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Toplam kayıt 348, listelenen: 61-70
Data-driven ensemble learning approach for optimal design of cantilever soldier pile retaining walls
(Elsevier, 2023)
Cantilever soldier pile retaining walls are used to ensure the stability of excavations. This paper deploys
ensemble machine learning algorithms towards achieving optimum design of these structures. A large dataset
was ...
Predictive modeling of recycled aggregate concrete beam shear strength using explainable ensemble learning methods
(2023)
Construction and demolition waste (CDW) together with the pollution caused by the
production of new concrete are increasingly becoming a burden on the environment. An appealing
strategy from both an ecological and a ...
Effect of equal-channel angular pressing on ordering kinetics and twinning in an 18-carat AuCuAg alloy
(2023)
The ability to modify microstructural features and the resulting properties of red gold provides an attractive
potential for applications in electronics, dental devices or jewelry. In this study, the effect of severe ...
New displacement method for free embedded cantilever walls in sand
(2024)
In the current literature, there is no practical formula to calculate the horizontal displace ment of cantilever walls. To fill this gap, in the present study, eight formulae for the estimation of wall
displacement were ...
Pilot-scale modeling of colloidal silica delivery to liquefiable sands
(Elsevier B.V., 2015)
Passive site stabilization is a developing technology for the in situ mitigation of the risk of liquefaction without surface disruption. It involves
the injection of stabilizing materials into liquefiable saturated sand. ...
Finite element-based p-y curves in sand
(Springer, 2023)
P-y curves are used in the prediction of non-linear soil resistance resulting from the horizontal pile movement. Many of the
p-y curves have been developed in the 1970s for the petroleum industry to predict the horizontal ...
Estimation of horizontal displacements for geosynthetic reinforced soil wall
(2023)
Nowadays, the geotechnical design trend is increasingly heading
towards the serviceability limit state. However, the current practice in the
design of geosynthetic reinforced soil (GRS) walls mostly relies on ultimate ...
Explainable data-driven ensemble learning models for the mechanical properties prediction of concrete confined by aramid fiber-reinforced polymer wraps using generative adversarial networks
(2023)
: The current study offers a data-driven methodology to predict the ultimate strain and
compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was
collected from the literature, on which ...
Neural network predictive models for alkali-activated concrete carbon emission using metaheuristic optimization algorithms
(2023)
Due to environmental impacts and the need for energy efficiency, the cement industry aims
to make more durable and sustainable materials with less energy requirements without compromising
mechanical properties based on ...
Explainable machine learning model for predicting punching shear strength of FRC flat slabs
(Elsevier BV, 2023)
Reinforced concrete slabs are vulnerable to punching shear failure at the slab-column joint, which can initiate catastrophic progressive collapse. The addition of steel fibers in the concrete matrix has emerged as an ...