Tytuł artykułu
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
Solid Mechanics Conference (SolMech 2018) (41 ; 27–31.08. 2018 ; Warsaw, Poland)
Języki publikacji
Abstrakty
The paper presents the development of the GPU-based discrete element method (DEM) code for simulating damage and fracture of cohesive solids with application to reinforced concrete at the scale of reinforcement ribs. The solid volume of concrete and steel is modelled by bonded spherical particles. Very fine discretization, containing more than million particles, is applied to describe the 3D reinforcement bar geometry at the scale of ribs and to investigate cracking behaviour of concrete near the reinforcement bar. The numerical model is validated by using experimental results of the double pull-out test. Influence of the discretization scale to the numerical solution is evaluated by using the reinforcement strain profiles and the cracking patterns. The developed GPU-based DEM algorithm efficiently handles interaction of particles, does not require any atomic operation and allows performing fast damage and fracture simulations with large number of particles. The performance measured on GPU is compared with that attained on different CPUs for varying number of particles. The high value of the Cundall number (particle number multiplied by time steps computed per second) equal to 4.3E+07 is measured on NVIDIA® Tesla™ P100 GPU in the case of 1858560 particles.
Czasopismo
Rocznik
Tom
Strony
459--488
Opis fizyczny
Bibliogr. 55 poz., rys. kolor.
Twórcy
autor
- Kaunas University of Technology, Kaunas, Lithuania
autor
- Vilnius Gediminas Technical University, Vilnius, Lithuania
autor
- Vilnius Gediminas Technical University, Vilnius, Lithuania
autor
- Vilnius Gediminas Technical University, Vilnius, Lithuania
autor
- Kaunas University of Technology, Kaunas, Lithuania
Bibliografia
- 1. P.A. Cundall, O.D.L. Strack, A discrete numerical model for granular assemblies, Géotechnique, 29, 1, 47–65, 1979.
- 2. A. Džiugys, B. Peters, An approach to simulate the motion of spherical and non-spherical fuel particles in combustion chambers, Granular Matter, 3, 4, 231–266, 2001.
- 3. H.P. Zhu, Z.Y. Zhou, R.Y. Yang, A.B. Yu, Discrete particle simulation of particulate systems: Theoretical developments, Chemical Engineering Science, 62, 13, 3378–3396, 2007.
- 4. C.J. Coetzee, Review: Calibration of the discrete element method, Powder Technology, 310, 104–142, 2017.
- 5. N. Govender, D.N. Wilke, C.-Y. Wu, J. Khinast, P. Pizette, W. Xu, Hopper flow of irregularly shaped particles (non-convex polyhedra): GPU-based DEM simulation and experimental validation, Chemical Engineering Science, 188, 34–51, 2018.
- 6. A. Kačeniauskas, R. Kačianauskas, A. Maknickas, D. Markauskas, Computation and visualization of discrete particle systems on gLite-based grid, Advances in Engineering Software, 42, 5, 237–246, 2011.
- 7. R. Tykhoniuk, J. Tomas, S. Luding, M. Kappl, L. Heim, H.J. Butt, Ultrafine cohesive powders: From interparticle contacts to continuum behaviour, Chemical Engineering Science, 62, 11, 2843–2864, 2007.
- 8. S. Wang, K. Luo, S. Yang, C. Hu, J. Fan, Parallel LES-DEM simulation of dense flows in fluidized beds, Applied Thermal Engineering, 111, 1523–1535, 2017.
- 9. J. Rojek, E. Oñate, C. Labra, H. Kargl, Discrete element simulation of rock cutting, International Journal of Rock Mechanics and Mining Sciences, 48, 6, 996–1010, 2011.
- 10. B. Kravets, H. Kruggel-Emden, Investigation of local heat transfer in random particle packings by a fully resolved LBM-approach, Powder Technology, 318, 293–305, 2017.
- 11. R. Kačianauskas, A. Maknickas, D. Vainorius, DEM analysis of acoustic wake agglomeration for mono-sized microparticles in the presence of gravitational effects, Granular Matter, 19, 3, 48–60, 2017.
- 12. R. Kačianauskas, V. Rimša, A. Kačeniauskas, A. Maknickas, D. Vainorius, R. Pacevič, Comparative DEM-CFD study of binary interaction and acoustic agglomeration of aerosol microparticles at low frequencies, Chemical Engineering Research and Design, 136, 548–563, 2018.
- 13. S. Hentz, L. Daudeville, F.V. Donzé, Identification and Validation of a discrete element model for concrete, Journal of Engineering Mechanics, 130, 6, 709–719, 2004.
- 14. G. Lilliu, J.G. Mier, 3D lattice type fracture model for concrete, Engineering Fracture Mechanics, 70, 927–41, 2003.
- 15. M. Ostoja-Starzewski, Lattice models in micromechanics, Lattice models in micromechanics, 55, 35–61, 2002.
- 16. G.A. D’Addetta, F. Kun, E. Ramm, On the application of a discrete model to the fracture process of cohesive granular materials, Granular Matter, 4, 77–90, 2002.
- 17. M. Nitka, J. Tejchman, A three-dimensional meso-scale approach to concrete fracture based on combined DEM with X-ray MCT images, Cement and Concrete Research, 107, 11–29, 2018.
- 18. D.O. Potyondy, P.A. Cundall, A bonded-particle model for rock, International Journal of Rock Mechanics and Mining Sciences, 41, 8, 1329–1364, 2004.
- 19. G. Cusatis, D. Pelessone, A. Mencarelli, Lattice Discrete Particle Model (LDPM) for failure behavior of concrete, Cement and Concrete Composites, 33, 881–971, 2011.
- 20. E. Lale, R. Rezakhani, M. Alnaggar, G. Cusatis, Homogenization coarse graining (HCG) of the lattice discrete particle model (LDPM) for the analysis of reinforced concrete structures, Engineering Fracture Mechanics, 197, 259–336, 2018.
- 21. X. Liang, C. Wu, Meso-scale modelling of steel fibre reinforced concrete with high strength, Construction and Building Materials, 165, 187–285, 2018.
- 22. J. Zhang, Z. Wang, H. Yang, Z. Wang, X. Shu, 3D meso-scale modeling of reinforcement concrete with high volume fraction of randomly distributed aggregates, Construction and Building Materials, 164, 350–61, 2018.
- 23. J. Ren, Z. Tian, J. Bu, Simulating tensile and compressive failure process of concrete with a user-defined bonded-particle model, International Journal of Concrete Structures and Materials, 12, 1, 56–74, 2018.
- 24. D. Zabulionis, O. Lukoševičienč, R. Kačianauskas, L. Tumonis, R. Kliukas, Stochastic lattice modelling of the force-displacement and cracking behaviour of the steel reinforced tie, Mathematical Problems in Engineering, 2019, 1–17, 2019.
- 25. T. Rabczuk, G. Zi, S. Bordas, H. Nguyen-Xuan, A geometrically non-linear three-dimensional cohesive crack method for reinforced concrete structures, Engineering Fracture Mechanics, 75, 4740–4808, 2008.
- 26. T. Rabczuk, T. Belytschko, Application of particle methods to static fracture of reinforced concrete structures, International Journal of Fracture, 137, 19–49, 2006.
- 27. P. Desnerck, J.M. Lees, C.T. Morley, Bond behaviour of reinforcing bars in cracked concrete, Construction and Building Materials, 94, 126–172, 2015.
- 28. D. Markauskas, A. Kačeniauskas, The comparison of two domain repartitioning methods used for parallel discrete element computations of the hopper discharge, Advances in Engineering Software, 84, 68–76, 2015.
- 29. A. Kačeniauskas, R. Pacevič, V. Starikovičius, A. Maknickas, M. Staškčnienč, G. Davidavičius, Development of cloud services for patient-specific simulations of blood flows through aortic valves, Advances in Engineering Software, 103, 57–64, 2017.
- 30. A. Kačeniauskas, P. Rutschmann, Parallel FEM software for CFD problems, Informatica, 15, 3, 363–378, 2004.
- 31. NVIDIA, Compute unified device architecture, 2018, https://docs.nvidia.com/cuda/.
- 32. J.E. Stone, D. Gohara, G. Shi, OpenCL: A parallel programming standard for heterogeneous computing systems, Computing in Science & Engineering, 12, 3, 66–73, 2010.
- 33. C.A. Radeke, B.J. Glasser, J.G. Khinast, Large-scale powder mixer simulations using massively parallel GPUarchitectures, Chemical Engineering Science, 65, 24, 6435–6442, 2010.
- 34. D. Nishiura, M. Furuichi, H. Sakaguchi, Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing, Computer Physics Communications, 194, 18–32, 2015.
- 35. X. Yue, H. Zhang, C. Ke, C. Luo, S. Shu, Y. Tan, C. Feng, A GPU-based discrete element modeling code and its application in die filling, Computers & Fluids, 110, 235–244, 2015.
- 36. Z. Zheng, M. Zang, S. Chen, H. Zeng, A GPU-based DEM-FEM computational frame-work for tire-sand interaction simulations, Computers & Structures, 209, 74–92, 2018.
- 37. T. Washizawa, Y. Nakahara, Parallel Computing of discrete element method on GPU, Applied Mathematics, 4, 1, 242–247, 2013.
- 38. Y. Tian, S. Zhang, P. Lin, Q. Yang, G. Yang, L. Yang, Implementing discrete element method for large-scale simulation of particles on multiple GPUs, Computers & Chemical Engineering, 104, 231–240, 2017.
- 39. J.Q. Gan, Z.Y. Zhou, A.B. Yu, A GPU-based DEM approach for modelling of particulate systems, Powder Technology, 301, 1172–1182, 2016.
- 40. J. Zheng, X. An, M. Huang, GPU-based parallel algorithm for particle contact detection and its application in self-compacting concrete flow simulations, Computers & Structures, 112–113, 193–204, 2012.
- 41. M. Durand, P. Marin, F. Faure, B. Raffin, DEM-based simulation of concrete structures on GPU, European Journal of Environmental and Civil Engineering, 16, 9, 1102–1114, 2012.
- 42. E.M.B. Campello, A description of rotations for DEM models of particle systems, Computational Particle Mechanics, 2, 109–134, 2015.
- 43. L. Tumonis, R. Kačianauskas, A. Kačeniauskas, Evaluation of friction due to deformed behaviour of rail in the electromagnetic railgun: numerical investigation, Mechanika, 63, 1, 58–63, 2007.
- 44. E. Stupak, R. Kačianauskas, A. Kačeniauskas, V. Starikovičius, A. Maknickas, R. Pacevič, M. Staškčnienč, G. Davidavičius, A. Aidietis, The geometric model-based patient-specific simulations of turbulent aortic valve flows, Archives of Mechanics, 69, 4–5, 317–345, 2017.
- 45. G. Liu, J.S. Marshall, S.Q. Li, Q. Yao, Discrete-element method for particle capture by a body in an electrostatic field, International Journal for Numerical Methods in Engineering, 84, 13, 1589–1612, 2010.
- 46. A. Zang, T.-F. Wong, Elastic stiffness and stress concentration in cemented granular material, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 32, 563–637, 1995.
- 47. S. Pilkavičius, R. Kačianauskas, A. Norkus, Investigation of normal contact interaction between two bonded spherical particles, Mechanika, 18, 632–641, 2013.
- 48. D. Estay, F. Chacana, J. Ibarra, L. Pérez, S. Lascano, Bond calibration method for Young’s modulus determination in the discrete element method framework, Granular Matter, 19, 3, 60–67, 2017.
- 49. G.A. Kohring, Studies of diffusional mixing in rotating drums via computer simulations, Journal de Physique I, 5, 1551–1612, 1995.
- 50. H. Kruggel-Emden, S. Wirtz, V. Scherer, A study on tangential force laws applicable to the discrete element method (DEM) for materials with viscoelastic or plastic behavior, Chemical Engineering Science, 63, 1523–1564, 2008.
- 51. R. Kačianauskas, A. Maknickas, A. Kačeniauskas, D. Markauskas, R. Balevičius, Parallel discrete element simulation of poly-dispersed granular material, Advances in Engineering Software, 41, 1, 52–63, 2010.
- 52. R. Pacevič, A. Kačeniauskas, The development of VisLT visualization service in open stack cloud infrastructure, Advances in Engineering Software, 103, 46–56, 2017.
- 53. G. Kaklauskas, A. Sokolov, R. Ramanauskas, R. Jakubovskis, Reinforcement strains in reinforced concrete tensile members recorded by strain gauges and FBG sensors: experimental and numerical analysis, Sensors, 19, 200–213, 2019.
- 54. J. Houde, Study of Force-Displacement Relationships for the Finite-Element Analysis of Reinforced Concrete, Ph.D. Thesis, McGill University, Montreal, 1974.
- 55. R. Jakubovskis, G. Kaklauskas, Bond-stress and bar-strain profiles in RC tension members modelled via finite elements, Engineering Structures, 194, 138–146, 2019.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6dc75dd4-fc11-4cf9-98d1-254a140f201c