Composite materials are presented in a wide variety of industrial sectors as an alternative to traditionally used materials. In recent years, a new sector has increasingly used these kinds of materials: the manufacture of musical instruments. Resonances of different elements that make up the geometries of musical instruments are commonly used with the aim of enhancing aspects of the timbre. These are sensitive to the mechanical characteristics of the material, so it is important to guarantee the properties of the composite. To do this, it is not uncommon to use pre-impregnated fibers (prepregs) which allow fine control of final volumetric fractions of the composite. Autoclaving is a high-quality process used to guarantee the desired mechanical properties in a composite, reducing porosity and avoiding delamination, but significantly raising production costs. On the contrary, manufacture without autoclaving increases competitiveness by eliminating the costs associated with autoclave production. In this paper, differences in dynamic behavior are evaluated under free conditions of different Carbon Fiber Reinforced Epoxy (CFRE) prepreg boards, processed by autoclave and out-of-autoclave. The results of the complex module are presented according to the frequency, quantifying the variations in the vibratory behavior of the material due to the change of processing.

This work evaluates the use of structural aspects in the manufacture of drum shells based on their modal behavior. The drum shells are made of composite carbon fiber-reinforced epoxy (CFRE) due to the structural variables commonly used in the industry for the manufacture of these musical instruments. Musicians consider the shell of a membranophone to be responsible for the differences in timbre between different instruments. Normally, this variation focuses attention on the mechanical characteristics of the material and on the overall thickness of the cylinder that forms the shell. Some manufacturers, especially those that use metals and composites, resort to low thicknesses, below 2 mm, which forces them to use structural reinforcements at the edges of the cylindrical shell to avoid deformations due to the tension generated by the membranes. As shown in this research work, these structural elements have great relevance within the acoustic behavior of the drum shell. Comparisons are made among the frequencies obtained for the different vibrational modes by using finite element simulations, establishing the length of the structural solution previously mentioned and the number of plies of composite laminate as design variables, starting from the characteristics of a real case constructed with CFRE and concluding with experimental validation. The range of study is limited to the values of the frequencies generated by the membranes. The results demonstrate that the use of different manufacturing variables can lead to savings in production costs without compromising the modal behavior of the shell.

This article presents the design and manufacturing of a hydrogen-powered unmanned aquatic surface vehicle (USV) hull. The design process comprised three stages: (1) defining the requirements for a preliminary geometry, (2) verifying the hydrodynamic hull performance using computational fluid dynamics (CFD) simulations, and (3) experimentally validating the hydrodynamic hull performance and CFD analysis results through experimental fluid dynamics in a calm water towing tank. The manufacturing process utilized additive manufacturing technologies, such as fused granular fabrication and selective laser sintering, to produce the hull and other components, including the propeller and the rudder; thermoplastic materials with carbon fiber reinforcement were employed. The experimental results demonstrate that the optimized trimaran hull exhibited low hydrodynamic resistance (7.5 N), high stability, and a smooth flow around the hull (up to 2 m/s). The design and manufacturing of the USV hull met expectations from both hydrodynamic and structural perspectives, and future work was outlined to integrate a power plant, navigation system, and scientific equipment.

The limited availability of labelled visual data remains a major constraint for training reliable species classifiers in ecological applications. Although synthetic data generation using generative artificial intelligence represents a promising alternative, robust methodological frameworks are still lacking to evaluate its effectiveness and its ability to generalise to real-world data.In this work, we present a reproducible framework based on biologically informed prompt engineering to generate ecologically plausible synthetic data and systematically assess synthetic-to-real generalisation. Two widely used generative paradigms, Text-to-Video (T2V) and Image-to-Video (I2V), were employed to construct training datasets. These datasets were used to train five convolutional neural network architectures, ranging from lightweight models to pre-trained deep networks, using invasive psittacines as a case study.Evaluation on an independent set of unseen real-world images showed that both paradigms achieve comparable overall performance across architectures, with no statistically significant differences in F1-score. However, clear differences emerged in error profiles: models trained with I2V exhibited higher precision and fewer false positives, whereas those trained with T2V achieved higher recall at the cost of increased false positives. These patterns were consistent across runs, indicating that they reflect systematic differences between generative paradigms rather than random variability.The results demonstrate that synthetic video data can serve as a robust and cost-effective complement to real-world data in ecological classification tasks, provided that its generation and evaluation are embedded within a rigorous and reproducible methodological framework.The code and data used in this study are available for peer review in an anonymous private repository: