Suivre
Sławomir Czarnecki
Titre
Citée par
Citée par
Année
Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
H Song, A Ahmad, F Farooq, KA Ostrowski, M Maślak, S Czarnecki, ...
Construction and Building Materials 308, 125021, 2021
3082021
A comparative study for the prediction of the compressive strength of self-compacting concrete modified with fly ash
F Farooq, S Czarnecki, P Niewiadomski, F Aslam, H Alabduljabbar, ...
Materials 14 (17), 4934, 2021
1082021
Application of novel machine learning techniques for predicting the surface chloride concentration in concrete containing waste material
A Ahmad, F Farooq, KA Ostrowski, K Śliwa-Wieczorek, S Czarnecki
Materials 14 (9), 2297, 2021
1022021
Evaluation of the height 3D roughness parameters of concrete substrate and the adhesion to epoxy resin
S Czarnecki, J Hoła
International Journal of Adhesion and Adhesives 67, 3-13, 2016
882016
An intelligent model for the prediction of the compressive strength of cementitious composites with ground granulated blast furnace slag based on ultrasonic pulse velocity …
S Czarnecki, M Shariq, M Nikoo, Ł Sadowski
Measurement 172, 108951, 2021
712021
Pull-off adhesion prediction of variable thick overlay to the substrate
Ł Sadowski, J Hoła, S Czarnecki, D Wang
Automation in Construction 85, 10-23, 2018
472018
The nature-inspired metaheuristic method for predicting the creep strain of green concrete containing ground granulated blast furnace slag
Ł Sadowski, M Nikoo, M Shariq, E Joker, S Czarnecki
Materials 12 (2), 293, 2019
462019
Artificial neural networks for non-destructive identification of the interlayer bonding between repair overlay and concrete substrate
S Czarnecki, Ł Sadowski, J Hoła
Advances in Engineering Software 141, 102769, 2020
362020
The effect of basalt aggregates and mineral admixtures on the mechanical properties of concrete exposed to sulphate attacks
A Karasin, M Hadzima-Nyarko, E Işık, M Doğruyol, IB Karasin, ...
Materials 15 (4), 1581, 2022
342022
Non-destructive neural identification of the bond between concrete layers in existing elements
Ł Sadowski, J Hoła, S Czarnecki
Construction and Building Materials 127, 49-58, 2016
322016
Random forest algorithm and support vector machine for nondestructive assessment of mass moisture content of brick walls in historic buildings
A Hoła, S Czarnecki
Automation in Construction 149, 104793, 2023
292023
Mechanical and microstructural properties of ordinary concrete with high additions of crushed glass
C Belebchouche, K Moussaceb, SE Bensebti, A Aït-Mokhtar, A Hammoudi, ...
Materials 14 (8), 1872, 2021
292021
Evaluation of interlayer bonding in layered composites based on non-destructive measurements and machine learning: Comparative analysis of selected learning algorithms
S Czarnecki, Ł Sadowski, J Hoła
Automation in Construction 132, 103977, 2021
272021
Non-destructive evaluation of the bond between a concrete added repair layer with variable thickness and a substrate layer using ANN
S Czarnecki
Procedia Engineering 172, 194-201, 2017
232017
The effect of the amount and particle size of the waste quartz powder on the adhesive properties of epoxy resin coatings
A Chowaniec, S Czarnecki, Ł Sadowski
International Journal of Adhesion and Adhesives 117, 103009, 2022
192022
The effect of mineral powders derived from industrial wastes on selected mechanical properties of concrete
A Galińska, S Czarnecki
IOP Conference Series: Materials Science and Engineering 245 (3), 032039, 2017
192017
Morphogenesis in solidification phases of lightweight concrete surface at early ages
Ł Sadowski, M Popek, S Czarnecki, TG Mathia
Construction and Building Materials 148, 96-103, 2017
192017
A nondestructive method of investigating the morphology of concrete sur-faces by means of newly designed 3D scanner
S CZARNECKI, J HOŁA, Ł SADOWSKI
XI Europejska Konferencja Badań Nieniszczących, ECNDT, 2014
142014
Brick wall moisture evaluation in historic buildings using neural networks
A Hoła, S Czarnecki
Automation in Construction 141, 104429, 2022
132022
Design of a machine learning model for the precise manufacturing of green cementitious composites modified with waste granite powder
S Czarnecki, M Hadzima-Nyarko, A Chajec, Ł Sadowski
Scientific reports 12 (1), 13242, 2022
132022
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–20