Structural optimization of filament wound composite pipes

doi:10.1007/s11709-022-0868-3

Front. Struct. Civ. Eng.

2022, Vol. 16

Issue (8) : 1056-1069 https://doi.org/10.1007/s11709-022-0868-3

RESEARCH ARTICLE

Structural optimization of filament wound composite pipes

Roham RAFIEE(

), Reza SHAHZADI, Hossein SPERESP

Faculty of New Science and Technologies, University of Tehran, Tehran 1439955171, Iran

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Abstract

An optimization procedure is developed for obtaining optimal structural design of filament wound composite pipes with minimum cost utilized in pressurized water and waste-water pipelines. First, the short-term and long-term design constraints dictated by international standards are identified. Then, proper computational tools are developed for predicting the structural properties of the composite pipes based on the design architecture of layers. The developed computational tools are validated by relying on experimental analysis. Then, an integrated design-optimization process is developed to minimize the price as the main objective, taking into account design requirements and manufacturing limitations as the constraints and treating lay-up sequence, fiber volume fraction, winding angle, and the number of total layers as design variables. The developed method is implemented in various case studies, and the results are presented and discussed.

Keywords composite pipes optimization experimental validation computational modeling filament winding

Corresponding Author(s): Roham RAFIEE

Just Accepted Date: 09 September 2022 Online First Date: 31 October 2022 Issue Date: 02 December 2022

Cite this article:

Roham RAFIEE,Reza SHAHZADI,Hossein SPERESP. Structural optimization of filament wound composite pipes[J]. Front. Struct. Civ. Eng., 2022, 16(8): 1056-1069.

URL:

https://academic.hep.com.cn/fsce/EN/10.1007/s11709-022-0868-3
https://academic.hep.com.cn/fsce/EN/Y2022/V16/I8/1056

Fig.1 Workflow of the research.

Fig.2 Measuring (a) HTS; (b) LTS; (c) pipe stiffness and (d) failure pressure.

Tab.1 Mechanical properties of glass fiber, polyester resin and sand

Tab.2 Comparing estimated HTS and LTS with experimental observations

Tab.3 Comparing estimated stiffness with experimental observations

Tab.4 Comparing failure pressure with experimental observations

scope	definition
objective design constraints	minimizing total wall thickness (t_hoop + t_cross + t_core)
	(HTS, LTS) $≥$ values in Ref. [28] based on DN and PN
	P_F $≥$ 2.C_PL·PN
	PS $?$ C_SL·SN
manufacturing constraints	θ ∈ [50°, 70°]
	W_f = [73%, 77%]
	V_s = [45%, 55%]
	total wall thickness $?$ 6 mm
design variables	1) No. of hoop layers (p); 2) No. of cross layers (q); 3) winding angle (θ); 4) mass of sand (m_s); 5) lay-up sequence
input parameters by user	mechanical properties of fiber, resin and sand
	DN-PN-SN
	C_PL and C_SL

Tab.5 Overview of optimization problem

Fig.3 Description of optimization scenarios for the verification purpose.

Tab.6 Outputs of optimization procedure for different scenarios

Fig.4 Outputs of optimization for the scenario “A”. (a) LTS and HTS; (b) pipe stiffness.

Fig.5 Outputs of optimization for the scenario “B”. (a) LTS and HTS; (b) pipe stiffness.

Fig.6 Outputs of optimization for the scenario “C”.

Fig.7 Comparing variations of thickness versus winding angle for different fiber weight fraction as the output of optimization for {600-16-1000} GFRP pipes with (a) 6 and (b) 7 layers.

1	S Nikbakt, S Kamarian, M Shakeri. A review on optimization of composite structures Part I: Laminated composites. Composite Structures, 2018, 195: 158–185 https://doi.org/10.1016/j.compstruct.2018.03.063
2	G Pan, J Lu, K Shen, J Ke. Optimization of composite cylindrical shell subjected to hydrostatic pressure. In: International Conference on Intelligent Robotics and Applications. Cham: Springer, 2015, 81–90
3	A A Smerdov. A computational study in optimum formulations of optimization problems on laminated cylindrical shells for buckling I. Shells under axial compression. Composites Science and Technology, 2000, 60(11): 2057–2066 https://doi.org/10.1016/S0266-3538(00)00102-0
4	C G Diaconu, M Sato, H Sekine. Buckling characteristics and layup optimization of long laminated composite cylindrical shells subjected to combined loads using lamination parameters. Composite Structures, 2002, 58(4): 423–433 https://doi.org/10.1016/S0263-8223(02)00130-7
5	J P Foldager, J S Hansen, N Olhoff. Optimization of the buckling load for composite structures taking thermal effects into account. Structural and Multidisciplinary Optimization, 2001, 21(1): 14–31 https://doi.org/10.1007/s001580050164
6	F X Irisarri, M M Abdalla, Z Gürdal. Improved Shepard’s method for the optimization of composite structures. AIAA Journal, 2011, 49(12): 2726–2736 https://doi.org/10.2514/1.J051109
7	M Abouhamze, M Shakeri. Multi-objective stacking sequence optimization of laminated cylindrical panels using a genetic algorithm and neural networks. Composite Structures, 2007, 81(2): 253–263 https://doi.org/10.1016/j.compstruct.2006.08.015
8	B Kriegesmann, R Rolfes, E L Jansen, I Elishakoff, C Hühne, A Kling. Design optimization of composite cylindrical shells under uncertainty. Computers, Materials & Continua, 2012, 32(3): 177–200
9	M Rouhi, H Ghayoor, S V Hoa, M Hojjati. Computational efficiency and accuracy of multi-step design optimization method for variable stiffness composite structures. Thin-walled Structures, 2017, 113: 136–143 https://doi.org/10.1016/j.tws.2017.01.019
10	U Topal. Multiobjective optimization of laminated composite cylindrical shells for maximum frequency and buckling load. Materials & Design, 2009, 30(7): 2584–2594 https://doi.org/10.1016/j.matdes.2008.09.020
11	Z Wang, J H S Jr Almeida, L St-Pierre, Z Wang, S G P Castro. Reliability-based buckling optimization with an accelerated Kriging metamodel for filament-wound variable angle tow composite cylinders. Composite Structures, 2020, 254: 112821 https://doi.org/10.1016/j.compstruct.2020.112821
12	Salim M., Bodaghi M., Kamarian S., Shakeri M.. Free vibration analysis and design optimization of SMA/Graphite/Epoxy composite shells in thermal environments. Latin American Journal of Solids and Structures, 2018, 15(1): 1–16
13	S Adali, M Walker, V E Verijenko. Multiobjective optimization of laminated plates for maximum prebuckling, buckling and postbucklikng strength using continuous and discrerte ply angles. Composite Structures, 1996, 35(1): 117–130
14	E Ameri, M M Aghdam, M Shakeri. Global optimization of laminated cylindrical panels based on fundamental natural frequencies. Composite Structures, 2012, 94(9): 2697–2705 https://doi.org/10.1016/j.compstruct.2012.04.005
15	Y Ohta. Genetic algorithms for optimization of laminated composite cylindrical shells. In: 8th Symposium on Multidisciplinary Analysis and Optimization. Long Beach, CA: AIAA, 4939
16	Y Ohta. Optimal stacking sequence for nonlinear vibration of laminated composite circular cylindrical shells. In: 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 18th AIAA/ASME/AHS Adaptive Structures Conference. Orlando, FL: AIAA, 2010, 2882
17	M H Yas, M Shakeri, N Khaksar. Stacking sequence optimization of a composite cylindrical shell for vibrations by hybrid continuous optimization. Proceedings of the Institution of Mechanical Engineers. Part C, Journal of Mechanical Engineering Science, 2008, 222(12): 2385–2394 https://doi.org/10.1243/09544062JMES900
18	M A Luersen, C A Steeves, P B Nair. Curved fiber paths optimization of a composite cylindrical shell via Kriging-based approach. Journal of Composite Materials, 2015, 49(29): 3583–3597 https://doi.org/10.1177/0021998314568168
19	M Shakeri, M H Yas, M G Gol. Optimal stacking sequence of laminated cylindrical shells using genetic algorithm. Mechanics of Advanced Materials and Structures, 2005, 12(4): 305–312 https://doi.org/10.1080/15376490590898501
20	I P CorreiaP G MartinsC M SoaresC M SoaresJ Herskovits. Modelling and optimization of laminated adaptive shells of revolution. Composite Structures, 2006, 75(1−4): 49−59
21	N Minsch, F H Herrmann, T Gereke, A Nocke, C Cherif. Analysis of filament winding processes and potential equipment technologies. Procedia CIRP, 2017, 66: 125–130 https://doi.org/10.1016/j.procir.2017.03.284
22	C Colombo, L Vergani. Optimization of filament winding parameters for the design of a composite pipe. Composites. Part B, Engineering, 2018, 148: 207–216 https://doi.org/10.1016/j.compositesb.2018.04.056
23	N J Jin, H G Hwang, J H Yeon. Structural analysis and optimum design of GRP pipes based on properties of materials. Construction & Building Materials, 2013, 38: 316–326 https://doi.org/10.1016/j.conbuildmat.2012.07.115
24	J H S Jr Almeida, M L Ribeiro, V Tita, S C Amico. Stacking sequence optimization in composite tubes under internal pressure based on genetic algorithm accounting for progressive damage. Composite Structures, 2017, 178: 20–26 https://doi.org/10.1016/j.compstruct.2017.07.054
25	C Liu, Y Shi. Design optimization for filament wound cylindrical composite internal pressure vessels considering process-induced residual stresses. Composite Structures, 2020, 235: 111755 https://doi.org/10.1016/j.compstruct.2019.111755
26	Z Zhang, S Hou, Q Liu, X Han. Winding orientation optimization design of composite tubes based on quasistatic and dynamic experiments. Thin-walled Structures, 2018, 127: 425–433 https://doi.org/10.1016/j.tws.2017.11.052
27	V Alcántar, S Ledesma, S M Aceves, E Ledesma, A Saldana. Optimization of type III pressure vessels using genetic algorithm and simulated annealing. International Journal of Hydrogen Energy, 2017, 42(31): 20125–20132 https://doi.org/10.1016/j.ijhydene.2017.06.146
28	C950-01 ANSI/AWWA. Standard for Fiberglass Pressure Pipe. Denver: American Water Works Association, 2001
29	R F Gibson. Principles of Composite Material Mechanics. 2nd ed. Boca Raton, FL: CRC Press, 2007
30	D K Roylance. Netting Analysis for Filament-wound Pressure Vessels. Watertown, MA: Army Materials and Mechanics Research Center, 1976
31	D2105-01 ASTM. Standard Test Method for Longitudinal Tensile Properties of Fiberglass (glass Fiber Reinforced Thermosetting Resin) Pipe and Tube. West Conshohocken, PA: ASTM, 2001
32	D2290-00 ASTM. Standard Test Method for Apparent Hoop Tensile Strength of Plastic or Reinforced Plastic Pipe by Split Disc Method. West Conshohocken, PA: ASTM, 2000
33	D1599-99 ASTM. Standard Test Method for Resistance to Short-time Hydraulic Pressure of Plastic Pipes, Tubing, and Fittings. West Conshohocken, PA: ASTM, 1999
34	D2412-02 ASTM. Standard Test Method for Determination of External Loading Characteristics of Plastic Pipe by Parallel-plate Loading. West Conshohocken, PA: ASTM, 2002
35	D3171-15 ASTM. Standard Test Method for Constituent Content of Composite Materials. West Conshohocken, PA: ASTM, 2015
36	D2992-06 ASTM. Standard Practice for Obtaining Hydrostatic or Pressure Design Basis for Fiberglass Pipe and Fitting. West Conshohocken, PA: ASTM, 2006
37	10468 ISO. Glass-reinforced Thermosetting Plastics (GRP) Pipes—Determination of the Ring Creep Properties Under Wet or Dry Condition. Genewa: ISO, 2018
38	R Rafiee, A Ghorbanhosseini. Developing a micro-macro mechanical approach for evaluating long-term creep in composite cylinders. Thin-walled Structures, 2020, 151: 106714 https://doi.org/10.1016/j.tws.2020.106714
39	R RafieeA Ghorbanhosseini. Experimental and theoretical investigations of creep on a composite pipe under compressive transverse loading. Fibers and Polymers, 2021, 22(1):222–230
40	R Rafiee, A Ghorbanhosseini. Analyzing the long-term creep behavior of composite pipes: Developing an alternative scenario of short-term multi-stage loading test. Composite Structures, 2020, 254: 112868 https://doi.org/10.1016/j.compstruct.2020.112868
41	R Rafiee, B Mazhari. Simulation of long-term hydrostatic tests on glass fiber reinforced plastic pipes. Composite Structures, 2016, 136: 56–63
42	R Rafiee, B Mazhari. Evaluating long-term performance of glass fiber reinforced plastic pipes subjected to internal pressure. Construction & Building Materials, 2016, 122: 694–701 https://doi.org/10.1016/j.conbuildmat.2016.06.103
43	A M Shaaban, C Anitescu, E Atroshchenko, T Rabczuk. An isogeometric Burton-Miller method for the transmission loss optimization with application to mufflers with internal extended tubes. Applied Acoustics, 2022, 185: 108410 https://doi.org/10.1016/j.apacoust.2021.108410
44	A M Shaaban, C Anitescu, E Atroshchenko, T Rabczuk. 3D isogeometric boundary element analysis and structural shape optimization for Helmholtz acoustic scattering problems. Computer Methods in Applied Mechanics and Engineering, 2021, 384: 113950 https://doi.org/10.1016/j.cma.2021.113950
45	A M Shaaban, C Anitescu, E Atroshchenko, T Rabczuk. Isogeometric boundary element analysis and shape optimization by PSO for 3D axi-symmetric high frequency Helmholtz acoustic problems. Journal of Sound and Vibration, 2020, 486: 115598 https://doi.org/10.1016/j.jsv.2020.115598
46	A M Shaaban, C Anitescu, E Atroshchenko, T Rabczuk. Shape optimization by conventional and extended isogeometric boundary element method with PSO for two-dimensional Helmholtz acoustic problems. Engineering Analysis with Boundary Elements, 2020, 113: 156–169 https://doi.org/10.1016/j.enganabound.2019.12.012
47	H Ghasemi, H S Park, T Rabczuk. A multi-material level set-based topology optimization of flexoelectric composites. Computer Methods in Applied Mechanics and Engineering, 2018, 332: 47–62 https://doi.org/10.1016/j.cma.2017.12.005
48	H Ghasemi, H S Park, T Rabczuk. A level-set based IGA formulation for topology optimization of flexoelectric materials. Computer Methods in Applied Mechanics and Engineering, 2017, 313: 239–258 https://doi.org/10.1016/j.cma.2016.09.029

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