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Physically-Based Object-Oriented Databases for Geotechnical Engineering

  • Sara RiosEmail author
  • Maxim Millen
  • Julieth Quintero
  • António Viana da Fonseca
Conference paper
Part of the Springer Series in Geomechanics and Geoengineering book series (SSGG)

Abstract

The large number of published assessment procedures in geotechnical engineering, as well as the large and ever-growing number of field and experimental data sets makes it difficult to perform a full validation of a new procedure. Essentially demonstrating that the new procedure is superior to existing approaches across all existing observed evidence. To enable more effective validation, this paper presents a framework for linking experimental/field data with geotechnical assessment procedures using physically based object-orientated databases. A brief explanation of physically based object-oriented programming in engineering is presented, as well as a framework for the development of compatible databases. The database design covers several key aspects: behaviour based type checking, identification numbers for objects, object methods handle saving and loading exceptions, and the use of default attribute names. This philosophy is then applied to a specific problem of earthquake geotechnical engineering where publicly available centrifuge test results are compared with simplified methods for prediction of the build up of excess pore pressure and the triggering of seismically induced soil liquefaction.

Keywords

Object-oriented programming Application programming interfaces Soil liquefaction Earthquake engineering Centrifuge databases 

Notes

Acknowledgements

LIQUEFACT project (Assessment and mitigation of liquefaction potential across Europe: a holistic approach to protect structures/infrastructures for improved resilience to earthquake-induced liquefaction disasters) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement GAP-700748. This work was financially supported by: UID/ECI/04708/2019- CONSTRUCT - Instituto de I&D em Estruturas e Construções funded by national funds through the FCT/MCTES (PIDDAC).The authors also acknowledge the Portuguese Foundation for Science and Technology (FCT) on scholarship SFRH/BPD/85863/2012.

References

  1. 1.
    Millen, M., Viana da Fonseca, A., Romão, X.: Human-driven machine-automation of engineering research. In: 9th European Conference on Numerical Methods in Geotechnical Engineering, Porto (2018)Google Scholar
  2. 2.
    Bächle, M., Kirchberg, P.: Ruby on rails. IEEE Softw. 26(6), 105–108 (2007).  https://doi.org/10.1109/ms.2007.176CrossRefGoogle Scholar
  3. 3.
    Eng-tools (2010). https://eng-tools.github.io/naming-conventions.html Accessed 18 Mar 2018
  4. 4.
    Millen, M.D.L.: Sfsimodels - a set of standard models for assessing structural and geotechnical problems (2019). https://pypi.org/project/sfsimodels/.  https://doi.org/10.5281/zenodo.2596721
  5. 5.
    Millen, M.D.L.: Geofound - A package to assess the bearing capacity and settlement of geofound (2019). https://pypi.org/project/geofound/
  6. 6.
    Millen, M.D.L.: Liquepy – Tools for soil liquefaction analysis (2019). https://pypi.org/project/liquepy/
  7. 7.
    University of Patras: Series database. http://www.dap.series.upatras.gr/default.aspx. Accessed 20 Jan 2018
  8. 8.
    Rathje, E.M., Dawson, C., Padgett, J.E., Pinelli, J.-P., Stanzione, D., Adair, A., Arduino, P., Brandenberg, S.J., Cockerill, T., Dey, C., Esteva, M., Haan Jr., F.L., Hanlon, M., Kareem, A., Lowes, L., Mock, S., Mosqueda, G.: Designsafe: new cyberinfrastructure for natural hazards engineering. Nat. Hazards Rev. 18(3), 06017001 (2017)CrossRefGoogle Scholar
  9. 9.
    Ancheta, T.D., Darragh, R.B., Stewart, J.P., Seyhan, E., Silva, W.J., Chiou, B.S.-J., Donahue, J.L.: PEER NGA-West2 Database PEER Report No. 2013/03. Pacific Earthquake Engineering Research Center, University of California, Berkeley, 134 p. (2013)Google Scholar
  10. 10.
    Akkar, S., Sandıkkaya, M.A., Şenyurt, M., Sisi, A.A., Ay, B.Ö., Traversa, P., Douglas, J., Cotton, F., Luzi, L., Hernandez, B., Godey, S.: Reference database for seismic ground-motion in Europe (RESORCE). Bull. Earthq. Eng. 12(1), 311–339 (2013)CrossRefGoogle Scholar
  11. 11.
    Seed, H., Idriss, I., Makdidi, F., Nanerjee, N.: Representation of irregular stress time histories by equivalent uniform stress series in liquefaction analyses Report No. EERC 75-29. Earthquake Engineering Research Center, University of California Berkeley (1975)Google Scholar
  12. 12.
    Boulanger, R.W., Idriss, I.M.: CPT-based liquefaction triggering procedure. J. Geotech. Geoenviron. Eng. 142(2), 04015065 (2016).  https://doi.org/10.1061/(ASCE)GT.1943-5606.0001388CrossRefGoogle Scholar
  13. 13.
    Booker, J.R., Rahman, M.S., Seed, H.B.: GADFLEA—a computer program for the analysis of pore pressure generation and dissipation during cyclic or earthquake loading. Rep. No. EERC 76-24 (1976)Google Scholar
  14. 14.
    Rios, S., Millen, M., Quintero, J., Viana da Fonseca, A.: Comparison among different approaches of estimating pore pressure development in liquefiable deposits. In: 7th International Conference on Earthquake Engineering, Rome, Italy (2019)Google Scholar
  15. 15.
    Idriss, I.M.: An update to the Seed-Idriss simplified procedure for evaluating liquefaction potential. In: TRB Workshop on New Approaches to Liquefaction Publication No. FHWARD- 99-165. Federal Highway Administration (1999)Google Scholar
  16. 16.
    Kottke, A., Bot, S.: Pysra v0.2.1. Pypi - Python package repository (2018).  https://doi.org/10.5281/zenodo.1400588
  17. 17.
    Dashti, S., Bray, J.D., Pestana, J.M., Riemer, M.R., Wilson, D.: Centrifuge testing to evaluate and mitigate liquefaction induced building settlement mechanisms. J. Geotech. Geoenviron. Eng. 136, 918–929 (2010).  https://doi.org/10.1061/(asce)gt.1943-5606.0000306CrossRefGoogle Scholar
  18. 18.
    Karimi, Z., Dashti, S.: Seismic performance of shallow founded structures on liquefiable ground: validation of numerical simulations using centrifuge experiments. J. Geotech. Geoenviron. Eng. 142(6), 1–13 (2016)CrossRefGoogle Scholar
  19. 19.
    Grammatikou, S., Biskinis, D., Fardis, M.N.: Flexural rotation capacity models fitted to test results using different statistical approaches. Struct. Concr. 14(3), 215–217 (2017).  https://doi.org/10.1002/suco.201600238CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.CONSTRUCT-GEO, Faculdade de Engenharia da Universidade do Porto (FEUP)PortoPortugal
  2. 2.Department of Civil and Natural Resources Engineering, Faculty of EngineeringUniversity of CanterburyChristchurchNew Zealand

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