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Wet–dry cycles and microstructural characteristics of expansive subgrade treated with sustainable cementitious waste materials (2023)
Journal Article
Abbey, S. J., Amakye, S. Y., Eyo, E. U., Booth, C. A., & Jeremiah, J. J. (2023). Wet–dry cycles and microstructural characteristics of expansive subgrade treated with sustainable cementitious waste materials. Materials, 16(8), 3124. https://doi.org/10.3390/ma16083124

This work presents an experimental study on the physico-mechanical and microstructural characteristics of stabilised soils and the effect of wetting and drying cycles on their durability as road subgrade materials. The durability of expansive road su... Read More about Wet–dry cycles and microstructural characteristics of expansive subgrade treated with sustainable cementitious waste materials.

Modified orange peel waste as a sustainable material for the adsorption of contaminants (2023)
Journal Article
Uloaku, M., Abbey, S. J., Ifelebuegu, A. O., & Eyo, E. U. (2023). Modified orange peel waste as a sustainable material for the adsorption of contaminants. Materials, 16(3), 1092. https://doi.org/10.3390/ma16031092

World orange production is estimated at 60 million tons per annum, while the annual production of orange peel waste is 32 million tons. According to available data, the adsorption capacity of orange peel ranges from 3 mg/g to 5 mg/g, while their wate... Read More about Modified orange peel waste as a sustainable material for the adsorption of contaminants.

Shear response of Lime/GGBS-Stabilised High-Sulphate-Bearing Clay under consolidated-undrained conditions (2022)
Journal Article
Eyo, E., & Abbey, S. (2022). Shear response of Lime/GGBS-Stabilised High-Sulphate-Bearing Clay under consolidated-undrained conditions. Applied Sciences, 12(20), https://doi.org/10.3390/app122010639

This study investigated the consolidated undrained shear behaviour of a stabilised high-sulphate soil system. Lime was used to stabilise the soil with the inclusion of ground granulated blast furnace slag (GGBS) as an ettringite suppressor. Both volu... Read More about Shear response of Lime/GGBS-Stabilised High-Sulphate-Bearing Clay under consolidated-undrained conditions.

Explainable machine learning for autonomous vehicle positioning using SHAP (2022)
Book Chapter
Onyekpe, U., Lu, Y., Apostolopoulou, E., Palade, V., Eyo, E. U., & Kanarachos, S. (2023). Explainable machine learning for autonomous vehicle positioning using SHAP. In M. Mehta, V. Palade, & I. Chatterjee (Eds.), Explainable AI: Foundations, Methodologies and Applications (157-183). Springer. https://doi.org/10.1007/978-3-031-12807-3_8

Despite the recent advancements in Autonomous Vehicle (AV) technology, safety still remains a key challenge for their commercialisation and development. One of the major systems influencing the safety of AVs is its navigation system. Road localisatio... Read More about Explainable machine learning for autonomous vehicle positioning using SHAP.

Using Artificial Intelligence techniques to predict intrinsic compressibility characteristic of Clay (2022)
Journal Article
Eyo, E. E., Abbey, S. J., & Booth, C. A. (2022). Using Artificial Intelligence techniques to predict intrinsic compressibility characteristic of Clay. Applied Sciences, 12(19), https://doi.org/10.3390/app12199940

Reconstituted clays have often provided the basis for the interpretation and modelling of the properties of natural clays. The term “intrinsic” was introduced to describe a clay remoulded or reconstituted at moisture content up to 1.5 times its liqui... Read More about Using Artificial Intelligence techniques to predict intrinsic compressibility characteristic of Clay.

Strength predictive modelling of soils treated with calcium-based additives blended with eco-friendly pozzolans—A machine learning approach (2022)
Journal Article
Eyo, E. U., Abbey, S. J., & Booth, C. A. (2022). Strength predictive modelling of soils treated with calcium-based additives blended with eco-friendly pozzolans—A machine learning approach. Materials, 15(13), Article 4575. https://doi.org/10.3390/ma15134575

The unconfined compressive strength (UCS) of a stabilised soil is a major mechanical parameter in understanding and developing geomechanical models, and it can be estimated directly by either lab testing of retrieved core samples or remoulded samples... Read More about Strength predictive modelling of soils treated with calcium-based additives blended with eco-friendly pozzolans—A machine learning approach.

Data on one-dimensional vertical free swelling potential of soils and related soil properties (2021)
Journal Article
U, E. E., & Onyekpe, U. (2021). Data on one-dimensional vertical free swelling potential of soils and related soil properties. Data in Brief, 39, Article 107608. https://doi.org/10.1016/j.dib.2021.107608

Most of the damaging geo-hazards recorded in modern history are caused by soil swelling or expansion. Therefore, proper evaluation of a soil's capacity to swell is very crucial for the achievement of a secure and safe ground for civil infrastructures... Read More about Data on one-dimensional vertical free swelling potential of soils and related soil properties.

Multiclass stand-alone and ensemble machine learning algorithms utilised to classify soils based on their physico-chemical characteristics (2021)
Journal Article
Abbey, S., & Eyo, E. (2022). Multiclass stand-alone and ensemble machine learning algorithms utilised to classify soils based on their physico-chemical characteristics. Journal of Rock Mechanics and Geotechnical Engineering, 14(2), 603-615. https://doi.org/10.1016/j.jrmge.2021.08.011

This study has provided an approach to classify soil using machine learning. Multiclass elements of stand-alone machine learning algorithms (i.e. logistic regression (LR) and artificial neural network (ANN)), decision tree ensembles (i.e. decision fo... Read More about Multiclass stand-alone and ensemble machine learning algorithms utilised to classify soils based on their physico-chemical characteristics.

Experimental study on early age characteristics of lime-GGBS-treated gypseous clays under wet-dry cycles (2021)
Journal Article
Abbey, S. J., Eyo, E. U., & Jeremiah, J. J. (2021). Experimental study on early age characteristics of lime-GGBS-treated gypseous clays under wet-dry cycles. Geotechnics, 1(2), 402-415. https://doi.org/10.3390/geotechnics1020019

Gypseous soils are capable of presenting ground construction challenges to civil and geotechnical engineers due to their unpredictable deformation characteristics. These undesirable responses are sometimes caused by environmental changes in moisture... Read More about Experimental study on early age characteristics of lime-GGBS-treated gypseous clays under wet-dry cycles.

Improved prediction of clay soil expansion using machine learning algorithms and meta-heuristic dichotomous ensemble classifiers (2021)
Journal Article
Eyo, E. U., Abbey, S. J., Lawrence, T. T., & Tetteh, F. K. (2022). Improved prediction of clay soil expansion using machine learning algorithms and meta-heuristic dichotomous ensemble classifiers. Geoscience Frontiers, 13(1), Article 101296. https://doi.org/10.1016/j.gsf.2021.101296

Soil swelling-related disaster is considered as one of the most devastating geo-hazards in modern history. Hence, proper determination of a soil's ability to expand is very vital for achieving a secure and safe ground for infrastructures. Accordingly... Read More about Improved prediction of clay soil expansion using machine learning algorithms and meta-heuristic dichotomous ensemble classifiers.