Universidad Politécnica de Madrid
Recent publications
Under-Frequency Load Shedding (UFLS) schemes are the last resort to contain a frequency drop in the grid by disconnecting part of the demand. The allocation methods for selecting feeders that would contribute to the UFLS scheme have traditionally relied on the fact that electric demand followed fairly regular patterns, and could be forecast with high accuracy. However, recent integration of Distributed Generation (DG) increases the uncertainty in net consumption of feeders which, in turn, requires a reformulation of UFLS-allocation methods to account for this uncertainty. In this paper, a chance-constrained methodology for selecting feeders is proposed, with mathematical guarantees for the disconnection of the required amount of load with a certain pre-defined probability. The correlation in net-load forecasts among feeders is explicitly considered, given that uncertainty in DG power output is driven by meteorological conditions with high correlation across the network. Furthermore, this method is applicable either to systems with conventional UFLS schemes (where relays measure local frequency and trip if this magnitude falls below a certain threshold), or adaptive UFLS schemes (where relays are triggered by control signals sent in the few instants following a contingency). Relevant case studies demonstrate the applicability of the proposed method, and the need for explicit consideration of uncertainty in the UFLS-allocation process.
This work deals with the study and implementation of a Local Space-Time DG ADER approach, in the finite volume framework with Weighted Essentially Non-Oscillatory (WENO) reconstruction in space, in the context of 2D porous media problems. The particular application performed concerns a biomedical problem dealing with the first stages of atherosclerosis disease, where the artery is considered as a porous medium, although the methodology described can be applied to other situations. The mathematical model on which this research is based is given by a system of two-dimensional nonlinear reaction-diffusion equations with a nonlinear source term in one of the equations, which is a variant of the model proposed originally in N. El Khatib, S. Genieys & V. Volpert (2007) Math. Model. Nat. Phenom., vol 2(2), pp. 126–141 [1]. The 2D model considered in this work has two main features: (i) the artery is taken as a porous medium and (ii) a nonlinear non-homogeneous Neumann boundary condition is incorporated, aimed to account for the recruitment of immune cells through the upper boundary, as a response to the production of cytokines. Certain theoretical properties of the stationary solutions and the evolution solution are stated and proved. Some of them are also verified with the numerical simulation results.
Computational Fluid Dynamic (CFD) codes are a widely used tool in spent nuclear fuel dry storage systems applications. A recurrent simplification used in most spent nuclear fuel CFD models found in the literature is the complete removal (or a non-explicit modelling) of the fuel assemblies flow nozzles and the spacer grids. In this paper, a full scope model of a dry storage cask, including detailed flow nozzles for each fuel assembly, has been developed and compared with a homologous model without flow nozzles, although the spacer grids are not considered. For steady-state simulations, it has been found that the differences are minimal. An additional sensitivity was performed, completely disabling the natural convection of the cask coolant. In this case, noticeably differences were found.
The development of superhydrophobic surfaces is significant due to the industrial applications in various fields, from energy to biomedical implants. The surface morphology and chemistry primarily govern the characteristics of the interface between the water droplet and the surfaces. Herein, a combination of laser patterning and low-pressure technique has been adopted to generate the superhydrophobic TiN surface. The superhydrophobic surface was subjected to wetting property and chemical analysis with respect to the surface geometry. The impact dynamics of water droplets at the laser-patterned superhydrophobic surface have been studied. The droplet impacts result in finger formation at the start of the spreading, and the droplets formed at the tip of fingers detached from the rim during the retraction. The resulting fragmentation favors decreased travel distance and time required for recoiling the water droplets. The fragmentation during the recoiling results from modified hydrodynamics induced by the surface morphology and wetting property. The laser-processed hierarchical surface structures are a potential method to reduce the contact time at the solid-liquid interface.
Tremendous advancement in optoelectronic devices can be achieved by the improvement of high-performing p-type TCOs. Herein, we exhibit the manufacturing of the delafossite CuCoO2 tied to exceptional electrical and optical properties. A spray pyrolysis technique which is simple, uncomplicated, and adjustable was used to deposit the delafossite layers. We achieved homogeneous CuCoO2 films, high crystalline, and smooth surfaces. We investigate the role of the Cu/Co cation ratio and the annealing process on the prepared layers’ properties. X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission electron microscopy (TEM), atomic force microscopy (AFM), and UV spectroscopy are used in order to examine the deposited CuCoO2 films. We demonstrated the percentages of 30%, 40%, 50%, and 60% of copper which gave us pure samples without any impurities with good morphology and adequate structure shown by SEM, AFM, and TEM analyses, are the samples with the ratio [Cu: Co] = [2:3] and [1:1] that are equivalent to 40% and 50% of copper, respectively. Their band gaps are 2,5 eV and 2,4 eV with a transmission of 76% at 650 nm and 80% at 700 nm of wavelength. The achieved results are an original study comparing to the literature treating the effect of the precursors' ratio of Cu/Co and the temperature on the growth of delafossite CuCoO2 films with a low-cost technique.
In this study, the photocatalytic activity of ZnO was effectively improved via its combination with spinel cobalt ferrite (SCF) nanoparticles. The catalytic performance of ZnO@SCF (ZSCF) was investigated in coupling with UV irradiation and ultrasound (US), as a heterogeneous sono-photocatalytic process, for the decontamination of phenanthrene (PHE) from contaminated soil. Soil washing tests were conducted in a batch environment, after extraction assisted by using Tween 80. Several characterization techniques such as XRD, FESEM-EDS, BET, TEM, UV-vis DRS, PL and VSM were utilized to determine the features of the as-prepared catalysts. ZSCF showed an excellent catalytic activity toward degradation of PHE in the presence of US and UV with a significant synergic effect. It was found that more than 93% of PHE (35 mg/L) and 87.5% of TOC could be eliminated by the integrated ZSCF/US/UV system under optimum operational conditions (pH: 8.0, ZSCF: 1.5 g/L, UV power: 6.0 W and US power: 70 W) within 90 min of reaction. After five times of use, ZSCF illustrated good reusability in the decontamination of PHE (87%) and TOC (79%). Quenching tests revealed the contribution of h + , HO • and e − species during PHE degradation over ZSCF/UV/US and an S-scheme photocatalytic mechanisms was proposed for the possible charge transfer routes under the ZSCF system. This study provides the important role of SCF in enhancing the ZnO photocatalytic activity due to its high performance, easy recovery and excellent durability, which it make an efficient and promising catalyst in environmental clean-up applications.
Damage localization is one of the most challenging topics within Structural Health Monitoring (SHM) in aeronautics, especially when the structure is manufactured out of carbon fiber-reinforced composite materials. Using ultrasonic guided waves (particularly Lamb waves), generated and recorded with piezoelectric transducers, is also challenging in this type of material. Otherwise, traditional methods used for this task are subjected to physics-based knowledge of the problem, such as damage imaging algorithms like delay-and-sum and RAPID. This paper presents an entirely data-driven approach, based on the ability of Deep Learning (DL) techniques (particularly those based on Convolutional Neural Networks – CNNs –) to extract features of interest for damage imaging from a pre-dataset. In this work, the selected feature to be estimated is the normal distance from the propagation path of the guided wave to a simulated damage, which allows, in combination with an especially designed positioning algorithm, to locate with high accuracy defects, even in different positions than the used for the training of the network (a fixed grid of points over the analysis zone). This paper presents the application of the method to a real composite material specimen, as well as the recorded results obtained from additional datasets recorded with the simulated damage (a piece of blu-tack) attached to different random positions other than those of the training grid.
The removal of the non-steroidal anti-inflammatory drug (NSAID) Naproxen (NAX) in water by hydroxyl radicals (•OH) was performed by electrochemical advanced oxidation processes either with Pt or BDD anodes and a 3D carbon felt cathode. The degradation of NAX by (•OH vs. electrolysis time) was well fitted to a pseudo-first-order reaction rate kinetic. The detected reaction intermediates (aromatic compounds and carboxylic acids) were experimentally monitored during the process via LC, while density functional theory (DFT) was applied to uncover undetected intermediates, some for the first time in literature. The formation of toxic intermediates with higher toxicity than NAX were identified, such as IMS4b (6-Methoxy-1-[1-(6-methoxynaphthalen-2-yl) ethyl] naphthalen-2-ol), catechol, and glycolic acid. Based on these data, a detailed oxidation pathway of NAX by •OH was proposed. The evolution of solution toxicity indicated that formed toxic intermediates were subsequently removed during the TOC removal process. Finally, almost complete mineralization of NAX was achieved in simulated urine or wastewater, by the electro-Fenton treatment with an optimized dose of iron as catalyst, showing the EAOPs’ potential to efficiently remove NAX even from challenging matrices. In extension, the strategies developed can be applied to the treatment of other NSAIDs.
This paper aims to introduce the implementation parameters of the layered infill patterns in additive manufacturing to evaluate their effects on the actual density in the fabricated parts. To achieve this goal, parameters involved in shaping different infill patterns are presented and the significance of different input parameters on the output (actual) infill density is evaluated. The reference models for infill implementation are generic cubic and cylindrical models as their specific geometries lead to fewer geometric parameters affecting infill density error and provide informative case studies.
Microplastics (MPs) and nanoplastics (NPs) are new types of emerging pollutant of high concern that appeared as an ineluctable consequence of our actual Plasticene era or Age of Plastics started in the mid-20th century with the exponential increase in the global production, consumption, and disposal of synthetic polymers and plastic products. In the wake of the first observation of oceanic macroscopic plastic debris in the 1970s, the problems of MPs and more recently of NPs gained an exponentially increasing and relevant attention from different scientific communities because of the essential contemporary questions and concerns it raises. Those micro- and nano-pollutants have to be considered as environmental contaminants of emerging concern as they may cause adverse ecological or human health impacts through the alteration of the quality of the ecosystems, of the environment, and of the entire food chain, while being still outside any official regulation by authorities to date. Because of the emerging nature of this multiscale solid pollution, no adequate wastewater treatments exist nowadays at the industrial scale for hindering its release to the environment. In addition to their accumulation in the soils and in the local ecosystems with subsequent interaction, MP and NP wastes, whether they are released deliberately or accidentally, have consequently the oceans as final destination with an ubiquitous distribution at the world scale.
Microplastics and nanoplastics are a new type of emerging pollutant that appears in the environment. The difference between those two is based on the particle size. The studies about microplastics and nanoplastics have recently increased because of the growing social awareness and because of the biological effects they provoke. To clarify these effects, proper sampling and identification methods are required. The lack of standard methods up to now makes the studies and the comparisons hard. This chapter provides an overview of the main existing methods of sampling, sample preparation, and the identification of debris comprising of microplastics (MPs) and nanoplastics (NPs) in nature. In conclusion, the methods used for these purposes depend on the type of material, the size, and the matrix in which the polymer is involved.
Microplastics (MPs) and nanoplastics (NPs) are ecotoxicological threats because they are able to accumulate and transport toxic metals, persistent organic pollutants, or pharmaceutical products. Consequently, NP pollution is also a public health problem. MP and NP particles arise into surface water bodies and sea water through two major routes: (1) by the transport in the marine environment as synthetic microbeads or microparticles (for example, incorporated into cosmetic products or during the washing of synthetic clothes) and (2) by the fragmentation of large plastic debris into MPs and NPs through ultraviolet (UV) photodegradation, biodegradation, and mechanical and chemical degradation processes (secondary microplastics). Even if the interest of the scientific community in environmental pollution caused by MPs and NPs started at the beginning of the 21st century, the research works for reducing and/or removing them in water are very recent. The objective of this chapter is to present the main methods of treatment or removal of MPs and NPs from water and the processes under development.
This study sheds light on the relationship between agglomeration, entrepreneurs' internal resources and capabilities, and new ventures' innovativeness using a multilevel framework. We argue that the urban agglomeration of economic agents within a country has an inverted U-shaped relationship with new ventures' innovativeness, suggesting that both insufficient and excessive agglomeration might be detrimental to entrepreneurial innovativeness. Additionally, we perform interactions between individual level factors and urban agglomeration to examine the differential effects of entrepreneurs' internal resources and capabilities. Results confirm our hypothesising that the geographical concentration of economic agents within a country exerts an inverted U-shaped influence on new ventures' innovativeness. Furthermore, we find that entrepreneurs with higher levels of education or prior entrepreneurial experience are better equipped to benefit from agglomeration and to mitigate its negative effects; in contrast, at low levels of agglomeration, entrepreneurs with lower resources exhibit increasing marginal returns. Entrepreneurs in contact with other entrepreneurs are better positioned to deal with agglomeration externalities although their benefits and drawbacks are intensified. Our research contributes to the understanding of agglomeration externalities and entrepreneurial innovativeness, its non-linear dynamics and differential effects.
During the cooling of the reactor core, as a result of a severe accident, a strongly exothermic oxidation reaction of the zirconium cladding occurs and leads to hydrogen production, this has been observed in Fukushima, Chernobyl and Three Mile Island accidents. Several experiments have been carried out for the understanding of the phenomena that are involved in a severe accident and of the adequate mathematical modeling of the behavior of these scenarios. The objective of this work is to develop a reduced model of low computational cost that simulates the cooling phenomenon considering the heat transfer for the fuel rods, the thermohydraulic phenomena in the coolant, and the hydrogen generation focus on the QUENCH-06 experiment, where the purpose of this experiment is to investigate the cooling process of fuel rods in a severe accident scenario in a light-water nuclear reactor. The reduced model is solved numerically. It is implemented in a C++ compiler and it is validated with the data of the experiment, obtaining a deviation in the integral hydrogen generation of -4.7%. Subsequently, a sensitivity and uncertainty analysis is carried out to determine the parameters involved with greater relevance in the integral hydrogen generation. The results show that the variables with the greatest impact on hydrogen generation are: the variation of the steam flow, the convective heat transfer coefficient, and the inlet temperature of steam and argon, the latter with the largest value of the Pearson's correlation coefficient.
Sheet‒pile groin appearing as two rows of piles, with both pile heads connected by a concrete sheet, are widely applied to resist the tidal bores, although its dynamic soil‒structure mechanism is still under research. This paper utilizes the Euler beam and one‒dimensional rod to simulate the pile and sheet constituting the framework of the sheet‒pile groin, respectively, and Biot's poroelastic theory is introduced to simulate the layered saturated soil in which the sheet‒pile groin is embedded. To account for the pile‒pile mutual interactions, interaction factors considering the secondary wave effect are adopted. Radiation wave theory is adopted to simulate the hydrodynamic pressure. The theoretical solutions to the dynamic response of the sheet‒pile groin in the frequency and time domains are derived by applying the matrix calculations and the Fourier transform. The correctness and accuracy of the present solution have been verified through FEM results. An extensive parametric analysis is then conducted to investigate the influence of various factors on the dynamic horizontal complex impedance of the sheet‒pile groin.
There has been an increasing interest in developing efficient immersed boundary method (IBM) based on Cartesian grids, recently in the context of high-order methods. IBM based on volume penalization is a robust and easy to implement method to avoid body-fitted meshes and has been recently adapted to high order discretizations [1]. This work proposes an improvement over the classic penalty formulation for high-order solvers based on flux reconstruction. We include a selective frequency damping (SFD) approach [2] acting only inside solid body defined through the immersed boundary masking, to damp spurious oscillations. An encapsulated formulation for the SFD method is implemented, which can be used as a wrapper around an existing time-stepping code. The numerical properties have been studied through eigensolution analysis based on the advection equation. These studies not only show the advantages of using the SFD method as an alternative of the traditional volume penalization, but also show the favorable properties of combining both approaches. This new approach is then applied to the Navier-Stokes equation to simulate steady flow past an airfoil and unsteady flow past a circular cylinder. The advantages of the SFD method in providing improved accuracy are reported.
Disulfide containing vitrimers are being widely studied to get renewable, reprocessable and self-healable resins. The most of them are based on thermally cured epoxy resin. Herein, new thermoset systems based on typical acrylate monomers with photo-curing were synthesized with self-healing capabilities by introducing monomers with disulfide bonds. These disulfide groups are able to exchange upon heating, leading to a renewal of the crosslinks across the damaged surfaces. Different ratios of associative reversible exchange covalent bonds have been studied. The samples were evaluated in terms of thermal and mechanical properties. It was found that the glass transition temperature (Tg) is lower than that corresponding to typical acrylate thermosets, but mechanical properties are better. Increases in hardness of 2.4 times and in elastic modulus of 1.7 times with respect to the reference networks were achieved. Finally, the self-healing properties of the disulfide acrylates were demonstrated by monitoring the repair of a scratch upon heating. A new experimental test for quantifying the self-healing efficiency has been optimized, following the recovery of the surface crack by perfilometry. The composition optimization allows us to achieve repair percentages of 95% in shorter times.
Debris flows can be considered a type of landslide with large velocities and long run-out distances. There are many types of debris flows, depending on the properties of the solid and fluid components of the mixture. The triggering and propagation of debris flows can be studied using a single 3D mathematical model. The computational cost can be very high because of their length, and depth-integrated models provide a good combination of accuracy and cost. Both types of models can be combined in the analysis, using 3D models for initiation and at singular points where more accuracy is wanted. As in a chain where the strength is never higher than that of the weaker link, we have to ensure that all the models are accurate enough in a joint model. This paper deals with a new depth-integrated model which can take into account the changes caused by dewatering in a debris flow. An important limitation of existing two-phase models allowing different velocities of solid and water particles is that when water abandons the mixture, porosity decreases and tends to zero. Here, a two-layer model is introduced, including an unsaturated upper layer on top of a saturated layer.
Variable renewable technologies are characterized by a large degree of intermittency due to their natural variability, creating a need for exploiting a range of sources. In this context, the use of energy storage systems is often proposed. There are different ways to store and use the overproduced electricity from these technologies. This paper aims to evaluate the global warming emissions savings obtained from storing the surplus electricity from the variable renewable technologies in the Spanish market and later using it in different end use applications, both for the present day and the 2030 time horizon. First, a review of the life cycle assessments of different energy storage technologies published in the scientific literature is performed. Then, selected values from this review, adapted to the emission intensity of variable renewable electricity stored in Spain, are used to compute GHG savings from storing and using this electricity for different end uses. Results show that the highest benefits in terms of GHG emissions avoidance would be obtained in transport applications and in the power sector. However, as the electricity mix becomes decarbonized, the use of batteries behind the meter would lead to no GHG emissions avoidance. Using electricity to produce heat leads to low GHG emission avoidance benefits that will reduce over time. Benefits will improve in time for the chemical sector, as there are few alternatives to decarbonize this sector. A specific storage strategy must be formulated for each particular case.
In the context of the European Green Deal and the Recovery Plan for Europe, CSP can play its role, by providing dispatchable and flexible energy when other renewable technologies cannot. The aim of this paper is to identify the potential socioeconomic, social and environmental impacts associated to the future deployment of CSP projects in Spain, taking into account the global value chain. Based on an extended multiregional input-output model developed by the authors, this paper identifies the country and sector-origin of nine sustainability indicators for the two dominant CSP technologies (parabolic trough and central receiver). The research considers the deployment of a 200 MW CSP power plant in Spain to compare the sustainability impacts of these two technologies under three different scenarios regarding the country-origin of the main components. The results show that central receivers have more positive economic impacts, both in terms of value added and employment creation, and lower negative environmental and social impacts than the parabolic trough alternative. The economic and environmental impacts of the CSP deployed in Spain depend on the origin of components, with the highest negative environmental impacts occurring when the components come from China and the lowest when they come from Germany. The same occurs for the social impacts and supply risks, which are lower when Germany supplies the main components. The scenario in which Spain supplies all the components performs better than the Chinese supply scenario in terms of social risks, whereas no major differences among them were found on supply risks.
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  • Departmento de Ingeniería Electrónica
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