|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|269663||504691||2016||7 صفحه PDF||سفارش دهید||دانلود رایگان|
• A descriptive analytical framework for the initial sprinkler spray is proposed.
• The framework describes the measured spray as a probability distribution function.
• Lagrangian particles are initialized by a stochastic sampling of the PDF.
• These particles are suitable for representing the sprinkler spray in CFD fire models.
Accurate representation of the fire sprinkler spray enables quantitative engineering analysis of fire suppression performance. Increasingly, fire sprinkler systems are analyzed with computational fluid dynamics (CFD) fire models where the sprinkler spray is simulated with Lagrangian particles dispersed throughout the fire induced flow. However, there is limited guidance for representing the complex, spatio-stochastic characteristics of the initial sprinkler sprays in terms of these Lagrangian particles. The present work establishes a descriptive analytical framework for the initial sprinkler spray that is rigorously grounded in statistical theory, related to local spray properties, and capable of translating high-fidelity measurements into CFD inputs. This framework describes the initial sprinkler spray as a unified probability distribution function, varying over an initialization surface, and statistically representing measurements of near field local spray properties (volume flux, drop size distribution, and drop size–velocity correlation). Lagrangian particles accurately representing the sprinkler spray may be initialized by a stochastic sampling of this probability distribution function. This novel representation enables high-fidelity initialization of the sprinkler spray in CFD fire models, improving their utility in quantitative engineering analysis.
Journal: Fire Safety Journal - Volume 84, August 2016, Pages 1–7