Pipe bends, or elbows, cause energy loss in pipelines due to the flow conditions they create. This energy loss has traditionally been approximated based on published minor loss coefficients, known as k-factors. However, the energy losses of elbows can vary based on geometric characteristics, which may not be accounted for in the published k-factors. The purpose of this research was to quantify the variance in energy loss resulting from elbows with geometric differences and to determine appropriate methods for approximating these variances using computational fluid dynamics (CFD). Eight polyvinyl chloride (PVC) elbows were physically tested in a hydraulic laboratory to determine the individual loss coefficients. The resulting data show that the minor loss coefficient k for two short-radius elbows of the same nominal size can vary by up to 51%. The same tests on two of the elbows were repeated using CFD, in which they were modeled two different ways: 1) using the ideal geometry and 2) using the actual geometry. The actual geometry was captured using 3D scanning. Each geometry was used in a series of simulations, and the results were compared to the experimental data. The CFD simulations were able to reproduce similar variances between the two elbows as displayed in the physical tests, although they were unable to reproduce the same k-factors. When compared to the experimental k-factor data, using the actual geometries captured by 3D scanning was not consistently more accurate than using idealized geometries.
| Published in | Applied Engineering (Volume 8, Issue 2) |
| DOI | 10.11648/j.ae.20240802.12 |
| Page(s) | 69-79 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
3D Scanning of Pipes, CFD Simulation, Geometric Effects on Flow, Minor Loss Coefficient, Pipe Elbow Energy Loss
| [1] | I. Goswami, Civil Engineering All-In-One PE Exam Guide: Breadth and Depth. McGraw-Hill Education, 2015. |
| [2] | W. J. Rahmeyer, “Pressure loss coefficients of threaded and forged weld pipe fittings for ells, reducing ells, and pipe reducers,” ASHRAE Transactions, vol. 105, p. 334, 1999. |
| [3] | H. J. Coombs, “Pressure loss coefficients for large mitered elbows with diameters ranging from 36-inches to 144-inches,” Master's thesis, Utah State University, Logan, UT, 2019. https://doi.org/10.26076/zvsk-fm62 |
| [4] | P. Wichowski, T. Siwiec, and M. Kalenik, “Effect of the concentration of sand in a mixture of water and sand flowing through pp and pvc elbows on the minor head loss coefficient,” Water, vol. 11, no. 4, p. 828, 2019. https://doi.org/10.3390/w11040828 |
| [5] | E. J. Finnemore, J. B. Franzini, et al., Fluid mechanics with engineering applications, vol. 10. McGraw-Hill New York, 2002. |
| [6] | M. C. Potter and D. C. Wiggert, Schaum's outline of fluid mechanics. McGraw-Hill Education, 2021. |
| [7] | R. Coffield, P. Brooks, and R. Hammond, “Piping elbow irrecoverable pressure loss coefficients for moderately high reynolds numbers,” Tech. Rep. WAPD-T-3064, Bettis Atomic Power Lab., West Mifflin, PA, 1995. |
| [8] | W. J. Rahmeyer, “Pressure loss data for PVC pipe elbows, reducers, and expansions,” ASHRAE Transactions, vol. 109, p. 230, 2003. |
| [9] | L. Yogaraja, N. Liyanagamage, and K. De Silva, “Comparison of experimental results with empirical relationships for energy losses in pipe flow,” in 2021 Moratuwa Engineering Research Conference (MERCon), pp. 522-527, IEEE, 2021. https://doi.org/10.1109/MERCon52712.2021.9525661 |
| [10] | Siemens, “Simcenter STAR-CCM+ user guide version 2020.3,” Siemens Digital Industries Software, 2020. |
| [11] | P. Dutta, S. K. Saha, N. Nandi, and N. Pal, “Numerical study on flow separation in 90° pipe bend under high reynolds number by k-ε modelling,” Engineering Science and Technology, an International Journal, vol. 19, no. 2, pp. 904-910, 2016. https://doi.org/10.1016/j.jestch.2015.12.005 |
| [12] | J. Kim, M. Yadav, and S. Kim, “Characteristics of secondary flow induced by 90-degree elbow in turbulent pipe flow,” Engineering Applications of Computational Fluid Mechanics, vol. 8, no. 2, pp. 229-239, 2014. https://doi.org/10.1080/19942060.2014.11015509 |
| [13] | S. Sami and J. Cui, “Numerical study of pressure losses in close-coupled fittings,” HVAC & R Research, vol. 10, no. 4, pp. 539-552, 2004. https://doi.org/10.1080/10789669.2004.10391119 |
| [14] | W. J. Rahmeyer, “Pressure loss coefficients for close-coupled pipe ells,” ASHRAE Transactions, vol. 108, p. 390, 2002. |
| [15] | G. Gan and S. Riffat, “k-factors for HVAC ducts: Numerical and experimental determination,” Building Services Engineering Research and Technology, vol. 16, no. 3, pp. 133-139, 1995. https://doi.org/10.1177/014362449501600303 |
| [16] | R. Röhrig, S. Jakirlić, and C. Tropea, “Comparative computational study of turbulent flow in a 90pipe elbow,” International Journal of Heat and Fluid Flow, vol. 55, pp. 120-131, 2015. https://doi.org/10.1016/j.ijheatfluidflow.2015.07.011 |
| [17] | A. G. Andersson, P. Andreasson, and T. Staffan Lundström, “CFD-modelling and validation of free surface flow during spilling of reservoir indown-scale model,” Engineering Applications of Computational Fluid Mechanics, vol. 7, no. 1, pp. 159-167, 2013. https://doi.org/10.1080/19942060.2013.11015461 |
| [18] | T. J. Ashby, “Evaluating the hydraulic performance of digital photogrammetry-derived 3-dimensional models of a hydraulic structure using computational fluid dynamics,” Master's thesis, Utah State University, Logan, UT, 2020. https://doi.org/10.26076/d1a7-8c5a |
| [19] | G. Mandlburger and C. Briese, “Using airborne laser scanning for improved hydraulic models,” in International Congress on Modelling and Simulation, pp. 731-738, 2007. |
| [20] | J.-H. Lee and S.-J. Lee, “Application of laser-generated guided wave for evaluation of corrosion in carbon steel pipe,” Ndt & E International, vol. 42, no. 3, pp. 222-227, 2009. https://doi.org/10.1016/j.ndteint.2008.09.011 |
| [21] | M. Lepot, N. Stanić, and F. H. Clemens, “A technology for sewer pipe inspection (part 2): Experimental assessment of a new laser profiler for sewer defect detection and quantification,” Automation in Construction, vol. 73, pp. 1-11, 2017. https://doi.org/10.1016/j.autcon.2016.10.010 |
| [22] | N. Stanić, F. H. Clemens, and J. G. Langeveld, “Estimation of hydraulic roughness of concrete sewer pipes by laser scanning,” Journal of Hydraulic Engineering, vol. 143, no. 2, p. 04016079, 2017. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001223 |
| [23] | F. Sedlacek and M. Skovajsa, “Optimization of an intake system using CFD numerical simulation,” Proceedings in Manufacturing Systems, vol. 11, no. 2, p. 71, 2016. |
| [24] | R. T. Christensen, “Age effects on iron-based pipes in water distribution systems,” Master's thesis, Utah State University, Logan, UT, 2009. https://doi.org/10.26076/28aa-15e2 |
| [25] | Z. Čarija, Z. Mrša, and S. Fućak, “Validation of francis water turbine CFD simulations,” Strojarstvo: &cuml;asopis za teoriju i praksu u strojarstvu, vol. 50, no. 1, pp. 5-14, 2008. |
| [26] | Spears, “Schedule 40 white.” Available from: https://www.parts.spearsmfg.com/ProductDetails.aspx (accessed 30 April 2021). |
| [27] | P. K. Swamee and A. K. Jain, “Explicit equations for pipe-flow problems,” Journal of the hydraulics division, vol. 102, no. 5, pp. 657-664, 1976. https://doi.org/10.1061/JYCEAJ.0004542 |
| [28] | SHINING 3D, “EinScan-SP specs desktop 3D scanner,” 2020. Available from: https://www.einscan.com/einscan-sp (accessed 20 May 2021). |
| [29] | I. B. Celik, U. Ghia, P. J. Roache, and C. J. Freitas, “Procedure for estimation and reporting of uncertainty due to discretization in CFD applications,” Journal of fluids Engineering-Transactions of the ASME, vol. 130, no. 7, 2008. https://doi.org/10.1115/1.2960953 |
| [30] | L. H. Hellström, M. B. Zlatinov, G. Cao, and A. J. Smits, “Turbulent pipe flow downstream of a bend,” Journal of Fluid Mechanics, vol. 735, 2013. https://doi.org/10.1017/jfm.2013.534 |
| [31] | N. Costa, R. Maia, M. Proenca, and F. Pinho, “Edgeeffects on the flow characteristics in a 90 deg tee junction,” J. Fluids Eng., vol. 128, no. 6, pp. 1204-1217, 2026, https://doi.org/10.1115/1.2354524 |
APA Style
Pack, A., Barfuss, S., Sharp, Z. (2024). Using Experiments, 3D Scanning, and CFD to Analyze the Variance in Energy Losses Through Pipe Elbows. Applied Engineering, 8(2), 69-79. https://doi.org/10.11648/j.ae.20240802.12
ACS Style
Pack, A.; Barfuss, S.; Sharp, Z. Using Experiments, 3D Scanning, and CFD to Analyze the Variance in Energy Losses Through Pipe Elbows. Appl. Eng. 2024, 8(2), 69-79. doi: 10.11648/j.ae.20240802.12
AMA Style
Pack A, Barfuss S, Sharp Z. Using Experiments, 3D Scanning, and CFD to Analyze the Variance in Energy Losses Through Pipe Elbows. Appl Eng. 2024;8(2):69-79. doi: 10.11648/j.ae.20240802.12
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ae.20240802.12,
author = {Adam Pack and Steven Barfuss and Zachary Sharp},
title = {Using Experiments, 3D Scanning, and CFD to Analyze the Variance in Energy Losses Through Pipe Elbows},
journal = {Applied Engineering},
volume = {8},
number = {2},
pages = {69-79},
doi = {10.11648/j.ae.20240802.12},
url = {https://doi.org/10.11648/j.ae.20240802.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ae.20240802.12},
abstract = {Pipe bends, or elbows, cause energy loss in pipelines due to the flow conditions they create. This energy loss has traditionally been approximated based on published minor loss coefficients, known as k-factors. However, the energy losses of elbows can vary based on geometric characteristics, which may not be accounted for in the published k-factors. The purpose of this research was to quantify the variance in energy loss resulting from elbows with geometric differences and to determine appropriate methods for approximating these variances using computational fluid dynamics (CFD). Eight polyvinyl chloride (PVC) elbows were physically tested in a hydraulic laboratory to determine the individual loss coefficients. The resulting data show that the minor loss coefficient k for two short-radius elbows of the same nominal size can vary by up to 51%. The same tests on two of the elbows were repeated using CFD, in which they were modeled two different ways: 1) using the ideal geometry and 2) using the actual geometry. The actual geometry was captured using 3D scanning. Each geometry was used in a series of simulations, and the results were compared to the experimental data. The CFD simulations were able to reproduce similar variances between the two elbows as displayed in the physical tests, although they were unable to reproduce the same k-factors. When compared to the experimental k-factor data, using the actual geometries captured by 3D scanning was not consistently more accurate than using idealized geometries.},
year = {2024}
}
TY - JOUR T1 - Using Experiments, 3D Scanning, and CFD to Analyze the Variance in Energy Losses Through Pipe Elbows AU - Adam Pack AU - Steven Barfuss AU - Zachary Sharp Y1 - 2024/09/05 PY - 2024 N1 - https://doi.org/10.11648/j.ae.20240802.12 DO - 10.11648/j.ae.20240802.12 T2 - Applied Engineering JF - Applied Engineering JO - Applied Engineering SP - 69 EP - 79 PB - Science Publishing Group SN - 2994-7456 UR - https://doi.org/10.11648/j.ae.20240802.12 AB - Pipe bends, or elbows, cause energy loss in pipelines due to the flow conditions they create. This energy loss has traditionally been approximated based on published minor loss coefficients, known as k-factors. However, the energy losses of elbows can vary based on geometric characteristics, which may not be accounted for in the published k-factors. The purpose of this research was to quantify the variance in energy loss resulting from elbows with geometric differences and to determine appropriate methods for approximating these variances using computational fluid dynamics (CFD). Eight polyvinyl chloride (PVC) elbows were physically tested in a hydraulic laboratory to determine the individual loss coefficients. The resulting data show that the minor loss coefficient k for two short-radius elbows of the same nominal size can vary by up to 51%. The same tests on two of the elbows were repeated using CFD, in which they were modeled two different ways: 1) using the ideal geometry and 2) using the actual geometry. The actual geometry was captured using 3D scanning. Each geometry was used in a series of simulations, and the results were compared to the experimental data. The CFD simulations were able to reproduce similar variances between the two elbows as displayed in the physical tests, although they were unable to reproduce the same k-factors. When compared to the experimental k-factor data, using the actual geometries captured by 3D scanning was not consistently more accurate than using idealized geometries. VL - 8 IS - 2 ER -
Hatch Associates Consultants, Minneapolis, United States
Civil and Environmental Engineering Department, Utah State University, Logan, United States
Civil and Environmental Engineering Department, Utah State University, Logan, United States
