کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
830663 1470358 2012 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A fuzzy model for evaluation and prediction of slurry erosion of 5127 steels
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی (عمومی)
پیش نمایش صفحه اول مقاله
A fuzzy model for evaluation and prediction of slurry erosion of 5127 steels
چکیده انگلیسی

This paper introduces a fuzzy logic model to evaluate and predict the slurry erosion of ductile materials in engineering and chemical applications. There are seven variables which have the most significant influences on the slurry erosion of ductile material, and must be taken into considerations. These are impact angle, time, roundness factor, aspect ratio, particle size, impact velocity and concentration of the particles. By using the fuzzy rules which can be generated based on some experimental observations, a two-layer fuzzy model could be developed to correlate these variables to the slurry erosion (weight loss of material). The model is based on the assumption that the slurry erosion characteristics of ductile materials is an imprecise complex function of many interacting variables, and can be described and evaluated by the theory of fuzzy sets. Membership functions and fuzzy rule-base for application to slurry erosion of 5127 steel as a ductile material are presented in detail to demonstrate the effectiveness of fuzzy logic in modeling such a complex system in an efficient way. This constructed model would facilitate the development of an expert, real-time and integrated system using fuzzy logic technology to monitor the level of the slurry erosion process.


► A fuzzy logic model to evaluate and predict the slurry erosion of ductile materials.
► Slurry erosion is a well known cause of the machine component failures.
► Effectiveness of fuzzy logic in modeling a complex system in an efficient way.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials & Design - Volume 39, August 2012, Pages 186–191
نویسندگان
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