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All issues Volume 21 / No 4 (2020) Mechanics & Industry, 21 4 (2020) 402 References
Open Access
Issue
Mechanics & Industry
Volume 21, Number 4, 2020
Article Number 402
Number of page(s) 14
DOI https://doi.org/10.1051/meca/2019086
Published online 06 May 2020
  1. C. Wang, Y. Han, S. Wang, Pressure control of rotary accumulator, Int. Conf. Fluid Power Mechatron. 14, 1395–1398 (2015) [Google Scholar]
  2. V.E. Geller, Characteristic features of necking during drawing and ultrahigh-speed spinning of polyethylene phthalate yarns, Review, Fibre Chem. 48, 1–11 (2016) [CrossRef] [Google Scholar]
  3. Z.X. Li, X.D. Shu, Numerical and experimental analysis on multi-pass conventional spinning of the cylindrical part with GH3030, Int. J. Adv. Manuf. Technol. 103, 2893–2901 (2019) [Google Scholar]
  4. H. Wu, W.C. Xu, D.B. Shan, Mechanism of increasing spinnability by multi-pass spinning forming − Analysis of damage evolution using a modified GTN model, Int. J. Mech. Sci. 159, 1–19 (2019) [CrossRef] [Google Scholar]
  5. B. Sun, J. Guo, Y. Lei, Simulation and verification of a non-equilibrium thermodynamic model for a steam catapult's steam accumulator, Int. J. Heat Mass Transf. 85, 88–97 (2015) [Google Scholar]
  6. R. Tomisawa, T. Ikaga, K.H. Kim, et al., Effect of melt spinning conditions on the fiber structure development of polyethylene terephthalate, Polymer 116, 367–377 (2016) [Google Scholar]
  7. Q.H. Su, F. Peng, J. Xing, Experimental research on advanced accumulator, Yuanzineng Kexue Jishu/At. Energy Sci. Technol. 51, 636–640 (2017) [Google Scholar]
  8. W. Latas, J. Stojek, A new type of hydrokinetic accumulator and its simulation in hydraulic lift with energy recovery system, Energy 153, 836–848 (2018) [CrossRef] [Google Scholar]
  9. H. Kadakia, A. Baker, M. Paulsen, A mechanistic accumulator model for RETRAN-3D, Nucl. Technol. 202, 71–80 (2018) [Google Scholar]
  10. B. Ryszard, B. Zbigniew, H.S. Anna, Methodology and a continuous time mathematical model for selecting the optimum capacity of a heat accumulator integrated with a CHP plant, Energies 11, 1240 (2018) [Google Scholar]
  11. I. Victor, S.A. Casper, Hydraulic pitch control system for wind turbines: Advanced modeling and verification of an hydraulic accumulator, Simul. Model. Pract. Theory. 79, 1–22 (2017) [Google Scholar]
  12. S.M. Ostroumov, Choice and optimization of parameters of a transpiration cooling accumulator, Inzhenerno-Fizicheskii Zhurnal 60, 918–922 (1991) [Google Scholar]
  13. J. Lee, U.Y. Lee, Design optimization of an accumulator for reducing rotary compressor noise, Proc. Inst. Mech. Eng. 226, 285–296 (2012) [CrossRef] [Google Scholar]
  14. J.Z. Hui, Y.K. Yang, H.Y. Zhang, Braking energy recovery system and control optimization of excavator based on accumulator, Chin. J. Highway Transp. 29, 143–151 (2016) [Google Scholar]
  15. M. Yu, B.Q. Shi, Optimization design and robust analysis of accumulator in hydraulic brake system, Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agri. Eng. 27, 132–136 (2011) [Google Scholar]
  16. Q.D. Zhu, P. Lu, Z.B. Yang, Multi-parameter optimization for the wet steam accumulator of a steam-powered catapult, Energies 12, 234 (2019) [Google Scholar]
  17. A. Hashemi, M.H. Gollo, Application of a new integrated optimization approach in sheet hydroforming process, Mech. Ind. 19, 303 (2018) [CrossRef] [Google Scholar]
  18. U.Y. Lee, B.J. Kim, J.B. Lee, Design optimization of an accumulator for noise reduction of rotary compressor, Trans. Korean Soc. Mech. Eng. 35, 759–766 (2011) [CrossRef] [Google Scholar]
  19. Q.J. Chen, Z.X. Xu, X.H. Yue, Characteristic modeling and parameter optimization of the accumulator in hydraulic power take-off system for wave power generation, Yingyong Jichu yu Gongcheng Kexue Xuebao/J. Basic Sci. Eng. 27, 226–237 (2019) [Google Scholar]
  20. Y.C. Lin, S.S. Qian, X.M. Chen, Staggered spinning of thin-walled Hastelloy C-276 cylindrical parts: Numerical simulation and experimental investigation, Thin-Walled Struct. 140, 466–476 (2019) [CrossRef] [Google Scholar]
  21. M. Li, Y.Y. Xu, H. Li, A novel spinning process for simultaneously producing two cone parts with big angle, J. Chin. Inst. Eng. 41, 547–556 (2018) [CrossRef] [Google Scholar]
  22. S. Mohammad, J. Iraj, K.N. Mehdi, Experimental study and FEM analysis of forward hot dieless spinning, Mech. Ind. 19, 404 (2018) [CrossRef] [Google Scholar]
  23. T. Yoichi, K. Shigefumi, N. Takuo, Effects of neck length on occurrence of cracking in tube spinning, Proc. Manuf. 15, 1200–1206 (2018) [Google Scholar]
  24. W. Luo, F. Chan, B. Vu, et al. Study on compound spinning technology of large thin-walled parts with ring inner ribs and curvilinear generatrix, Int. J. Adv. Manuf. Technol. 98, 1199–1216 (2018) [Google Scholar]
  25. X. Zhiyong, R. Yuejuan, L. Wenbo, Effect of feed speed on aluminum alloy pipe neck-spinning process and deformation analysis via simulation, MATEC Web Conf. 67, 05011–05016 (2016) [CrossRef] [Google Scholar]
  26. X. Zhanga, L. Zhaoa, T. Wena, An optimized neck-spinning method for improving the inner surface quality of titanium domes, Procedia Eng. 207, 1731–1736 (2017) [Google Scholar]
  27. K.R. Biplov, Y.P. Korkolis, A. Yoshio, Experiments and simulation of shape and thickness evolution in multi-pass tube spinning, J. Phys. Conf. Ser. 1063, 012087–012092 (2018) [Google Scholar]
  28. S.M. Ghoreishian, M. Norouzi, A. Fereydooni, Optimization of melt-spinning parameters of poly(ethylene terephthalate) partially oriented multi-filament yarn in an industrial scale: Central composite design approach, Fibers Polym. 18, 1280–1287 (2017) [CrossRef] [Google Scholar]
  29. J.J. Cummins, S. Thomas, C.J. Nash, Experimental evaluation of the efficiency of a pneumatic strain energy accumulator, Int. J. Fluid Power. 18, 167–180 (2017) [CrossRef] [Google Scholar]
  30. A. Kumar, J. Das, K. Dasgupta, et al., Effect of hydraulic accumulator on pressure surge of a hydrostatic transmission system, J. Inst. Eng. (India) Ser. C 99, 169–174 (2017) [CrossRef] [Google Scholar]
  31. J. Cai, K. Wang, P. Zhai, A modified Johnson-Cook constitutive formula to predict hot deformation behavior of Ti-6Al-4V alloy, J. Mater. Eng. Perf. 24, 32–44 (2015) [CrossRef] [Google Scholar]
  32. L.Z. Zhou, L.M. Yang, Comparative study on constitutive models to predict flow stress of Fe-Cr-Ni preform reinforced Al-Si-Cu-Ni-Mg composite, J. Wuhan Univ. Technol. Mater. Sci. Ed. 32, 666–676 (2017) [CrossRef] [Google Scholar]
  33. M. Alitavoli, A. Darvizeh, M. Moghaddam, Numerical modeling based on coupled Eulerian-Lagrangian approach and experimental investigation of water jet spot welding process, Thin-Walled Struct. 127, 617–628 (2018) [CrossRef] [Google Scholar]
  34. X.-q. Chang, L.-y. Zhang, Y.-b. Yang, J.-l. Ren, Constitutive Models for Compressive Deformation of AZ80 Magnesium Alloy under Multiple Loading Directions and Strain Rates, J. Iron Steel Res. Int. 23, 64–68 (2016) [CrossRef] [Google Scholar]
  35. D.-N. Zhang, Q.-Q. Shangguan, C.-J. Xie, F. Liu, A modified Johnson-Cook model of dynamic tensile behaviors for 7075-T6 aluminum alloy, J. Alloys Compd. 619, 186–194 (2015) [Google Scholar]
  36. M. Machorro-López José, A. Bellino, S. Marchesiello, Wavelets-based damage localization on beams under the influence of moving loads, Mechanics 14, 107–113 (2013) [Google Scholar]
  37. K. Erik, Meshing recommendations for the P-approach application in ABAQUS − A tool for pheno-numerical spring-in prediction, Compos. Struct. 203, 1–10 (2018) [Google Scholar]
  38. S.Q. Zhang, J.X. Yan, L. Cao, Crack Propagation Simulation of Hot Mill Grinding with Wood Based on ADAMS and ABAQUS, Linye Kexue/Scientia Silvae Sinicae. 54, 149–156 (2018) [Google Scholar]
  39. Z.R. Yang, X.L. Bai, Y.H. Xie, Finite element analysis on the collision between serial risers by using ABAQUS software, J. Vib. Shock 36, 196–200 (2017) [Google Scholar]
  40. X. Shi, P. Teixeira, J. Zhang, Kriging response surface reliability analysis of a ship-stiffened plate with initial imperfections, Struct. Infrastruct. Eng. 89, 1–16 (2014) [Google Scholar]
  41. X.L. Jia, J. Wang, Y.L. Zhang, True stress and shakedown analysis of pressure vessel under repeated internal pressure, Mech. Ind. 17, 410 (2016) [CrossRef] [Google Scholar]
  42. C.N.C. Bhatra, S.A. Saheb, Note on reduction of dimensionality for second order response surface design model, Commun. Stat. Theory Methods 46, 3520–3525 (2016) [Google Scholar]
  43. R.K. Kamaraj, J.G. Thankachi Raghuvaran, A.F. Panimayam, Performance and exhaust emission optimization of a dual fuel engine by response surface methodology, Energies 11, 3508 (2018) [Google Scholar]
  44. W.S. Liu, X.M. Yao, C.Q. Li, Optimization of configuration parameters of tail-sitter UAV based on response surface and genetic algorithm, Trans. Chin. Soc. Agri. Mach. 50, 88–95 (2019) [Google Scholar]
  45. A. Caglar, T. Sahan, M.S. Cogenli, A novel central composite design based response surface methodology optimization study for the synthesis of Pd/CNT direct formic acid fuel cell anode catalyst, Int. J. Hydrogen Energy 43, 11002–11011 (2018) [Google Scholar]
  46. C. Lu, L. Gao, X. Li, Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm, J. Clean. Prod. 137, 1516–1531 (2016) [Google Scholar]
  47. M.A. Sahali, I. Belaidi, R. Serra, New approach for robust multi-objective optimization of turning parameters using probabilistic genetic algorithm, Int. J. Adv. Manuf. Technol. 83, 1265–1279 (2016) [Google Scholar]
  48. J. Song, J. Li, Q.H. Yang, Multi-objective optimization and its application on irrigation scheduling based on AquaCrop and NSGA-II, J. Hydraulic Eng. 49, 1284–1295 (2018) [Google Scholar]
  49. J. Huang, Z.B. Chen, Q.M. Liu, Multi-objective optimization for laser closure process parameters in vitro skin tissue based on NSGA-II, Chin. J. Lasers 46, 0207001 (2019) [CrossRef] [Google Scholar]
  50. L.B. Huo, Z.Q. Cao, F. Zhang, Numerical and experimental study on TC4-DT titanium alloy structure after double cold expansion, J. Northwest. Polytech. Univ. 36, 701–708 (2018) [CrossRef] [Google Scholar]

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