Prediction of bearing capacity of H shaped skirted footings on sand using soft computing techniques

• Autorzy: Gnananandarao , Khatri V. N. , Dutta R. K.

Identyfikatory

DOI

10.5604/01.3001.0014.3356

• Języki publikacji: EN

Abstrakty

EN

Purpose: The present study aims to apply soft computing techniques, Artificial Neural Network (ANN) and M5P model tree, to predict the ultimate bearing capacity of the H plan shaped skirted footing on the sand Design/methodology/approach: A total of 162 laboratory test data for the regular plan shaped (square, circular, rectangular, and strip (up to L/B = 2.5) skirted footing were collected from the literature to develop the soft computing-based models. These models were later modified for the H Plan shaped skirted footing with the introduction of the multiplication factor. The input variables chosen for the regular plan shaped footings were skirt depth to width of the footing ratio (Ds/B), friction angle of the sand (o), the ratio of the interface friction angle-to-friction angle of sand (5/o), and length-to-width (L/B) ratio of the footing. The output is the bearing capacity ratio (BCR, a ratio of the bearing capacity of the skirted footing to the bearing capacity of un-skirted footing). Findings: Sensitivity analysis was carried out to see the impact of the individual variable on the BCR). The sensitivity results reveal that the skirt depth to width of the footing ratio is the primary variable affecting the BCR. Finally, the performance of the developed soft computing models was assessed using six statistical parameters. The results from the statistical parameters reveal that model developed using ANN was performing superior to the one prepared using M5P model tree technique for the prediction of the ultimate bearing capacity of H plan shaped skirted footing on sand. Research limitations/implications: The model equations are developed with experimental laboratory data. Hence, these equations need further improvement by using field data. However, until now there no field data have been available to include in the present data set. Practical implications: These proposed model equations can be used to predict the bearing capacity of the H-shaped footing with the help of Ds/B, o, S/o and L/B without performing the laboratory experiments. Originality/value: There is no such model equation that was developed so far for the H-shaped skirted footings. Hence, an attempt was made in this article to predict the bearing capacity of the H-shaped footing by using available experimental data with the help of soft computing techniques.

Słowa kluczowe

EN

bearing capacity ratio; sand; artificial neural networks; M5P model tree; regular plan shaped skirted footings; H plan shaped skirted footings

PL

współczynnik nośności; piasek; sztuczne sieci neuronowe; drzewo modelu M5P

• Wydawca: International OCSCO World Press
• Czasopismo: Archives of Materials Science and Engineering
• Rocznik: 2020
• Tom: Vol. 103, nr 2
• Strony: 62--74
• Opis fizyczny: Bibliogr. 47 poz.

Twórcy

autor

Gnananandarao

• Department of Civil Engineering, National Institute of Technology, Hamirpur, India

autor

Khatri V. N.

• Department of Civil Engineering, Indian Institute of Technology, Dhanbad, India

autor

Dutta R. K.

• Department of Civil Engineering, National Institute of Technology, Hamirpur, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)