Department of Mechanical Engineering

Permanent URI for this communityhttps://repository.nileuniversity.edu.ng/handle/123456789/129

Browse

Author: search.filters.author.Jude A. OkolieStart date: 2024

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    A Review of Rare Earth Ion-Doped Glasses: Physical, Optical, and Photoluminescence Properties
    (Trends in Sciences, 2024-10-22) Serifat Olamide Adeleye; Adekunle Akanni Adeleke; Petrus Nzerem; Adebayo Isaac Olosho; Esther Nneka Anosike-Francis; Temitayo Samson Ogedengbe; Peter Pelumi Ikubanni; Rabiatu Adamu Saleh; Jude A. Okolie
    Researchers worldwide have shown significant interest in doping glasses with rare-earth ions. This is particularly intriguing because rare-earth ions are extensively used to enhance the optical properties of host glasses, capitalizing on their unique spectroscopic characteristics due to optical transitions within the intra-4f shell. An in-depth review was conducted on various glass fabrication methods, such as sputtering, solgel, chemical vapor deposition, ion exchange, and direct melt quenching. The study emphasized the physical, optical, and photoluminescence properties of glasses made from glass formers co-doped with rare earth ions. Understanding the interrelationship between these properties is crucial for optimizing material performance across various technological applications. The research highlights the broad applicability of rare-earth-doped glasses in fields like white light emission, photonic devices, solid-state lasers, optical fiber communication, and biomedical applications
  • No Thumbnail Available
    Item
    Enhancing biomass Pyrolysis: Predictive insights from process simulation integrated with interpretable Machine learning models
    (Elsevier, 2024-03-01) Douglas Chinenye Divine; Stell Hubert; Emmanuel I. Epelle; Alaba U. Ojo; Adekunle Akanni Adeleke; Chukwuma C. Ogbaga; Olugbenga Akande; Patrick U. Okoye; Adewale Giwa; Jude A. Okolie
    Waste biomass pyrolysis is a promising thermochemical conversion process for the production of biofuels and sustainable materials. However, it is challenging to accurately predict the properties and yield of products formed during pyrolysis. Machine learning (ML) is a useful tool for predicting the performance of a process. In the present study, ML algorithms integrated with process simulation were explored to accurately model waste biomass pyrolysis based on properties such as H/C, O/ C, oil yield, gas yield, and char yield. Six different ML models including Random Forest (RF), Gradient Boosting Regressor (GBR), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), Artificial Neural Network (ANN), and Stochastic Gradient Descent (SGD) were used to model pyrolysis process. It was found that the out-of-the-box (without optimization) models for RF, XGBoost, ANN, and GBR performed the best and did not benefit from hyperparameter optimization. The GBR was identified as the most effective among various ML models. It accurately predicted yields of gas, biochar, bio-oil yields, and their H/C and O/C compositions. GBR effectively demonstrated the complex relationships between these variables. The box plot showing the root mean squared logarithmic error (RMSE) revealed that the GBR model had the best overall performance with a value less than 0.03. Also, the partial dependence plot and SHAP feature importance were evaluated to better understand each feature’s effect on the output. Lastly, a shareable graphical user interface (GUI) was created to enable researchers explore and predict pyrolysis yield
  • No Thumbnail Available
    Item
    A comprehensive review on the similarity and disparity of torrefied biomass and coal properties
    (Elsevier, 2024-05-09) Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Stephen S. Emmanuel; Moses O. Fajobi; Praise Nwachukwu; Ademidun A. Adesibikan; Jamiu Kolawole Odusote; Emmanuel O. Adeyemi; Oluwaseyi M. Abioye; Jude A. Okolie
    The use of coal for energy generation is facing serious scrutiny because of environmental concerns. As a result, there is a growing global interest in biomass, a renewable and readily available energy source. However, the utilization of biomass comes with significant drawbacks, including its heterogeneity, low bulk density, and calorific value. Biomass also has a low energy content, high moisture, poor grindability, and high volatile matter, which affect its handling, bulk transportation, and storage. Torrefaction technology has been employed in previous works to improve the properties of biomass for subsequent handling and transportation and for low-cost energy generation. Since coal is a promising precursor for energy generation, it is imperative to compare the physicochemical properties of coal with that of torrefied biomass. Therefore, this study aims to conduct a comprehensive comparison between various grades of coal and torrefied biomass. The review revealed that torrefied biomass could replace coal, as its properties are similar to those of coal, except for high-grade coals. The proximate and ultimate analyses of coals (lignite and bituminous) were found to be comparable to various torrefied biomass materials. The fuel ratio (0.5–2.0), and higher heating values (16,100–19,000 kJ/kg) of coal and torrefied biomass were within the range useful for coal-fired plants. Additionally, ash analyses, ash fusion temperature, hygroscopic tendency, functional group study, and microstructural comparison were reviewed in this study. The results from various studies have shown close similarities with only small disimilarities in the fuel properties between coal and torrefied biomass. Therefore, torrefied biomass is proposed as a complimentary feedstock to coal in various applications.