An aerothermodynamic design optimization framework for hypersonic vehicles

In the aviation field great interest is growing in passengers transportation at hypersonic speed. This requires, however, careful study of the enabling technologies necessary for the optimal design of hypersonic vehicles. In this framework, the present work reports on a highly integrated design environment that has been developed in order to provide an optimization loop for vehicle aerothermodynamic design. It includes modules for geometrical parametrization, automated data transfer between tools, automated execution of computational analysis codes, and design optimization methods. This optimization environment is exploited for the aerodynamic design of an unmanned hypersonic cruiser flying at M∞=8 and 30 km altitude. The original contribution of this work is mainly found in the capability of the developed optimization environment of working simultaneously on shape and topology of the aircraft. The results reported and discussed highlight interesting design capabilities, and promise extension to more challenging and realistic integrated aerothermodynamic design problems

The design of more-electric engine power systems

The More-Electric Aircraft (MEA) concept is now a well-established concept, following its introduction and development over the previous couple of decades. MEA systems are underpinned by state-of-the-art technologies to realise the reduction of CO2 emissions and increased the effectiveness of on-board power transmission. The More-Electric Engine (MEE) concept is increasingly being seen as a complementary solution for MEA applications. Within this concept, the engine auxiliary systems such as fuel pumps, oil pumps and actuation systems will be replaced by electrically driven equivalents and power will be extracted from multiple different engine shafts for electrical generation, with the potential to achieve significant fuel savings. However, with these changes, a dedicated high-integrity and flexibly reconfigurable MEE multiple-channel power architecture is required. When designing a multiple-channel power architecture for MEE，it should comply with relevant power system design certification standards, requiring the application of a multi-disciplinary design methodology. In this thesis, key design certification and airworthiness standards are reviewed in order to identify those applicable to MEE design. Combining these with traceable qualitative and quantitative design logic, the first power system design rule set for MEE power system architecture baselining is established. Building on this foundational knowledge base, candidate novel multiple-channel power architectures are proposed and evaluated. These studies determine that a high degree of controllability and redundancy is key to achieving high system reliability and resilience in MEE power system architectures. In addition, a review of the research literature in this thesis is shown to reveal a shortage of proposed design and optimisation processes for flexible and redundant MEE-type power systems, making it difficult to maximise the design value of a feasible solution. As interdisciplinary and multi-system design processes can be time-consuming and laborious, this thesis instead presents a concurrent design (Co-design) methodology, addressing both MEE power architecture concepts and power management functions. This novel design process includes an initial coarse optimisation to determine the design space boundaries and exclude unsuitable and over-designed solutions for further detailed design, reducing design iterations. A subsequent collaborative synthesis stage for the concurrent design process is then proposed, in which fault scenario case studies and load shedding factor are used to verify the robustness of the combined MEE architecture and power management solutions to off-nominal operating conditions. This enables the refinement of the solution-space by using the simulated results to highlight the areas of the MEE power architecture that can be further optimised, demonstrating the benefits of knowledge-based collaborative design as a process for multi-criteria design. The contributions to the design of MEE power systems architectures presented in this thesis hence provide end-to-end value to the academic and industrial research community in the formation and design of new MEE concepts, with wider application to technologically-adjacent applications (such as hybrid electric aircraft, or high-integrity dc microgrids) also possible.The More-Electric Aircraft (MEA) concept is now a well-established concept, following its introduction and development over the previous couple of decades. MEA systems are underpinned by state-of-the-art technologies to realise the reduction of CO2 emissions and increased the effectiveness of on-board power transmission. The More-Electric Engine (MEE) concept is increasingly being seen as a complementary solution for MEA applications. Within this concept, the engine auxiliary systems such as fuel pumps, oil pumps and actuation systems will be replaced by electrically driven equivalents and power will be extracted from multiple different engine shafts for electrical generation, with the potential to achieve significant fuel savings. However, with these changes, a dedicated high-integrity and flexibly reconfigurable MEE multiple-channel power architecture is required. When designing a multiple-channel power architecture for MEE，it should comply with relevant power system design certification standards, requiring the application of a multi-disciplinary design methodology. In this thesis, key design certification and airworthiness standards are reviewed in order to identify those applicable to MEE design. Combining these with traceable qualitative and quantitative design logic, the first power system design rule set for MEE power system architecture baselining is established. Building on this foundational knowledge base, candidate novel multiple-channel power architectures are proposed and evaluated. These studies determine that a high degree of controllability and redundancy is key to achieving high system reliability and resilience in MEE power system architectures. In addition, a review of the research literature in this thesis is shown to reveal a shortage of proposed design and optimisation processes for flexible and redundant MEE-type power systems, making it difficult to maximise the design value of a feasible solution. As interdisciplinary and multi-system design processes can be time-consuming and laborious, this thesis instead presents a concurrent design (Co-design) methodology, addressing both MEE power architecture concepts and power management functions. This novel design process includes an initial coarse optimisation to determine the design space boundaries and exclude unsuitable and over-designed solutions for further detailed design, reducing design iterations. A subsequent collaborative synthesis stage for the concurrent design process is then proposed, in which fault scenario case studies and load shedding factor are used to verify the robustness of the combined MEE architecture and power management solutions to off-nominal operating conditions. This enables the refinement of the solution-space by using the simulated results to highlight the areas of the MEE power architecture that can be further optimised, demonstrating the benefits of knowledge-based collaborative design as a process for multi-criteria design. The contributions to the design of MEE power systems architectures presented in this thesis hence provide end-to-end value to the academic and industrial research community in the formation and design of new MEE concepts, with wider application to technologically-adjacent applications (such as hybrid electric aircraft, or high-integrity dc microgrids) also possible

Power Electronics and Energy Management for Battery Storage Systems

The deployment of distributed renewable generation and e-mobility systems is creating a demand for improved dynamic performance, flexibility, and resilience in electrical grids. Various energy storages, such as stationary and electric vehicle batteries, together with power electronic interfaces, will play a key role in addressing these requests thanks to their enhanced functionality, fast response times, and configuration flexibility. For the large-scale implementation of this technology, the associated enabling developments are becoming of paramount importance. These include energy management algorithms; optimal sizing and coordinated control strategies of different storage technologies, including e-mobility storage; power electronic converters for interfacing renewables and battery systems, which allow for advanced interactions with the grid; and increase in round-trip efficiencies by means of advanced materials, components, and algorithms. This Special Issue contains the developments that have been published b researchers in the areas of power electronics, energy management and battery storage. A range of potential solutions to the existing barriers is presented, aiming to make the most out of these emerging technologies

Multi-level-objective design optimization of permanent magnet synchronous wind generator and solar photovoltaic system for an urban environment application

This Ph.D. thesis illustrates a novel study on the analytical and numerical design optimization of radial-flux permanent magnet synchronous wind generators (PMSGs) for small power generation in an urban area, in which an outer rotor topology with a closed-slot stator is employed. The electromagnetic advantages of a double-layer fractional concentration non-overlapping winding configuration are discussed. The analytical behavior of a PMSG is studied in detail; especially for magnetic flux density distribution, time and space harmonics, flux linkages, back-EMF, cogging torque, torque, output power, efficiency, and iron losses computation. The electromagnetic behavior of PMSGs are evaluated when a number of various Halbach array magnetization topologies are presented to maximize the generator’s performance. In addition, the thermal behavior of the PMSG is improved using an innovative natural air-cooling system for rated speed and higher to decrease the machine’s heat mainly at the stator teeth. The analytical investigation is verified via 2-D and 3-D finite element analysis along with a good experimental agreement. Design optimization of electrical machines plays the deterministic role in performance improvements such as the magnetization pattern, output power, and efficiency maximization, as well as losses and material cost minimization. This dissertation proposes a novel multi-objective design optimization technique using a dual-level response surface methodology (D-RSM) and Booth’s algorithm (coupled to a memetic algorithm known as simulated annealing) to maximize the output power and minimize material cost through sizing optimization. Additionally, the efficiency maximization by D-RSM is investigated while the PMSG and drive system are on duty as the whole. It is shown that a better fit is available when utilizing modern design functions such as mixed-resolution central composite (MR-CCD) and mixed-resolution robust (MR-RD), due to controllable and uncontrollable design treatments, and also a Window-Zoom-in approach. The proposed design optimization was verified by an experimental investigation. Additionally, there are several novel studies on vibro-acoustic design optimization of the PMSGs with considering variable speed analysis and natural frequencies using two techniques to minimize the magnetic noise and vibrations. Photovoltaic system design optimization considered of 3-D modeling of an innovative application-oriented urban environment structure, a smart tree for small power generation. The horizon shading is modeled as a broken line superimposed onto the sun path diagram, which can hold any number of height/azimuth points in this original study. The horizon profile is designed for a specific location on the Barcelona coast in Spain and the meteorological data regarding the location of the project was also considered. Furthermore, the input weather data is observed and stored for the whole year (in 2016). These data include, ambient temperature, module’s temperature (open and closed circuits tests), and shading average rate. A novel Pareto-based 3-D analysis was used to identify complete and partial shading of the photovoltaic system. A significant parameter for a photovoltaic (PV) module operation is the nominal operating cell temperature (NOCT). In this research, a glass/glass module has been referenced to the environment based on IEC61215 via a closed-circuit and a resistive load to ensure the module operates at the maximum power point. The proposed technique in this comparative study attempts to minimize the losses in a certain area with improved output energy without compromising the overall efficiency of the system. A Maximum Power Point Track (MPPT) controller is enhanced by utilizing an advanced perturb & observe (P&O) algorithm to maintain the PV operating point at its maximum output under different temperatures and insolation. The most cost-effective design of the PV module is achieved via optimizing installation parameters such as tilt angle, pitch, and shading to improve the energy yield. The variation of un-replicated factorials using a Window-Zoom-in approach is examined to determine the parameter settings and to check the suitability of the design. An experimental investigation was carried out to verify the 3-D shading analysis and NOCT technique for an open-circuit and grid-connected PV module.Esta tesis muestra un novedoso estudio referente al diseño optimizado de forma analítica y numérica de un generador síncrono de imanes permanentes (PMSGs) para una aplicación de microgeneración eólica en un entorno urbano, donde se ha escogido una topología de rotor exterior con un estator de ranuras cerradas. Las ventajas electromagnéticas de los arrollamientos fraccionarios de doble capa, con bobinas concentradas se discuten ampliamente en la parte inicial del diseño del mismo, así como las características de distribución de la inducción, los armónicos espaciales y temporales, la fem generada, el par de cogging así como las características de salida (par, potencia generada, la eficiencia y la distribución y cálculo de las pérdidas en el hierro que son analizadas detalladamente) Posteriormente se evalúan diferentes configuraciones de estructuras de imanes con magnetización Halbach con el fin de maximizar las prestaciones del generador. Adicionalmente se analiza la distribución de temperaturas y su mejora mediante el uso de un novedoso diseño mediante el uso de ventilación natural para velocidades próximas a la nominal y superiores con el fin de disminuir la temperatura de la máquina, principalmente en el diente estatórico. El cálculo analítico se completa mediante simulaciones 2D y 3D utilizando el método de los elementos finitos así como mediante diversas experiencias que validan los modelos y aproximaciones realizadas. Posteriormente se desarrollan algoritmos de optimización aplicados a variables tales como el tipo de magnetización, la potencia de salida, la eficiencia así como la minimización de las pérdidas y el coste de los materiales empleados. En la tesis se proponen un nuevo diseño optimizado basado en una metodología multinivel usando la metodología de superficie de respuesta (D-RSM) y un algoritmo de Booth (maximizando la potencia de salida y minimizando el coste de material empleado) Adicionalmente se investiga la maximización de la eficiencia del generador trabajando conjuntamente con el circuito de salida acoplado. El algoritmo utilizado queda validado mediante la experimentación desarrollada conjuntamente con el mismo. Adicionalmente, se han realizado diversos estudios vibroacústicos trabajando a velocidad variable usando dos técnicas diferentes para reducir el ruido generado y las vibraciones producidas. Posteriormente se considera un sistema fotovoltaico orientado a aplicaciones urbanas que hemos llamado “Smart tree for small power generation” y que consiste en un poste con un generador eólico en la parte superior juntamente con uno o más paneles fotovoltaicos. Este sistema se ha modelado usando metodologías en 3D. Se ha considerado el efecto de las sombras proyectadas por los diversos elementos usando datos meteorológicos y de irradiación solar de la propia ciudad de Barcelona. Usando una metodología basada en un análisis 3D y Pareto se consigue identificar completamente el sistema fotovoltaico; para este sistema se considera la temperatura de la célula fotovoltaica y la carga conectada con el fin de generar un algoritmo de control que permita obtener el punto de trabajo de máxima potencia (MPPT) comprobándose posteriormente el funcionamiento del algoritmo para diversas situaciones de funcionamiento del sistemaLa tesis desenvolupa un nou estudi per al disseny optimitzat, analític i numèric, d’un generador síncron d’imants permanents (PMSGs) per a una aplicació de microgeneració eòlica en aplicacions urbanes, on s’ha escollit una configuració amb rotor exterior i estator amb ranures tancades. Es discuteixen de forma extensa els avantatges electromagnètics dels bobinats fraccionaris de doble capa així com les característiques resultats vers la distribució de les induccions, els harmònics espacials i temporals, la fem generada, el parell de cogging i les característiques de sortida (parell, potencia, eficiència i pèrdues) Tanmateix s’afegeix l’estudi de diferents estructures Halbach per als imants permanents a fi i efecte de maximitzar les característiques del generador. Tot seguit s’analitza la distribució de temperatures i la seva reducció mitjançant la utilització d’una nova metodologia basada en la ventilació natural. Els càlculs analítics es complementen mitjançant anàlisi en 2 i 3 dimensions utilitzant elements finits i diverses experiències que validen els models i aproximacions emprades. Una vegada fixada la geometria inicial es desenvolupen algoritmes d’optimització per a diverses variables (tipus de magnetització dels imants, potencia de sortida, eficiència, minimització de pèrdues i cost dels materials) La tesi planteja una optimització multinivell emprant la metodologia de superfície de resposta i un algoritme de Booth; a més, es realitza la optimització considerant el circuit de sortida. L’algoritme resta validat per la experimentació realitzada. Finalment, s’han considerat diversos estudis vibroacústic treballant a velocitat variable, emprant dues tècniques diferents per a reduir el soroll i les vibracions desenvolupades. Per a finalitzar l’estudi es considera un sistema format per una turbina eòlica instal·lada sobre un pal de llum autònom, els panells fotovoltaics corresponents i el sistema de càrrega. Per a modelitzar l’efecte de l’ombrejat s’ha emprat un model en 3D i les dades del temps i d’irradiació solar de la ciutat de Barcelona. El model s’ha identificat completament i s’ha generat un algoritme de control que considera, a més, l’efecte de la temperatura de la cèl·lula fotovoltaica y la càrrega connectada al sistema per tal d’aconseguir el seguiment del punt de màxima potenciaPostprint (published version

Cross-feature trained machine learning models for QoT-estimation in optical networks

The ever-increasing demand for global internet traffic, together with evolving concepts of software-defined networks and elastic-optical-networks, demand not only the total capacity utilization of underlying infrastructure but also a dynamic, flexible, and transparent optical network. In general, worst-case assumptions are utilized to calculate the quality of transmission (QoT) with provisioning of high-margin requirements. Thus, precise estimation of the QoT for the lightpath (LP) establishment is crucial for reducing the provisioning margins. We propose and compare several data-driven machine learning (ML) models to make an accurate calculation of the QoT before the actual establishment of the LP in an unseen network. The proposed models are trained on the data acquired from an already established LP of a completely different network. The metric considered to evaluate the QoT of the LP is the generalized signal-to-noise ratio (GSNR), which accumulates the impact of both nonlinear interference and amplified spontaneous emission noise. The dataset is generated synthetically using a well-tested GNPy simulation tool. Promising results are achieved, showing that the proposed neural network considerably minimizes the GSNR uncertainty and, consequently, the provisioning margin. Furthermore, we also analyze the impact of cross-features and relevant features training on the proposed ML models’ performance

Optimal tuned mass-damper-inerter (TMDI) design for seismically excited MDOF structures with model uncertainties based on reliability criteria

The tuned mass-damper-inerter (TMDI) is a recently proposed linear passive dynamic vibration absorber for the seismic protection of buildings. It couples the classical tuned mass damper (TMD) with an inerter, a two-terminal device resisting the relative acceleration of its terminals, in judicial topologies, achieving mass-amplification and higher-modes-damping effects compared to the TMD. This paper considers an optimum TMDI design framework accommodating the above effects while accounting for parametric uncertainty to the host structure properties, modeled as a linear multi degree of freedom system, and to the seismic excitation, modeled as stationary colored noise. The inerter device constant, acting as a TMD mass amplifier, is treated as a design variable, whereas performance variables sensitive to high-frequency structural response dynamics are used to account for the TMDI influence to the higher structural modes. Reliability criteria are adopted for quantifying the structural performance, expressed through the probability of occurrence of different failure modes related to the trespassing of acceptable thresholds for the adopted performance variables: floor accelerations, interstory drifts, and attached mass displacement. The design objective function is taken as a linear combination of these probabilities following current performance-based seismic design trends. Analytical and simulation-based tools are adopted for the efficient estimation of the underlying stochastic integral defining the structural performance under uncertainty. A 10-story building under stationary Kanai-Tajimi stochastic excitation is considered to illustrate the design framework for various TMDI topologies and attached mass values. It is shown that the TMDI achieves enhanced structural performance and robustness to building and excitation uncertainties compared to same mass/weight TMDs