|
|
|
|
|
Mariane Rodrigues Rita, Pierre Rossi, Eduardo de Moraes Rego Fairbairn and Fernando Luiz Bastos Ribeiro
This paper presents an extension of the validation domain of a previously validated three-dimensional probabilistic semi-explicit cracking numerical model, which was initially validated for a specific concrete mix design. This model is implemented in a f...
ver más
|
|
|
|
|
|
|
|
|
Hao Zou, Jing-Sen Cai, E-Chuan Yan, Rui-Xuan Tang, Lin Jia and Kun Song
Due to the spatial variability of hydraulic properties, probabilistic slope seepage analysis becomes necessary. This study conducts a probabilistic analysis of slope seepage under rainfall, considering the spatial variability of saturated hydraulic condu...
ver más
|
|
|
|
|
|
|
|
|
Michal Juszczyk
Analyses of efficiency are vital for planning and monitoring the duration and costs of construction works, as well as the entire construction project. This paper introduces a combined quantitative (probabilistic) and qualitative (machine learning-based) ...
ver más
|
|
|
|
|
|
|
|
|
Mohammadreza Mohammadi, Araliya Mosleh, Mehran S. Razzaghi, Pedro Alves Costa and Rui Calçada
The purpose of this research is to study the seismic performance of railway embankments through a probabilistic approach. Nonlinear response history analyses were conducted utilizing PLAXIS software. Three categories of railway embankments were selected ...
ver más
|
|
|
|
|
|
|
|
|
Aristeidis Karras, Christos Karras, Konstantinos C. Giotopoulos, Dimitrios Tsolis, Konstantinos Oikonomou and Spyros Sioutas
Federated learning (FL) has emerged as a promising technique for preserving user privacy and ensuring data security in distributed machine learning contexts, particularly in edge intelligence and edge caching applications. Recognizing the prevalent chall...
ver más
|
|
|
|