Prediction of load-carrying capacity of adhesive anchors by soft computing techniques

Materials and Structures/Materiaux et Constructions

Volumn 40, Issue 9, 2007, Pages 939-951

  Gesoğlu, Mehmet ^a   Güneyisi, Erhan ^a  

^a GAZIANTEP UNIVERSITY   (Turkey)

Author keywords

Adhesive anchors; Anchor bolt; Genetic programming; Neural network; Tensile capacity

Indexed keywords

BOLTS; COMPUTATIONAL METHODS; CONCRETES; ERROR ANALYSIS; GENETIC PROGRAMMING; NEURAL NETWORKS;

ADHESIVE ANCHORS; CONCRETE CAPACITY DESIGN (CCD) METHOD; LOAD-CARRYING CAPACITY; TENSILE CAPACITY;

ADHESIVES;

EID: 35048842705     PISSN: 13595997     EISSN: None     Source Type: Journal    
DOI: 10.1617/s11527-007-9265-6     Document Type: Article

References (45)

1. Gesoǧlu M, Özturan T, Özel M, Güneyisi E (2005) Tensile behavior of post-installed anchors in plain and steel fiber-reinforced normal-and high-strength concretes. ACI Struct J 102(2):224-231
2. McVay MC, Cook RA, Krishnamurthy K (1996) Pullout simulation of post-installed chemically bonded anchors. J Struct Eng 122(9):1016-1024
3. Cook RA, Kunz J, Fuchs W, Konz RC (1998) Behavior and design of single adhesive anchors under tensile load in uncracked concrete. ACI Struct J 95(1):9-26
4. Cook RA, Konz RC (2001) Factors influencing bond strength of adhesive anchors. ACI Struct J 98(1):76-86
5. Cook RA (1993) Behavior of Chemically bonded anchors. J Struct Eng 119(9):2744-2762
6. Cook RA, Doerr GT, Klingner RE (1993) Bond stress model for design of adhesive anchors. ACI Struct J 90(5):514-524
7. Higgins CC, Klingner RE (1998) Effects of environmental exposure on the performance of cast-in-place and retrofit anchors in concrete. ACI Struct J 95(5):506-517
8. Fujikake K, Nakayama J, Sato H, Mindess S, Ishibashi T (2003) Chemically bonded anchors subjected to rapid pullout loading. ACI Mater J 100(3):246-252
9. Klingner RE, Mendonca JA (1982). Tensile capacity of short anchor bolts and wlded studs: a literature review. ACI J Proc79(4):270-279
10. Primavera E, Pinelli J, Kalajian JE (1997) Tensile behavior of cast-in-place and undercut anchors in high strength concrete. ACI Struct J 94(5):583-594
11. ACI Committee 349 (1997) Code requirements for nuclear safety related structures (ACI 349-85) (Revised 1990) (Reapproved 1997). American Concrete Institute, Farmington Hills, Mich
12. Fuchs W, Eligehausen R, Breen JB (1995) Concrete capacity design (CCD) approach for fastening to concrete. ACI Struct J 92(1):73-94
13. ACI Committee 355 (1997) State of art report on anchorage to concrete (ACI 355.1R-91) (Reapproved 1997). American Concrete Institute, Farmington Hills, Mich
14. Gesoǧlu M (1998) Load-deflection behavior of high strength concrete anchors under static and cyclic tension, and shear loading. MS Thesis, Bogazici University, Istanbul
15. Özel M (1998) Load-deflection behavior of concrete anchors in tension. MS Thesis, Bogazici University, Istanbul
16. ACI 318-02 (2002) Building code requirements for structural concrete (ACI 318-02) and commentary (ACI 318R-02). American Concrete Institute, Farmington Hills, Mich
17. Sakla SSS, Ashour AF (2005) Prediction of tensile capacity of single adhesive anchors using neural networks. Comput Struct 83:1792-803
18. Oh JW, Lee IW, Kim JT, Lee GW (1999) Application of neural networks for proportioning of concrete mixes. ACI Mater J 96(1):61-67
19. Yeh IC (1998) Modeling of strength of high performance concrete using artificial neural networks. Cement Concrete Res 28(12):1797-1808
20. Yeh IC (1999) Design of high performance concrete mixture using neural network and nonlinear programming. J Comput Civil Eng 13(1):36-42
21. Hong-Guang N, Ji-Zong W (2000) Prediction of compressive strength of concrete by neural networks. Cement Concrete Res 30(8):1245-1250
22. Lee S-C (2003) Prediction of concrete strength using artificial neural networks. Eng Struct 25(7):849-857
23. Dias WPS, Pooliyadda SP (2001) Neural networks for predicting properties of concretes with admixtures. Construct Build Mater 15(8):371-379
24. Goh ATC (1995) Prediction of ultimate shear strength of deep beams using neural networks. ACI Struct J 92(1):28-32
25. Sanad A, Saka MP (2001) Prediction of ultimate shear strength of reinforced concrete deep beams using neural networks. J Struct Eng-ASCE 127(7):818-828
26. Baykasoglu A, Dereli T, TanIs S (2004) Prediction of cement concrete using soft computing techniques. Cement Concrete Res 34:2083-2090
27. Yang Y, Soh CK (2002) Automated optimum design of structures using genetic programming. Comput Struct 80:1537-1546
28. Ashour AF, Alvarez LF, Toropov VV (2003) Empirical modeling of shear strength RC deep beams by genetic programming. Comput Struct 81:331-338
29. Zadeh LA (1994) Soft computing and fuzzy logic. IEEE Software 11(6):48-56
30. Alexhander I, Morton H (1993) Neurons and symbols: the staff that mind is made of. Chapman and Hall, London
31. Arbib MA (1995) The handbook of Brain theory and neural networks. MIT Press, Cambridge, MA
32. Anderson JA (1995) An introduction to neural networks. A bradford Book. MIT Press, Cambridge, MA
33. Birinci F, Tigdemir M, Demir F (2001) Prediction of concrete compressive strength using artificial neural Networks. In: Proc. of symposium of modern methods, Istanbul, 2001
34. Öztas A, Pala M, Özbay E, Kanca E, Çaglar N, Asghar Bhatti M (2005) Predicting the compressive strength and slump of high strength concrete using neural network. Construct Build Mater 20(9):769-775
35. Pala M (2006) A new formulation for distortional buckling stress in cold-formed steel members. J Construct Steel Res 62:716-722
36. Wang D (1993) Pattern recognition: neural networks in perspective. IEEE Expert 8: 52-60
37. Nielsen DH (1988) Neurocomputing: picking the human brain. IEEE Spectrum 25(3):36-41
38. Kohonen T (1988) An introduction to neural computing. Neural Networks 1:3-16
39. Al-Tabtabai H, Alex PA (1999) Using genetic Algorithm to solve optimization problems in construction. Eng Construct Architect Manage 6(2):121-132
40. Ferreira C (2002) Gene expression programming: mathematical modeling by an artificial intelligence, 2002
41. Goldberg D (1989) Genetic algorithms in search, optimization and machine learning. Addison-Welsley, Reading, MA
42. Miles JC, Sisk GM, Moore CJ (2001) The conceptual design of commercial buildings using a genetic algorithm. Comput Struct 79:1583-92
43. Chang WT, Hao H (2001) An application of genetic algorithm to precast production scheduling. Comput Struct 79:1605-16
44. Hagan MT, Demuth HB, Beale MH (1996) Neural network design. PWS Publishing Company, Boston, MA
45. Ferreira C (2001) Gene Expression programming: a new adaptive algorithm for solving problems. Complex Syst 13(2):87-129