Mani Sankar

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Research Subjects

Thermodynamics

Research Interests

Mani Sankar has a total of 79 co-authors. Here are the top co-authors by number of shared publications:

H. A. Kumara Swamy
Department of Mathematics, School of Engineering, Presidency University, Bengaluru, India
10 shared publications
N. Keerthi Reddy
Ulsan National Institute of Science and Technology
10 shared publications
Younghae Do
Department of Mathematics, Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, Daegu, 41566, Republic of Korea
8 shared publications
H. A. Kumara Swamy
Department of Mathematics, Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, Daegu, Republic of Korea
6 shared publications
N. Keerthi Reddy
Department of Mechanical Engineering, Ulsan National Institute of Science and Technology 2 , Ulsan 44919, South Korea
4 shared publications
S. Kiran
Nitte Meenakshi Institute of Technology
4 shared publications

Latest Publications

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- 13 October 2026
- Published by MDPI AG in Algorithms
Reliability and Availability of a Repairable k-Out-of-n System via Event-Triggered Maintenance Semi-Markovian Modelling Reinforcement Q-Learning, and Copula Repair
by Suresh Rasappan, Mani Sankar, Praveen Kumar Poonia
This paper develops a reliability and availability model for a repairable two-tier k-out-of-n computer network system. Four analytical components are combined: event-triggered repair intensification, Gumbel–Hougaard copula-based restoration, a semi-Markovian state-transition formulation, and a reinforcement Q-learning layer for adaptive threshold selection. Subsystem 1 consists of n identical web servers operating under a k-out-of-n: G policy. Subsystem 2 contains three identical database replicas under a one-out-of-three: G policy. The full system is available only when both subsystems and both load balancers are operational. State probabilities are derived via the supplementary variable technique and Laplace transforms. The semi-Markovian extension decouples embedded-chain transition probabilities from state-specific holding-time distributions. Stationary availability is expressed as the weighted ratio of mean up-state sojourn times to total mean sojourn times, accommodating non-exponential failure and repair time laws. The event-triggered policy fires repair intensification when the system availability $A (t)$ falls; specifically, when the degradation indicator $Ξ (t) = 1 - A (t)$ crosses a threshold subject to a minimum inter-event time. A Q-learning agent selects the threshold–gain action from a finite set, updating a Q-table by the Bellman rule. Numerical results from MATLAB 2026 show baseline availability converging to $0.8581$ , $0.8537$ , and $0.8496$ for $k = 5$ , $k = 15$ , and $k = 25$ . Without repair, reliability reaches $0.0720$ , $0.0521$ , and $0.0398$ at $t = 25$ . The fixed event-triggered policy generates two trigger events per configuration, achieving area-under-the-curve (AUC) gains between $0.5412 %$ and $0.5652 %$ . The Q-learning policy generates three trigger events and achieves larger AUC gains for the stricter configurations: $0.7154 %$ for $k = 15$ and $1.0066 %$ for $k = 25$ . These gains are validated by 30 Monte Carlo replications with non-overlapping 95% confidence intervals for $k = 15$ and $k = 25$ . Under Weibull aging with shape $β_{w} = 1.8$ , semi-Markovian stationary availability is lower than the exponential Markov baseline for all values of k.
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- 13 October 2026
- Published by MDPI AG in Algorithms
Open Access
Reliability and Availability of a Repairable k-Out-of-n System via Event-Triggered Maintenance Semi-Markovian Modelling Reinforcement Q-Learning, and Copula Repair
by Suresh Rasappan, Mani Sankar, Praveen Kumar Poonia
This paper develops a reliability and availability model for a repairable two-tier k-out-of-n computer network system. Four analytical components are combined: event-triggered repair intensification, Gumbel–Hougaard copula-based restoration, a semi-Markovian state-transition formulation, and a reinforcement Q-learning layer for adaptive threshold selection. Subsystem 1 consists of n identical web servers operating under a k-out-of-n: G policy. Subsystem 2 contains three identical database replicas under a one-out-of-three: G policy. The full system is available only when both subsystems and both load balancers are operational. State probabilities are derived via the supplementary variable technique and Laplace transforms. The semi-Markovian extension decouples embedded-chain transition probabilities from state-specific holding-time distributions. Stationary availability is expressed as the weighted ratio of mean up-state sojourn times to total mean sojourn times, accommodating non-exponential failure and repair time laws. The event-triggered policy fires repair intensification when the system availability $A (t)$ falls; specifically, when the degradation indicator $Ξ (t) = 1 - A (t)$ crosses a threshold subject to a minimum inter-event time. A Q-learning agent selects the threshold–gain action from a finite set, updating a Q-table by the Bellman rule. Numerical results from MATLAB 2026 show baseline availability converging to $0.8581$ , $0.8537$ , and $0.8496$ for $k = 5$ , $k = 15$ , and $k = 25$ . Without repair, reliability reaches $0.0720$ , $0.0521$ , and $0.0398$ at $t = 25$ . The fixed event-triggered policy generates two trigger events per configuration, achieving area-under-the-curve (AUC) gains between $0.5412 %$ and $0.5652 %$ . The Q-learning policy generates three trigger events and achieves larger AUC gains for the stricter configurations: $0.7154 %$ for $k = 15$ and $1.0066 %$ for $k = 25$ . These gains are validated by 30 Monte Carlo replications with non-overlapping 95% confidence intervals for $k = 15$ and $k = 25$ . Under Weibull aging with shape $β_{w} = 1.8$ , semi-Markovian stationary availability is lower than the exponential Markov baseline for all values of k.
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- 30 September 2026
- Published by Elsevier in Chaos, Solitons & Fractals
Secured dynamic event-triggered finite-time control for fuzzy interconnected PDE systems with deception attacks
by Ridhan Kumar Manikandan, Aravinth Narayanan, Oh-Min Kwon, Suresh Rasappan, Sankar Mani, Sakthivel Rathinasamy
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- 30 September 2026
- Published by Elsevier in Chaos, Solitons & Fractals
Secured dynamic event-triggered finite-time control for fuzzy interconnected PDE systems with deception attacks
by Ridhan Kumar Manikandan, Aravinth Narayanan, Oh-Min Kwon, Suresh Rasappan, Sankar Mani, Sakthivel Rathinasamy
Open Access
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Cited by 2
- 3 November 2025
- Published by MDPI AG in Mathematics
Buoyant Convective Thermal Transport in a Discretely Heated–Cooled Porous Parallelogrammic Configuration Saturated with Nanofluids: A Tiwari and Das Approach
by Vishwanatha Shivakumar, Vinay C. Veeranna, Mani Sankar, Sebastian A. Altmeyer, Abdulrahman Al Maqbali
The strategic positioning of heating and cooling segments within complex non-rectangular geometries has emerged as a critical engineering challenge across multiple industries in thermal management systems for electronic components. This analysis presents a numerical inspection of buoyancy-driven convective flow and thermal transport mechnisms of nanofluids in a parallelogrammic porous geometry. A single discrete heating–cooling segment has been placed along the slanting surfaces of the geometry. The mathematical model is formulated utilizing Darcy’s law, incorporating the Tiwari and Das approach to characterize the thermophysical properties of the nanofluid. The governing model equations corresponding to the physical process are solved numerically using finite-difference-based alternating direction implicit (ADI) and successive line over-relaxation (SLOR) techniques. Computational simulations are performed for various parametric conditions, including different nanoparticle volume fractions ( $ϕ = 0$ – $0.05$ ), Rayleigh numbers ( $R a = 10^{1}$ – $10^{3}$ ), and parallelogram geometry ( $α$ ) and sidewall ( $γ$ ) tilting angles ( $- 45^{°} \leq α \leq + 45^{°}$ and $- 45^{°} \leq γ \leq + 45^{°}$ ), while examining the effect of discrete thermal locations. The results reveal a significant decrement in thermal transfer rates with an increasing nanoparticle concentration, particularly at higher Rayleigh numbers. The skewness of the parallelogrammic boundaries is found to substantially influence flow patterns and thermal transport characteristics compared to conventional rectangular enclosures. Further, the discrete placement of heating and cooling sources creates unique thermal plumes that modify circulation patterns within the domain. The predictions suggest profound insights for optimizing thermal management systems by employing nanofluids in non-rectangular porous configurations, with potential applications in geothermal energy extraction, electronic cooling systems, and thermal energy storage devices.
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- 3 November 2025
- Published by MDPI AG in Mathematics
Open Access
Buoyant Convective Thermal Transport in a Discretely Heated–Cooled Porous Parallelogrammic Configuration Saturated with Nanofluids: A Tiwari and Das Approach
by Vishwanatha Shivakumar, Vinay C. Veeranna, Mani Sankar, Sebastian A. Altmeyer, Abdulrahman Al Maqbali
The strategic positioning of heating and cooling segments within complex non-rectangular geometries has emerged as a critical engineering challenge across multiple industries in thermal management systems for electronic components. This analysis presents a numerical inspection of buoyancy-driven convective flow and thermal transport mechnisms of nanofluids in a parallelogrammic porous geometry. A single discrete heating–cooling segment has been placed along the slanting surfaces of the geometry. The mathematical model is formulated utilizing Darcy’s law, incorporating the Tiwari and Das approach to characterize the thermophysical properties of the nanofluid. The governing model equations corresponding to the physical process are solved numerically using finite-difference-based alternating direction implicit (ADI) and successive line over-relaxation (SLOR) techniques. Computational simulations are performed for various parametric conditions, including different nanoparticle volume fractions ( $ϕ = 0$ – $0.05$ ), Rayleigh numbers ( $R a = 10^{1}$ – $10^{3}$ ), and parallelogram geometry ( $α$ ) and sidewall ( $γ$ ) tilting angles ( $- 45^{°} \leq α \leq + 45^{°}$ and $- 45^{°} \leq γ \leq + 45^{°}$ ), while examining the effect of discrete thermal locations. The results reveal a significant decrement in thermal transfer rates with an increasing nanoparticle concentration, particularly at higher Rayleigh numbers. The skewness of the parallelogrammic boundaries is found to substantially influence flow patterns and thermal transport characteristics compared to conventional rectangular enclosures. Further, the discrete placement of heating and cooling sources creates unique thermal plumes that modify circulation patterns within the domain. The predictions suggest profound insights for optimizing thermal management systems by employing nanofluids in non-rectangular porous configurations, with potential applications in geothermal energy extraction, electronic cooling systems, and thermal energy storage devices.
Cited by 2
Open Access
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Cited by 7
- 17 October 2025
- Published by Elsevier in Case Studies in Thermal Engineering
Integrating machine learning with numerical simulations of magneto-convective flow and irreversibility dynamics in a partially porous cavity with hot blocks
by N. Keerthi Reddy, H.A. Kumara Swamy, Yoseb Kang, M. Sankar, Younghae Do
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- 17 October 2025
- Published by Elsevier in Case Studies in Thermal Engineering
Open Access
Integrating machine learning with numerical simulations of magneto-convective flow and irreversibility dynamics in a partially porous cavity with hot blocks
by N. Keerthi Reddy, H.A. Kumara Swamy, Yoseb Kang, M. Sankar, Younghae Do
Cited by 7
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Cited by 2
- 23 September 2025
- Published by Elsevier in Applied Mathematics and Computation
Composite sliding mode adaptive tracking control for singularly perturbed semi-Markov jump non-linear systems with fault and disturbances
by N. Shobana, R. Sakthivel, O.M. Kwon, M. Sankar, M. Asha Safana
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- 23 September 2025
- Published by Elsevier in Applied Mathematics and Computation
Composite sliding mode adaptive tracking control for singularly perturbed semi-Markov jump non-linear systems with fault and disturbances
by N. Shobana, R. Sakthivel, O.M. Kwon, M. Sankar, M. Asha Safana
Cited by 2
Open Access
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Cited by 7
- 27 August 2025
- Published by MDPI AG in Energies
ANN-Assisted Numerical Study on Buoyant Heat Transfer of Hybrid Nanofluid in an Annular Chamber with Magnetic Field Inclination and Thermal Source–Sink Effects
by Mani Sankar, Maimouna S. Al Manthari, Praveen Kumar Poonia, Suresh Rasappan
A significant challenge in thermal device designs across diverse industries is optimizing heat dissipation rates to enhance system performance. Among different geometric configurations, a partially heated–cooled annular system containing magneto-nanofluids presents unique complexities due to the curvature ratio and strategic positioning of thermal sources–sinks, which substantially influences flow dynamics and thermal transfer mechanisms. The present investigation examines the buoyancy-driven heat transfer in an annular cavity containing a hybrid nanofluid under the influence of an inclined magnetic field and thermal source–sink pairs. Five different thermal source–sink arrangements and a wide range of magnetic field orientations are considered. The governing equations are solved using a finite difference approach that combines the Alternating Direction Implicit (ADI) method with relaxation techniques to capture the flow and thermal characteristics. An artificial neural network (ANN) is trained using simulation data to estimate the average Nusselt number for a range of physical conditions. Among different source–sink arrangements, the Case-1 arrangement is found to produce a stronger flow circulation and thermal dissipation rates. Also, an oblique magnetic field offers greater control compared with vertical or horizontal magnetic orientations. The network, structured with multiple hidden layers and optimized using a conjugate gradient algorithm, produces predictions that closely match the numerical results. Our analysis reveals that Case-1 demonstrates superior thermal performance, with approximately 19% greater heat dissipation compared with other chosen heating configurations. In addition, the Case-1 heating configuration combined with blade-shaped nanoparticles yields more than 27% superior thermal performance among the considered configurations. The outcomes suggest that at stronger magnetic fields $(H a = 50)$ , the orientation angle becomes critically important, with perpendicular magnetic fields $(γ = 90^{\circ})$ significantly outperforming other orientations.
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- 27 August 2025
- Published by MDPI AG in Energies
Open Access
ANN-Assisted Numerical Study on Buoyant Heat Transfer of Hybrid Nanofluid in an Annular Chamber with Magnetic Field Inclination and Thermal Source–Sink Effects
by Mani Sankar, Maimouna S. Al Manthari, Praveen Kumar Poonia, Suresh Rasappan
A significant challenge in thermal device designs across diverse industries is optimizing heat dissipation rates to enhance system performance. Among different geometric configurations, a partially heated–cooled annular system containing magneto-nanofluids presents unique complexities due to the curvature ratio and strategic positioning of thermal sources–sinks, which substantially influences flow dynamics and thermal transfer mechanisms. The present investigation examines the buoyancy-driven heat transfer in an annular cavity containing a hybrid nanofluid under the influence of an inclined magnetic field and thermal source–sink pairs. Five different thermal source–sink arrangements and a wide range of magnetic field orientations are considered. The governing equations are solved using a finite difference approach that combines the Alternating Direction Implicit (ADI) method with relaxation techniques to capture the flow and thermal characteristics. An artificial neural network (ANN) is trained using simulation data to estimate the average Nusselt number for a range of physical conditions. Among different source–sink arrangements, the Case-1 arrangement is found to produce a stronger flow circulation and thermal dissipation rates. Also, an oblique magnetic field offers greater control compared with vertical or horizontal magnetic orientations. The network, structured with multiple hidden layers and optimized using a conjugate gradient algorithm, produces predictions that closely match the numerical results. Our analysis reveals that Case-1 demonstrates superior thermal performance, with approximately 19% greater heat dissipation compared with other chosen heating configurations. In addition, the Case-1 heating configuration combined with blade-shaped nanoparticles yields more than 27% superior thermal performance among the considered configurations. The outcomes suggest that at stronger magnetic fields $(H a = 50)$ , the orientation angle becomes critically important, with perpendicular magnetic fields $(γ = 90^{\circ})$ significantly outperforming other orientations.
Cited by 7
Open Access
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Cited by 3
- 26 June 2025
- Published by Elsevier in Results in Engineering
Double-diffusive magnetoconvection in a tilted porous parallelogrammic domain with discrete heated-cooled segments: Leveraging machine learning and CFD approach
by P. Ravindra, M. Sankar, Suresh Rasappan, Wardah Abdullah Al Majrafi, Pugalarasu Rajan, S. Sanal Kumar
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- 26 June 2025
- Published by Elsevier in Results in Engineering
Open Access
Double-diffusive magnetoconvection in a tilted porous parallelogrammic domain with discrete heated-cooled segments: Leveraging machine learning and CFD approach
by P. Ravindra, M. Sankar, Suresh Rasappan, Wardah Abdullah Al Majrafi, Pugalarasu Rajan, S. Sanal Kumar
Cited by 3
Open Access
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Cited by 3
- 19 June 2025
- Published by MDPI AG in Mathematics
Buoyant Flow and Thermal Analysis in a Nanofluid-Filled Cylindrical Porous Annulus with a Circular Baffle: A Computational and Machine Learning-Based Approach
by Pushpa Gowda, Sankar Mani, Ahmad Salah, Sebastian A. Altmeyer
Control of buoyancy-assisted convective flow and the associated thermal behavior of nanofluids in finite-sized conduits has become a great challenge for the design of many types of thermal equipment, particularly for heat exchangers. This investigation discusses the numerical simulation of the buoyancy-driven convection (BDC) of a nanofluid (NF) in a differently heated cylindrical annular domain with an interior cylinder attached with a thin baffle. The annular region is filled with non-Darcy porous material saturated-nanofluid and both NF and the porous structure are in local thermal equilibrium (LTE). Higher thermal conditions are imposed along the interior cylinder as well as the baffle, while the exterior cylinder is maintained with lower or cold thermal conditions. The Darcy–Brinkman–Forchheimer model, which accounts for inertial, viscous, and non-linear drag forces was adopted to model the momentum equations. An implicit finite difference methodology by considering time-splitting methods for transient equations and relaxation-based techniques is chosen for the steady-state model equations. The impacts of various pertinent parameters, such as the Rayleigh and Darcy numbers, baffle dimensions, like length and position, on flow, thermal distributions, as well as thermal dissipation rates are systematically estimated through accurate numerical predictions. It was found that the baffle dimensions are very crucial parameters to effectively control the flow and associated thermal dissipation rates in the domain. In addition, machine learning techniques were adopted for the chosen analysis and an appropriate model developed to predict the outcome accurately among the different models considered.
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- 19 June 2025
- Published by MDPI AG in Mathematics
Open Access
Buoyant Flow and Thermal Analysis in a Nanofluid-Filled Cylindrical Porous Annulus with a Circular Baffle: A Computational and Machine Learning-Based Approach
by Pushpa Gowda, Sankar Mani, Ahmad Salah, Sebastian A. Altmeyer
Control of buoyancy-assisted convective flow and the associated thermal behavior of nanofluids in finite-sized conduits has become a great challenge for the design of many types of thermal equipment, particularly for heat exchangers. This investigation discusses the numerical simulation of the buoyancy-driven convection (BDC) of a nanofluid (NF) in a differently heated cylindrical annular domain with an interior cylinder attached with a thin baffle. The annular region is filled with non-Darcy porous material saturated-nanofluid and both NF and the porous structure are in local thermal equilibrium (LTE). Higher thermal conditions are imposed along the interior cylinder as well as the baffle, while the exterior cylinder is maintained with lower or cold thermal conditions. The Darcy–Brinkman–Forchheimer model, which accounts for inertial, viscous, and non-linear drag forces was adopted to model the momentum equations. An implicit finite difference methodology by considering time-splitting methods for transient equations and relaxation-based techniques is chosen for the steady-state model equations. The impacts of various pertinent parameters, such as the Rayleigh and Darcy numbers, baffle dimensions, like length and position, on flow, thermal distributions, as well as thermal dissipation rates are systematically estimated through accurate numerical predictions. It was found that the baffle dimensions are very crucial parameters to effectively control the flow and associated thermal dissipation rates in the domain. In addition, machine learning techniques were adopted for the chosen analysis and an appropriate model developed to predict the outcome accurately among the different models considered.
Cited by 3
Open Access
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- 30 November 2024
- Published by Akademia Baru Publishing in Journal of Advanced Research in Fluid Mechanics and Thermal Sciences
Effect of Lorentz Force and Magnetic Viscosity on Shliomis Model Ferro Flow due to Rotating Disk
by Meghashree Gollahalli Rajagopal, Asha Chikkasomanahalli Shivegowda, Sumana Krishna Prasad, Achala Laxmivenkatesh Nargund, Mani Sankar
The present work involves the study of ferrofluid flow over a rotating disk analysed through Shliomis model in the presence of alternating magnetic field applied in the radial direction. Shliomos model is the appropriate model to analyse ferrofluid flows as it provides prominence to the particle’s movement in the fluid. Here the flow alters due to the viscosity dependent on applied magnetic field in the presence of Lorentz force. The governing equations leading to nonlinear partial differential equations are reduced to nonlinear ordinary differential equations using similarity transformation and solved numerically using the shooting method with the error tolerance of 10-6. The results obtained are represented in the form of graphs and the effects of parameters are analysed on the velocity profiles and pressure. The magnetic parameter declines whereas the magnetic field dependent viscosity enhances the velocity of the flow by reducing the pressure, which finds its application in many hardware devices. Also, the comparative study provides a quantitative agreement for the limiting case of the present work.
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- 30 November 2024
- Published by Akademia Baru Publishing in Journal of Advanced Research in Fluid Mechanics and Thermal Sciences
Open Access
Effect of Lorentz Force and Magnetic Viscosity on Shliomis Model Ferro Flow due to Rotating Disk
by Meghashree Gollahalli Rajagopal, Asha Chikkasomanahalli Shivegowda, Sumana Krishna Prasad, Achala Laxmivenkatesh Nargund, Mani Sankar
The present work involves the study of ferrofluid flow over a rotating disk analysed through Shliomis model in the presence of alternating magnetic field applied in the radial direction. Shliomos model is the appropriate model to analyse ferrofluid flows as it provides prominence to the particle’s movement in the fluid. Here the flow alters due to the viscosity dependent on applied magnetic field in the presence of Lorentz force. The governing equations leading to nonlinear partial differential equations are reduced to nonlinear ordinary differential equations using similarity transformation and solved numerically using the shooting method with the error tolerance of 10-6. The results obtained are represented in the form of graphs and the effects of parameters are analysed on the velocity profiles and pressure. The magnetic parameter declines whereas the magnetic field dependent viscosity enhances the velocity of the flow by reducing the pressure, which finds its application in many hardware devices. Also, the comparative study provides a quantitative agreement for the limiting case of the present work.
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Cited by 37
- 1 August 2024
- Published by AIP Publishing in Physics of Fluids
Computational analysis of magnetohydrodynamic ternary-hybrid nanofluid flow and heat transfer inside a porous cavity with shape effects
by Hyunju Kim, Younghae Do, Sivaraj Ramachandran, M. Sankar, K. Thirumalaisamy
The current study aims to analyze the magnetohydrodynamic natural convective fluid flow and heat transmission features of the ternary-hybrid nanofluid filled the partially heated porous square cavity under the impacts of heat absorption/generation and thermal radiation. The governing equations are solved using the Marker and Cell method. In the present study, three different types of nanoparticles, such as molybdenum disulfide (MoS2), single-walled carbon nanotube (SWCNT), and silver (Ag), are suspended in an inorganic (water) or non-polar organic (kerosene) solvent. Nine different shapes of nanoparticles are utilized in this study. The outcomes show that for the fixed pertinent parameter values of the existence and nonexistence of heat generation/absorption, the MoS2+SWCNT+Ag/water ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average thermal transmission rate is increased by 40.8523%, 36.329%, and 38.7025%, respectively, than sphere-shaped nanoparticles. In addition, utilizing the MoS2+SWCNT+Ag/kerosene ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average heat transmission rate is augmented by 38.0322%, 33.0464%, and 35.5868%, respectively, than sphere-shaped nanoparticles. The current study reveals that the fluid flow and heat transfer efficiency are significantly increased by improving the nanoparticle volume fraction and shape factors depending upon the existence of heat absorption/generation. The high average heat transfer efficiency is observed when lamina-shaped nanoparticles are dispersed into the water compared to kerosene in the presence of a heat source. This study can enhance heat transmission efficiency in various industrial and engineering fields, such as heat exchangers, solar collectors, and fuel cells.
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- 1 August 2024
- Published by AIP Publishing in Physics of Fluids
Computational analysis of magnetohydrodynamic ternary-hybrid nanofluid flow and heat transfer inside a porous cavity with shape effects
by Hyunju Kim, Younghae Do, Sivaraj Ramachandran, M. Sankar, K. Thirumalaisamy
The current study aims to analyze the magnetohydrodynamic natural convective fluid flow and heat transmission features of the ternary-hybrid nanofluid filled the partially heated porous square cavity under the impacts of heat absorption/generation and thermal radiation. The governing equations are solved using the Marker and Cell method. In the present study, three different types of nanoparticles, such as molybdenum disulfide (MoS2), single-walled carbon nanotube (SWCNT), and silver (Ag), are suspended in an inorganic (water) or non-polar organic (kerosene) solvent. Nine different shapes of nanoparticles are utilized in this study. The outcomes show that for the fixed pertinent parameter values of the existence and nonexistence of heat generation/absorption, the MoS2+SWCNT+Ag/water ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average thermal transmission rate is increased by 40.8523%, 36.329%, and 38.7025%, respectively, than sphere-shaped nanoparticles. In addition, utilizing the MoS2+SWCNT+Ag/kerosene ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average heat transmission rate is augmented by 38.0322%, 33.0464%, and 35.5868%, respectively, than sphere-shaped nanoparticles. The current study reveals that the fluid flow and heat transfer efficiency are significantly increased by improving the nanoparticle volume fraction and shape factors depending upon the existence of heat absorption/generation. The high average heat transfer efficiency is observed when lamina-shaped nanoparticles are dispersed into the water compared to kerosene in the presence of a heat source. This study can enhance heat transmission efficiency in various industrial and engineering fields, such as heat exchangers, solar collectors, and fuel cells.
Cited by 37

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