scholarly journals MATHEMATICAL MODELLING OF RUNNING CROWN FOREST FIRES

2010 ◽  
Vol 15 (2) ◽  
pp. 161-174 ◽  
Author(s):  
Dmitry Barovik ◽  
Valery Taranchuk
Keyword(s):  
Mathematical Model ◽  
Forest Fire ◽  
Forest Fires ◽  
Computer Modelling ◽  
Fire Behaviour ◽  
Fire Propagation ◽  
Finite Difference Approximations ◽  
Difference Approximations ◽  
Simplifying Assumptions ◽  
Crown Forest

Adapted mathematical model for simulation of running crown forest fire propagation is considered. Simplifying assumptions, equations of the model, initial and boundary conditions, finite difference approximations are introduced. The results of computer modelling and the peculiarities of forest fire behaviour in heterogeneous forests are discussed.

scholarly journals MATHEMATICAL MODEL OF THE INTERACTION OF THE SCREW WORKING BODIES OF FOREST FIRE GROUND-THROWING MACHINES WITH THE GROUND COVER

2021 ◽  
Vol 11 (1) ◽  
pp. 163-171
Author(s):  
Petr Popikov ◽  
Anton Pozdnyakov
Keyword(s):  
Mathematical Model ◽  
Forest Fire ◽  
Forest Fires ◽  
Hydraulic Drive ◽  
Ground Cover ◽  
Forest Litter ◽  
Working Fluid ◽  
Hydraulic Motor ◽  
Working Bodies ◽  
Fire Ground

The paper provides an overview of research on the working processes of screw working bodies of technological machines. It is noted that at present such important issues in the theory of auger working bodies as the required number of auger turns, the required position of the auger spiral in relation to the center, etc. have not been fully resolved, since the solution of these issues can provide an increased productivity of the tool. A structural and technological scheme of a forest fire machine with multifunctional modules is proposed, which consists of auger working bodies, which can be changed modularly with a screw metal thread for a brush, depending on the area and type of soil, the rotor of the thrower, with the ability to drive the cutters-throwers and auger working bodies both from the power take-off shaft of the tractor, and using a hydraulic motor, a guide casing. A mathematical model of an auger working body with a hydraulic drive has been compiled for removing the ground cover with forest litter when extinguishing forest fires with a ground gun, so that combustible materials do not fall into the fire zone together with the soil flow from the rotor-thrower. The working process of the hydraulic drive of the auger working bodies of a forest fire ground-sweeping machine is described by a system of differential equations, including the equations of translational and rotational movements of the auger working body and the equation of the flow rate of the working fluid. The problem of optimization of kinematic and dynamic parameters of auger working bodies of forest fire ground-sweeping machine is set

scholarly journals Mathematical Model of Forest Fire Soil-thrower Movement

2020 ◽  
Author(s):  
Olga Dornyak ◽  
Ivan Bartenev ◽  
Mikhail Drapalyuk ◽  
Dmitry Stupnikov ◽  
Sergey Malyukov ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Forest Fire ◽  
Forest Fires ◽  
Degrees Of Freedom ◽  
Translational Motion ◽  
Steady Motion ◽  
Technological Parameters ◽  
Lagrange Equations ◽  
Milling Tool ◽  
The Mathematical Model

The design of a forest fire soil-thrower made to prevent and eliminate ground forest fires is presented. A mathematical model of machine movement has been developed, which enables to study the laws of the interaction process of the design with the soil. It is accepted that the machine has two degrees of freedom. The mathematical model has been obtained using the Lagrange equations of the second kind. The design and technological parameters of the forest fire soil-throwing machine, affecting the efficiency of its work, including mass and width of the grip of the ripper casing, mass, radius and frequency of rotation of the milling tool, the number and geometric parameters of the blades are taken into account. Mathematical model enables to determine the effect of these parameters on the characteristics of the movement of ripper casing and milling working body. A mathematical model is needed to synchronize the translational motion of the unit and the rotational motion of the rotor. Formulas have been obtained for the steady motion of the forest fire soil-thrower, that determine the hauling power of tractor and torque that ensures the operation of milling tools.

scholarly journals First steps towards a dynamical model for forest fire behaviour in Argentinian landscapes

2020 ◽  
Vol 20 (2) ◽  
pp. e09
Author(s):  
Monica Denham ◽  
Karina Laneri ◽  
Viviana Zimmerman ◽  
Sigfrido Waidelich
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Reaction Diffusion ◽  
Dynamical Model ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Propagation ◽  
Diffusion Convection ◽  
And Diffusion ◽  
Simulation Time

We developed a Reaction Diffusion Convection (RDC) model for forest fire propagation coupled to a visualization platform with several functionalities requested by local firefighters. The dynamical model aims to understand the key mechanisms driving fire propagation in the Patagonian region. We'll show in this work the first tests considering combustion and diffusion in artificial landscapes. The simulator, developed in CUDA/OpenGL, integrates several layers including topography, weather, and fuel data. It allows to visualize the fire propagation and also to interact with the user in simulation time. The Fire Weather Index (FWI), extensively used in Argentina to support operative preventive measures for forest fires management, was also coupled to our visualization platform. This additional functionality allows the user to visualize on the landscape the fire risks, that are closely related to FWI, for Northwest Patagonian forests in Argentina.

Forest Fire Propagation in Inclined Terrains

2001 ◽  
Author(s):  
K. Satoh ◽  
K. T. Yang
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Control Strategies ◽  
Weather Conditions ◽  
Strong Wind ◽  
Fire Control ◽  
Fire Propagation ◽  
Hot Air ◽  
Fire Scenarios ◽  
Local Weather

Abstract Forest fires are of common occurrence all over the world, causing the loss of precious natural resources. The propagation of forest fires depends on many factors, notably local weather conditions. Additionally, the local terrain such as mountainous areas also plays an important role. For instance, forest fires may propagate from mountain ridges to ridges due to locally strong wind by means of firebrands and hot air flows. While much is known cm the methodologies on the forest fire control, they are largely empirical and may not be totally effective. Therefore, scientific studies based on fundamental physical understanding of the underlying phenomena are needed to provide definitive data on cause-effect relationships in various forest fire scenarios, so that the collective database can be used to suggest control strategies and preventive measures for forest fires. The present study is motivated by this approach, and specifically focuses on the phenomena of rapid forest-fire propagation from mountain slqpes to other similar mountain slopes in the direction of the wind. The study deals with both laboratory experiments and numerical simulations by the use of a CFD-based fire field model.

scholarly journals A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Learning Strategy ◽  
Early Stage ◽  
Fire Detection ◽  
Surveillance Systems ◽  
Region Detection ◽  
Decision Network ◽  
Fire Smoke ◽  
Weakly Supervised

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.

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