دانلود رایگان مقاله مدل سازی انتشار آتش سوزی بیابانی با مدل شبکه نیمه فیزیکی

عنوان فارسی
مدل سازی انتشار آتش سوزی بیابانی با استفاده از یک مدل شبکه نیمه فیزیکی
عنوان انگلیسی
Modeling wildland fire propagation using a semi-physical network model
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
8
سال انتشار
2015
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E2766
رشته های مرتبط با این مقاله
مهندسی مکانیک
گرایش های مرتبط با این مقاله
ایمنی صنعتی
مجله
مطالعات موردی در ایمنی آتش - Case Studies in Fire Safety
دانشگاه
ساحل عاج
کلمات کلیدی
آتش سوزی بیابانی، نرخ انبساط، انتقال حرارت، مدل شبکه، تجزیه و تحلیل میزان حساسیت
چکیده

ABSTRACT


In this paper we present a surface wildfire model which can be used to develop and test new firefighting strategies and land use planning practices. This model is simple, easy to implement and can predict the rate of fire spread, the fire contour and both burning and burned areas. It also incorporates weather conditions and land topography. The predictive capability of the model is partially assessed by comparison with data from laboratoryscale and prescribed burning experiments. A sensitivity analysis is conducted to identify the most influential input model parameters controlling fire propagation.

نتیجه گیری

5. Conclusion


A fast and simple surface fire model is presented, which combines the features of a network model with those of a semiphysical model of the interaction between the fire and vegetative cells which strongly depends on weather conditions, land topography, and vegetation. Radiation and convection from the flaming zone and embers, and radiative heat loss to the ambient are considered in the preheating process of unburned cells. The predictive capability of the model is partially assessed by comparison with data from laboratory-scale and prescribed burning experiments. Discrepancies between model results and measurements are observed. A better agreement should be obtained by increasing the accuracy with which model parameters are determined. A sensitivity study is performed using a full factorial plan of experiment showing how sensitive the rate of fire spread is to variations in certain model parameters. This could help to identify the parameters we should focus on in the future.


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