Udeme Udo Imoh
58512216800
Publications - 10
Performance of Concrete Incorporating Waste Glass Cullet and Snail Shell Powder: Workability and Strength Characteristics
Publication Name: Buildings
Publication Date: 2025-07-01
Volume: 15
Issue: 13
Page Range: Unknown
Description:
This study investigates the combined use of waste glass cullet (WGC) and snail shell powder (SSP) as a sustainable binary cementitious system to enhance the mechanical performance and durability of concrete, particularly for rigid pavement applications. Nine concrete mixes were formulated: a control mix, four mixes with 5%, 10%, 15%, and 20% WGC as partial cement replacement, and four corresponding mixes with 1% SSP addition. Slump, compressive strength, and flexural strength were evaluated at various curing ages. Results showed that while WGC reduced workability due to its angular morphology (slump decreased from 30 mm to 20 mm at 20% WGC), the inclusion of SSP slightly mitigated this reduction (21 mm at 20% WGC + 1% SSP). At 28 days, compressive strength increased from 40.0 MPa (control) to 45.0 MPa with 20% WGC and further to 48.0 MPa with the addition of SSP. Flexural strength also improved from 7.0 MPa (control) to 7.8 MPa with both WGC and SSP. These improvements were statistically significant (p < 0.05) and supported by correlation analysis, which revealed a strong inverse relationship between WGC content and slump (r = −0.97) and strong positive correlations between early and later-age strength. Microstructural analyses (SEM/EDX) confirmed enhanced matrix densification and pozzolanic activity. The findings demonstrate that up to 20% WGC with 1% SSP not only enhances strength development but also provides a viable, low-cost, and eco-friendly alternative for producing durable, load-bearing, and sustainable concrete for rigid pavements and infrastructure applications. This approach supports circular economic principles by valorizing industrial and biogenic waste streams in civil construction.
Open Access: Yes
Analysis and Prediction of Traffic Conditions Using Machine Learning Models on Ikorodu Road in Lagos State, Nigeria
Publication Name: Infrastructures
Publication Date: 2025-05-01
Volume: 10
Issue: 5
Page Range: Unknown
Description:
Traffic counts are essential for assessing road capacity to provide efficient, effective, and safe mobility. However, current methods for generating models for traffic count studies are often limited in their accuracy and applicability, which can lead to incorrect or imprecise estimates of traffic volume. This study focused on analyzing and predicting traffic conditions on Ikorodu Road in Lagos State. The analysis involved an examination of historical traffic data, specifically focusing on daily and hourly traffic volumes. The prediction involved the use of machine learning models, including decision trees, gradient boosting, and random forest classifiers. The results of this study revealed significant variations in traffic volume across different days of the week and times of the day, indicating peak and off-peak periods. The study also highlighted the need for a more comprehensive approach that includes additional factors, such as weather conditions, road work, and special events, which could significantly impact traffic volume.
Open Access: Yes
Micro-mechanical characterization of polymer-modified asphalt mixtures using discrete element modelling with soft-bond and linear contact bond models
Publication Name: Construction and Building Materials
Publication Date: 2025-11-28
Volume: 501
Issue: Unknown
Page Range: Unknown
Description:
Polymer-modified asphalt (PMA) mixtures offer improved performance compared with conventional binders, particularly in terms of crack resistance and durability under increasing traffic and environmental loading. However, capturing their micromechanical behavior and failure mechanisms remains challenging owing to their internal heterogeneity and particle-scale interactions. This study utilized the Discrete Element Method (DEM), implemented via the Particle Flow Code (PFC), to simulate Uniaxial Compressive Strength (UCS) and Indirect Tensile Strength (ITS) tests on PMA mixtures with varying specimen sizes and aggregate gradations. Two contact models, Linear Contact Bond (LCB) and Soft Bond (SB), were evaluated to represent tensile fracture and progressive bond degradation. The numerical models were calibrated and validated against the experimental results, which showed a deviation of less than 1.5 % in the compressive strength and modulus across the nine PMA formulations. A strength-size effect was observed and modeled, enabling the conversion of non-standard field core strengths to laboratory-equivalent values. Additionally, a high-resolution image dataset of asphalt surface distress (cracks, potholes, and marking degradation) was developed to support computer vision–based pavement monitoring. The integrated simulation and imaging framework presented in this study offers new insights into microscale failure behavior, supports more accurate field data interpretation, and contributes to intelligent maintenance strategies for resilient pavement infrastructure.
Open Access: Yes
Mechanistic and comparative laboratory assessment of lime dosage and uniaxial geogrid on the strength and durability of classified lateritic subgrade
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
This study presents a mechanistic and comparative laboratory assessment of lime stabilization and uniaxial geogrid reinforcement, applied independently and in combination, to improve the engineering performance of a classified A-7-6 (CL–ML) lateritic subgrade from Ogun State, Nigeria. The objective was to evaluate the effect of lime dosage and geogrid inclusion on the short- and long-term California Bearing Ratio (CBR), Unconfined Compressive Strength (UCS), and Resilient Modulus (MR), and to test the hypothesis that chemical and mechanical stabilization mechanisms act synergistically to enhance stiffness and durability. Quicklime (CaO > 90%) was added at 2–8% by dry weight, while the geogrid used was uniaxial polypropylene with an aperture size of 30 mm and tensile strength of 22 kN/m. Specimens were prepared by mixing, compacting, and curing at 25 ± 2 °C and 95 ± 2% RH for 7, 14, and 28 days, then tested according to ASTM and AASHTO standards. Each condition was replicated thrice, and the data were analyzed using one-way ANOVA (p < 0.05). Results showed that lime treatment reduced the plasticity index from 30 ± 1.2 to 6 ± 0.5%, increased UCS from 300 ± 15 to 950 ± 40 kPa and improved soaked CBR from 23 ± 1.1 to 57.5 ± 2.3% after 28 days. Single and double geogrid layers enhanced soaked CBR to 33 ± 1.4% and 43 ± 1.7%, respectively, with negligible strength loss after three moisture cycles, confirming durability under wetting–drying conditions. Combined lime–geogrid stabilization achieved the highest performance, with CBR > 65%, MR > 90 MPa, and UCS > 1.0 MPa, exceeding AASHTO subgrade requirements. The findings demonstrate that lime primarily enhances chemical bonding, whereas geogrid reinforcement improves mechanical confinement; their combination offers a durable, cost-effective, and low-carbon alternative to conventional cement stabilization for tropical lateritic subgrades.
Open Access: Yes
Metakaolin-Enhanced Laterite Rock Aggregate Concrete: Strength Optimization and Sustainable Cement Replacement
Publication Name: Buildings
Publication Date: 2025-12-01
Volume: 15
Issue: 24
Page Range: Unknown
Description:
The growing demand for concrete in tropical regions faces two unresolved challenges: the high carbon footprint of ordinary Portland cement (OPC) and limited understanding of how supplementary cementitious materials affect the mechanical performance of laterite rock aggregates concrete. Although metakaolin (MK) is a highly reactive pozzolan, its combined use with laterite rock aggregates concrete and its influence on strength development and microstructure have not been sufficiently clarified. This study investigates the mechanical behavior and sustainability potential of laterite rock aggregate concrete in which OPC is partially replaced by MK at 0%, 5%, 10%, 15%, and 20% by weight. All mixes were prepared at a constant water–binder ratio of 0.50 and tested for workability, compressive strength, split-tensile strength, and flexural strength at 7, 14, and 28 days, with and without a polycarboxylate-based superplasticizer. The results show that MK significantly enhances the mechanical performance of laterite rock concrete, with an optimum at 10% replacement: the 28-day compressive strength increased from 35.6 MPa (control) to 53.9 MPa in the superplasticized mix, accompanied by corresponding gains in tensile and flexural strengths. SEM–EDS analyses revealed microstructural densification, reduced portlandite, and a refined interfacial transition zone, explaining the improved strength and cracking resistance. From an environmental perspective, a 10% MK replacement corresponds to an approximate 10% reduction in clinker-related CO2 emissions, while the use of locally available laterite rock reduces the dependence on quarried granite and transportation impacts. The findings demonstrate that MK-modified laterite rock concrete is a viable and eco-efficient option for structural applications in tropical regions. The study concludes that MK-enhanced laterite rock aggregate concrete can deliver higher structural performance and improved sustainability without altering conventional mix design and curing practices.
Open Access: Yes
Effect of Sugarcane Bagasse Ash on the sustainable performance of hot-mix asphalt: A case study of experimental and numerical analysis
Publication Name: Case Studies in Construction Materials
Publication Date: 2026-07-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
The growing demand for sustainable road infrastructure has intensified the interest in alternative mineral fillers that reduce natural resource consumption and environmental impacts. This study investigates the use of Sugarcane Bagasse Ash (SBA), an abundant agricultural by-product in sub-Saharan Africa, as a partial replacement for conventional mineral fillers in hot-mix asphalt (HMA). Unlike previous studies that considered SBA primarily as a minor additive, this study provides a systematic evaluation across a wide replacement range (0–16 %), combined with experimental testing and numerical validation. Marshall and indirect tensile strength (ITS) tests were conducted on HMA mixtures produced using locally sourced Nigerian aggregates and 60/70 penetration-grade bitumen. A three-dimensional finite element model (FEM) of the ITS configuration was developed to corroborate the experimental response and identify stress concentration zones. results indicate that SBA improves both mechanical and volumetric performance within an optimal replacement range of 6–10 %, with peak performance of approximately 8 % SBA. Within this range, Marshall stability increased from 7.6 kN to 9.0 kN, the Marshall quotient reached 3.3 kN/mm, bulk density increased to 2.51 g/cm³, and air voids decreased from 4.9 % to 3.5 %, remaining within standard design limits. Microstructural analyses confirmed the predominance of amorphous silica and porous SBA morphology, which promoted enhanced filler–binder interactions and mixture densification. FEM predictions of peak tensile stress agreed with laboratory ITS results within 10 % and successfully reproduced observed crack initiation zones. Excessive SBA content (> 10 %) led to reduced stability and density owing to over-filling effects. The findings demonstrate that 6–10 % SBA is a technically viable and sustainable filler replacement for HMA, particularly in sugarcane-producing regions, offering improved performance alongside waste valorization and reduced reliance on quarry-derived fillers.
Open Access: Yes
Mechanical and microstructural performances of hot-mix asphalt modified with recycled polyethylene terephthalate
Publication Name: Results in Engineering
Publication Date: 2026-03-01
Volume: 29
Issue: Unknown
Page Range: Unknown
Description:
The increasing accumulation of plastic waste and the persistent durability challenges associated with conventional asphalt pavements have prompted the search for sustainable material modifications. Among potential additives, recycled polyethylene terephthalate (RPET) has emerged as a promising modifier capable of enhancing pavement performance while supporting environmental sustainability. This study investigated the mechanical and microstructural behavior of hot-mix asphalt (HMA) modified with RPET using a drying process. RPET was incorporated at proportions ranging from 0% to 10% of the total mix mass, and the mixtures were evaluated through Marshall stability and flow, uniaxial compressive strength, indirect tensile strength, rutting resistance, dynamic modulus, semi-circular bending, moisture sensitivity, and scanning electron microscopy. Results indicate that RPET significantly improves HMA performance up to an optimal content of 8%. At this dosage, Marshall stability increased from 6.40 to 11.97 kN, while flow decreased from 11.67 to 5.17 mm, demonstrating enhanced stiffness and resistance to permanent deformation. UCS and ITS rose from 1.10 to 1.85 MPa and 0.165 to 0.278 MPa, respectively, and rutting depth declined from 5.0 to 3.0 mm. Additionally, the dynamic modulus increased from 1500 to 2500 MPa, and the SCB increased from 320 to 590 J/m², confirming the enhanced cracking resistance. SEM analysis revealed stronger binder–aggregate interaction at intermediate RPET levels, whereas excessive RPET (10%) caused particle agglomeration and slight performance reductions. The findings show that RPET improves hot mix asphalt mainly through physical reinforcement and microstructural densification, with optimal dosage offering a sustainable way to enhance pavement durability while reducing plastic waste.
Open Access: Yes
Developing a mix-specific NDT model for compressive strength prediction of concrete using local Nigerian materials
Publication Name: Results in Engineering
Publication Date: 2026-06-01
Volume: 30
Issue: Unknown
Page Range: Unknown
Description:
Accurate estimation of concrete compressive strength using non-destructive testing (NDT) methods remains challenging because widely used empirical correlations often neglect key mix design parameters, particularly the water–cement (w/c) ratio. This study investigates the influence of the w/c ratio on concrete compressive strength and on the predictive performance of combined rebound hammer (RH) and ultrasonic pulse velocity (UPV) models through controlled laboratory experiments using locally sourced Nigerian materials. Six concrete mixes with w/c ratios ranging from 0.45 to 0.70 were prepared with a constant 1:1:2 mix proportion and tested at curing ages of 7, 14, and 28 days. RH and UPV measurements were conducted on laboratory-cured cube specimens and correlated with compressive strength obtained from standard destructive tests. Pearson correlation analysis revealed strong positive relationships between compressive strength and RH (r = 0.96) and UPV (r = 0.93), while increasing w/c ratio consistently reduced both strength and NDT responses. A multivariate regression model incorporating RH, UPV, and curing age was developed to predict compressive strength across the investigated mixes. The model achieved a coefficient of determination (R²) of 0.79 with low prediction errors (RMSE = 1.46 MPa; MAE = 1.26 MPa). Comparative analysis showed that the proposed model outperformed single-parameter approaches and highlighted the limitations of generic SonReb correlations when applied without local calibration. The results demonstrate that reliable NDT-based strength prediction is strongly mix-sensitive and requires locally calibrated models for accurate laboratory-based quality control.
Open Access: Yes
Rutting Resistance and Fatigue Performance of Crumb Rubber-Modified Asphalt Concrete: Experimental Investigation and Mechanistic–Empirical Modeling
Publication Name: Infrastructures
Publication Date: 2026-04-01
Volume: 11
Issue: 4
Page Range: Unknown
Description:
Crumb rubber-modified asphalt concrete (CMAC) has gained increasing attention as a sustainable pavement material capable of improving mechanical performance while utilizing waste tire resources. This study investigates the rutting resistance and fatigue behavior of CMAC using a combined experimental and mechanistic–empirical modeling approach. Asphalt mixtures containing 0–25% crumb rubber by binder weight were prepared and evaluated through Marshall stability and indirect tensile fatigue tests, whereas Fourier-transform infrared spectroscopy (FTIR) was used to examine binder–rubber interactions. The results indicate that crumb rubber significantly influences both the volumetric and mechanical properties of asphalt mixtures. Mixtures containing 10–15% crumb rubber exhibited optimal performances, achieving up to 36% higher Marshall stability and improved fatigue life compared with conventional asphalt mixtures. FTIR analysis revealed that rubber particle swelling and limited chemical interactions enhanced binder elasticity and improved binder–aggregate compatibility. However, excessive rubber content (≥20%) resulted in reduced stability owing to increased binder absorption and decreased effective binder film thickness. A mechanistic–empirical model incorporating viscoelastic, viscoplastic, and fatigue damage parameters successfully reproduced the experimental trends and identified the same optimal rubber content range. The findings demonstrate that CMAC with a moderate rubber content can enhance pavement durability and structural performance while promoting environmentally sustainable road construction through the reuse of waste tires.
Open Access: Yes
Hybrid generative–ensemble approach for predicting recycled aggregate concrete strength properties
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
This study proposes a hybrid generative–ensemble framework to predict key mechanical properties of recycled aggregate concrete from mix proportions. An established database of 112 mixes was used to model compressive strength, split tensile strength, flexural strength, and elastic modulus. To mitigate data scarcity, a conditional variational autoencoder was trained on the training data only and used to generate additional physically plausible input samples, after which seven supervised learning algorithms were trained and compared using cross-validation. Gradient boosting and support vector regression achieved the most accurate and stable predictions across all targets, outperforming baseline linear models and commonly used empirical correlations. Feature-attribution analysis was used to identify the dominant drivers of each property, showing that binder-related variables primarily govern strength, while aggregate-related variables dominate stiffness. The results support practical, data-driven screening of recycled aggregate concrete mixes and provide interpretable guidance for sustainable mix design.
Open Access: Yes
