ORIGINAL_ARTICLE
Steel Plate Shear Wall with Different Infill Steel Plates
The steel plate shear wall (SPSW) system is one of the most common and acceptable lateral-resisting structural systems for steel structures. Although the advantages of SPSW over the other structural systems are somehow well-known, the wall-farm interaction of the system is not comprehensively investigated. Therefore, the present study aims at investigating the interaction of the infill steel walls and the moment frames with RBS beams, using finite element method. For this purpose, different finite element model of SPSWs with various span lengths and infill steel plates are developed. The models have the low-yield, medium-yield, and high-strength infill steel plates. At first, eigenvalue buckling analysis is accomplished and those buckling mode shapes were used to introduce the initial imperfection for a realistic simulation. In the study, the important seismic parameters−including the lateral stiffness, the ultimate shear capacity, energy absorption, and ductility−are investigated using nonlinear pushover analysis. Finite element results of the study indicate utilizing the low-yield steel plate affects inversely the contribution to the wall-frame interaction and reduces significantly the shear capacity of SPSWs. However, using high-strength structural steel plate enhances the shear capacity. Moreover, using infill steel plates with different properties does not change the initial elastic stiffness of the shear wall. Additionally, increasing the span length of steel plate shear wall, the ultimate shear strength and energy dissipation increase significantly, but the ductility of the system decreases.
https://www.jcepm.com/article_62799_49cd144d2f178c6477045a7e025788a3.pdf
2018-07-01
1
14
10.22115/cepm.2018.118244.1011
steel plate shear wall
Finite element method
Nonlinear behavior
Pushover analysis
Mohammad Hossein
Kashefizadeh
mkashefi@uark.edu
1
Ph.D. Candidate, Department of Civil Engineering, University of Arkansas, USA
AUTHOR
Mohammad
Azimzadeh Koocheh
m.azimzadeh.k@gmail.com
2
Department of Civil Engineering, Kish International Branch, Islamic Azad University, Kish Island, Iran
AUTHOR
Behtash
Amiri
amiri.behtash@gmail.com
3
Young Researchers Club, Roudehen Branch, Islamic Azad University, Roudehen, Iran
LEAD_AUTHOR
Reza
Esmaeilabadi
esmaeilabadi@riau.ac.ir
4
Assistant Professor, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran
AUTHOR
[1] Sabelli R, Bruneau M. Steel Plate Shear Walls, American Institute of steel construction. Inc AISC Steel Des Guid 2006;20:1–21.
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[2] Vian D, Bruneau M, Tsai K-C, Lin Y-C. Special perforated steel plate shear walls with reduced beam section anchor beams. I: Experimental investigation. J Struct Eng 2009;135:211–20.
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[3] Astaneh-Asl A. Seismic behavior and design of steel shear walls 2001.
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[4] Association CS. Limit states design of steel structures—CAN/CSA-S16. 1-94. Rexdale, Ontario Can Stand Assoc 1994.
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[5] Construction AI of S. Seismic provisions for structural steel buildings. American Institute of Steel Construction; 2002.
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[6] Driver RG, Kulak GL, Kennedy DJL, Elwi AE. Cyclic test of four-story steel plate shear wall. J Struct Eng 1998;124:112–20.
6
[7] Jahanpour A, Moharrami H, Aghakoochak A. Evaluation of ultimate capacity of semi-supported steel shear walls. J Constr Steel Res 2011;67:1022–30. doi:10.1016/j.jcsr.2011.01.007.
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[8] Jahanpour A, Jönsson J, Moharrami H. Seismic behavior of semi-supported steel shear walls. J Constr Steel Res 2012;74:118–33. doi:10.1016/j.jcsr.2012.02.014.
8
[9] Alinia MM, Hosseinzadeh SAA, Habashi HR. Buckling and post-buckling strength of shear panels degraded by near border cracks. J Constr Steel Res 2008;64:1483–94. doi:10.1016/j.jcsr.2008.01.007.
9
[10] Amiri B, AghaRezaei H, Esmaeilabadi R. The Effect of Diagonal Stiffeners on the Behaviour of Stiffened Steel Plate Shear Wall. J Comput Eng Phys Model 2018;1:58–67.
10
[11] Zhao Q, Astaneh-Asl A. Cyclic Behavior of Traditional and Innovative Composite Shear Walls. J Struct Eng 2004;130:271–84. doi:10.1061/(ASCE)0733-9445(2004)130:2(271).
11
[12] Shafaei S, Ayazi A, Farahbod F. The effect of concrete panel thickness upon composite steel plate shear walls. J Constr Steel Res 2016;117:81–90. doi:10.1016/j.jcsr.2015.10.006.
12
[13] Rassouli B, Shafaei S, Ayazi A, Farahbod F. Experimental and numerical study on steel-concrete composite shear wall using light-weight concrete. J Constr Steel Res 2016;126:117–28. doi:10.1016/j.jcsr.2016.07.016.
13
[14] Ayazi A, Ahmadi H, Shafaei S. The effects of bolt spacing on composite shear wall behavior. World Acad Sci Eng Technol 2012;6:10–27.
14
[15] Shafaei S, Farahbod F, Ayazi A. Concrete Stiffened Steel Plate Shear Walls With an Unstiffened Opening. Structures 2017;12:40–53. doi:10.1016/j.istruc.2017.07.004.
15
[16] Shafaei S, Farahbod F, Ayazi A. The wall-frame and the steel-concrete interactions in composite shear walls. Struct Des Tall Spec Build 2018;27:e1476. doi:10.1002/tal.1476.
16
[17] Arabzadeh A, Soltani M, Ayazi A. Experimental investigation of composite shear walls under shear loadings. Thin-Walled Struct 2011;49:842–54. doi:10.1016/j.tws.2011.02.009.
17
[18] Guo L, Li R, Rong Q, Zhang S. Cyclic behavior of SPSW and CSPSW in composite frame. Thin-Walled Struct 2012;51:39–52. doi:10.1016/j.tws.2011.10.014.
18
[19] Shafaei S, Rassouli B, Ayazi A, Farahbod F. Nonlinear behavior of concrete stiffened steel plate shear wall. 7th Int. Conf. Seismol. Earthq. Eng. Tehran, Iran, 2015, p. 18–21.
19
[20] Ayazi A, Farahbod F, Rassouli B, Shafaei S. Experimental research on concrete stiffened steel plate shear wall. 7th Int. Conf. Seismol. Earthq. Eng. Tehran, Iran, 2015, p. 18–21.
20
[21] Sabouri-Ghomi S, Ventura CE, Kharrazi MH. Shear Analysis and Design of Ductile Steel Plate Walls. J Struct Eng 2005;131:878–89. doi:10.1061/(ASCE)0733-9445(2005)131:6(878).
21
[22] Berman JW, Bruneau M. Experimental investigation of light-gauge steel plate shear walls for the seismic retrofit of buildings 2003.
22
[23] Hosseinzadeh SAA, Tehranizadeh M. Introduction of stiffened large rectangular openings in steel plate shear walls. J Constr Steel Res 2012;77:180–92. doi:10.1016/j.jcsr.2012.05.010.
23
[24] Lubell AS, Prion HGL, Ventura CE, Rezai M. Unstiffened Steel Plate Shear Wall Performance under Cyclic Loading. J Struct Eng 2000;126:453–60. doi:10.1061/(ASCE)0733-9445(2000)126:4(453).
24
[25] Habashi HR, Alinia MM. Characteristics of the wall–frame interaction in steel plate shear walls. J Constr Steel Res 2010;66:150–8. doi:10.1016/j.jcsr.2009.09.004.
25
[26] ABAQUS Analysis user’s manual, version 6.10. n.d.
26
ORIGINAL_ARTICLE
Three-Dimensional Modelling of Concrete Mix Structure for Numerical Stiffness Determination
A three dimensional (3-D) numerical model with explicit representation of two distinctive phases is used for precise prediction of the stiffness and Poisson’s ratio of concrete mixture, CM. Using ANSYS code, a 3-D macro scale numerical finite elements model was developed. The aggregates size, shape and distribution are created randomly using enclosing spheres. The sizes of spheres determine the nominal sizes of stone aggregates. Uniform simplified regular spherical stones aggregates are also considered for comparison purposes. The obtained results are compared with experimental and numerical models ones from the literature. The comparison shows a reliable and reasonable agreement. The results are found to be bounded by the upper and the lower bound of the mixtures rule. The results show a close agreement with Hobbs model as well. Therefore, the finite element model perform well under induced compression loading for predicting the stiffness and the Poisson’s ratio of the concrete mix.
https://www.jcepm.com/article_64894_d16e9dccc28003bfd6e900733b892737.pdf
2018-07-01
15
27
10.22115/cepm.2018.118218.1010
Compression Stiffness
Macro-scale model
Concrete Mix
Ansys
Three-Dimensional FEM modelling
Mofid
Mahdi
mmahdi@kfu.edu.sa
1
. Department of Mechanical Engineering, KFU, KSA
LEAD_AUTHOR
Iqbal
Marie
iqbal@hu.edu.jo
2
Department of Civil Engineering, the Hashemite University, Jordan
AUTHOR
[1] Bilim C, Atiş CD, Tanyildizi H, Karahan O. Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network. Adv Eng Softw 2009;40:334–40. doi:10.1016/j.advengsoft.2008.05.005.
1
[2] Sarıdemir M. Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic. Adv Eng Softw 2009;40:920–7. doi:10.1016/J.ADVENGSOFT.2008.12.008.
2
[3] Sarıdemir M. Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks. Adv Eng Softw 2009;40:350–5. doi:10.1016/J.ADVENGSOFT.2008.05.002.
3
[4] Vakhshouri B, Nejadi S. Prediction of compressive strength of self-compacting concrete by ANFIS models. Neurocomputing 2018;280:13–22. doi:10.1016/J.NEUCOM.2017.09.099.
4
[5] Yaseen ZM, Deo RC, Hilal A, Abd AM, Bueno LC, Salcedo-Sanz S, et al. Predicting compressive strength of lightweight foamed concrete using extreme learning machine model. Adv Eng Softw 2018;115:112–25. doi:10.1016/J.ADVENGSOFT.2017.09.004.
5
[6] Li G, Zhao Y, Pang S-S, Li Y. Effective Young’s modulus estimation of concrete. Cem Concr Res 1999;29:1455–62. doi:10.1016/S0008-8846(99)00119-2.
6
[7] Zhou R, Song Z, Lu Y. 3D mesoscale finite element modelling of concrete. Comput Struct 2017;192:96–113. doi:10.1016/J.COMPSTRUC.2017.07.009.
7
[8] Mahdi M, Marie I. Numerical Simulation of Concrete Mix Structure and Detection of its Elastic Stiffness ARTICLE INFO ABSTRACT List of nomenclatures CM concrete mix E CM Elastic stiffness of concrete mix. J Comput Eng Phys Model 2018;1:12–22. doi:10.22115/cepm.2018.54011.
8
[9] Thirumalaiselvi A, Anandavalli N, Rajasankar J. Mesoscale studies on the effect of aggregate shape idealization in concrete. Mag Concr Res 2018:1–34. doi:10.1680/jmacr.17.00184.
9
[10] Li J, Liu Z, Qu XF, Zhu CQ, Zhang Y. Finite Element Analysis of Compressive Strength of Recycled Coarse Aggregate-Filled Concrete. Adv Mater Res 2011;250–253:331–4. doi:10.4028/www.scientific.net/AMR.250-253.331.
10
[11] Tarek I. Zohdi, Peter Wriggers. An Introduction to Computational Micromechanics - Tarek I. Zohdi, Peter Wriggers - Google Books. Springer; 2005.
11
[12] Lie HA, Nurhuda I, Setiawan Y. The Effect of Aggregate Shape and Configuration to the Concrete Behavior. Smart Sci 2014;2:85–90. doi:10.1080/23080477.2014.11665609.
12
[13] Anson M, Newman K. The effect of mix proportions and method of testing on Poisson’s ratio for mortars and concretes. Mag Concr Res 1966;18:115–30. doi:10.1680/macr.1966.18.56.115.
13
[14] Häfner S, Eckardt S, Luther T, Könke C. Mesoscale modeling of concrete: Geometry and numerics. Comput Struct 2006;84:450–61. doi:10.1016/j.compstruc.2005.10.003.
14
[15] Callister WD, Rethwisch DG. Materials Science and Engineering An Introduction Library of Congress Cataloging-in-Publication Data 2003.
15
[16] Hobbs DW. The dependence of the bulk modulus, Young’s modulus, creep, shrinkage and thermal expansion of concrete upon aggregate volume concentration. Matériaux Constr 1971;4:107–14. doi:10.1007/BF02473965.
16
[17] Tasdemir MA, Karihaloo BL. Effect of Type and Volume Fraction of Aggregate on the Fracture Properties of Concrete. Swets & Zeitlinger 2001;90:2651–825.
17
ORIGINAL_ARTICLE
Experimental and Numerical Investigations of Laterally Loaded Pile Group in Multilayered Cohesionless soil
This paper presents the results of experimental and numerical analysis of laterally loaded bamboo pipe piles embedded in multilayered cohesionless soil. An experimental investigation on model piles had been carried out using bamboo pipe pile with outer diameter of 24mm and inner diameter of 20mm in a multilayered cohesionless soil. In first case, a loose layer is maintained between the dense layers with H/D ratio of 0.50 and in second case, only dense sand layer of H/D ratio 0.0 is maintained with the depth of 0.0m. Where, H is the depth of middle soil layer and D is the embedment depth of pile of different slenderness (L/d) ratio of 25, 30 and 38. An experiment was carried out to study the behaviour of lateral load on bamboo pipe piles of different slenderness ratio of 25, 30 and 38. The experimental results of first case and second case show that the lateral load –lateral displacement response depends on the slenderness ratio of the piles. The experimental program was further verified by a two dimensional finite-element technique. The experimental results were compared with numerical analysis and are in a close agreement.
https://www.jcepm.com/article_82840_741f2cbe90689d7aa7df3a6245936b69.pdf
2018-07-01
28
45
10.22115/cepm.2018.108513.1005
finite element analysis
Laterally loaded pile
lateral displacement
Lateral response
slenderness ratio
Babu
Chawhan
baburao.chawhan@gmail.com
1
Civil Engineering Department, BVB College of Engineering and Technology, Hubli, Karnataka, India
LEAD_AUTHOR
S.S.
Quadri
2
Civil Engineering Department, BVB College of Engineering and Technology, Hubli, Karnataka, India
AUTHOR
[1] Brown DA, Morrison C, Reese LC. Lateral Load Behavior of Pile Group in Sand. J Geotech Eng 1988;114:1261–76. doi:10.1061/(ASCE)0733-9410(1988)114:11(1261).
1
[2] Chaney R, Demars K, McVay M, Shang T-I, Casper R. Centrifuge Testing of Fixed-Head Laterally Loaded Battered and Plumb Pile Groups in Sand. Geotech Test J 1996;19:41. doi:10.1520/GTJ11406J.
2
[3] Focht JA, Koch KJ. Rational Analysis of the Lateral Performance of Offshore Pile Groups. Offshore Technol. Conf., Offshore Technology Conference; 1973. doi:10.4043/1896-MS.
3
[4] Poulos HG. Behavior of laterally loaded piles II. Pile groups. J Soil Mech Found Div 1971.
4
[5] Davisson MT. Lateral load capacity of piles. Highw Res Rec 1970.
5
[6] Kim B-T, Kim Y-S. Back analysis for prediction and behavior of laterally loaded single piles in sand. KSCE J Civ Eng 1999;3:273–88. doi:10.1007/BF02823813.
6
[7] Prakash S, Kumar S. Nonlinear Lateral Pile Deflection Prediction in Sands. J Geotech Eng 1996;122:130–8. doi:10.1061/(ASCE)0733-9410(1996)122:2(130).
7
[8] Rao SN, Ramakrishna VGST, Rao MB. Influence of Rigidity on Laterally Loaded Pile Groups in Marine Clay. J Geotech Geoenvironmental Eng 1998;124:542–9. doi:10.1061/(ASCE)1090-0241(1998)124:6(542).
8
[9] Chandrasekaran SS, Boominathan A, Dodagoudar GR. Group Interaction Effects on Laterally Loaded Piles in Clay. J Geotech Geoenvironmental Eng 2010;136:573–82. doi:10.1061/(ASCE)GT.1943-5606.0000245.
9
[10] Salini U, Girish MS. Lateral Load Capacity of Model Piles on Cohesionless Soil. Electron J Geotech Eng 2009;14:1–11.
10
[11] Mohamedzein YE-A, Nour Eldaim FAE, Abdelwahab AB. Laboratory model tests on laterally loaded piles in plastic clay. Int J Geotech Eng 2013;7:241–50. doi:10.1179/1938636213Z.00000000030.
11
[12] Sawant VA, Shukla SK. Effect of Edge Distance from the Slope Crest on the Response of a Laterally Loaded Pile in Sloping Ground. Geotech Geol Eng 2014;32:197–204. doi:10.1007/s10706-013-9694-7.
12
[13] MAHMOUD M, BURLEY E. LATERAL LOAD CAPACITY OF SINGLE PILES IN SAND. Proc Inst Civ Eng - Geotech Eng 1994;107:155–62. doi:10.1680/igeng.1994.26468.
13
[14] Muthukkumaran K. Effect of Slope and Loading Direction on Laterally Loaded Piles in Cohesionless Soil. Int J Geomech 2014;14:1–7. doi:10.1061/(ASCE)GM.1943-5622.0000293.
14
[15] Muthukkumaran K, Sundaravadivelu R, Gandhi SR. Effect of slope on py curves due to surcharge load. Soils Found 2008;48:353–61.
15
[16] Rifat Kahyaoglu M, Imancli G, Ugur Ozturk A, Kayalar AS. Computational 3D finite element analyses of model passive piles. Comput Mater Sci 2009;46:193–202. doi:10.1016/j.commatsci.2009.02.022.
16
[17] Chae KS, Ugai K, Wakai A. Lateral Resistance of Short Single Piles and Pile Groups Located Near Slopes. Int J Geomech 2004;4:93–103. doi:10.1061/(ASCE)1532-3641(2004)4:2(93).
17
[18] Zhao M, Liu D, Zhang L, Jiang C. 3D finite element analysis on pile-soil interaction of passive pile group. J Cent South Univ Technol 2008;15:75–80. doi:10.1007/s11771-008-0016-9.
18
[19] Georgiadis K, Georgiadis M. Undrained Lateral Pile Response in Sloping Ground. J Geotech Geoenvironmental Eng 2010;136:1489–500. doi:10.1061/(ASCE)GT.1943-5606.0000373.
19
[20] Zhang L, McVay MC, Lai P. Numerical Analysis of Laterally Loaded 3 × 3 to 7 × 3 Pile Groups in Sands. J Geotech Geoenvironmental Eng 1999;125:936–46. doi:10.1061/(ASCE)1090-0241(1999)125:11(936).
20
[21] Bisaws SK, Mukherjee S, Chakrabarti S, De M. Experimental investigation of free head model piles under lateral load in homogenous and layered sand. Int J Geotech Eng 2015;9:363–78. doi:10.1179/1939787914Y.0000000078.
21
[22] Rathod D, Muthukkumaran K, Sitharam TG. Effect of Slope on p-y Curves for Laterally Loaded Piles in Soft Clay. Geotech Geol Eng 2018;36:1509–24. doi:10.1007/s10706-017-0405-7.
22
[23] Mayerhof GG. Bearing capacity and settlemtn of pile foundations. J Geotech Geoenvironmental Eng 1976;102.
23
ORIGINAL_ARTICLE
Modeling of the New Boundary of Reaction Force Based on Particle Collision in the Smoothed Particle Hydrodynamics
A new reaction force model of particle collision is built, which is based on the conservation of momentum and the conservation of energy. Combined with weakly compressible smoothed particle hydrodynamics and the artificial compressibility, the new model and a conventional reaction force model of Lennard-Jones is used to simulate the phenomenon of shear driven cavity and the flow around a square cylinder, respectively. For verifying the accuracy of the new model, the DNS method is also used to simulate the flow phenomenon. By comparing and analyzing the calculating results, it can be concluded that: The new reaction force model can effectively prevent particles from unphysically penetrating through the boundary, and the variation of velocity and tangential stress near the boundary can be relatively accurate calculated. The new model helps to enhance the calculation accuracy of smooth particle hydrodynamics (SPH) for the whole flow field, and it has relatively good stability.
https://www.jcepm.com/article_82841_d181690227c879ae211dc1efa297f28c.pdf
2018-07-01
46
66
10.22115/cepm.2018.141232.1037
Smoothed particle hydrodynamic
boundary conditions
reaction force
particles collision
L.
Wang
wanglecsi@163.com
1
School of Energy and Power Engineering, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212003, China
LEAD_AUTHOR
P.
Wang
wpyy316@163.com
2
School of Mathematics and Information Engineering, Lianyungang Normal College, Lianyungang 222006, China
AUTHOR
[1] Daxini SD, Prajapati JM. A Review on Recent Contribution of Meshfree Methods to Structure and Fracture Mechanics Applications. Sci World J 2014;2014:1–13. doi:10.1155/2014/247172.
1
[2] Lucy LB. A numerical approach to the testing of the fission hypothesis. Astron J 1977;82:1013. doi:10.1086/112164.
2
[3] Gingold RA, Monaghan JJ. Smoothed particle hydrodynamics: theory and application to non-spherical stars. Mon Not R Astron Soc 1977;181:375–89. doi:10.1093/mnras/181.3.375.
3
[4] Altomare C, Crespo AJC, Domínguez JM, Gómez-Gesteira M, Suzuki T, Verwaest T. Applicability of Smoothed Particle Hydrodynamics for estimation of sea wave impact on coastal structures. Coast Eng 2015;96:1–12. doi:10.1016/j.coastaleng.2014.11.001.
4
[5] Soutter J, Hamilton N, Russell P, Russell C, Bushby K, Sloper P, et al. The Golden Freeway: a preliminary evaluation of a pilot study advancing information technology as a social intervention for boys with Duchenne muscular dystrophy and their families. Heal Soc Care Community 2004;12:25–33. doi:10.1111/j.1365-2524.2004.00465.x.
5
[6] Nguyen MT, Aly AM, Lee S-W. A numerical study on unsteady natural/mixed convection in a cavity with fixed and moving rigid bodies using the ISPH method. Int J Numer Methods Heat Fluid Flow 2018;28:684–703. doi:10.1108/HFF-02-2017-0058.
6
[7] Aly AM. Modeling of multi-phase flows and natural convection in a square cavity using an incompressible smoothed particle hydrodynamics. Int J Numer Methods Heat Fluid Flow 2015;25:513–33. doi:10.1108/HFF-05-2014-0161.
7
[8] Basser H, Rudman M, Daly E. SPH modelling of multi-fluid lock-exchange over and within porous media. Adv Water Resour 2017;108:15–28. doi:10.1016/j.advwatres.2017.07.011.
8
[9] Kunz P, Zarikos IM, Karadimitriou NK, Huber M, Nieken U, Hassanizadeh SM. Study of Multi-phase Flow in Porous Media: Comparison of SPH Simulations with Micro-model Experiments. Transp Porous Media 2016;114:581–600. doi:10.1007/s11242-015-0599-1.
9
[10] Mayrhofer A, Laurence D, Rogers BD, Violeau D. DNS and LES of 3-D wall-bounded turbulence using Smoothed Particle Hydrodynamics. Comput Fluids 2015;115:86–97. doi:10.1016/j.compfluid.2015.03.029.
10
[11] Di Mascio A, Antuono M, Colagrossi A, Marrone S. Smoothed particle hydrodynamics method from a large eddy simulation perspective. Phys Fluids 2017;29:035102. doi:10.1063/1.4978274.
11
[12] Ni W, Lu L, Fang J, Moulinec C, Yao Y. Direct numerical simulation of turbulent channel flow with spanwise alternatively distributed strips control. Mod Phys Lett B 2018;32:1840004. doi:10.1142/S0217984918400043.
12
[13] Liu, G. R. and Liu, M. B., Smoothed Particle Hydrodynamics: A meshfree particle method, Word Scientific Publishing Co, Pte. Ltd. 2003.
13
[14] Monaghan JJ. Simulating Free Surface Flows with SPH. J Comput Phys 1994;110:399–406. doi:10.1006/jcph.1994.1034.
14
[15] LIU GR, GU YT. A LOCAL RADIAL POINT INTERPOLATION METHOD (LRPIM) FOR FREE VIBRATION ANALYSES OF 2-D SOLIDS. J Sound Vib 2001;246:29–46. doi:10.1006/jsvi.2000.3626.
15
[16] Hong-Fu HY-WQ, Wei-Ran ZJ-LG. A new repulsive model for solid boundary condition in smoothed particle hydrodynamics [J]. Acta Phys Sin 2013;4.
16
[17] Cummins SJ, Rudman M. An SPH Projection Method. J Comput Phys 1999;152:584–607. doi:10.1006/jcph.1999.6246.
17
[18] Dalrymple RA, Knio O. SPH Modelling of Water Waves. Coast. Dyn. ’01, Reston, VA: American Society of Civil Engineers; 2001, p. 779–87. doi:10.1061/40566(260)80.
18
[19] LIU MB, LIU GR, ZONG Z. AN OVERVIEW ON SMOOTHED PARTICLE HYDRODYNAMICS. Int J Comput Methods 2008;05:135–88. doi:10.1142/S021987620800142X.
19
[20] Morris JP. Analysis of smoothed particle hydrodynamics with applications. Monash University Australia; 1996.
20
[21] Lee E-S, Moulinec C, Xu R, Violeau D, Laurence D, Stansby P. Comparisons of weakly compressible and truly incompressible algorithms for the SPH mesh free particle method. J Comput Phys 2008;227:8417–36. doi:10.1016/j.jcp.2008.06.005.
21
[22] Morris JP, Fox PJ, Zhu Y. Modeling Low Reynolds Number Incompressible Flows Using SPH. J Comput Phys 1997;136:214–26. doi:10.1006/jcph.1997.5776.
22
ORIGINAL_ARTICLE
The Effects of Outrigger Type and Distribution on Seismic Behavior of Super-Tall Building
Seismic performance and behavior of super-tall building is one of significant place of doubt while using energy dissipated outriggers. To enhance the seismic performance of super-tall building structures using outrigger is one common method; however, the performance and behavior of the outrigger varies based on the outrigger section and more importantly the elevation and multitude of outrigger in structure, that could cause great differences in seismic behavior of outrigger and the compressive force that is going to apply to mega columns. To evaluate the seismic performance of the building, a case study was carried out. The models was provided with two different outrigger and two different outrigger distribution and results was find out for each model to compare and present the best model that has the higher performance in whole building. The numerical models for the structures in different condition were established with the aid of ETABS software. The responses of the modeled buildings were obtained for TSC 2007 and TSC 2017 and compared. The results show that using outrigger at roof level could significantly affect the story displacement; however, it increases the periods at both X and Y directions.
https://www.jcepm.com/article_82843_dab50bfd8c91a80cf3d9e2d37719e737.pdf
2018-07-01
67
78
10.22115/cepm.2018.125321.1016
Super-tall building
Outrigger system
seismic behavior
Numerical modeling
Ali
Ahani
ahani16@itu.edu.tr
1
M.Sc. Student, Department of Civil Engineering, Istanbul Technical University, Istanbul, Turkey
LEAD_AUTHOR
Elshan
Ahani
elshan.ahani@gmail.com
2
M.Sc. Graduate of Structural Engineering, Sahand University of Technology, Tabriz, Iran
AUTHOR
Hadi
Abbaszadeh
abbaszadeh17@itu.edu.tr
3
. M.Sc. Student, Department of Civil Engineering, Istanbul Technical University, Istanbul, Turkey
AUTHOR
[1] Taranath BS. Structural analysis and design of tall buildings: Steel and composite construction. CRC press; 2016.
1
[2] Kamath K. A Study on Static and Dynamic Behavior of Outrigger Structural System for Tall Buildings. Bonfring Int J Ind Eng Manag Sci 2012;2:15–20. doi:10.9756/BIJIEMS.1655.
2
[3] Patil DM, Sangle KK. Seismic Behaviour of Different Bracing Systems in High Rise 2-D Steel Buildings. Structures 2015;3:282–305. doi:10.1016/j.istruc.2015.06.004.
3
[4] Roeder CW, Popov EP. Eccentrically braced steel frames for earthquakes. J Struct Div 1978;104:391–412.
4
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28
ORIGINAL_ARTICLE
Controlling Blast Loading of the Structural System by Cladding Material
Shelter is one of the main component of the living creature, it should be safe, uneconomical, hygenic and protective. Now a days shelter should be protective from blast load due to terrorist attack, nuclear explosive, chemical reactions occurring inside the building may be internal blast or external blast.A SDOF structural system subjected to blast load on Front wall, rear wall and roof is studied.The response of the structure is determined. The Pressure impulse curve is determined. Pressure impulse curve plays a vital role in determining the damage level of structure subjected to blast load.A LCS model is considered and studied. A LCS model made up of aluminium foam plays a vital role in the protection of structures subjected to blast load. A parameter of non dimensional parameters κ and τ are studied.A non dimensional parameters κ and τ plays a vital role in finding the damage level of the structure.
https://www.jcepm.com/article_82849_f45d66c16002028d39346e8b7dd45829.pdf
2018-07-01
79
99
10.22115/cepm.2018.141294.1038
LCS
Blast load
Pressure impulse diagram
Non dimensional parameters κ and τ
K.K.
Kiran
kirankk0202@gmail.com
1
M.Tech, Civil Engineering Department, Government Engineering College Haveri Karnataka, India
LEAD_AUTHOR
Jagadish
Kori
korijg@gmail.com
2
Ph.D. Civil Engineering Department, Government Engineering College Haveri Karnataka, India
AUTHOR
[1] Theodor. Krauthammer. Modern Protective Structures CRC. 2015.
1
[2] Risk Reinsurance, Human Resources, Terrorism & Political Violence Risk Map 2016.
2
[3] Xia Y, Wu C, Zhang F, Li Z-X, Bennett T. Numerical Analysis of Foam-Protected RC Members under Blast Loads. Int J Prot Struct 2014;5:367–90. doi:10.1260/2041-4196.5.4.367.
3
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6
[7] Ye ZQ, Ma GW. Effects of Foam Claddings for Structure Protection against Blast Loads. J Eng Mech 2007;133:41–7. doi:10.1061/(ASCE)0733-9399(2007)133:1(41).
7
[8] Xu J, Wu C, Li J, Cui J. Simplified finite element method analysis of ultra-high-performance fibre-reinforced concrete columns under blast loads. Adv Struct Eng 2017;20:139–51. doi:10.1177/1369433216646012.
8
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9
[10] Xia Y, Wu C, Li Z-X. Optimized Design of Foam Cladding for Protection of Reinforced Concrete Members under Blast Loading. J Struct Eng 2015;141:06014010. doi:10.1061/(ASCE)ST.1943-541X.0001190.
10
ORIGINAL_ARTICLE
Flexural Capacity Prediction for Reinforced Concrete Beams by Group Method of Data Handling Approach
Application of group method of data handling (GMDH) to predict the capacity of reinforced concrete beams strengthened with CFRP laminate has been investigated in this paper. The proposed model considers nine parameters including concrete compressive strength, width of beam, effective depth, area of tension reinforcement, area of compression reinforcement, yield strength of steel, modulus of elasticity of steel, width of CFRP sheet, length of CFRP sheet. There are fourteen second order polynomials in three middle layers and an output layer. The coefficients of these polynomials are determined based on a collection of experimental laboratory tests, which were collected from the literature. In addition, 66 datasets were used to estimate unknown coefficients of the polynomials. To validate the model, 17 datasets were considered from the collected database. The results of the proposed GMDH showed that it can use as a predictive model for determining the ultimate flexural capacity of reinforced concrete beams strengthened with CFRP laminates.
https://www.jcepm.com/article_82844_9553fc5a4dda5f54a30bef0c1d0cc3a7.pdf
2018-07-01
100
110
10.22115/cepm.2018.136502.1033
Flexural capacity
reinforced concrete
FRP
GMDH
Alla
Azimi
alla.azimi@gmail.com
1
Faculty of Civil Engineering, University of Birmingham, UK
AUTHOR
Reza
Farahnaki
rf847@uowmail.edu.au
2
University of Wollongong, New South Wales, Australia
LEAD_AUTHOR
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1
[2] Xu X. Calculation Method and Analysis of Bearing Capacity of FRP Rebar Concrete Beam. ICTE 2011, Reston, VA: American Society of Civil Engineers; 2011, p. 1572–7. doi:10.1061/41184(419)260.
2
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17
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