Reliability bearing capacity analysis of footings on cohesive soil slopes using RFEM

Luo, Ning; Bathurst, Richard J.

doi:10.1016/j.compgeo.2017.04.013

Cited by 35 publications

(5 citation statements)

References 13 publications

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“…The key purpose of homogenizing soil is to break down the large clumps of soil and mix the elements throughout the soil matrix (Laiho and Perämäki 2005; Brent et al . 2017; Luo and Bathurst 2017; Goff et al . 2020).…”

Section: Resultsmentioning

confidence: 99%

“…Whilst each preparation step is important, demonstrating the insignificant difference in proportional concentration across ex‐situ stages limited the preparation steps required for accurate data. Instead, the key advantage of homogenizing soil was for operational reproducibility and reduced variation (Luo and Bathurst 2017; Theden‐Ringl and Gadd 2017). Sieving soil to remove debris, larger particles and assist with homogeneity is a standard stage of preparing soil for analysis, and should be applied to archaeological soil analysis, although sieving < 2 mm induced soil‐sorting effects (Elliott and Cambardella 1991; Shand and Wendler 2014; Thermo Scientific 2014).…”

Section: Discussionmentioning

confidence: 99%

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pXRF method development for elemental analysis of archaeological soil

2020

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Portable X‐ray fluorescence (pXRF) is now widely used for detecting the elemental composition of a material. Elemental analysis can enhance archaeological interpretations, such as mapping, preservation analysis and identifying anthropogenic activities. However, validated and reproducible protocols for analysing archaeological soil are still required. The elemental concentrations detected with three sets of preparation methods were compared: in‐situ (no preparation), in‐field (analysing through plastic bags) and ex‐situ analysis (laboratory‐based preparation). Influential factors were also investigated: calibration parameter, moisture, homogeneity, sieve size and soil type. In‐field analysis attempted to improve reliability without offsite processing, but instead substantially reduced elemental concentrations and skewed the proportional distributions. Ex‐situ analysis significantly increased elemental concentrations and reduced variation. Proportional distribution was different between the three methods, but unchanged following homogenizing and sieving. These comparisons demonstrated that ex‐situ analysis maximizes detection and ensures consistent samples.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

pXRF method development for elemental analysis of archaeological soil

2020

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“…For example, moisture content may be different across soil contexts, resulting in significantly different elemental concentrations and identified activity zones due to attenuation of X-rays by moisture (Williams et al, 2020;Stockmann et al, 2016). Full ex-situ preparation was therefore required for reliable mapping by minimising the impact of soil matrix effects between samples (Williams et al, 2020;Luo and Bathurst, 2017). This ensured consistency without requiring bespoke correction factors (Tian et al, 2018;Maruyama et al, 2008).…”

Section: Considerations For Elemental Mapping With Pxrfmentioning

confidence: 99%

Mapping an archaeological site: Interpreting portable X-ray fluorescence (pXRF) soil analysis at Boroughgate, Skelton, UK

Williams

Errickson

Taylor

2021

Journal of Archaeological Science: Reports

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“…Natural soil deposits possess specific degrees of inherent variability, thus giving rise to the uncertainty issues when encountering geotechnical stability problems [8]. Probabilistic evaluation of the bearing capacity of shallow foundations resting on earth slopes has been carried out in some of previous studies in the literature by considering soil non-homogeneity and spatial variability [9,10].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Assessment of Seismic Bearing Capacity of Strip Footings Seated on Heterogeneous Slopes Using Finite Element Limit Analysis (FELA) and Response Surface Method (RSM)

Fathipour¹,

Javankhoshdel²,

Abolfazlzadeh³

et al. 2023

Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)

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The paper demonstrates the use of the response surface method (RSM) to carry out probabilistic assessment of the seismic bearing capacity of shallow footings seated near naturally occurring heterogeneous slopes. To this end, a pseudo-static loading is applied to a randomly uniform slope, which is homogeneous in each case but random between realizations. The method substantially reduces the number of Monte Carlo simulations required to carry out cumbersome probabilistic slope stability analyses. A finite element limit analysis model based on the lower bound theorem is developed, which is then used to generate a large synthetic database of numerical results for the seismic bearing capacity of shallow foundations resting on inherently variable natural slopes. To this end, a permutation of the key parameters is formed and lower bound FELA-based limit loads are sought through optimization in MATLAB. A closed-form solution is formulated using RSM-based polynomials. The RSM equations, which are acquired from least squares regression analyses, are used to carry out probabilistic Monte Carlo simulations and the results are presented in forms of cumulative distribution functions. Results from the probabilistic analyses are introduced into some reliability-based design approach to render design loads for different reliability levels.

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Reliability bearing capacity analysis of footings on cohesive soil slopes using RFEM

Cited by 35 publications

References 13 publications

pXRF method development for elemental analysis of archaeological soil

pXRF method development for elemental analysis of archaeological soil

Mapping an archaeological site: Interpreting portable X-ray fluorescence (pXRF) soil analysis at Boroughgate, Skelton, UK

Probabilistic Assessment of Seismic Bearing Capacity of Strip Footings Seated on Heterogeneous Slopes Using Finite Element Limit Analysis (FELA) and Response Surface Method (RSM)

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