Experimental evaluation of correlations used to calculate friction factor for turbulent flow in cylindrical pipes

La distribución usando redes hidráulicas define la planeación, producción y flexibilidad de la hidro-gestión en empresas. Sin embargo, las fugas representan perdidas económicas en términos de mantenimiento y ubicación de las fallas. En este contexto, el flujo y presión al momento de que ocurra un fallo son las variables de análisis. Como primera contribución de esta investigación proponemos simular las perdidas volumétricas de agua. De hecho, el software libre Openfoam es la herramienta computacional y el modelo de turbulencia k-ω se seleccionó para un fluido en transición, es decir fluido que esta entre el régimen laminar y turbulento. La segunda contribución de esta investigación consiste en un algoritmo para detectar fugas en un sistema de tuberías. El algoritmo está basado en Teorema de Reynolds. Respecto a los resultados obtenidos con el Teorema de Reynolds, podemos decir que resultados son comparados con una red hidráulica real, obteniendo errores porcentuales de 4% para los mejores datos y 9% para el peor, y una distancia promedio para encontrar la fuga igual a 2,7 metros. Se demostró que la presión cae de forma lineal de acuerdo con la ley de Darcy. En conexión con los resultados, en métodos tradicionales se instalan manómetros a lo largo de las tuberías para identificar esta caída de presión, si el número de manómetros no es suficiente, la fuga puede pasar indetectada. El método propuesto en este proyecto permite localizar la fuga únicamente utilizando 2 manómetros. Lo cual lo hace más práctico para el caso de tuberías de difícil acceso.

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“…En [38] y [39] se establecieron para el flujo turbulento la relación entre las variables f y Re que es mostrada en la ecuación 2 no lineal.…”

Section: Ecuación De Colebrookunclassified

Modelo numérico de detección de fugas para sistema de tuberias.

Camperos

García-Guarín

Nolasco-Serna

2020

AiBi Revista de Investigación, Administración e Ingeniería

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“…We use the Wright ω-function implemented in Matlab as WrightOmegaq [21] for verifications of all approximations in this reply. However, to date, the Lambert W-function has been more commonly used in hydraulics [22][23][24][25][26] compared to its cognate Wright ω-function. Unfortunately, built-in procedures for these special functions do not exist in common spreadsheet solvers, such as Microsoft Excel [27].…”

Section: Colebrook Equation Expressed Through the Wright ω-Functionmentioning

confidence: 99%

Accurate and Efficient Explicit Approximations of the Colebrook Flow Friction Equation Based on the Wright ω-Function: Reply to Discussion

Brkić¹,

Praks

2019

Mathematics

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This reply gives two corrections of typographical errors in respect to the commented article, and then provides few comments in respect to the discussion and one improved version of the approximation of the Colebrook equation for flow friction, based on the Wright ω-function. Finally, this reply gives an exact explicit version of the Colebrook equation expressed through the Wright ω-function, which does not introduce any additional errors in respect to the original equation. All mentioned approximations are computationally efficient and also very accurate. Results are verified using more than 2 million of Quasi Monte-Carlo samples.

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“…For the first derivatives, [8,9,[21][22][23] should be consulted. For Example 1, in which Re = 2.3 × 10 5 and ε D = 10 −4 , for initial starting point…”

Section: Multi-point Iterative Proceduresmentioning

confidence: 99%

“…The task can start with a simple trial/error approach that can, in a certain way, put the Colebrook equation in balance, while, furthermore, a simple fixed-point iteration method can be introduced in the curriculum [20]. Then, more complex approaches that require derivatives of the Colebrook equation can lead students to the Newton-Raphson iterative methods [21][22][23] or to the more complex multi-point iterative methods [8,9]. A first simple explicit approximate formula with inner iterative cycles can be introduced using such approaches [24].…”

Section: Introductionmentioning

confidence: 99%

What Can Students Learn While Solving Colebrook’s Flow Friction Equation?

Brkić

Praks

2019

Fluids

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Even a relatively simple equation such as Colebrook’s offers a lot of possibilities to students to increase their computational skills. The Colebrook’s equation is implicit in the flow friction factor and, therefore, it needs to be solved iteratively or using explicit approximations, which need to be developed using different approaches. Various procedures can be used for iterative methods, such as single the fixed-point iterative method, Newton–Raphson, and other types of multi-point iterative methods, iterative methods in a combination with Padé polynomials, special functions such as Lambert W, artificial intelligence such as neural networks, etc. In addition, to develop explicit approximations or to improve their accuracy, regression analysis, genetic algorithms, and curve fitting techniques can be used too. In this learning numerical exercise, a few numerical examples will be shown along with the explanation of the estimated pedagogical impact for university students. Students can see what the difference is between the classical vs. floating-point algebra used in computers.

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Experimental evaluation of correlations used to calculate friction factor for turbulent flow in cylindrical pipes

Cited by 7 publications

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Modelo numérico de detección de fugas para sistema de tuberias.

Modelo numérico de detección de fugas para sistema de tuberias.

Accurate and Efficient Explicit Approximations of the Colebrook Flow Friction Equation Based on the Wright ω-Function: Reply to Discussion

What Can Students Learn While Solving Colebrook’s Flow Friction Equation?

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