CINXE.COM

<rss version="2.0"> <channel> <title>International Journal of Engineering Research in Africa</title> <link>https://www.scientific.net/JERA</link> <description>Latest Results for International Journal of Engineering Research in Africa</description> <language>en-us</language> <image> <title>International Journal of Engineering Research in Africa</title> <link>https://www.scientific.net</link> <url>https://www.scientific.net/Image/JournalCover/17</url> </image> <item> <title>Study on Diffusion Characteristics of Liquid Water in Gas Diffusion Layer by Lattice Boltzmann Method</title> <link>https://www.scientific.net/JERA.71.1</link> <guid>10.4028/p-3yl8Ms</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Sheng Zheng Ji, Zhuang Song, Ying He The gas diffusion layer (GDL) is a crucial component of Proton Exchange Membrane Fuel Cells (PEMFC), water flooding will occur during the operation of PEMFC, resulting in performance degradation, and its water management plays a significant role in PEMFC performance. To investigate the transport mechanism of liquid water in GDL, the lattice Boltzmann method to simulate the behavior of GDL droplets using the 'random reconstruction' method. The accuracy of this model by calculating the tortuosity and comparing it with reported results in literature. The effects of different GDL structural parameters on permeability were studied. Finally, the conductivity and thermal conductivity of the GDL in various directions were examined. The results indicate that the porosity error of the three-dimensional structure model of GDL is within 0.01, enabling a realistic simulation of the GDL structure. The average error between the calculated results and the Bruggeman equation is only 2.5362%, and the average error compared to the reference results is less than 6%, demonstrating the model's high accuracy. As the porosity and fiber diameter of the GDL three-dimensional structure model increase, the permeability also increases. Conversely, the permeability decreases with an increase in the thickness of the GDL three-dimensional structure model. Moreover, an increase in GDL porosity leads to a gradual decrease in electrical conductivity and thermal conductivity in both the thickness and plane directions, with a more pronounced effect on the thickness. This study uncovers the transport characteristics of liquid water in the gas diffusion layer, which can inform the optimization of GDL structure design and serve as a theoretical reference for enhancing water management in proton exchange membrane fuel cells. Future research directions will focus on further optimizing the three-dimensional structure of GDL to improve its transmission characteristics and overall performance. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:50 +0100</feedDate> </item> <item> <title>Thermal Inertia Performance via TRNSYS Software of Recycled Wastewater Treatment Plant Sludge as a Construction Material Additive to Ecological Lightweight Earth Bricks</title> <link>https://www.scientific.net/JERA.71.17</link> <guid>10.4028/p-5sLqfi</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Ghizlane El Hajoui, Imad Manssouri, Tajeddine Manssouri, Hassane Sahbi, Houssame Limami This research investigates the thermal performance of earth bricks made with different percentages of wastewater sludge additive (0%, 1%, 3%, 7%, 15%, 20%) in terms of cooling and heating loads, time lag and decrement factor. The simulation of a reference house (2.5m,10m,6m) using TRNSYS software allows for the evaluation of these parameters, external wall thicknesses, bulk density, thermal conductivity, and specific heat capacity are employed as inputs in dynamic thermal inertia model. The results showed that the use of bricks with higher sludge additive percentages resulted in a drop in cooling and heating loads, the lowest cooling and heating loads of 1720 KWH and 1534 KWH respectively were recorded with the highest percentage of wastewater sludge additive of 20% and the biggest wall thickness of 30cm, it was also noted that the use of higher wastewater sludge additive percentages and bigger wall thicknesses led to higher time lags and lower decrement factor, the highest time lag of 15 hours and the lowest decrement factor of 0.019 were as well recorded with the highest wastewater sludge additive of 20%, and the biggest wall thickness of 30cm. These results were attributed to the higher specific heat capacity, and lower thermal conductivity of the bricks with higher wastewater sludge additive percentages. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:50 +0100</feedDate> </item> <item> <title>Evaluation of the Performance of Fiber-Reinforced Mortars Based on Dredged Sludge</title> <link>https://www.scientific.net/JERA.71.31</link> <guid>10.4028/p-KiAW2W</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Salhi Mohamed, Benyahia Amar, Alex Li, Toufik Boubekeur, Ashraf Ashour, Choucha Said River-carried solids, especially during floods, lead to dam sedimentation. Dredging extends dam life, but excess unusable sediment storage threatens the environment. The aim of this work is to investigate the influence of the recovery of calcined mud from Chorfa dam on the physico-mechanical and chemical characteristics of mortars fiber bundles. The sludge is used as a partial substitute for cement by volume at rates of 10%, 15%, 20% and 25%. All test specimens had water / binder (W/B) ratio and steel fibers ratio. Testing programme included measuring the fluidity, ultrasonic pulse velocity test, dynamic modulus of elasticity, flexural and compressive strengths. Compared to the control mortar, the fluidity represented by the diameter of M0, M15 and M25 mixtures decreased by approximately 11%, 14% and 22%, respectively. The compressive strength of M15 increased by 17.4% at 28 days, compared with the control specimen. At 7 days, the ultrasonic speed of the M25 mixture decreases by 1.7% compared to that of M15. The dynamic modulus of elasticity of M20 and M25 increases by 13% and 12% as the age ranges from 2 to 28 days. At 28 days, the flexural strength of the M20 blends increased by approximately 64%. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>Mechanical Behavior Analysis of Lightweight Concrete Reinforced by Metalized Plastic Waste Fibers</title> <link>https://www.scientific.net/JERA.71.45</link> <guid>10.4028/p-NGvb4Z</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Maher Chakhari, Nawel Salem, Rachida Idir, Jamel Neji This study evaluates the impact of adding metalized plastic waste (MPW) fibers to lightweight concrete that is used as a filler material in building slopes and bridge ramps. The goal is to open up new opportunities for recycling plastic waste and promote a more sustainable and productive construction industry. This study examined the mechanical behavior of lightweight concrete (LC) at 3, 28, and 90 days, both with and without MPW fiber (1%, 2%, and 3%). Compression tests, 3-point bending tests, and pull-out tests were used to measure the fibers' compressive strength, flexural strength, and maximum load-bearing capacity, respectively. According to the results, the compressive strength (CS) and elasticity modulus (MOE) decreased with increasing fiber content when MPW fiber was added. In the long term, the CS and MOE decrease for the LC containing 3% MPW fiber was 8% and 7%, respectively, lower than for the control concrete. At 90 days, the flexural strength of the LC with 1% MPW fiber was marginally higher than that of the control concrete, rising by 2.40%. After this initial rise, however, the flexural strength declined as the fiber concentration increased, eventually reaching an 8% reduction for LC with 3% MPW fiber.The optimum method for determining maximal load-bearing and comprehending the deformation mechanism is hence the fiber pull-out test. The microstructure study of the LC examined how the pull-out test affected the quality of bonding at fiber-matrix interfaces. The tensile and flexural strength of lightweight concrete are enhanced by MPW fiber's ability to bear significant pulling stress. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>Comprehensive Study on Mechanical and Transport Properties of Roller-Compacted Concrete Incorporating Reclaimed Asphalt Pavement</title> <link>https://www.scientific.net/JERA.71.61</link> <guid>10.4028/p-ZrpJX0</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Ines Boussetta, Saloua El Euch Khay, Jamel Neji This study assesses the feasibility and effects of incorporating reclaimed asphalt pavement (RAP) into roller-compacted concrete (RCC) for pavement applications. Six RCC mixtures, incorporating varying RAP fractions (0% to 100% as volumetric substitutions of natural aggregates), were formulated and evaluated for their fresh, mechanical, and transport properties. Scanning electron microscopy (SEM) analysis was conducted on the RCC mixture containing 100% RAP. The results indicated a decrease in overall mechanical properties as RAP content increased, with 28-day compressive and split tensile strengths declining by 70% and 40%, respectively, in the case of full replacement. This decline in mechanical performance was accompanied by heightened porosity and sorptivity. Nevertheless, RCC mixtures with up to 60% RAP met pavement construction specifications. SEM micrographs revealed significant pore concentration, especially in the interfacial transition zone between RAP aggregates and the cementitious matrix, indicating poor adhesion between these RCC phases. Furthermore, empirical correlations were established to illustrate the influence of RAP content and increased porosity on RCC's mechanical properties and sorptivity. These correlations allow engineers to predict the characteristics of RCC for any RAP rate and provide insights into the impact of substituting natural aggregates with RAP on porosity and, consequently, RCC's hardened-state characteristics. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>Modeling Stress Concentration Factors for Fatigue Design of KT-Joints Subjected to In-Plane Bending Loads Using Artificial Neural Networks</title> <link>https://www.scientific.net/JERA.71.79</link> <guid>10.4028/p-zOOom9</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Mohsin Iqbal, Saravanan Karuppanan, Veeradasan Perumal, Mark Ovinis, Muhammad Faizan, Adnan Rasul, Muhammad Iqbal Stress concentration factor (SCF) is an important parameter for the fatigue design of offshore joints. There are many empirical equations for quick estimation of SCF in tubular joints, based on experimental and numerical investigations. However, most of these equations apply at the crown and saddle points only, even though the maximum SCF may not always occur at these points, resulting in overestimated fatigue life. As the maximum SCF location varies due to multiplanar loads, damage, or reinforcement of joints, its location and magnitude are critical for a realistic fatigue life estimation. However, conventional statistical tools cannot approximate the complex behavior of SCF around the brace axis. On the other hand, artificial neural networks (ANN) can efficiently approximate complex phenomena. This study uses ANN to develop empirical models for determining SCF around the weld toe of KT-joints subjected to in-plane bending (IPB) loads. Eighteen hundred and fifty-eight (1858) designs were simulated using finite element analyses to generate data for training the ANN. Two IPB load conditions were focused on, and empirical equations were proposed for SCF around the chord side of the central brace-chord interface. These equations approximate maximum SCF with less than 5% error. This methodology applies to other joints and load configurations also. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>Fuzzy Model Based Model Predictive Control for Biomass Boiler</title> <link>https://www.scientific.net/JERA.71.93</link> <guid>10.4028/p-6uV4X4</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Getinet Asimare Nibiret, Abrham Tadesse Kassie In the realm of renewable energy, biomass plays a crucial role. A key component of power plants, the biomass boiler unit, is responsible for steam production. This unit operates as a nonlinear, highly coupled multivariable process. Traditional controllers used in the industry are ineffective for such systems. To address this, this paper presents a novel approach: a model predictive controller designed for biomass boiler plants. Fuzzy modelling, employed to approximate nonlinear functions to linear ones, is used for system identification. The methodology is implemented using MATLAB/Simulink and the Fuzzy modelling and identification (FMID) toolbox, utilizing input-output data from the Wenji-Shoa sugar factory for fuzzy model identification. The proposed controller demonstrates significant improvements, achieving settling times of 7.5, 13, and 7 seconds, with acceptable overshoots of 0.5%, 0.39%, and 0.46% for pressure, temperature, and level, respectively, for MISO systems. In contrast, the MPC shows improved performance in MIMO systems compared to MISO systems, with settling times of 5, 4, and 7 seconds, while the overshoot is reduced only for the pressure output, with 0.214%. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>Iterative LMI-Tuned PID Controller for Robust Decentralized Multi-Area Automatic Generation Control in Deregulated Electricity Markets</title> <link>https://www.scientific.net/JERA.71.109</link> <guid>10.4028/p-Lv4H7u</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Peter Anuoluwapo Gbadega, Yan Xia Sun This study proposes an Iterative Linear Matrix Inequality (LMI)-Tuned Proportional-Integral-Derivative (PID) controller for robust decentralized AGC in the context of deregulated electricity markets. The study addresses the challenges posed by market uncertainties and diverse generation sources, aiming to enhance the stability and performance of power systems. This study is driven by the urgent need to develop robust AGC strategies that are adapted to the complex dynamics of decentralized power systems operating in deregulated markets. The conventional centralized control approaches are often inadequate to address the diverse and distributed nature of modern generation units. Furthermore, the intermittent and variable nature of renewable energy sources adds a layer of complexity that demands innovative control solutions. The impact of bilateral contracts on the dynamics is taken into consideration while modifying the conventional LFC of interconnected power networks. To model these bilateral contracts, the distribution company (DISCO) participation matrix (DPM) is presented, and the multi-area block diagram reflects these concepts. Simulation studies are conducted to evaluate and compare the performance of the proposed Iterative LMI-Tuned PID Controller and Conventional PID Controller. Results are analyzed against key performance metrics, considering scenarios reflective of diverse market conditions. Comparative studies with the conventional PID controller provide insights into the efficacy and robustness of the proposed approach. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> <item> <title>CNN-LSTM is all you Need for Efficient Resource Allocation in Cloud Computing</title> <link>https://www.scientific.net/JERA.71.141</link> <guid>10.4028/p-O4CrN9</guid> <description>Publication date: 18 September 2024 Source: International Journal of Engineering Research in Africa Vol. 71 Author(s): Moussa Aboubakar, Yasmine Titouche, Mickael Fernandes, Ado Adamou Abba Ari, Md Siddiqur Rahman Many organizations have embraced cloud computing in recent years to provide new services, easily expand their IT resources, and reduce the cost of their IT infrastructure. This has been made possible through the implementation of resource allocation strategies by cloud service providers. One of the major challenges during resource allocation is to minimize power consumption while ensuring the required Service Level Agreement (SLA). To solve this problem, a new approach to efficiently allocate resources in cloud computing while optimizing energy consumption and guaranteeing the required service level agreement has been proposed. The main idea of this proposal is to leverage the CNN-LSTM architecture to accurately predict resource utilization in order to make the appropriate resource allocation decision. The proposed solution was validated in two steps: step 1) a comprehensive set of statistical performance analysis and step 2) an intensive simulation of the solution for resource allocation using cloudSim Plus tool. The results of the experimentation demonstrated that the proposed solution can help cloud service providers achieve energy savings while guaranteeing the required SLA. </description> <pubDate>Wed, 18 Sep 2024 00:00:00 +0200</pubDate> <feedDate>Sat, 23 Nov 2024 01:45:51 +0100</feedDate> </item> </channel> </rss>