Estimation of Austenitizing and Multiple Tempering Temperatures from the Mechanical Properties of AISI 410 using Artificial Neural Network
نویسندگان
چکیده
منابع مشابه
scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
assessment of the efficiency of s.p.g.c refineries using network dea
data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
Estimation of Reference Evapotranspiration Using Artificial Neural Network Models and the Hybrid Wavelet Neural Network
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficienc...
متن کاملdetermination of some physical and mechanical properties red bean
چکیده: در این تحقیق، برخی خواص فیزیکی و مکانیکی لوبیا قرمز به-صورت تابعی از محتوی رطوبت بررسی شد. نتایج نشان داد که رطوبت بر خواص فیزیکی لوبیا قرمز شامل طول، عرض، ضخامت، قطر متوسط هندسی، قطر متوسط حسابی، سطح تصویر شده، حجم، چگالی توده، تخلخل، وزن هزار دانه و زاویه ی استقرار استاتیکی در سطح احتمال 1 درصد اثر معنی داری دارد. به طوری که با افزایش رطوبت از 54/7 به 12 درصد بر پایه خشک طول، عرض، ضخام...
15 صفحه اولPrediction of Mechanical Properties of TWIP Steels using Artificial Neural Network Modeling
In recent years, great attention has been paid to the development of high manganese austenitic TWIP steels exhibiting high tensile strength and exceptional total elongation. Due to low stacking fault energy (SFE), cross slip becomes more difficult in these steels and mechanical twinning is then the favored deformation mode besides dislocation gliding. Chemical composition along with processing ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Engineering & Technology
سال: 2018
ISSN: 2227-524X
DOI: 10.14419/ijet.v7i4.19.27997