Multi-Objective Prediction of the Mechanical Properties and Environmental Impact Appraisals of Self-Healing Concrete for Sustainable Structures

Simple item page
dc.contributor.authorOnyelowe, Kennedy C.
dc.contributor.authorEbid, Ahmed M.
dc.contributor.authorRiofrio, Ariel
dc.contributor.authorBaykara, Haci
dc.contributor.authorSoleymani, Atefeh
dc.contributor.authorMahdi, Hisham A.
dc.contributor.authorJahangir, Hashem
dc.contributor.authorIbe, Kizito
dc.date.accessioned2022-09-14T07:25:33Z
dc.date.available2022-09-14T07:25:33Z
dc.date.issued2022
dc.description.abstractAs the most commonly used construction material, concrete produces extreme amounts of carbon dioxide (CO2) yearly. For this resulting environmental impact on our planet, supplementary materials are being studied daily for their potentials to replace concrete constituents responsible for the environmental damage caused by the use of concrete. Therefore, the production of bioconcrete has been studied by utilizing the environmental and structural benefit of the bacteria, Bacillus subtilis, in concrete. This bio-concrete is known as self-healing concrete (SHC) due to its potential to trigger biochemical processes which heal cracks, reduce porosity, and improve strength of concrete throughout its life span. In this research paper, the life cycle assessment (LCA) based on the environmental impact indices of global warming potential, terrestrial acidification, terrestrial eco-toxicity, freshwater eco-toxicity, marine eco-toxicity, human carcinogenic toxicity, and human noncarcinogenic toxicity of SHC produced with Bacillus subtilis has been evaluated. Secondly, predictive models for the mechanical properties of the concrete, which included compressive (Fc), splitting tensile (Ft), and flexural (Ff) strengths and slump (S), have been studied by using artificial intelligence techniques. The results of the LCA conducted on the multiple data of Bacillus subtilis-based SHC mixes show that the global warming potential of SHC-350 mix (350 kg cement mix) is 18% less pollutant than self-healing geopolymer concrete referred to in the literature study. The more impactful mix in the present study has about 6% more CO2 emissions. In the terrestrial acidification index, the present study shows a 69–75% reduction compared to the literature. The results of the predictive models show that ANN outclassed GEP and EPR in the prediction of Fc, Ft, Ff, and S with minimal error and overall performance.en_US
dc.identifier.citationOnyelowe, K.C.; Ebid, A.M.; Riofrio, A.; Baykara, H.; Soleymani, A.; Mahdi, H.A.; Jahangir, H.; Ibe, K. Multi-Objective Prediction of the Mechanical Properties and Environmental Impact Appraisals of Self-Healing Concrete for Sustainable Structures. Sustainability 2022, 14, 9573. https://doi.org/10.3390/su14159573en_US
dc.identifier.urihttps://doi.org/10.3390/su14159573
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4717
dc.language.isoenen_US
dc.publisherSustainabilityen_US
dc.subjectSelf-healing concrete (SHC)en_US
dc.subjectBacillus subtilisen_US
dc.subjectLife cycle assessment (LCA)en_US
dc.subjectEnvironmental impacten_US
dc.subjectSustainable environmenten_US
dc.subjectSustainable constructionen_US
dc.subjectConcrete strength and workabilityen_US
dc.titleMulti-Objective Prediction of the Mechanical Properties and Environmental Impact Appraisals of Self-Healing Concrete for Sustainable Structuresen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
sustainability-14-09573.pdf
Size:
7.51 MB
Format:
Adobe Portable Document Format
Description:
Article
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Engineering and Technology