Air tanker drop patterns

Legendre, Dominique; Becker, Ryan; Alméras, Elise; Chassagne, Amélie

doi:10.1071/wf13029

Cited by 20 publications

(34 citation statements)

References 5 publications

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“…The main goal was to find a relation determining the suppression patch dimensions from aircraft payload mass and at most two other input parameters. The suppressant drop experiment data, which was collected from [11], was obtained from a wide variety of aircraft types and delivery systems. In general, the delivery systems in the study can be first classified (as Model) into fixed-wing aircraft and rotorcraft.…”

Section: Wildfire Suppressant Drop Modelmentioning

confidence: 99%

System of Systems Simulation Driven Wildfire Fighting Aircraft Design

Prakasha

Nagel

Kilkis

et al. 2021

Aiaa Aviation 2021 Forum

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Large wildfires are increasingly occurring phenomenon in several since the past few years. The suppression of wildfires is complex considering heterogeneous independent constituent systems operating together to monitor, mitigate, and suppress the fire. In addition, the management of the disaster response involve multiple institutions in collaboration. Recognition of this wildfire fighting scenario, as a System of Systems (SoS) is valid. Aerial vehicles may play a big role in firefighting considering monitoring and suppression at early stages when the fire is still small. Thus, there is scope for designing a new Unmanned Aerial Vehicle (UAV) with a payload of 250 kg to 500 kg for aerial forest fire suppression, using a SoS wildfire simulation driven aircraft design approach, where the individual optimum performance of a system, especially of a new aircraft for firefighting, does not guarantee optimum overall firefighting mission effectiveness. Whereas an optimum combinationof fleet, technology and operational tactics can effectively suppress fire. For this reason, this research focuses on four different aspects: 1) Applying the inverse design paradigm to a wildfire suppression air vehicle by coupling a fire propagation cellular automata model with a stochastic agent-based simulation of an evolved firefighting SoS. An efficient SoS framework to Evaluate fleet performance. 2) Four System of systemssystemsubsystem interlinking research questions are addressed with corresponding sensitivity results. The impact of wildfire based on vehicle fleet size, vehicle architecture (Tiltrotor, Compound Heli, Multirotor or Lift cruise), payload carrying capability, response time and cruise speed. 3) The evolution of perfect combination of aerial vehicle fleet with different vehicle architectures, technologies and performances using simulations. 4) Obtaining a set of system level (aircraft level) Measures of Performance (MoP) for the large suppression UAVs that produce improved SoS-level Measures of Effectiveness (MoE) during an initial attack quantified by containment time and total fire burnt area. As addressed by research questions and results. The response time and Number of Aircraft has large impact on success of the firefighting mission. As the time advantage deteriorate, the wild fire expands exponentially.

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Section: Wildfire Suppressant Drop Modelmentioning

confidence: 99%

System of Systems Simulation Driven Wildfire Fighting Aircraft Design

Prakasha

Nagel

Kilkis

et al. 2021

Aiaa Aviation 2021 Forum

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“…The pattern of the drop has also been modelled, Suter (2000) discussed the statistical matters and experiment design to characterize air-tanker drops. Legendre et al (2014) and Martínez Oller (2015) conducted a series of experiments with air-tankers and helicopters. These studies conclude that the water drops are stadium shaped, which length is controlled by the coverage level and speed and a standard width of 30 meters for air-tankers and 5 meters for helicopters (both ventral tank or bambi bucket).…”

Section: Air Operations Simulationmentioning

confidence: 99%

Simulation of Aerial Supression Tasks in Wildfire Events Integrated with Gisfire Simulator

Jové

Petit

Garcia

2020

2020 Winter Simulation Conference (WSC)

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Wildfire simulation tools focus on how fire spreads in the natural environment. Simulation of fire containment operations can provide managers with a tool that combine wildfire evolution with suppression operations. Combined simulation tools are useful to evaluate different strategies and tactics in firefighting wildfires. This paper presents the modelling and simulation of aerial containment operations integrated into a wildfire spread simulator. A continuous space wildfire spread simulator has been used for fire spread simulation. This simulator called GisFIRE integrates aerial operations and uses QGIS geographical information system to integrate both simulation tools with geographical information. The information system combines air facilities locations, usable bodies of water, and other relevant geo-information with the simulation procedures. Open source software is a requirement to allow integration of different software packages and usage of OGC standards to represent geographical information.

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“…Amorim [13]- [15] has made a very detailed numerical study on the water-dropping model, especially discussing the mechanism of droplet rupture and the influence of tree canopy on gas-liquid flow. Furthermore, Legendre et al [16] combine the multi-type experimental data and theories to fit the formula of waterdropping distribution and verify it with the experimental data from Giroud et al [17]. Under considering the breakdown and dispersion of droplets, Qureshi and Altman [18] improve the distribution model.…”

Section: Introductionmentioning

confidence: 99%

“…where, L m is the quality of the droplet, , , c. In the diffusion distribution stage, the relationship among the water-dropping scheme, the above parameters, the diffusion radius and ground distribution of water body needs to be built. Combined with the jet theory from Albertson [32] and the experimental fitting model of Legendre [16], it can be seen that after reaching a certain height, the evaporation and dissipation of the droplet will stop the expansion of the diffusion radius. Therefore, the entire diffusion radius of the water body will expand in accordance with the law of jet flow first.…”

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confidence: 98%

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A Fast Optimization Method of Water-Dropping Scheme for Fixed-Wing Firefighting Aircraft

Wang

Tian

et al. 2021

IEEE Access

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The water-dropping scheme plays an important role in the aerial firefighting mission. When a wildfire occurs, the main problem faced by the aircrew is how to choose the appropriate water-dropping scheme (speed, height and trajectory) to achieve the optimal firefighting effect. However, so far, the crew members can only rely on the existing experience to generate the scheme, which lacks the corresponding theory method support. To solve above problem, this paper proposes a fast optimization method of waterdropping scheme for fixed-wing firefighting aircraft. Through the feature extraction of grid distribution, the agent model between aircraft water-dropping scheme and water distribution polygon is built taking advantage of neural network. Meanwhile, the corresponding extinguishing efficiency evaluation model is established with discrete points of fire area. Based on these researches, the combined genetic algorithm is used for searching the optimal water-dropping scheme. Finally, the feasibility and rapidity of the method are demonstrated through the application of examples. It is also shown that the method can optimize the water-dropping scheme quickly instead of aircrew experience and play a role of auxiliary decision support for the firefighting mission of fixed-wing firefighting aircraft.INDEX TERMS aerial firefighting, agent water-dropping model, fixed-wing firefighting aircraft, genetic algorithms, water-dropping scheme, neural networks, aerospace simulation

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Air tanker drop patterns

Cited by 20 publications

References 5 publications

System of Systems Simulation Driven Wildfire Fighting Aircraft Design

System of Systems Simulation Driven Wildfire Fighting Aircraft Design

Simulation of Aerial Supression Tasks in Wildfire Events Integrated with Gisfire Simulator

A Fast Optimization Method of Water-Dropping Scheme for Fixed-Wing Firefighting Aircraft

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