Joel Sena Sales Junior

This study presents a comprehensive parametric optimization of the blade geometry for the so-called Vertical Axis Autorotation Current Turbine (VAACT) using Computational Fluid Dynamics (CFD) simulations at high-blockage conditions. The optimization process aimed to minimize the resisting torque produced by the returning blade, the major contributor to performance loss in drag-type vertical axis turbines. The investigation was first conducted to assess the effects of maximum camber and its position on turbine efficiency. A response surface relating the power coefficient (C_P) to maximum camber (M), camber position (P), and tip speed ratio (TSR) was then generated and used as input for the optimization routine. The optimal configuration was M = 40%, P = 65%, and TSR = 1.06, achieving an efficiency of 40.68% at 21.4% blockage ratio. The enhanced blade demonstrated a 21% improvement in performance compared to the conventional S-shaped profile, primarily due to the reduction of resisting torque during the returning phase. The intra-cycle analysis showed that the optimized turbine allowed a better distribution of hydrodynamic effects along the cycle, improving efficiency. Flow field analysis confirmed that the optimized geometry delays vortex shedding and reduces pressure gradients along the returning blade, leading to improved hydrodynamic behavior. The results demonstrate this procedure offers an effective way for the design of vertical axis hydrokinetic turbines.

Autonomous surface vehicles (ASVs) have played a crucial role in various areas, including oceanographic research, environmental monitoring, and asset inspection. However, the high cost and proprietary nature of many platforms limit accessibility. Thus, this work introduces a low-cost, fully open-source ASV platform designed to support a wide range of applications, from academic research to community-driven monitoring projects, bridging the existing gap between low-cost prototyping and naval architecture-based ASV development. Featuring a modular 2 m hull design, the vehicle integrates off-the-shelf components and open-source software to ensure affordability, flexibility, and ease of replication. Field tests were conducted on Ilha do Fundão (Fundão Island), located within the campus of the Federal University of Rio de Janeiro (UFRJ), Brazil. All design files and code are released on GitHub (version 1.0.0) to encourage adoption and collaborative improvement.

Unmanned Surface Vehicles (USVs) have emerged as key enablers of autonomous maritime operations, offering innovative solutions across multiple industries, including defense, oceanography, offshore energy, and logistics. This review examines the current state of operative USVs, analyzing their technological evolution, design characteristics, and applications. The study highlights trends in autonomy, propulsion, endurance, and communication technologies, providing insights based on market-ready platforms. While USVs present significant advantages in terms of efficiency and operational safety, challenges such as regulatory constraints, cybersecurity risks, and limitations in autonomous decision-making persist. This paper aims to update researchers, policymakers, and industry stakeholders on the technological advancements and emerging trends shaping the future of unmanned vehicles.

The search for energy alternatives is becoming more important in the strategic development of countries, as global energy demand accelerates. The thermal energy in the oceans, the highest exploitation potential, is renewable and has the ability to remove heat from the oceans and carbonic gas from the atmosphere. In this study, we used the temperature results from the numerical model HYCOM for resoucers evaluation of Ocean Thermal Energy Conversion (OTEC). Based on these data, daily, monthly, seasonal and annual averages were calculated, allowing to evaluate the thermal gradient variability in the Blue Amazon, region where Brazil has sovereign rights for exploration, conservation and management of living and nonliving natural resources. Three thermal energy sites were obtained the definition of their viability and operational of his conversion by teorical OTEC plant throughout the period of the average. The brazilian northern region stands out with the higher energy potential between the surface and a depth range of 600m ≤ z ≥ 1000m, from the results we indicate that the Brazilian Ocean Thermal Energy Park (OTEP) is technically feasible for the operations of OTEC. However, form the economic perspective, results show that only portions closest to the continental shelf, have the capacity to operate.

The behavior of subsea equipment has been widely studied by companies to minimize risks during subsea installation, which brings huge costs to the operation. The prediction of equipment motions typically is accomplished by utilizing either commercial software or recommended practices from Classification Societies to comply with the minimum requirements for launching operations. This paper analyzes subsea installation in time and frequency domains using experimental, numerical, and analytical approaches. Experiments have been carried out at Instituto de Pesquisas Tecnológicas (IPT) to investigate the dependency of drag and added mass coefficients on Keulegan-Carpenter number and at Laboratory of Waves and Currents (LOC-COPPE/UFRJ) to study equipment and cable responses on the installation. A numerical model is made in OrcaFlex^® for determining the transmissibility of displacement and force in function of frequency ratio, and the time series of manifold responses. Linearized models from DNV [1] and the so-called natural KC (proposed in the present paper) are taken in the investigation and compared to previous methodologies. The natural KC approach arises as an innovative way of investigating subsea equipment as the literature only provides parametric analysis considering an arbitrary KC value (i.e., Pestana et al. [2]). The analyses notice a good agreement among experiments, OrcaFlex^® model and natural KC model whereas the curves found by the DNV method usually overpredict the response of subsea equipment, especially around resonance region.

When considering a system composed of a group of robots, swarm robotics is an approach that can be used to coordinate this group. These swarms can be inspired or not by social insects or other animal societies (Trianni, 2008), where basic behaviors are usually used to compose complex tasks. These previously mentioned basic behaviors have been studied for a long time, with applications, for example, to flocks, herds, and schools (Reynolds, 1987) and multi-robot teams (T. Balch & Arkin, 1998). Here we introduce PySwarming, a tool that makes easy the coordination of swarms and serves as a centerpiece, organizing different methods developed in the swarm robotics field. Its flexibility (written in Python) and customizability (easily customized by users) encourage interaction and scientific progress in the research community.