참고문헌 (58)

1. Lloyd A. Performance of reinforced concrete columns under shock tube induced shock wave loading. MSc thesis. Ottawa: Dept. of Civil Engineering: University of Ottawa; 2010. p. 2. 

2. Eng Struct Kiakojouri 262 2022 10.1016/j.engstruct.2022.114274 Strengthening and retrofitting techniques to mitigate progressive collapse: A critical review and future research agenda 

   상세보기

3. Eng Struct Kiakojouri 206 2020 10.1016/j.engstruct.2019.110061 Progressive collapse of framed building structures: Current knowledge and future prospects 

   상세보기

4. Eng Struct Adam 173 122 2018 10.1016/j.engstruct.2018.06.082 Research and practice on progressive collapse and robustness of building structures in the 21st century 

   상세보기

5. 10.1061/(ASCE)0733-9399(2002)128:1(87) Li QM, Meng H. Pressure-impulse diagram for blast loads based on dimensional analysis and single-degree-of-freedom model. J Eng Mech 2002; 128(1): 87-92. https://doi.org/ 10.1061/(asce)0733-9399(2002)128:1(87). 

   상세보기

6. J Perform Constr Facil El-Dakhakhni 24 4 311 2010 10.1061/(ASCE)CF.1943-5509.0000090 Validity of SDOF models for analyzing two-way reinforced concrete panels under blast loading 

   상세보기

7. Int J Impact Eng Ma 34 6 1081 2007 10.1016/j.ijimpeng.2006.05.001 P-I diagram method for combined failure modes of rigid-plastic beams 

   상세보기

8. Eng Fail Anal Yu 100 520 2019 10.1016/j.engfailanal.2019.02.001 Generation of pressure-impulse diagrams for failure modes of RC columns subjected to blast loads 

   상세보기

9. J Perform Constr Facil El-Dakhakhni 23 5 353 2009 10.1061/(ASCE)CF.1943-5509.0000015 Vulnerability screening and capacity assessment of reinforced concrete columns subjected to blast 

   상세보기

10. J Perform Constr Facil Cui 29 5 B4015003 2015 10.1061/(ASCE)CF.1943-5509.0000766 Failure Analysis and Damage Assessment of RC Columns under Close-In Explosions 

    상세보기

11. Int J Impact Eng Wu 38 1 29 2011 10.1016/j.ijimpeng.2010.09.002 Residual axial compression capacity of localized blast-damaged RC columns 

    상세보기

12. Eng Struct Kyei 142 148 2017 10.1016/j.engstruct.2017.03.044 Effects of transverse reinforcement spacing on the response of reinforced concrete columns subjected to blast loading 

    상세보기

13. J Perform Constr Facil Rajkumar 34 1 04019102 2020 10.1061/(ASCE)CF.1943-5509.0001382 Numerical study on parametric analysis of reinforced concrete column under blast loading 

    상세보기

14. Int J Impact Eng Shi 35 11 1213 2008 10.1016/j.ijimpeng.2007.09.001 Numerical derivation of pressure-impulse diagrams for prediction of RC column damage to blast loads 

    상세보기

15. Eng Struct Li 242 2021 10.1016/j.engstruct.2021.112519 Predication of the residual axial load capacity of CFRP-strengthened RC column subjected to blast loading using artificial neural network 

    상세보기

16. Int J Impact Eng Almustafa 162 2022 10.1016/j.ijimpeng.2021.104145 Machine learning model for predicting structural response of RC columns subjected to blast loading 

    상세보기

17. Structures Almustafa 39 1092 2022 10.1016/j.istruc.2022.04.007 Novel hybrid machine learning approach for predicting structural response of RC beams under blast loading 

    상세보기

18. Cement Concrete Comp Almustafa 126 2022 10.1016/j.cemconcomp.2021.104378 Machine learning prediction of structural response of steel fiber-reinforced concrete beams subjected to far-field blast loading 

    상세보기

19. J Build Eng Shin 57 2022 Optimum retrofit strategy of FRP column jacketing system for non-ductile RC building frames using artificial neural network and genetic algorithm hybrid approach 

20. Adv Struct Eng Chaiyasarn 24 7 1480 2021 10.1177/1369433220975574 Concrete crack detection and 3D mapping by integrated convolutional neural networks architecture 

    상세보기

21. Adv Struct Eng Andrushia 24 9 1896 2021 10.1177/1369433220986637 Deep learning based thermal crack detection on structural concrete exposed to elevated temperature 

    상세보기

22. Constr Build Mater Deng 175 562 2018 10.1016/j.conbuildmat.2018.04.169 Compressive strength prediction of recycled concrete based on deep learning 

    상세보기

23. Constr Build Mater Zhou 208 144 2019 10.1016/j.conbuildmat.2019.03.006 Quick image analysis of concrete pore structure based on deep learning 

    상세보기

24. Earthq Eng Struct Dyn Kim 49 7 657 2020 10.1002/eqe.3258 Pre-and post-earthquake regional loss assessment using deep learning 

    상세보기

25. LS-DYNA 971. Livermore software technology corporation. CA, USA: Livermore; 2015. 

26. Int J Impact Eng Malvar 19 9-10 847 1997 10.1016/S0734-743X(97)00023-7 A plasticity concrete material model for DYNA3D 

    상세보기

27. Mater Struct Bischoff 24 144 425 1991 10.1007/BF02472016 Compressive behavior of concrete at high strain rates 

    상세보기

28. Malvar LJ, Crawford JE. Dynamic increase factors for concrete. In: 28th Department of Defense Explosives Safety seminar, Orlando, FL; 1998, p. 1-17. 

29. Hallquist 2007 LS-DYNA theory manual - ls971. Technical report 

30. Malvar LJ, Crawford JE. Dynamic Increase Factors for Steel Reinforcing Bars. In: 28th DDESB Seminar, Orlando, USA; 1998, p. 1-18. 

31. Comput Struct Xu 84 5-6 431 2006 10.1016/j.compstruc.2005.09.029 Numerical simulation study of spallation in reinforced concrete plates subjected to blast loading 

    상세보기

32. Comput Struct Baylot 85 11-14 891 2007 10.1016/j.compstruc.2007.01.001 Effect of responding and failing structural components on the airblast pressures and loads on and inside of the structure 

    상세보기

33. 10.1139/cjce-2016-0390 Braimah A, Siba F. Near-field explosion effects on reinforced concrete columns: an experimental investigation. Can J Civ Eng 2018;45(4):289-303. https://doi.org/ 10.1139/cjce-2016-0390. 

    상세보기

34. Acta Armamentarii Wang 37 8 1421 2016 Damage criterion of Reinforced Concrete beams under blast loading 

35. 10.1016/j.engfailanal.2015.11.038 Codina R, Ambrosini D, De Borbon F. Alternatives to prevent the failure of RC members under close-in blast loadings. Eng Fail Anal 2016;60:96-106. https://doi.org/ 10.1016/j.engfailanal.2015.11.038. 

    상세보기

36. 10.1680/jstbu.18.00223 Dua A, Braimah A, Kumar M. Contact explosion response of reinforced concrete columns: Experimental and validation of numerical model. In: Proceedings of the Paper presented at the 6th International Disaster Mitigation Specialty Conference, Fredericton, New Brunswick, Canada; 2018: p. 13-16. https://doi.org/10.1680/jstbu.18.00223. 

    상세보기

37. Structures Liu 22 341 2019 10.1016/j.istruc.2019.08.014 Improved SDOF and numerical approach to study the dynamic response of reinforced concrete columns subjected to close-in blast loading 

    상세보기

38. J Beijing Univ Technol Yan 46 02 154 2020 Comparison of numerical analysis loading methods of RC columns under near-field explosion 

39. Int J Impact Eng Li 68 41 2014 10.1016/j.ijimpeng.2014.02.001 Numerical study of concrete spall damage to blast loads 

    상세보기

40. Eng Fail Anal Thai 92 350 2018 10.1016/j.engfailanal.2018.06.001 Numerical investigation of the damage of RC members subjected to blast loading 

    상세보기

41. Eng Blasting Wu 27 02 58 2021 Analysis of explosion damage factors in reinforced concrete columns 

42. J Build Struct Shi 42 11 155 2021 Rapid evaluation method for blast damage of reinforced concrete columns based on measured frequency 

43. Chinese Standard. GB 50010-2010. Code for design of concrete structures. Beijing: China Planning Press; 2010. (in Chinese). 

44. Chinese Standard. GB 50011-2010. Code for seismic design of buildings. Beijing: China Planning Press; 2010. (in Chinese). 

45. Berry M, Parrish M, Eberhard M. PEER structural performance database user’s manual (version 1.0). Berkeley: University of California; 2004. 

46. FEMA 426 Reference manual to mitigate potential terrorist attacks against buildings. Federal Emergency Management Agency; 2003. 

47. J Build Struct Ding 34 4 57 2013 Research on categorized explosion protection criterion of anti-terrorism building structures 

48. Chinese Standard. GB 50180-93. Code of urban residential areas planning & design. Beijing: China Planning Press; 2016. (in Chinese). 

49. Liu Y, Starzyk JA, Zhu Z. Optimizing number of hidden neurons in neural networks. In: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, Innsbruck, AUSTRIA; 2007: p.121-126. 

50. Int J Eng Trends & Tech Karsoliya 3 6 714 2012 Approximating number of hidden layer neurons in multiple hidden layer BPNN architecture 

51. 10.1109/SAMI48414.2020.9108717 Rasamoelina AD, Adjailia F, Sincak P. A review of activation function for artificial neural network. In: 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI), Herlany, SLOVAKIA; 2020: p. 281-286. 

    

52. Ruder S. An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747, 2016. 

53. AI Expert Garson 6 4 46 1991 Interpreting neural network connection weights 

54. Gulli A, Pal S. Deep learning with Keras. Packt Publishing Ltd; 2017. 

55. 10.1073/pnas.79.8.2554 Hopfield JJ. Neural networks and physical systems with emergent collective computational abilities. P Natl Acad Sci USA 1982;79(8):2554-2558. https://doi.org/ 10.1073/pnas.79.8.2554. 

    상세보기

56. Neural Comput Hochreiter 9 8 1735 1997 10.1162/neco.1997.9.8.1735 Long short-term memory 

    상세보기

57. J Mach Learn Res Srivastava 15 1 1929 2014 Dropout: a simple way to prevent neural networks from overfitting 

    상세보기

58. Reliab Eng Syst Saf Nguyen 188 251 2019 10.1016/j.ress.2019.03.018 A new dynamic predictive maintenance framework using deep learning for failure prognostics 

    상세보기