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Related Concept Videos

Flame Photometry: Overview01:02

Flame Photometry: Overview

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Flame Photometry: Lab01:16

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In a flame photometer, when a solution like potassium chloride is aspirated into the flame, the solvent evaporates, leaving behind dehydrated salt. This salt dissociates into free gaseous atoms in their ground state. Some of these atoms absorb energy from the flame, leading to their excitation. The excited atoms return to the ground state, emitting photons at characteristic wavelengths. Because only electronic transitions are involved, the resulting emission lines are very narrow. The intensity...
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Plane potential flows simplify fluid motion by assuming the fluid to be irrotational and incompressible. These characteristics allow these flows to be described by a velocity potential function, ϕ, representing the flow speed in a given direction, and a stream function, ψ, that visualizes the flow path, both governed by Laplace's equation. These parameters help in estimating flow patterns, velocity distributions, and pressure fields around various hydraulic structures.
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A fire extinguisher that uses pressurized water relies on fluid dynamics principles to generate a high-velocity stream capable of suppressing flames. The water is stored at a much higher pressure inside the extinguisher than the surrounding atmosphere. This pressure difference forces the water to flow rapidly when the extinguisher is activated, and the behavior of the water as it exits the nozzle can be understood using fundamental equations of fluid dynamics.
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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
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Related Experiment Video

Updated: Sep 16, 2025

Wind Tunnel Experiments to Study Chaparral Crown Fires
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Fire spread simulations using Cell2Fire on synthetic and real landscapes.

Minho Kim1, Cristobal Pais2, Marta C Gonzalez3,4

  • 1Landscape Architecture and Environmental Planning, University of California, Berkeley, CA, 94720, USA.

Scientific Reports
|July 11, 2025
PubMed
Summary

Cell2Fire, a new wildfire spread model, accurately simulates fire behavior and outperforms existing models after optimization. It offers improved accuracy and computational efficiency for realistic wildfire predictions.

Keywords:
Fire spread modelingOptimizationWildfires

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Area of Science:

  • Wildfire modeling
  • Computational science
  • Environmental science

Background:

  • Wildfires are a global concern impacting natural and built environments.
  • Fire spread models (FSMs) are crucial for understanding and predicting wildfire behavior.
  • Existing FSMs may not always produce perfectly realistic simulations.

Purpose of the Study:

  • To evaluate Cell2Fire, a cellular automata-based FSM, against established models.
  • To enhance Cell2Fire's simulation accuracy using optimization techniques.
  • To assess Cell2Fire's computational efficiency compared to other FSMs.

Main Methods:

  • Tested Cell2Fire on synthetic landscapes, including U.S. terrains.
  • Applied multi-objective optimization and blackbox optimization to adjust fire spread parameters.
  • Validated optimized Cell2Fire against the 2001 Dogrib Fire data.

Main Results:

  • Cell2Fire showed high agreement with existing FSMs on synthetic landscapes.
  • Optimized Cell2Fire significantly improved prediction accuracy (F1-score from 0.74 to 0.83) for the Dogrib Fire.
  • Cell2Fire demonstrated superior computational efficiency with linear runtime scaling versus exponential for Prometheus.

Conclusions:

  • Optimized Cell2Fire provides more realistic wildfire simulations than benchmark FSMs.
  • Cell2Fire offers enhanced accuracy and computational efficiency for wildfire modeling.
  • The model can be adapted with custom data for broader applications.