Prediction of the compressive strength of strain‐hardening cement‐based composites using soft computing models

Authors: Saleh, Peshkawt Yaseen, Jaf, Dilshad Kakasor Ismael, Abdalla, Aso A., Ahmed, Hemn Unis, Faraj, Rabar H., Mahmood, Wael, Mohammed, Ahmed Salih

Source: Structural concrete. 24(5):6761-6777

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Compressive strength of geopolymer concrete composites: a systematic comprehensive review, analysis and modeling

Authors: Ahmed, Hemn Unis, Mohammed, Ahmed S., Qaidi, Shaker M. A., Faraj, Rabar H., Hamah Sor, Nadhim, Mohammed, Azad A.

Source: European journal of environmental and civil engineering. 27(3):1383-1428

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A Comprehensive Exploration on the Effect of Waste Glass Powder as a Partial Replacement of Cement in Mortar: A Review, Analysis, and Modeling Investigation.

Authors: Ahmad, Soran Abdrahman¹ (AUTHOR) soran.abdrahman@univsul.edu.iq, Ahmed, Hemn Unis^1,2,3 (AUTHOR), Rafiq, Serwan Khwrshid¹ (AUTHOR), Mahmood, Kawa Omar Fqi⁴ (AUTHOR), Rostam, Khalan Jalil⁵ (AUTHOR), Jafer, Frya Shawkat⁶ (AUTHOR)

Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Apr2024, Vol. 49 Issue 4, p5721-5748. 28p.

Subject Terms: *MORTAR, *GLASS waste, *POWDERED glass, *ARTIFICIAL neural networks, *WASTE recycling, *CEMENT

Engineering properties of geopolymer concrete composites incorporated recycled plastic aggregates modified with nano-silica

Authors: Ahmed, Hemn Unis, Mohammed, Ahmed S., Mohammed, Azad A.

Source: In Journal of Building Engineering 15 September 2023 75

Effitioned soft computing models to evaluate the impact of silicon dioxide (SiO2) to calcium oxide (CaO) ratio in fly ash on the compressive strength of concrete

Authors: Kakasor Ismael Jaf, Dilshad, Abdulrahman, Alan Saeed, Abdulrahman, Payam Ismael, Salih Mohammed, Ahmed, Kurda, Rawaz, Ahmed, Hemn Unis, Faraj, Rabar H.

Source: In Journal of Building Engineering 1 September 2023 74

Rubberized geopolymer composites: A comprehensive review

Authors: Qaidi, Shaker M.A., Mohammed, Ahmed S., Ahmed, Hemn Unis, Faraj, Rabar H., Emad, Wael, Tayeh, Bassam A., Althoey, Fadi, Zaid, Osama, Sor, Nadhim Hamah

Source: Ceramics international. 48(17):24234-24259

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Experimental and empirical evaluation of strength for sustainable lightweight self-compacting concrete by recycling high volume of industrial waste materials

Authors: Hamah Sor, Nadhim, Hilal, Nahla, Faraj, Rabar H., Ahmed, Hemn Unis, Sherwani, Aryan Far H.

Source: European journal of environmental and civil engineering. 26(15):7443-7460

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Mathematical modeling techniques to predict the compressive strength of high-strength concrete incorporated metakaolin with multiple mix proportions

Authors: Ahmed, Hemn Unis, Abdalla, Aso A., Mohammed, Ahmed S., Mohammed, Azad A.

Source: In Cleaner Materials September 2022 5

Analytical and innovative modeling investigations on the performance of nanoparticle-modified self-compacting mortars.

Authors: Faraj, Rabar H.¹ (AUTHOR) eng.raberhame@gmail.com, Ahmed, Hemn Unis^2,3 (AUTHOR), Rafiq, Serwan Khwrshid³ (AUTHOR), Sor, Nadhim Hamah⁴ (AUTHOR)

Source: European Journal of Environmental & Civil Engineering. Mar2025, Vol. 29 Issue 5, p881-900. 20p.

Performance of Self-Compacting mortars modified with Nanoparticles: A systematic review and modeling

Authors: Faraj, Rabar H., Ahmed, Hemn Unis, Rafiq, Serwan, Sor, Nadhim Hamah, Ibrahim, Dalya F., Qaidi, Shaker M.A.

Source: In Cleaner Materials June 2022 4

The role of nanomaterials in geopolymer concrete composites: A state-of-the-art review

Authors: Ahmed, Hemn Unis ^∗, Mohammed, Azad A., Mohammed, Ahmed S.

Source: In Journal of Building Engineering 15 May 2022 49

Use of recycled fibers in concrete composites: A systematic comprehensive review

Authors: Ahmed, Hemn Unis, Faraj, Rabar H., Hilal, Nahla, Mohammed, Azad A., Sherwani, Aryan Far H.

Source: In Composites Part B 15 June 2021 215

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

Authors: Ahmed, Hemn Unis^1,2 (AUTHOR) hemn.ahmed@univsul.edu.iq, Mohammed, Ahmed S.¹ (AUTHOR), Faraj, Rabar H.³ (AUTHOR), Abdalla, Aso A.¹ (AUTHOR), Qaidi, Shaker M. A.^4,5 (AUTHOR), Sor, Nadhim Hamah⁶ (AUTHOR), Mohammed, Azad A.¹ (AUTHOR)

Source: Neural Computing & Applications. Jun2023, Vol. 35 Issue 17, p12453-12479. 27p.

Subject Terms: *COMPRESSIVE strength, *POLYMER-impregnated concrete, *CONCRETE curing, *CONCRETE, *ALKALINE solutions, *MOLARITY

Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete.

Authors: Ahmed, Hemn Unis¹ (AUTHOR) hemn.ahmed@univsul.edu.iq, Mostafa, Reham R.² (AUTHOR), Mohammed, Ahmed¹ (AUTHOR) ahmed.mohammed@univsul.edu.iq, Sihag, Parveen³ (AUTHOR), Qadir, Azad¹ (AUTHOR)

Source: Neural Computing & Applications. Jan2023, Vol. 35 Issue 3, p2909-2926. 18p.

Subject Terms: *POLYMER-impregnated concrete, *COMPRESSIVE strength, *INORGANIC polymers, *KAOLIN, *PARTICLE swarm optimization, *PETROLEUM as fuel, *CONCRETE, *FLY ash

Innovative machine learning approaches to predict the compressive strength of recycled plastic aggregate self-compacting concrete incorporating different waste ashes.

Authors: Ali, Brwa Hamah Saeed Hamah, Faraj, Rabar H., Saeed, Mariwan Ahmad Hama, Ahmed, Hemn Unis, Ahmed, Faraedoon Waly

Source: Multiscale & Multidisciplinary Modeling, Experiments & Design; Jul2024, Vol. 7 Issue 3, p2585-2604, 20p

A comparative analysis of tree-based machine learning algorithms for predicting the mechanical properties of fibre-reinforced GGBS geopolymer concrete.

Authors: Philip, Shimol, Nidhi, M., Ahmed, Hemn Unis

Source: Multiscale & Multidisciplinary Modeling, Experiments & Design; Jul2024, Vol. 7 Issue 3, p2555-2583, 29p

Retraction Notice to “Fresh and mechanical performances of recycled plastic aggregate geopolymer concrete modified with nano-silica: Experimental and computational investigation” [Constr. Build. Mater. 394 (2023) 132266]

Authors: Ahmed, Hemn Unis ^{a, ⁎}, Mohammed, Ahmed S. ^b, Mohammed, Azad A. ^b

Source: In Construction and Building Materials 20 December 2024 456

Multivariable models including artificial neural network and M5P-tree to forecast the stress at the failure of alkali-activated concrete at ambient curing condition and various mixture proportions.

Authors: Ahmed, Hemn Unis¹ (AUTHOR) hemn.ahmed@univsul.edu.iq, Mohammed, Ahmed S.¹ (AUTHOR) ahmed.mohammed@univsul.edu.iq, Mohammed, Azad A.¹ (AUTHOR)

Source: Neural Computing & Applications. Oct2022, Vol. 34 Issue 20, p17853-17876. 24p.

Subject Terms: *CONCRETE curing, *ARTIFICIAL neural networks, *CONCRETE fatigue, *MORTAR, *SUSTAINABLE construction, *COMPRESSIVE strength, *NONLINEAR regression, *CURING

RETRACTED: A review of the sustainable utilisation of red mud and fly ash for the production of geopolymer composites

Authors: Qaidi, Shaker M.A., Tayeh, Bassam A., Ahmed, Hemn Unis, Emad, Wael

Source: Construction & building materials. 350

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Recycling of mine tailings for the geopolymers production: A systematic review

Authors: Qaidi, Shaker M.A., Tayeh, Bassam A., Zeyad, Abdullah M., de Azevedo, Afonso R.G., Ahmed, Hemn Unis, Emad, Wael

Source: Case studies in construction materials. 16

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100187763546.0x000001&indx=1&recIds=ETOCvdc_100187763546.0x000001