|
| Titre : |
Monte Carlo Simulation on Gamma Spectrometry and Application to Radioactivity Measurement in Honey Samples |
| Type de document : |
document électronique |
| Auteurs : |
Ghada Mellak, Auteur ; Boukhenfouf,Wassila, Directeur de thèse |
| Editeur : |
Sétif:UFA1 |
| Année de publication : |
2025 |
| Importance : |
1 vol (107 f.) |
| Format : |
29 cm |
| Langues : |
Anglais (eng) |
| Catégories : |
Thèses & Mémoires:Physique
|
| Mots-clés : |
Monte Carlo simulations
MCNP5 Code
HPGe Detector Efficiency
Computational
Tools(MEFFTRAN,ANGLE) |
| Index. décimale : |
530 - Physique |
| Résumé : |
By integrating computational modeling (MCNP5, ANGLE, MEFFTRAN) and experimental
techniques (gamma spectrometry, AAS, CHARM II),this thesis develops and applies advanced
methodologies for analyzing radioactivity and contaminants in honey, a dense and complex matrix
with significant nutritional value. The study specifically addresses critical challenges in
gamma spectrometry, including photon attenuation, self-absorption, and true coincidence summing
(TCS) effects. The optimized Monte Carlo simulations demonstrated excellent agreement
with the experimental data (deviations <5% for low-energy gamma rays). The validated model
was then applied to quantify naturally occurring radionuclides (226Ra, 232Th, and 40K) in honey
samples from various geographical origins. Additional analyses using AAS and CHARM II were
employed to evaluate trace levels of heavy metals (K, Zn, Cu, Al, As) and antibiotic residues
(tetracyclines and chloramphenicol), revealing contamination trends linked to industrial zones
and environmental or apicultural practices. This interdisciplinary approach offers a robust and
transferable framework for contaminant analysis in dense matrices, with important implications
for food safety regulations, environmental monitoring, and public health protection. |
| Note de contenu : |
Sommaire
General Introduction 1
1 Theoretical Background 4
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Contaminants, their Sources, and detection . . . . . . . . . . . . . . . . . . 5
1.2.1 Radioactivity in the Environment . . . . . . . . . . . . . . . . . . . 5
1.2.1.1 Natural Sources of Radioactivity . . . . . . . . . . . . . . 5
1.2.1.2 Artificial Sources of Radioactivity . . . . . . . . . . . . . . 6
1.2.2 Detection of Radioactivity: Principles and Interactions . . . . . . . 6
1.2.2.1 Interactions of Gamma Rays . . . . . . . . . . . . . . . . 7
1.2.2.2 Radiation Detectors . . . . . . . . . . . . . . . . . . . . . 7
1.2.2.3 Semiconductor Detectors . . . . . . . . . . . . . . . . . . . 8
1.2.2.4 Spectrometer Performance Characterization . . . . . . . . 11
1.2.2.5 Detection setup . . . . . . . . . . . . . . . . . . . . . . . . 12
1.2.3 Transition from Experimental Detection to Simulation . . . . . . . 13
1.2.3.1 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . 13
1.2.3.2 MCNP 5 Code . . . . . . . . . . . . . . . . . . . . . . . . 14
1.2.3.3 MCNP5 code structure . . . . . . . . . . . . . . . . . . . 14
1.2.3.4 Tools Supporting Efficiency Calculation: ANGLE and MEFFTRAN
software . . . . . . . . . . . . . . . . . . . . . . . . 18
1.2.4 Heavy Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.2.5 Heavy metals detection and measurement . . . . . . . . . . . . . . 20
1.2.5.1 Atomic Absorption Spectroscopy (AAS) . . . . . . . . . . 21
1.2.5.2 Principle of Atomic Absorption Spectroscopy (AAS) . . . 21
1.2.5.3 Instrumentation and Components of AAS . . . . . . . . . 21
CONTENTS
1.2.5.4 Working Process of AAS . . . . . . . . . . . . . . . . . . . 22
1.2.6 Antimicrobial Residues . . . . . . . . . . . . . . . . . . . . . . . . . 23
1.2.7 Antimicrobial residues detection and measurement . . . . . . . . . . 23
1.2.7.1 What is the CHARM Technique? . . . . . . . . . . . . . . 24
1.2.7.2 Principle of CHARM . . . . . . . . . . . . . . . . . . . . . 24
1.3 Contamination Pathways and Mechanisms . . . . . . . . . . . . . . . . . . 25
1.4 Bioaccumulation and Biomagnification . . . . . . . . . . . . . . . . . . . . 26
2 Monte Carlo Simulation and Detector Efficiency Modeling 27
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.2 Gamma Spectrometry Experimental Setup . . . . . . . . . . . . . . . . . . 28
2.2.1 Detector features . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3 Calibration of the Measurement Chain . . . . . . . . . . . . . . . . . . . . 29
2.3.1 Energy Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.2 Efficiency calibration for Point Source . . . . . . . . . . . . . . . . . 30
2.4 Simulations using the Monte Carlo MCNP5 Code . . . . . . . . . . . . . . 32
2.4.1 Modeling the detector geometry . . . . . . . . . . . . . . . . . . . . 32
2.4.2 Initial Model Based on Manufacturer Specifications . . . . . . . . . 34
2.4.3 Germanium Crystal Dead Layer Adjustment . . . . . . . . . . . . . 35
2.4.4 Influence of Cross-Section Libraries on Efficiency Calculations . . . 38
2.4.5 Marinelli Beaker Geometry . . . . . . . . . . . . . . . . . . . . . . . 38
2.4.6 Modeling of Detector Efficiency for a Marinelli Source . . . . . . . . 39
2.4.7 True Coincidence Summing Effects . . . . . . . . . . . . . . . . . . 42
2.4.8 Methodology for True Coincidence Summing Correction . . . . . . . 44
2.4.9 Application of the Validated Model to Honey Samples . . . . . . . 46
2.4.10 Determination of Self-Absorption Correction Factors using the Developed
Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.4.11 Impact of Cross-Section Library Selection on Simulated Efficiency . 48
2.5 ANGLE Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.6 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . 50
2.6.1 Validation of the optimized detector model . . . . . . . . . . . . . . 50
2.6.2 Experimental vs. MCNP5 Simulated Efficiency . . . . . . . . . . . 51
2.6.2.1 Experimental Vs Simulation calculations . . . . . . . . . . 51
3 Experimental Methodology 54
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.2 Sample Collection and preparation . . . . . . . . . . . . . . . . . . . . . . 54
3.2.1 Sampling Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.3.1 Radioactivity measurements . . . . . . . . . . . . . . . . . . . . . . 57
3.3.2 Gamma Spectrometry Analysis . . . . . . . . . . . . . . . . . . . . 57
3.4 Heavy Metal Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.1 Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.2 Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.4.3 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.5 Antibiotics residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5.1 Charm II test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5.2 Tetracycline Test for Honey . . . . . . . . . . . . . . . . . . . . . . 64
3.5.3 Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.4 Determination of the Control Point (CP) . . . . . . . . . . . . . . . 65
3.5.5 Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . 65
4 Results And Discussions 67
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2 Experimental Analysis of Radioactive Contamination . . . . . . . . . . . . 67
4.2.1 Activity Concentrations . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2.2 Spatial Distrbution . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2.3 Radiological Risk Assessment . . . . . . . . . . . . . . . . . . . . . 70
4.2.4 Multivariate Statistical Analysis . . . . . . . . . . . . . . . . . . . . 73
4.3 Experimental Analysis of Heavy Metals Contamination . . . . . . . . . . . 77
4.3.1 Heavy Metals concentrations . . . . . . . . . . . . . . . . . . . . . . 77
4.3.2 Spatial Distrbution . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3.3 Health Risk Assesssments . . . . . . . . . . . . . . . . . . . . . . . 81
4.3.4 Multivariate statistical analysis . . . . . . . . . . . . . . . . . . . . 86
4.4 Experimental Analysis of Antibiotics Residues Contamination . . . . . . . 90
4.4.1 Antibiotics residues concentrations . . . . . . . . . . . . . . . . . . 90 |
| Côte titre : |
Dph/0320 |
Monte Carlo Simulation on Gamma Spectrometry and Application to Radioactivity Measurement in Honey Samples [document électronique] / Ghada Mellak, Auteur ; Boukhenfouf,Wassila, Directeur de thèse . - [S.l.] : Sétif:UFA1, 2025 . - 1 vol (107 f.) ; 29 cm. Langues : Anglais ( eng)
| Catégories : |
Thèses & Mémoires:Physique
|
| Mots-clés : |
Monte Carlo simulations
MCNP5 Code
HPGe Detector Efficiency
Computational
Tools(MEFFTRAN,ANGLE) |
| Index. décimale : |
530 - Physique |
| Résumé : |
By integrating computational modeling (MCNP5, ANGLE, MEFFTRAN) and experimental
techniques (gamma spectrometry, AAS, CHARM II),this thesis develops and applies advanced
methodologies for analyzing radioactivity and contaminants in honey, a dense and complex matrix
with significant nutritional value. The study specifically addresses critical challenges in
gamma spectrometry, including photon attenuation, self-absorption, and true coincidence summing
(TCS) effects. The optimized Monte Carlo simulations demonstrated excellent agreement
with the experimental data (deviations <5% for low-energy gamma rays). The validated model
was then applied to quantify naturally occurring radionuclides (226Ra, 232Th, and 40K) in honey
samples from various geographical origins. Additional analyses using AAS and CHARM II were
employed to evaluate trace levels of heavy metals (K, Zn, Cu, Al, As) and antibiotic residues
(tetracyclines and chloramphenicol), revealing contamination trends linked to industrial zones
and environmental or apicultural practices. This interdisciplinary approach offers a robust and
transferable framework for contaminant analysis in dense matrices, with important implications
for food safety regulations, environmental monitoring, and public health protection. |
| Note de contenu : |
Sommaire
General Introduction 1
1 Theoretical Background 4
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Contaminants, their Sources, and detection . . . . . . . . . . . . . . . . . . 5
1.2.1 Radioactivity in the Environment . . . . . . . . . . . . . . . . . . . 5
1.2.1.1 Natural Sources of Radioactivity . . . . . . . . . . . . . . 5
1.2.1.2 Artificial Sources of Radioactivity . . . . . . . . . . . . . . 6
1.2.2 Detection of Radioactivity: Principles and Interactions . . . . . . . 6
1.2.2.1 Interactions of Gamma Rays . . . . . . . . . . . . . . . . 7
1.2.2.2 Radiation Detectors . . . . . . . . . . . . . . . . . . . . . 7
1.2.2.3 Semiconductor Detectors . . . . . . . . . . . . . . . . . . . 8
1.2.2.4 Spectrometer Performance Characterization . . . . . . . . 11
1.2.2.5 Detection setup . . . . . . . . . . . . . . . . . . . . . . . . 12
1.2.3 Transition from Experimental Detection to Simulation . . . . . . . 13
1.2.3.1 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . 13
1.2.3.2 MCNP 5 Code . . . . . . . . . . . . . . . . . . . . . . . . 14
1.2.3.3 MCNP5 code structure . . . . . . . . . . . . . . . . . . . 14
1.2.3.4 Tools Supporting Efficiency Calculation: ANGLE and MEFFTRAN
software . . . . . . . . . . . . . . . . . . . . . . . . 18
1.2.4 Heavy Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.2.5 Heavy metals detection and measurement . . . . . . . . . . . . . . 20
1.2.5.1 Atomic Absorption Spectroscopy (AAS) . . . . . . . . . . 21
1.2.5.2 Principle of Atomic Absorption Spectroscopy (AAS) . . . 21
1.2.5.3 Instrumentation and Components of AAS . . . . . . . . . 21
CONTENTS
1.2.5.4 Working Process of AAS . . . . . . . . . . . . . . . . . . . 22
1.2.6 Antimicrobial Residues . . . . . . . . . . . . . . . . . . . . . . . . . 23
1.2.7 Antimicrobial residues detection and measurement . . . . . . . . . . 23
1.2.7.1 What is the CHARM Technique? . . . . . . . . . . . . . . 24
1.2.7.2 Principle of CHARM . . . . . . . . . . . . . . . . . . . . . 24
1.3 Contamination Pathways and Mechanisms . . . . . . . . . . . . . . . . . . 25
1.4 Bioaccumulation and Biomagnification . . . . . . . . . . . . . . . . . . . . 26
2 Monte Carlo Simulation and Detector Efficiency Modeling 27
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.2 Gamma Spectrometry Experimental Setup . . . . . . . . . . . . . . . . . . 28
2.2.1 Detector features . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3 Calibration of the Measurement Chain . . . . . . . . . . . . . . . . . . . . 29
2.3.1 Energy Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.2 Efficiency calibration for Point Source . . . . . . . . . . . . . . . . . 30
2.4 Simulations using the Monte Carlo MCNP5 Code . . . . . . . . . . . . . . 32
2.4.1 Modeling the detector geometry . . . . . . . . . . . . . . . . . . . . 32
2.4.2 Initial Model Based on Manufacturer Specifications . . . . . . . . . 34
2.4.3 Germanium Crystal Dead Layer Adjustment . . . . . . . . . . . . . 35
2.4.4 Influence of Cross-Section Libraries on Efficiency Calculations . . . 38
2.4.5 Marinelli Beaker Geometry . . . . . . . . . . . . . . . . . . . . . . . 38
2.4.6 Modeling of Detector Efficiency for a Marinelli Source . . . . . . . . 39
2.4.7 True Coincidence Summing Effects . . . . . . . . . . . . . . . . . . 42
2.4.8 Methodology for True Coincidence Summing Correction . . . . . . . 44
2.4.9 Application of the Validated Model to Honey Samples . . . . . . . 46
2.4.10 Determination of Self-Absorption Correction Factors using the Developed
Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.4.11 Impact of Cross-Section Library Selection on Simulated Efficiency . 48
2.5 ANGLE Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.6 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . 50
2.6.1 Validation of the optimized detector model . . . . . . . . . . . . . . 50
2.6.2 Experimental vs. MCNP5 Simulated Efficiency . . . . . . . . . . . 51
2.6.2.1 Experimental Vs Simulation calculations . . . . . . . . . . 51
3 Experimental Methodology 54
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.2 Sample Collection and preparation . . . . . . . . . . . . . . . . . . . . . . 54
3.2.1 Sampling Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.3.1 Radioactivity measurements . . . . . . . . . . . . . . . . . . . . . . 57
3.3.2 Gamma Spectrometry Analysis . . . . . . . . . . . . . . . . . . . . 57
3.4 Heavy Metal Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.1 Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.2 Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.4.3 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.5 Antibiotics residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5.1 Charm II test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5.2 Tetracycline Test for Honey . . . . . . . . . . . . . . . . . . . . . . 64
3.5.3 Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.4 Determination of the Control Point (CP) . . . . . . . . . . . . . . . 65
3.5.5 Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . 65
4 Results And Discussions 67
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2 Experimental Analysis of Radioactive Contamination . . . . . . . . . . . . 67
4.2.1 Activity Concentrations . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2.2 Spatial Distrbution . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2.3 Radiological Risk Assessment . . . . . . . . . . . . . . . . . . . . . 70
4.2.4 Multivariate Statistical Analysis . . . . . . . . . . . . . . . . . . . . 73
4.3 Experimental Analysis of Heavy Metals Contamination . . . . . . . . . . . 77
4.3.1 Heavy Metals concentrations . . . . . . . . . . . . . . . . . . . . . . 77
4.3.2 Spatial Distrbution . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3.3 Health Risk Assesssments . . . . . . . . . . . . . . . . . . . . . . . 81
4.3.4 Multivariate statistical analysis . . . . . . . . . . . . . . . . . . . . 86
4.4 Experimental Analysis of Antibiotics Residues Contamination . . . . . . . 90
4.4.1 Antibiotics residues concentrations . . . . . . . . . . . . . . . . . . 90 |
| Côte titre : |
Dph/0320 |
|
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