Investigation of the Statistical Behaviour of Thin ZnO-based Varistors Using a Monte Carlo Algorithm

سال انتشار: 1385
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,393

فایل این مقاله در 6 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

ICEE14_417

تاریخ نمایه سازی: 25 تیر 1387

چکیده مقاله:

In this paper a computational method has been used for investigation of the statistical behaviour of the thin zinc-oxide varistors. In a ZnO varistor, when a voltage is applied between the electrodes, there is certain number of grains, which does not present any non-linear characteristic and/or are nonconducting. Under the applied voltage, several current paths occur from one electrode to the other, which we call them the current percolation paths. From the previous works it is known that the overall current through the varistor depends on the block thickness as well as the percentage of nonconducting grains in the varistor. Then the number of grains between the electrodes crossing by the current is a statistical parameter, depending on the block thickness and percentage of nonconducting grains. In this work a Monte Carlo method has been used to study the statistical behaviour of the thin varistors. It is found that the number of ZnO grains providing the percolation path in thin varistors follows a lognormal distribution. The results can help us to have a better understanding of behaviour of the varistors, which enables us to make more realistic electric models for these elements.

نویسندگان

Mohammad Reza Meshkatoddini

Electric Materials Department, Shahid Abbaspour University of Technology, Tehran, Iran (Currently with the University of Toronto)

Steven Boggs

Department of Electrical and Computer Engineering, University of Toronto, Canada

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Steven Boggs and Hideyasu Andoh, 00A Statistical Approach to Prediction ...
  • F. Greuter and G. Blatter, 0Electric properties of grain boundaries ...
  • Shengtao Li, Feng Xie & Fuyi Liu, 0#Relation between Residual ...
  • C.P.Robert and G. Casella. "Monte Carlo Statistical Methods" (second edition). ...
  • C _ W .Ueberhuber, Numerical Computation 2: Methods, Software, and ...
  • M _ R _ M eshkatoddini et al, "New High ...
  • M _ R _ Me shkatoddini, "Comparative Study of Different ...
  • نمایش کامل مراجع