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Corrosion inhibition of aluminium radiators by zinc-stabilized Moringa Oleifera and Newbouldia Laevis Bio-additives: A weight loss study
No full textConcerns about the toxicity and biodegradability of conventional glycol coolants have led to the hunt for environmentally preferable substitutes. In this work, a green coolant made from leaf extracts of Moringa oleifera and Newbouldia laevis stabilised with zinc sulphate was used to investigate the corrosion inhibition of aluminium radiators. Extracts were prepared in a one-to-one blend and tested with zinc sulfate at 0.1 M and 1.0 M concentrations, dosed at 0.25 g and 1.0 g per 15 L of distilled water. Aluminium coupons were immersed for 24 days under controlled conditions, and corrosion rates were determined by the gravimetric weight loss method. Results showed significant inhibition compared with distilled water, with inhibition efficiencies exceeding 80 percent at optimal zinc dosage. As an alternative to hazardous glycol-based coolants, the study shows that zinc-stabilized Moringa-Newbouldia bioadditives offer aluminium radiators efficient, long-lasting corrosion protection
Effect of process parameters on strength and hardness of AA1100 fabricated by friction stir additive manufacturing
No full textThis study investigates the process–property relationships in AA1100 aluminium alloy fabricated via Friction Stir Additive Manufacturing (FSAM), with a focus on optimising ultimate tensile strength (UTS) and Vickers microhardness through parameter tuning. A Taguchi L4 orthogonal array was employed to systematically vary tool rotational speed (900 and 1120 RPM), feed rate (25 and 40 mm/min), and tilt angle (1° and 2°), enabling quantitative analysis of main effects via analysis of means (ANOM). Results reveal that tilt angle is the most influential factor for UTS (Δ = 2.73 MPa), with a 1° setting delivering the highest UTS of 91.89 MPa by promoting symmetric stirring and defect‐free interlayer bonding. Conversely, rotational speed dominates hardness evolution (Δ = 1.2 HV), where 1120 RPM enhanced dynamic recrystallization and yielded a peak average hardness of 36.63 HV. The UTS variation across runs was limited to approximately 3 MPa and hardness fluctuation was within 1.4 HV and this proved the process stability of FSAM for AA1100 and its capability to produce dimensionally and structurally consistent builds. The interplay between parameters highlights a trade‐off: settings optimal for strength differ from those maximising surface hardness, necessitating application‐ specific process selection. These findings position FSAM as a viable, energy‐efficient route for manufacturing dimensionally precise, mechanically stable, corrosion‐resistant aluminium components, especially for aerospace, marine, and structural applications. Future work can focus on advanced microstructural characterisation, fatigue analysis and machine learning based predictive modelling for FSAM of aluminium alloys
Optimizing polymer classification through FTIR spectra and feature-scaled machine learning models
No full textThe research is based on the characterization of polymer materials by Fourier Transform Infrared (FTIR) spectroscopy which is a method of characterizing polymers in terms of their characteristic molecular vibration patterns. Three widely used thermoplastics ABS (Acrylonitrile Butadiene Styrene), PP (Polypropylene) and Nylon-66 were selected and analyzed on the basis of FTIR transmittance spectra. Wavenumbers and the values of percent transmittance were obtained and converted into feature vectors. Gaussian noise was used to boost and clean the data. Machine learning methods that were used to classify the materials included Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), random forest, and logistic regression, where 80% of the data were used to train the machine learning model and 20% to test it. Accuracy measures and confusion matrices were used to determine the performance of the models. Random Forest was the best in terms of performance in Nylon-66 classification; however, the overall accuracy was influenced by the error in classifying ABS and PP. Consequently, k-NN (70) and the Logistic Regression (69) have shown a high performance compared to the Random Forest (57) in terms of overall accuracy. This study reveals that even though the Random Forest could be used to classify a particular set of polymers, polymers that have very similar spectral characteristics are still difficult to differentiate, indicating that the work should be improved by increasing the size of the data set and the number of extracted features
Experimental investigation of electric discharge machining behaviour of TiC and graphite reinforced aluminium hybrid composites
No full textIn the current work, aluminum composites enhanced with graphite and titanium carbide (TiC) were fabricated using a liquid metallurgy route to guarantee uniform dispersion. TiC and graphite particles were added as reinforcements to the aluminum 6061 matrix. The EDM method was used to assess the machinability. Commercial EDM oil served as a dielectric, and copper served as the tool. Tool wear rate (TWR), material removal rate (MRR), and roughness (Ra) were observed in relation to essential parameters such as pulse off time, current, and pulse on time. The findings demonstrated that an increase in current and pulse-on duration raised MRR, it had a impact on surface quality. In addition to lowering TWR, graphite improved surface quality and acted as a solid lubricant, while TiC improved resistance to wear. Using SEM and common EDM features such craters, microcracks, and re-solidified layers, the surface morphology was examined. The research indicates that the machinability and surface quality of composites containing TiC and gr particles can be considerably improved
Techno-Economic Analysis of Hybrid Renewable Energy System for a Rural Community Health Centre in Uganda
No full textThe total power generation of Uganda stands at 1,777 MW which is far below phase two target for the National Development Plan II of 2,325 MW. To achieve the NDP II. To guarantee a sustainable development, the use of renewable energy mostly solar photovoltaic must be fast-tack. Solar technology in Uganda is moderately expensive as a result of high initial investment cost, this necessitates the need to diversify the energy mix of the country thus enhancing security of energy supply which formed the subject of this study. This study dealt with the techno-economic analysis of a hybrid Power system for Busitema Health Centre III. The daily energy demand for the health Centre was 3.979 kWh. The Net Present Cost, Levelized Cost of Electricity and Energy Output of the optimal system were determined using HOMER Pro software. Various combinations were obtained from the HOMER optimization simulations. From the analysis, a solar PV-diesel hybrid system stood out as the optimal configuration. This system is a 15.75 kW Solar PV, 10 kW diesel generator, and a battery bank capacity of 3,375AH
Corrosion inhibition of aluminium radiators by iron-stabilized Moringa Oleifera and Newbouldia Laevis Bio-additives: A weight loss study
No full textIn corrosion research, iron is a paradoxical element since it may promote film formation in some situations while speeding up dissolution in others. This study set out to examine how iron(II) sulfate can alter the behaviour of plant-based inhibitors when applied in radiator coolants. Extracts of Moringa oleifera and Newbouldia laevis were blended in equal ratios and stabilised with FeSO4 at 0.1 M and 1.0 M concentrations. Aluminium coupons were immersed in the prepared formulations for 576 hours, and mass loss was used to calculate corrosion rates. The 0.1 M system produced measurable inhibition, reducing the final corrosion rate to 0.61 mm/year compared with 5.07 mm/year in the control. By contrast, the 1.0 M solution triggered an aggressive onset of corrosion before gradually levelling off. These findings suggest that iron-stabilized bio-additives can both protect and destabilise, with their performance hinging on dosage and exposure time
Experimental investigation of corrosion behaviour in Al alloy reinforced with SiC functionally graded composite
No full textThe corrosion behavior of Al6061 alloy reinforced with 10 wt.% Silicon Carbide (SiC) particles in a Functionally Graded Composite (FGC) that was produced using vertical centrifugal casting and stir casting techniques is the primary focus of this investigation. The microstructural analysis demonstrated a distinct gradient in the distribution of ceramic particles, which led to low, intermediate, and high particle concentration zones throughout the cross section. The highest hardness was confirmed in the high particulate concentration zone by Vickers microhardness testing, which was attributed to enhanced ceramic dispersion. The corrosion performance of a Taguchi L9 orthogonal array was assessed in acidic media, including hydrochloric acid (HCl), sulphuric acid (H₂SO₄), and nitric acid (HNO₃), at varying plunging durations and distances from the boundary edge. The results indicate that the Corrosion Rate (CR) was significantly influenced by the acid type and plunging durations. The CR was at its highest in HCl and decreased as the immersion duration increased as a result of the formation of passive layers. The CR increased as the distance from the boundary margin increased, as a result of the weaker development of passive layers in the inner areas and the lower ceramic content
Chemical pretreatment of
No full textThis study investigated the impact of various chemical pretreatment methods on the biomethane production from Xyris capensis. The feedstock was treated with NaOH, HCl, H2O2, and oxidation using 3, 9, 5, and 75% H2O2 + 25% H2SO4, respectively. Pretreated and untreated substrates were analyzed for physicochemical characteristics and subjected to anaerobic digestion at a mesophilic temperature in a laboratory-batch experiment. The results show that chemical pretreatment significantly influences the physicochemical characteristics of Xyris capensis. It was noticed that the C/N ratios of 37.15, 37.26, 28.90, 27.63, and 28.02 were recorded for NaOH, HCl, H2O2, oxidative pretreatment, and untreated Xyris capensis, respectively. Compared to the untreated substrate, methane generation was enhanced by 20%, 107%, 68%, and 88% for NaOH, HCl, H2O2, and oxidative pretreatment, respectively. Therefore, chemical pretreatment presents a promising biotechnological approach for producing methane from lignocellulose feedstocks. The technique is sustainable due to its ability to recover and reuse chemicals, thereby reducing production costs
Optimization of gin saws for sustainable and eco-friendly cotton processing
No full textThe growing attention to environmental responsibility in the textile and apparel industry necessitates the development of innovative and sustainable manufacturing technologies. This study presents an energy- efficient processing technology aimed at improving cotton processing efficiency, focusing on optimizing the design of ginning saws. Using a comprehensive design methodology, key processing parameters, such as cutting speed, feed rate, tool-material interaction, and machine dynamics, were carefully optimized to meet sustainability goals. To ensure improvements that minimize energy consumption and environmental impact, the behavior of cotton fibers and the influence of environmental conditions on processing performance were considered. A new method for modeling and generating an optimized ginning saw tooth profile is presented, resulting in improved cutting efficiency, reduced fiber damage, and increased tool life. The results demonstrate that this method not only improves productivity but also facilitates the adoption of more environmentally friendly manufacturing practices by reducing resource consumption and improving manufacturing sustainability. This research contributes to the development of environmentally responsible production strategies in the textile and clothing industry, thereby contributing to the achievement of broader environmental goals
The present status of the TORIC-SSFPQL codes
No full textThe codes TORIC and SSFPQL allow detailed selfconsistent simulations of wave propagation and absorption in the Ion Cyclotron (IC) range of frequencies in tokamak plasmas. We review the options presently available in the codes, and we illustrate their performances with two examples: a typical minority heating experiment in a medium size device, and a possible IC heating scenario in a ITER like plasma. The problem of ensuring charge neutrality when the ion distribution functions develop anisotropic suprathermal tails is discussed