TRAINING BOAT DIGITAL TWIN (TRABODIT)
Principal researcher: José Antonio González Prieto
The main objective of the Training Boat Digital Twin (TraBoDiT) research project is to develop a methodology for the creation of digital twins from existing boats (training boats). Its development has a relevant importance in procedures such as:
- Active safety systems and predictive control.
- Fault tolerant systems and predictive maintenance.
- Collaborative systems.
- Impact avoidance.
The use of simulators that integrate models with fidelity with respect to the maneuverability conditions of the boats that military personnel will handle during their training sessions is a particularly relevant objective in the educational field. TraBoDiT proposes the creation and validation of models related to the dynamics of a naval platform, for which it is proposed to install a sensor network in the training boats and use techniques based on dynamic models and data analysis tools (machine learning) to merge the recorded information. It is intended that the models obtained as a result of TraBoDiT can be integrated, in a second stage of development, in the SIMNAV simulator of the ENM so that they simulate, with a certain level of accuracy and robustness, the behavior of real boats.
OSINT PLATFORM BASED ON AI TECHNIQUES FOR MONITORING THE DEFENSE COMMUNITY ON (POSINTIA)
Principal researcher: Norberto Fernández García
The objective of this project is the development of an OSINT platform (Open Source Intelligence or intelligence produced from public information) based on artificial intelligence techniques, for the monitoring of the community of users of the social network Twitter of interest for Defense.
The main expected result of the project is the development of a technological demonstrator of a system that, in an automated way (although potentially supervised by humans), allows to extract relevant information from the community of users on Twitter that publishes content (in Spanish and/or English) related to the field of Defense. To this end, a set of requirements, seed accounts, keywords and/or topics of interest provided by experts in the field of Defense will be used as a starting point. With this information, we will search for and select (using multivariate statistical techniques, artificial intelligence, etc.) Twitter users who are candidates to be included in the community to be observed, and then extract (using natural language processing techniques, event or anomaly detection, etc.) public information from their accounts. Among the information of potential interest to be obtained from the system, in addition to the community itself, would be: alerts of misuse of information, thematic trends, evolution of the community, etc.
LOW-COST BATHYMETRIC FRAMEWORK FOR INFANTRY OPERATIONS IN SHALLOW WATER (LAMINAE)
Principal researcher: Iván Puente Luna
The determination of detailed bathymetric information is key for near-shore activities, such as seabed reconnaissance missions carried out by Marine Corps units as part of amphibious operations, which are currently performed manually by divers. It also has applications in coastal engineering, sedimentary processes, archaeological mapping or biological research.
This project proposes the development and integration of a framework composed of a low-cost Unmanned Surface Vehicle (USV), with an underwater camera and a positioning system, and a Spatial Data Infrastructure (SDI) for the management and use of the data and information generated from the photogrammetric models. In addition, the SDI will integrate other sources of open data at both national and European level, including State Ports (SP), the Hydrographic Institute of the Navy (HIM) and EMODnet.
This tool will support the study, analysis, evolution and marine planning tasks carried out by the Marines during amphibious operations.
ADDITIVE MANUFACTURING OF NEW MATERIALS FOR PHOTOCATALYTIC WATER TREATMENT (FAMOH2O)
Principal researcher: Jesús del Val García
One of the major current problems in water treatment systems is the deficient elimination of micropollutants of pharmaceutical and personal care origin, whose presence has increased significantly in recent decades due to the high consumption of medicines and cosmetic products in today’s society. Due to the fact that water treatment plants are not usually designed for the presence of this type of pollutants, it is necessary to adopt complementary measures that allow their correct elimination.
With this problem in mind, the present project aims to eliminate organic compounds in wastewater by combining photocatalysis with additive manufacturing. Starting from a photocatalytic material generated by the sol-gel technique, based on silane/siloxane and titanium oxide doped with nanoparticles as photocatalyst, a three-dimensional structure of hybrid material, highly porous, with a high surface area and high regeneration capacity (reusable), easily adaptable to water treatment systems, and allowing the degradation of pollutants at low cost, will be manufactured by 3D printing.
FUNDAMENTALS OF RECOVERY OF SOIL CONTAMINATED WITH ESCHERICHIA COLI AND ANTIBIOTICS THROUGH MYCORREDIATION STRATEGIES (FUNGI)
Principal researcher: Alicia Vázquez Carpentier
The presence of E. coli in soils can have consequences on crop growth and water contamination, due to the possibility of being washed into the groundwater table during heavy rainfall events. On the other hand, current purification systems are not specifically designed to remove antibiotics from water.
The main objective of this project is to evaluate the bioremediation capacity of fungi in soils contaminated with Escherichia coli and antibiotics. Mycoremediation techniques with the potential to mineralize organic pollutants in situ with the minimum disturbance of the system will be used, through the in vitro culture of several types of mycelia that will be exposed to varying concentrations of the selected pollutants, evaluating the kinetics of mineralization, the evaluation of toxicity and the quality of the resulting product.
ANALYSIS OF MIMO CONFIGURATIONS TO IMPROVE THE PERFORMANCE OF PASSIVE RADARS WITH APPLICATION TO THE MARITIME FIELD (MIRAPAMAR)
Principal researcher: José María Núñez Ortuño
Multiple-input multiple-output (MIMO) radars are a recent development in the radar world inspired by the previous success of MIMO techniques in communications. These technologies can improve detection capability and coverage, improving conventional passive radars based on array processing.
The objective of the project is to analyze and evaluate the different MIMO techniques that can be used in a passive radar system in the maritime and/or naval field in order to improve the performance in the detection of low reflectivity targets in coastal environments of complex orography.
After the evaluation of different alternatives, it is intended to develop a small demonstrator to evaluate these schemes in a scenario of maritime targets and digital terrestrial television (DVB-T) illuminators.
CONSTRUCCIÓN DE UNA PLANTA PILOTO DE PRODUCCIÓN, PURIFICACIÓN Y ALMACENAMIENTO DE HIDRÓGENO CON HIDRUROS METÁLICOS A PARTIR DE GLICERINA PARA USO EN SUBMARINOS CON SISTEMAS AIP DE PILA DE COMBUSTIBLE (ProPuAlH2)
Principal researcher: Rocío Maceiras Castro
This project proposes the construction of a pilot plant for obtaining, purifying, compressing and storing hydrogen from glycerin. This completes the process initiated with the project awarded in the previous call, which consisted of the construction of a reformer for obtaining hydrogen from glycerin. In this case, the purification, compression and storage in metal hydrides of the hydrogen produced in the reforming process is added.
In parallel to the process of obtaining hydrogen, a global simulation of the process is proposed based on experimental data. These simulations would allow its subsequent scaling and thus to analyze the feasibility of its implementation in submarines, for an Air Independent Propulsion (AIP) system in fuel cell submarines.
SAAM PROJECT: ASSISTED POSITIONING SYSTEM FOR AT-SEA PROVISIONING OF NAVY SHIPS
Principal researcher: Paula Gómez Pérez
Fleet ships often spend long periods of time at sea without making stopovers, so it is common for them to need refuelling on the high seas. In the refuelling manoeuvre, the ship requiring refuelling must sail parallel to the logistic support ship to exchange supplies, materials or even personnel. Maintaining direction and speed in conditions of low visibility or rough seas can be extremely difficult and dangerous. Currently, the distance line is used as a reference, but it is insufficient and unreliable.
The SAAM Project implements an Assisted Positioning System for the at-sea provisioning manoeuvre, providing accurate information in real time and under a highly intuitive interface of the navigation data of the receiving and supplying ship, including: lateral and ahead distance, speeds of both ships, and dangerous trend indicators.
VIRTUAL BATTLE LABORATORY FOR IMMERSIVE FIREARM SHOOTING TRAINING (BATTLELAB360)
Principal Investigator: Xavier Núñez Nieto
Fourth Generation Industry (i4.0) has meant a significant increase in the consolidation of the digital world within the Armed Forces (FAS). This project proposes the use of this technology for the hyper-realistic 3D modelling of a battle lab (battlelab), which will serve as a virtual training platform for the military practice of shooting with firearms. By combining various i4.0 techniques, the characteristic graphical environment and user/device interaction will be recreated. In addition, the different Rules of Engagement (ROA) involved in the real battlefield will be recreated and a fully immersive user experience will be obtained. All of this is in accordance with the lines of interest established by the Technology and Innovation Strategy (ETID) of the Ministry of Defence, as described in the Technological Goal (MT.6.4.1.) referring to the modelling of the battlefield and its environment.
BIORREACTOR DESIGN AND OPTIMISATION FOR THE ELIMINATION OF NUTRIENTS AND PHARMACEUTICAL COMPOUNDS IN WATER (Acronym: BNC)
Principal Investigator: Rosa Devesa Rey
The main objective of this project is the design and optimisation of a bioreactor for the simultaneous removal of nutrients and pharmaceutical micropollutants from water. The elimination of the proposed compounds will be carried out through the design of a bioreactor equipped with an active filter with a high surface area and biological activity: on the one hand, a ceramic filter functionalised with fibres of an adsorbent material will be manufactured in the laboratory by electrospinning, obtaining a material with a high surface area and uniform pore size, suitable for the adsorption of phosphates. This filter would also allow the eventual desorption and recovery of phosphate, which gives a geostrategic dimension to this stage of the project. On the other hand, the bioreactor will favour the growth of a biofilm composed of heterotrophic microorganisms, photosynthetic bacteria and algae, connected in a complex matrix of extracellular polymeric substances (SPE).
The effect of the biofilm on the reduction and/or detoxification of contaminated water, the role of the active filter in the retention of phosphate and the optimisation of the bioreactor’s operating parameters are the main points of the project: on the one hand, the detoxification of pharmaceutical compounds treated with a bioreactor will be investigated, checking their mitigation with chromatographic techniques and their detoxification by means of phytotoxicity tests; on the other hand, the efficiency of the adsorption process referring to phosphates will be evaluated using spectrophotometric techniques measured in the water column. As a final stage of the project, the data obtained will be used to obtain a mathematical model that allows the conditions that occur in a real scenario to be replicated, with an acceptable degree of error.
STUDY OF RADON GAS BEHAVIOUR IN ENCLOSED SPACES AND INDOOR ENVIRONMENT QUALITY CONTROL THROUGH ENERGY-EFFICIENT VENTILATION (RNVENT)
Principal Investigator: Arturo González Gil
The aim of this project is to advance our knowledge on the behaviour of radon gas in indoor spaces and to optimise air renewal as a mitigation measure. Firstly, the experimental study of the different factors that determine the evolution of radon gas in enclosed spaces, including meteorological, constructive and geological factors, will be addressed. As a methodological novelty in this field of study, georadar and advanced acoustic techniques will be applied. Subsequently, a numerical model will be developed to evaluate and predict the behaviour of radon gas in different ventilation scenarios. A transitory model will also be developed to simulate the operation of the ventilation and air-conditioning systems of the premises under study in different working conditions. The main outcome of the project will be the development of a comprehensive tool to facilitate the design of optimal ventilation strategies to ensure adequate levels of air quality and thermal comfort with minimum energy demand.
DESIGN AND DEVELOPMENT OF A HYDROGEN PRODUCTION PLANT BY REFORMING GLYCERINE FOR POSSIBLE IMPLEMENTATION IN SUBMARINES WITH AIP TECHNOLOGY
Principal Investigator: Rocío Maceiras Castro
This project proposes the study of the glycerine reforming technique for the production of hydrogen and its possible use “in situ” in fuel cells. This whole process of hydrogen production and use would be oriented towards a possible implementation in submarines with air-independent propulsion systems, commonly known as AIP or anaerobic systems. To this end, hydrogen production is proposed, using the steam reforming technique applied to glycerine.
In order to achieve this objective, the construction of a steam reformer at pilot plant level and its subsequent commissioning is proposed. Another very important aspect to be taken into account is the purity of the hydrogen obtained in the reforming process, since the presence of impurities can poison the catalyst of the cell. In order to minimise this circumstance and achieve the operating ratios of the fuel cell, based on the experimental data, a hydrogen purification stage will be simulated.
STUDY OF THE ADDITIVE MANUFACTURING OF MACRO-COMPOUNDS WITH THE ADDITION OF PHASE-CHANGE MATERIALS
Principal Investigator: Guillermo Lareo Calviño
Phase change materials (PCMs) are one of the most widely used options as a passive energy storage method, given their great thermal capacity to absorb-release heat in solid-liquid state changes, and the materials used can do so in applications that allow thermal energy peaks to be absorbed, such as the heating of a battery.
On the other hand, additive manufacturing is revolutionising the field of customised manufacturing. The current manufacturing of PCM in powder or plate form makes heat absorption difficult because of the irregular surfaces or small dimensions of the parts. It is in these scenarios that the need arises to create PCM coatings adapted to the surface to be treated.
Therefore, the combination of additive manufacturing and materials is a perfect solution to this problem, which is the objective of the work, given that there is no established development to date to provide PCM properties to additively manufactured objects.
SIRENA – ARTIFICIAL INTELLIGENCE SYSTEM FOR MARITIME ENVIRONMENT RECOGNITION
Principal Investigator: Miguel Rodelgo Lacruz
The aim of the project is to develop a technological demonstrator that allows the application of Artificial Intelligence techniques to Maritime Environment Awareness (MEA) in order to improve the operational procedures developed by the Navy from the Maritime Action Operations and Surveillance Centre (COVAM), responsible for the supervision of maritime areas of national interest. Specifically, the demonstrator will receive the AIS (Automatic Identification System) data stream containing real-time ship and positioning information, and will use data analysis and artificial intelligence techniques to detect scenarios and anomalies of interest defined by the COVAM. Due to the high rate of messages transmitted, it is necessary to analyse and select Big Data technologies for the storage and processing of information in real time and the research and development of Data Analytics and Machine Learning techniques to process and extract knowledge from the large volume of data involved.
DEVELOPMENT OF A DEMONSTRATOR FOR UNDERWATER ACOUSTIC COMMUNICATIONS IN ULF USING WS PROTOCOLS
Principal Investigator: José María Núñez Ortuño
In ultra-low frequency (ULF) underwater acoustic communications, the attenuation of the marine environment is low, so there is great potential for very long distance contacts. However, the use of ULF carriers leads to very narrow bandwidths and therefore a very low transfer rate. On the other hand, the heterogeneity of the underwater environment over long distances means that the received signal suffers from fading and has a low signal-to-noise ratio.
In very long distance HF radio communications, digital communications protocols are used, characterised by the use of Weak Signals (WS) in reception, but robust against channel fading.
Given the analogy between the radio channel for ionospheric communications and the underwater channel, this project aims to investigate the application of WS protocols in underwater acoustic communications.
It is proposed to develop a demonstrator to study the performance of WS protocols.
As an example of application, long-distance data communication using simple messages and voice communication using a low-speed speech-to-text-to-data-to-text-to-voice conversion technique will be tested.
PROCESSING AUDIO AND NATURAL LANGUAGE FOR NAVAL COMMUNICATIONS TASKS (PANNACOTA)
Principal Investigator: Milagros Fernández Gavilanes
The oceans are an important means of communication and transport. Global maritime traffic density has experienced substantial growth in recent years. This growth has led to an increase in VHF band radio communications. Considering that the number of simultaneous voice communications that can be handled by a human operator is limited, monitoring these exchanges would require more personnel than is available for the task.
The PANNACOTA project aims to obtain a system to support the monitoring of radio conversations in the VHF band with the capacity to automatically detect those voice communications of relevance. These selected conversations will be analysed using artificial intelligence techniques, specifically natural language processing, with the aim of extracting information that could be of potential interest to operators involved in surveillance tasks.