Description:FIELD OF THE INVENTION
The present invention relates to the field of thermodynamic and fluid mechanics, specifically to the analysis of entropy generation in non-Newtonian fluid flows. More particularly, the invention concerns a computational framework and method for quantifying thermodynamic irreversibility in complex fluid systems and providing optimization strategies for improving energy efficiency in industrial, biomedical, and engineering applications.
BACKGROUND OF THE INVENTION
In many industrial and engineering applications such as polymer processing, biofluid dynamics, food manufacturing, and enhanced oil recovery, non-Newtonian fluids are frequently encountered. Unlike Newtonian fluids, their viscosity varies with the rate of shear strain, which adds complexity to their flow behavior. Simultaneously, entropy generation, a key aspect of thermodynamic irreversibility, becomes critical in evaluating the energy efficiency and sustainability of these flow systems.
However, existing entropy generation analyses are primarily focused on Newtonian fluids and simplified geometries, offering limited insights into complex non-linear behaviors associated with non-Newtonian rheology. Additionally, the effects of thermal gradients, viscous dissipation, and boundary conditions on entropy generation in non-Newtonian flows remain inadequately explored.
This research seeks to address this gap by conducting a comprehensive thermodynamic entropy generation analysis of non-Newtonian fluid flows under various boundary conditions and flow configurations. The goal is to quantify the sources of irreversibility, analyze the influence of different flow models (e.g., Power-law, Bingham, Carreau), and propose optimization strategies to minimize entropy production for better thermal-fluid system performance.
US8367004B2: Apparatus, systems and methods are provided that utilize microreactor technology to achieve desired mixing and interaction at a micro and/or molecular level between and among feed stream constituents. Feed streams are fed to an intensifier pump at individually controlled rates, e.g., based on operation of individually controlled feed pumps. The time during which first and second feed streams are combined/mixed prior to introduction to the microreactor is generally minimized, thereby avoiding potential reactions and other constituent interactions prior to micro- and/or nano-scale interactions within the microreactor. Various microreactor designs/geometries may be employed, e.g., “Z” type single or multi-slot geometries and “Y” type single or multi-slot geometries. Various applications benefit from the disclosure, including emulsion, crystallization, encapsulation and reaction processes.
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Non-Newtonian fluids, widely encountered in polymer processing, biofluid dynamics, food industries, and enhanced oil recovery, exhibit viscosity dependent on shear rate, making their flow behavior highly complex. Conventional computational tools are primarily developed for Newtonian fluids and provide limited insight into entropy generation, which is a critical parameter in assessing thermodynamic efficiency. Current methods lack dedicated modules for entropy analysis, rely on manual post-processing, and fail to incorporate optimization for minimizing irreversibility. The present invention overcomes these shortcomings by offering an integrated computational system and method for analyzing entropy generation in non-Newtonian fluid flows with varying rheological models and boundary conditions, coupled with optimization strategies.
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 provides a computational system and method that integrates thermodynamic entropy generation analysis with non-Newtonian fluid flow simulations. It incorporates rheological models such as Power-law, Bingham plastic, Casson, and Carreau-Yasuda to evaluate entropy production arising from viscous dissipation, pressure gradients, and heat transfer mechanisms.
The system employs computational fluid dynamics (CFD)-based modules to simulate two- and three-dimensional flow geometries under different thermal boundary conditions, including isothermal, adiabatic, and convective heating. Entropy equations are combined with energy and momentum balances to identify regions of high irreversibility within the flow domain.
An optimization module, employing algorithms such as Genetic Algorithm or Response Surface Methodology, is integrated to minimize entropy generation. This provides improved energy efficiency and enhances system performance. The invention further enables visualization and mapping of entropy distribution, supporting decision-making in design and process improvements.
This integrated framework ensures accurate analysis of complex fluid behaviors and delivers optimized solutions for industries requiring sustainable and efficient thermal-fluid systems.
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.
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 proposed work involves creating a framework for studying entropy generation using non-Newtonian fluids. The principle is to devise a proper approach that allows us to measure entropy production due to viscous dissipation, heat transfer and pressure gradients in non-Newtonian fluids that follow the Power-law, Bingham plastic, Casson and Carreau-Yasuda models.
The new model involves a general version of entropy generation designed for non-Newtonian flows which is connected to CFD methods. Functions in the system help simulate 2D and 3D flows in various systems (like parallel plates or pipes) subjected to different boundary heat arrangements (such as isothermal, convective or adiabatic). By combining energy and momentum balances with entropy equations, it can help find zones in a system that are not very efficient.
Furthermore, the design also features an optimization module that uses numerical strategies (Genetic Algorithm or Response Surface Methodology) to decrease the amount of entropy generated in a practical system. The tool can be used for biofluids, smart fluids and solutions based on polymers, so it applies to biomedical engineering, food processing and energy systems.
Novel & Inventive Features
• Analyzing systems with various non-linear rheological behaviors by using entropy generation methods.
• Combining computer simulations with thermodynamics helps improve optimization.
• Supplying map-based and figure-based measures to guide improvements in the design.
Therefore, this invention is envisioned to assist engineers, researchers and system designers in designing more energy efficient systems processing non-Newtonian flows, by understanding and applying the distributions and means of generating entropy.
The invention discloses a system for analyzing entropy generation in non-Newtonian fluid flows. The system comprises a computational framework consisting of simulation modules, entropy evaluation algorithms, and optimization tools.
The simulation module employs CFD-based numerical solvers that incorporate governing equations of mass, momentum, and energy balance, along with constitutive relations of different non-Newtonian models. The supported rheological models include Power-law fluids, Bingham plastics, Casson fluids, and Carreau-Yasuda formulations.
The entropy evaluation algorithm integrates thermodynamic principles by quantifying irreversibility due to viscous dissipation, pressure drop, and heat transfer. Entropy generation rate is calculated at each computational cell within the domain, thereby creating a spatial distribution map of irreversibility across the flow field.
The system supports two-dimensional and three-dimensional geometrical configurations, such as parallel plate channels, circular pipes, and non-standard conduits. These geometries can be subjected to boundary conditions including uniform temperature walls, convective heat flux boundaries, or insulated walls.
The optimization module operates in conjunction with the simulation and entropy algorithms. Numerical optimization techniques such as Genetic Algorithms or Response Surface Methodology are applied to minimize the global entropy generation within the system. By adjusting flow parameters, boundary conditions, or fluid properties, the optimizer reduces thermodynamic losses.
The invention also provides a visualization interface for entropy distribution. This enables engineers and designers to identify high-loss regions, interpret flow-thermal interactions, and implement design modifications.
The method of working involves defining the problem domain, selecting the non-Newtonian rheological model, specifying flow and thermal boundary conditions, executing CFD simulations, calculating entropy generation, and applying optimization strategies.
The invention further extends applicability to biofluids such as blood, polymeric solutions, food-grade fluids, and industrial suspensions, making it relevant for healthcare, manufacturing, and energy industries.
An example embodiment includes analysis of blood flow in arterial models under pulsatile conditions to predict entropy generation associated with wall shear and heat transfer. Another example involves optimization of polymer extrusion processes to reduce thermal irreversibility.
The novelty lies in the coupling of thermodynamic entropy analysis with advanced CFD modeling for non-Newtonian fluids, providing direct optimization tools within a unified computational framework.
This description should not be considered limiting, as modifications and extensions within the scope of claims are possible.
Best Method of Working
The best method of working involves implementing the system in a CFD environment with integrated thermodynamic modules. The user selects a rheological model based on the fluid type, defines geometry and thermal conditions, and executes simulations. Entropy generation is computed at each timestep and mapped across the computational domain. The optimization algorithm is then activated to iteratively minimize entropy production, yielding an energy-efficient design configuration. The process is particularly effective when applied to heat exchangers using non-Newtonian coolants, polymer processing channels, and biomedical flow systems.
, Claims:1. A system for thermodynamic entropy generation analysis of non-Newtonian fluid flows, comprising:
• a computational fluid dynamics simulation module configured to solve governing equations of mass, momentum, and energy;
• a rheological model library including Power-law, Bingham plastic, Casson, and Carreau-Yasuda formulations;
• an entropy evaluation module configured to calculate irreversibility arising from viscous dissipation, pressure gradients, and heat transfer;
• a geometry and boundary condition module supporting two- and three-dimensional domains under isothermal, convective, and adiabatic conditions;
• an optimization module employing numerical algorithms to minimize entropy generation; and
• a visualization interface for mapping entropy distribution in the fluid domain.
2. The system as claimed in claim 1, wherein the optimization module employs Genetic Algorithm or Response Surface Methodology for reducing entropy generation.
3. The system as claimed in claim 1, wherein the entropy evaluation module generates spatial and temporal maps of irreversibility for flow visualization.
4. The system as claimed in claim 1, wherein the rheological models are selectable based on polymeric, biofluid, or industrial suspension applications.
5. The system as claimed in claim 1, wherein the geometry includes parallel plate channels, pipes, and customized conduits.
6. A method for analyzing entropy generation in non-Newtonian fluid flows, comprising the steps of:
• defining a computational domain and boundary conditions;
• selecting a non-Newtonian rheological model from a library including Power-law, Bingham plastic, Casson, and Carreau-Yasuda;
• performing computational fluid dynamics simulations for mass, momentum, and energy balance;
• calculating entropy generation from viscous dissipation, pressure drop, and heat transfer;
• mapping entropy distribution across the domain; and
• optimizing parameters using numerical algorithms to minimize entropy generation.
7. The method as claimed in claim 6, wherein the optimization employs Genetic Algorithm or Response Surface Methodology.
8. The method as claimed in claim 6, wherein entropy distribution is displayed through a visualization interface for design improvement.
9. The method as claimed in claim 6, wherein the analysis is applied to biofluid dynamics, polymer processing, and energy system design.
10. The method as claimed in claim 6, wherein the computational framework is implemented for two-dimensional and three-dimensional flow domains with variable thermal boundary conditions.