Velocity Profiles Research Articles

Numerical exploration of micropolar fluid stratified flow over curved stretching sheet under buoyancy effect

AbstractThis article focuses on the effect of buoyancy on the bioconvective micropolar fluid flow over a curved stretching surface under the slip boundary condition. Mass and heat transfer analysis has been analysed using double stratification, linear heat source, chemical reaction and Joule dissipation. The calculation of entropy formation in a fluid flow is also illustrated. Using similarity transformations, the system of partial differential equations is transformed into a set of ordinary differential equations through reduction in the flow equations and then solved using the numerical methodology of the Runge‐Kutta‐Fehlberg 4th‐5th order method. The mathematical data obtained for velocity, temperature, concentration, and bio‐convection profiles with different parameters are presented on graphs. The velocity profile exhibits consistent behaviour near the buoyancy parameter, with a decrease at the boundary followed by an increase. Notably, the velocity profile experiences a decrease under first‐order slip conditions but grows when subjected to second‐order slip. Micro‐rotation intensifies as the material parameter increases. Conversely, temperature and concentration has declined as the stratification parameter rises. Additionally, the concentration of motile microorganisms reduces with increasing Lewis number and Peclet number. As the material parameter rises, entropy decreases while the Bejan number increases.

Natural convection and variable fluid properties of tangent hyperbolic nanofluid flow with Cattaneo-Christov theories and heat generation

The main aim behind this work is that we have to determine the enhancement that happens in thermal conductivity by using the Buongiorno model of nanofluid when the nanofluid particles are added to the tangent hyperbolic base fluid moving above the stretched surface. The viscosity of tangent hyperbolic nanofluid is assumed to be temperature-dependent. The modified form of the Fourier law of heat conduction motivated us; therefore, the Cattaneo-Christov heat and mass flux model is considered to observe its significance for heat and mass transport. The chemical reaction and heat generation are also considered to determine their influence on temperature and concentration gradients. This study is crucial because of its application in industrial manufacturing processes such as the coating of wire, the thinning of copper, the production of paper, photographic films, hot rolling, and the purification of crude oil. In electronic cooling systems, the efficient dissipation of heat in smartphones, computers, and data centers is critical to preventing overheating. Nanofluids, with their enhanced thermal properties, can significantly improve heat transfer rates, ensuring better performance, stability, and energy savings. The partial governing equations arising from fluid flow, mass, and heat transfer are transformed into ordinary differential equations via appropriate similarity variables. The obtained ordinary differential equations are solved numerically by using the Runge-Kutta Fehlberg method in the MATLAB software. The effects of the emerging parameters are represented through graphs. According to the results, the velocity profile upsurges due to the natural convection parameters and curvature parameter, while the power law index declines the velocity profile. As the Brownian motion coefficient rises, the concentration profile diminishes while the temperature profile increases. Both the concentration and temperature profiles increase for larger values of the thermophoresis parameter. The concentration profile declines for larger values of chemical reaction parameters, and enhancement happens in the temperature region.

Efficient modeling of atmospheric infrasound propagation with the Semi-Analytical-Finite-Element (SAFE) method

Downward refraction in the lower atmosphere, attributed to winds and temperature inversion, can enable infrasound to efficiently propagate over long distances inside acoustic waveguides. In this study, we use the semi-analytic finite element (SAFE) method to predict this effect in stratified, inhomogeneous, moving air for range-independent noise propagation over reflective half-planes. We present solutions for different temperature and velocity profiles and compare them to direct numerical solutions of the two-dimensional linearized Euler equations. The SAFE method separates the exact two-dimensional wave equation for a stratified, inhomogeneous, moving medium by expressing the pressure field as a sum of vertical eigenmodes propagating in the range direction. This simplifies the acoustic problem into a one-dimensional eigenvalue problem. As this problem is addressed with the finite-element method, the method can accommodate arbitrary wind and temperature profiles. For large, range-independent domains, the proposed procedure proves to be much more efficient than the tested direct numerical computations. Additionally, it converges against the exact solution of the acoustic problem if enough modes are included in the calculation. Therefore, the method offers a viable procedure for benchmarking other pressure field prediction techniques.

Pedestrians' street-crossing decisions compared between conventional and electric vehicles

To safely cross a road before an approaching vehicle, pedestrians need to accurately judge the vehicle's motion. Recent studies from our lab demonstrated that the noise emitted by a vehicle conveys important information about its motion, particularly in the case of accelerating approaches. Here, we compared street-crossing decisions between conventional (ICEVs) and electric vehicles (EVs) with or without AVAS sounds. The experiment presented high-fidelity audiovisual VR simulations of approaching vehicles, based on recordings of real ICEVs and EVs. The presented velocity profiles included a large variation in acceleration rates, a = 0 to 4.4 m/s^2, and two velocities at the moment of the crossing decision (28 km/h versus 50 km/h). To investigate whether the lower sound level of EVs compared to ICEVs contributes to differences in crossing decisions, we additionally presented a condition in which the sound levels were matched between vehicle types. All experimental conditions were presented in two modality conditions (auditory-only and audiovisual). We compare the crossing decisions between vehicle types, velocity profiles and level profiles in terms of collision probabilities estimated from the measured psychometric functions. Preliminary results confirm differences between crossing decisions made in interaction with EVs compared to ICEVs, reduced in the level-matched conditions.

Aerodynamic and aeroacoustic characterization of an axial fan using Adaptive Mesh Refinement (AMR) based CFD and CAA

This work focuses on numerical analysis of a low-pressure axial fan using Computational Fluid Dynamics (CFD) and Computational Aeroacoustics (CAA) methods. These simulations are performed with the commercial software Hexagon's Cradle scFLOW. The investigation focuses on flow prediction using incompressible Large Eddy Simulation (LES), and acoustic propagation based on the Ffowcs Williams-Hawkings (FW-H) equation. We present a method to evaluate the mesh resolution for LES and a mesh refinement approach to resolve strong flow interactions, particularly near the tip-gap region. Both the aerodynamic and aeroacoustics performance of the fan are compared to experimental measurements for model validation. The pressure rise, velocity profiles and surface pressure fluctuations are captured well. Similarly, the sound propagation results are in good agreement with the experimental measurements. At low-mid frequencies, the blade passing frequencies and subharmonic peaks are captured, and at high frequencies, the broadband energy content is underpredicted, but still reasonably correlated. Additionally, a discussion regarding the mesh quality for LES is presented.

Efficiency analysis of solar radiation on chemical radioactive nanofluid flow over a porous surface with magnetic field

Artificial neural networks have revolutionized machine learning by providing exceptional capabilities for modeling complicated mechanisms and solving various challenges. Backpropagation is an important training technique in the field of artificial neural networks. However, this technique must be optimized when working with complicated fluid dynamics. This study analyzes the three-dimensional radiative flow of a tangent hyperbolic fluid driven by the Cattaneo-Christov flux system across a porous stretching sheet using ANN backpropagation enhanced by Bayesian Regularization approach. Heat and mass transfer analysis includes thermal radiation, chemical reactions and Cattaneo-Christov flux model. Porosity, radiation, chemical reaction rate, and ion slip effect are among the important physical characteristics that are modified to see how they affect fluid dynamics. Using MATLAB's BVP4C solver, the velocity, temperature, and concentration profiles that result from these model equations provide the training dataset for ANNs. The dataset is divided into 80 % for training, 10 % for testing, and 10 % for validation. Performance plots, regression graphs, and error histograms are used to analyze the performance of the LMT-based ANN and demonstrate its high accuracy and efficiency. With an R2 value of 1, the ANN produced a mean squared error of around 10⁻11. Fluid mobility drops as the magnetic parameter grows, while the thermal profile exhibits an increasing trend. Similarly, decreasing fluid velocity is the outcome of raising the porosity parameter. The study's conclusions have great potential for use in sectors that need sophisticated cooling and heating equipment.

Unsteady Upwind Aerodynamics of a Sailing Yacht

_ Sail aerodynamics has been a researched topic since the start of competitive racing, such as the America's Cup and Whitbread Round the World Race. Recently, with restrictions on the use of wind tunnels and towing tanks in the America's Cup, there has been an increase in computational fluid dynamics (CFD) to study the aerodynamics and performance of yacht sails. These studies typically model steady-state conditions, but in contrast, this paper demonstrates the implementation of dynamic wind conditions in Reynolds Averaged Navier Stokes CFD and the effects it has on the aerodynamics of a yacht sailing upwind. A user-defined function was used to give a velocity profile and vary the wind direction with time to simulate a gust condition with a period of 10 s. In addition to the gusting model, steady models were run for the apparent wind angles (AWA) experienced in the gust to see if the dynamic wind conditions could be modelled by a series of steady state snapshots. The results show minor differences in the streamlines of two models and the pressure distributions show no significant difference. There is only a slight difference in sail forces at high AWAs. Although further research would be required this information could be valuable to anyone using CFD to test sail designs. Keywords CFD; transient; steady; upwind; UDF; RANS

Influence of slip conditions and applied magnetic field on peristaltic propulsion of ellis fluid flow in a homogeneous conduit: a parametric analysis

The peristaltic mechanism has recently garnered significant attention in biological and biomedical engineering fields. This study investigates the magnetohydrodynamic (MHD) peristaltic propulsion of an Ellis fluid through a uniform channel, incorporating slip boundary conditions. Both magnetic field presence and slip effects modulate the peristaltic motion, with various factors influencing the sinusoidal waves along the channel walls. Through appropriate assumptions and simplifications, we derive governing equations for the flow and magnetic field. The resulting nonlinear system of differential equations is solved using a perturbation technique. We thoroughly examine three key metrics: velocity, pressure gradient, and streamlines. Findings indicate that magnetic field presence and slip conditions significantly impact flow behaviour. Slip coefficients positively influence velocity and pressure difference, while the magnetic field tends to decelerate the velocity profile. A comparative analysis between Newtonian and non-Newtonian models reveals notable differences in velocity profiles. These insights have potential applications across a wide spectrum of industrial and biological contexts. This study contributes to the understanding of complex fluid dynamics in peristaltic systems, offering valuable perspectives for both theoretical advancement and practical applications in biomedical and industrial fields.

Developing high-precision battery electric forklift driving cycle with variable cargo weight

Driving cycles are essential for assessing vehicle energy demand, estimating driving range, and evaluating environmental impacts. Numerous driving cycles have been developed for passenger cars and buses. However, tailored driving cycles for logistics vehicles, especially forklifts, remains limited. Therefore, we introduce high-precision driving cycles for battery electric forklifts, which include profiles of velocity and cargo mass. The construction of driving cycles involves route selection, data acquisition, micro-trip segmentation, characteristic parameters selection, driving pattern categorization, transition probability matrix development, and driving cycle construction and evaluation. The methods proposed for constructing driving cycles are based on Markov Chain, Micro-trips combinations, and genetic algorithms. The constructed driving cycles are evaluated using relative error analysis and a simulation model. The results confirm that these cycles accurately reflect actual forklift operations and can be utilized to estimate their energy consumption.

Enhancing LSPIV accuracy in low-speed flows and heterogeneous seeding conditions using image gradient

Flow measurement in rivers and channels is crucial for water resource management and infrastructure planning, especially under the context of climate change. However, traditional methods like mechanical current meters and hydroacoustic instruments face limitations in terms of cost, intrusiveness, and accessibility. In recent years, image-based velocimetry techniques have emerged as promising alternatives due to their non-contact nature and cost-effectiveness. Nevertheless, persistent challenges remain, particularly concerning the uniform distribution of surface tracers necessary for precise measurements. These challenges are particularly pronounced in cases involving artificial seeding, where ensuring uniform distribution poses a significant obstacle. To address this issue, this study presents a novel methodology for filtering Large Scale Particle Image Velocimetry (LSPIV) data based on indicators of pixel intensity gradients. The methodology was evaluated across various field measurements under low flow conditions, encompassing a wide range of seeding characteristics. The evaluations demonstrated improvements in mean surface velocity profile estimation, showing reductions of up to 70 % in normalized root mean square error compared to not using filters. Additionally, the results were compared with filters typically employed by experienced LSPIV users, such as background subtraction and cross-correlation coefficient thresholds, showing improvements with the proposed filter. Implementation of the proposed strategy reduces the subjectivity in LSPIV implementation, particularly for users with limited knowledge of the technique, but also require minimal post-processing efforts. The methodology is anticipated to be integrated into existing software tools, thereby enhancing the accessibility of LSPIV for individuals with limited expertise in image velocimetry. Overall, this methodology facilitates cost-effective expansion of hydrological information availability, particularly in resource-constrained regions.

Investigating thermal conduction dynamics in ternary Carreau–Yasuda nanofluids under convective boundary conditions and exponential heat source/sink effects

The analysis of the Carreau–Yasuda nanofluid (CYNF) across a stretching surface has practical applications in several fields, such as heat exchange, engineering, and material science. Scholars may discover novel perspectives for increasing heat transfer performance, establishing advanced materials, and enhancing the efficiency of multiple engineering systems by studying the behavior of CYNF in this particular instance. The energy transfer through trihybrid CYNF flow with the effect of magnetic dipole across a stretching sheet is examined in the present study. The ternary hybrid nanofluid (THNF) has been prepared by the addition of ternary nanoparticles (NPs) in the water (50%) and ethylene glycol (50%). Titanium dioxide (TiO2), silicon dioxide (SiO2), and aluminum oxide (Al2O3) are used in base fluid. The fluid velocity and heat transfer are examined under the impact of Darcy–Forchheimer, chemical reaction, convective condition, activation energy, and exponential heat source. The fluid flow has been stated in form of velocity, energy, and concentration equations. The set of modeled equations is simplified to non-dimensional form of ordinary differential equations (ODEs) by using similarity substitutions. Numerically, the system of lowest order ODEs is calculated through the parametric continuation method. It has been noticed that the temperature field augments against the variation of viscous dissipation and heat source term. Furthermore, the magnetic dipole has significant impact to enhance the thermal curve of THNF whereas falloffs the velocity profile. It can be noticed that the energy propagation rate enhances with the rising numbers of ternary NPs, from 1.22% to 5.98% (nanofluid), 2.30% to 9.61% (hybrid nanofluid), and 3.23% to 11.12% (trihybrid nanofluid).

Irreversibility analysis in an electro‐osmotically driven flow using ternary hybrid nanofluids in a microchannel with a porous material

AbstractFlow enhancement is one of the most significant challenges in microfluidics with extremely low permeability. Based on this, electrokinetics remediation for the double‐layer flow of hybrid ternary nanofluid is proposed based on the transport of ions under constant pumping pressure. The entropy generation volumetric rate relation is also modeled. The nonlinear system of equations is formulated, solved, and validated numerically by the collocation method and shooting Runge–Kutta method. Results are shown graphically to explore the impacts of governing parameters, such as the Darcy parameter, viscosity index, electrokinetic, and Joule heating effects, on the velocity, temperature, entropy, and Bejan number profiles. The flow and heat transmission in microchannels may be significantly changed and controlled by the electric double layer. The findings show that as the electrokinetic parameter's magnitude increases, the flow is slowed down, and thermal dispersion is impeded by nanoparticle collisions, which lowers the velocity field and heat transfer profile.

Modeling of Electric MHD Flow of Nanoparticles in a CMC-Water Based Casson Hybrid Nanofluid over a Porous Medium

The principal focus of this exploration is to study the computationally simulate the combined convection of CMC-water-based Casson hybrid nanofluid through a stretching sheet with electric magnetic force in a porous medium. Copper (Cu) and Silver (Ag) nanoparticles are included to enhance the heat transfer performance of CMC-water. The physical problem is formulated with mathematical PDEs, and to solve this, initially we used similarity transformation technique to reduce the PDEs into ODEs, then Runge-Kutta Fehlberg method (RKFM) of order four with shooting technique is adopted for further reduction from the non-linear ODEs to first order DEs. The influence of key parameters such as the magnetic field parameter (M), porous medium parameters (K), electric field factor (E), radiation parameter (Nr), permeability parameter (λ), Casson parameter (β), and Eckert number (Ec) on relevant physical quantities is illustrated through tables and graphical visualizations. The impact of these parameters on velocity and temperature profiles, as well as on the skin friction coefficient and Nusselt number of the nanofluid, is observed. Our results indicate that an increase in the Casson parameter values leads to a decrease in the velocity of the host fluid in the case of opposite flow, and a similar behavior is observed with the nanoparticle porous medium parameter (K) in the case of assisting flow. Furthermore, the use of the Runge-Kutta Fehlberg Method (RKFM) is found to be more accurate and reliable in dealing with the problem studied in this work.

Effects of Arrhenius activation energy and melting heat transfer on Carreau fluid through a stretching sheet

ABSTRACT This article investigates the effect of activation energy on Carreau fluid flow in the presence of variable thermal conductivity, inclined magnetic field, melting heat transfer, and Soret and Dufour phenomena. A set of suitable similarity transformations is applied for transforming the governing partial differential equations (PDEs) considered for the physical phenomena into non-linear ordinary differential equations (ODEs). We obtained the results by solving the non-linear ODEs numerically which describe the behavior of the velocity, temperature, and concentration profiles of the fluid against the governing parameters and illustrated these graphically. The velocity distribution decreases for angle of inclination while it is increasing against higher melting parameter. The temperature distribution enhances with higher modified Dufour parameter and Prandtl number while it declines for thermal conductivity, activation energy, and melting parameters. The concentration distribution increases for melting parameter, Soret number, and activation energy parameter while decreasing for temperature difference parameter, Schmidt number, and reaction rate parameter. Skin friction, Nusselt and Sherwood numbers are evaluated numerically against the various governing parameters. Accuracy of the present work is illustrated and established through comparison carried out for skin friction versus magnetic parameter with existing results in the literature.

Characteristics of gusts with different velocity profiles and control parameters

The characteristics of gust flow are essential for gust response and alleviation. To investigate the influence of control parameters on gusts with different velocity profiles, four vertical gust profiles were designed. Methods were proposed to generate them with two pitching airfoils in a low-speed water tunnel. The velocity field was measured via phase-locked particle image velocimetry. The coefficient of determination R2 was proposed to evaluate the generated gust profile quality, which referred to the quality of the vertical velocity profile. The influence of control parameters on different gust profiles was investigated, and the cause of the profile distortion was explored. For continuous sine gusts, the gust ratio GR increased approximately linearly with the pitching amplitude, while the gust ratio initially increased and then decreased with increasing frequency. As the two control parameters increased, the flow uniformity decreased because the airfoil wakes disturbed the measured flow field. In terms of continuous 1-cosine gusts, the gust ratio increased nonlinearly with pitching amplitude. Compared with those of the sine gusts, the GR values of the 1-cosine gusts were higher, whereas the R2 values were lower. In addition, the discrete and continuous gust profiles had similar distortion near the peaks. However, discrete gusts had lower R2 values than continuous gusts because the starting and stopping vortices of the pitching airfoils disturbed the gust flow. Based on these findings, a method to improve the profile quality and field uniformity by increasing the spacing of the pitching airfoils was proposed. This work can support further studies of gust response and alleviation during complex gust encounters.

Non-similar analysis of heat generation and thermal radiation on Eyring-Powell Hybrid nanofluid flow across a stretching surface

This paper portrays a two-dimensional mathematical model developed for the analysis of Eyring-Powell hybrid nanofluid flow, incorporating variable temperature and velocity profiles. This study investigates the flow through a porous media with a mixture of hybrid nanoparticles (copper dioxide, magnetite) integrated into ethylene glycol ([Formula: see text]) across a stretching sheet. The model takes magnetic effects, heat generation, and thermal radiation into account. Additionally, nonsimilar partial differential equations (PDEs) are transformed into ordinary differential equations using the local nonsimilarity approach. These equations are then numerically solved using the built-in Matlab function bvp4c. To examine the effects of adjusting parameters on heat, mass transfer, and skin friction, the results are displayed graphically. With an increase in the given values of magnetic field [Formula: see text], the velocity profile [Formula: see text] is seen to decay. Moreover, it is observed that the hybrid nanofluid density and dynamic viscosity increase as the volume fraction rises. It is estimated that the thermal conductivity and viscosity of the [Formula: see text] hybrid nanofluid are expected to increase to 4.1% and 12.35%, respectively, and to 71.55% and 78.01%, respectively, for volume concentrations ranging from 0.02% to 0.05%. It is also concluded that the local skin-friction coefficient has the opposite trend while the local Nusselt number rises monotonically with both the slip velocity parameter and the surface convection parameter. This research has broad applications In the glass and polymer industries, metallic plate cooling, plastic sheet contractions, etc.

Enhancing the two-layer k-epsilon turbulence model through rough wall modification

Surface roughness significantly influences turbulence structures, affecting skin friction and velocity profiles. Precisely modeling the roughness effects is essential for reliable numerical simulation results in various engineering applications. This paper introduces enhancements to the two-layer k-epsilon (k−ε) turbulence model, incorporating surface roughness effects by adjusting variables in prescribed length scales and turbulent boundary conditions and ensuring the model switches between different roughness regimes. The accuracy of the enhanced model was validated using the Grigson–Colebrook type roughness function and experimental data from flat plate flows, as well as more complex geometries such as sand dune flow and ramp flow. The modified model demonstrated strong agreement with experimental data, accurately predicting the effects of roughness across diverse flow conditions, particularly in terms of velocity profiles. The proposed roughness modifications substantially improve the model's capability to simulate turbulent flows over rough surfaces, providing a valuable tool for predicting flow behavior in engineering applications involving rough surfaces.

Tangent hyperbolic MHD nanoliquids on non-isothermal stretched sheets: Analyzing the impact of transport parameters, variable fluid properties and convective boundary conditions

The key focus of this research is to look at how tangent hyperbolic magnetohydrodynamic (MHD) nano-liquids move in a non-isothermal coagulated stretched sheet. In this study, we intend to explore how fluid behavior responds to alternations in transport physical parameters. The coagulated sheet is subjected to two distinct boundary conditions to inspect the heat and mass transport rate of the nano liquid. The convective heat boundary condition (CBC) and mass-convective boundary condition (MCBC) are employed to specify the physical conditions at the boundaries of the problem domain. The boundary conditions, responsible for regulating heat flow and mass transfer rates, play a crucial role in shaping the liquid’s behavior. Using a similarity solution, the partial differential equation describing the flow of mass and heat within the system transforms into an interconnected network of non-linear ordinary differential equations. These mathematical equations are subsequently figured out using a numerical finite difference method. This study additionally examines the correlation between thermophoresis and Brownian motion, two fundamental concepts in the dynamics of colloidal suspensions. The study’s findings indicate that the temperature profile increases in all scenarios when the variable thermal conductivity and variable viscosity parameters are increased. In contrast, for the same parameters, the velocity profile is decreased. Further, increasing wall thickness reduces heat dissipation; consequently, the temperature profile similarly affects the velocity power index. The Biot number improves the rates of temperature transfer. These results underscore the significant influence of these parameters in predicting the behavior of MHD tangent hyperbolic nanofluids. This study elucidates the intricate interaction among different physical parameters in the dynamics of nano liquids, which holds significant implications for various industrial applications.

Numerical investigation into the transition of electrohydrodynamic spraying modes and behaviors

Electrohydrodynamic (EHD) spraying is an interesting phenomenon where the liquid subjected to an electrical stress deforms into an electrified liquid drop, a thin liquid jet, or the so-called Taylor cone, which is also highly complicated owing to its various spraying modes and behaviors. Due to the lack of critical information such as the electric charge density and internal velocity profile, the underlying physics behind the transition of different EHD spraying modes are still not adequately understood. In light of this, we conducted a numerical investigation into the transition of EHD spraying modes and behaviors under the three most important operating parameters including electric voltage, nozzle height, and liquid flow rate. Four typical spraying modes, namely, dripping, cone-jet, multi-jet, and jetting, are observed. From the numerical results, we obtained the voltage distribution in the environment, electric charge density at the liquid–air interface, and velocity profile inside the liquid, which help us to comprehensively analyze and explicate the influences of these three parameters on the transition of spraying modes and behaviors. This eventually leads us to a spraying mode map showing the correlation between the spraying modes and the electric Bond number. To the best of our knowledge, this is the first numerical work focusing on the transition of EHD spraying mode, from which we intend to expand the knowledge of this interesting phenomenon.

Hydrothermal dynamics of darcy Forchheimer ternary hybrid nanofluid flow past bended surface with active—passive controls

This dynamic study investigates hydrothermal and rheological properties of two-dimensional ternary nanofluid flow by using active passive control mechanisms on nanoparticles navigating a porous curved surface. The working fluid contains nanometer sized spherical shaped particles of three different metals [Formula: see text], which are homogenously and stably dispersed in liquid dihydrogen monoxide as host fluid. A strong magnetic force of strength [Formula: see text] acts along radial direction of curved surface. Thermal radiation term in heat equation suggests a strong heat source in the vicinity. This unique amalgamation, which has not been addressed so far by any researcher incorporates Brownian motion and thermophoresis to construct the hydrothermal framework. The passive control of nanoparticles on surface influenced by Brownian movement and thermophoresis, which is considered more realistic in comparison to constant concentration hypothesis (active control), have been taken into account. The nanoliquid flow is governed by system of Partial Differential Equations (PDEs) that cater thermophysical properties of nanoparticles. After simplifying the system to Ordinary Differential Equations (ODEs) using suitable transform, it is solved numerically using bvp4c in MATLAB 2023a. The obtained graphical and numerical results are discussed in detail to explain physics of observed thermo-rheological behaviour and mass diffusivity. The study reveals that curvature and porosity factors have opposite effects on velocity profile. All involved parameters augment temperature profile for both active and passive controls except curvature factors. In all the cases, active control assures higher temperature over passive control. Dual consequences have been noted for active and passive controls for concentration panels in most cases. Nusselt number is found increasing for increasing nanoparticles concentration with ternary nanofluid having maximum heat transfer rate. This study significantly contributes to the knowledge of ternary nanofluidic thermo-rheological analysis on curved stretching surface having numerous applications in mechanical, thermal and industrial domains. It also offers insights for developing advanced coatings and materials in industrial and engineering context.