Planning for offshore wind energy projects is intricate due to the consideration of multiple variables in identifying optimal project areas. The primary challenge lies in locating suitable sites, a process that often necessitates extensive feasibility studies spanning several years. The primary goal of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize criteria and sub-criteria, facilitating decision-making in choosing appropriate locations for offshore wind projects in the Colombian Caribbean Sea. The weights derived from FAHP were utilized in a Geographic Information System (GIS) to analyze the physical characteristics of the Caribbean Sea’s surface. This tool plays a critical role in evaluating and selecting sites that fulfill established criteria, providing a database of indicators and map visualizations. Four criteria were defined: technical, environmental, social, and economic, along with fourteen sub-criteria, which were prioritized through FAHP based on expert judgment. The results revealed that the most relevant sub-criteria were protected areas and wind speed. Utilizing the ArcGIS Pro software, five zones meeting the predetermined criteria were identified, defining the most feasible areas for offshore wind farm installation, located in the departments of Guajira, Magdalena, Atlántico and Bolívar. The GIS–FAHP methods proved to be useful for feasibility analysis.

The electrification of industrial processes offers sustainable opportunities for reducing carbon footprints and enhancing energy efficiency in the chemical industry. This paper presents an overview of recent research developments in incorporating electrical energy as a replacement for conventional thermal sources like gas and coal in industrial sectors. A literature review was conducted, identifying 70 relevant articles published until September 2020. The topics cover applications for industrial hydrogen generation processes and others, heat pumps, heat pumps, vapor re-compression systems, electric and magnetic fields as heat sources, nanoparticles for improved heat exchange, and ionized gases (plasma) in heating systems. While the application of industrial electrification shows promise globally, its sustainability depends on the efficiency and cost of electrical energy production and transportation at the regional and national levels. Among the various technologies, heat pumps integrated with vapor re-compression systems (VCR) for chemical processes, particularly in industrial distillation product separation columns, appear to be the most viable and widely applicable for waste heat recovery in the near future. Other technologies like electrochemical, plasma, microwave, magnetic, and electric field heating are still in the early stages of development or are limited to specific pilot or laboratory-scale processes.

The optimal extubating moment is still a challenge in clinical practice. Respiratory pattern variability analysis in patients assisted through mechanical ventilation to identify this optimal moment could contribute to this process. This work proposes the analysis of this variability using several time series obtained from the respiratory flow and electrocardiogram signals, applying techniques based on artificial intelligence. 154 patients undergoing the extubating process were classified in three groups: successful group, patients who failed during weaning process, and patients who after extubating failed before 48 hours and need to reintubated. Power Spectral Density and time-frequency domain analysis were applied, computing Discrete Wavelet Transform. A new Q index was proposed to determine the most relevant parameters and the best decomposition level to discriminate between groups. Forward selection and bidirectional techniques were implemented to reduce dimensionality. Linear Discriminant Analysis and Neural Networks methods were implemented to classify these patients. The best results in terms of accuracy were, 84.61 ± 3.1% for successful versus failure groups, 86.90 ± 1.0% for successful versus reintubated groups, and 91.62 ± 4.9% comparing the failure and reintubated groups. Parameters related to Q index and Neural Networks classification presented the best performance in the classification of these patients.

The development of a prototype linear solar collector Type Fresnel, has a purpose the use of direct solar heat radiation for water heating and/or steam production, as an alternative to supply conventional water heating systems or steam generators, which consume energy from fossil fuels. For the development of the system, used the solar radiation of the UTS, located in Bucaramanga, Colombia, is identify the mathematical models to perform the sizing, then materials based on technical specifications and availability in Colombia, in order to perform the assembly and field tests, measuring the ambient and in the collector temperature to determine the efficiency of the model. It should be noted that, the model presented does not have a control system for flow, temperature, pressure and level, it has no solar tracking of any kind; Its movement was done manually with each reflex. Finally, the model does not have a hydraulic system forced, and has a preheater at the entry of the concentration point.

Subsequent to the study of the energy demand and the evaluation of possible available resources in the remote area of Riosucio, Chocó region, Colombia, an analysis is performed on the implementation of three alternative systems of power generation. The first is a micro hydroelectric power station on the Truando River, which includes the design using HOMER software simulation, the costs of building and implementation, and its share in the energy mix. The second system is an array of photovoltaic panels in isolated configuration. This will include the design, via HOMER software simulation, of batteries, panel distribution, inverters, and connections, for a usable specific area restricted by the limited solar resource of the area. Finally, wind power is analyzed, a system that will include the determination of the most suitable turbine for the available wind resource in the area, as well as the analysis of the ideal quantity of wind generators based on its share in the energy mix and associated costs. For each of the assessed systems, a financial analysis and the feasibility are obtained, based on the investment, percentage of energy, and the electricity savings for each of the homes.