Shaker Qaidi

Machine learning techniques and multi-scale models to evaluate the impact of silicon dioxide (SiO2) and calcium oxide (CaO) in fly ash on the compressive strength of green concrete

Dilshad Kakasor Ismael Jaf, Payam Ismael Abdulrahman, Ahmed Salih Mohammed et al. · Construction and Building Materials · 2023 · 302 citations

Architecture, Materials Engineering, Materials Science +17

Geopolymer concrete as a cleaner construction material: An overview on materials and structural performances

Hemn Unis Ahmed, Lavan Jutyar Mahmood, Muhammad Muhammad et al. · Cleaner Materials · 2022 · 294 citations · Full text

Engineering, Civil Engineering, Materials Engineering +17

Prediction of concrete materials compressive strength using surrogate models

Wael Emad, Ahmed Salih Mohammed, Rawaz Kurda et al. · Structures · 2022 · 219 citations

Architecture, Materials Engineering, Materials Science +14

Innovative modeling techniques including MEP, ANN and FQ to forecast the compressive strength of geopolymer concrete modified with nanoparticles

Hemn Unis Ahmed, Ahmed Salih Mohammed, Rabar H. Faraj et al. · Neural Computing and Applications · 2023 · 203 citations

Engineering, Civil Engineering, Materials Engineering +14

Compressive strength of geopolymer concrete modified with nano-silica: Experimental and modeling investigations

Hemn Unis Ahmed, Ahmed Salih Mohammed, Rabar H. Faraj et al. · Case Studies in Construction Materials · 2022 · 202 citations · Full text

Architecture, Materials Engineering, Materials Science +17