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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 ...
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 ...
Inspection of RCF rail defects – Review of NDT methods
(Academic Press, 2023)
Rail inspection research is a substantive topic for the railway industry. Management of rolling contact fatigue rail defects is crucial for transport safety worldwide because uncontrolled development of these defects could ...
Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate
(Elsevier, 2022)
For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensemble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted ...
The feasibility of using copper slag in asphalt mixtures for base and surface layers based on laboratory results
(Construction and Building Materials - Elsevier, 2023)
This study aims to assess the feasibility of using copper slag (CS) in asphalt mixtures in both the surface and base
layers of road pavements. For this purpose, two sets of asphalt mixtures with different CS content (15 ...
Improving performance of bucket-type hydrological models in high latitudes with multi-model combination methods: Can we wring water from a stone?
(Elsevier, 2024)
Multi-model combination (averaging) methods (MMCMs) are used to improve the accuracy of hydrological (precipitation-runoff) outputs in simulation or forecasting/prediction modes. In this paper, we examined if the application ...
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 ...
Uni- and multivariate bias adjustment of climate model simulations in Nordic catchments: Effects on hydrological signatures relevant for water resources management in a changing climate
(Elsevier, 2023)
Hydrological climate-change-impact studies depend on climatic variables simulated by climate models. Due to parametrization and numerous simplifications, however, climate-model outputs come with systematic biases compared ...
Progressive failure analysis of open-hole composite laminates using FLWT-SCB prediction model
(Elsevier, 2022)
This paper presents the original incorporation of the smeared crack band (SCB) damage model within the full layerwise theory (FLWT) framework, to contribute to the increase of the computational efficiency of the progressive ...