Nigerian Journal of Technological Development

Sustainability assessment of textile and apparel sector: a review of current approaches and tools

T.G. Fadara, K. Y. Wong, M. I. Maulana — Sun, 15 Oct 2023 00:00:00 +0000

The purpose of this study is to provide an overview of sustainability evaluation techniques in textile and apparel sector. The review studies are divided into two namely product relate assessment methods and integrated assessment methods which summarizes the different dimension covered, weightage, number of indicators involved, and highlight the weakness and strength of the previous developed sustainability assessment methods in the textile industry. The analysis revealed that majority of the product-related assessment methods focused on environmental factors only, while all the studies reviewed in this category neglected triple bottom line (TBL) in their assessment approach. Nevertheless, there is still a need to focus more on integrated assessment tools to fulfil the TBL goals. This current study offers comprehensive details of product related assessment and integrated assessment methods that was published from 2010 to 2022. Furthermore, examined current sustainability evaluation methods and offered insights into how sustainability assessment techniques have evolved in the textile and apparel industry. The review showed the product related assessment tools are impact assessment techniques are frequently used as an independent tool for evaluating the specific impact of one sustainability measurement, also have no weights attached to them because most indicators assessed were more generic. While integrated assessment method revealed that results would be less reliable if weighting and data collection were non-standardized and inconsistent. However, from the uncertainty’s perspectives, only integrated assessment tools considered fuzziness, grey and stochastic ambiguities in some of their methods, whereas product related assessment tools studied, ignored fuzziness and grey uncertainties completely.

Absorbent mixtures optimisation for COD and Ammonia Nitrogen reduction in stabilised leachate

M. H. Abubakar, Z. Daud, H. A. Abba — Sun, 15 Oct 2023 00:00:00 +0000

This paper describes the optimisation of mixed media for Chemical Oxygen Demand (COD) and Ammonia Nitrogen (NH3-N) removal from stabilised leachate by feldspar (FE), zeolite (ZE), activated carbon (AC), and cockle shells (CS) mixtures using D-optimal mixture design. Linear equations characterised the optimal mixture. The optimum mitigation of COD and NH3-N in landfill leachate was favourable at 12.5 mg/L, 9.72 mg/L, 6 mg/L, and 11.79 mg/L of adsorbent mixed dosage for FE, ZE, AC, and CS, respectively, with the desirability value of 0.886. The predicted R-squared values for NH3-N (0.9839) and COD (0.8972) were in close agreement with the adjusted R-squared values of 0.9940 and 0.9900 for COD and NH3-N, respectively, which validates the obtained regression models. The Lack of Fit F-values of 0.6015 (COD) and 0.4565 (NH3-N) are insignificant, indicating that the models accurately predict the removal. The Fourier transform infrared spectroscopy (FTIR) revealed that the predominant hydroxyl group consisted of –OH at spectra 3306.18 and 3338.74. The study also revealed that the D-optimal mixture design has extremely high application potential as it produces a good mixture design based on the remediation of contaminants from stabilised leachate.

Comparative analysis of deep learning techniques based COVID-19 impact assessment on electricity consumption in distribution network

A. O. Amole, S. Oladipo, D. Ighravwe, K. A. Makinde, J. Ajibola — Sun, 15 Oct 2023 00:00:00 +0000

Energy is a fundamental human need for several activities. Energy can be impacted by several factors ranging from technical to social and environmental. The impact of COVID-19 outbreak on the energy sector is enormous with serious global socioeconomic disruptions affecting all economic sectors, including tourism, industry, higher education, and the electricity industry. Based on the unstructured data obtained from Eko Electricity Distribution Company this paper proposes three deep learning (DL) models namely: Long Short-Term Memory (LSTM), Simple Recurrent Neural Network (SimpleRNN), and Gated Recurrent Unit (GRU) were used to analyse the effect of COVID-19 pandemic on energy consumption and predict future energy consumption in various district in Lagos, Nigeria. The models were evaluated using the following performance metrics namely: Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). On overall, the lowest MAPE, MAE, RMSE, and MSE of 0.120, 71.073, 93.981, and 8832.466 were obtained for LSTM in Orile, SRNN in Ijora, and GRU in Ijora, respectively. Generally, the GRU performed better in predicting energy consumption in most of the districts of the case study than the LSTM and SimpleRNN. Hence, GRU model can be considered the optimal model for energy consumption prediction in the case study. The importance of having this model is that it can help the government and other stakeholders in economic planning of electricity distribution networks.

Production of medium chain fatty acids from ensiled potato peels; effect of inoculum type and kinetic study

J. A. Undiandeye, S. Kiman, J. V. Anaele — Sun, 15 Oct 2023 00:00:00 +0000

Medium chain fatty acids (MCFAs) are fatty acids containing 6 to 12 carbon atoms with a wide range of industrial application. They can be produced by the fermentation of waste biomass through a process called chain elongation (CE). During CE, the type of inoculum used plays a key role in determining the optimal yield of MCFAs. In this study, we showed, for the first time, the use of three different inocula including leachate, rumen fluid and digestate from a biogas reactor for the batch fermentation of ensiled potato peels for MCFAs production. Results showed that the highest chain elongation was obtained when leachate was used as inoculum with a maximum yield of 57, 4 and 26 g/kgVS for caproic acid, heptanoic acid and caprylic acid respectively. A kinetic study shows that the production of MCFAs from ensiled potato peels was better described by the first-order model than by the modified Gompertz model.

Oil extraction from Treculia africana seeds: process conditions, kinetic and thermodynamic studies

O. O. Okwonna, A. A. J. Obuebite, I. J. Otaraku — Sun, 15 Oct 2023 00:00:00 +0000

The declining global supply and sources of vegetable oil consumed across different parts of the world have become a source of growing concern. Finding alternative sources demands concerted efforts and studies on other agricultural products not adequately utilized. This study investigates the extraction of oil from Treculia africana seeds using n-hexane as a solvent. The effect of heat pre-treatment of the seed samples on the process was also investigated using oven-drying and sun-drying methods, respectively. The pre-treatment process had no effect on the physicochemical properties of the extract except the maximum yields at 60 min obtained as 42.5 and 40.31%, respectively. Characterization of the extract using the physicochemical properties of the oil showed specific gravity 0.931, saponification value 624.4 mgNaOHg^-1oil, acid value 2.57 mgKOHg^-1oil, and iodine value 14.13mg100g^-1 which indicates its suitability for consumption, soap making, production of pharmaceuticals and as a lubricant. The Kinetics of the process which was studied under different temperatures and time intervals indicate a first-order reaction. Several thermodynamic parameters were determined such as activation energy, enthalpy, and entropy. These physicochemical properties indicate that the extract is comparable to the vegetable oil obtained from other sources. The kinetics and thermodynamics studies indicate the spontaneity of the process showing that the energy required to break the solute-solvent/solvent-solvent interaction was more significant than that required to maintain the bonds between them thereby favouring the forward reaction and product formation.

Capacities and irreversibility of the vapour compression refrigeration system’s components using aluminium oxide (Al₂O₃) based nanolubricants

M. Ogbonnaya, O. O. Ajayi, M.A. Waheed — Sun, 15 Oct 2023 00:00:00 +0000

Hydrochlorofluorocarbon and chlorofluorocarbon refrigerants commonly used in vapour compression refrigeration system (VCRS) have been phased out due to their negative impact on the ecosystem. R134a and R600a refrigerants were considered as their replacement, but they possess low thermal properties, thereby affecting the performance of the VCRS. In this study, the effect of varying aluminium oxide (Al₂O₃) nanoparticle size (10 nm, 20 – 30 nm and 80nm) and volume concentration (1%, 3%, 5% 10% and 20%) on the capacity and exergy efficiency of each component of VCRS for the optimisation of the VCRS performance and reduction of energy consumption was analysed using R134a and R600a refrigerants. The nanolubricant were prepared using the two-step method. The VCRS showed no significant deterioration in the performance of its components as confirmed for over 24 hours when nanorefrigerant was used. The compressor capacity of nanorefrigerant was lower than that of pure refrigerants while the addition of nanoparticle enhanced the refrigeration effect. The exergy efficiency of the vapour compression system improved with the addition of nanoparticles into the system, the exergy destruction caused by friction in the compressor significantly reduced, thereby reducing the energy consumed by the system.

Physio-mechanical assessment and process mapping of AlSi10mg/Cu material for automobile application

O. Olaniran, A. A. Adediran, A.A. Akinwande, O.S. Adesina, O.A. Mosadomi — Sun, 15 Oct 2023 00:00:00 +0000

In this study, copper (Cu) particles were used as a replacement for ceramic particles in an AlSi10Mg matrix to lessen the brittleness often associated with ceramic particles when used as fillers in aluminum matrix. AlSi10Mg was combined with 0, 2, 4, and 6% Cu, and microwave sintering was performed at 300, 450, and 600 °C. The composites produced were subjected to physical tests (porosity, density, shrinkage, and relative density), tensile tests (yield and ultimate strength, elastic modulus, and elongation), and microstructure test. Cu particles were observed to be dispersed at 2% and 4% sintering temperatures and clustered at 6% sintering temperatures, according to the microstructural images. The incorporation of 2% and 4% Cu decreased porosity, leading to increased yield, ultimate tensile strength, and elastic modulus respectively. It was noted that 6% Cu addition resulted in strength reduction owing to particle clusters. Sintering temperatures between 300 and 450 ℃ were favorable for all property investigated; nevertheless, temperatures above 600 °C were detrimental to property responses. The proposed process map revealed diverse response values for varying input combination parameters; hence, a Cu dosage of 4% at a sintering temperature of ≤ 450 °C is recommended.

Effect of electric potential on the structure and yield of graphene oxide using electrochemical exfoliation method

O. D. Adigun, L. E. Umoru, T. N. Iwatan — Sun, 15 Oct 2023 00:00:00 +0000

Optimization of the electrochemical exfoliation of graphene oxide synthesis was investigated in this report using varying potentials. Graphite from waste lithium-ion batteries was used as the electrodes for the DC (direct current) electrochemical set-up. Electric potentials of 7.5 V, 12 V, and 15 V were applied for 225 minutes using 0.2M H₂SO₄ as the electrolyte. The characterization of the produced graphene oxide was done using Raman spectroscopy, high-resolution scanning electron microscopy (HRSEM), and energy dispersive x-ray spectroscopy (EDS) attached to the scanning electron microscope (SEM). The results obtained showed that both the rate of graphene oxide yield and the C/O ratio increased correspondingly with the increase in electric potential. However, the structure of graphene oxide produced at 7.5 V was of superior quality compared to others produced at higher potentials with regards to the crystallite lattice characteristics such as defects, lateral dimensions, thickness, and the number of graphene layers. Consequently, tailor-made graphene oxide properties (and yield) for target applications may be achieved using the electrochemical exfoliation method via the choice of the electric potential.

Removal of heavy metals from domestic wastewater using Beneficiated Kaolin Clay, Silver Oxide and zinc Oxide nanocomposite

F.O. Ogundipe, M. Saidu, A.S. Abdulkareem, A.O Busari — Sun, 15 Oct 2023 00:00:00 +0000

This study describes the removal of total iron, cadmium, lead, copper, manganese, arsenic, mercury silver and zinc from domestic wastewater disposed of via sewers, using Beneficiated Kaolin Clay (BKC), BKC/Ag, BKC/ZnO and BKC/Ag/ZnO nanocomposite adsorbents produced by blending Silver Oxide (Ag) and Zinc Oxide (ZnO) nanoparticles with kaolin clay. High Resolution Transmission Electron Microscope (HRTEM) results showed that the produced adsorbents were polycrystalline in nature, while the interplanar spacing and average crystalline sizes are 1.775 – 4.712 nm and 26. 834 – 40.258 nm respectively, according to X-Ray Diffractometer (XRD) analysis. The Dispersive X – Ray Fluorescence (XRF) analysis indicated that SiO₂/Al₂O₃ ratios for BKC/Ag, BKC/ZnO and BKC/Ag/ZnO nanocomposites adsorbents were 1.5170, 1.4818 and 1.5231 respectively. Brunauer – Emmett – Teller (BET) analysis showed that the desorption average pore sizes fell in the mesopore widths of 13.8994 – 16.9233 nm and surface areas of 1.0545 - 14.5126 m².g^-1. The removal efficiencies of the produced adsorbents followed this trend: BKC/Ag/ZnO > BKC/Ag > BKC/ZnO > BKC. These adsorbents were excellent in the removal of total iron, cadmium, lead, copper, manganese, arsenic, mercury silver and zinc pollutants from domestic wastewater, and hence, recommended for large scale production.

Microstructural evaluations of mild steel and HT250 grey cast iron in ethanol environment

Sat, 14 Oct 2023 00:00:00 +0000

The study focused on the response of mild steel and HT250 grey cast iron in varying ethanol concentration. First, a robust review of both materials’ behaviour under different environment was established using microstructural evolutions. Secondly, 30 × 30 × 10 mm dimension of both materials were employed in the study by immersing them in varying ethanol concentrations of BG-43 %, ESG- 42 %, CG-43 %, SQD- 42 % using distilled water as control. The microstructural behaviour showed that every of the sample responded according to the medium of interaction (ethanol). The degree of surface damage also depends on the ethanol concentration and the heavy presence of Fe and oxygen especially in that of grey cast iron. Corrosion cracks and deposits can be attributed to the reaction between the surface and the ethanol. Thus, environment of application is important in material selection. Results suggests that the microstructural changes provide to the material scientist the qualitative corrosion information of these materials in different environment. Conclusively, the study has enlightened the design engineers and material specialist on the need for proper material selection during engineering design.

Maximising efficient water capacity through reservoir configuration with a case study for Malang City of Indonesia

G. Samudro, H. Samudro, S. Mangkoedihardjo — Sun, 15 Oct 2023 00:00:00 +0000

All forms of water supply systems had unique characteristics of idle capacity. However, achieving a sustainable water supply over the long term could not eliminate idle capacity. This paper discussed methods for providing efficient capacity without compromising long-term water requirements. The objective of efficient capacity was to reduce idle water capacity and water-carrying infrastructure. This study method reviews previous research results with an in-depth case of a piped water supply system in an urban area. The assessment method referred to the pattern of water demand by consumers. Fluctuations in water demand determined the dimensions of all water supply system components. The results of this study showed that water distribution determines the minimum idle capacity, which directs the need for priority areas for efficient capacity and opens reservoir placement options. Under these priority areas, a decentralised reservoir position resulted in an efficient system dimension. The closer the reservoir was to the consumer, the smaller the idle capacity, which was the contribution of the onsite reservoir. The critical implementation was based on the flexibility of the phasing of water supply and infrastructure. The flexibility addressed the use of flow rates for a certain period, diversification of water sources, and system configuration that determines the dimensions of the infrastructure and maximising utilisation.

Performance analysis of a permanent magnet synchronous motor with dual stator windings

O. J. Tola, E. S. Obe, L. U. Anih — Sun, 15 Oct 2023 00:00:00 +0000

This paper presents the modelling and performance analysis of a line-start three-phase interior permanent magnet synchronous motor (IPMSM) with dual stator windings. The machine has two sets of windings, main and auxiliary windings. The main winding is connected to the supply while the auxiliary is connected to a balanced capacitor. The dynamic model equations are derived in the d-q rotor reference frame using the concept of winding function theory. The machine input impedance was construed from the steady-state equations, where the effects of capacitance on the performance of the motor were studied. An improved torque was obtained when a suitable capacitance was connected to the auxiliary winding. A point of good performance was established by enhancing its direct axis reactance and the quadrature axis reactance which depend on the size of the capacitor. It is shown that the
new configuration has better performance characteristics when compared with those of the traditional configuration in terms of output power, torque density and efficiency.

Investigation of electric field enhancement and effects of discharge severity in an insulated power cable with multiple gaseous cavities

Sun, 15 Oct 2023 00:00:00 +0000

Gaseous cavities in the insulation of high voltage (HV) cables affect the electric field distribution and increase the electrical stress. This accelerates material ageing and creates partial discharge (PD) regions, which can cause cable failure. In this study, a simulation approach using a Finite Element Method (FEM) has been deployed to evaluate the discharge activity and electric field variation in cross-linked polyethylene (XLPE) insulated power cables. 2-Dimension models corresponding to sections of a practical three-core XLPE insulated cable were developed using COMSOL Multiphysics. Multiple cavities of different dimensions and configurations were considered. The results show that the electric field varies depending on the configuration and dimensions of the cavity. It was found that maximum field strength magnitude depends on the cavities, arrangement and location; an increase of up to 68.7% when compared to the case without cavities.

Leveraging on low-cost devices for wireless data acquisition in remote pipeline networks

I. C. Febaide, G. O. Uzedhe — Sun, 15 Oct 2023 00:00:00 +0000

Pipeline infrastructures are the most used means of transporting oil and gas from extraction point to production and sales point. These pipelines are exposed to various attacks either by natural occurrences, indiscriminate human activities around pipelines or direct criminal sabotage, and therefore require constant monitoring. The use of low-cost wireless devices for pipeline data acquisition as it applies to remote and difficult terrain is presented. Different methods and models have been suggested in literature with several existing systems such as SCADA, DCS, and satellite spectral imaging currently in use for pipeline operations. Among the challenges here is the need for lower operational costs, even at reduced response time demand. The Wireless Data Acquisition System (WDAS) presented simulates a pipeline system in a testbed in which a petroleum product is caused to flow and its parameters read, processed as data and wirelessly transmitted, through a wireless sensor network, to a remote device for monitoring. Results indicate a very short response time of about 3.0sec in the simulation at a percentage accuracy of 0.07% over 1km. It also shows that low-cost wireless sensor networking can provide a cost-effective means for pipeline infrastructure management and should be explored.

Time series forecasting of electrical energy consumption using deep learning algorithm

Sun, 15 Oct 2023 00:00:00 +0000

Energy consumption forecasting is an operation of predicting the future energy consumption of electrical systems using previous or historical data. The Long Short-term Memory (LSTM) Model; a deep learning model was used in this project to analyze the Short-term consumption forecast performance. This was carried out by using an energy consumption dataset obtained from the Transmission Company of Nigeria (TCN) Benin City regional 132/33KV transmission station. The dataset were daily load readings recorded in the half-hourly format from August to December 2021. The model was used to demonstrate the feasibility of generating an accurate short-term load forecast for the case study despite the peculiarity and insufficiency of the energy consumption readings. Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) are the statistical evaluation metrics used. The approach produces exceptional levels of accuracy, with MAPE of 0.010 and RMSE of 19.759 for a 100 time-step. The findings imply that the LSTM model can make accurate predictions with minimal error, and this Deep learning model may be a useful tool for short-term forecasting demand. This finding serves as a baseline for future research in this field of study and power system planning.

Mechanical characteristics and regression models of rice husk silica reinforced natural rubber composites

Sun, 15 Oct 2023 00:00:00 +0000

Carbon black and silica fillers have been widely used as reinforcing fillers in tyres and engine mounts. However, both fillers are non-renewable and with REACH legislation in Europe, the USA and elsewhere, where some of these fillers are termed hazardous due to the presence of polyaromatic hydrocarbons (PAHs), there is a need to search for sustainable alternative fillers to wholly or partially replace carbon black as a filler. This research studied rice husks-derived silica (RHS) as a filler in natural rubber (NR). The characteristics of RHS at 50 phr to 90 phr filler loading levels were examined to determine its suitability as a substitute for unsustainable carbon black (N772) fillers used in the rubber industry. Bound rubber content, crosslink density, tensile strength, young modulus, tear strength, shore A hardness, compressive set, and elongation at break were measured. Regression models were generated and the correlation of determination (R²) values was obtained. The RHS composites resulted in maximum tensile strength of 13.20 MPa at 90 phr, tear strength of 119 MPa at 90 phr, shore A hardness of 69 at 90 phr, compressive set of 6.72% at 80 and 90 phr, elongation at break of 453.60% at 80 phr, bound rubber content of 92.14% at 50 phr and crosslink density of 3.87×10^-2 mol/cm³ at 70 phr. The results obtained were within the range of those obtained for the carbon black filled composites across various loading levels. The R² value of mechanical characteristics for the RHS and N772 samples respectively were 50.06% and 62.18% (bound rubber content), 97.62% and 99.85% (tensile strength), 98.44% and 63.97% (tear strength), 89.16 and 97.40% (Shore A hardness), 32.90% and 91.80% (compressive set), a d 50.91% and 46.91% (elongation at break). Rice husk-derived Silica filled natural rubber composites showed favourable mechanical properties and can substitute traditional fillers in tyres, rubber engine mounts, bushings, seals and doormats.

Heat transfer enhancement using combined microchannel with vertical rectangular micro fins

N. Y. Godi — Sun, 15 Oct 2023 00:00:00 +0000

This paper focuses on the numerical optimisation of a combined hybrid microchannel heat sink with rectangular solid fins. The axial length and volume are fixed, and external structure is allowed to vary. The simulation was performed on an elemental unit cell of the microchannel heat sink . The purpose of the optimisation is to discover an optimal geometric arrangement in internal and external configurations that minimises peak temperature in the microchannel heat sink. A high-density uniform heat flux of 250 W/cm² is assumed to be dissipated on the bottom wall of the unit cell by microelectronics circuit boards devices. Computational fluid dynamic code was used to discretized the fluid domain and solve a set of governing equations. The influence of hydraulic diameter, external structural shape and fluid velocity on peak temperature and global thermal resistance, is discussed. Coolant or water of Reynolds number range 400 to 500 in a forced convection laminar flow is introduced through the inlet of the computational domain to remove the heat at the bottom of the rectangular block microchannel. The results show that when the fluid velocity is increased from 9.8 to 12.3 m/s across the axial length of the micro heat sink, more heat is removed from the bottom of the combined heat sink. The results revealed that the pump power increased by 37.1% in combined microchannels with fins and from by 27.2% in finless micro heat sink. The result of the study is validated with what is documented in open literature for a traditional micro heat sink with circular flow channel and the trends agree.

Automatic classification of breeds of dog using convolutional neural network

P.O. Adejumobi, I.O. Adejumobi, O.A. Adebisi, S.O. Ayanlade, I.I. Adeaga — Sun, 15 Oct 2023 00:00:00 +0000

Dog is a mammal that has been a friend of man for ages, it is naturally a domestic animal with a high level of phenotype differences in behaviour and morphology. Breeding and crossbreeding activities have increased the number of dog breeds globally, thereby resulting in dogs with inter breed similarities and intra breed differences thereby creating a difficulty in their classification. The American Kennel Club (AKC) classified breeds of dog into groups based on characteristic, purpose, behaviuor and uses in order to optimize the potentials in the breeds. However, most people find it difficult to identify and classify the dog breed groups. Existing works did not consider the automatic grouping of dog breeds. Hence, there is need for automatic techniques to classify dog breeds into groups with improved accuracy. This work used the concept of Convolutional Neural Network (CNN) to develop a model that will automatically classify dog breeds into group based on the American Kennel Club standard using the Stanford’s dog dataset. The developed model achieved 92.2% accuracy, 80.0% sensitivity, 95.3% specificity and 93.4% area under curve (AUC). The model’s performance is excellent compared to existing works that used the same dataset. The experimental result was validated with two classic CNN models (ResNet-50 and SqueezeNet) using the same parameters.

Optimal capacitor planning for power factor improvement using hybrid particle swarm and harmony search optimization

A. H. Ibrahim, E. C. Ashigwuike, W. Oluyombo, A. A. Sadiq — Sun, 15 Oct 2023 00:00:00 +0000

Industrial loads reduce the Power Factor (PF) of supply systems, causing increases in power losses, damaging equipment and higher utility bills. Optimization techniques are used in planning reactive sources to improve PF of power systems. However, conventional techniques suffer difficulties in passing over local optimal, divergence risk, constraints handling or computing higher order derivatives. Herein, the hybridization of Particle Swarm and Harmony Search Algorithm (PS – HSA) is developed for optimal capacitor planning to improve PF, and comparison is made with the Enhanced Particle Swarm Optimization (EPSO) and Improved Adaptive Harmony Search Algorithm (IAHSA). The test systems are the Modified IEEE 6 and 16 buses and nodes respectively. To create semblance of industrial load dominated power systems, the test networks were modified by increasing the reactive load demand at all buses of the IEEE 6 and 16 by 50% and 70% respectively. The capacitor is modelled as static shunt-controlled element deployed to inject reactive power at buses/nodes. Results show that for IEEE 6 buses, PF improved from 0.68 to 0.8983, 0.8986 and 0.8992 with EPSO, IAHSA and hybrid PS – HSA respectively. Similarly, in IEEE 16 nodes, PF improved from 0.76 to 0.9439, 0.943, and 0.944 with EPSO, IAHSA and hybrid PS – HSA respectively. Furthermore, real power losses reduced from 16.94 MW to 14.03 MW in IEEE 6 buses, translating to 17.2% reduction with the hybrid PS - HSA. While in IEEE 16 nodes, reduction is from 0.719 MW to 0.69 MW accounting for 4% reduction, also with the hybrid PS - HSA.

Wind resource of Ilorin City for vortex-induced wind turbine power generation and off-grid electrification

Sun, 15 Oct 2023 00:00:00 +0000

This study examined the appraisal of wind resources of Ilorin, Nigeria for vortex-induced wind turbine power generation and off-grid electrification. The technical potential of Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA-2) was employed as a tool to generate an estimated wind resource of Ilorin city, using five different hub-heights (10, 30, 50, 70, and 90 m). A statistical analysis of wind characteristics for 21 years from 2001 to 2021 was carried out using Weibull distribution function. The daytime and night-time wind characteristics were studied to determine prospective and investment hub-height(s). It was observed that the study area is a low wind region with a minimum and maximum mean wind speed of 2.89 m/s at 10 m and 7.68 m/s at 90 m, respectively. Wind turbines with cut-in wind speed of 2, 2.5, and 3 m have operational chances of 98%, 95% and 88%, respectively. Wind power density at 10, 30, and 50 m elevations was classified as poor while at 70 and 90 m elevations, was regarded as marginal and fair, respectively.

Nigerian Journal of Technological Development

Sustainability assessment of textile and apparel sector: a review of current approaches and tools

Absorbent mixtures optimisation for COD and Ammonia Nitrogen reduction in stabilised leachate

Comparative analysis of deep learning techniques based COVID-19 impact assessment on electricity consumption in distribution network

Production of medium chain fatty acids from ensiled potato peels; effect of inoculum type and kinetic study

Oil extraction from Treculia africana seeds: process conditions, kinetic and thermodynamic studies

Capacities and irreversibility of the vapour compression refrigeration system’s components using aluminium oxide (Al2O3) based nanolubricants

Physio-mechanical assessment and process mapping of AlSi10mg/Cu material for automobile application

Effect of electric potential on the structure and yield of graphene oxide using electrochemical exfoliation method

Removal of heavy metals from domestic wastewater using Beneficiated Kaolin Clay, Silver Oxide and zinc Oxide nanocomposite

Microstructural evaluations of mild steel and HT250 grey cast iron in ethanol environment

Maximising efficient water capacity through reservoir configuration with a case study for Malang City of Indonesia

Performance analysis of a permanent magnet synchronous motor with dual stator windings

Investigation of electric field enhancement and effects of discharge severity in an insulated power cable with multiple gaseous cavities

Leveraging on low-cost devices for wireless data acquisition in remote pipeline networks

Time series forecasting of electrical energy consumption using deep learning algorithm

Mechanical characteristics and regression models of rice husk silica reinforced natural rubber composites

Heat transfer enhancement using combined microchannel with vertical rectangular micro fins

Automatic classification of breeds of dog using convolutional neural network

Optimal capacitor planning for power factor improvement using hybrid particle swarm and harmony search optimization

Wind resource of Ilorin City for vortex-induced wind turbine power generation and off-grid electrification

Capacities and irreversibility of the vapour compression refrigeration system’s components using aluminium oxide (Al₂O₃) based nanolubricants