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)

A comparative study of Monte Carlo-coupled depletion codes applied to a Sodium Fast Reactor design loaded with minor actinides

inor actinides (MAs) transmutation is a main design objective of advanced nuclear systems such as generation IV Sodium Fast Reactors (SFRs). In advanced fuel cycles, MA contents in final high level waste packages are main contributors to short term heat production as well as to long-term radiotoxicity. Therefore, MA transmutation would have an impact on repository designs and would reduce the environment burden of nuclear energy. In order to predict such consequences Monte Carlo (MC) transport codes are used in reactor design tasks and they are important complements and references for routinely used deterministic computational tools. In this paper two promising Monte Carlo transport-coupled depletion codes, EVOLCODE and SERPENT, are used to examine the impact of MA burning strategies in a SFR core, 3600 MWth. The core concept proposal for MA loading in two configurations is the result of an optimization effort upon a preliminary reference design to reduce the reactivity insertion as a consequence of sodium voiding, one of the main concerns of this technology. The objective of this paper is double. Firstly, efficiencies of the two core configurations for MA transmutation are addressed and evaluated in terms of actinides mass changes and reactivity coefficients. Results are compared with those without MA loading. Secondly, a comparison of the two codes is provided. The discrepancies in the results are quantified and discussed.

Monte Carlo simulation on a system of hard cylinders at a very high packing fraction

Using the Monte Carlo method the behavior of a system of true hard cylinders has been studied. Values of the length-to-breadth ratio L/D and packing fraction η have been chosen similar to those of real nematic liquid crystals. Results include radial distribution function g(r), structure factor S(k), and orientational order parameter M. These results lead to the conclusion that the hard cylinder model may be a useful reference for real mesomorphic phases.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Monte Carlo uncertainty propagation approaches in ADS burn-up calculations

In activation calculations, there are several approaches to quantify uncertainties: deterministic by means of sensitivity analysis, and stochastic by means of Monte Carlo. Here, two different Monte Carlo approaches for nuclear data uncertainty are presented: the first one is the Total Monte Carlo (TMC). The second one is by means of a Monte Carlo sampling of the covariance information included in the nuclear data libraries to propagate these uncertainties throughout the activation calculations. This last approach is what we named Covariance Uncertainty Propagation, CUP. This work presents both approaches and their differences. Also, they are compared by means of an activation calculation, where the cross-section uncertainties of 239Pu and 241Pu are propagated in an ADS activation calculation.

Red Cell Volume Expansion at Altitude: A Meta-analysis and Monte Carlo Simulation

Meta-análisis del volumen de eritrocitos en altitud

FocusDET, a new toolbox for SISCOM analysis. Evaluation of the registration accuracy using monte carlo simulation

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.

On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

Review and comparison of effective delayed neutron fraction calculation methods with Monte Carlo codes

The calculation of the effective delayed neutron fraction, beff , with Monte Carlo codes is a complex task due to the requirement of properly considering the adjoint weighting of delayed neutrons. Nevertheless, several techniques have been proposed to circumvent this difficulty and obtain accurate Monte Carlo results for beff without the need of explicitly determining the adjoint flux. In this paper, we make a review of some of these techniques; namely we have analyzed two variants of what we call the k-eigenvalue technique and other techniques based on different interpretations of the physical meaning of the adjoint weighting. To test the validity of all these techniques we have implemented them with the MCNPX code and we have benchmarked them against a range of critical and subcritical systems for which either experimental or deterministic values of beff are available. Furthermore, several nuclear data libraries have been used in order to assess the impact of the uncertainty in nuclear data in the calculated value of beff .

Efficient Monte Carlo optimization for multi-label classifier chains

Multi-label classification (MLC) is the supervised learning problem where an instance may be associated with multiple labels. Modeling dependencies between labels allows MLC methods to improve their performance at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies. On the one hand, the original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors down the chain. On the other hand, a recent Bayes-optimal method improves the performance, but is computationally intractable in practice. Here we present a novel double-Monte Carlo scheme (M2CC), both for finding a good chain sequence and performing efficient inference. The M2CC algorithm remains tractable for high-dimensional data sets and obtains the best overall accuracy, as shown on several real data sets with input dimension as high as 1449 and up to 103 labels.

Análisis y diseño de multiplicadores y mezcladores mediante el método de Monte Carlo en la banda de THz = Analysis and design of multipliers and mixers via Monte Carlo modelling at THz bands

La región del espectro electromagnético comprendida entre 100 GHz y 10 THz alberga una gran variedad de aplicaciones en campos tan dispares como la radioastronomía, espectroscopíamolecular, medicina, seguridad, radar, etc. Los principales inconvenientes en el desarrollo de estas aplicaciones son los altos costes de producción de los sistemas trabajando a estas frecuencias, su costoso mantenimiento, gran volumen y baja fiabilidad. Entre las diferentes tecnologías a frecuencias de THz, la tecnología de los diodos Schottky juega un importante papel debido a su madurez y a la sencillez de estos dispositivos. Además, los diodos Schottky pueden operar tanto a temperatura ambiente como a temperaturas criogénicas, con altas eficiencias cuando se usan como multiplicadores y con moderadas temperaturas de ruido en mezcladores. El principal objetivo de esta tesis doctoral es analizar los fenómenos físicos responsables de las características eléctricas y del ruido en los diodos Schottky, así como analizar y diseñar circuitos multiplicadores y mezcladores en bandas milimétricas y submilimétricas. La primera parte de la tesis presenta un análisis de los fenómenos físicos que limitan el comportamiento de los diodos Schottky de GaAs y GaN y de las características del espectro de ruido de estos dispositivos. Para llevar a cabo este análisis, un modelo del diodo basado en la técnica de Monte Carlo se ha considerado como referencia debido a la elevada precisión y fiabilidad de este modelo. Además, el modelo de Monte Carlo permite calcular directamente el espectro de ruido de los diodos sin necesidad de utilizar ningún modelo analítico o empírico. Se han analizado fenómenos físicos como saturación de la velocidad, inercia de los portadores, dependencia de la movilidad electrónica con la longitud de la epicapa, resonancias del plasma y efectos no locales y no estacionarios. También se ha presentado un completo análisis del espectro de ruido para diodos Schottky de GaAs y GaN operando tanto en condiciones estáticas como variables con el tiempo. Los resultados obtenidos en esta parte de la tesis contribuyen a mejorar la comprensión de la respuesta eléctrica y del ruido de los diodos Schottky en condiciones de altas frecuencias y/o altos campos eléctricos. También, estos resultados han ayudado a determinar las limitaciones de modelos numéricos y analíticos usados en el análisis de la respuesta eléctrica y del ruido electrónico en los diodos Schottky. La segunda parte de la tesis está dedicada al análisis de multiplicadores y mezcladores mediante una herramienta de simulación de circuitos basada en la técnica de balance armónico. Diferentes modelos basados en circuitos equivalentes del dispositivo, en las ecuaciones de arrastre-difusión y en la técnica de Monte Carlo se han considerado en este análisis. El modelo de Monte Carlo acoplado a la técnica de balance armónico se ha usado como referencia para evaluar las limitaciones y el rango de validez de modelos basados en circuitos equivalentes y en las ecuaciones de arrastredifusión para el diseño de circuitos multiplicadores y mezcladores. Una notable característica de esta herramienta de simulación es que permite diseñar circuitos Schottky teniendo en cuenta tanto la respuesta eléctrica como el ruido generado en los dispositivos. Los resultados de las simulaciones presentados en esta parte de la tesis, tanto paramultiplicadores comomezcladores, se han comparado con resultados experimentales publicados en la literatura. El simulador que integra el modelo de Monte Carlo con la técnica de balance armónico permite analizar y diseñar circuitos a frecuencias superiores a 1 THz. ABSTRACT The terahertz region of the electromagnetic spectrum(100 GHz-10 THz) presents a wide range of applications such as radio-astronomy, molecular spectroscopy, medicine, security and radar, among others. The main obstacles for the development of these applications are the high production cost of the systems working at these frequencies, highmaintenance, high volume and low reliability. Among the different THz technologies, Schottky technology plays an important rule due to its maturity and the inherent simplicity of these devices. Besides, Schottky diodes can operate at both room and cryogenic temperatures, with high efficiency in multipliers and moderate noise temperature in mixers. This PhD. thesis is mainly concerned with the analysis of the physical processes responsible for the characteristics of the electrical response and noise of Schottky diodes, as well as the analysis and design of frequency multipliers and mixers at millimeter and submillimeter wavelengths. The first part of the thesis deals with the analysis of the physical phenomena limiting the electrical performance of GaAs and GaN Schottky diodes and their noise performance. To carry out this analysis, a Monte Carlo model of the diode has been used as a reference due to the high accuracy and reliability of this diode model at millimeter and submillimter wavelengths. Besides, the Monte Carlo model provides a direct description of the noise spectra of the devices without the necessity of any additional analytical or empirical model. Physical phenomena like velocity saturation, carrier inertia, dependence of the electron mobility on the epilayer length, plasma resonance and nonlocal effects in time and space have been analysed. Also, a complete analysis of the current noise spectra of GaAs and GaN Schottky diodes operating under static and time varying conditions is presented in this part of the thesis. The obtained results provide a better understanding of the electrical and the noise responses of Schottky diodes under high frequency and/or high electric field conditions. Also these results have helped to determine the limitations of numerical and analytical models used in the analysis of the electrical and the noise responses of these devices. The second part of the thesis is devoted to the analysis of frequency multipliers and mixers by means of an in-house circuit simulation tool based on the harmonic balance technique. Different lumped equivalent circuits, drift-diffusion and Monte Carlo models have been considered in this analysis. The Monte Carlo model coupled to the harmonic balance technique has been used as a reference to evaluate the limitations and range of validity of lumped equivalent circuit and driftdiffusion models for the design of frequency multipliers and mixers. A remarkable feature of this reference simulation tool is that it enables the design of Schottky circuits from both electrical and noise considerations. The simulation results presented in this part of the thesis for both multipliers and mixers have been compared with measured results available in the literature. In addition, the Monte Carlo simulation tool allows the analysis and design of circuits above 1 THz.

Hybrid Monte Carlo dose algorithm for low energy X-rays intraoperative radiation therapy

Low energy X-rays Intra-Operative Radiation Therapy (XIORT) treatment delivered during surgery (ex: INTRABEAM, Carl Zeiss, and Axxent, Xoft) can benefit from accurate and fast dose prediction in a patient 3D volume.

Efficient Monte Carlo methods for multi-dimensional learning with classifier chains

Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional classification problems. Since these classes are often strongly correlated, modeling the dependencies between them allows MDC methods to improve their performance – at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies, one of the most popular and highest-performing methods for multi-label classification (MLC), a particular case of MDC which involves only binary classes (i.e., labels). The original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors along the chain. Here we present novel Monte Carlo schemes, both for finding a good chain sequence and performing efficient inference. Our algorithms remain tractable for high-dimensional data sets and obtain the best predictive performance across several real data sets.

Student academic performance stochastic simulator based on the Monte Carlo method

In this paper, a computer-based tool is developed to analyze student performance along a given curriculum. The proposed software makes use of historical data to compute passing/failing probabilities and simulates future student academic performance based on stochastic programming methods (MonteCarlo) according to the specific university regulations. This allows to compute the academic performance rates for the specific subjects of the curriculum for each semester, as well as the overall rates (the set of subjects in the semester), which are the efficiency rate and the success rate. Additionally, we compute the rates for the Bachelors degree, which are the graduation rate measured as the percentage of students who finish as scheduled or taking an extra year and the efficiency rate (measured as the percentage of credits of the curriculum with respect to the credits really taken). In Spain, these metrics have been defined by the National Quality Evaluation and Accreditation Agency (ANECA). Moreover, the sensitivity of the performance metrics to some of the parameters of the simulator is analyzed using statistical tools (Design of Experiments). The simulator has been adapted to the curriculum characteristics of the Bachelor in Engineering Technologies at the Technical University of Madrid(UPM).