytical model to calculate the proper dimensions of piezoelectric patches used to repair cracked beams is also introduced. This model shows that the thickness of the piezoelectric patch depends mainly on the thickness of the cracked beam, the electro-mechanical properties of the patch material, the applied load and the crack location. Furthermore, the model shows that the length of the piezoelectric patches depends on the thickness of the patch as well as it depends on the length of the cracked beam and the crack depth. The additio

The utilization of carbon dioxide (CO₂) to enhance wellbore injectivity presents a cost-effective and sustainable strategy for mitigating greenhouse gas emissions while improving reservoir performance. This study introduces an environmentally friendly method employing a water-soluble chitosan salt (CS) that generates a carbonated-rich acid solution upon contact with dry CO₂ at 25 °C and 508 psi. CS solutions (100–2000 ppm) were prepared and evaluated for CO₂ uptake, acid generation, and rheological behavior. Results show that 1000 ppm achieves an optimal CO2 uptake (2612 mg/l), with moderate viscosity increase (from 1.52 to 3.37 cp), while higher concentrations exhibit a sharp rise due to polymer-like network formation. Core floodi

In this paper, an analytical solution describing the deflection of a cracked beam repaired with piezoelectric patch is introduced. The solution is derived using perturbation method. A novel analytical model to calculate the proper dimensions of piezoelectric patches used to repair cracked beams is also introduced. This model shows that the thickness of the piezoelectric patch depends mainly on the thickness of the cracked beam, the electro-mechanical properties of the patch material, the applied load and the crack location. Furthermore, the model shows that the length of the piezoelectric patches depends on the thickness of the patch as well as it depends on the length of the cracked beam and the crack depth. The additional flexibil

Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

The provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification