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العنوان
Advanced Study for Large Sample Neutron Activation Analysis \
المؤلف
Emam, Adel Emam Mohamed.
هيئة الاعداد
باحث / عادل امام محمد امام
مشرف / محسن عبده أبو مندور
مشرف / علياء عادل بدوي
مشرف / نادر محمود عبد الحليم
مناقش / مصطفى عزيز عبد الوهاب
مناقش / محمد حسن محمد حسن
الموضوع
Nuclear Engineering.
تاريخ النشر
2014.
عدد الصفحات
83 p. :
اللغة
الإنجليزية
الدرجة
الدكتوراه
التخصص
الهندسة (متفرقات)
تاريخ الإجازة
1/12/2014
مكان الإجازة
جامعة الاسكندريه - كلية الهندسة - الهندسة النووية
الفهرس
Only 14 pages are availabe for public view

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Abstract

The main challenge in the Large Sample Neutron Activation Analysis (LSNAA)is the determination of neutron self shielding and gamma ray self attenuation corrections.After these corrections are determined, the analysis proceeds as in normal Neutron Activation Analysis (NAA), as if the sample were infinitely small.In this study, these corrections are calculated using the MCNP code for different standard samples geometry with different diameters. Analytical formula for the correction factors for neutron self shielding and gamma ray self attenuation is driven. All LSNAA limitations are studied and the effect of sample size(thickness/height) on calculated parameter is calculated. Sample height to thickness ratio is considered for different materials to be not less than 3 to avoid the effect of top bottom neutron/gamma leakage. Monte Carlo MCNP-5 code is used for sample modeling of different materials, Norm, industrial, nuclear materials and hypothetical materials are modeled. All calculated parameters were tabulated and graphed. A relation between calculated parameters is plotted for a large number of known samples. from the calculated data, other unknown material’s parameters could be obtained based on tabulated data or graphs. The above methodology will be a direct and easier way to do large sample neutron activation analysis with no need for complex calculation. Also for the users which do not have a good experience with codes like MCNP, they can use the chart or the tabulated information to define his unknown sample with required information for the LSNAA experiment.