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A note on r-circulant matrices involving generalized Narayana numbers
(Journal of Mathematical Inequalities, 2023)
In order to further connect structured matrices and integer sequences, r-circulant matrices involving the generalized Narayana numbers are considered. Estimates for spectral norms bounds of such matrices are presented and ...
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 ...
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 ...
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 ...
Future Drought Propagation through the Water-Energy-Food-Ecosystem Nexus – a Nordic Perspective
(Elsevier, 2022)
Droughts can affect a multitude of public and private sectors, with impacts developing slowly over time. While droughts are traditionally quantified in relation to the hydrological components of the water cycle that they ...
Prediction model for calculation of the limestone powder concrete carbonation depth
(Elsevier Ltd, 2024)
The efficient way to mitigate the impact of the concrete industry on climate change is to reduce the clinker content in the concrete mix. Beside incorporating supplementary cementitious materials (SCMs), it is possible to ...
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 ...
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 ...
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 ...
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 ...