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Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
(Springer, 2023)
This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number ...
Research in computing‑intensive simulations for nature‑oriented civil‑engineering and related scientific fields, using machine learning and big data: an overview of open problems
(Springer, 2023)
This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best performance of ...
A multi-fidelity wind surface pressure assessment via machine learning: A high-rise building case
(Elsevier, 2023)
Computational fluid dynamics (CFD) represents an attractive tool for estimating wind pressures and wind loads on high-rise buildings. The CFD analyses can be conducted either by low-fidelity simulations (RANS) or by ...
Experimental and numerical study of structural damping in a beam with bolted splice connection
(Thin-Walled Structures, 2023)
The objective of this research is to develop a numerical model of one widely used bolted beam splice connection
that dissipates energy through structural damping. The reference experimental setup is carefully designed ...
Practical ANN prediction models for the axial capacity of square CFST columns
(Springer, 2023)
In this study, two machine-learning algorithms based on the artificial neural network
(ANN) model are proposed to estimate the ultimate compressive strength of square
concrete-filled steel tubular columns. The development ...