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Matrix effects corrections in prompt gamma-ray spectra of a PGNAA online analyzer system using artificial neural network
, Article Progress in Nuclear Energy ; Volume 118 , 2020 ; Vosoughi, N ; Saheli, F ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
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...
Processing scintillation gamma-ray spectra by artificial neural network
, Article Journal of Radioanalytical and Nuclear Chemistry ; Volume 325, Issue 2 , 2020 , Pages 471-483 ; Vosoughi, N ; Saheli, F ; Sharif University of Technology
Springer Netherlands
2020
Abstract
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....
Studying and Synthesize of H2S Gas Sensors Based on Modified WO3 Nanostructure Thin Films
, M.Sc. Thesis Sharif University of Technology ; Iraji zad, Aazam (Supervisor) ; Rahimi, Fereshte (Co-Advisor)
Abstract
H2S is a toxic gas used in chemical laboratories and industries. H2S is also liberated in nature due to biological processes and also from mines and petroleum fields. At some threshold level, exposure to concentrations over 10 ppm can result in headaches, irritability, dizziness and in some case leads to death. So that introducing sensors which sense H2S at ppm level with the low response time is so essential. The present work emphasizes on H2S resistance-sensing properties of pure and Pd doped WO3 films prepared by Arc discharge method. XRD, SEM, EDAX and XPS were applied to analyze crystal structure, morphology and chemical composition of the films. The analyzes results showed that films...
Conceptual models for Seawater Intrusion Simulation
, M.Sc. Thesis Sharif University of Technology ; Ataie Ashtiani, Behzad (Supervisor)
Abstract
Ground water resources are the main source of water supply in many regions. During last decades ground water quality has been deteriorated due to many sources of contamination. Seawater intrusion in coastal aquifers is one of these sources. With development of different numerical models, simulation of seawater intrusion in coastal and island aquifers has been used greatly in analyzing the condition of these aquifers. The first step in performing a numerical modeling is determination of a suitable conceptual model. Considering the complexity of a real problem, a proper conceptual model should show the true condition of the problem as well as lead to a cost and time effective simulation. In...
Single peak analysis of proton induced prompt gamma counts
, Article Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms ; Volume 475 , 2020 , Pages 63-70 ; Vosoughi, N ; Riazi, Z ; Shahabinejad, H ; Rasouli, F. S ; Sharif University of Technology
Elsevier B.V
2020
Abstract
Online elemental analysis of irradiated tissues is an important challenge in proton therapy for estimating the depth of the Bragg peak and monitoring the healing process. In the present study, the prompt gamma (PG) spectra of the most abundant elements of human tissues were obtained for two different incident protons of 30 MeV and 120 MeV using the Geant4 toolkit. Train phantoms were defined to study the elemental analysis of the tissue from PG spectra. It was found that the intensities of 7.12 and 3.91 MeV PG depend on the mass of 16O and 20Ca elements for both proton energies, respectively. Furthermore, multi-variable linear functions were presented for overlapping peaks like 4.44 and 2.31...
Quantitative Elemental Analysis Using Whole Spectral Information (with GA and MLR Methods) of Proton Induced Prompt Gamma-Rays Simulated Using Geant4 Toolkit
, Article Frontiers in Biomedical Technologies ; Volume 10, Issue 1 , 2023 , Pages 78-87 ; 23455829 (ISSN) ; Vosoughi, N ; Riazi, Z ; Rasouli, F. S ; Jowkar, A ; Sharif University of Technology
Tehran University of Medical Sciences
2023
Abstract
Purpose: Online determination of the elemental composition of tissues near the Bragg peak is a challenge in proton therapy related studies. In the present work, an analysis method based on the whole spectral information is presented for the quantitative determination of the elemental composition (weight %) of an irradiated target from its emitted Prompt Gamma (PG) spectrum. Materials and Methods: To address this issue, four test phantoms with different weights (%) of 12C, 16O, 20Ca, and 14N elements were considered. The simulated PG spectra were recorded using 3 × 3 inch NaI detectors. A library consisting of the spectra of single-element phantoms as well as the spectra of test-irradiated...
Evaluation the nonlinear response function of a HPGe detector for 59 keV to 10.7 MeV gamma-rays using a Monte Carlo simulation and comparison with experimental data
, Article Journal of Instrumentation ; Volume 16, Issue 7 , 2021 ; 17480221 (ISSN) ; Riazi, Z ; Jokar, A ; Shahabinejad, H ; Vosoughi, N ; Ghasemi, S. A ; Sharif University of Technology
IOP Publishing Ltd
2021
Abstract
Modeling of High Purity Germanium (HPGe) detector on a wide energy range is important in gamma-ray spectroscopy. The precisely modeled detector can be used for proton-induced prompt gamma-ray spectroscopy. In this work, we used both the gamma-rays of calibration sources and prompt gamma-rays emitted in proton capture reactions to model a coaxial p-type HPGe detector using Geant4 Monte Carlo simulation for the gamma-ray energy range of 59–10764 keV. The calibration sources were 137Cs, 241Am, 60Co, 152Eu, and 133Ba, while the prompt gamma-rays were due to the gamma-ray cascades following the 27Al(p,γ)28Si reaction capture at the resonant energies of 992, 1317 and 2483 keV, as well as the...
Feasibility Study of Using the Elemental Analysis of Prompt Gamma Spectrum to Improve the Treatment Planning in Hadron Therapy
, Ph.D. Dissertation Sharif University of Technology ; Vosoughi, Naser (Supervisor) ; Riazi, Zafar (Supervisor) ; Rasouli, Fateme (Co-Supervisor)
Abstract
Hadron therapy is one of the cancer treatment methods using the targeted dose distributhion. In hadron therapy, the prompt gamma is produced from excited nucleas of target in the following of non-elastic nuclear interactions between the target and the incident proton within few nano-seconds and with energy less than 10 MeV. The excited energy level depends on incident particle energy and the target materials. Since the Spatial distribution of prompt gamma rays depends on incident particles energy, it can be useful for determinding the incident particle range. Also, the prompt gamma energy spectrum of each element is an individual feature, thereby targets with different composition of...
Development of Microorganisms with Improved Biosurfactant Activity
, Ph.D. Dissertation Sharif University of Technology ; Roosta Azad, Reza (Supervisor) ; Rouholamini Najafabadi, Abdolhossein (Supervisor) ; Akbari Noghabi, Kambiz (Co-Advisor) ; Shahcheraghi, Fereshte (Co-Advisor)
Abstract
This thesis discusses the work on the production of a rhamnolipid-type biosurfactant by Pseudomonas aeruginosa MR01, its structural characterization and environmental applications. First, results from analytical approaches for screening of biosurfactant producers suggested the oil spreading method as the fastest, simplest and most consistent analytical method. The second part of the thesis describes the properties of the most efficient biosurfactant-producing bacteria isolated from oil fields in south of Iran and according to it’s biochemical characteristics and partial sequenced 16S rRNA gene affiliated with Pseudomonas aeruginosa. Time course study indicated that the maximum biosurfactant...