Browsing by Author "Obimba-Wogu, Jesuborn"

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    Support vector machine (SVM) prediction of coefficients of curvature and uniformity of hybrid cement modified unsaturated soil with NQF inclusion
    (leaner Engineering and Technology, 2021) Onyelowe, Kennedy C.; Mahesh, Chilakala B.; Srikanth, Bandela; Nwa-David, Chidobere; Obimba-Wogu, Jesuborn; Shakeri, Jamshid
    Support vector machine (SVM) with its feature known as the statistical risk minimization (SRM) has been employed in the prediction of coefficient of curvature and uniformity on unsaturated lateritic soil treated with composites of hybrid cement and nanostructured quarry fines. This feature utilized by SVM is the advantage it exercises over other intelligent learning techniques. This prediction has become necessary due to the time and equipment needs required to regularly conduct laboratory experiments prior to earthwork designs and construction. It is important to note that earthwork projects involving unsaturated soils pose threats of failure due to volume changes during seasonal cycles of wetting and drying especially for hydraulically bound environments and substructures. With an intelligent prediction, these design and construction worries are overcome. The soil used in the current work has been classified as an A-7-6 group soil with highly plastic consistency. Multiple experiments were conducted to generate multitude of datasets for the hybrid cement, nanostructured quarry fines, clay content and activity and frictional angle, which were selected as the independent variables for the model to predict coefficients of curvature and uniformity as the dependent variables. In order to correlate the relationship between the input and output parameters and as well validate the SVM model, detailed statistical analysis including Pearson’s coefficient of correlation (R) and determination (R2) and error analysis were conducted. Based upon the statistical analysis, the parameters were observed to have good correlation and determination ranging between 0.97 and 0.99. It was also observed that SVM outclassed MLR more in predicting Cu then it did in predicting Cc. Finally, sensitivity analysis was carried out and it was found that the Cc value is dependent mostly on frictional angle while Cu is dependent most on the NQF.
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    Valorization and sequestration of hydrogen gas from biomass combustion in solid waste incineration NaOH oxides of carbon entrapment model (SWI-NaOH-OCE Model)
    (Materials Science for Energy Technologies, 2020) Onyelowe, Kennedy C.; A. Onyelowe, Deborah Favour; Bui Van, Duc; Ikpa, Chidozie; Salahudeen, Bunyamin; Eberemu, Adrian O.; Osinubi, Kolawole J.; Onukwugha, Eze; Odumade, Adegboyega O.; Chigbo, Ikechukwu C.; Amadi, Agapitus A.; Igboayaka, Ekene; Obimba-Wogu, Jesuborn; Saing, Zubair; Amhadi, Talal
    The valorization of biomass-based solid wastes for both geotechnical engineering purposes and energy needs has been reviewed to achieve eco-friendly, eco-efficient and sustainable engineering and reengineering of civil engineering materials and structures. The objective of this work was to review the procedure developed by SWI-NaOH-OCE Model for the valorization of biomass through controlled direct combustion and the sequestration of hydrogen gas for energy needs. The incineration model gave a lead to the sequestration of emissions released during the direct combustion of biomass and the subsequent entrapment of oxides of carbon and the eventual release of abundant hydrogen gas in the entrapment jar. The generation of geomaterials ash for the purpose of soil stabilization, concrete and asphalt modification has encouraged greenhouse emissions but eventually the technology that has been put in place has made it possible to manage and extract these emissions for energy needs. The contribution from researchers has shown that hydrogen sequestration from other sources requires high amount of energy because of the lower energy states of the compounds undergoing thermal decomposition. But this work has presented a more efficient approach to release hydrogen gas, which can easily be extracted and stored to meet the energy needs of the future as fuel cell batteries to power vehicles, mobile devices, robotic systems, etc. More so, the development of MXene as an exfoliated two-dimensional nanosheets with permeability and filtration selectivity properties, which are connected to its chemical composition and structure used in hydrogen gas extraction and separation from its molecular combination, has presented an efficient procedure for the production and management of hydrogen gas for energy purposes.