Advances in aircraft and spacecraft science

  • 제5권4호
  • /
  • Pages.499-513
  • /
  • 2018
  • /
  • 2287-528X(pISSN)
  • /
  • 2287-5271(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Monitoring the water absorption in GFRE pipes via an electrical capacitance sensors

  • Altabey, Wael A. (International Institute for Urban Systems Engineering, Southeast University) ;
  • Noori, Mohammad (International Institute for Urban Systems Engineering, Southeast University)
  • 투고 : 2017.07.20
  • 심사 : 2018.05.24
  • 발행 : 2018.07.25
⟨ 이전 논문 다음 논문 ⟩

초록

One of the major problems in glass fiber reinforced epoxy (GFRE) composite pipes is the durability under water absorption. This condition is generally recognized to cause degradations in strength and mechanical properties. Therefore, there is a need for an intelligent system for detecting the absorption rate and computing the mass of water absorption (M%) as a function of absorption time (t). The present work represents a new non-destructive evaluation (NDE) technique for detecting the water absorption rate by evaluating the dielectric properties of glass fiber and epoxy resin composite pipes subjected to internal hydrostatic pressure at room temperature. The variation in the dielectric signatures is employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such defects. ECS consists of twelve electrodes mounted on the outer surface of the pipe. Radius-electrode ratio is defined as the ratio of inner and outer radius of pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes on the basis of water absorption rate in the pipe material as a function of absorption time. The arrangements for positioning12-electrode sensor parameters such as capacitance, capacitance change and change rate of capacitance are analyzed by ANSYS and MATLAB to plot the mass of water absorption curve against absorption time (t). An analytical model based on a Fickian diffusion model is conducted to predict the saturation level of water absorption ($M_S$) from the obtained mass of water absorption curve. The FE results are in excellent agreement with the analytical results and experimental results available in the literature, thus, validating the accuracy and reliability of the proposed expert system.

키워드

참고문헌

  1. Abouelwafa, M.N., El-Gamal, H.A., Mohamed, Y.S. and Al-Tabey, W.A. (2014), "An expert system for life prediction of woven-roving GFRE closed end thick tube subjected to combined bending moments and internal hydrostatic pressure using artificial neural network", J. Adv. Mater. Res., 845, 12-17.
  2. Agari, Y., Anan, Y., Nomura, R. and Kawasaki, Y. (2007), "Estimation of the compositional gradient in a PVC/PMMA graded blend prepared by the dissolution-diffusion method", Polym., 48(4), 1139-1147. https://doi.org/10.1016/j.polymer.2006.11.064
  3. Al-Tabey, W.A. (2012), Finite Element Analysis in Mechanical Design Using ANSYS: Finite Element Analysis (FEA) Hand Book for Mechanical Engineers with ANSYS Tutorials, LAP Lambert Academic Publishing, Germany.
  4. Altabey, W.A. and Noori, M. (2017), "An extensive overview of lamb wave technique for detecting fatigue damage in composite structures", J. Ind. Syst. Eng., 2(1), 1-20.
  5. Altabey, W.A. and Noori, M. (2017), "Detection of fatigue crack in basalt FRP laminate composite pipe using electrical potential change method", 12th International Conference on Damage Assessment of Structures, IOP Conf. Series: J. Physics, 842(1), 012079, Japan, July.
  6. Altabey, W.A. and Noori, M. (2018), "Fatigue life prediction for carbon fiber/epoxy laminate composites under spectrum loading using two different neural network architectures", J. Sustain. Mater. Struct. Syst., 3(1), 53-78.
  7. Altabey, W.A. (2010), "Effect of pipeline filling material on electrical capacitance tomography", Proceedings of the International Postgraduate Conference on Engineering (IPCE 2010), Perlis, Malaysia, October 16-17.
  8. Altabey, W.A. (2015), "The fatigue behavior of woven-roving glass fiber reinforced epoxy under combined bending moments and internal hydrostatic pressure", Ph.D. Dissertation, Alexandria University, Egypt.
  9. Altabey, W.A. (2016), "The thermal effect on electrical capacitance sensor for two-phase flow monitoring", J. Struct. Monitor. Maintenance, 3(4), 335-347. https://doi.org/10.12989/smm.2016.3.4.335
  10. Altabey, W.A. (2016a), "Detecting and predicting the crude oil type inside composite pipes using ECS and ANN", J. Struct. Monitor. Maintenance, 3(4), 377-393. https://doi.org/10.12989/smm.2016.3.4.377
  11. Altabey, W.A. (2016b), "FE and ANN model of ECS to simulate the pipelines suffer from internal corrosion", J. Struct. Monitor. Maintenance, 3(3), 297-314. https://doi.org/10.12989/smm.2016.3.3.297
  12. Altabey, W.A. (2017a), "EPC method for delamination assessment of basalt FRP pipe: Electrodes number effect", J. Struct. Monitor. Maintenance, 4(1), 69-84. https://doi.org/10.12989/smm.2017.4.1.069
  13. Altabey, W.A. (2017b), "Delamination evaluation on basalt FRP composite pipe by electrical potential change", J. Adv. Aircraft Spacecraft Sci., 4(5), 515-528.
  14. Altabey, W.A., Noori, M. and Wang, L. (2018a), Using ANSYS for Finite Element Analysis: A Tutorial for Engineers, Volume I, Momentum Press, New York, U.S.A.
  15. Altabey, W.A., Noori, M. and Wang, L. (2018b), Using ANSYS for Finite Element Analysis: Dynamic, Probabilistic, Design and Heat, Transfer Analysis, Volume II, Momentum Press, New York, U.S.A.
  16. ANSYS, Inc. (2014), ANSYS Low-Frequency Electromagnetic analysis Guide, The Electrostatic Module in the Electromagnetic subsection of ANSYS, ANSYS, Inc., U.S.A.
  17. Asencio, K., Bramer-Escamilla, W., Gutierrez, G. and Sanchez, I. (2015), "Electrical capacitance sensor array to measure density profiles of a vibrated granular bed", J. Powder Technol., 270, 10-19. https://doi.org/10.1016/j.powtec.2014.10.003
  18. Athijayamani, A., Thiruchitrambalam, M., Natarajan, U. and Pazhanivel, B. (2009), "Effect of moisture absorption on the mechanical properties of randomly oriented natural fibers/polyester hybrid composite", J. Mater. Sci. Eng. A, 517(1-2), 344-353. https://doi.org/10.1016/j.msea.2009.04.027
  19. d'Almeida, J.R.M., de Almeida, R.C. and de Lima, W.R. (2008), "Effect of water absorption of the mechanical behavior of fiberglass pipes used for offshore service waters", J. Compos. Struct., 83(2), 221-225. https://doi.org/10.1016/j.compstruct.2007.04.020
  20. Daoye, Y., Bin, Z., Chuanlong, X., Guanghua, T. and Shimin, W. (2009), "Effect of pipeline thickness on electrical capacitance tomography", Proceedings of the 6th International Symposium on Measurement Techniques for Multiphase Flows, J. Phys: Conference Series, 147, 1-13.
  21. Ellyin, F. and Maser, R. (2004), "Environmental effects on the mechanical properties of glass-fiber epoxy composite tubular specimens", J. Compos. Sci. Technol., 64(12), 1863-1874. https://doi.org/10.1016/j.compscitech.2004.01.017
  22. Fasching, G.E. and Smith, N.S. (1988), "High resolution capacitance imaging system", DOE/METC-88/4083; US Dept. Energy, U.S.A.
  23. Fasching, G.E. and Smith, N.S. (1991), "A capacitive system for 3-Dimensional imaging of fluidized-beds", Rev. Sci. Instr., 62(9), 2243-2251. https://doi.org/10.1063/1.1142343
  24. Jaworski, A.J. and Bolton, G.T. (2000), "The design of an electrical capacitance tomography sensor for use with media of high dielectric permittivity", Measurement Sci. Technol., 11(6), 743-757. https://doi.org/10.1088/0957-0233/11/6/318
  25. Komai, K., Minoshima, K., Shibutai, T. and Nomura, T. (1989), "The influence of water on the mechanical properties and fatigue strength of angle-ply carbon/epoxy composites", JSME Int. J. Series. 1, Solid Mechanics, Strength of Materials, 32(4), 588-595. https://doi.org/10.1299/jsmea1988.32.4_588
  26. Li, H. and Huang, Z. (2000), Special Measurement Technology and Application, Zhejiang University Press, Hangzhou, China.
  27. Lundgren, J.E. and Gudmundson, P. (1994), "Moisture absorption in glass-fibre/epoxy laminates with transverse matrix cracks", J. Compos. Sci. Technol., 59(13), 1983-1991.
  28. Maggana, C. and Pissis, P. (1999), "Water sorption and diffusion studies in an epoxy resin system", J. Polym Sci., Part B: Polym Phys., 37(11), 1165-1182. https://doi.org/10.1002/(SICI)1099-0488(19990601)37:11<1165::AID-POLB11>3.0.CO;2-E
  29. McKague, Jr. E.L., Reynolds, J.D. and Halkias, J.E. (1976), "Moisture diffusion in fiber reinforced plastics", J. Eng. Mater. Technol., 98(1), 92-95. https://doi.org/10.1115/1.3443342
  30. Mohamad, E.J., Rahim, R.A., Leow, P.L., Fazalul, Rahiman, M.H., Marwah, O.M.F., Nor Ayob, N.M., Rahim, H.A. and Mohd Yunus, F.R. (2012), "An introduction of two differential excitation potentials technique in electrical capacitance tomography", J. Sensors Actuators A, 180, 1-10 https://doi.org/10.1016/j.sna.2012.03.025
  31. Mohamad, E.J., Rahim, R.A., Rahiman, M.H.F., Ameran, H.L.M., Muji, S.Z.M. and Marwah, O.M.F. (2016), "Measurement and analysis of water/oil multiphase flow using Electrical Capacitance Tomography sensor", J. Flow Measurement Instrumentation, 47, 62-70. https://doi.org/10.1016/j.flowmeasinst.2015.12.004
  32. Pei, T. and Wang, W. (2009), "Simulation analysis of sensitivity for electrical capacitance tomography", Proceedings of 9th International Conference on Electronic Measurement and Instruments (ICEMI 2009), Beijing, China, August.
  33. Perreux, D. and Suri, C. (1997), "A study of a coupling between the phenomena of water absorption and damage in glass/epoxy composite pipe", J. Compos. Sci. Technol., 57(9-10), 1403-1413. https://doi.org/10.1016/S0266-3538(97)00076-6
  34. Peyser, P. and Bascom, W.B. (1981), "The anomalous lowering of the glass transition of an epoxy resin by plasticization with water", J. Mater Sci., 16(1), 75-82. https://doi.org/10.1007/BF00552061
  35. Prian, L. and Barkatt, A. (1999), "Degradation mechanism of fiber-reinforced plastics and its implications to prediction of long-term behavior", J. Mater. Sci., 34(16), 3977-3989. https://doi.org/10.1023/A:1004647511910
  36. Sardeshpande, M.V., Harinarayan, S. and Ranade, V.V. (2015), "Void fraction measurement using electrical capacitance tomography and high speed photography", J. Chem. Eng. Res. Design, 9(4), 1-11.
  37. Springer, G.S. (1981), "Environmental effects", Environmental Effects on Composite Materials, Volume 3, Technomic Pub. Co., Lancaster, United Kingdom.
  38. Xie, C.G., Huang, S.M., Hoyle, B.S., Thorn, R., Lenn, C., Snowden, D. and Beck, M.S. (1992), "Electrical capacitance tomography for flow imaging: System model for development of image reconstruction algorithms and design of primary sensors", IEEE Proceedings-G (Circuits, Devices and Systems), 139(1), 89-98. https://doi.org/10.1049/ip-g-2.1992.0015
  39. Yang, W.Q., Stott, A.L., Beck, M.S. and Xie, C.G. (1995a), "Development of capacitance tomographic imaging systems for oil pipeline measurements", Rev. Sci. Instruments, 66(8), 4326. https://doi.org/10.1063/1.1145322
  40. Yang, W.Q., Beck, M.S. and Byars, M. (1995b), "Electrical capacitance tomography-from design to applications", Measurement Control, 28(9), 261-266 https://doi.org/10.1177/002029409502800901
  41. Zamri, M.H., Akil, H.M., Abu Bakar, A., Ishak, Z.A.M. and Wei Cheng, L. (2011), "Effect of water absorption on pultruded jute/glass fiber-reinforced unsaturated polyester hybrid composites", J. Compos. Mater., 46(1), 51-56. https://doi.org/10.1177/0021998311410488
  42. Zhang, W., Wang, C., Yang, W. and Wang, C. (2014), "Application of electrical capacitance tomography in particulate process measurement-A review", J. Adv. Powder Technol., 25(1), 174-188. https://doi.org/10.1016/j.apt.2013.12.003
  43. Zhao, Y., Noori, M., Altabey, W.A. and Wu, Z. (2018), "Fatigue damage identification for composite pipeline systems using electrical capacitance sensors", J. Smart Mater. Struct., doi.org/10.1088/1361-665X/aacc99.

피인용 문헌

  1. Deep Learning-Based Damage, Load and Support Identification for a Composite Pipeline by Extracting Modal Macro Strains from Dynamic Excitations vol.8, pp.12, 2018, https://doi.org/10.3390/app8122564
  2. A Comparison of Three Different Methods for the Identification of Hysterically Degrading Structures Using BWBN Model vol.4, pp.None, 2018, https://doi.org/10.3389/fbuil.2018.00080
  3. Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling vol.11, pp.13, 2018, https://doi.org/10.3390/app11136063