Search Results (2)

The technologically advanced learning ocean system—wave energy converter (TALOS-WEC) project addresses the urgent need for sustainable and efficient energy solutions by leveraging the vast potential of wave energy. This project presents a pioneering approach to wave energy capture through its unique multi-axis and omnidirectional point absorber design. Featuring a fully enclosed power take-off (PTO) system, the TALOS-WEC harnesses energy across six degrees of freedom (DoFs) using an innovative internal reaction mass (IRM) mechanism. This configuration enables efficient energy extraction from the relative motion between the IRM and the hull, aiming for energy conversion efficiencies ranging between 75–80% under optimal conditions, while ensuring enhanced durability in harsh marine environments. The system’s adaptability is reflected in its versatile geometric configurations, including triangular, octagonal, and circular designs, customised for diverse marine conditions. Developed at Lancaster University, UK, and supported by international collaborations, the TALOS-WEC project emphasises cutting-edge advancements in hydrodynamic modelling, geometric optimisation, and control systems. Computational methodologies leverage hybrid frequency-time domain models and advanced panel codes (WAMIT, HAMS, and NEMOH) to address non-linearities in the PTO system, ensuring precise simulations and optimal performance. Structured work packages (WPs) guide the project, addressing critical aspects such as energy capture optimisation, reliability enhancement, and cost-effectiveness through innovative monitoring and control strategies. This paper provides a comprehensive overview of the TALOS-WEC, detailing its conceptual design, development, and validation. Findings demonstrate TALOS’s potential to achieve scalable, efficient, and robust wave energy conversion, contributing to the broader advancement of renewable energy technologies. The results underscore the TALOS-WEC’s role as a cutting-edge solution for harnessing oceanic energy resources, offering perspectives into its commercial viability and future scalability. Full article

The Global Change Observation Mission-Climate (GCOM-C) is currently the only satellite sensor providing aerosol optical thickness (AOT) in the ultraviolet (UV) region during the morning overpass time. The observations in the UV region are important to detect the presence of absorbing aerosols in the atmosphere. The recently available GCOM-C dataset of AOT at 380 nm for January to September 2019 were evaluated using ground-based SKYNET sky radiometer measurements at Chiba, Japan (35.62° N, 140.10° E) and Phimai, central Thailand (15.18° N, 102.56° E), representing urban and rural sites, respectively. AOT retrieved from sky radiometer observations in Chiba and Phimai was compared with coincident AERONET and multi-axis differential optical absorption spectroscopy (MAX-DOAS) AOT values, respectively. Under clear sky conditions, the datasets showed good agreement. The sky radiometer and GCOM-C AOT values showed a positive correlation (R) of ~0.73 for both sites, and agreement between the datasets was mostly within ±0.2 (the number of coincident points at both sites was less than 50 for the coincidence criterion of ≤30 km). At Chiba, greater differences in the AOT values were primarily related to cloud screening in the datasets. The mean bias error (MBE) (GCOM-C – sky radiometer) for the Chiba site was −0.02 for a coincidence criterion of ≤10 km. For a similar coincidence criterion, the MBE values were higher for observations at the Phimai site. This difference was potentially related to the strong influence of biomass burning during the dry season (Jan–Apr). The diurnal variations in AOT, inferred from the combination of GCOM-C and ozone monitoring instrument (OMI) observations, showed good agreement with the sky radiometer data, despite the differences in the absolute AOT values. Over Phimai, the AOT diurnal variations from the satellite and sky radiometer observations were different, likely due to the large differences in the AOT values during the dry season. Full article