### Browsing by Author "Ramos del Olmo, Ángel Manuel"

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Publication A compositional Eulerian approach for modeling oil spills in the sea(Elsevier, 2021-10-22) Ivorra, Benjamin; Gómez, Susana; Carrera, Jesus; Ramos del Olmo, Ángel ManuelWe present a Compositional Eulerian model to forecast the evolution of oil spills in the sea. The model allows studying the fate of not only the oil concentration but also of each component (e.g., volatile, non-volatile, water in the oil). Therefore, the problem is formulated as a conservation equation for each component, plus an equation to estimate the age of the oil, which allows us to assess weathering processes (e.g., evaporation, natural dispersion, emulsion) and the associated changes in oil properties. We describe an efficient implementation, using second order numerical schemes for advection and nonlinear diffusion terms, to reduce numerical diffusion. We perform numerical experiments, based on real and synthetic cases, to illustrate and validate the capabilities of our model to forecast the evolution of oil spills and to perform environmental risk analysis in the case of a potential accident.Publication A controllability approach to shape identification(Pergamon-Elsevier Science Ltd, 2008) Azencott, R.; Glowinski, R.; Ramos del Olmo, Ángel ManuelThe main goal of this work is to discuss a controllability approach to the image matching/shape identification problem, an important issue in many applications, medical ones in particular. The matching problem is formulated as an approximate controllability problem involving a cost functional whose gradient is computed using an adjoint equation based methodology. The time discrete version of the image matching problem is also discussed in this work.Publication A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru(Elsevier, 2014) Martínez López, Beatriz; Ivorra, Benjamin; Fernández Carrión, Eduardo; Perez, A.M.; Medel-Herrero, A.; Sánchez-Vízcaino Buendía, Fernando; Ramos del Olmo, Ángel Manuel; Sánchez-Vizcaíno, José ManuelThis study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of food animal diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI-II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV), connects outputs from mI-III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I-IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 73 (1–1164), 2,152 (1–13,250), 63 days (0–442), and US$1.2 million (1,072–9.5 million), respectively. Spread of disease was primarily local (<4.5 km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru.Publication A Multi-Layer Line Search Method to Improve the Initialization of Optimization Algorithms (Preprint submitted to Optimization Online)(Mathematical Otimization Society, 2015-03-23) Ivorra, Benjamin; Mohammadi, Bijan; Ramos del Olmo, Ángel ManuelWe introduce a novel metaheuristic methodology to improve the initialization of a given deterministic or stochastic optimization algorithm. Our objective is to improve the performance of the considered algorithm, called core optimization algorithm, by reducing its number of cost function evaluations, by increasing its success rate and by boosting the precision of its results. In our approach, the core optimization is considered as a suboptimization problem for a multi-layer line search method. The approach is presented and implemented for various particular core optimization algorithms: Steepest Descent, Heavy-Ball, Genetic Algorithm, Differential Evolution and Controlled Random Search. We validate our methodology by considering a set of low and high dimensional benchmark problems (i.e., problems of dimension between 2 and 1000). The results are compared to those obtained with the core optimization algorithms alone and with two additional global optimization methods (Direct Tabu Search and Continuous Greedy Randomized Adaptive Search). These latter also aim at improving the initial condition for the core algorithms. The numerical results seem to indicate that our approach improves the performances of the core optimization algorithms and allows to generate algorithms more efficient than the other optimization methods studied here. A Matlab optimization package called ”Global Optimization Platform” (GOP), implementing the algorithms presented here, has been developed and can be downloaded at: http://www.mat.ucm.es/momat/software.htmPublication A Multi-Layers Method to Improve Optimization Algorithms. Application to the Design of Dispersive Bioreactors for Water Treatment(2011-12) Ivorra, Benjamin; Bello Rivas, Juan Manuel; Ramos del Olmo, Ángel Manuel; Harmand, Jerome; Rapaport, AlainPublication A multi-objective approach to identify parameters of compartmental epidemiological models—Application to Ebola Virus Disease epidemics(Elsevier, 2023) Ferrández, M.R.; Ivorra, Benjamin; Redondo, Juana L.; Ramos del Olmo, Ángel Manuel; Ortigosa, Pilar M.In this work, we propose a novel methodology to identify parameters of compartmental epidemiological models. It is based on solving a multi-objective optimization problem that consists in fitting some of the model outputs to real observations. First, according to the available data of the considered epidemic, we define a multi-objective optimization problem where the model parameters are the optimization variables. Then, this problem is solved by considering a particular optimization algorithm called ParWASF-GA (Parallel Weighting Achievement Scalarizing Function Genetic Algorithm). Finally, the decision maker chooses, within the set of possible solutions, the values of parameters that better suit his/her preferences. In order to illustrate the benefit of using our approach, it is applied to estimate the parameters of a deterministic epidemiological model, called Be-CoDiS (Between-Countries Disease Spread), used to forecast the possible spread of human diseases within and between countries. We consider data from different Ebola outbreaks from 2014 up to 2019. In all cases, the proposed methodology helps to obtain reasonable predictions of the epidemic magnitudes with the considered model.Publication A novel spatial and stochastic model to evaluate the within and between farm transmission of classical swine fever virus: II Validation of the model(Elsevier, 2012) Martínez López, Beatriz; Ivorra, Benjamin; Ramos del Olmo, Ángel Manuel; Sánchez-Vizcaíno, José ManuelA new, recently published, stochastic and spatial model for the evaluation of classical swine fever virus (CSFV) spread into Spain has been validated by using several methods. Internal validity, sensitivity analysis, validation using historical data, comparison with other models and experiments on data validity were used to evaluate the overall reliability and robustness of the model. More than 100 modifications in input data and parameters were evaluated. Outputs were obtained after 1000 iterations for each new scenario of the model. As a result, the model was shown to be robust, being the probability of infection by local spread, the time from infectious to clinical signs state, the probability of detection based on clinical signs at day t after detection of the index case outside the control and surveillance zones and the maximum number of farms to be depopulated at day t the parameters that more influence (>10% of change) on the magnitude and duration of the epidemic. The combination of a within- and between- farm spread model was also shown to give significantly different results than using a purely between-farm spread model. Methods and results presented here were intended to be useful to better understand and apply the model, to identify key parameters for which it will be critical to have good estimates and to provide better support for prevention and control of future CSFV outbreaks.Publication A novel spatial and stochastic model to evaluate the within- and between-farm transmission of classical swine fever virus. I. General concepts and description of the model(Elsevier Science, 2011-01-27) Martínez López, Beatriz; Ivorra, Benjamin; Ramos del Olmo, Ángel Manuel; Sánchez-Vizcaíno, José ManuelA new stochastic and spatial model was developed to evaluate the potential spread of classical swine fever virus (CSFV) within- and between-farms, and considering the specific farm-to-farm contact network. Within-farm transmission was simulated using a modified SI model. Between-farm transmission was assumed to occur by direct contacts (i.e. animal movement) and indirect contacts (i.e. local spread, vehicle and person contacts) and considering the spatial location of farms. Control measures dictated by the European legislation (i.e. depopulation of infected farms, movement restriction, zoning, surveillance, contact tracing) were also implemented into the model. Model experimentation was performed using real data from Segovia, one of the provinces with highest density of pigs in Spain, and results were presented using the mean, 95% probability intervals [95% PI] and risk maps. The estimated mean [95% PI] number of infected, quarantined and depopulated farms were 3 [1,17], 23 [0,76] and 115 [0,318], respectively. The duration of the epidemic was 63 [26,177] days and the most important way of transmission was associated with local spread (61.4% of the infections). Results were consistent with the spread of previous CSFV introductions into the study region. The model and results presented here may be useful for the decision making process and for the improvement of the prevention and control programmes for CSFV.Publication A numerical method to solve a duopolistic differential game in a closed-loop equilibrium(Universidad Complutense. Departamento de Matemática Aplicada, 2012-10) De la Cruz, Jorge H.; Ivorra, Benjamin; Ramos del Olmo, Ángel ManuelIn this work, we develope a numerical method to solve infinite time differential games in closed-loop equilibria. Differential games are thought to be run in dynamic decissions and competitive situations, such as marketing investments and pricing policies in a company. Closed-loop equilibria allow us to obtain strategies as a function of ourselves and our competitor. We apply our algorithm to a real data set of two competitive firms. We show how our algorithm is able to develop a different price-advertising strategy to get bigger benefitsPublication A simple but complex enough -SIR type model to be used with COVID-19 real data. Application to the case of Italy(Elsevier, 2021-01-01) Ramos del Olmo, Ángel Manuel; Fernández, M. R.; Vela Pérez, M.; Kubik, Alicja Barbara; Ivorra, BenjaminSince the start of the COVID-19 pandemic in China many models have appeared in the literature, trying to simulate its dynamics. Focusing on modeling the biological and sociological mechanisms which influence the disease spread, the basic reference example is the SIR model. However, it is too simple to be able to model those mechanisms (including the three main types of control measures: social distancing, contact tracing and health system measures) to fit real data and to simulate possible future scenarios. A question, then, arises: how much and how do we need to complexify a SIR model? We develop a -SEIHQRD model, which may be the simplest one satisfying the mentioned requirements for arbitrary territories and can be simplified in particular cases. We show its very good performance in the Italian case and study different future scenarios.Publication A uniqueness result for the identification of a time-dependent diffusion coefficient(IOP Publishing, 2013) Fraguela, A.; Infante del Río, Juan Antonio; Ramos del Olmo, Ángel Manuel; Rey Cabezas, Jose MaríaThis paper deals with the problem of determining the time-dependent thermal diffusivity coefficient of a medium, when the evolution of the temperature in a part of it is known. Such situations arise in the context of food technology, when thermal processes at high pressures are used for extending the shelf life of the food, in order to preserve its nutritional and organoleptic properties (Infante et al 2009 On the Modelling and Simulation of High Pressure Processes and Inactivation of Enzymes in Food Engineering pp 2203–29 and Otero et al 2007 J. Food Eng. 78 1463–70). The phenomenon is modeled by the heat equation involving a term which depends on the source temperature and pressure increase, and appropriate initial and boundary conditions. We study the inverse problem of determining time-dependent thermal diffusivities k, when some temperature measurements at the border and inside the medium are known. We prove the uniqueness of the inverse problem solution under suitable a priori assumptions on regularity, size and growth of k.Publication A variance-expected compliance approach for topology optimization(2010) Carrasco, Miguel; Ivorra, Benjamin; Lecaros, Rodrigo; Ramos del Olmo, Ángel ManuelIn this paper we focus on the adaptation to topology optimization of a previous variance-expected compliance applied to truss design. The principal objective of such a model is to find robust structures for a given main load and its perturbations. In particular we are interested in avoiding high compliance values in cases of important perturbations. In the first part, we recall the varianceexpected formulation and main results in the case of truss structures. Then, we extend this model to topology optimization. Finally, we study the interest of this model on a 2D benchmark test.Publication A Variance-Expected Compliance Model for Structural Optimization(Springer, 2012-01) Carrasco, Miguel; Ivorra, Benjamin; Ramos del Olmo, Ángel Manuelt The goal of this paper is to find robust structures for a given main load and its perturbations. In the first part, we show the mathematical formulation of an original variance-expected compliance model used for structural optimization. In the second part, we study the interest of this model on two 3D benchmark test cases and compare the obtained results with those given by an expected compliance modelPublication Algunos problemas en ecuaciones en derivadas parciales relacionados con la teoría de control(Universidad Complutense de Madrid, Servicio de Publicaciones, 2002) Ramos del Olmo, Ángel Manuel; Díaz Díaz, Jesús IldefonsoEn esta memoria se abordan dos problemas relacionados con la teoría de control de ecuaciones en derivadas parciales.en el primer capitulo se estudia la controlabilidad aproximada de ecuaciones parabólicas semilineales y se obtienen tanto resultados de controlabilidad como contraejemplos. En el segundo se analiza la factorización de una ecuación elíptica lineal y se establece un paralelismo con la factorización lu del sistema discretizado correspondientePublication An expected compliance model based on topology optimization for designing structures submitted to random loads(Element d.o.o, 2012) Carrasco, Miguel; Ivorra, Benjamin; Lecaros, Rodrigo; Ramos del Olmo, Ángel ManuelIn this paper, we focus in developing a stochastic model for topology optimization. The principal objective of such a model is to find robust structures for a given main load having a stochastic behavior. In the first part, we present the expected compliance formulation and some results in topology optimization. Then, in order to illustrate the interest of our approach, we consider a preliminary 3D cantilever benchmark experiment and compare the obtained results with the one given by a single load approach.Publication An Hybrid Global Optimization Method For Credit Portfolio Management(2007-08) Ivorra, Benjamin; Mohammadi, Bijan; Ramos del Olmo, Ángel ManuelPublication Analysis and simplification of a mathematical model for high-pressure food processes(Elsevier, 2014-01-01) Smith, Nadia A. S; Mitchell, S. L.; Ramos del Olmo, Ángel ManuelNowadays, consumers look for minimally processed, additive-free food products that maintain their organoleptic properties. This has led to the development of new technologies for food processing. One emerging technology is high hydrostatic pressure, as it proves to be very effective in prolonging the shelf life of foods without losing its properties. Recent research has involved modelling and simulating the effect of combining thermal and high pressure processes (see Denys et al. (2000), Infante et al. (2009), Knoerzer et al. (2007), Otero et al. (2007)). The focus is mainly on the inactivation of certain enzymes and microorganisms that are harmful to food. Various mathematical models that study the behaviour of these enzymes and microorganisms during a high pressure process have been proposed (see Infante et al. (2009), Knoerzer et al. (2007)). Such models need the temperature and pressure profiles of the whole process as an input. In this paper we present two dimensional models, with different types of boundary conditions, to calculate the temperature profile for solid type foods. We give an exact solution and propose several simplifications, in both two and one dimensions. The temperature profile of these simplified two and one dimensional models is calculated both numerically and analytically, and the solutions are compared. Our results show a very good agreement for all the approximations proposed, and so we can conclude that the simplifications and dimensional reduction are reasonable for certain parameter values, which are specified in this work.Publication Analysis and simplification of a mathematical model for high-pressure food processes(Elsevier, 2014-01-01) Smith, N.A.S.; Mitchell, S. L.; Ramos del Olmo, Ángel ManuelNowadays, consumers look for minimally processed, additive-free food products that maintain their organoleptic properties. This has led to the development of new technologies for food processing. One emerging technology is high hydrostatic pressure, as it proves to be very effective in prolonging the shelf life of foods without losing its properties. Recent research has involved modelling and simulating the effect of combining thermal and high pressure processes (see Denys et al. (2000) [3], Infante et al. (2009) [5], Knoerzer et al. (2007) [6], Otero et al. (2007) [9]). The focus is mainly on the inactivation of certain enzymes and microorganisms that are harmful to food. Various mathematical models that study the behaviour of these enzymes and microorganisms during a high pressure process have been proposed (see Infante et al. (2009) [5], Knoerzer et al. (2007) [61). Such models need the temperature and pressure profiles of the whole process as an input. In this paper we present two dimensional models, with different types of boundary conditions, to calculate the temperature profile for solid type foods. We give an exact solution and propose several simplifications, in both two and one dimensions. The temperature profile of these simplified two and one dimensional models is calculated both numerically and analytically, and the solutions are compared. Our results show a very good agreement for all the approximations proposed, and so we can conclude that the simplifications and dimensional reduction are reasonable for certain parameter values, which are specified in this work.Publication Approximate controllability and obstruction phenomena for quasilinear diffusion equations(John Wiley & Sons., 1997) Díaz Díaz, Jesús Ildefonso; Ramos del Olmo, Ángel Manuel; Bristeau, M.O; Etgen, G.; Fitzgibbon, W.; Lions, J.L.; Periaux, J; Wheeler, M.F.Publication Asymptotic stability of a coupled Advection-Diffusion-Reaction system arising in bioreactor processes.(2016-10-18) Crespo Moya, María; Ramos del Olmo, Ángel Manuel; Ivorra, BenjaminIn this work, we perform an asymptotic analysis of a coupled system of two Advection-Diffusion-Reaction equations with Danckwerts boundary conditions, which models the interaction between a microbial population (e.g., bacterias), called biomass, and a diluted organic contaminant (e.g., nitrates), called substrate, in a continuous flow bioreactor. This system exhibits, under suitable conditions, two stable equilibrium states: one steady state in which the biomass becomes extinct and no reaction is produced, called washout, and another steady state, which corresponds to the partial elimination of the substrate. We use the method of linearization to give sufficient conditions for the asymptotic stability of the two stable equilibrium configurations. Finally, we compare our asymptotic analysis with the usual asymptotic analysis associated to the continuous bioreactor when it is modeled with ordinary differential equations.