Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Optimising Site Investigations Using Monte Carlo Analysis and Genetic Algorithms
It is generally accepted that, in civil engineering construction projects, the largest element of financial and technical risk generally lies beneath the ground. Indeed, structural foundation failure, construction over-runs and delays can often be attributed to inadequate and/or inappropriate site investigations. Unfortunately, geotechnical engineers have, at their disposal, limited guidance when scoping the extent and nature of site investigations. Often, the scope of geotechnical investigations is not governed by what is needed to characterise appropriately the subsurface conditions but, rather, is driven by budgetary constraints. A pressing need is to arm geotechnical engineers with guidelines that link the scope of a site investigation to ground variability and the probability that the foundation will be under-designed, resulting in some form of failure, or over-designed, resulting in the foundation being larger and more costly than needed. This paper outlines research undertaken to develop such guidance, focusing on the design of pile foundations in variable ground using the probabilistic techniques of random field theory, Monte Carlo simulation and genetic algorithms (GAs). The GA analyses showed that, when the number of boreholes is less than or equal to the number of piles, the boreholes are best located coincident with the piles. A single borehole should be placed at the building’s centre-most pile. With two boreholes, they are best located at the sides of the building, and three boreholes should be placed to form an equilateral triangle, as much as possible, while still being near the piles.
Optimising Site Investigations Using Monte Carlo Analysis and Genetic Algorithms
It is generally accepted that, in civil engineering construction projects, the largest element of financial and technical risk generally lies beneath the ground. Indeed, structural foundation failure, construction over-runs and delays can often be attributed to inadequate and/or inappropriate site investigations. Unfortunately, geotechnical engineers have, at their disposal, limited guidance when scoping the extent and nature of site investigations. Often, the scope of geotechnical investigations is not governed by what is needed to characterise appropriately the subsurface conditions but, rather, is driven by budgetary constraints. A pressing need is to arm geotechnical engineers with guidelines that link the scope of a site investigation to ground variability and the probability that the foundation will be under-designed, resulting in some form of failure, or over-designed, resulting in the foundation being larger and more costly than needed. This paper outlines research undertaken to develop such guidance, focusing on the design of pile foundations in variable ground using the probabilistic techniques of random field theory, Monte Carlo simulation and genetic algorithms (GAs). The GA analyses showed that, when the number of boreholes is less than or equal to the number of piles, the boreholes are best located coincident with the piles. A single borehole should be placed at the building’s centre-most pile. With two boreholes, they are best located at the sides of the building, and three boreholes should be placed to form an equilateral triangle, as much as possible, while still being near the piles.
Optimising Site Investigations Using Monte Carlo Analysis and Genetic Algorithms
Lecture Notes in Civil Engineering
Khabbaz, Hadi (Herausgeber:in) / Rujikiatkamjorn, Cholachat (Herausgeber:in) / Parsa-Pajouh, Ali (Herausgeber:in) / Jaksa, Mark B. (Autor:in) / Crisp, Michael P. (Autor:in)
Sydney Symposium ; 2022 ; Sydney, NSW, Australia
Geotechnical Lessons Learnt—Building and Transport Infrastructure Projects ; Kapitel: 4 ; 57-75
18.09.2024
19 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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