Sharif Digital Repository

OBJECTIVE: This study aims to benchmark a Monte Carlo (MC) model of the 18 MV photon beam produced by the Siemens Oncor® linac using the BEAMnrc and DOSXYZnrc codes. METHODS: By matching the percentage depth doses and beam profiles calculated by MC simulations with measurements, the initial electron beam parameters including electron energy, full width at half maximum (spatial FWHM), and mean angular spread were derived for the 10×10 cm2 and 20×20 cm2 field sizes. The MC model of the 18 MV photon beam was then validated against the measurements for different field sizes (5×5, 30×30 and 40×40 cm2) by gamma index analysis. RESULTS: The optimum values for electron energy, spatial FWHM and mean... 

Up to now, different methods have been developed for estimation of buildup factor (BF). However, either expensive estimation or time-consuming estimation are major restrictions/challenges of these methods. In this study a new technique utilizing combination of Monte Carlo method and the Bayesian regularization (BR) learning algorithm of multilayer feed-forward neural network (FFNN) is employed for estimation of BFs. First, the BFs of the different elements (i.e. Al, Cu, and Fe) at different energies and different mean free paths (MFPs) are modeled by the MCNP code. The results show that the calculated BFs by MCNP code are in good agreement with the reported values of American nuclear society... 

In this paper, a comparative techno-economic evaluation of hydrogen production by glycerol reforming in aqueous and gaseous phases are presented. To accomplish the techno-economic evaluation, firstly the process modeling and design are presented. Based on the equipment purchased costs, with 80 kg/h hydrogen production, the total cost of hydrogen production is estimated 3.65 and 3.55 $/kgH2 for steam reforming and aqueous phase reforming plants, respectively. Regarding the installation factor in the equipment costs, the total cost of hydrogen production is estimated 7.49 and 7.45 $/kgH2 for steam reforming and aqueous phase reforming plants, respectively. To investigate the impact of... 

Computed tomography (CT) simulators are versatile tools for scanning protocol evaluation, optimization of geometrical design parameters, assessment of image reconstruction algorithms, and evaluation of the impact of future innovations attempting to improve the performance of CT scanners. Computational human phantoms (CHPs) play a key role in simulators for the radiation dosimetry and assessment of image quality tasks in the medical x-ray systems. Since the construction of patient-specific CHPs can be both difficult and time-consuming, nominal standard/reference CHPs have been established, yielding significant discrepancies in the special design and optimization demands of patient dose and... 

The aim of this work is to develop a mammography Monte Carlo MCNP-FBSM based simulation platform called 'MamSim' that is able to model the detailed geometry and physics of commercial screen-film and digital mammography units. This simulation platform is designed to enable the virtual assessment and optimization of mammography protocols and parameters for obtaining the desired image quality while diminishing radiation dose to the patient in both contact and magnification modes. A graphical user interface generates MCNP-FBSM input files for simulating mammography units under various geometries and imaging protocols. We considered the full simulation of all components of mammography procedure... 

A charge sharing technique for high-speed double-tail comparators is presented. This technique is applied to the pre-amplifier stage of the dynamic comparators so that the maximum differential gain is applied to the latch during the latching process reducing the input referred offset voltage. In dynamic comparators a large portion of the input referred offset voltage is coming from the latch, and the proposed technique is introduced to alleviate this issue. Monte- Carlo simulations show that the proposed technique reduces the offset voltage from 16 mV to 8 mV. Due to the charge sharing technique, the pre-amplifier draws just enough power for its operation reducing the average power by 40%... 

Energy use in buildings contributes a large part in global energy demand. To reduce energy use in this group of consumers, specially in cold seasons, an automatic control technique is proposed. In this paper, a model predictive controller (MPC) is employed to minimize the boiler activation time. The method uses the building model and incorporates the weather forecast data to act on the actuator in an optimal fashion while treating the user comfort constraints. This technique, as a part, can be embedded into the building energy management system. The building model parameters are obtained via an online identification process using unscented kalman filter (UKF). This identification is... 

This paper proposes a multi-unit building model, in which the parameters are obtained via an online identification process. The identification process is carried out on-the-fly so it can update the best model of the building units. A model predictive controller (MPC) is also employed that uses the prediction of the building model, as well as the weather forecast data and acts on the heating boiler in an optimal fashion. In addition, since the controller is designed for a multi-unit building, it is crucial to estimate the amount of the delay that takes the hot flow to reach the units. This paper presents a very simple method for the delay identification based on unscented kalman filter. For... 

Two-dimensional engagement of a pursuer and a maneuvering target, affected by matched uncertainties, is formulated as a nonlinear differential game. The uncertain guidance problem is converted into a nonlinear model predictive control problem by introducing an appropriate cost function. The objective is to calculate the best guidance commands of the pursuer and the worst possible target maneuvers simultaneously, over a receding horizon. The proposed cost function penalizes the line-of-sight rate, the pursuer acceleration, and the uncertainties. It also rewards the target maneuver. A particle swarm-based dynamic optimization algorithm is developed to solve the nonlinear model predictive... 

Given the importance and complexity of the three-dimensional (3D) neutron transport equation solution, in the current research, a new Modular Ray Tracing (MRT) Algorithm and 3D characteristic kernel for heterogeneous structures are presented. Improvement of memory management and cache coherency are achieved to some acceptable level. Also, parallel implementation of transport algorithm utilizing OpenMP, cause significant reduction in runtime. To validate our Algorithm, first, a self-constituted pin cell and a lattice arrangement are modeled and results are compared with Monte-Carlo simulation. Second, the well-known 3D benchmark, Takeda model one and two, are investigated and results compared... 

Application of composite lattice structures in aerospace application can bring about considerable weight savings, thus allowing for increased payload weight. This study is devoted to reliability analysis of composite anisogrid lattice interstage structure (CALIS) used in typical launch vehicle (LV). CALIS is usually formed in to thin-walled cylindrical or conical shell via helical and circumferential ribs that can act as a lightweight load bearing support structure interfacing any two stages of the LV. Thus, the current study is of practical importance as the interstage structure is acted upon by rather high axial and bending forces emanating from LV external aerodynamics, thrust and... 

This paper deals with the simulation-based design optimization and experimental validation of the characteristics of an in-core silver Self-Powered Neutron Detector (SPND). Optimized dimensions of the SPND are determined by combining Monte Carlo simulations and analytical methods. As a first step, the Monte Carlo transport code MCNPX is used to follow the trajectory and fate of the neutrons emitted from an external source. This simulation is able to seamlessly integrate various phenomena, including neutron slowing-down and shielding effects. Then, the expected number of beta particles and their energy spectrum following a neutron capture reaction in the silver emitter are fetched from the... 

This paper presents a hierarchical Bayesian modeling framework for the uncertainty quantification in modal identification of linear dynamical systems using multiple vibration data sets. This novel framework integrates the state-of-the-art Bayesian formulations into a hierarchical setting aiming to capture both the identification precision and the variability prompted due to modeling errors. Such developments have been absent from the modal identification literature, sustained as a long-standing problem at the research spotlight. Central to this framework is a Gaussian hyper probability model, whose mean and covariance matrix are unknown, encapsulating the uncertainty of the modal parameters.... 

Elemental analysis can be performed using obtained gamma-ray spectrum of the sample under study. In this work, simple Multi-Layer Perceptron (MLP) neural network models are proposed for analyzing a gamma-ray emitting sample using whole information of its obtained gamma-ray spectrum. Elemental analysis is performed in two fields of study using 3 × 3 inch NaI(Tl) detectors: Radio-Isotope Identification (RIID) and Prompt Gamma Neutron Activation Analysis (PGNAA). The gamma-ray point sources are used for an empirical study in RIID field, while a Monte Carlo simulation study is considered for determining chlorine and water content of crude oil using combination of PGNAA technique and a MLP model.... 

One of the well-known online monitoring techniques used for quality control of bulk samples is Prompt Gamma Neutron Activation Analysis (PGNAA). PGNAA suffers from the so-called matrix effect problems such as density, thickness and moisture content of the sample under study. In this work, an Artificial Neural Network (ANN) model is introduced to deal with these effects. The required spectra for training and testing the proposed ANN model are obtained by Monte Carlo simulation of the gamma-ray spectra recorded in a PGNAA online analyzer system used in cement factories. The gamma-ray spectra related to given set of density, thickness and moisture content are corrected channel-to-channel using... 

As radar signals propagate above the ocean surface to determine the trajectory of a target, the signals that are reflected directly from the target arrive at the receiver along with indirect signals reflected from the ocean surface. These unwanted signals must be properly filtered; otherwise, their interference may mislead the signal receiver and significantly degrade the tracking performance of the radar. To this end, we propose a low-elevation target tracking mechanism considering the specular and diffuse reflection effects of multipath propagation over the ocean surface simultaneously. The proposed mechanism consists of a state-space model and a particle filtering algorithm and promises... 

In order to determine the activity of C137s in soil resulting from nuclear accidents or fallouts, the best choice is to use HPGe detectors due to their best energy resolutions. In this regard, in order to enhance the detection efficiency, the Marinelli beakers have been used to increase the radiation interaction with the sensitive volume of the detector. In previous works, to optimize the dimension of Marinelli beakers, the assumption was that the emission rate of the source is homogeneous in beaker volume. In the present study, to investigate the effect of the inhomogeneous emission rate of the source on the optimum dimensions of the beaker, in a simple case, the beaker was divided into two... 

Purpose: The purpose of this paper is to present a new efficient method for the tolerance–reliability analysis and quality control of complex nonlinear assemblies where explicit assembly functions are difficult or impossible to extract based on Bayesian modeling. Design/methodology/approach: In the proposed method, first, tolerances are modelled as the random uncertain variables. Then, based on the assembly data, the explicit assembly function can be expressed by the Bayesian model in terms of manufacturing and assembly tolerances. According to the obtained assembly tolerance, reliability of the mechanical assembly to meet the assembly requirement can be estimated by a proper first-order... 

This paper proposes a new method for solving the time-dependent neutron transport equation based on nodal discretization using the MCNPX code. Most valid nodal codes are based on the diffusion theory with differences in approximating the leakage term until now. However, the Monte Carlo (MC) method is able to estimate transport parameters without approximations usual in diffusion method. Therefore, improving the nodal approach via the MC techniques can substantially reduce the errors caused by diffusion approximations. In the proposed method, the reactor core is divided into nodes of arbitrary dimensions, and all terms of the transport equation e.g. interaction rates and leakage ratio are... 

In this paper, we develop a stochastic programming model for the capacitated location-allocation problem in the heterogeneous environment where the demands are distributed according to the Bernoulli function with different probabilities. The capacitated sub-sources of facilities are also involved to satisfy customers’ demands in this work. This study aims to find optimal locations of facilities and optimal allocations of existing customers to the facilities so that the total cost of operating facilities, allocating the customers, expected servicing and outsourcing is minimized. Due to the large amount of customers with different demand probabilities, accurate estimation of the outsourcing...