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Pressure gradient influence on magnetohydrodynamic (MHD) flow of blood-based hybrid nanofluid containing gold and copper nanoparticles is investigated in the present study. We adopted Caputo’s definition of fractional derivative to transform time-varying terms in governing equations after being appropriately normalized. Partial-analytical solutions of these equations are then numerically sought via the concentrated matrix exponential (CME) method, since complex forms of modified Bessel functions are contained in the normalized equations whose inverse Laplace transforms cannot easily be accomplished using known analytical schemes, which is the overriding novelty of this study. Results for velocity, temperature, and concentration profiles are analyzed graphically. Numerical results for skin friction, Nusselt, and Sherwood numbers are also presented in a table. Our results revealed that the fractional-order derivative increases velocity, temperature, skin friction, and Sherwood’s number, while concentration and Nusselt’s number decrease, accounting for its memory effects in the behavior of the fluid. Additionally, we observed that blood velocity declines with magnetic parameter values, while temperature distribution increases with Eckert’s number values. The study also shows fluctuations in flow motion, temperature, concentration, skin friction, and Nusselt’s number with the stenosis/aneurysmal height. Overall, our findings have significant implications for targeted drug delivery in the arterial system, especially concerning the treatment of atherosclerosis, aneurysms, and other cardiovascular diseases.

The MHD flow of a blood-based hybrid nanofluid with thermal radiation and stenosis effects is explored in this study. Gold (Au) and Copper (Cu) hybrid nanoparticles are assumed to be distributed in the blood. Relevant governing equations are established and appropriately normalized. The Caputo fractional-order derivative is used to convert the transient terms of normalized equations into time-fractional forms, which are then semi-analytically solved using the Laplace transform method to yield complex forms of modified Bessel functions. The concentrated matrix exponential (CME) approach is used to numerically determine approximate inverse Laplace transforms of the updated equations. The distribution patterns of velocity, temperature, and concentration are evaluated graphically. The results showed that the fractional-order derivative and the height of stenosis greatly influence the velocity, temperature and concentration profiles. We also observed that both velocity and temperature decreased with increasing values of Ha. Temperature rises with increasing values of the thermal radiation parameter (Ra) and the Eckert number (Ec) whilst concentration is enhanced with rising values of the chemical reaction parameter (Cr) and the Schmidt number (Sc). Our numerical results show that relevant parameters have considerable influences on skin friction, Nusselt number, and Sherwood number, which are important for understanding blood mobility, heat and mass transfer dynamics, and treating cardiovascular illnesses. Our results are also essential for controlling blood flow, temperature and delivery of drugs to diseased arteries in the human body.

Globally, the quality of groundwater has proven to have been affected by some natural and human activities in recent years. To ensure there is good drinking water (Sustainable Development Goal 6.3, there is a need to elucidate the groundwater quality status of the area of interest. The groundwater in the northwestern parts of Ghana is not yet well characterized. Hence, this study employed a multi-method approach of hydrochemistry, water quality index (WQI), multivariate statistics, and machine models: multiple linear regression (MLR), decision tree regression (DTR), random forest regression (RFR), and artificial neural network (ANN), are combined in the characterization and prediction of the water quality in the area. They are robust in providing conclusions on groundwater assessment that can be relied upon for decision-making processes regarding groundwater usage and monitoring. Except for NO3− and TDS exceeding their standard levels in 22 and 2 locations, respectively, the other physicochemical parameters are within acceptable limits. The groundwater is generally good for domestic usage based on the WQI, with 79.2% of excellent to good waters. The groundwater evolved from Na-type, Cl-type, and Cl(SO4)-Ca(Mg) facies. Agricultural activities are the main source of human impact on the groundwater. Silicate mineral dissolution and ion exchange processes are the natural processes that affect groundwater mineralization, with mineral dissolution being the dominant process. Based on the performance metrics: MAE, MSE and RMSE of the ML methods considered in the WQI forecasting, the order of performance of the models is ANN > RFR > DTR > MLR, with the following respective R2 values 0.9974, 0.9193, 0.8966 and 0.8886.