Fluid Thermal Conductivity Research Articles

Modelling the effective thermal conductivity and porosity of an open-cell material using an image-based technique coupled with machine learning

Effective thermal conductivity is considered one of the most important parameters in the characterization of insulating materials. The effective thermal conductivity of open-cell porous materials is influenced by both their microstructure and the types of solid and fluid phases present. Currently, many analytical models are available for predicting the final performance based on material porosity, as well as the thermal conductivity of the solid and fluid phases. However, these procedures have two main drawbacks: difficulty in selecting the correct prediction model and challenges in accurately determining porosity. Moreover, when attempting to measure effective thermal conductivity, strict procedural conditions and defined sample geometries are required, necessitating multiple samples due to variations in porosity from specimen to specimen. The procedure proposed here aims to address these challenges. Utilizing microtomography coupled with 3D virtualization and finite element method simulation, this procedure provides validated results which are then used as a dataset to train a machine-learning model capable of predicting thermal conductivity across a comprehensive range of porosities, solid thermal conductivities and fluid thermal conductivities. Comparative analysis has demonstrated that this procedure is significantly more accurate than conventional analytical models or measurement procedures and it has the potential to be applied to any material.

Effects of viscous dissipation, temperature dependent thermal conductivity, and local thermal non‐equilibrium on the heat transfer in a porous channel to Casson fluid

AbstractThe current paper deals with viscous dissipation effects in a permeable (or porous) channel filled with non‐Newtonian Casson fluid by considering the local thermal non‐equilibrium (LTNE) model. The dependency of the effective thermal conductivities of the solid and fluid phases on the respective temperatures has been studied along with the spatially varying Biot number. The Brinkman number Casson fluid parameter , thermal conductivity variation parameter , porosity Darcy number , and the ratio of fluid and solid phase thermal conductivities are the main governing parameters. The Darcy–Brinkman model is employed to govern the fluid flow in permeable media and the velocity profile has been obtained analytically. Moreover, the energy equations for both phases along with suitable boundary conditions are derived and solved with the fourth order boundary value solver. The findings of the current study depict that the Nusselt number increases with the increment in Casson fluid parameter and decreases with the increment in Brinkman number and thermal conductivity variation parameter. Overall, the heat transmission between the solid and fluid phases increases with the decrement in Brinkman number and thermal conductivity variation parameter. On the other hand, the heat transmission between both the phases magnifies by increasing the value of Casson fluid parameter.

Numerical study of MHD flow over stretching cylinder with variable Prandtl number and viscous dissipation in ternary hybrid nanofluids with velocity and thermal slip conditions

Industrial applications in domains such as warm rolling, crystal development, thermal extrusion and optical fiber illustration are seeing a significant increase. These applications specifically focus on addressing the challenge of a cylinder in motion inside a fluid environment. Elevated temperatures may affect the viscosity and thermal conductivity of fluids. Understanding the relationship between temperature and the properties of fluids is crucial. In light of these presumptions, the primary goal of this study is to examine, under transverse magnetic field, shape factor, velocity, thermal slip conditions and viscous dissipation, how temperature-dependent fluid properties could enhance the heat transfer efficiency and performance evolution of ternary hybrid nanofluid. In order to study flow fluctuations, the impact of nanoparticle addition and improvements in heat transfer, a variable Prandtl number is also included. The use of similarity variables converts the controlling flow model from partial differential equations (PDEs) to ordinary differential equations (ODEs). Mathematica’s shooting strategy solves ODEs using the fourth-order Runge–Kutta (RK-IV) method. Numerical calculations were done after setting parameters to acquire the desired results. Analytical data are provided in tables and graphs for convenient usage. The results showed that the velocity profile increases as the values of [Formula: see text], Pr, M, Re and S grow, and decreases when the values of [Formula: see text] decrease. Re, Pr and S lower the temperature profile, whereas [Formula: see text], [Formula: see text] and Ec raise it. The skin friction profile steepens as [Formula: see text], S, Re and M increase relative to the stretched cylinder, and flattens as [Formula: see text] and [Formula: see text] decrease. The Nusselt number profile rises as [Formula: see text], Pr, S and Re decrease with [Formula: see text], Ec and [Formula: see text]. When the Prandtl number goes from 3.0 to 6.2 in a ternary hybrid nanofluid with brick-shaped nanoparticles, the Nusselt number goes up by around 55.7%.

Linear temporal stability of Jeffery–Hamel flow of nanofluids

Flow stability plays a key role in transition to turbulence in various systems. This transition initiates with disturbances appearing in the laminar base flow, potentially amplifying over time based on flow and fluid parameters. In response to these amplified disturbances, the flow undergoes successive stages of different laminar flows, ultimately transitioning to turbulence. One influential parameter affecting flow stability is the nanoparticle volume fraction (ϕ) in nanofluids, extensively employed in thermofluid systems like cooling devices to enhance fluid thermal conductivity and the heat transfer coefficient. Focusing on the impact of nanoparticles on Jeffery–Hamel flow stability, this study assumes fluid properties are temperature- and pressure-independent, exclusively examining the momentum transfer aspect. The analysis commences by deriving the base laminar flow solution. Subsequently, linear temporal stability analysis is employed, imposing infinitesimally-small perturbations on the base flow as a modified form of normal modes. A generalized Orr–Sommerfeld equation is derived and solved using a spectral method. Results indicate that, assuming nanofluid viscosity as μnf=μf/(1−ϕ)2.5, nanoparticle effects on momentum transfer and flow stability hinge on the ratio of nano-solid particle density to base fluid density (Rρ=ρs/ρf). For ϕ∈(0,0.1], flow stabilization occurs with ϕ when Rρ<3.5000, while destabilization is observed when Rρ>4.0135. Notably, nanoparticles exhibit a negligible impact on flow stability when 3.5000≤Rρ≤4.0135.

Modified 3ω conductivity technique for measurements of thermal conductivity in cryogenic fluids

An instrument based on a modification to the 3-omega thermal conductivity technique that allows precise measurement of thermal properties in fluids is presented. Existing hot-wire techniques have difficulty measuring thermal conductivity because of the effects of natural convection distorting the measurement, however the standard 3-omega technique has been used extensively in the measurement of the properties of solids with great success. To address the challenge posed by natural convection in fluids, we modify the boundary condition of the 3-omega device configuration to be finite in extent, thereby restricting fluid motion and enabling a direct high-precision measurement of a fluid’s thermal conductivity. This modified scenario also presents an opportunity for a simultaneous measurement of the thermal diffusivity of the fluid. The behavior of the device is described with the reformed boundary conditions to show how a simultaneous measurement is made. By applying a constant temperature finite boundary condition, the solution characteristic in the frequency domain gains features that allow for simultaneous measurements of the fluid thermal conductivity and diffusivity. Given the density of the fluid, measured separately, the specific heat of the fluid can be calculated. The effects of the thermal properties of the measurement wire influence the measurement characteristic, and only when the wire thermal properties are sufficiently small compared to those of the fluid can a simultaneous measurement be made. Due to limitations in the dynamic reserve of the measurement devices, a setup is described that allows the signal of interest to be extracted and a precise measurement to be made with minimal distortion. Initial data on the thermal conductivity of helium is presented in the 4-300K temperature range. Preliminary specific heat data is also presented. Limitations on the device’s thermal properties prevent a specific heat measurement above 70K. This data is compared with reference fluid properties databases to validate the device performance.

Computational Fluid Dynamics Heat Transfer Analysis of Double Pipe Heat Exchanger and Flow Characteristics Using Nanofluid TiO2 with Water

A device called a heat exchanger is used to exchange heat transfer between two fluids with different temperatures. Because of its durability and ability to handle high-pressure application, the concentric double pipe heat exchangers are widely utilized for numerous industrial applications. To conserve pumping power energy, many researchers were involved in study of the nanoparticles to be embedded in the fluid, which will enrich the fluid thermal conductivity and surface area. This article demonstrates the flow characteristics and convective heat transfer of nanofluids containing 0.2, 0.4 and 0.6 of vol% TiO2 nanoparticles dispersed in water under turbulent conditions, which mainly can be used for cooling nuclear reactors applications. Reynolds numbers varying from 4000 to 18,000 are examined numerically. The convective heat transfer coefficient results of the nanofluid agree well against experimental data, which are slightly more than that of base water at 1.94%. The results of the numerical model showed that the convective heat transfer coefficient of nanofluids will increase when the Reynolds and volume fraction increases. By increasing the temperature of the annular hot water, the heat transfer rate will increase, showing no major impact to the convective heat transfer coefficient of nanofluids. A generalised solution predicting the convective heat transfer coefficient for extensive nanoparticle materials is proposed. The conclusion of the empirical equation is tested among published data and the results are highly congruent, confirming the strength of the gamma equation.

Dynamics of magnetized viscous dissipative material of hybrid nanofluid with irregular thermal generation/absorption

The intriguing thermophysical properties of nanoparticles have considerable potential in thermal transportation for engineering applications. The inclusion of solid nanoparticles in the base fluid raises the fluid's thermal conductivity, which improves thermal transfer characteristics. Thus, an analysis is performed by assuming the Tiwari and Das model, for the flow and energy transportation aspects of hybrid nanoparticles in a shrinkable porous medium. The current study focuses on the thermal heat transfer performance on the dynamic of ethylene glycol-based titania and alumina nanoparticles. The flow-controlling system of PDEs is transformed into a system of non-linear ODEs by using similarity transformations, and the resulting equations are then solved numerically through the solver bvp4c in Matlab function with a limit of tolerance 10−6. The multiple branches of solutions are noted for distinct values of suction and shrinking parameters. The outcomes reveal that the inclusion of titania and alumina nanocomposites improves the thermophysical properties of the base fluid significantly. The findings indicate that hybrid nanofluids are more effective for increasing the thermal transport rate. Further, in the upper branch solution, the friction drags, and energy transportation rate raises for the higher influence of suction strength while it declines for the lower branch.

Evaluation of nanolayer and particle size on fluid transport through rotating disks

AbstractIn this paper, the impact of nanolayer which shows the relationship between the nanoparticle and pure fluid is investigated on the fluid transport and thermal transfer through a rotating system. The nanolayer shows the relationship between the nanoparticle and base liquid, signifying a higher thermal conductivity than the nanoparticle and lower conductivity than the base fluid. Also, the effect of larger nanoparticle size and volume on fluid thermal distribution is considered. The nanoparticle raises the fluid thermal conductivity with the aim of conserving thermal transfer during fluid transport, consequently saving energy. The mechanics of the fluid is developed using a higher‐order coupled system of nonlinear models, solved with the aid of the Homotopy perturbation method. Obtained results from the analysis show the impact of nanolayer expansion on thermal distribution increases boundary layer thickness. Also, the size of the nanoparticle when varied from 10 to 40 nm shows a heat transfer increase of 17.02% at the center of the disk. Particle size increase indicates temperature rise as nanolayer size encompassing the nanoparticle increases. Obtained results when compared against literature give good agreement. The study finds useful applications in coolant and lubricant processing amongst other practical applications.

A comprehensive heat transfer prediction model for tubular moving bed heat exchangers using CFD-DEM: Validation and sensitivity analysis

This study established a complete heat transfer prediction model that integrates four heat transfer sub-models, including contact heat conduction, gas film heat conduction, heat radiation, and heat convection, along with an artificial softening correction based on combined approach of computational fluid dynamics and discrete element method (CFD-DEM). The model’s precision was confirmed by experimental results with relative errors below 5 %. The discussion on the heat flux contributions of the above four heat transfer mechanisms shows that with an initial particle temperature of 200℃, tube wall temperature of 30℃, and particle descent velocity of 1.3 mm/s, gas film conduction heat flux is the primary contributor to the total tube wall heat flux at 60.5 %, followed by radiation heat flux (19.5 %), contact conduction heat flux (12.1 %), and convection heat flux (7.9 %). Besides, the presentation of physical fields related to particles and the fluid showcases the model’s capability in elucidating the heat and mass transfer characteristics of the particle–fluid-wall system within tubular MBHEs. Furthermore, a local nominal range sensitivity analysis, along with a study of factors’ influence rules, was performed to quantify the effects of the 8 key model parameters on heat transfer results. The analysis indicates that fluid thermal conductivity is the predominant factor with its nondimensionalized first-order sensitivity coefficient of 54.9 %, succeeded by particle-to-wall angle factor (15.4 %), wall emissivity (14.4 %), gas film thickness (9.6 %), wall thermal conductivity (2.3 %), wall roughness (-1.6 %), particle Young’s modulus (-1.4 %), and particle specific heat capacity (0.4 %). Finally, their impacts on the heat prediction results were presented in detail.

Machine learning backpropagation network analysis of permeability, Forchheimer coefficient, and effective thermal conductivity of macroporous foam–fluid systems

Macroporous materials exhibit outstanding properties in heat and mass transfer due to their high pore volume, high surface area, and high Young's modulus. Consequently, understanding their thermofluidic properties is crucial in the design, synthesis, and optimal application of these materials. Therefore, this study, premieres, the use of a machine learning (ML) backpropagation network to develop and train a series of datasets for permeability, Forchheimer coefficient, and effective thermal conductivity of variable macroporous foam–fluid systems with respect to degrees of interstices, fluid and solid properties. To account for permeability values for flowing fluids in the Darcy regime, numerical simulations of slow–moving fluids were implemented over the materials' interstices. In comparison to similarly substantiated values of permeability in the Forchheimer regime, these values were a bit lower. The ML-based backpropagation algorithm was used to analyze data, which produced predictions (output signals) that are more than 90 % in correlation to CFD datasets. This provided insight into the effect of porosity and reduced mean pore openings on macroporous structures' thermofluidic behaviour. Material porosity was observed to play a dominant role in estimating Forchheimer coefficients and effective thermal conductivities for these foam-fluid systems. However, reduced mean pore openings were observed to be more critical for estimating permeability. The contributory effects of reduced mean pore openings on the effective thermal conductivity for these macroporous foam–fluid systems were determined to vary between 5.8 and 13.2 percent. Furthermore, the effective thermal conductivity of macroporous foam–fluid systems was also evaluated in relation to changes in the interstitial fluid and solid matrix thermal conductivity.

Experimental studies on thermal conductivity and heat transfer of 1-Butyl-3-methylimidazolium tetrafluoroborate ionic liquid and its nanocolloids

This paper outlines and discusses the thermal conductivity of 1-Butyl-3-methylimidazolium tetrafluoroborate ionic liquid, as well as three classes of nanocolloids. The [C4mim][BF4] ionic liquid was enhanced with three kinds of nanoparticles, Al2O3, ZnO and MWCNT and all fluids thermal conductivity was experimentally measured. Results discussion includes also an in-depth analysis on Prandtl number and thermal diffusivity. All the data were carefully debated in terms of state of the art advancement and these suspensions suitability for practical applications in heat transfer. It was found that the thermal conductivity increases with nanoparticles addition and this enhancement depends on nanoparticle type and temperature. Plus, the temperature influence is rather limited, while the consideration on Prandtl number and thermal diffusivity revealed that it is extremely relevant to consider all the thermophysical properties when choosing a new thermal fluid. Additionally, a comparison with well known correlations was inserted, concluding that no theory can estimate the ionic liquids nanocolloids thermal conductivity. Concluding, the thermal properties of [C4mim][BF4] ionic liquid and its nanocolloids with Al2O3, ZnO and MWCNT shows that these nanocolloids uncover great potential for heat transfer applications.

Bioconvective flow of Maxwell nanoparticles with variable thermal conductivity and convective boundary conditions

Owing to recent development in the thermal sciences, scientists are focusing towards the wide applications of nanofluids in industrial systems, engineering processes, medical sciences, enhancing the transport sources, energy production etc. In various available studies on nanomaterials, the thermal significance of nanoparticles has been presented in view of constant thermal conductivity and fluid viscosity. However, exponents verify that in many industrial and engineering process, the fluid viscosity and thermal conductivity cannot be treated as a constant. The motivation of current research is to investigates the improved thermal aspects of magnetized Maxwell nanofluid attaining the variable viscosity and thermal conductivity. The nanofluid referred to the suspension of microorganisms to ensure the stability. The insight of heat transfer is predicted under the assumptions of radiated phenomenon. Additionally, the variable thermal conductivity assumptions are encountered to examine the transport phenomenon. Whole investigation is supported with key contribution of convective-Nield boundary conditions. In order to evaluating the numerical computations of problem, a famous shooting technique is utilized. After ensuring the validity of solution, physical assessment of problem is focused. It is claimed that velocity profile boosted due to variable viscosity parameter. A reduction in temperature profile is noted due to thermal relaxation constant.

A Comparative Study of Selected Models for Effective Thermal Conductivity

This paper conducts a comparative evaluation of 22 models focusing on the effective thermal conductivity of two-phase porous materials. Calculations were performed for each model across a range of solid-to-fluid thermal conductivity ratios, spanning from 1 to 15,000, and for two different porosities: 0.1 and 0.2. The study advocates the use of dimensionless charts that normalised solid thermal conductivity (ks) and effective thermal conductivity (kef) concerning fluid thermal conductivity (kf) for qualitative analysis. Employing this approach, the examined models were categorised into four fundamental groups. The latter portion of the paper compares selected models with experimental data. These experiments involved testing eight porous media samples in the form of packed steel bars, arranged in two configurations: staggered and in-line. The tests were conducted over a temperature range of 75–400°C, corresponding to ks-to-kf ratios ranging from 1,800 to 855. Various graphical representations were used to compare measurement data with model calculations. The findings indicate that the most accurate comparisons can be made using linear charts, which present absolute values of the kef coefficient in relation to the thermal conductivity of the solid phase.

An overview of the Transient Hot Wire and preliminary studies for its implementation

The opportunity to design a new portable system for measuring thermal conductivity in fluids arose from the need to measure the phase state (liquid and/or vapour). As is well known, thermal conductivity varies in relation to the phase state of the fluid. The Transient Hot Wire Method was used to measure thermal conductivity. First, the work includes innovations in the analytical model of heat transfer, progressing over time to contemporary numerical models used in standards. The applications in the bibliography span a wide range, including gases, liquids, and the latest advances in the field of nanofluids. Secondly, the study delves into the transient model of heat exchange, focusing on conduction. The authors used standardized correction equations for the prototype, ensuring accuracy and relevance. Finally, the work includes the design and construction of the transducer. This process begins with a Monte Carlo simulation, predicting the expected results. This simulation helps to define measurement system components based on their performance characteristics and in-depth analysis.

The function of nano layer in enhancing the thermal conductivity of TiO2/water nanofluids

Nanoparticles have the capability to effectively improve the thermal conductivity of base fluids, thus improving the heat transfer coefficient of heat transfer systems. In this study, a non-equilibrium molecular dynamics (NEMD) method based on the Fourier law is employed to study the thermal conductivity of TiO2 (r-TiO2)/water nanofluids with temperatures ranging between303K and 333K and volume fractions in the range of1-2%. The ordered layer structure as a shell is analyzed and its influence is surveyed by calculating the number density and radial distribution function (RDF).The results revealed that a clear, solid-like nanolayer of about 0.5 nm can be observed around the nanoparticle. In this regard, the thickness of the nanolayer is less affected by variations in volume fraction and temperature. The g(r) values and the number density decreased with the increase in temperature. Additionally, the g(r) values and the number density at the level of the nanolayer were much higher compared to those at other parts. This indicates the existence of more water molecules in the nanolayer, thereby reducing contact thermal resistance and improving thermal conductivity. Macroscopically, the thermal conductivity increases with the increase in volume fraction. It was found that the increase in the volume fraction from 1%to 2%at303Kresulted in an increase in the effective thermal conductivity from1.027 and 1.042, respectively. In other words, the thermal conductivity of the nanofluid was 2.7% and 4.2% higher than that of the base liquid under the same conditions.

Thermal conductivity measurements for n-nonane and n-undecane at elevated temperature and pressure

Hydrocarbons have wide applications in various industrial processes, and the knowledge of thermophysical properties is the foundation for their utilization. As an important thermophysical property, the thermal conductivity of fluids is vital in the evaluation of energy conversion quality, like heat transfer enhancement, thermodynamic cycle efficiency evaluation, etc. Therefore, obtaining accurate experimental data is of great importance for the utilization of hydrocarbons. Here, the thermal conductivities of liquid n-nonane and n-undecane were investigated using the transient hot-wire method (combined expanded uncertainty is 2.0 %) with a wide temperature and pressure range from 293.15 to 523.15 K and 0.1 to 15.0 MPa. For the convenience of engineering applications, a polynomial as a function of temperature and pressure was proposed to correlate the experimental data, the average absolute deviations between experimental data and fitted data are 0.29 % for n-nonane and 0.35 % for n-undecane, which indicates that the polynomial describes the experimental data well in the measured region. Meanwhile, the available literary data were collected and compared with our results, and good agreement was found between literary data and our results. This work is not only helpful for the industrial applications of hydrocarbons but also helps to understand the internal mechanism of the thermal conductivity of hydrocarbons.

Conjugate heat transfer analysis of sidewall-heated rectangular microchannels with different bottom wall materials

In this study, the conjugate heat transfer in a microchannel under four sidewalls (left, right, top, and bottom wall facing upstream) heating conditions is investigated experimentally and numerically. The microchannel has a width of 500 μm and a depth of 100 μm. Micro-Particle Image Velocimetry (Micro-PIV) and Temperature Sensitive Paint (TSP) are respectively applied to measure the velocity and temperature fields at a Reynolds number (Re) of 20. The experimental results demonstrate that the temperature gradient exists in both the left, right, and bottom wall, indicating the existence of conjugate heat transfer. Thus, 3D conjugate heat transfer simulations are subsequently conducted. Good agreements are attained between numerical and experimental data only with the non-ideal boundary condition. Otherwise, there is a significant discrepancy between them. Further parametric studies on bottom wall to fluid thermal conductivity ratio (kb/kf) and Re show that the fully developed overall Nusselt number (Nu‾) in the conjugate heat transfer case is approximately 4.55, much higher than the analytical solution 0.87 without accounting for conjugate heat transfer. As kb/kf is varied from 0.21 to 6.48, there exists a critical kb/kf=1.79, before and beyond which the total heat flux respectively increases and decreases with kb/kf. However, Nu‾ is a monotonically increasing function of kb/kf, with a peak value of 5.75 occurring at kb/kf = 6.48.

Thermal conductivity in one-dimensional electronic fluids

We study thermal conductivity in one-dimensional electronic fluids combining kinetic [R. Samanta, I. V. Protopopov, A. D. Mirlin, and D. B. Gutman, Thermal transport in one-dimensional electronic fluid, Phys. Rev. Lett. 122, 206801 (2019)] and hydrodynamic [I. V. Protopopov, R. Samanta, A. D. Mirlin, and D. B. Gutman, Anomalous hydrodynamics in one-dimensional electronic fluid, Phys. Rev. Lett. 126, 256801 (2021)] theories. The kinetic approach is developed by partitioning the Hilbert space into bosonic and fermionic sectors. We focus on the regime where the long-living thermal excitations are fermions and compute thermal conductivity. From the kinetic theory standpoint, the fermionic part of thermal conductivity is normal, while the bosonic one is anomalous, that scales as ω–1/3 and thus dominates in the infrared limit. The multi-mode hydrodynamic theory is obtained by projecting the fermionic kinetic equation on the zero modes of its collision integral. On a bare level, both theories agree and the thermal conductivity computed in hydrodynamic theory matches the result of the kinetic equation. The interaction between hydrodynamic modes leads to renormalization and consequently to anomalous scaling of the transport coefficients. In a four-mode regime, all modes are ballistic and the anomaly manifests itself in Kardar-Parisi-Zhang-like broadening with asymmetric power-law tails. “Heads” and “tails” of the pulses contribute equally to thermal conductivity, leading to ω–1/3 scaling of heat conductivity. In the three-mode regime, the system is in the universality class of a classical viscous fluid [Herbert Spohn, Nonlinear fluctuating hydrodynamics for anharmonic chains, J. Stat. Phys. 154, 1191 (2014); O. Narayan and S. Ramaswamy, Anomalous heat conduction in one-dimensional momentum-conserving systems, Phys. Rev. Lett. 89, 200601 (2002)].

Wellbore-heat-transfer-model-based optimization and control for cooling downhole drilling fluid

To address the two critical issues of evaluating the necessity of implementing cooling techniques and achieving real-time temperature control of drilling fluids underground in the current drilling fluid cooling technology, we first established a temperature and pressure coupled downhole heat transfer model, which can be used in both water-based and oil-based drilling fluid. Then, fourteen factors, which could affect wellbore temperature, were analyzed. Based on the standard deviation of the downhole temperature corresponding to each influencing factor, the influence of each factor was quantified. The influencing factors that can be used to guide the drilling fluid's cooling technology were drilling fluid thermal conductivity, drilling fluid heat capacity, drilling fluid density, drill strings rotation speed, pump rate, viscosity, ROP, and injection temperature. The nondominated sorting genetic algorithm was used to optimize these six parameters, but the optimization process took 182 min. Combining these eight parameters' influence rules with the nondominated sorting genetic algorithm can reduce the optimization time to 108 s. Theoretically, the downhole temperature has been demonstrated to increase with the inlet temperature increasing linearly under quasi-steady states. Combining this law and PID, the downhole temperature can be controlled, which can reduce the energy for cooling the surface drilling fluid and can ensure the downhole temperature reaches the set value as soon as possible.

Efficiency Improvement of Double Pipe Heat Exchanger by using TiO2/water Nanofluid

Heat exchangers are commonly utilized to transfer heat between two fluids in a number of industries. However, parameters such as fluid flow velocity, temperature difference, and thermal conductivity limit their efficiency. Researchers have investigated the use of nanofluids - fluids containing nanoparticles that boost thermal characteristics - to improve the performance of heat exchangers. The use of nanofluids can improve the efficiency of double-pipe heat exchangers. However, research on the influence of TiO2/water nanofluid on the performance of double-pipe heat exchangers is insufficient. The purpose of this research is to investigate the impact of TiO2/water nanofluid on the efficiency of a double-pipe copper counter-flow heat exchanger. A double-pipe copper counter-flow heat exchanger using cold (room temperature) and hot (70°C) water as working fluids was used in an experimental investigation. They created nanofluids by adding varying concentrations (0.1%, 0.3%, and 0.5%) of TiO2 nanoparticles to water and measuring their heat conductivity and viscosity. They then calculated the overall heat transfer coefficient and efficacy by measuring the input and outlet temperatures as well as the flow rates of both fluids. It was discovered that adding TiO2 nanoparticles to water enhanced its heat conductivity and viscosity substantially. The overall heat transfer coefficient increased up to 0.3% but declined at 0.5% nanoparticle concentration. At a nanoparticle concentration of 0.3%, the maximum effectiveness was attained, with a corresponding increase in efficiency of up to 23%. The scientists found that using TiO2/water nanofluid to improve the efficiency of double-pipe heat exchangers is a viable option.