DINGO: A Pile Load Test Database

Paul J Vardanega; Jamie J Crispin; Charlotte Gilder; Elia Voyagaki; K.  Ntassiou

doi:10.1680/pttc.65048.229

DINGO: A Pile Load Test Database

Paul J Vardanega, Jamie J Crispin^*, Charlotte Gilder, Elia Voyagaki, K. Ntassiou

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Abstract

Prediction of pile performance often relies upon full-scale pile load testing to better manage geotechnical uncertainty and enable less conservative design. Many analysis methods (e.g. the α-method) require a load test database for calibration. Databases of these tests can provide detailed design guidance in specific geological deposits. However, full scale tests are expensive, and the results, for a variety of reasons, are not always shared with the wider geotechnical community. The DINGO database is an openly accessible database of full-scale pile load tests carried out in UK soils. This paper reports on the building of the database as well as the challenges involved and lessons learnt in collecting and sharing the pile test data. The pile test data in the database is presented by sorting for ‘Geological Deposit’, ‘Construction Decade’ and ‘Construction Type’. A preliminary classification of the quality of information contained in the database is also presented.

Original language	English
Title of host publication	Piling 2020
Subtitle of host publication	Proceedings of the Piling 2020 Conference
Editors	K.G. Higgins, Y. Ainsworth, D.G. Toll, A.S. Osman
Place of Publication	London, UK
Publisher	ICE Publishing
Pages	229-234
ISBN (Print)	9780727765048
DOIs	https://doi.org/10.1680/pttc.65048.229
Publication status	Published - 5 Mar 2021
Event	PILING 2020 - Online Duration: 23 Mar 2021 → 26 Mar 2021 https://www.piling2020.org/

Conference

Conference	PILING 2020
Period	23/03/21 → 26/03/21
Internet address	https://www.piling2020.org/

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10.1680/pttc.65048.229

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This is the author accepted manuscript (AAM). The final published version (version of record) is available online via ICE Publishing at https://www.icevirtuallibrary.com/doi/abs/10.1680/pttc.65048.229 . Please refer to any applicable terms of use of the publisher.
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1 Conference Contribution (Conference Proceeding)

Preliminary study of ultimate load prediction using the DINGO database
Othman, M. M. A., Voyagaki, E., De Luca, F., Mylonakis, G., Vardanega, P. J. & Crispin, J., 4 Aug 2023, Smart Geotechnics for Smart Societies: Proceedings of the 17th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering (17ARC), Astana, Kazakhstan, 14-18 August 2023. Zhussupbekov, A., Sarsembayeva, A. & Kaliakin, V. N. (eds.). London: CRC Press/Balkema, Taylor & Francis Group, p. 1487-1492 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Databases to INterrogate Geotechnical Observations (DINGO)
Vardanega, P. J. (Principal Investigator)
1/07/17 → 9/06/19
Project: Research

The DINGO Database, v1.0
Vardanega, P. (Creator), Voyagaki, E. (Creator), Crispin, J. (Creator), Gilder, C. (Creator) & Ntasiou, K. (Creator), University of Bristol, 30 May 2019
DOI: 10.5523/bris.3r14qbdhv648b2p83gjqby2fl8, http://data.bris.ac.uk/data/dataset/3r14qbdhv648b2p83gjqby2fl8
Dataset

Cite this

@inproceedings{e38e6ebcb9174d1ab7f3142b64f838d5,

title = "DINGO: A Pile Load Test Database",

abstract = "Prediction of pile performance often relies upon full-scale pile load testing to better manage geotechnical uncertainty and enable less conservative design. Many analysis methods (e.g. the α-method) require a load test database for calibration. Databases of these tests can provide detailed design guidance in specific geological deposits. However, full scale tests are expensive, and the results, for a variety of reasons, are not always shared with the wider geotechnical community. The DINGO database is an openly accessible database of full-scale pile load tests carried out in UK soils. This paper reports on the building of the database as well as the challenges involved and lessons learnt in collecting and sharing the pile test data. The pile test data in the database is presented by sorting for {\textquoteleft}Geological Deposit{\textquoteright}, {\textquoteleft}Construction Decade{\textquoteright} and {\textquoteleft}Construction Type{\textquoteright}. A preliminary classification of the quality of information contained in the database is also presented.",

author = "Vardanega, {Paul J} and Crispin, {Jamie J} and Charlotte Gilder and Elia Voyagaki and K. Ntassiou",

year = "2021",

month = mar,

day = "5",

doi = "10.1680/pttc.65048.229",

language = "English",

isbn = "9780727765048",

pages = "229--234",

editor = "Higgins, { K.G.} and Y. Ainsworth and D.G. Toll and Osman, { A.S.}",

booktitle = "Piling 2020",

publisher = "ICE Publishing",

note = "PILING 2020 ; Conference date: 23-03-2021 Through 26-03-2021",

url = "https://www.piling2020.org/",

}

DINGO: A Pile Load Test Database. / Vardanega, Paul J; Crispin, Jamie J; Gilder, Charlotte et al.
Piling 2020: Proceedings of the Piling 2020 Conference. ed. / K.G. Higgins; Y. Ainsworth; D.G. Toll; A.S. Osman. London, UK: ICE Publishing, 2021. p. 229-234.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - DINGO

T2 - PILING 2020

AU - Vardanega, Paul J

AU - Crispin, Jamie J

AU - Gilder, Charlotte

AU - Voyagaki, Elia

AU - Ntassiou, K.

PY - 2021/3/5

Y1 - 2021/3/5

N2 - Prediction of pile performance often relies upon full-scale pile load testing to better manage geotechnical uncertainty and enable less conservative design. Many analysis methods (e.g. the α-method) require a load test database for calibration. Databases of these tests can provide detailed design guidance in specific geological deposits. However, full scale tests are expensive, and the results, for a variety of reasons, are not always shared with the wider geotechnical community. The DINGO database is an openly accessible database of full-scale pile load tests carried out in UK soils. This paper reports on the building of the database as well as the challenges involved and lessons learnt in collecting and sharing the pile test data. The pile test data in the database is presented by sorting for ‘Geological Deposit’, ‘Construction Decade’ and ‘Construction Type’. A preliminary classification of the quality of information contained in the database is also presented.

AB - Prediction of pile performance often relies upon full-scale pile load testing to better manage geotechnical uncertainty and enable less conservative design. Many analysis methods (e.g. the α-method) require a load test database for calibration. Databases of these tests can provide detailed design guidance in specific geological deposits. However, full scale tests are expensive, and the results, for a variety of reasons, are not always shared with the wider geotechnical community. The DINGO database is an openly accessible database of full-scale pile load tests carried out in UK soils. This paper reports on the building of the database as well as the challenges involved and lessons learnt in collecting and sharing the pile test data. The pile test data in the database is presented by sorting for ‘Geological Deposit’, ‘Construction Decade’ and ‘Construction Type’. A preliminary classification of the quality of information contained in the database is also presented.

U2 - 10.1680/pttc.65048.229

DO - 10.1680/pttc.65048.229

M3 - Conference Contribution (Conference Proceeding)

SN - 9780727765048

SP - 229

EP - 234

BT - Piling 2020

A2 - Higgins, K.G.

A2 - Ainsworth, Y.

A2 - Toll, D.G.

A2 - Osman, A.S.

PB - ICE Publishing

CY - London, UK

Y2 - 23 March 2021 through 26 March 2021

ER -

DINGO: A Pile Load Test Database

Abstract

Conference

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Research output

Preliminary study of ultimate load prediction using the DINGO database

Projects

Databases to INterrogate Geotechnical Observations (DINGO)

Datasets

The DINGO Database, v1.0

Cite this