Description:FIELD OF THE INVENTION
The invention relates to thermal engineering and fluid mechanics. More particularly, it concerns a system and method for enhancing heat transfer in industrial and energy applications using hybrid nanofluids formed from multiple nanoparticles suspended in base fluids, modeled and optimized through computational and experimental techniques.
BACKGROUND OF THE INVENTION
The fields of microelectronics cooling, automotive heat exchangers, nuclear reactors and solar collectors are experiencing strong growth and require efficient thermal solutions. Based on their thermal conductivity, water, ethylene glycol and oil are not well-suited for the demanding thermal needs of emerging technologies. For this reason, using nanofluid heat transfer fluids is being explored because they have better heat-carrying properties.
Recent research found that mixtures of different nanoparticles in a base fluid are able to perform better than classic nanofluids by combining their strengths to enhance thermal conductivity and heat transfer. How hybrid nanofluids distribute heat is still not well understood in places with complex flows and differing conditions.
It is also difficult to model properly how hybrid nanofluids move and transfer heat, because of the impact of nanoparticle interactions, the volume fraction, the flow geometry and the influence of thermophysical properties. A lack of complete theoretical, computational and experimental assessments is limiting the use of hybrid nanofluids in many industrial thermal applications.
Consequently, this study wishes to analyze how hybrid nanofluid flow performs under different geometries and boundary circumstances, using advanced tools and methods of mathematical modeling and simulation. The aim is to make models and recommendations that allow hybrid nanofluids to be used efficiently in heat transfer systems.
US20200376565A1: The present disclosure proposes an electrocaloric assisted internal cooling, texture turning tool and a nanofluid minimal quantity lubrication (NMQL) intelligent working system. The electrocaloric assisted internal cooling texture turning tool comprises an internal cooling turning tool handle, a direction-adjustable nozzle and an internal cooling turning tool blade; the internal cooling turning tool blade is arranged at one end of the internal cooling turning tool handle serving as a bearing device; an internal cooling turning tool pad is arranged between the internal cooling turning tool blade and a structure of the internal cooling turning tool handle bearing the blade; an internal cooling turning tool blade pressing device is further arranged on the internal cooling turning tool handle; the internal cooling turning tool blade is tightly pressed on the internal cooling turning tool handle by the internal cooling turning tool blade pressing device.
US10175669B2: Systems and methods for measuring and controlling fluid flow comprises an orifice plate defining a variable opening, wherein the orifice plate includes an outer assembly comprising a central opening and an inner assembly extending through the central opening. Another embodiment comprises a plurality of blades disposed parallel to each other, wherein the blades are pivotable along its longitudinal axis and include at least one low-flow blade or partial blade and a plurality of high-flow blades The flow device regulates high and very low volumes of fluid with precision, inexpensively, with superior acoustics, reduced energy, a simpler design, and prevents building infiltration. The high turndown device permits use at lower velocities, thereby reducing noise generation and eliminating need for sound-attenuating liners. The high rangeability device combines several part numbers into fewer parts, thereby streamlining product portfolios. Cost benefits associated with the flow device allow equipment to be scaled back 100:1 rather than legacy 4:1, providing energy savings, fewer product variations, simple and more robust applications. The device meets new and old building fresh air, comfort and energy codes. The flow device can be engineered, selected, and sized without sophisticated software programs.
Conventional coolants such as water, ethylene glycol, and oil have low thermal conductivity and cannot meet the demands of advanced microelectronics, automotive systems, nuclear reactors, and renewable energy devices. Single nanoparticle-based nanofluids improve conductivity but are limited by instability, non-uniform dispersion, and insufficient adaptability across varied flow conditions. Existing models fail to capture the complexity of hybrid nanofluid behavior, including particle interactions, concentration effects, and thermophysical variations. The present invention solves these issues by providing a hybrid nanofluid system supported by mathematical modeling, numerical simulation, and optimization frameworks that maximize heat transfer while maintaining stability and minimizing additional pumping power.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
The invention introduces a hybrid nanofluid system formed by blending two or more types of nanoparticles in a base fluid such as water or ethylene glycol. The combination improves thermal conductivity, enhances convective heat transfer, and stabilizes dispersion under varying flow geometries and boundary conditions.
The system incorporates mathematical models based on governing equations of continuity, momentum, and energy, along with particle interaction models considering Brownian motion, thermophoresis, and volume fraction effects. Numerical simulations are performed using finite volume or finite element methods for two- and three-dimensional flow geometries such as channels, cavities, and heat sinks.
An optimization framework evaluates the impact of nanoparticle type, concentration, Reynolds number, Prandtl number, and channel aspect ratio on heat transfer performance. The invention further provides design guidelines for integrating hybrid nanofluids into heat exchangers, microelectronics cooling, and renewable energy systems.
Through this integrated approach, the invention significantly increases the Nusselt number, reduces thermal resistance, and provides compact, high-efficiency cooling solutions adaptable to diverse industrial applications.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The new invention uses hybrid nanofluids to improve the efficiency of transferring heat in fluid flow systems. This invention focuses on building a model and selecting the best flow for hybrid nanofluids in channels, cavities and heat sinks, with the aim of using them in microelectronics cooling, automotive refrigeration and renewable energy systems.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The new invention uses hybrid nanofluids to improve the efficiency of transferring heat in fluid flow systems. This invention focuses on building a model and selecting the best flow for hybrid nanofluids in channels, cavities and heat sinks, with the aim of using them in microelectronics cooling, automotive refrigeration and renewable energy systems.
The hybrid nanofluid used in the invention is formed by blending different types of nanoparticles (e.g., Al₂O₃, Cu, TiO₂, CuO, SiO₂, AlN) and a standard base fluid (water or ethylene glycol). Thermo-physical interactions between various nanoparticles make it possible to achieve enhanced conductivity, a better temperature and increased convective heat transfer.
Key components of the proposed invention include:
1. Mathematical Modeling and Simulation:
A multi-physics model is developed which accounts for the governing equations of continuity, momentum (Navier-Stokes) and energy with interaction models of the nanoparticle. Volume fraction, Brownian motion, thermophoresis and temperature dependent viscosity and conductivity are considered in the model.
2. Numerical Implementation:
Implementation of Finite Volume Method (FVM) or Finite Element Method (FEM) based hybrid CFD simulation using ANSYS Fluent, COMSOL Multiphysics or MATLAB to investigate hybrid nanofluid flow in 2D and 3D geometries. Model validation, parametric studies and grid independence will be carried out, to ensure the accuracy and robustness of the achieved results.
3. Optimization of Parameters:
Investigation of the effects of nanoparticle concentration, Reynolds number, Prandtl number, and aspect ratio of the flow channel on thermal performance. The invention includes an optimization framework (e.g., using Taguchi method, RSM, or AI-based algorithms) to identify the optimal combination of nanoparticle types and operational parameters.
4. Experimental Prototype (optional/future scope):
A small scale experimental setup is designed for validation of numerical findings using thermal imaging and flow visualization techniques. Real world benefits of this methodology will also be shown in heat exchanger design with prototype.
5. Innovative Outcomes:
o Enhanced Nusselt number and reduced thermal resistance.
o Better stability and homogeneity of the hybrid nanofluid.
o Compact, high-efficiency heat exchanger designs.
o Guidelines for industrial integration of hybrid nanofluids.
The invention provides the bridge between theoretical understanding and practical implementation of hybrid nanofluid flow systems with a scalable and robust solution to next generation thermal systems. This constitutes a considerable aspect in energy efficiency, system miniaturization and enhanced thermal management in high performance technologies.
A novel approach to significantly enhance the heat transfer of nanofluids under dynamic operating conditions by incorporating optimized hybrid nanofluid composition, real time thermal performance analysis and adaptive flow control.
The invention provides a system for improving thermal management through the use of hybrid nanofluids. Hybrid nanofluids are created by dispersing two or more nanoparticles such as alumina, copper, silica, titanium oxide, copper oxide, or aluminum nitride in a base fluid. The resulting mixture combines the advantages of each nanoparticle, leading to enhanced thermal conductivity and convective heat transfer properties compared to conventional nanofluids or base fluids.
The system includes a mathematical modeling framework. Governing equations of fluid flow and heat transfer are modified to account for nanoparticle interactions, concentration, and temperature-dependent viscosity and conductivity. These models describe the transport phenomena within hybrid nanofluids under different operating conditions.
A numerical simulation framework is employed to analyze hybrid nanofluid flows in geometries such as parallel channels, cavities, and heat sinks. Finite volume or finite element methods are used to solve the equations with boundary conditions representing practical applications.
The invention accounts for Brownian motion and thermophoresis effects, which influence nanoparticle dispersion and stability. By including these mechanisms, the model ensures accurate prediction of hybrid nanofluid behavior in complex flows.
Optimization techniques are integrated into the system to determine the best combinations of nanoparticle type, volume fraction, and flow parameters. Methods such as response surface methodology, design of experiments, or AI-based algorithms can be used to maximize heat transfer efficiency while minimizing pressure drop.
The system demonstrates that hybrid nanofluids achieve higher Nusselt numbers and reduced thermal resistance compared to traditional fluids. This results in superior performance in cooling applications with minimal increases in pumping power.
In one embodiment, hybrid nanofluids are applied to microelectronics cooling, where high heat fluxes demand efficient removal. The system shows improved temperature control and extended device lifetime.
In automotive systems, hybrid nanofluids can be used in radiators and intercoolers to increase efficiency and reduce size, weight, and fuel consumption.
In nuclear reactors, the improved thermal conductivity of hybrid nanofluids enhances safety margins by improving heat removal from critical components.
In solar thermal collectors, hybrid nanofluids improve absorption and heat transport, increasing overall efficiency of renewable energy systems.
Experimental validation of numerical findings may be conducted using small-scale prototypes. Thermal imaging and flow visualization techniques demonstrate practical improvements and stability of hybrid nanofluid applications.
The invention provides industrial guidelines for integrating hybrid nanofluids into heat exchangers and cooling systems, offering scalable solutions for emerging high-performance technologies.
Best Method of Working
The best method of working involves preparing hybrid nanofluids by dispersing selected nanoparticles into a base fluid using controlled mixing techniques to achieve stability. The prepared hybrid nanofluid is introduced into flow systems such as channels, cavities, or heat sinks. Numerical models are applied to predict performance under different geometries and operating conditions, while optimization frameworks are used to select nanoparticle types and concentrations for maximum efficiency. The system is validated through prototype experiments, ensuring reproducibility and stability. This method ensures adaptability for diverse applications including microelectronics cooling, automotive heat exchangers, nuclear reactors, and solar energy systems.
, Claims:1. A system for enhancing heat transfer using hybrid nanofluid flow, comprising:
o a hybrid nanofluid prepared by dispersing two or more types of nanoparticles in a base fluid;
o a mathematical modeling module configured to represent continuity, momentum, and energy equations with nanoparticle interaction effects;
o a numerical simulation module configured to analyze hybrid nanofluid flows in channels, cavities, and heat sinks;
o an optimization module configured to determine optimal nanoparticle concentration, type, Reynolds number, Prandtl number, and flow geometry;
o an experimental validation module configured to test thermal imaging and flow visualization prototypes;
o an application interface configured to integrate the hybrid nanofluid into microelectronics cooling, automotive, nuclear, and renewable energy systems;
wherein all modules are interconnected to improve thermal conductivity, convective heat transfer, and system efficiency.
2. The system as claimed in claim 1, wherein the hybrid nanofluid includes nanoparticles selected from alumina, copper, titanium oxide, silica, copper oxide, or aluminum nitride.
3. The system as claimed in claim 1, wherein the mathematical modeling module accounts for Brownian motion, thermophoresis, and temperature-dependent viscosity and conductivity.
4. The system as claimed in claim 1, wherein the numerical simulation module uses finite volume or finite element methods for two- and three-dimensional analysis.
5. The system as claimed in claim 1, wherein the optimization module applies statistical or AI-based techniques to maximize heat transfer efficiency.
6. A method for enhancing heat transfer using hybrid nanofluids, comprising the steps of:
o preparing a hybrid nanofluid by dispersing two or more types of nanoparticles in a base fluid;
o modeling hybrid nanofluid flow using governing equations of continuity, momentum, and energy with nanoparticle interaction effects;
o simulating hybrid nanofluid flow in different geometries using numerical methods;
o optimizing nanoparticle concentration, flow parameters, and geometry for improved thermal conductivity and convective heat transfer;
o validating numerical results with experimental prototypes using thermal imaging and flow visualization;
o integrating the hybrid nanofluid into cooling systems for microelectronics, automotive, nuclear, and renewable energy applications.
7. The method as claimed in claim 6, wherein nanoparticle combinations are selected to maximize thermal conductivity while maintaining stability.
8. The method as claimed in claim 6, wherein Reynolds number and Prandtl number are optimized for enhanced convective performance.
9. The method as claimed in claim 6, wherein experimental validation demonstrates increased Nusselt number and reduced thermal resistance.
10. The method as claimed in claim 6, wherein integration guidelines are provided for scalable industrial adoption of hybrid nanofluids.