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Accueil Tous les numéros Volume 75 (2020) Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles, 75 (2020) 86 Références
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Numéro
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 75, 2020
Numéro d'article 86
Nombre de pages 16
DOI https://doi.org/10.2516/ogst/2020076
Publié en ligne 27 novembre 2020
  • Brentner K.S., Farassat F. (1998) Analytical comparison of the acoustic analogy and Kirchhoff formulation for moving surfaces, AIAA J. 360, 8, 1379–1386. https://doi.org/10.2514/2.558. [CrossRef] [Google Scholar]
  • Bai H. (2020) Mechanism analysis, anti-corrosion techniques and numerical modeling of corrosion in energy industry, Oil Gas Sci. Technol. - Rev IFP Energies nouvelles 75, 42. [CrossRef] [Google Scholar]
  • Shi J., Al-Durra A., Matraji I., Al-Wahedi K., Abou-Khousa M. (2019) Application of Particle Swarm Optimization (PSO) algorithm for Black Powder (BP) source identification in gas pipeline network based on 1-D model, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 74, 47. [CrossRef] [Google Scholar]
  • Su H., Zio E., Zhang J., Yang Z., Li X., Zhang Z. (2018) A systematic hybrid method for real-time prediction of system conditions in natural gas pipeline networks, J. Nat. Gas Sci. Eng. 57, 31–44. [CrossRef] [Google Scholar]
  • Sanaye S., Mahmoudimehr J. (2012) Technical assessment of isothermal and non-isothermal modelings of natural gas pipeline operational conditions, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 3, 435–449. [CrossRef] [Google Scholar]
  • Qiao W., Huang K., Azimi M., Han S. (2019) A novel hybrid prediction model for hourly gas consumption in supply side based on improved whale optimization algorithm and relevance vector machine, IEEE Access 7, 88218–88230. [CrossRef] [Google Scholar]
  • Wang P., Yu B., Deng Y., Zhao Y. (2015) Comparison study on the accuracy and efficiency of the four forms of hydraulic equation of a natural gas pipeline based on linearized solution, J. Nat. Gas Sci. Eng. 22, 235–244. [CrossRef] [Google Scholar]
  • Bagajewicz M., Valtinson G. (2014) Computation of natural gas pipeline hydraulics, Ind. Eng. Chem. Res. 53, 26, 10707–10720. [CrossRef] [Google Scholar]
  • Streeter V.L., Wylie E.B. (1970) Natural gas pipeline transients, Soc. Pet. Eng. J. 10, 04, 357–364. [CrossRef] [Google Scholar]
  • Osiadacz A.J. (1996) Different transient flow models-limitations, advantages, and disadvantages, in: PSIG Annual Meeting, PSIG-9606, San Francisco, California. [Google Scholar]
  • Yow W. (1971) Analysis and control of transient flow in natural gas piping systems. http://hdl.handle.net/2027.42/8473. [Google Scholar]
  • Osiadacz A. (1984) Simulation of transient gas flows in networks, Int. J. Numer. Meth. Fl. 4, 1, 13–24. [CrossRef] [Google Scholar]
  • Wylie E.B., Stoner M.A., Streeter V.L. (1971) Network: System transient calculations by implicit method, Soc. Pet. Eng. J. 11, 04, 356–362. [CrossRef] [Google Scholar]
  • Luongo C.A. (1986) An efficient program for transient flow simulation in natural gas pipelines, in: PSIG Annual Meeting, PSIG-8605, New Orleans, Louisiana. [Google Scholar]
  • Behbahani-Nejad M., Shekari Y. (2008) Reduced order modeling of natural gas transient flow in pipelines, Int. J. Eng. Appl. Sci. 5, 7, 148–152. [Google Scholar]
  • Wang P., Yu B., Han D., Li J., Sun D., Xiang Y., Wang L. (2018) Adaptive implicit finite difference method for natural gas pipeline transient flow, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 73, 21. [CrossRef] [Google Scholar]
  • Wang P., Yu B., Han D., Sun D., Xiang Y. (2018) Fast method for the hydraulic simulation of natural gas pipeline networks based on the divide-and-conquer approach, J. Nat. Gas Sci. Eng. 50, 55–63. [CrossRef] [Google Scholar]
  • Wang P., Ao S., Yu B., Han D. (2019) An efficiently decoupled implicit method for complex natural gas pipeline network simulation, Energies 12, 8, 1516. [CrossRef] [Google Scholar]
  • Thibault J.C. (2009) Implementation of a Cartesian grid incompressible Navier-Stokes solver on multi-GPU desktop platforms using CUDA, Boise State University, Boise, Idaho. [Google Scholar]
  • Lacasta A., Morales-Hernández M., Murillo J., García-Navarro P. (2014) An optimized GPU implementation of a 2D free surface simulation model on unstructured meshes, Adv. Eng. Softw. 78, 1–15. [CrossRef] [Google Scholar]
  • Tölke J., Krafczyk M. (2008) TeraFLOP computing on a desktop PC with GPUs for 3D CFD, Int. J. Comput. Fluid. D. 22, 7, 443–456. [CrossRef] [Google Scholar]
  • Michalakes J., Vachharajani M. (2008) GPU acceleration of numerical weather prediction, Parallel Process. Lett. 18, 04, 531–548. [CrossRef] [Google Scholar]
  • Acuña M., Aoki T. (2009) Real-time tsunami simulation on multi-node GPU cluster, in: ACM/IEEE Conference on Supercomputing. [Google Scholar]
  • Lu X., Han B., Hori M., Xiong C., Xu Z. (2014) A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing, Adv. Eng. Softw. 70, 90–103. [CrossRef] [Google Scholar]
  • Cai Y., Li G., Wang H., Zheng G., Lin S. (2012) Development of parallel explicit finite element sheet forming simulation system based on GPU architecture, Adv. Eng. Softw. 45, 1, 370–379. [CrossRef] [Google Scholar]
  • Zheng J., Song F., Chen G. (2011) Development of RealPipe-Gas simulation software for gas pipeline network, Oil Gas Storage Transp. 30, 9, 659–662. (in Chinese). [Google Scholar]
  • Luskin M. (1979) An approximation procedure for nonsymmetric, nonlinear hyperbolic systems with integral boundary conditions, Siam J. Numer. Anal. 16, 1, 145–164. [CrossRef] [Google Scholar]
  • Kiuchi T. (1994) An implicit method for transient gas flows in pipe networks, Int. J. Heat. Fluid Fl. 15, 5, 378–383. [CrossRef] [Google Scholar]
  • Abbaspour M., Chapman K.S. (2008) Nonisothermal transient flow in natural gas pipeline, J. Appl. Fluid Mech. 75, 3, 519–525. [Google Scholar]
  • Zhang T., Li Y., Li Y., Sun S., Gao X. (2020) A self-adaptive deep learning algorithm for accelerating multi-component flash calculation, Comput. Method. Appl. M. 369, 113207. [CrossRef] [Google Scholar]
  • Li R., Saad Y. (2013) GPU-accelerated preconditioned iterative linear solvers, J. Supercomput. 63, 2, 443–466. [CrossRef] [Google Scholar]
  • Hockney R.W., Jesshope C.R. (2019) Parallel computers 2: Architecture, programming and algorithms, CRC Press, Boca Raton, FL. [CrossRef] [Google Scholar]
  • Harris M. (2013) How to access global memory efficiently in CUDA C/C++ kernels. http://devblogs.nvidia.com/parallelforall/how-access-global-memory-efficientlycuda-c-kernels. [Google Scholar]
  • Yu B., Wang P., Wang L., Xiang Y. (2017) A simulation method for natural gas pipeline networks based on the divide-and-conquer concept, Oil Gas Storage Transp. 36, 1, 75–84. (in Chinese). [Google Scholar]

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