scholarly journals Modeling Wind Direction Distributions Using a Diagnostic Model in the Context of Probabilistic Fire Spread Prediction

Author(s):  
Rachael Quill ◽  
Jason J. Sharples ◽  
Natalie S. Wagenbrenner ◽  
Leesa A. Sidhu ◽  
Jason M. Forthofer
2020 ◽  
Vol 59 (2) ◽  
pp. 263-280
Author(s):  
Ilze Pretorius ◽  
Andrew Sturman ◽  
Tara Strand ◽  
Marwan Katurji ◽  
Grant Pearce

AbstractIn February 2017, a wildfire occurred in the Port Hills on the southern boundary of Christchurch city in New Zealand. It was one of the country’s most severe fires of the last decade in terms of the scale of evacuation, infrastructure damage, and property loss. On the third day of the fire, fire behavior was unexpectedly active, and two rapid downhill fire-spread events took place, creating a dangerous situation for firefighters. The aim of this paper is to explore the atmospheric processes that influenced the fire behavior at a range of meteorological scales, from the synoptic to meso- and microscales. Meteorological and fire data analyzed include observed data together with model simulations of weather conditions at different scales: 1) the Weather Research and Forecasting (WRF) numerical weather prediction model, which provided the regional context of the fire; and 2) the California Meteorological (CALMET) diagnostic model, which was used to undertake a higher-resolution investigation of atmospheric processes near the fire. Results indicate that the fire was not strongly seasonally influenced. Instead, it appears the fire conditions were the effect of a specific combination of synoptic weather conditions and local meteorological conditions. The first rapid downhill fire-spread event was the result of airflow interaction with the intricate terrain of the Port Hills under stable nocturnal conditions. The second downhill fire-spread event bears similarities to vorticity-driven lateral spread, because the downhill component of the spread happened on a broad fire flank perpendicular to the surface wind direction and characteristic pyrocumulus convection occurred.


2021 ◽  
Vol 7 ◽  
Author(s):  
Sampath Adusumilli ◽  
James E. Chaplen ◽  
David L. Blunck

Source terms of the number of firebrands released as trees/shrubs torch are essential for helping to more accurately implement detailed physics-based models of wildfire propagation, particularly when torching occurs. A key challenge in estimating these source terms is the difficulty in measuring firebrand generation rates from the source. Typical studies have reported generation characteristics (firebrands/m2), but enumeration of the total number of firebrands released has remained elusive. Recently, a fire-resistant fabric was successfully employed to quantify “hot” firebrands (i.e., can potentially lead to further fire spread) generated during tree-scale burns. In this paper, a total of 71 tree/shrubs were burned to quantify hot firebrand production statistics for Douglas-fir, ponderosa pine, and sagebrush. A network of 65 fire-resistant fabric stations were deployed during the burns to measure the “hot” firebrands that are released. These stations are placed strategically at several radii and angles in the prominent wind direction. Using the number of firebrands determined from the fabric, a first-order extrapolation method was developed and evaluated to estimate the source terms (i.e., total number of hot firebrands released). Variation in the firebrand production with the height of the trees and for three species is reported. The total number of hot firebrands produced typically increased with the height of the tree/shrub burned as expected. The specific hot firebrand production (firebrands produced per kg dry mass burned) is exponentially dependent on the moisture content of the tree and had an inconclusive correlation with the height of the trees. Overall, for trees of comparable moisture content, sagebrush produced higher specific hot firebrands when compared to ponderosa pine and Douglas-fir species.


Author(s):  
Lanfang Zheng ◽  
Liang Zhou ◽  
Xiangtao Jia ◽  
Xiaokang Li

Author(s):  
M. M. Klunnikova

The work is devoted to the consideration of improving the quality of teaching students the discipline “Numerical methods” through the development of the cognitive component of computational thinking based on blended learning. The article presents a methodology for the formation of computational thinking of mathematics students, based on the visualization of algorithmic design schemes and the activation of the cognitive independence of students. The characteristic of computational thinking is given, the content and structure of computational thinking are shown. It is argued that a student with such a mind is able to manifest himself in his professional field in the best possible way. The results of the application of the technique are described. To determine the level of development of the cognitive component of computational thinking, a diagnostic model has been developed based on measuring the content, operational and motivational components. It is shown that the proposed method of developing computational thinking of students, taking into account the individual characteristics of students’ thinking, meaningfully based on the theoretical and practical aspects of studying the discipline, increases the effectiveness of learning the course “Numerical methods”. The materials of the article are of practical value for teachers of mathematical disciplines who use information and telecommunication technologies in their professional activities.


2012 ◽  
Vol 11 (8) ◽  
pp. 1475-1480 ◽  
Author(s):  
Omer Kucuk ◽  
Ertugrul Bilgili ◽  
Serkan Bulut ◽  
Paulo M. Fernandes

Author(s):  
Irina Bystrova ◽  
E. Danil'chuk ◽  
Boris Podkopaev

The problem of constructing a diagnostic model for a network S consisting of a number of digital automata is considered, provided that the diagnostic models of all network components are known. It is assumed that these models are given by systems of logical equations, and the errors to be detected are localized in any but a single component of the network.


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