Calculus of the uncertainty in acoustic field measurements: comparative study between the uncertainty propagation method and the distribution propagation method

The new Spanish Regulation in Building Acoustic establishes values and limits for the different acoustic magnitudes whose fulfillment can be verify by means field measurements. In this sense, an essential aspect of a field measurement is to give the measured magnitude and the uncertainty associated to such a magnitude. In the calculus of the uncertainty it is very usual to follow the uncertainty propagation method as described in the Guide to the expression of Uncertainty in Measurements (GUM). Other option is the numerical calculus based on the distribution propagation method by means of Monte Carlo simulation. In fact, at this stage, it is possible to find several publications developing this last method by using different software programs. In the present work, we used Excel for the Monte Carlo simulation for the calculus of the uncertainty associated to the different magnitudes derived from the field measurements following ISO 140-4, 140-5 and 140-7. We compare the results with the ones obtained by the uncertainty propagation method. Although both methods give similar values, some small differences have been observed. Some arguments to explain such differences are the asymmetry of the probability distributions associated to the entry magnitudes,the overestimation of the uncertainty following the GUM

Preference intensity in MCDM when an additive utility function represents DM preferences

We propose a new method for ranking alternatives in multicriteria decision-making problems when there is imprecision concerning the alternative performances, component utility functions and weights. We assume decision maker?s preferences are represented by an additive multiattribute utility function, in which weights can be modeled by independent normal variables, fuzzy numbers, value intervals or by an ordinal relation. The approaches are based on dominance measures or exploring the weight space in order to describe which ratings would make each alternative the preferred one. On the one hand, the approaches based on dominance measures compute the minimum utility difference among pairs of alternatives. Then, they compute a measure by which to rank the alternatives. On the other hand, the approaches based on exploring the weight space compute confidence factors describing the reliability of the analysis. These methods are compared using Monte Carlo simulation.

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.

Cover crops effect on farm benefits and nitrate leaching: Linking economic and environmental analysis.

Introducing cover crops (CC) interspersed with intensively fertilized crops in rotation has the potential to reduce nitrate leaching. This paper evaluates various strategies involving CC between maize and compares the economic and environmental results with respect to a typical maize?fallow rotation. The comparison is performed through stochastic (Monte-Carlo) simulation models of farms? profits using probability distribution functions (pdfs) of yield and N fertilizer saving fitted with data collected from various field trials and pdfs of crop prices and the cost of fertilizer fitted from statistical sources. Stochastic dominance relationships are obtained to rank the most profitable strategies from a farm financial perspective. A two-criterion comparison scheme is proposed to rank alternative strategies based on farm profit and nitrate leaching levels, taking the baseline scenario as the maize?fallow rotation. The results show that when CC biomass is sold as forage instead of keeping it in the soil, greater profit and less leaching of nitrates are achieved than in the baseline scenario. While the fertilizer saving will be lower if CC is sold than if it is kept in the soil, the revenue obtained from the sale of the CC compensates for the reduced fertilizer savings. The results show that CC would perhaps provide a double dividend of greater profit and reduced nitrate leaching in intensive irrigated cropping systems in Mediterranean regions.

A new dominance intensity method to deal with ordinal information about a DM's preferences within MAVT

Dominance measuring methods are a new approach to deal with complex decision-making problems with imprecise information. These methods are based on the computation of pairwise dominance values and exploit the information in the dominance matrix in dirent ways to derive measures of dominance intensity and rank the alternatives under consideration. In this paper we propose a new dominance measuring method to deal with ordinal information about decision-maker preferences in both weights and component utilities. It takes advantage of the centroid of the polytope delimited by ordinal information and builds triangular fuzzy numbers whose distances to the crisp value 0 constitute the basis for the de?nition of a dominance intensity measure. Monte Carlo simulation techniques have been used to compare the performance of this method with other existing approaches.

Risk-based methodology for parameter calibration of a reservoir flood control model

Flash floods are of major relevance in natural disaster management in the Mediterranean region. In many cases, the damaging effects of flash floods can be mitigated by adequate management of flood control reservoirs. This requires the development of suitable models for optimal operation of reservoirs. A probabilistic methodology for calibrating the parameters of a reservoir flood control model (RFCM) that takes into account the stochastic variability of flood events is presented. This study addresses the crucial problem of operating reservoirs during flood events, considering downstream river damages and dam failure risk as conflicting operation criteria. These two criteria are aggregated into a single objective of total expected damages from both the maximum released flows and stored volumes (overall risk index). For each selected parameter set the RFCM is run under a wide range of hydrologic loads (determined through Monte Carlo simulation). The optimal parameter set is obtained through the overall risk index (balanced solution) and then compared with other solutions of the Pareto front. The proposed methodology is implemented at three different reservoirs in the southeast of Spain. The results obtained show that the balanced solution offers a good compromise between the two main objectives of reservoir flood control management

Modelos Estadísticos Dinámicos para Análisis de Evolución de Tasas de Accidentes: Metodología y Herramientas Computacionales

Los accidentes del tráfico son un fenómeno social muy relevantes y una de las principales causas de mortalidad en los países desarrollados. Para entender este fenómeno complejo se aplican modelos econométricos sofisticados tanto en la literatura académica como por las administraciones públicas. Esta tesis está dedicada al análisis de modelos macroscópicos para los accidentes del tráfico en España. El objetivo de esta tesis se puede dividir en dos bloques: a. Obtener una mejor comprensión del fenómeno de accidentes de trafico mediante la aplicación y comparación de dos modelos macroscópicos utilizados frecuentemente en este área: DRAG y UCM, con la aplicación a los accidentes con implicación de furgonetas en España durante el período 2000-2009. Los análisis se llevaron a cabo con enfoque frecuencista y mediante los programas TRIO, SAS y TRAMO/SEATS. b. La aplicación de modelos y la selección de las variables más relevantes, son temas actuales de investigación y en esta tesis se ha desarrollado y aplicado una metodología que pretende mejorar, mediante herramientas teóricas y prácticas, el entendimiento de selección y comparación de los modelos macroscópicos. Se han desarrollado metodologías tanto para selección como para comparación de modelos. La metodología de selección de modelos se ha aplicado a los accidentes mortales ocurridos en la red viaria en el período 2000-2011, y la propuesta metodológica de comparación de modelos macroscópicos se ha aplicado a la frecuencia y la severidad de los accidentes con implicación de furgonetas en el período 2000-2009. Como resultado de los desarrollos anteriores se resaltan las siguientes contribuciones: a. Profundización de los modelos a través de interpretación de las variables respuesta y poder de predicción de los modelos. El conocimiento sobre el comportamiento de los accidentes con implicación de furgonetas se ha ampliado en este proceso. bl. Desarrollo de una metodología para selección de variables relevantes para la explicación de la ocurrencia de accidentes de tráfico. Teniendo en cuenta los resultados de a) la propuesta metodológica se basa en los modelos DRAG, cuyos parámetros se han estimado con enfoque bayesiano y se han aplicado a los datos de accidentes mortales entre los años 2000-2011 en España. Esta metodología novedosa y original se ha comparado con modelos de regresión dinámica (DR), que son los modelos más comunes para el trabajo con procesos estocásticos. Los resultados son comparables, y con la nueva propuesta se realiza una aportación metodológica que optimiza el proceso de selección de modelos, con escaso coste computacional. b2. En la tesis se ha diseñado una metodología de comparación teórica entre los modelos competidores mediante la aplicación conjunta de simulación Monte Cario, diseño de experimentos y análisis de la varianza ANOVA. Los modelos competidores tienen diferentes estructuras, que afectan a la estimación de efectos de las variables explicativas. Teniendo en cuenta el estudio desarrollado en bl) este desarrollo tiene el propósito de determinar como interpretar la componente de tendencia estocástica que un modelo UCM modela explícitamente, a través de un modelo DRAG, que no tiene un método específico para modelar este elemento. Los resultados de este estudio son importantes para ver si la serie necesita ser diferenciada antes de modelar. b3. Se han desarrollado nuevos algoritmos para realizar los ejercicios metodológicos, implementados en diferentes programas como R, WinBUGS, y MATLAB. El cumplimiento de los objetivos de la tesis a través de los desarrollos antes enunciados se remarcan en las siguientes conclusiones: 1. El fenómeno de accidentes del tráfico se ha analizado mediante dos modelos macroscópicos. Los efectos de los factores de influencia son diferentes dependiendo de la metodología aplicada. Los resultados de predicción son similares aunque con ligera superioridad de la metodología DRAG. 2. La metodología para selección de variables y modelos proporciona resultados prácticos en cuanto a la explicación de los accidentes de tráfico. La predicción y la interpretación también se han mejorado mediante esta nueva metodología. 3. Se ha implementado una metodología para profundizar en el conocimiento de la relación entre las estimaciones de los efectos de dos modelos competidores como DRAG y UCM. Un aspecto muy importante en este tema es la interpretación de la tendencia mediante dos modelos diferentes de la que se ha obtenido información muy útil para los investigadores en el campo del modelado. Los resultados han proporcionado una ampliación satisfactoria del conocimiento en torno al proceso de modelado y comprensión de los accidentes con implicación de furgonetas y accidentes mortales totales en España. ABSTRACT Road accidents are a very relevant social phenomenon and one of the main causes of death in industrialized countries. Sophisticated econometric models are applied in academic work and by the administrations for a better understanding of this very complex phenomenon. This thesis is thus devoted to the analysis of macro models for road accidents with application to the Spanish case. The objectives of the thesis may be divided in two blocks: a. To achieve a better understanding of the road accident phenomenon by means of the application and comparison of two of the most frequently used macro modelings: DRAG (demand for road use, accidents and their gravity) and UCM (unobserved components model); the application was made to van involved accident data in Spain in the period 2000-2009. The analysis has been carried out within the frequentist framework and using available state of the art software, TRIO, SAS and TRAMO/SEATS. b. Concern on the application of the models and on the relevant input variables to be included in the model has driven the research to try to improve, by theoretical and practical means, the understanding on methodological choice and model selection procedures. The theoretical developments have been applied to fatal accidents during the period 2000-2011 and van-involved road accidents in 2000-2009. This has resulted in the following contributions: a. Insight on the models has been gained through interpretation of the effect of the input variables on the response and prediction accuracy of both models. The behavior of van-involved road accidents has been explained during this process. b1. Development of an input variable selection procedure, which is crucial for an efficient choice of the inputs. Following the results of a) the procedure uses the DRAG-like model. The estimation is carried out within the Bayesian framework. The procedure has been applied for the total road accident data in Spain in the period 2000-2011. The results of the model selection procedure are compared and validated through a dynamic regression model given that the original data has a stochastic trend. b2. A methodology for theoretical comparison between the two models through Monte Carlo simulation, computer experiment design and ANOVA. The models have a different structure and this affects the estimation of the effects of the input variables. The comparison is thus carried out in terms of the effect of the input variables on the response, which is in general different, and should be related. Considering the results of the study carried out in b1) this study tries to find out how a stochastic time trend will be captured in DRAG model, since there is no specific trend component in DRAG. Given the results of b1) the findings of this study are crucial in order to see if the estimation of data with stochastic component through DRAG will be valid or whether the data need a certain adjustment (typically differencing) prior to the estimation. The model comparison methodology was applied to the UCM and DRAG models, considering that, as mentioned above, the UCM has a specific trend term while DRAG does not. b3. New algorithms were developed for carrying out the methodological exercises. For this purpose different softwares, R, WinBUGs and MATLAB were used. These objectives and contributions have been resulted in the following findings: 1. The road accident phenomenon has been analyzed by means of two macro models: The effects of the influential input variables may be estimated through the models, but it has been observed that the estimates vary from one model to the other, although prediction accuracy is similar, with a slight superiority of the DRAG methodology. 2. The variable selection methodology provides very practical results, as far as the explanation of road accidents is concerned. Prediction accuracy and interpretability have been improved by means of a more efficient input variable and model selection procedure. 3. Insight has been gained on the relationship between the estimates of the effects using the two models. A very relevant issue here is the role of trend in both models, relevant recommendations for the analyst have resulted from here. The results have provided a very satisfactory insight into both modeling aspects and the understanding of both van-involved and total fatal accidents behavior in Spain.

Evaluación de la seguridad al deslizamiento de una presa de fábrica en un cimiento con una familia de discontinuidades y con un criterio de rotura con ley de fluencia no asociada

En España existen del orden de 1,300 grandes presas, de las cuales un 20% fueron construidas antes de los años 60. El hecho de que existan actualmente una gran cantidad de presas antiguas aún en operación, ha producido un creciente interés en reevaluar su seguridad empleando herramientas nuevas o modificadas que incorporan modelos de fallo teóricos más completos, conceptos geotécnicos más complejos y nuevas técnicas de evaluación de la seguridad. Una manera muy común de abordar el análisis de estabilidad de presas de gravedad es, por ejemplo, considerar el deslizamiento a través de la interfase presa-cimiento empleando el criterio de rotura lineal de Mohr-Coulomb, en donde la cohesión y el ángulo de rozamiento son los parámetros que definen la resistencia al corte de la superficie de contacto. Sin embargo la influencia de aspectos como la presencia de planos de debilidad en el macizo rocoso de cimentación; la influencia de otros criterios de rotura para la junta y para el macizo rocoso (ej. el criterio de rotura de Hoek-Brown); las deformaciones volumétricas que ocurren durante la deformación plástica en el fallo del macizo rocoso (i.e., influencia de la dilatancia) no son usualmente consideradas durante el diseño original de la presa. En este contexto, en la presente tesis doctoral se propone una metodología analítica para el análisis de la estabilidad al deslizamiento de presas de hormigón, considerando un mecanismo de fallo en la cimentación caracterizado por la presencia de una familia de discontinuidades. En particular, se considera la posibilidad de que exista una junta sub-horizontal, preexistente y persistente en el macizo rocoso de la cimentación, con una superficie potencial de fallo que se extiende a través del macizo rocoso. El coeficiente de seguridad es entonces estimado usando una combinación de las resistencias a lo largo de los planos de rotura, cuyas resistencias son evaluadas empleando los criterios de rotura no lineales de Barton y Choubey (1977) y Barton y Bandis (1990), a lo largo del plano de deslizamiento de la junta; y el criterio de rotura de Hoek y Brown (1980) en su versión generalizada (Hoek et al. 2002), a lo largo del macizo rocoso. La metodología propuesta también considera la influencia del comportamiento del macizo rocoso cuando este sigue una ley de flujo no asociada con ángulo de dilatancia constante (Hoek y Brown 1997). La nueva metodología analítica propuesta es usada para evaluar las condiciones de estabilidad empleando dos modelos: un modelo determinista y un modelo probabilista, cuyos resultados son el valor del coeficiente de seguridad y la probabilidad de fallo al deslizamiento, respectivamente. El modelo determinista, implementado en MATLAB, es validado usando soluciones numéricas calculadas mediante el método de las diferencias finitas, empleando el código FLAC 6.0. El modelo propuesto proporciona resultados que son bastante similares a aquellos calculados con FLAC; sin embargo, los costos computacionales de la formulación propuesta son significativamente menores, facilitando el análisis de sensibilidad de la influencia de los diferentes parámetros de entrada sobre la seguridad de la presa, de cuyos resultados se obtienen los parámetros que más peso tienen en la estabilidad al deslizamiento de la estructura, manifestándose además la influencia de la ley de flujo en la rotura del macizo rocoso. La probabilidad de fallo es obtenida empleando el método de fiabilidad de primer orden (First Order Reliability Method; FORM), y los resultados de FORM son posteriormente validados mediante simulaciones de Monte Carlo. Los resultados obtenidos mediante ambas metodologías demuestran que, para el caso no asociado, los valores de probabilidad de fallo se ajustan de manera satisfactoria a los obtenidos mediante las simulaciones de Monte Carlo. Los resultados del caso asociado no son tan buenos, ya que producen resultados con errores del 0.7% al 66%, en los que no obstante se obtiene una buena concordancia cuando los casos se encuentran en, o cerca de, la situación de equilibrio límite. La eficiencia computacional es la principal ventaja que ofrece el método FORM para el análisis de la estabilidad de presas de hormigón, a diferencia de las simulaciones de Monte Carlo (que requiere de al menos 4 horas por cada ejecución) FORM requiere tan solo de 1 a 3 minutos en cada ejecución. There are 1,300 large dams in Spain, 20% of which were built before 1960. The fact that there are still many old dams in operation has produced an interest of reevaluate their safety using new or updated tools that incorporate state-of-the-art failure modes, geotechnical concepts and new safety assessment techniques. For instance, for gravity dams one common design approach considers the sliding through the dam-foundation interface, using a simple linear Mohr-Coulomb failure criterion with constant friction angle and cohesion parameters. But the influence of aspects such as the persistence of joint sets in the rock mass below the dam foundation; of the influence of others failure criteria proposed for rock joint and rock masses (e.g. the Hoek-Brown criterion); or the volumetric strains that occur during plastic failure of rock masses (i.e., the influence of dilatancy) are often no considered during the original dam design. In this context, an analytical methodology is proposed herein to assess the sliding stability of concrete dams, considering an extended failure mechanism in its rock foundation, which is characterized by the presence of an inclined, and impersistent joint set. In particular, the possibility of a preexisting sub-horizontal and impersistent joint set is considered, with a potential failure surface that could extend through the rock mass; the safety factor is therefore computed using a combination of strength along the rock joint (using the nonlinear Barton and Choubey (1977) and Barton and Bandis (1990) failure criteria) and along the rock mass (using the nonlinear failure criterion of Hoek and Brown (1980) in its generalized expression from Hoek et al. (2002)). The proposed methodology also considers the influence of a non-associative flow rule that has been incorporated using a (constant) dilation angle (Hoek and Brown 1997). The newly proposed analytical methodology is used to assess the dam stability conditions, employing for this purpose the deterministic and probabilistic models, resulting in the sliding safety factor and the probability of failure respectively. The deterministic model, implemented in MATLAB, is validated using numerical solution computed with the finite difference code FLAC 6.0. The proposed deterministic model provides results that are very similar to those computed with FLAC; however, since the new formulation can be implemented in a spreadsheet, the computational cost of the proposed model is significantly smaller, hence allowing to more easily conduct parametric analyses of the influence of the different input parameters on the dam’s safety. Once the model is validated, parametric analyses are conducting using the main parameters that describe the dam’s foundation. From this study, the impact of the more influential parameters on the sliding stability analysis is obtained and the error of considering the flow rule is assessed. The probability of failure is obtained employing the First Order Reliability Method (FORM). The probabilistic model is then validated using the Monte Carlo simulation method. Results obtained using both methodologies show good agreement for cases in which the rock mass has a nonassociate flow rule. For cases with an associated flow rule errors between 0.70% and 66% are obtained, so that the better adjustments are obtained for cases with, or close to, limit equilibrium conditions. The main advantage of FORM on sliding stability analyses of gravity dams is its computational efficiency, so that Monte Carlo simulations require at least 4 hours on each execution, whereas FORM requires only 1 to 3 minutes on each execution.

Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

Service capacity reserve under uncertainty by hospital's ER's analogies: a practical model for car services

El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.

FPGA Acceleration of Monte Carlo-based Financial Simulation: Design Challenges and Lessons Learnt

The simulation of interest rate derivatives is a powerful tool to face the current market fluctuations. However, the complexity of the financial models and the way they are processed require exorbitant computation times, what is in clear conflict with the need of a processing time as short as possible to operate in the financial market. To shorten the computation time of financial derivatives the use of hardware accelerators becomes a must.

Optimization of Monte Carlo code for clinical simulation of electron beams

The aim of this work is to optimize a Monte Carlo (MC) kernel for electron radiation therapy (IOERT) compatible with intraoperative usage and to integrate it within an existing IOERT dedicated treatment planning system (TPS)

Simulation tools for statistical model comparison: an application to unobserved componenet models versus dynamic regression models

Aplicación de simulación de Monte Carlo y técnicas de Análisis de la Varianza (ANOVA) a la comparación de modelos estocásticos dinámicos para accidentes de tráfico.

MMonCa: A flexible and powerful new Kinetic Monte Carlo simulator

Kinetic Monte Carlo (KMC) is a widely used technique to simulate the evolution of radiation damage inside solids. Despite de fact that this technique was developed several decades ago, there is not an established and easy to access simulating tool for researchers interested in this field, unlike in the case of molecular dynamics or density functional theory calculations. In fact, scientists must develop their own tools or use unmaintained ones in order to perform these types of simulations. To fulfil this need, we have developed MMonCa, the Modular Monte Carlo simulator. MMonCa has been developed using professional C++ programming techniques and has been built on top of an interpreted language to allow having a powerful yet flexible, robust but customizable and easy to access modern simulator. Both non lattice and Lattice KMC modules have been developed. We will present in this conference, for the first time, the MMonCa simulator. Along with other (more detailed) contributions in this meeting, the versatility of MMonCa to study a number of problems in different materials (particularly, Fe and W) subject to a wide range of conditions will be shown. Regarding KMC simulations, we have studied neutron-generated cascade evolution in Fe (as a model material). Starting with a Frenkel pair distribution we have followed the defect evolution up to 450 K. Comparison with previous simulations and experiments shows excellent agreement. Furthermore, we have studied a more complex system (He-irradiated W:C) using a previous parametrization [1]. He-irradiation at 4 K followed by isochronal annealing steps up to 500 K has been simulated with MMonCa. The He energy was 400 eV or 3 keV. In the first case, no damage is associated to the He implantation, whereas in the second one, a significant Frenkel pair concentration (evolving into complex clusters) is associated to the He ions. We have been able to explain He desorption both in the absence and in the presence of Frenkel pairs and we have also applied MMonCa to high He doses and fluxes at elevated temperatures. He migration and trapping dominate the kinetics of He desorption. These processes will be discussed and compared to experimental results. [1] C.S. Becquart et al. J. Nucl. Mater. 403 (2010) 75

Simulation of impulse response for indoor visible light communications using 3D CAD models

n this article, a tool for simulating the channel impulse response for indoor visible light communications using 3D computer-aided design (CAD) models is presented. The simulation tool is based on a previous Monte Carlo ray-tracing algorithm for indoor infrared channel estimation, but including wavelength response evaluation. The 3D scene, or the simulation environment, can be defined using any CAD software in which the user specifies, in addition to the setting geometry, the reflection characteristics of the surface materials as well as the structures of the emitters and receivers involved in the simulation. Also, in an effort to improve the computational efficiency, two optimizations are proposed. The first one consists of dividing the setting into cubic regions of equal size, which offers a calculation improvement of approximately 50% compared to not dividing the 3D scene into sub-regions. The second one involves the parallelization of the simulation algorithm, which provides a computational speed-up proportional to the number of processors used.