Meta models for real-time design assessment within an integrated information and numerical modelling framework

Ninic, Jelena, Koch, Christian and Tizani, Walid (2018) Meta models for real-time design assessment within an integrated information and numerical modelling framework. Lecture Notes in Computer Science, 10836 . pp. 1-18. ISSN 0302-9743

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In situations where rapid decisions are required or a large number of design alternatives is to be explored, numerical predictions of construction pro-cesses have to be performed in near real-time. For the design assessment of com-plex engineering problems such as mechanised tunnelling, simple numerical and analytical models are not able to reproduce all complex 3D interactions. To over-come this problem, in this paper a novel concept for on-demand design assess-ment for mechanized tunnelling using simulation-based meta models is proposed. This concept includes: i) the generation of enhanced simulation-based meta mod-els; ii) real-time meta model-based design assessment in the design tool, and; iii) the implementation within a unified numerical and information modelling plat-form called SATBIM. The capabilities of this concept are demonstrated through an example for the evaluation of tunnel alignment design and the assessment of the impact of tunnelling on existing infrastructure. Moreover, meta models are used for fast forward calculation in sensitivity analyses for the evaluation of the importance of model parameters. The concept proved its efficiency by assessing the design alternatives in real-time with the prediction error of less than 3% com-pared to complex numerical simulation in presented example.

Item Type: Article
Additional Information: Also published as: Advanced computing strategies for engineering : 25th International Workshop 2018, EG-ICE 2018, Lausanne, Switzerland, June 10-13, 2018 : proceedings, part I / Smith, Ian F. C., Domer, Bernd (Eds.).
Keywords: Building Information Modelling, Numerical analysis, Meta models, Level of Detail, Soil-structure interaction, Real-time prediction
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
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Depositing User: Eprints, Support
Date Deposited: 27 Apr 2018 12:53
Last Modified: 04 May 2020 19:46

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