Natural sources of green energy include sunshine, water, biomass, geothermal heat, and wind. These energies are alternate forms of electrical energy that do not rely on fossil fuels. Green energy is environmentally benign, as it avoids the generation of greenhouse gases and pollutants. Various systems and equipment have been utilized to gather natural energy. However, most technologies need a huge amount of infrastructure and expensive equipment in order to power electronic gadgets, smart sensors, and wearable devices. Nanogenerators have recently emerged as an alternative technique for collecting energy from both natural and artificial sources, with significant benefits such as light weight, low-cost production, simple operation, easy signal processing, and low-cost materials. These nanogenerators might power electronic components and wearable devices used in a variety of applications such as telecommunications, the medical sector, the military and automotive industries, and internet of things (IoT) devices. We describe new research on the performance of nanogenerators employing several green energy acquisition processes such as piezoelectric, electromagnetic, thermoelectric, and triboelectric. Furthermore, the materials, applications, challenges, and future prospects of several nanogenerators are discussed.

Structural failures in the barge midship sections can cause operational delay, sinking, cargo loss and environmental damage. These failures can be generated by the barge and cargo weights, and wave load effects on the midships sections. These load types must be considered in the design of the barge midship sections. Here, we present the structural analysis of a barge midship section that has decreased up to 36.4% of its deck thickness caused by corrosion. This analysis is developed using finite element method (FEM) models that include the barge and cargo weights, and wave load effects. The FEM models regarded three cargo tanks in the midship section, containing the main longitudinal and transverse structural elements. In addition, the hull girder section modulus and the required deck thickness of the barge were calculated using Lloyd’s Register rules. These rules were applied to estimate the permissible bending stresses at deck and bottom plates under sagging and hogging conditions, which agreed well with those of the FEM models. Based on FEM models, the maximum compressive normal stress and von Mises stress of the hull girder structure were 175.54 MPa and 215.53 MPa, respectively. These stress values do not overcome the yield strength (250 MPa) of the barge material, allowing a safe structural behavior of the barge. The structural modeling of the barge midship section can predict its structural behavior under different sagging and hogging conditions, considering the cargo, weight and wave loads.

Ocean energy is an abundant, eco-friendly, and renewable energy resource that is useful for powering sensor networks connected to the maritime Internet of Things (MIoT). These sensor networks can be used to measure different marine environmental parameters that affect ocean infrastructure integrity and harm marine ecosystems. This ocean energy can be harnessed through hybrid nanogenerators that combine triboelectric nanogenerators, electromagnetic generators, piezoelectric nanogenerators, and pyroelectric generators. These nanogenerators have advantages such as high-power density, robust design, easy operating principle, and cost-effective fabrication. However, the performance of these nanogenerators can be affected by the wear of their main components, reduction of wave frequency and amplitude, extreme corrosion, and sea storms. To address these challenges, future research on hybrid nanogenerators must improve their mechanical strength, including materials and packages with anti-corrosion coatings. Herein, we present recent advances in the performance of different hybrid nanogenerators to harvest ocean energy, including various transduction mechanisms. Furthermore, this review reports potential applications of hybrid nanogenerators to power devices in marine infrastructure or serve as self-powered MIoT monitoring sensor networks. This review discusses key challenges that must be addressed to achieve the commercial success of these nanogenerators, regarding design strategies with advanced simulation models or digital twins. Also, these strategies must incorporate new materials that improve the performance, reliability, and integration of future nanogenerator array systems. Thus, optimized hybrid nanogenerators can represent a promising technology for ocean energy harvesting with application in the maritime industry.

Constantly growing environmental concerns focused on reducing pollution, in addition to rising fuel costs in recent years, have led the maritime industry to develop and implement fuel-saving solutions. Among them is the optimization of marine propeller efficiency, as marine propellers are a crucial part of ship’s propulsion system. During the initial design stage, selecting the optimal propeller is considered a multi-objective optimization process. This research focused on maximizing propeller open water efficiency, while minimizing engine brake power constrained by thrust and cavitation. Optimization was applied to Wageningen B-series propellers and conducted using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The algorithm selected optimum parameters to create the propeller model, which was then evaluated numerically through computational fluid dynamics (CFD) with a multiple reference frame (MRF) and under the SST k-ω turbulence model, to obtain the open water hydrodynamic characteristics. In addition, the cavitation effect was evaluated using the Zwart–Gerber–Belamri cavitation model. The numerical model results were validated through comparison with open water experimental data from the Netherlands Ship Model Basin for the Wageningen B-series propellers. The results showed errors of 3.29% and 2.01% in efficiency under noncavitating and cavitating conditions, respectively. Correct performance of the functions was shown, based on neural networks trained to estimate thrust and torque coefficients instead of polynomials. The proposed optimization process and numerical model are suitable for solving multi-objective optimization problems in the preliminary design of fixed-pitch marine propellers.

The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (C_L) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was modified by developing a genetic algorithm that operates with the IGP parameterization and performs the aerodynamic analysis using XFOIL in the MATLAB environment. Subsequently, a numerical model was made for each baseline and optimized airfoil using a commercial computational fluid dynamics (CFD) code to analyze the behavior of the lift coefficient. An increase in the average C_L was obtained for the Eppler 68, MH 70, and Wortmann FX 60-126 airfoils for angles of attack ranging from 0 to 10, obtaining increments of 17.243%, 14.967%, and 10.708%, respectively. Additionally, an average 5.027% uncertainty was obtained in lift coefficient calculations between XFOIL and CFD. The utility of the IGP method and genetic algorithms for parameterizing and optimizing airfoils was demonstrated. In addition, airfoils could be tailored for a specific UAV depending on the mission profile. Volume 2 of this study will include experimental data from wind tunnel.

Plastics are essential to technological and industrial development, yet their prevalent single-use life and poor recycling rates are contributing to escalating environmental concerns. Expanded polystyrene (EPS), although valued for being lightweight, durable, and insulating, poses a significant challenge as it is typically disposed of after a single use. Furthermore, traditional recycling is limited because it requires clean, well-separated waste. Therefore, it remains necessary to develop recycling strategies that maximize the value of plastics. To address this issue, the present work aims to provide a comparative evaluation of the synthesis and characterization of FeMg/Al₂O₃ and Fe/Al₂O₃-MgO as catalysts, along with an analysis of their catalytic performance in the pyrolysis of EPS waste at varying temperatures and catalyst loadings. The results showed an advantage in using catalysts in the pyrolysis of EPS waste; however, the FeMg/Al₂O₃ (15 wt.%) catalyst demonstrated the best efficiency in the pyrolysis of EPS waste at 400 °C, achieving 96% liquid yield and reducing reaction times by up to 45% due to its high metal dispersion and strong metal-support interaction, which promotes faster and more efficient conversion. In contrast, Fe/Al₂O₃-MgO showed lower catalytic performance, although it can offer lower synthesis costs and good thermal stability, making it more viable on a large scale. These findings represent a significant advance in catalytic EPS recycling, offering promising strategies to promote the circular economy of EPS and extend its useful life.