Search results for "Monte Carlo method."
showing 10 items of 1217 documents
Design and characterization of a new high-dose-rate brachytherapy Valencia applicator for larger skin lesions
2016
Purpose: The aims of this study were (i) to design a new high-dose-rate (HDR) brachytherapy applicator for treating surface lesions with planning target volumes larger than 3 cm in diameter and up to 5 cm in size, using the microSelectron-HDR or Flexitron afterloader (Elekta Brachytherapy) with a 192Ir source; (ii) to calculate by means of the Monte Carlo(MC) method the dose distribution for the new applicator when it is placed against a water phantom; and (iii) to validate experimentally the dose distributions in water. Methods: The penelope2008MC code was used to optimize dwell positions and dwell times. Next, the dose distribution in a water phantom and the leakage dose distribution arou…
Cu cluster shell structure at elevated temperatures
1991
Equilibrium structures of small (3--29)-atom Cu clusters are determined by simulated annealing, and finite-temperature ensembles are simulated by Monte Carlo techniques using the effective-medium theory for the energy calculation. Clusters with 8, 18, and 20 atoms are found to be particularly stable. The equilibrium geometrical structures are determined and found to be determined by a Jahn-Teller distortion, which is found to affect the geometry also at high temperatures. The ``magic'' clusters retain their large stability even at elevated temperatures.
Statics and dynamics of colloid-polymer mixtures near their critical point of phase separation: A computer simulation study of a continuous Asakura–O…
2008
We propose a new coarse-grained model for the description of liquid-vapor phase separation of colloid-polymer mixtures. The hard-sphere repulsion between colloids and between colloids and polymers, which is used in the well-known Asakura-Oosawa (AO) model, is replaced by Weeks-Chandler-Anderson potentials. Similarly, a soft potential of height comparable to thermal energy is used for the polymer-polymer interaction, rather than treating polymers as ideal gas particles. It is shown by grand-canonical Monte Carlo simulations that this model leads to a coexistence curve that almost coincides with that of the AO model and the Ising critical behavior of static quantities is reproduced. Then the …
Depletion-induced percolation in networks of nanorods.
2006
Above a certain density threshold, suspensions of rod-like colloidal particles form system-spanning networks. Using Monte Carlo simulations, we investigate how the depletion forces caused by spherical particles affect these networks in isotropic suspensions of rods. Although the depletion forces are strongly anisotropic and favor alignment of the rods, the percolation threshold of the rods decreases significantly. The relative size of the effect increases with the aspect ratio of the rods. The structural changes induced in the suspension by the depletant are characterized in detail and the system is compared to an ideal fluid of freely interpenetrable rods.
Non-linear systems under parametric white noise input: digital simulation and response
2005
Abstract Monte Carlo technique is constituted of three steps. Therefore, improving such technique in practice means, improving the procedure used in one of the three following steps: (i) sample paths of the stochastic input process, (ii) calculation of the outputs corresponding to the generated input samples by using methods of classical dynamics and (iii) estimating statistics of the output process from sample outputs related to the previous step. For linear and non-linear systems driven by parametric impulsive inputs such as normal or non-normal white noises, a general integration method requires a considerable reduction of the integration step when the impulse occurs, treating the impuls…
An open-source GA framework for optimizing the seismic upgrading design of RC frames through BRBs
2022
Abstract Optimizing seismic upgrading interventions in reinforced concrete (RC) structures is a difficult task, due to the inner non-linearity of the analyses usually performed. Additionally, it is well known that the displacement demand to the structure depends from the mass and stiffness of the system, and consequently its definition cannot be made a-priori. This paper presents the application of a soft-computing method -i.e. Genetic Algorithm (GA)- for the shaping optimization of code-compliant seismic upgrading interventions on plane RC frames through Buckling-Restrained Braces (BRB). The metaheuristic procedure allows to minimize the cost while ensuring the required safety level, witho…
A new strategy for effective learning in population Monte Carlo sampling
2016
In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.
Incremental heuristic approach for meter placement in radial distribution systems
2019
The evolution of modern power distribution systems into smart grids requires the development of dedicated state estimation (SE) algorithms for real-time identification of the overall system state variables. This paper proposes a strategy to evaluate the minimum number and best position of power injection meters in radial distribution systems for SE purposes. Measurement points are identified with the aim of reducing uncertainty in branch power flow estimations. An incremental heuristic meter placement (IHMP) approach is proposed to select the locations and total number of power measurements. The meter placement procedure was implemented for a backward/forward load flow algorithm proposed by…
Reliability-based design optimization of trusses under dynamic shakedown constraints
2019
A reliability-based design optimization problem under dynamic shakedown constraints for elastic perfectly plastic truss structures subjected to stochastic wind actions is presented. The simultaneous presence of quasi-static (cyclic) thermal loads is also considered. As usual in the shakedown theory, the quasi-statical loads will be defined as variable within a deterministic domain, while the dynamic problem will be treated considering an extended Ceradini-Gavarini approach. Some sources of uncertainties are introduced in the structural system and in the load definition. The reliability-optimization problem is formulated as the minimization of the volume of the structure subjected to determi…
Bayesian adaptive estimation: The next dimension
2006
Abstract We propose a new psychometric model for two-dimensional stimuli, such as color differences, based on parameterizing the threshold of a one-dimensional psychometric function as an ellipse. The Ψ Bayesian adaptive estimation method applied to this model yields trials that vary in multiple stimulus dimensions simultaneously. Simulations indicate that this new procedure can be much more efficient than the more conventional procedure of estimating the psychometric function on one-dimensional lines independently, requiring only one-fourth or less the number of trials for equivalent performance in typical situations. In a real psychophysical experiment with a yes–no task, as few as 22 tri…