Mathematical Modeling for Evaluating the Hydraulic and Thermodynamic Performance of the Hamada–Zawiya Pipeline: A Novel Net Exergy Improvement through Heating (NEIH) Index and Enhanced Light-Crude-Oil Transport Efficiency
DOI:
https://doi.org/10.65405/c97zva17Keywords:
Hamada crude oil; Pipeline transportation; Hydraulic performance; Exergy analysis; Net Exergy Improvement through Heating (NEIH); Andrade model; Pressure dropAbstract
Long-distance crude-oil transportation through pipelines is subject to significant operational and hydraulic challenges arising from thermal variations, which directly affect the fluid’s rheological and physical properties. This study develops an integrated mathematical modeling framework to evaluate the influence of temperature on the rheological, hydraulic, and thermodynamic behavior of Hamada light crude oil (42.6° API) flowing through the 387-km Hamada–Zawiya pipeline. The Andrade model was employed to represent the temperature dependence of dynamic viscosity, while the Swamee–Jain equation was used to calculate the friction factor under turbulent-flow conditions. The analysis further introduces the Net Exergy Improvement through Heating (NEIH) index, which quantitatively balances the mechanical-exergy savings obtained from reducing viscous losses against the thermal exergy consumed in heating the crude oil.
Simulation results showed that increasing the operating temperature sharply reduced the dynamic viscosity from 11.84 cP at 10°C to 1.85 cP at 100°C, accompanied by an increase in the Reynolds number (Re) from 42,422 to 250,373. The total pressure drop decreased from 137.02 bar to 91.41 bar as flow resistance declined, thereby generating substantial mechanical-energy savings. The NEIH index also demonstrated a clear advantage over the conventional index: it increased from a negative value of −5.3437 at 10°C to a maximum of 6.4777 at 20°C, revealing an improved balance between thermal and mechanical exergy and enabling the identification of the most energy-efficient thermal operating range. The proposed model provides a quantitative framework for evaluating crude-oil pipeline performance and supporting decisions aimed at optimizing energy consumption and thermodynamic efficiency.
Downloads
References
[1] Mohitpour, M., Golshan, H., & Murray, A. (2007). Pipeline Design and Construction: A Practical Approach. 3rd ed. New York: ASME Press.
[2] Speight, J. G. (2014). The Chemistry and Technology of Petroleum. 5th ed. Boca Raton: CRC Press.
[3] Andrade, E. N. da C. (1930). The Viscosity of Liquids. Nature, 125, 309–310.
[4] Zawiya Oil Refining Company. (2025). Internal Laboratory Report No. CO-412: Hamada Crude Oil Quality Analysis. Zawiya Refinery Laboratory, Libya.
[5] ASTM International. (2023). ASTM D1298: Standard Test Method for Density, Relative Density, or API Gravity of Crude Petroleum and Liquid Petroleum Products by Hydrometer Method. West Conshohocken,PA:ASTM International.
[6] ASTM International. (2024). ASTM D445: Standard Test Method for Kinematic viscosity
of Transparent and Opaque Liquids. West Conshohocken, PA: ASTM International.
[7] ASTM International.(2022). ASTM D97: Standard Test Method For Pour Point of Petroleum Products. West Conshohocken, PA: ASTM International.
[8] ASTM International.(2022) (Latest edition). ASTM D3230: Standard Test Method for Salts in Crude Oil. West Conshohocken, PA: ASTM International.
[9] ASTM International. (Latest edition).(2022) ASTM D1796: Standard Test Method for Water and Sediment in Fuel Oils by the Centrifuge Method. WestConshohocken, PA: ASTM International.
[10] Colebrook, C. F., & White, C. M. (1937). Experiments with Fluid Friction in
Roughened Pipes. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 161(906), 367–381.
[11] Swamee, P. K., & Jain, A. K. (1976). Explicit Equations for Pipe-Flow Problems. Journal of the Hydraulics Division, 102(5), 657–664.
[12] Dincer, I., & Rosen, M. A. (2021). Exergy: Energy, Environment and Sustainable Development (3rd ed.). Elsevier.
[13] Alriheebi, R. A. (2026). Integrated Modeling and Mult objective Control of Multilevel DC/AC Inverters for Conducted Electromagnetic Interference Mitigation. Al-Farooq Journal of Sciences, 2(3), 897-925.
[14] Hamied, R. S., Mohammed Ali, A. N., & Sukkar, K. A. (2023). Enhancing Heavy Crude Oil Flow in Pipelines through Heating-Induced Viscosity Reduction in the Petroleum Industry. Fluid Dynamics & Materials Processing, 19(8), 2027–2039.
[15] Dolatyari, A., Ahmady, M., & Kazemi, A. (2024). A Novel Mathematical Model for Modeling Viscosity and Temperature Relationship for Dead Oils. Scientific Reports, 14(1), Article 22836.
[16] Yuan, Q., Luo, Y., Shi, T., et al. (2023). Investigation into the heat transfer models for the hot crude oil transportation in a long-buried pipeline. Energy Science & Engineering, 11, 2169–2184. https://doi.org/10.1002/ese3.1446
[17] White, F. M. (2016). Fluid Mechanics. 8th ed. New York: McGraw-Hill Education.
[18] Gong, F., Zhao, X., Du, C., Zheng, K., Shi, Z., & Wang, H. (2024). Pressure and Temperature Prediction of Oil Pipeline Networks Based on a Mechanism- Data Hybrid Driven Method. Information, 15(11), 709.
[19] Cheng, Q., Zheng, A., Yang, L., Wu, H., Lv, L., & Xie, H. (2018). Studies of the unavoidable exergy loss rate and analysis of influence parameters for pipeline transportation process. Case Studies in Thermal Engineering, 12, 517–527.
[20] Kılkış, B. (2026). Reducing CO₂ Emissions in Heat-Traced Oil Pipelines through Exergy-Based Flow Optimization. Academia Green Energy, 3. https://doi.org/10.20935/AcadEnergy8141
[21] A. Bejan, Advanced Engineering Thermodynamics, 4th ed., John Wiley & Sons, Hoboken, NJ, 2016.
[22] Krichene, E., Hmadi, M. S. A., & Al-Gajamiya, S. K. (2026). A Fair Comparative Framework for Time-Series Forecasting Using ARIMAX, XGBoost, and LSTM: Evidence from Libya. Al-Farooq Journal of Sciences, 2(3), 69-85.
[23] M. J. Moran, H. N. Shapiro, D. D. Boettner, M. B. Bailey, Fundamentals of Engineering Thermodynamics, 8th ed., Hoboken, NJ: John Wiley & Sons, 2016.
