Yazar "Ekwueme, Godspower Onyekachukwu" seçeneğine göre listele

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    Biobased hybrid composite design for optimum hardness and wear resistance
    (Elseiver, 2023) Okafor, Christian Emeka; Sunday, Iweriolor; Ani, Okwuchukwu Innocen; Akçakale, Nürettin; Ekwueme, Godspower Onyekachukwu; Ugwu, Peter Chukwuemeka; Nwanna, Emmanuel Chukwudi
    The present investigation considered the design of a biobased hybrid particulate composite for optimal hardness and wear resistance. Tests were conducted based on the plan of 20 sets of experiments generated through ModelBased Calibration ToolboxTM contained in MATLAB routines. A Portable Ultrasonic Hardness tester was used to record the hardness properties while the wear behavior of the composite was tested using a pin-on-disk machine. The optimization study was applied to the Calibration Generation (CAGE) platform utilizing the Normal Boundary Intersection (NBI) algorithm which enables the development of a Pareto optimal set with a continuous and equally distributed chart. Scanning Electron Microscopy (SEM) was used to perform morphological examination. From the optimized results, it was observed that a particle size of 1752 mu m, a volume fraction of 45%, and a stirring time of 70 s gave the best-ranked composite exhibiting optimal values of 784.91 Leeb hardness, 643.19 Rockwell hardness, 593.17 Brinell hardness, and 0.000139 mm3/Nm specific wear rate. Under the same conditions, the predicted values of the optimization model closely matched the experimental results. The NBI optimization technique proves to be a viable method for performing material design and property improvement tasks. Surface morphology analysis via SEM revealed that the wearing of bio-based hybrid particulate composite parts is associated with delamination and abrasion mechanisms. It is implied that the new material can be used for applications such as furniture, automotive spare parts, and other inexpensive technical solutions.
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    Intelligent modeling of carbonized wood-silicon dioxide filled natural rubber composite for outer shoe sole manufacturing
    (KeAi Publishing Communications Ltd., 2024) Okafor, Christian Emeka; Iweriolor, Sunday; Nwekeoti, Chukwunakueze Arinze; Akçakale, Nürettin; Ekwueme, Godspower Onyekachukwu; Ihueze, Christopher Chukwutoo; Ekengwu, Ignatius Echezona
    Large amount of wood dust is created as a byproduct of woodworking activities. Every year, there is an increase in wood dust generation, which severely pollutes the environment. Consequently, it becomes imperative to use wood dust in the production of useful products. A Carbonized Wood-Silicon Dioxide Filled Natural Rubber Composite (CWSDFNRC) was therefore created in this work using a compression molding method. The friction and compression properties of the composites were determined. Modeling of the composite's mechanical and friction characteristics was done using artificially intelligent techniques including Response Surface Methodology (RSM), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The novel material was thermally analyzed using Dynamic Mechanical Analysis (DMA), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), and Differential Thermal Analysis (DTA). The effectiveness of RSM, ANN, and ANFIS was demonstrated by relevant error indices. The optimization method revealed the ideal level of fitness at particle size, carbonization temperature, filler content, curing temperature, curing pressure, and curing time of 150 ?m, 214 °C, 51 phr, 150 °C, 3 Pa, and 10 min respectively. These fitness conditions gave an optimal value of 17.63 MPa for compressive strength and a friction coefficient of 0.96. The novel material's characteristics contrasted well with those of comparable materials described in the literature, suggesting that it has the potential to be used in the manufacture of outer shoe soles and other elastomeric applications. © 2023 The Authors