Current Concepts in Engineering Research and Technology Vol. 1

Investigating the Grindability Behaviour of Anka’s-Zamfara State, Nigeria Manganese Ore, Towards Effective Manganese Mineral Liberation

Y. E. Gbadamosi — 2026-02-27

Mineral processing involves the enrichment of concentrate by separating the grains of valuable mineral from the gauge, and since most ore minerals are usually finely intimately associated with gangue minerals, the various minerals must be liberated before they can be collected as separate products. The Bond standard grindability test provides a Work Index that is widely used to estimate the energy required for ore grinding. The research investigates the work index of Anka Manganese ore at the Anka deposit in Zamfara state, Nigeria. The reference ore (Quartz) was sourced from the studied ore overburden in the mine. 500 g each of the manganese ore and quartz were sampled and prepared by crushing and grinding to 100% passing a 1200 μm sieve. 100 g of prepared ores were charged into an array of sieves arranged in √2 series from 1000 μm to 63 μm. A set of sieves was mounted on the Automated Pascal Denver sieve shaker (16153) and was in operation for 20 minutes. The work index of reference ore was used to calculate the work index of the test ore using Gaudin Schuman expression to obtain a work index of 14.16 Kwh/ton for test ore and it lies within the work index of 10-15.14 Kwh/ton for manganese ore stated in the literature and the energy expended to achieve communition at mineral liberation size was calculated to be 3.3984 Kw/ton. Assessing the grindability behaviour of Anka manganese ore towards effective manganese mineral liberation was investigated. This is very important to know the grinding characteristics of the ore towards the determination of suitable power to be selected for its comminution process and hence selecting suitable design parameters for the construction of grinding machine suitable for communition process of studied test ore to its liberation size avoid excess grinding or under grinding.

Development and Performance Evaluation of Vehicle-Mounted Wind Turbine for Electrical Power Generation

B. Olajiga — 2026-02-27

Environmental degradation from continuous use of fossil fuels and the attendant effects on human and animal environments demand sustainable, renewable energy alternatives to protect the environment from further deterioration. Wind energy offers a promising solution as it is available everywhere, inexhaustible, and can be accessed anytime for the continuous powering of electric vehicles while in motion. The present study aims to investigate the effects of wind speed, car speed, and altitude on power generation using a vehicle-mounted wind turbine (VMWT) on a moving vehicle. A VMWT was developed and tested at varying altitudes, wind and vehicle speeds across the northern and southern zones of Nigeria to assess its energy generation potential for use in powering electric vehicles. The Horizontal axis wind turbine (HAWT) utilised a dynamo rated at 12V 10 W at 325 rpm, a swept area of 0.159 m² operating directly without a mechanical multiplier system, a cup anemometer and a data logger to capture real-time data. The data obtained was analysed using analysis of variance (ANOVA) SPSS16 and Minitab software and Design Expert.v.18. The data obtained was grouped using six driving speed ranges (0-20km/hr,20- 40km/hr,40-60km/hr,60-80km/hr,80-100km/hr and 100-120km/hr), four altitude ranges (0- 100m,100-200m,200-300m, and 300-400m) and four wind speed ranges (0-50m/s,50-100m/s,200- 250m/s and above 250m/s). The lowest mean wind speed of 8.68m/s was recorded at a car driving speed range of 0-20km/hr and at an altitude range of 0-100m and the mean power generated was 266.476mW, while the highest mean wind speed of 108.47m/s occurred at a driving speed range of 100-120km/hr at altitude range of 100-200m with a peak electrical power of 6479.242mW. The peak power output of 6662.131mW for this research was recorded at the altitude range of 300-400m, driving speed range of 100-120km/hr and wind speed 570m/s. This output can be further enhanced by utilising both a mechanical multiplier and a buck-boost converter to efficiently charge the car battery, thereby extending the vehicle's driving range. The result of this Study shows that electrical power generation increased with higher vehicle speeds and wind speeds across all altitude ranges. Further studies are required to be carried out on the turbine blades for increased power generation.

The Vector Control of Induction Machines with MRAS-Based Third-Order Sliding Mode Speed Observer

Rakia Tarkhani — 2026-02-27

The effectiveness of vector control depends heavily on the accurate estimation of rotor flux and speed. Among sensorless techniques, Model Reference Adaptive System (MRAS) are widely used due to its simplicity and low computational cost. This chapter presents an advanced vector control strategy for induction machines that combines a Third-Order Sliding Mode (TOSM) control scheme with a MRAS–based speed observer. The proposed MRAS-TOSM structure ensures precise and reliable rotor speed estimation under parameter uncertainties and varying operating conditions. By integrating third-order sliding mode control, the system exhibits enhanced robustness against disturbances and parameter variations (such as stator resistance and rotor inductance), fast convergence, and minimised estimation errors. Key performance metrics, including overshoot reduction, settling time, and steady-state accuracy, are analysed in detail through extensive simulation studies. The simulation results demonstrate that the proposed approach significantly improves dynamic performance, stability, and robustness compared to conventional control methods. The results also highlight its potential for high-performance industrial drive applications and practical implementations, making it a suitable solution for both academic research and real-world engineering systems.

A Machine-Aided Framework for Real-Time Gas Leak Detection: Case Study of the JK-52 Gas Processing Plant

Godsday Idanegbe Usiabulu — 2026-02-27

Natural gas is considered a fossil energy source from under the earth's surface. Its main component is methane, but it can contain non-hydrocarbon gases and natural gas liquids as well. Leaks are considered very dangerous since they can build up into an explosive concentration. Gas leaks can be hazardous to health as well as the environment. Leak detection is a method in which the existence of a leak within a system is determined. Many fluid leak detection mechanisms rely on observation of volume changes and physical evidence of a leak, which may take hours, days and sometimes weeks or months to be seen. This is a concern in gas plants where the proximity of the leakage may constitute environmental pollution as well as health hazards for personnel in the vicinity. Economic losses have also resulted from delays in mitigating a gas leak problem due to late detection.

This study applies a machine learning technique to develop an algorithm that can detect gas leaks in real-time, where the only possible delay is the lag-time between the inlet gauges at the upstream valve and the outlet gauge at the downstream valve. The dataset for the study was collected, and a pre-processing phase was performed, which included cleaning the data, attempting a linear regression model and other regressions (Random Forest). This study also proposed a model and evaluated its performance. In this case study of the JK-52 gas processing plant, the difference in pressure gauge readings was calibrated against the volume of the gas in the inlet section to quantify the leak volume. Because gaseous fluids do not present a physical indication of volume, a pressure-based method was used for the detection, where a drop in gauge pressure due to depressurisation indicates leakage in the absence of a recorded gas supply or collection.

To build the model, the dataset was divided into samples to train and test the model. Python coding language, using Jupyter and PyCharm Integrated Development Environments (IDEs), was used for the programming. The machine learning algorithm analyses the incoming streaming pressure versus time datasets from the gauges during the residual and ramp-up flow phases to set the acceptable pressure difference cut-off. A minimum difference in gauge reading may be normal within an acceptable error margin. The change in the consistency of reading within this acceptable window defines the tolerance. The system is set up to blare an alarm when there is leakage, usually based on a cut-off or tolerance, to be detected by the machine-aided process. Even if no immediate event triggers the alarm, a leak can still be suspected and later confirmed through further analysis. Over time, the model becomes predictive, improving detection accuracy as it learns from experience.

Hybrid Watermarking Framework Using Discrete Wavelet Transform and Visual Cryptographic Scheme

Deepak Sharma — 2026-02-27

The rapid growth of the internet and easy access to multimedia data have increased concerns about unauthorised use and redistribution of digital content. Digital watermarking is a widely used technique for copyright protection and authentication of digital multimedia. Several watermarking techniques have been proposed in the literature, limited research has been conducted on the effective integration of multi-level DWT with visual hiding schemes to achieve both high robustness and perceptual quality simultaneously. This chapter presents a robust copyright protection scheme based on the discrete wavelet transform (DWT) and visual hiding scheme (VHS). Unlike the traditional schemes, in this proposed scheme, the original image was modified by embedding the watermark into the original image. The visual hidden scheme was used to construct a watermarked image. In embedding, 3 level DWT was applied on the cover image and then the embedding of the watermark was performed using the VHS technique after resizing the watermark image. In order to express the robustness and perceptibility of the presented watermark scheme, experimental results show the performance of the proposed scheme based on parameters, peak signal-to-noise ratio and resistance against various signal processing operations and attacks. The proposed scheme shows higher perceptible performance of the watermarked image without an attack environment produces 51.8 dB PSNR and a minimum of 47.7dB for test images. Under an attack environment, the performance degrade not significantly but in under tolerable range of 30 dB to 42 dB. In future work, the fractional transforms can be more suitably used to increase system robustness in the same direction.

Sieving and Separation Automation with AI in the Food Processing Industry: Challenges of Implementing Advanced Solutions

Kshitij Mohan Sharma — 2026-02-27

The food processing industry is presently experiencing a data revolution, and sieving and separation processes are no exception. Sieving, also known as screening, is a method of separating particles based on size. It's a common process in food processing to refine and separate products like flour, sugar, cocoa powder, and spices. It can also be used for grading products into different sizes, like tea or coffee beans. While traditionally reliant on mechanical adjustments and operator experience, sieving and separation operations are now being transformed by the power of artificial intelligence (AI). AI-driven sieving and separation systems are emerging as key innovations that enhance efficiency, safety, and sustainability. This article explores how these advancements are driving a new era of intelligent processing in the food processing sector. It further studies the concept of sieving and separation automation from the angle of artificial intelligence [AI] and tries to study the hierarchical interrelationships amongst the various challenges faced by food processing companies in implementing advanced sieving solutions with the help of the VAXO technique embedded in ISM methodology.

Numerical Modelling of an Unsaturated Capillary Barrier Cover System Using HYDRUS-2D for Percolation Control

Mohammad Ali Hagh Shenas — 2026-02-27

Inclined multi-layered barriers can be used to protect underlying waste storage facilities. The intended barriers can confine infiltration through the implementation of the capillary barrier effect. In this study, the effect of rainfall, evaporation, and transpiration on the hydraulic properties of inclined covers was assessed by performing simulations using HYDRUS-2D numerical models. The material layers included clay loam soil as a seepage control layer, sandy soil as a moisture retention layer, and gravel as a capillary break layer. The numerical analysis simulated 20 years of climatological data (2000-2019) from Windsor, Canada, representing humid conditions with variable precipitation and evapotranspiration patterns.

Key quantitative results indicate that 21.09% of cumulative net rainfall was converted to lateral drainage along the sloped interfaces, while 78.91% of infiltrated water eventually exited through the bottom boundary as vertical percolation. The mean flux across the bottom boundary was 206.70 cm/day (2.39×10⁻⁶ m/s), demonstrating minimal deep percolation under the prevailing climatic conditions. Lateral diversion occurred at the interface between the seepage control layer and moisture retention layer due to the significant slope (10%) and contrasting hydraulic properties of adjacent layers. At reduced degrees of saturation, water movement between layers was restricted by low hydraulic conductivity, with the negative pressure head in the seepage control layer having minimal effect on water content in underlying layers.

This modelling approach, which uniquely combines an inclined multi-layer configuration with long-term transient climatic forcing, demonstrates that properly designed capillary barrier covers can effectively minimise leachate generation in waste containment systems. The findings provide quantitative design guidance for landfill covers in humid regions, showing that 10% slopes with layered clay loam, sand, and gravel materials achieve the capillary barrier effect under variable climatological conditions. The performance of this protective earthen cover can be guaranteed under the current climatological conditions, offering engineers a validated numerical framework for optimising waste containment cover designs.

Structural Response of High-Rise Buildings against Dynamic Effect of Wind Forces Coupled with SSI

Aditya Kumar Singh — 2026-02-27

An effective design of a high-rise structure requires safeguarding both structural and non-structural components against wind-induced forces, which represent one of the primary lateral dynamic loads affecting the structural behaviour of tall buildings. The framed building superstructure consists of reinforced concrete beams, slabs, columns, and walls; it transfers gravity loads (including self-weight and occupancy/live loads) as well as wind forces to the foundation. In conventional structural analysis, the contributions of slab and masonry wall stiffness are frequently overlooked. The foundation transmits these accumulated loads to the underlying soil, where vertical settlement occurs based on geotechnical characteristics of underlying founding strata, thereby inducing additional stresses within the structure. The foundation supports are typically modelled as either fixed or pinned; however, due to the complexity of full structural analysis, the influence of soil deformability is commonly disregarded.

This present research study incorporates a spring-based representation to assess the performance of G+13 RCC building while accounting for soil-foundation interaction, specifically considering a clayey soil layer overlying a soft rock-like medium. The research investigates the coupled effects of soil-structure interaction (SSI) and wind loading on the overall structural behaviour. The results indicate that SSI leads to greater overall resilience of the building against wind forces in comparison to the conventional analysis with the assumption of a fixed base. The increased flexibility introduced by the soft clay and soft rock-like soil at the base significantly amplifies the structural response parameters.