Experimental investigation of non linear flame dynamics

The main goal of this project is to develop a method to analyze and characterize the evolution of a combustion process by means of image processing. In order to do it some experimental data is required. Analyzing the flame dynamics by means of the evolution of the instabilities, length and motion ease and improve the characterization of the flame behavior simplifying its further analysis. By implementing elliptical coordinates, "Block Matching" and image mapping the process attemps to clarify the motion and development of the combustion in a 2D channel. All the work was made using the software Matlab, creating a code and implementing several algorithms on it. Prior to all the study, an experimental procedure was carried out in the laboratories inside Universidad Carlos III de Madrid, in which several mixtures of propane were ignited inside a Hele-Shaw cell and followed by a high speed camera. Finally, it can be observed how the reaction is more stable and controllable inside the stoichiometric regime, how the curvilinear analysis eases the computations over the instabilities and how the Block Matching algorithm has a perfect implementation into the fluid dynamics field as it becomes so useful to obtain motion.El principal objetivo de este proyecto es el desarrollo de un método de análisis para caracterizar la evolución de un proceso de combustión mediante el procesado de imágenes. Para llevarlo a cabo, algunos datos experimentales son necesarios. Analizando la dinámica de la llama mediante la evolución de sus inestabilidades, longitud y movimiento facilita y mejora la caracterización del comportamiento de la llama simplificando asi su análisis posterior. Implementando coordenadas elípticas, "Block Matching" y mapeado de imágenes, el proceso intenta esclarecer el movimiento y desarrollo de la combustión en un canal 2D. Todo el trabajo fue realizado mediante el software Matlab, creando un código e implementando varios algoritmos en él. Antes de todo este estudio, un experimento fue realizado en los laboratorios de la Universidad Carlos III de Madrid, en el cual varias mezclas de propano con aire fueron encendidas y seguidas por una cámara de alta velocidad dentro de una célula de Hele-Shaw. Finalmente, se puede observar como la reacción es más estable y controlable sobre el régimen estequiométrico, como el análisis curvilíneo de las inestabilidades favorece su procesado y como la herramienta de Block Matching tiene una adaptación perfecta al campo de la dinámica de fluidos ya que es muy útil en la obtención de movimiento.Ingeniería Aeroespacia

On the potential contribution of rooftop PV to a sustainable electricity mix: the case of Spain

This work evaluates the potential contribution of rooftop PV to the future electricity mix. Several sustainable scenarios are considered, each comprising different shares of centralized renewables, rooftop PV and storage. For each generation scenario, the storage capacity that balances the net hourly demand is determined, and the portfolio combination that minimizes the cost of supplying electricity is obtained. The analysis is applied to mainland Spain, using public information and detailed granular models, both in time (hourly resolution) and space (municipal level). For the Spanish case, when the flexibility of hydro and biomass generation is taken into account, the least-cost portfolio involves rather modest storage capacities, in the order of daily rather than seasonal values. This shows that a sustainable, almost emissions-free electricity system for Spain is possible, at a cost that can be even lower than current wholesale market prices.Comment: 7 tables & 11 figures in the main body (24 pages), and 13 pages for the supplementary material, wit

Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods

This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad TIN2013-46801-C4-1-

Jackknife Variance Estimation from Complex Survey Designs

Large scale surveys very often involve multi-stage sampling design, where the first-stage units are selected with varying probability sampling without replacement method and the second and subsequent stages units are selected with varying or equal probability sampling schemes. It is well known (vide Chaudhuri and Arnab (1982)) that for such sampling designs it impossible to find an unbiased estimator of the variance of the estimator of the population total (or mean) as a homogeneous quadratic function of the estimators of the totals (means) of second-stage units without estimating variances of the estimators of the totals (means) of the second and sub-sequent stages of sampling. Wolter (1985) has shown that the Jackknife estimators of the population total based on unequal probability sampling overestimates the variance. In this paper we have proposed an alternative Jackknife estimator after reduction of bias from the original Jackknife estimator. The performances of the proposed Jackknife estimator and the original estimator are compared through simulation studies using Household Income and Expenditure Survey (HIES) 2002/03 data collected by CSO, Botswana. The simulation studies reveal that the proposed estimator fares better than the original Jackknife estimator in terms of relative bias and mean-square error

A Framework for Understanding the Strategies of Openness of the Intelligence Services

The relationship of the intelligence services with openness has been elusive and erratic, changing at the path of the scandals that shaked politics and public opinion. At different rhythms and marked by their national contexts, different intelligence services have embarked over the last two decades in different initiatives to promote societal awareness and a better understanding among society on the intelligence function. In this paper, a theoretical framework is proposed for understanding those openness strategies implemented by the intelligence agencies. The paper discusses two potential approaches to openness with a spectrum of mixed approaches in-between them. The first consists of generating and maintaining a (good) image/reputation and, the second is to legitimize its existence and its role within the State. © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC

Robustness of electricity systems with nearly 100% share of renewables: A worst-case study

Several research studies have shown that future sustainable electricity systems, mostly based on renewable generation and storage, are feasible with today's technologies and costs. However, recent episodes of extreme weather conditions, probably associated with climate change, cast shades of doubt on whether the resulting generation portfolios are sufficiently robust to assure, at all times, a suitable balance between generation and demand, when adverse conditions are faced. To address this issue, this work elaborates a methodology intended to determine a sustainable electricity generation system, that can endure extreme weather conditions which are likely to occur. First, using hourly production and demand data from the last decade, along with estimates of new uses of electricity, a worst-case scenario is constructed, including the storage capacity and additional photovoltaic power which are needed to serve the demand on an hourly basis. Next, several key parameters which may have a significant influence on the LCOE are considered, and a sensitivity analysis is carried out to determine their real impact, significance and potential trends. The proposed methodology is then applied to the Spanish system. The results show that, under the hypotheses and conditions considered in this paper, it is possible to design a decarbonized electricity system that, taking advantage of existing sustainable assets, satisfies the long-term needs by providing a reliable supply at an average cost significantly lower than current market prices.Agencia Estatal de Investigación (AEI) PID2020-116433RB-I00Centro para el Desarrollo Tecnológico Industrial (CDTI) España CER-2019101

Detection of Non-Technical Losses in Smart Distribution Networks: a Review

With the advent of smart grids, distribution utilities have initiated a large deployment of smart meters on the premises of the consumers. The enormous amount of data obtained from the consumers and communicated to the utility give new perspectives and possibilities for various analytics-based applications. In this paper the current smart metering-based energy-theft detection schemes are reviewed and discussed according to two main distinctive categories: A) system statebased, and B) arti cial intelligence-based.Comisión Europea FP7-PEOPLE-2013-IT

Robustness of electricity systems with nearly 100% share of renewables: a worst-case study

Several research studies have shown that future sustainable electricity systems, mostly based on renewable generation and storage, are feasible with current technologies and costs. However, recent episodes of extreme weather conditions, probably associated with climate change, cast shades of doubt on whether the resulting generation portfolios are sufficiently robust to assure, at all times, a suitable balance between generation and demand, when adverse conditions are faced. To address this issue, this work elaborates a methodology intended to determine a sustainable electricity system that can endure extreme weather conditions, which are likely to occur. First, using hourly production and demand data from the last decade, along with estimates of new uses of electricity, a worst-case scenario is constructed, including the storage capacity and additional photovoltaic power which are needed to serve the demand on an hourly basis. Next, several key parameters which may have a significant influence on the LCOE are considered, and a sensitivity analysis is carried out to determine their real impact, significance and potential trends. The proposed methodology is then applied to the Spanish system. The results show that, under the hypotheses and conditions considered in this paper, it is possible to design a decarbonized electricity system that, taking advantage of existing sustainable assets, satisfies the long-term needs by providing a reliable supply at an average cost significantly lower than current market prices.Comment: 33 pages, 13 figures, 10 table