Assessment of RC exterior beam-column Joints based on artificial neural networks and other methods
•Development of a database comprising experimental information of 153 RC beam-column elements.•Development of an ANN model so as to predict the failure mode and strength of the subject elements.•Verification of the proposed ANN by comparing its predictions with the available test data.•Comparative s...
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| Vydané v: | Engineering structures Ročník 144; s. 1 - 18 |
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| Jazyk: | English |
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01.08.2017
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| ISSN: | 0141-0296, 1873-7323 |
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| Abstract | •Development of a database comprising experimental information of 153 RC beam-column elements.•Development of an ANN model so as to predict the failure mode and strength of the subject elements.•Verification of the proposed ANN by comparing its predictions with the available test data.•Comparative study of the predictions of the ANN with those obtained from codes and other methods.
A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and used for the development, training and validation of an artificial neural network (ANN) based model. The ANN model predictions on the mode of failure and load-carrying capacity of the joints, together with the predictions of widely used code methods and those of a recently proposed method, which does not require calibration through the use of test data, are compared with their counterparts stored in the database developed herein. The comparison confirms the already reported shortcomings of current code methods and demonstrates that both ANN model and the recently proposed method can provide reliable alternatives to the code methods. |
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| AbstractList | •Development of a database comprising experimental information of 153 RC beam-column elements.•Development of an ANN model so as to predict the failure mode and strength of the subject elements.•Verification of the proposed ANN by comparing its predictions with the available test data.•Comparative study of the predictions of the ANN with those obtained from codes and other methods.
A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and used for the development, training and validation of an artificial neural network (ANN) based model. The ANN model predictions on the mode of failure and load-carrying capacity of the joints, together with the predictions of widely used code methods and those of a recently proposed method, which does not require calibration through the use of test data, are compared with their counterparts stored in the database developed herein. The comparison confirms the already reported shortcomings of current code methods and demonstrates that both ANN model and the recently proposed method can provide reliable alternatives to the code methods. A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and used for the development, training and validation of an artificial neural network (ANN) based model. The ANN model predictions on the mode of failure and load-carrying capacity of the joints, together with the predictions of widely used code methods and those of a recently proposed method, which does not require calibration through the use of test data, are compared with their counterparts stored in the database developed herein. The comparison confirms the already reported shortcomings of current code methods and demonstrates that both ANN model and the recently proposed method can provide reliable alternatives to the code methods. |
| Author | Kotsovou, Gregoria M. Cotsovos, Demitrios M. Lagaros, Nikos D. |
| Author_xml | – sequence: 1 givenname: Gregoria M. surname: Kotsovou fullname: Kotsovou, Gregoria M. organization: Heriot Watt University, Edinburgh, UK – sequence: 2 givenname: Demitrios M. surname: Cotsovos fullname: Cotsovos, Demitrios M. email: d.cotsovos@hw.ac.uk organization: Heriot Watt University, Edinburgh, UK – sequence: 3 givenname: Nikos D. surname: Lagaros fullname: Lagaros, Nikos D. organization: National Technical University of Athens, Athens, Greece |
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| Cites_doi | 10.5459/bnzsee.7.1.27-47 10.5459/bnzsee.14.3.131-144 10.1680/macr.1992.44.160.175 10.1680/stco.2003.4.4.175 10.1002/eqe.793 10.1680/macr.2008.60.7.487 10.1016/j.engstruct.2012.03.049 10.56330/TGYZ8512 10.1016/S0141-0296(02)00081-0 10.1680/stbu.2008.161.2.91 10.1061/(ASCE)1090-0268(2003)7:1(39) 10.1016/S0965-9978(03)00112-1 10.1061/(ASCE)0733-9445(1991)117:3(829) 10.1007/s10518-011-9303-1 10.1080/13632469809350320 10.1680/macr.9.00194 10.1061/JSDEAG.0001785 10.1002/eqe.783 |
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| Keywords | Design External beam-column joints Codes of practice Artificial neural networks Reinforced concrete |
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| Snippet | •Development of a database comprising experimental information of 153 RC beam-column elements.•Development of an ANN model so as to predict the failure mode... A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and... |
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| SubjectTerms | Artificial neural networks Beam-columns Carrying capacity Codes of practice Design External beam-column joints Load carrying capacity Neural networks Reinforced concrete |
| Title | Assessment of RC exterior beam-column Joints based on artificial neural networks and other methods |
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