ABSTRACT

The past few years have witnessed increasing interest by researchers specializing in studying and developing vertical-axis wind turbines. This group of researchers studied to explore and analyze a wide range of complex issues and problems related to this type of turbine. Among these problems, a pivotal and continuous issue emerged, which is related to the ability of the Darius turbine to self-start torque. Researchers continue to focus on it with the aim of finding innovative solutions to overcome this basic obstacle and improve the efficiency of this turbine. One feasible approach to mitigating this problem is the design and implementation of a hybrid Darius-Savonius vertical-axis wind turbine (VAWT). The VAWT enhances its self-starting capability by increasing the power factor (Cp) within the low tip speed ratio (TSR) range while improving the torque factor (Cm) at initial azimuth angles. This improvement is critical during the blades' transition from the windward to the upwind position. A significant challenge associated with conventional hybrid vertical-axis wind turbines (VAWTs), which feature two rotors mounted on a common shaft, is the documented reduction in efficiency observed within the high tip speed ratio (TSR) range. The observed efficiency drop can be attributed to the inherent performance limitations of the Savonius internal rotor, which is specifically designed to operate optimally at low angular velocities.

Keywords: Wind Turbine; Combined Vertical axis Wind Turbines; Self-starting Torque

ABSTRACT

Determination of some physico-chemical parameters of Tagwai Lake Minna, Niger State, Nigeria was conducted from August – November 2020. Parameters such as carbon dioxide (CO2), Electrical conductivity (EC), Total dissolve solid (TDS), Biological Oxygen Demand (BOD), Total hardness (TH), Total alkalinity (TA), Nitrate (NO2), Chloride (Cl), Phosphate (PO4-) samples were taken to the lab for water analysis while temperature, transparency, hydrogen ion concentration (PH), water depth, Dissolve oxygen (DO), was determined in the field. The study showed that mean values of the physico-chemical parameters obtained were within the acceptable limit to save aquatic lives. Though there were Monthly variationsin some physico-chemical parameters. The mean monthly value for phosphate-phosphorus, water depth, chloride, was significantly different across the stations on level of (P<0.05). Correlation matrix of water quality parameters of station 1: Air temperature, water temperature, pH, conductivity, BOD, total hardness, CO2, TDS and Nitrate were negatively correlated. While Air temperature, water temperature, transparency, D.O, Total hardness, chloride and phosphate were positively correlated. The correlation was significant at either 0.01 or 0.05 levels. Air temperature, correlated Negatively with water depth, conductivity BOD, CO2, chloride and NO3 while Air temperature correlated positively with Transparency, water depth, pH, T.A, Total hardness, PO4 and TDS at station 5. There was correlation between Transparency and water temperature, D.O, and total hardness at 0.05 level of significance. Air temperature correlated negatively with water temperature, pH, conductivity, CO2, TDS, and NO3, while Air temperature correlated positively with water depth, Transparency, D.O, BOD, T.A, Total hardness and PO4 at station 3.  Air temperature – correlated negatively with water temperature, pH, Conductivity, CO2, PO-4, TDs and NO3 while Air temperature – correlated positively with water depth, Transparency, DO, BOD, Total alkalinity, T.H and chloride in station 4.  Air temperature correlated negatively with water depth, water temperature, pH conductivity, CO2, chloride, TDs and No3 in station 5.

Keywords: : Determination, Physico-Chemical Parameters, Tagwai Lake Minna.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 

ABSTRACT

This study investigates the use of artificial intelligence (AI) algorithms to model and analyze non-Newtonian fluid flow behavior. Traditional numerical methods often struggle with the complexity and nonlinearity of such fluids, especially in industrial contexts. The research introduces AI-based models including ANN, ANFIS, and SVM, trained on high-resolution simulation data and validated against classical methods. Experimental setups with viscometers were used to acquire key flow parameters. Different neural architectures were evaluated based on accuracy, convergence rate, and predictive capabilities. Models were tested across varying Reynolds numbers and fluid types. Results demonstrated superior efficiency, stability, and generalization of AI models. The study concludes that AI offers a robust alternative for real-time prediction and modeling of non-Newtonian fluid flows.

Keywords:  Non-Newtonian Fluids, Artificial Intelligence (AI), Artificial Neural Networks (ANN), Viscosity Modeling, Computational Fluid Dynamics (CFD).

ABSTRACT

This paper aims to investigate the current state, challenges, and research gaps in the implementation of Green Human Resource Management (GHRM) in Palestine, with a particular emphasis on the West Bank, where sustainability practices remain underdeveloped due to institutional, economic, and political constraints. The study critically examines the role of GHRM in enhancing organizational sustainability in Palestine and explores how firms integrate environmentally responsible practices within their human resource functions. The research adopts a library research approach based on an extensive review of relevant literature. It systematically analyzes academic and industry studies related to GHRM in Palestine and applies theoretical frameworks including Resource-Based Theory (RBT), Stakeholder Theory, and Institutional Theory to interpret findings. Through this conceptual lens, the paper assesses key GHRM practices, such as Green Recruitment and Selection (GRS), Green Training and Development, and Green Performance Management (GPM), evaluating their impact on organizational environmental performance. The main results indicate that while some Palestinian firms have initiated GHRM practices and experienced improvements in environmental outcomes, the overall adoption remains fragmented and limited. Principal barriers include weak regulatory frameworks, financial limitations, socio-political instability, employee resistance, and insufficient managerial commitment. Additionally, the study identifies a significant research gap concerning the role of GHRM within Palestinian public institutions. It emphasizes the necessity for context-specific frameworks that align GHRM practices with broader corporate environmental and sustainability agendas. The findings suggest that addressing these challenges through stronger policy enforcement, increased investment in sustainability initiatives, and enhanced employee engagement could substantially advance Palestine’s progress toward achieving Sustainable Development Goals (SDGs). The paper recommends that future research focus on bridging the gap between theoretical models and practical application, ensuring that GHRM strategies are strategically aligned with both local organizational priorities and global sustainability objectives.

Keywords: Green Human Resource Management, sustainability, West Bank, Palestine, Resource-Based Theory, Institutional Theory, employee engagement, Sustainable Development Goals.

ABSTRACT

This study presents a detailed stability analysis of Newtonian boundary layer flow over a heated flat plate, incorporating the effects of temperature-dependent viscosity. Based on the classical Blasius boundary layer framework, the research investigates how thermal expansion, buoyancy forces, and mixed convection influence flow stability. Numerical methods, including finite difference schemes and spectral collocation using MATLAB and ProSPAN, are applied to solve the Favre-averaged Navier-Stokes and energy equations, along with turbulence model equations, while accounting for rough boundary wall effects. The governing equations are non-dimensionalized and analyzed using linear and nonlinear perturbation techniques. Eigenvalue analysis identifies critical Reynolds numbers and dominant instability modes. Simulations reveal that heating and wall roughness accelerate the transition to turbulence, while thermal control strategies enhance flow stability. Comparisons with experimental data validate the numerical results and show good agreement. Sensitivity analyses demonstrate that variations in Reynolds number and viscosity are key factors influencing stability thresholds. Overall, the study extends classical theories to more realistic heated surface flows and offers insights into controlling instability in practical thermal-fluid systems. These findings provide a foundation for further investigations into transitional and turbulent boundary layer behaviors under thermal effects.

Keywords: Boundary Layer Stability, Newtonian Fluids, Heated Plate, Temperature-Dependent Viscosity, Mixed Convection, Numerical Simulation, MATLAB, Spectral Collocation, Thermal-fluid systems.