Experimental investigation of the physics of Electrodeless Plasma Thrusters for in-space propulsion
Supervisors
Jaume Navarro Cavallé (UC3M)
Abstract
The objectives of this thesis are to clarify the main physical mechanisms governing plasma transport and wave coupling phenomena in Electrodeless Plasma Thrusters (EPTs) and their magnetic nozzles (MNs), and to advance the implementation of cutting-edge diagnostics, beyond the current state of the art, for the characterization and validation of EPTs.
ZARATHUSTRA (Revolutionizing advanced electrodeless plasma thrusters for space transportation) ERC-ZARATHUSTRA project, European Research Council, ERC-Starting Grant program. Grant number: 950466. Principal Investigator: Mario Merino.
Funding entity and Program: Horizon MSCA fellowship (HORIZON-MSCA-2022-DN-01)
PhD Thesis
Low-order Modelling and Compressed Sensing for Real-time Flow Modelling in Operating Rooms
Supervisors
Andrea Ianiro (UC3M)
Abstract
This research aims to develop tools for real-time analysis of dynamic airflow in operating rooms using limited measurements. It focuses on creating low-order models for airflow in healthcare facilities, enhancing air quality management, and contributing to safer, more efficient hospital environments and better patient outcomes.
European Union’s Horizon Europe research and innovation program under the Marie Sklodowska-Curie (HORIZON-MSCA-2022-DN-01, project no 101119726)
Ultra-Broadband Wireless Communications Systems Development
Supervisors
Guillermo Carpintero (UC3M) and Alejandro Rivera (LeapWave Technologies)
Abstract
The objective of this work is to develop an ultra-wideband wireless communication system for millimeter and sub-millimeter mobile communications. This system will work from 50 GHz up to 500 GHz. Its central frequency and its bandwidth will be freely set inside said frequency range. All its millimeter and sub-millimeter components will be integrated, which will lead to a compact and cost-competitive device.
Turbulent transport characterization in Hall thruster
Supervisors
Eduardo Ahedo (UC3M) & Adrián Dominguez Vazquez (Universidad de Malaga)
Abstract
Instabilities and associated turbulence are ubiquitous in magnetized propulsion plasmas. They increase transport perpendicular to the magnetic field and degrade confinement. Turbulence occurs over a wide range of wavelengths (from fluid-dynamic to cyclotronic and electrostatic) and frequencies (from a few kHz to tens of MHz). The most studied and interesting case is that of the Hall Effect Thruster (HET). Since its conception, it has been known that some instabilities substantially increase transport perpendicular to the magnetic field. This has a negative impact on energy efficiency, a key parameter for any space engine. Although significant advances have been made, a solid turbulence model that determines the main instability, its intensity, and characteristics in terms of plasma parameters has yet to be established and implemented in HET simulation codes.
Project participation
HEEP – Propulsión Electromagnética por efecto Hall
Ref.No.: PID2022-140035OB-I00
Funding Entity: Agencia Estatal de Investigación (AEI)
Aircraft Trajectory Optimization using SAF and Climate Change
Supervisors
Manuel Soler Arnedo (UC3M) & Maria Cerezo Magaña (UC3M)
Abstract
Currently, there are many studies on the optimization of trajectories using conventional fuel. In order to achieve the goal of global net-zero emissions by 2050 (COP26) aligned with global warning reduction plans, this research will aim at adapting the current models for conventional fuels to Sustainable Aviation Fuels (SAF).
Project participation
REFMAP – Reducing Environmental Footprint through transformative Multi-scale Aviation Planning by the European Commission under Grant 101096698
Optical Navigation and Guidance for Safe and Precise Lunar Landing
Supervisors
Manuel Sanjurjo Rivo (UC3M)
Abstract
New Lunar landing missions are being developed and others are being planned for the near future. The NASA Precision Landing Challenge (2022) considers the need for new technologies to make landing in polar areas, shadow and dark, possible. Optical technologies for lunar landing may serve several goals and may be exploited along several stages of an S/C orbiting the Moon: S/C localization, terrain relative navigation (TRN), and hazard detection and avoidance (HDA). Also, they should be integrated with the guidance, navigation and control (GNC) mechanisms of the S/C mission.
The goals of this thesis are:
1. Developing a localization method for an S/C or vehicle orbiting the Moon.
The data set will consist of rendered synthetic images using a Python programming pipeline. The methodology will consist of the use of deep CNN for localization and attitude estimation, based on place recognition for different trajectories (orbital, powered descent) and with generalization ability
2. Study the feasibility of terrain relative navigation method based on crater (or other features).
3. Developing autonomous hazard detection and avoidance algorithms.
A pipeline for 3d landing simulation and study of several HDA algorithms will be deployed.
4. Guidance, navigation, and control.
According to results from previous sections, a 3d, lossless convexification method for moon descent and landing will be developed.
Design and optimisation methodology for hydrogen-powered aircraft development and environmental impact assessment
Supervisors
Andrea Cini (UC3M) & Marco Raiola (UC3M)
Abstract
An efficient powertrain/airframe integration is required to offset the weight and performance penalties caused by the technology lack of maturity. All the aircraft conceptual design and optimisation modules will be adapted to allow the H2-fuelled powertrain integration and the airliner performance and operational capability assessment. Structural weight will be computed by means of GFEM-based airframe sizing procedures owing to the lack of experience-based weight estimation correlation formulas for H2-fuelled airliner. Reduced Order Models (ROMs) will be generated from the FE sizing and implemented on the optimisation for fast and computational cost-effective weight estimations.
A tool, able to predict the acoustic footprint has to be integrated within the optimisation. Different models for propeller noise and aerodynamics with different degrees of fidelity will be identified and implemented. While simplest model can be based on semiempirical correlations, more refined implementations can rely on physically grounded low-fidelity models for the aerodynamics (e.g. Blade-Element Momentum Theory, Blade Vortex Theory) and aeroacoustics analogies (e.g. Ffowcs Williams-Hawkings Analogy) and derived models (e.g. Hanson’s method) for the noise. Blade-wake and wake-airframe interaction problems will be accounted in the modelling. The models will be then validated against high fidelity data, either proceeding form simulations or experiments where available. To this purpose high-fidelity propeller URANS/LES simulations in commercial CFD solvers which will serve as a baseline for the assessment of the developed models will be developed.
The optimisation platform will also allow airliner mission performance evaluation and operational capabilities review. Airworthiness requirements will drive the powertrain configuration sizing and selection in terms of engine inoperative conditions, fire protection and reliability. Operation capability prediction methods and strategies will be implemented to evaluate aircraft turnaround time, 24h flight capabilities, and the impact of ground handling on airport infrastructures and procedure. A conceptual design cost model will be developed as well to assess the economic viability of H2 powered short-range airliner. The environmental benefits of the novel H2 powered airliners will be quantified by Life Cycle Assessment (LCA) method, assessing the potential environmental impact of a product system during its entire life cycle.
Identification of actuation manifolds in wall-bounded flows
Supervisors
Stefano Discetti (UC3M) and Andrea Ianiro (UC3M)
Abstract
Closed-loop turbulence control holds the promise of significantly enhancing efficiency and reducing the environmental impact in various domains, including transportation, energy production, and industrial processes. Nevertheless, the complex and multi-scale nature of turbulence poses a challenge for real-time sensing strategies, necessitating a low-dimensional model to efficiently select the most appropriate control measures. In this context, reduced order models and dimensionality reduction become crucial. Reduced order models based on coherent structures have been obtained for several flows and it is often feasible to identify low-dimensional representations of the dynamics of uncontrolled flows. Such low-dimensional representations lead to the identification of n-dimensional surfaces (referred to as manifolds) over which flow systems may “live”. To date, however, this is still a relatively unexplored territory when dealing with flow control scenarios. Identifying actuation manifolds, i.e., manifolds of systems under prescribed control laws, would be a key enabler for the future of closed-loop control of turbulent flows.
This thesis will explore whether an actuation manifold can be identified in wall-bounded flows in presence of control actions, which can be in the form of pulsed jets, plasma actuators, or moving parts. Furthermore, it will be explored the possibility to map the full state of the flow on the manifold coordinates, to use it as a guidance for the definition of optimal control strategies, as well as to interpret black-box strategies such as those based on machine learning techniques. Efforts will be made to ensure that the resulting control laws are straightforward and interpretable, offering valuable insights from laboratory experiments.
Project participation
EXCALIBUR – Extracción de estrategias de aprendizaje automático para el control de flujos turbulentos
Ref.No.: PID2022-138314NB-I00
Funding Entity: Agencia Estatal de Investigación (AEI)
Experimental characterization of electrodeless plasma thrusters for very low Earth Orbit applications
Supervisors
Pablo Fajardo Peña (UC3M) and Jaume Navarro Cavallé (UC3M)
Abstract
In the last years, the space industry has explored the development of different technologies to exploit very low altitude orbits. In this frame, air-breathing electric propulsion (ABEP) has been underlined as a good solution. This Thesis will develop or readapt EPT prototypes, as well as the required diagnostics, to explore the feasibility of EPT for the ABEP concept.
SUPERLEO – PROPELENTES SOSTENIBLES PARA MOTORES DE PLASMA EN ORBITA TERRESTRE MUY BAJA
Funded by Agencia Estatal de Investigación (AEI) Grant: TED2021-132484B-I00
ADAPT: Propulsión de plasma avanzada para misiones espaciales: modelado y validación experimental Grant Number: PID2023-150052OB-I00 Funding Entity: AGENCIA ESTATAL DE INVESTIGACION (AEI) Desde 01/01/2025
Carlos Sanmiguel Vila (INTA-UC3M) & Rodrigo Castellanos (INTA)
Abstract
In the rapidly evolving automotive industry, the intricacies of aerodynamics demand fresh approaches for swift, reliable, and efficient solutions. This thesis delves into data-driven methods, offering a comprehensive perspective on optimising a road vehicle’s aerodynamic shape from a holistic point of view, minimising its aerodynamic resistance, and ensuring stability via lift balance.
Funding entity: Doctorado Industrial Comunidad de Madrid
PhD Thesis
Methods for orbiting objects characterization and space traffic management
Supervisors
Manuel Sanjurjo Rivo (UC3M) & Diego Escobar Antón (GMV Aerospace and Defence)
Abstract
The objective of this PhD is to develop methods for estimating physical properties (shape, size, materials…) and the attitude of Earth orbiting objects. In the frame of Space Traffic Management (STM), this PhD also aims at developing methods for predicting the population of orbiting objects, quantifying the orbital capacity and mitigating the risk of in-orbit collisions.
Funding entity: Doctorado Industrial Comunidad de Madrid
PhD Thesis
Operations and Propulsion Maneuver Planning in Satellites Based on Digital Twins and Multidisciplinary Optimization
Supervisors
Manuel Sanjurjo Rivo (UC3M) & Daniel González Arribas (Ienai SPACE)
Abstract
The thesis proposes to address challenges in small satellite-based space missions and orbital constellations. These challenges include the need to maneuver satellites in orbit to modify their orbits, avoid collisions, and deorbit in a controlled manner. Currently, electric propulsion, despite its lower efficiency compared to chemical propulsion, is preferred due to mass and volume constraints. However, it requires more complex operational planning, interfering with nominal operations. The use of digital twins, simulations, and optimization algorithms are proposed to solve these challenges. Digital twins translate the physical and logical configuration of the system into models that can be simulated. These simulations are then used by multidisciplinary optimization algorithms and sensitivity analysis tools to design and evaluate the satellite, its operations, and maneuvers. The proposed approach also allows managing uncertainties during the mission, producing solutions that meet requirements and maximize performance in various scenarios. Additionally, the proposed methodology enables integrating mobility operations with other satellite operations, improving the overall efficiency of the mission.
Industrial PhD granted by Comunity of Madrid, carried out within ienai SPACE
Analysis of the plasma discharge in a radiofrequency ion thruster
Supervisors
Eduardo Ahedo (UC3M)
Abstract
The overall objective of the research is to achieve an in-depth understanding of the complex physics of plasma discharge in Radio-Frequency Ion Thrusters (RIT) and the influence of design parameters. Special attention will be given to identifying physical limits in the engine’s performance through the utilization of numerical codes.
Prediction of adverse weather events and climate impact using neural networks
Supervisors
Manuel Soler (UC3M) & Javier García-Heras (UC3M)
Abstract
Meteorology and aviation share the same object, the atmosphere, and are linked by a common history. Each pushes the other in the quest for safety (25% of air accidents are associated accidents are associated with a meteorological cause) and improved performance (air delays in Europe cost more than 1 billion a year to airlines, at least as much as air navigation charges. Air Navigation Charges (ANC). On average, 5% of delays in Europe are weather-related). It is therefore vital to improve our methods of forecasting this phenomenon. The idea of this work is to use AI methods to perform nowcasting (0-2h) and downscaling. We will study the performance of physically constrained architectures (PINNs) on weather observations (stations, satellite, aircraft observations, etc …)
KAIROS
Horizon Europe (HORIZON) Call: HORIZON-SESAR-2022-DES-IR-01-WA5-1 Grant No 101114701
Prediction and control of low-Reynolds aerodynamics in atmospheric turbulence
Supervisors
Alberto Vela (UC3M)
Abstract
This research will explore the impact of free-stream turbulent perturbations on the aerodynamics of airfoils and wings experiencing relatively low-Reynolds-number flow conditions. Such setting is representative for micro-aerial vehicles (MAVs) typically flying at low flight speed and altitudes well within the so-called atmospheric boundary layer (ABL), resulting in conditions where the turbulence intensity is much stronger than in more conventional aeronautical applications. Furthermore, the relatively small size of these devices is often comparable to the integral length-scale of the turbulent disturbances, another peculiar feature with a potentially dramatic influence on the aerodynamic performance. Because of this, understanding and predicting the impact of turbulence on the flight performance is key to design passive and active control strategies that allow MAVs to fly in challenging scenarios. Here, we will characterize the turbulence-structure interactions arising in low-Reynolds MAVs with focus on predictability and control. These two problems will be addressed from the powerful point of view of dynamical system theory, in which all the possible evolutions of the wing-turbulence system are represented in a highly dimensional phase space. An intensive exploration of this space is key to find optimal predictive algorithms and control strategies. The predictability of the flow conditions and the airfoil response will be characterized using massive ensemble forecasting, a technique that will be used in this project to study wing-turbulence interactions. These data will be later used to construct statistical models by optimizing information theoretic functionals to predict adverse flow conditions with partial measurements, ensuring the best predictive capabilities with the available data.
Carlos Sanmiguel Vila (INTA-UC3M) & Rodrigo Castellanos (INTA)
Abstract
This research studies turbulent flow control enhancement through various machine-learning and data-driven methods. It focuses on the study of optimal sensor placement strategies, aiming to determine the best sensing configurations for specific flow control problems, while combining multiple data sources with varying fidelities to enhance measurement quality and resolution.
Artifical Neural Networks for the Prediction of Contrails and Aviation Induced Cloudiness
Supervisors
Manuel Fernando Soler (UC3M) & Javier García Heras (UC3M)
Abstract
In my research, the objective is to bridge, to some extent, the current knowledge gap regarding the climate impact of aviation. Specifically, my doctoral thesis revolves around the development of Artificial Neural Networks for the detection and prediction of contrails and aviation-induced cloud formation, with the aim of assessing their impact on the climate
E-CONTRAIL – Artificial Neural Networks for the Prediction of Contrails and Aviation Induced Cloudiness
SESAR Joint Undertaking (JU) under grant N. 101114795
Data-driven modelling of turbulent flows under active flow control
Supervisors
Stefano Discetti (UC3M) & Andrea Ianiro (UC3M)
Abstract
Active Flow control is a paradigm that has shown great potential in the performance enhancement of countless applications/devices in the industry. The complexity of its implementation (actuators positions, control authority, sensoring, definition of control strategy, etc.) makes it an interesting problem that still requires fundamental research to fully understand its potential and limitations. Even when control is successful in the laboratory environment, it is challenging to transfer the lessons learned into the real-world applications. It is necessary to provide complete measurement techniques and analytical tools to interpret the successful control logics to bring their application outside of the lab. The main aim of this thesis is to establish data-driven modeling techniques to distil models from configurations with active flow control. For this purpose, I look forward to developing techniques for nonlinear system identification, and innovative experimental setup configurations capable of obtaining complete information of the flow with limited hardware. A combination of surface measurements, velocimetry, and density-based techniques (for instance Background Oriented Schlieren) will be implemented and tested for the extraction of interpretable control models.
NEXTFLOW – Next-generation flow diagnostics for control.
Funding entity: Doctorado Industrial Comunidad de Madrid
PhD Thesis
Improving Severe Weather Hazard Prediction for Aviation using Machine Learning
Supervisors
Aniel Jardines (Applied Innovative Methods) & Manuel Soler (UC3M)
Abstract
This PhD thesis strives to bridge the gap between existing weather forecast products and the needs of the aviation industry. By enhancing situational awareness through improved weather predictions, the research aims to optimize operations, reduce delays, enhance safety, and minimize economic losses. Through the development of advanced machine learning models, continuous learning techniques, and accessible visualization tools, this research has the potential to make a significant impact on the aviation sector and advance the field of weather forecasting.
Development of convex optimization techniques for space vehicles with high autonomy
Supervisors
Rafael Vázquez Valenzuela (Universidad de Sevilla) & Manuel Sanjurjo Rivo (UC3M)
Abstract
Research for developing convex optimization techniques and algorithms focused on the guidance and control of space systems, putting special attention to HW, SW, and robustness requirements. The final goal is to implement an autocodable optimization engine to be validated with representative HW.
The thesis focuses on the research and development of a demonstrator of an AWE yo-yo fly-actuated machine. The goal of the thesis is to utilize these actuators to control the geometry of the kite’s bridle in a novel and innovative way, setting it apart from current solutions that use a pod.
Cátedra UC3M-CT INGENIEROS
BANCO DE ENSAYOS EN LABORATORIO DE SUBSISTEMA ELECTRICO DE UNA MAQUINA DE GENERACION DE ENERGIA EOLICA AEROTRANSPORTADA- AEI
Jet-noise Diagnostics with Massive Acoustic Camera
Supervisors
Marco Raiola (UC3M) & Luis Azpicueta (UC3M, Signal Theory and Communication Department)
Abstract
Aircraft noise remains a critical environmental challenge, particularly with the projected rise in global air traffic. Among the various noise sources, turbulent jet noise generated by the exhaust of modern turbofan engines constitutes a dominant component, necessitating advanced diagnostic approaches for its mitigation. This thesis addresses the development and application of a novel acoustic diagnostic tool designed for high-resolution jet-noise characterization. The research is conducted within the framework of the JAMAICAM project, which aims to construct a massive acoustic camera using a large array of low-cost MEMS microphones. This system is optimized for jet-noise studies through careful evaluation of sensor selection, array configuration, and beamforming algorithm performance. The resulting acoustic camera is validated in controlled laboratory experiments, demonstrating its capability to localize and analyze sound emission mechanisms in turbulent jets. The outcomes contribute to the broader objective of enabling effective noise-reduction strategies for future aircraft engine designs.
Jet-noise Diagnostics with Massive Acoustic Camera (JAMAICAM)
Multidisciplinary design and optimization of hybrid-electric, ultra-silent high-aspect ratio wings
Supervisors
Rauno Cavallaro (BSC-CNS) & Andrea Cini (UC3M)
Abstract
Achieving the goals of climate neutrality by reducing the impact of aviation is a task that requires a carefully drafted roadmap for the development of disruptive technologies and concepts of operations. With particular attention to the emissions of pollutants and noise in airport local airport areas, a synergetic approach is needed that combines interventions on the aircraft side and on the airport side. This calls for coordinated efforts in developing technologies that not only provide benefits during cruise conditions but also are capable of improving the local air quality and noise in airport areas where the impact of pollutants and annoyance to local communities has been demonstrated to be quite large in terms of morbidity and mortality.
The aim of the proposed thesis is contributing in identifying the margins of improvement in airport local air quality and noise resulting from the introduction of a new non-conventional mid-range aircraft featuring distributed propulsion based on hybrid electric/sustainable and conventional fuel powertrain and large aspect-ratio wings capable to fly quietly and in zero-to-low-emission mode (i.e. electric and SAF) at low altitudes near airports and resort to conventional aviation fuel only when required, e.g., at higher altitudes or to recharge batteries during cruise. This project will explore a new paradigm for the next-generation of silent and clean mid-range aircraft and for the way such a new aircraft will allow transforming the operations “at and near” airports. It will introduce improved methods for the analysis of future aviation environmental impact that, under the filter of uncertainty, will be able to account for non-conventional aircraft performance and future airport scenarios. The main contribution will be performing a multidisciplinary optimization (MDO) of High-aspect-ratio wings (HARW) featuring Distributed Electric Propulsion (DEP) at different fidelity levels.
INDIGO: Integration and Digital Demonstration of Low-emission Aircraft Technologies and Airport Operations
Stability analysis of magnetized plasma flows for space propulsion
Supervisors
Mario Merino Martinez (UC3M) and Eduardo Ahedo (UC3M)
Abstract
Magnetic Nozzles (MN) are the acceleration device of electrodeless plasma thrusters. While the fundamental physics of MNs has been investigated experimentally and theoretically in the past, there are several topics that remain unclear and require further study. In particular, recent experiments evidence the existence of oscillations and/or instabilities in the plasma flow of these devices, an aspect so far not investigated but of dire importance on the efficiency of the MN as they may drive cross-field electron transport. Preliminary results suggest that these instabilities may fall within the drift wave category, but the exact nature of them remains to be ascertained.
This thesis aims to study plasma fluid instabilities in the MN by analytical and numerical modeling. To this end, a two-fluid model will first be established, and a linear stability analysis will be performed. The model will be gradually extended from an axial magnetoplasma column to a slowly-diverging magnetoplasma flow. Then, a quasi-2D fluid code will be developed to perform a global stability analysis of the MN. Modeling results will be compared against existing laboratory data.
Activities to be carried out include:
Literature review of plasma waves and instabilities in relevant configurations
Derivation of drift dispersion relation for a plasma slab (under different degrees of simplification)
Extension to axisymmetric, slowly-diverging plasma flow
Application of dispersion relation to equilibria flows from simulations and experiments
Development of quasi-2D code to perform a global linear stability analysis of the MN
ZARATHUSTRA – Revolutionizing advanced electrodeless plasma thrusters for space transportation.
Design and Validation of the Avionic System of a Deorbit Device Based on an ElectrodynamicTether
Supervisors
Gonzalo Sánchez Arriaga (UC3M)
Abstract
This thesis will design and validate the avionic system of the deorbit device (DD) based on electrodynamic tether technology that reached TRL 4 in the framework of the E.T.PACK project. The DD has two modules (electron emitter module and deployment mechanism module) and each of them has its own avionic and control systems with their own requirements. The design will consider all the phases of the E.T.PACK-F IOD mission, i.e. detumbling, deployment preparation phase, tether deployment, and deorbit manoeuvre. A validation campaign will be developed in the lab. In addition to the avionics, the thesis will also prepare the ground station to be used in the E.T.PACK-F IOD mission. All these activities will be carried out for the Engineering Qualification Model and the Flight Model of the DD.
A Ready-to-Fly Deorbit Device Based on Electrodynamic Tether Technology (E.T.PACK-F)
Model Predictive Control applied to turbulent flows
Supervisors
Stefano Discetti (UC3M) & Andrea Meilán Vila (UC3M, Department of Statistics)
Abstract
Controlling the behaviour of turbulent flows is of immense technological importance but their strongly nonlinear chaotic multiscale behaviour hinders the use of efficient closed-loop control techniques.
Model Predictive Control (MPC) provides a versatile framework in this field based on iterative optimization of control actions applied on compact models of the dynamics.
The goal of the research is the development of novel efficient MPC techniques for turbulent flows, which need to be highly robust to measurement noise and model uncertainty due to dynamics truncation.
Modelling and Mission Analysis of Bare-Photovoltaic Tethers in Low Earth Orbit
Supervisors
Gonzalo Sánchez Arriaga (UC3M)
Abstract
Bare-Photovoltaic Tethers provide extra power for on-board use and propellant-less in-orbit propulsion. This enhancement is useful for different scenarios such as deorbiting space debris, station-keeping and reboost maneuvers. They all will be integrated in the mission analysis software BETsMA v2.0.
2022 – May 2024
A Ready-to-Fly Deorbit Device Based on Electrodynamic Tether Technology (E.T.PACK-F)
HORIZON-EIC-2021-TRANSITIONOPEN-01 No. 101058166
A Consumable-less Propulsion System Based on a Bare-Photovoltaic Tether
Funding entity and Program: Industrial PhD granted by CAM and carried out within CT Ingenieros.
PhD Thesis
Ground-Actuated Airborne Wind Energy System Demonstrator
Date of Defense: 04 November 2026
Supervisors
Gonzalo Sánchez Arriaga (UC3M)
Abstract
Airborne Wind Energy Systems (AWES) are aircrafts (flexible kites or fixed-wings) attached to the ground by a system of tethers and capable of harnessing the of the wind to generate electricity. Their main advantages, compared to traditional wind turbines, are lower manufacturing and installation costs, the capability of reaching higher altitudes where the wind is stronger and more stable, a better capacity factor, a reduced visual impact and their ease of transport. Their biggest disadvantage is their complexity, derived from the need of autonomous flight on changing wind conditions. Several European companies have developed AWES prototypes within the 100 to 200 kW range and are in the pre-commercialization phase.
The main goal of this Industrial PhD is to develop a ground-actuated AWE demonstrator based on the UC3M Testbed for the Aerodynamic Characterization of Kites. The proposed work plan aims to achieve this goal in two phases. Firstly, a new control system will be designed, aimed to be more scalable, more robust and to have better control capabilities. In particular, it will be able to control the steering of the kite, its angle of attack and to carry out reel-in and reel-out procedures. Secondly, a power generation system will be added, based on a Yo-Yo AWE generator architecture. Every phase will include flight campaigns which will allow to first demonstrate its open-loop operation capabilities and then its closed-loop control system robustness. Autonomous take-off and landing will also be included in the research.
Project participation
Demostrador de Máquina de Generación de Energía Eólica con Sistemas Aerotransportado Actuado en Tierra
Ref.No.: IND2022/AMB-23521
Funding Entity: Consejería de Educación, Universidades, Ciencia y Portavocía (Comunidad de Madrid)
GreenKite-2
Ref.No.: PID2019-110146RB-I00
Funding Entity: Agencia Estatal de Investigación (Ministerio de Ciencia, Innovación y Universidades)
Active Flow Control Solutions for Noise Reduction in Jet Flows
Supervisors
Stefano Discetti (UC3M) & Marco Raiola (UC3M)
Abstract
Active AI-based flow control strategies for noise and mixing in turbulent jet flows will be investigated. Implementing simultaneously optical techniques and probe measurements, the final objective is to extract reduced-order models of the controlled system, with interpretable control actions.
NEXTFLOW – Next-generation flow diagnostics for control.
PhD in Aerospace Engineering UC3M 