Browsing by Author "Onyia, Michael E."

Now showing 1 - 7 of 7
  • Thumbnail Image
    Item
    Application of 3‑algorithm ANN programming to predict the strength performance of hydrated‑lime activated rice husk ash treated soil
    (Multiscale and Multidisciplinary Modeling, Experiments and Design, 2021) Onyelowe, Kennedy C.; Iqbal, Mudassir; Jalal, Fazal E.; Onyia, Michael E.; Onuoha, Ifeanyichukwu C.
    Artificial neural network (ANN) method has been applied in the present work to predict the California bearing ratio (CBR), unconfined compressive strength (UCS), and resistance value (R) of expansive soil treated with recycled and activated composites of rice husk ash. Pavement foundations suffer from poor design and construction, poor material handling and utilization and management lapses. The evolutions of soft computing techniques have produced various algorithms developed to overcome certain lapses in performance. Three of such algorithms from ANN are Levenberg–Muarquardt Backpropagation (LMBP), Bayesian Programming (BP), and Conjugate Gradient (CG) algorithms. In this work, the expansive soil classified as A-7-6 group soil was treated with hydrated-lime activated rice husk ash (HARHA) in varying proportions between 0.1 and 12% by weight of soil at the rate of 0.1% to produce 121 datasets. These were used to predict the behavior of the soil’s strength parameters (CBR, UCS and R) utilizing the evolutionary hybrid algorithms of ANN. The predictor parameters were HARHA, liquid limit (wL), (plastic limit (wP), plasticity index (IP), optimum moisture content (wOMC), clay activity (AC), and (maximum dry density (δmax). A multiple linear regression (MLR) was also conducted on the datasets in addition to ANN to serve as a check and linear validation mechanism. MLR and ANN methods agreed in terms of performance and fit at the end of computing and iteration. However, the response validation on the predicted models showed a good correlation above 0.9 and a great performance index. Comparatively, the LMBP algorithm yielded an accurate estimation of the results in lesser iterations than the Bayesian and the CG algorithms, while the Bayesian technique produced the best result with the required number of iterations to minimize the error. And finally, the LMBP algorithm outclassed the other two algorithms in terms of the predicted models’ accuracy.
  • Thumbnail Image
    Item
    Application of Gene Expression Programming to Evaluate Strength Characteristics of Hydrated-Lime-Activated Rice Husk Ash-Treated Expansive Soil
    (Applied Computational Intelligence and Soft Computing, 2021) Onyelowe, Kennedy C.; Jalal, Fazal E.; Onyia, Michael E.; Onuoha, Ifeanyichukwu C.; Alaneme, George U.
    Gene expression programming has been applied in this work to predict the California bearing ratio (CBR), unconfined compressive strength (UCS), and resistance value (R value or Rvalue) of expansive soil treated with an improved composites of rice husk ash. Pavement foundations suffer failures due to poor design and construction, poor materials handling and utilization, and management lapses. -e evolution of sustainable green materials and optimization and soft computing techniques have been deployed to improve on the deficiencies being suffered in the abovementioned areas of design and construction engineering. In this work, expansive soil classified as A-7-6 group soil was treated with hydrated-lime activated rice husk ash (HARHA) in an incremental proportion to produce 121 datasets, which were used to predict the behavior of the soil’s strength parameters utilizing the mutative and evolutionary algorithms of GEP. -e input parameters were HARHA, liquid limit (wL), (plastic limit (wP), plasticity index (IP), optimum moisture content (wOMC), clay activity (AC), and (maximum dry density (δmax) while CBR, UCS, and R value were the output parameters. A multiple linear regression (MLR) was also conducted on the datasets in addition to GEP to serve as a check mechanism. At the end of the computing and iterations, MLR and GEP optimization methods proposed three equations corresponding to the output parameters of the work. -e responses validation on the predicted models shows a good correlation above 0.9 and a great performance index. -e predicted models’ performance has shown that GEP soft computing has predicted models that can be used in the design of CBR, UCS, and R value for soils being used as foundation materials and being treated with admixtures as a binding component.
  • Thumbnail Image
    Item
    Hydraulic conductivity predictive model of RHA-ameliorated laterite for solving landfill liner leachate, soil and water contamination and carbon emission problems
    (International Journal of Low-Carbon Technologies, 2022) Onyelowe, Kennedy C.; Ebid, Ahmed M; Baldovino, Jair de Jesús Arrieta; Onyia, Michael E.
    The environment is seriously being affected by the leachate release at the unconstructed and badly constructed waste containment or landfill facilities around the globe. The worst hit is the developing world where there is little or totally no waste management system and facilities to receive waste released into the atmosphere. This research work is focused on the leachate drain into the soil and the underground water from landfills, which toxicifies both the soil and the water. Also, the construction of the liner or barrier with cement poses serious threat to the environment due to oxides of carbon release and this research also took this into account by replacing the utilization of cement with rice husk ash (RHA), which has proven to have the potentials of replacing cement as a supplementary binder. Laboratory tests were conducted to determine the hydraulic conductivity (K) of lateritic soil (LS) ameliorated with different dosages of RHA. Other hydromechanical properties of the treated blend were studied and multiple data were generated for the artificial neural network (ANN) back-propagation (-BP), genetic algorithm (GA) and gradual reducing gradient (GRG), genetic programming (GP) and evolutionary polynomial regression (EPR) prediction exercises. Results show that the LS was a poorly graded A-2 sandy silt soil, which was subjected to three different compaction energies with the minimum of the British standard light (BSL) and derived k of 6.95E-10, 50.75E-10 and 32.33E-10 for BSL, west African standard and British standard heavy, respectively. The RHA addition improved the studied properties of the ameliorated LS. Out of the five models, the ANN-GRG outclassed others with a performance of 99% with minimal error compared with the rest. Potentially, this research has shown that RHA with a pozzolanic chemical moduli of 81.47% can replace cement in the construction of ecofriendly and more efficient landfills and waste containemnt barriers to save the soil and the underground water as well as the environment from leachate contamination and carbon emissions.
  • Thumbnail Image
    Item
    Morphology and mineralogy of rice husk ash treated soil for green and sustainable landfill liner construction
    (Cleaner Materials, 2021) Onyelowe, Kennedy C.; Obianyo, Ifeyinwa I.; Onwualu, Azikiwe P.; Onyia, Michael E.; Moses, Chima
    The morphology and mineralogy of the soil treated with rice husk ash (RHA) under different molding moisture conditions. Leachate condition in landfills built with compacted clay soil is damaging the underground water flow with the hazards released from disposed and decomposing waste materials. This makes landfills dangerous infrastructure. The leakage can be dealt with through the deployment of green materials developed from agricultural waste. One of such wastes is rice husk combusted to derive ash. The test soil used in this exercise has been classified as highly plastic and poorly graded. The treated soil was examined by scanning electron microscopy and x‐ray diffractometer methods. From the test results, the presence of goethite alongside quartz and kaolinite were observed in the XRD (X‐ray Diffraction) spectra of 6% and 10 % RHA treated soil. The Goethite possessing an inner needle‐like structure with a closed packed striated structure makes the composite a promising material for constructing landfill liners. This is because the closed packed striated structure of the goethite present in the composite will slow down the vertical seepage of leachate to allow its collection and removal by the leachate collection system. The composite will form a barrier between groundwater, soil, and substrata, and waste. From the SEM (Scanning Electron Microscopy), the uniformly distributed grain boundaries and smaller grain size of the composite (lateritic soil and RHA) will serve as a barrier to the movement of contaminants and other leachates to the groundwater and thus, making the composite a viable material for landfill liner system.
  • Thumbnail Image
    Item
    Pozzolanic Reaction in Clayey Soils for Stabilization Purposes: A Classical Overview of Sustainable Transport Geotechnics
    (Advances in Materials Science and Engineering, 2021) Onyelowe, Kennedy C.; Onyia, Michael E.; Bui Van, Duc; Baykara, Haci; Ugwu, Hyginus U.
    Problematic soil stabilization processes involve the application of binders to improve the engineering properties of the soil. /is is done to change the undesirable properties of these soils to meet basic design standards. However, very little attention has been given to the reactive phase of soil stabilization. /is phase is the most important in every stabilization protocol because it embodies the reactions that lead to the bonding of the dispersed particles of clayey soil. Hence, this reactive phase is reviewed. When clayey soils which make up the greatest fraction of expansive soil come in contact with moisture, they experience volume changes due to adsorbed moisture that forms films of double diffused layer on the particles. When this happens, the clayey particles disperse and float, increasing the pore spaces or voids that exist in the soil mass. Stabilizations of these soils are conducted to close the gaps between the dispersed clayey soil particles. /is is achieved by mixing additives that will release calcium, aluminum, silicon, etc., in the presence of adsorbed moisture, and a hydration reaction occurs. /is is followed by the displacement reaction based on the metallic order in the electrochemical series. /is causes a calcination reaction, a process whereby calcium displaces the hydrogen ions of the dipole adsorbed moisture and displaces the sodium ion responsible for the swelling potential of clayey soils. /ese whole processes lead to a pozzolanic reaction, which finally forms calcium alumina-silica hydrate. /is formation is responsible for soil stabilization.
  • Thumbnail Image
    Item
    Predicting nanocomposite binder improved unsaturated soil UCS using genetic programming
    (Nanotechnology for Environmental Engineering, 2021) Onyelowe, Kennedy C.; Ebid, Ahmed M.; Onyia, Michael E.; Nwobia, Light I.
    The ability of the compacted soils and treated/compacted soils to withstand loads as foundation materials depends on the stability and durability of the soils. The design of such phenomena in treated soils whether as subgrade of pavements or embankments, backfills, etc., is a crucial phase of foundation constructions. Often, it is observed that soil mechanical and structural properties fall below the minimum design and construction requirements and this necessitates the stabilization in order to improve the needed properties. It can be observed that for this reason, there is a steady use of the laboratory and equipment prior to any design and construction as the case may be. In this work, genetic programming (GP) has been employed to predict the unconfined compressive strength of unsaturated lateritic soil treated with a hybridized binder material called hybrid cement (HC), which was formulated by blending nanotextured quarry fines (NQF) and hydrated lime activated nanotextured rice husk ash. Tests were conducted to generate multiple values for output and inputs parameters, and the values were deployed into soft computing technique to forecast UCS adopting three (3) different performance complexities (2, 3 and 4 levels of complexity). The results of the prediction models show that the four (4) levels of complexity GP model outclassed the others in performance and accuracy with a total error (SSE) of 2.4% and coefficient of determination (R2) of 0.991. Generally, GP has shown its robustness and flexibility in predicting engineering problems for use in design and performance evaluation.
  • Thumbnail Image
    Item
    Swelling Potential of Clayey Soil Modified with Rice Husk Ash Activated by Calcination for Pavement Underlay by Plasticity Index Method (PIM)
    (Advances in Materials Science and Engineering, 2021) Onyelowe, Kennedy C.; Onyia, Michael E.; Nguyen-Thi, Diu; Bui Van, Duc; Onukwugha, Eze; Baykara, Haci; Obianyo, Ifeoma. I.; Dao-Phuc, Lam; Ugwu, Hyginus U.
    Volume change in expansive soils is a problem encountered in earth work around the world. ,is is prominent with hydraulically bound structures or foundations subjected to prolonged moisture exposure. ,is behavior of clayey used as subgrade, foundation, landfill, or backfill materials causes undesirable structural functionality and failures. To prevent this happening, clayey soils are studied for possible volume change potential and degree of expansion. Consequently, the problematic soils are stabilized. In this work, the stabilization of clayey highly expansive soil classified as A-7-6 soil and highly plastic with high clay content was conducted under laboratory conditions. ,e treatment exercise was experimented using quicklime-activated rice husk ash (QARHA), hydrated lime-activated rice husk ash (HARHA), and calcite-activated rice husk ash (CARHA) at the rates of 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, and 10%. Upon treatment with the three calcium compounds to produce three sets of treated experimental specimens, the plasticity index was observed and recorded and swelling potentials were evaluated using the plasticity index method (PIM). ,e results showed a consistent improvement on the properties of the treated soil with the addition of the different activated admixtures. While the utilization of CARHA and HARHA improved the clayey soil to medium expansive soil, the treated clayey soil substantially improved from highly expansive soil with a potential of 23.35% to less expansive with a final potential of 0.59% upon the addition of 10% QARHA. Finally, QARHA was adjudged as the best binding composite due to the highest rate of reduction recorded with its utilization.