Magnetic Field Parameters Research Articles

Operational SYM‐H Forecasting With Confidence Intervals Using Deep Neural Networks

AbstractIn this study, we develop a robust real‐time forecast system for the SYM‐H index using Deep Neural Networks and real‐time Solar Wind measurements along with Interplanetary Magnetic Field parameters. This system provides not only one‐off forecasts but also quantile‐based confidence intervals, offering a range within which the observed SYM‐H values are expected to fall, enhancing forecast reliability and usability. The model is tested both on historical level 2 science‐ready data and on preliminary observations, which are closer to the operational environment that the model is expected to work on, demonstrating the model's robustness and practical utility in real‐time scenarios. The integration of quantile forecasts into SYM‐H prediction models represents a significant advancement, providing decision‐makers with more accurate and trustworthy information to manage the hazard of geomagnetic storms.

A new theoretical model for high-order harmonics of SH0 mode ultrasonic guided waves based on magnetostrictive mechanism

In recent years, it was found that magnetostrictive ultrasonic guided wave transducers experimentally excited nonlinear harmonic components under a certain combination of dynamic and static magnetic fields. However, a satisfactory model for the relevant excitation mechanisms is not available. In this study, a new magnetostrictive guided wave excitation model was established and the causes for harmonics generation were analyzed. In addition, the calculation results of the model were obtained under different magnetic field parameters. We firstly changed the calculation conditions of magnetostrictive strain in the model and then theoretically calculated the odd and even harmonics of SH0 mode ultrasonic guided waves for the first time. Furthermore, the accuracy of the model was experimentally verified. By changing the strength ratio of the dynamic magnetic field to the static magnetic field (HD/HS), the excitation amplitudes of odd and even harmonics could be regulated with a magnetostrictive sensor. As the ratio of HD/HS increased, the normalized amplitude of the second harmonic firstly increased and then decreased, whereas the normalized amplitude of the third harmonic showed an exponential growth with different curvatures. This study enriched the theory of magnetostrictive guided wave excitation and provided a theoretical basis for the applications of magnetostrictive sensors.

МГД-волны в области предфронта межпланетных ударных волн 6 и 7 сентября 2017 г.

We analyze strong space weather disturbances during first ten days of September 2017, using the geomagnetic Dst index, parameters of normals to interplanetary shock fronts, direct measurements of interplanetary magnetic field, solar wind, and cosmic ray parameters. By applying spectral analysis methods to interplanetary medium data, we analyze MHD waves at the pre-front of two interplanetary shocks responsible for geomagnetic disturbances on September 6 and 7, 2017. The main results are as follows: the contribution of three branches of MHD waves (Alfvén, fast and slow magnetosonic) to the observed spectrum of the interplanetary magnetic field modulus has been established. We have confirmed the conclusion that the generation of Alfvén waves and fast magnetosonic waves is due to the presence of low-energy proton fluxes (Ep~1 MeV) at the pre-front of interplanetary shocks. We have also discovered a predominant contribution of slow magnetosonic waves to the observed spectrum of the interplanetary magnetic field modulus, but its reason is yet unknown. It is noted that different orientations of the normals to the interplanetary shock fronts and to the direction of the interplanetary magnetic field average vector on spacecraft located fairly close to each other may indicate waviness of the shock front structure.

Явления гистерезиса в отклике геомагнитной активности и параметров космических лучей на вариации межпланетной среды во время магнитной бури

The dynamics of the intensity of cosmic rays is known to be different on the ascending and descending branches of the 11-year solar cycle, i.e., hysteresis phenomena are observed. Recently, it has been obtained that at shorter intervals on the scale of magnetic storms there are also signs of hysteresis in dependences of cosmic ray cutoff rigidities R (geomagnetic thresholds) on heliosphere and geosphere parameters. R is the rigidity below which a particle flux is cut off due to geomagnetic shielding. In this paper, we have analyzed the dependence of the geomagnetic storm index Dst and the variation of the ΔR thresholds on interplanetary magnetic field (IMF) and solar wind (SW) parameters during the two-step magnetic storm on September 7–8, 2017. We have found hysteresis phenomena in the following paired series: (1) dependences of Dst on SW and IMF parameters, and (2) dependences of ΔR on SW and IMF parameters. We have established that the dependence curves in the storm descending phase (main phase) and ascending phase (recovery phase) do not coincide — hysteresis loops are formed. A specific feature of the storm under study is the second lowering of Dst in the recovery phase. The hysteresis pattern reflects this specific storm dynamics, forming two hysteresis loops in response to the two Dst drops.

MHD waves at the pre-front of interplanetary shocks on September 6 and 7, 2017

We analyze strong space weather disturbances during first ten days of September 2017, using the geomagnetic Dst index, parameters of normals to interplanetary shock fronts, direct measurements of interplanetary magnetic field, solar wind, and cosmic ray parameters. By applying spectral analysis methods to interplanetary medium data, we analyze MHD waves at the pre-front of two interplanetary shocks responsible for geomagnetic disturbances on September 6 and 7, 2017. The main results are as follows: the contribution of three branches of MHD waves (Alfvén, fast and slow magnetosonic) to the observed spectrum of the interplanetary magnetic field modulus has been established. We have confirmed the conclusion that the generation of Alfvén waves and fast magnetosonic waves is due to the presence of low-energy proton fluxes (Ep~1 MeV) at the pre-front of interplanetary shocks. We have also discovered a predominant contribution of slow magnetosonic waves to the observed spectrum of the interplanetary magnetic field modulus, but its reason is yet unknown. It is noted that different orientations of the normals to the interplanetary shock fronts and to the direction of the interplanetary magnetic field average vector on spacecraft located fairly close to each other may indicate waviness of the shock front structure.

Hysteresis phenomena in the response of geomagnetic activity and cosmic ray parameters to variations in the interplanetary medium during a magnetic storm

The dynamics of the intensity of cosmic rays is known to be different on the ascending and descending branches of the 11-year solar cycle, i.e., hysteresis phenomena are observed. Recently, it has been obtained that at shorter intervals on the scale of magnetic storms there are also signs of hysteresis in dependences of cosmic ray cutoff rigidities R (geomagnetic thresholds) on heliosphere and geosphere parameters. R is the rigidity below which a particle flux is cut off due to geomagnetic shielding. In this paper, we have analyzed the dependence of the geomagnetic storm index Dst and the variation of the ΔR thresholds on interplanetary magnetic field (IMF) and solar wind (SW) parameters during the two-step magnetic storm on September 7–8, 2017. We have found hysteresis phenomena in the following paired series: (1) dependences of Dst on SW and IMF parameters, and (2) dependences of ΔR on SW and IMF parameters. We have established that the dependence curves in the storm descending phase (main phase) and ascending phase (recovery phase) do not coincide — hysteresis loops are formed. A specific feature of the storm under study is the second lowering of Dst in the recovery phase. The hysteresis pattern reflects this specific storm dynamics, forming two hysteresis loops in response to the two Dst drops.

Computational simulation of Casson hybrid nanofluid flow with Rosseland approximation and uneven heat source/sink

This article candidly presents the magnetohydrodynamics Casson hybrid nanofluid flow over a stretching surface. In the present study, we added a nonuniform heat source or sink and non-linear thermal radiation. We considered Al2O3 and copper nanoparticles to have antibacterial and antiviral properties without any harmful impacts and used water as the host fluid. We simplified the governing flow equations by using suitable self-similarity variables, which are used to convert PDEs to ODEs. The mathematical equations are numerically solved by using the bvp5c technique in the MATLAB software. Additionally, with higher values of the magnetic field and Casson fluid parameters the velocity profile decreased. The temperature profile is enhanced by increasing the magnetic field and thermal radiation parameters. Increasing the Casson fluid and radiation parameters enhances the skin friction and Nusselt number profiles. Alumina nanoparticles find applications in cosmetic fillers, polishing materials, catalyst carriers, analytical reagents. Copper nanoparticles have high electrical conductivity, which has many uses in electrical circuits and biosensors.

Aviation aspects of engine oil conveying copper tiny particles embedded in a rotating disk with a binary chemical reaction

Nanofluids have significant industrial applications and motivating heat transfer characteristics for various factors that contribute to the movement of nanofluids are essential significance. The aim of the present study focused on importance of heat transfer analysis on engine oil conveying copper nano particles embedded in a porous rotating disk with potential application in aerospace technology. In this model we considered magnetohydrodynamics, non-linear thermal radiation, thermophoresis and Brownian motion. The present investigation utilized copper nanoparticle and engine oil as a base fluid. The mathematical flow equations are transformed into ordinary differential equations (ODEs) by employing suitable self-similarity variables. The resultant ordinary differential equations are solved numerically by using the Midrich technique in the Maple software. The results are calculated to measure the impact of active parameters on velocity, temperature, concentration equations are presented graphically and in tabular form. Higher values of the magnetic field parameter the velocity profile decreased while the opposite tendency we noticed on energy profile. When increasing the radiation parameter values the energy profile increased. In both cases when increasing the magnetic field and radiation parameter values the Nusselt number profile increased. The research has important implications in a number of real-world situations. In particularly, the advancement of aircraft technology has presented manufacturers with new criteria and problems for the functioning of their devices. It is essential that, in order to guarantee the secure operation of aerospace machinery, the failure mechanisms be identified and the operational durability of critical structural components be improved as quickly as possible.

Circular-ring tied arc loaded excellent metamaterial absorber for EMI shielding of Wi-Fi signal and impurity sensing of cooking oil

This paper demonstrates a unique symmetric structure excellent metamaterial absorber (MMA) loaded with circular-ring tied arcs. The FR4 substrate-based MMA can accomplish 98.88 % and 99.81 % absorption maximums at the Wi-Fi and 5G frequencies of 2.4 GHz and 5.0 GHz respectively. The unit cell dimension of 0.16λ0×0.16λ0×0.0128λ0 is considered where the wavelength, λ0 is calculated at 2.4 GHz. The performance of the absorber is analyzed through the electric field, magnetic field, surface current, and effective parameters. The dimensions are optimized through the parametric analysis of the developed model in CST software. The model exhibits stability up to 60° for Transverse electric and magnetic polarizations. During electromagnetic interference (EMI) shielding demonstration, it can achieve a high shielding effectiveness (SE) of 54.34 dB at 2.4 GHz and 77.96 dB at 5.0 GHz. For sensing operation, it can attain a quality factor (Q-factor) of 25.61, a sensitivity of 3.30 %, and a figure of merit (FoM) of 84.51. The prototype measurements of the MMA for EMI shielding and impurity sensing of oil samples have a strong correlation with the simulation performance. Because of the high SE, Q-factor, sensitivity, and FoM, the developed MMA can be a competitive candidate in EMI shielding and oil impurity sensing applications.

Flow and heat transfer insights into a chemically reactive micropolar Williamson ternary hybrid nanofluid with cross-diffusion theory

Abstract The need for efficient nanotechnology has led to unexpected developments. Conserving continuous thermal propagation is essential in many industrial and thermal systems because it improves the efficiency of thermal engineering engines and machinery. Therefore, a promising platform to increase thermal power energy is the hybridization of magnetic nanoparticles in a heat-supporting, non-Newtonian fluid. In light of the above applications, a mathematical model is established to analyze the variable fluid features of the thermally radiative and chemically reactive flow of a micropolar Williamson ternary hybrid nanofluid with electromagnetohydrodynamic and electroosmosis forces on a porous stretching surface. Stratification boundary conditions and variable fluid properties were used to analyze the thermal and solutal behavior of the fluid flow. Furthermore, to measure the disorder of the flow system, entropy generation was considered by the impact of Joule heating and viscous dissipation. To develop the numerical scheme BVP4C in MATLAB, we first converted the mathematical flow model into two ordinary differential equations using a suitable transformation. The graphical and numerical results were determined against several parameters of a ternary hybrid nanofluid ( MWCNT , A l 2 O 3 , SiC ) ({\rm{MWCNT}},\hspace{0.25em}{\rm{A}}{{\rm{l}}}_{2}{{\rm{O}}}_{3},\hspace{0.25em}{\rm{SiC}}) and unary nanofluid ( A l 2 O 3 ) ({\rm{A}}{{\rm{l}}}_{2}{{\rm{O}}}_{3}) . The results indicate that the heat transfer rate is more prominent in the ternary hybrid nanofluid than in the unary nanofluid because the addition of nanofluids to the base fluid is used to improve the heat transport rate. It can be seen from the figures that a greater estimation of the magnetic and electric field parameters improves the fluid velocity because, for low values of M ≤ 1 M\le 1 , the aiding force is dominant compared to the retarding force, which results in an improvement in the velocity profile. Furthermore, the entropy generation rate increases for higher values of the Brinkman number and temperature ratio parameter because more heat is produced due to the greater values of Br {\rm{Br}} .

Lie symmetry neural networking for heat transfer in magnetized williamson fluid (MWF) with heat source (HS) and thermal slip (TS)

In the analysis, design, and optimization of a wide range of engineering applications involving stretching surfaces and fluid flow, the skin friction coefficient (SFC) at a stretching surface with heat transfer is an important parameter that reflects the fluid dynamics, heat transfer characteristics, and surface interactions. Owing such importance, the purpose of present article is offer artificial neural networking remedy for evaluation of SFC for Williamson flow field with thermal slip and heat source effects. The Williamson fluid flow is realized by considering surface stretching with an externally supplied magnetic field. The energy equation is used to address the heat transmission. The constructed differential system for flow field is solved by conjecturing artificial neural networking with Lie symmetry and shooting methods. Artificial Neural Networking (ANN) model is developed to predict the surface quantity namely SFC at thermally magnetized surface. The major findings includes the variation in SFC for pertinent flow parameters and we found that in the presence of heat transfer aspects, the SFC admits declining nature towards Weissenberg number while opposite is the case for magnetic field parameter.

Magnetically Driven Quadruped Soft Robot with Multimodal Motion for Targeted Drug Delivery.

Untethered magnetic soft robots show great potential for biomedical and small-scale micromanipulation applications due to their high flexibility and ability to cause minimal damage. However, most current research on these robots focuses on marine and reptilian biomimicry, which limits their ability to move in unstructured environments. In this work, we design a quadruped soft robot with a magnetic top cover and a specific magnetization angle, drawing inspiration from the common locomotion patterns of quadrupeds in nature and integrating our unique actuation principle. It can crawl and tumble and, by adjusting the magnetic field parameters, it adapts its locomotion to environmental conditions, enabling it to cross obstacles and perform remote transportation and release of cargo.

Toroidal modified Miller-Turner CME model in EUHFORIA: Validation and comparison with flux rope and spheromak

Rising concerns about the impact of space-weather-related disruptions demand modelling and reliable forecasting of coronal mass ejection (CME) impacts. In this study, we demonstrate the application of the modified Miller-Turner (mMT) model implemented within EUropean Heliospheric FORecasting Information Asset (EUHFORIA) in forecasting the geo-effectiveness of observed coronal mass ejection (CME) events in the heliosphere. Our goal is to develop a model that not only has a global geometry, in order to improve overall forecasting, but is also fast enough for operational space-weather forecasting. We test the original full torus implementation and introduce a new three-fourths Torus version called the Horseshoe CME model. This new model has a more realistic CME geometry, and overcomes the inaccuracies of the full torus geometry. We constrain the torus geometrical and magnetic field parameters using observed signatures of the CMEs before, during, and after the eruption. We perform EUHFORIA simulations for two validation cases -- the isolated CME event of 12 July 2012 and the CME--CME interaction event of 8-10 September 2014. We performed an assessment of the model's capability to predict the most important $B_z$ component using the advanced dynamic time-warping (DTW) technique. The Horseshoe model predictions of CME arrival time and geo-effectiveness for both validation events compare well with the observations and are weighed against the results obtained with the spheromak and FRi3D models, which were already available in EUHFORIA. The runtime of the Horseshoe model simulations is close to that of the spheromak model, which is suitable for operational space weather forecasting. However, the capability of the magnetic field prediction at 1 AU of the Horseshoe model is close to that of the FRi3D model. In addition, we demonstrate that the Horseshoe CME model can be used for simulating successive CMEs in EUHFORIA, overcoming a limitation of the FRi3D model.

Entropy generated nonlinear mixed convective beyond constant characteristics nanomaterial wedge flow

Background and objectiveNanomaterial flows at present have received much attention of the researchers. Such motivation stems for their utilization in pharmaceutical, industrial, petroleum, manufacturing and engineering applications including regenerative medicine, treatment of cancer, electronic device cooling, solar collector, mineral oil, antimicrobial agents, thermal storage system, transformer cooling and X-imaging etc. Higher thermal energy requirement in several electrical and mechanical systems is desired in recent time due to high advancement of science and technology. For important application here the stagnation point flow due to wedge with nonlinear convection is explored. For porous media, the Darcy-Forchheimer relation is considered. Characteristics of nanofluid is added by utilizing Buongiorno's model. Variable fluid characteristics are under consideration. Applied magnetic field is accounted. Energy expression comprises thermal radiation, Brownian motion, Ohmic heating, thermophoresis and heat generation. First order reaction and entropy rate are considered. MethodologyNonlinear differential expressions are changed into dimensionless ordinary systems through adequate transformations. The resultant nonlinear ordinary systems are solved through optimal homotopy analysis technique (OHAM). ResultsOutcomes for influential variables about temperature, velocity, concentration and entropy rate have been arranged. Here results show that for magnetic field the liquid flow and entropy rate have opposite scenarios. Thermal distribution and concentration have reverse effects for random motion variable while similar effect holds for thermophoresis parameter. Magnetic field and diffusion parameters contribute to augment entropy generation. Higher values of temperature dependent electrical conductivity variable lead to increase entropy rate. Thermal distribution for radiation and Eckert number is similar.

Effect of Rarefactions and Convective Heat Change on Free Convective Unsteady MHD Flow in a Slip-Flow Regime Past a Vertical Wall with Convective Surface Boundary Condition

The study investigates the unsteady free convective two-dimensional MHD flow past a vertical porous plate with convective surface boundary condition in porous medium in slip flow regime under the action of variable suction velocity. Analytical solutions are obtained for the system using perturbation technique that converts non-linear coupled governing partial differential equations into non-dimensional form of ordinary differential equations. Effects of variable suction velocity, rarefactions parameter and heat change parameter are analysed and discussed graphically for various values of effective physical parameter such as Grasshof number, Magnetic field parameter, Prandtl number, Permeability parameter on fluid velocity and temperature, skin friction, and heat transfer.

Entropy optimization on Casson nanofluid flow with radiation and Arrhenius activation energy over different geometries: A numerical and statistical approach

This study employs numerical and statistical approaches to investigate the entropy optimization of steady Casson nanofluid flow over three different geometries subject to boundary conditions induced by convective flow. Multiple linear regression is employed to statistically examine. The present model incorporates several novel elements, such as Arrhenius activation energy, Brownian motion, the Cattaneo-Christov dual flux, thermophoresis, thermal radiation, and so on. Moreover, a comparison is presented between Newtonian and non-Newtonian fluids. By applying the proper similarity transformations, ordinary differential equations (ODEs) are obtained by converting foundational partial differential equations (PDEs). The Runge-Kutta fourth-order method is utilised to solve the obtained ODEs along with the shooting technique. The outcomes are visually depicted via tables and graphs. The velocity drops with increasing Grashof number, and the magnetic field becomes progressively more forceful as the suction parameter increases. The temperature gets reduced with the increase of the suction parameter, solute Grashof number increases with the magnetic field, thermophoresis, and radiation parameters. The entropy is observed to rise with the increase of the effective parameters (magnetic field, Brinkmann number and radiation). The MAD (mean absolute deviation), MSE (mean squared error), and RMSE (root mean square error) values are approaching zero, indicating that the derived outcomes are highly accurate. A lower MAPE (mean absolute percentage error) suggests that the model has a higher level of precision. Therefore, the outcomes of the present model are more precise and reliable. This study has various potential applications such as power plant heat exchangers, material processing industries, and solar thermal energy systems.

Time Series of Magnetic Field Parameters of Merged MDI and HMI Space-weather Active Region Patches as Potential Tool for Solar Flare Forecasting

Solar flare prediction studies have been recently conducted with the use of Space-Weather MDI (Michelson Doppler Imager on board Solar and Heliospheric Observatory) Active Region Patches (SMARPs) and Space-Weather HMI (Helioseismic and Magnetic Imager on board Solar Dynamics Observatory) Active Region Patches (SHARPs), which are two currently available data products containing magnetic field characteristics of solar active regions (ARs). The present work is an effort to combine them into one data product, and perform some initial statistical analyses in order to further expand their application in space-weather forecasting. The combined data are derived by filtering, rescaling, and merging the SMARP and SHARP parameters, which can then be spatially reduced to create uniform multivariate time series. The resulting combined MDI–HMI data set currently spans the period between 1996 April 4 and 2022 December 13, and may be extended to a more recent date. This provides an opportunity to correlate and compare it with other space-weather time series, such as the daily solar flare index or the statistical properties of the soft X-ray flux measured by the Geostationary Operational Environmental Satellites. Time-lagged cross correlation indicates that a relationship may exist, where some magnetic field properties of ARs lead the flare index in time. Applying the rolling-window technique makes it possible to see how this leader–follower dynamic varies with time. Preliminary results indicate that areas of high correlation generally correspond to increased flare activity during the peak solar cycle.

Entropy generation analysis on hybrid dusty nanofluid flow over a heated stretching sheet: aerospace technology

Over the last few decades, many kinds of advanced substances that are acceptable for specific aerospace applications have been developed. An aircraft engine has a number of duties that are performed by kerosene oil. These responsibilities include oiling, air conditioning, servicing, preventing corrosion and reducing loudness. Maintenance is a matter of extreme importance. Without maintenance, it is only inevitable that any moving component might have the capacity to run away quickly. This project’s efforts are focused on reducing expenditures by extending the usable lifetimes of aviation components. Additionally, the initiative aims to improve fuel efficiency, load capacity and travel distance. The importance of the heat transfer investigation on MHD dusty hybrid nanofluid across a porous stretching sheet with entropy generation and thermal radiation is examined in the current research. We used the self-similarity transformation to transform the partial differential equation into ordinary differential equations. After applying transformations, for graphical purposes we have used the Bvp4c technique in MATLAB solver. The effect of active important parameters affecting the fluid’s capacity to transfer importance is shown in graphs and tables. For higher values of the magnetic field parameter, the velocity outline decreased, while the opposite nature was noticed in the energy profile. Based on our investigation, we found that mixed nanofluids are more effective in transferring energy carriers compared to dusty tiny fluids.

Effects of Longitudinal Alternating Magnetic Field on the Microstructure and Properties of CMT-WAAM Al-5%Mg Alloy

The major challenges in wire arc additive manufacturing (WAAM) of aluminum alloys include improving the forming quality, reducing pore and crack defects, and optimizing the overall mechanical properties. In this study, an external longitudinal alternating magnetic field (LAMF) was applied to assist cold metal transfer (CMT) WAAM process of Al-5%Mg alloy. This study compared the effects of different LAMF intensity parameters on the electrical behavior, molten droplet transition, macroscopic forming, microstructure and mechanical properties of CMT-WAAM multi-layer thin-walled structures. Compared with the situation without the alternating magnetic field, the application of an external LAMF could cause the arc to expand and rotate, deflect droplets and stir the molten pool periodically. When the alternating magnetic field parameters were set at a current of 3A and frequency of 100Hz with magnetic field intensity of 9mT, the deposited samples achieved macroscopic forming with superior surface quality and geometric accuracy, and the internal defect rate was reduced from 0.742% to 0.168%. Also, the mean grain size of the deposited layer was reduced from 186μm to 154μm, and the average hardness was increased from 68.1HV0.2 to 91.1HV0.2 with an improvement rate of 33.7%. Moreover, the longitudinal tensile strength was increased from 249 MPa to 257 MPa, the transverse tensile strength was increased from 264 MPa to 273 MPa, and the yield strength and elongation at break were both increased. This study demonstrates theoretical guidance for enhancing the component overall performance of aluminum alloy LAMF-WAAM technology.

Parametric Optimization of Entropy Generation in Hybrid Nanofluid in Contracting/Expanding Channel by Means of Analysis of Variance and Response Surface Methodology

This study aims to propose a central composite design (CCD) combined with response surface methodology (RSM) to create a statistical experimental design. A new parametric optimization of entropy generation is presented. The flow behavior of magnetohydrodynamic hybrid nanofluid (HNF) flow through two flat contracting expanding plates of channel alongside radiative heat transmission was considered. The lower fixed plate was externally heated whereas the upper porous plate was cooled by injecting a coolant fluid with a uniform velocity inside the channel. The resulting equations were solved by the Homotopic Analysis Method using MATHEMATICA 10 and Minitab 17.1. The design consists of several input factors, namely a magnetic field parameter (M), radiation parameter (N) and group parameter (Br/A1). To obtain the values of flow response parameters, numerical experiments were used. Variables, especially the entropy generation (Ne), were considered for each combination of design. The resulting RSM empirical model obtained a high coefficient of determination, reaching 99.97% for the entropy generation number (Ne). These values show an excellent fit of the model to the data.