Heat Transfer Parameters Research Articles

Investigation of the Hottel–Whillier–Bliss Model Applied for an Evacuated Tube Solar Collector

The goal of this research is to examine the applicability of the Hottel–Whillier–Bliss model, developed for flat-plate collectors, to evacuated tube solar collectors. During this study, the model is applied to an evacuated tube collector, and then the identification and validation of the model are made with the help of measurements performed on the collector. This research also includes the application, identification and validation of the energy balance model for the investigated solar collector. This model works for both flat-plate and evacuated tube collectors. The results obtained with the two different models are then compared. By comparing the modelled results with the measured values, the accuracy and applicability of the models can be determined. Based on the results, the Hottel–Whillier–Bliss model works excellently with evacuated tube solar collectors for predicting the outlet temperature of the medium from the solar collector. It is important to note that the identification gives negative heat transfer parameter values. According to the validation, the average absolute error is 0.8 °C, and the average relative error is 1%. For the energy balance model, these values are 0.87 °C and 1.1% respectively, indicating that the accuracy of the Hottel–Whillier–Bliss model is very similar, and even slightly higher. Additionally, the research provides further proof of the applicability of the energy balance model to evacuated tube collectors.

Graphene functionalized nano-encapsulated composite phase change material based nanofluid for battery cooling: An experimental investigation

The graphene-nano encapsulated composite phase change material (GnePCM) based nanofluid holds great potential as a coolant for batteries in electric vehicles. The current work focuses on the synthesis and study of the cooling performance of GnePCM-based nanofluid. Few layered graphene (FLG) was synthesized via the liquid phase exfoliation method. Mini-emulsion polymerization was adopted to encapsulate composite PCM (octadecane: paraffin wax) within polystyrene shell and distribute these nanoballs across the graphene flakes of FLG to obtain GnePCM. Differential Scanning Calorimetry (DSC) was used to optimize the composition of composite PCM based on the melting range and latent heat. GnePCM was characterized by Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), DSC, Fourier Transform Infrared (FTIR) spectroscopy, and Raman Spectroscopy. Nanofluid was made by mixing GnePCM slurry with the base fluid (ethylene glycol − water mixture) and its thermo-physical properties were estimated. The analysis of thermal conductivity and specific heat capacity showed a 14.7 % and 56 % increase for the nanofluid compared to the base fluid. The optimal concentration of nanofluid for maximum stability was 10 % v/v based on zeta potential measurements. The heat transfer studies and pressure drop studies were conducted on a set of 10 cylindrical heaters, mimicking a 18,650 battery cell pack. The nanofluid could potentially achieve a maximum reduction of 5 °C in average surface temperatures of the cells as compared to the base fluid. The enhanced cooling efficiency of nanofluid could be related to the increased thermal conductivity and heat capacity of GnePCM, as well as the absorption of latent heat during its melting process. Enhancement in heat transfer parameters was found to be more prominent at lower flow rates for the nanofluids. The results reveal that the flow rate and power input play a significant role in the cooling performance of the nanofluid. Due to the increased viscosity of the nanofluid, a slight increase in the pressure drop and pumping power was observed at higher flow rates, as compared to base fluid.

Python-based machine learning estimation of thermo-hydraulic performance along varying nanoparticle shape, nanofluid and tube configuration

In this research article, a Python-based machine learning model prediction study was conducted based on the study results obtained from sudden expansion tubes containing different expansion angles, dimpled fin structures and nanofluids, whose thermo-hydraulic performance was previously examined. In the study, Artificial Neural Network and Ridge regression models were used to make predictions on the average Nusselt number (Nu), average Darcy friction factor (f) and performance evaluation criteria (PEC). Physical variations of the sudden expansion tube were taken into account and a detailed comparison of the results was made. A superior average Nu was acquired as 172.45 %, 22.05 %, 17.18 %, 13.65 %, and 7.76 % compared to Ag-MgO/H2O, Al2O3/H2O (blade), CoFe2O4/H2O, Al2O3/H2O (cylindrical), and Al2O3/H2O (platelet), respectively. The highest Performance Evaluation Criteria (PEC) for Re= 2000 based on Al2O3/H2O (platelet) shows an increase of 4.84 %, 12.08 %, 11.76 %, 66.05 %, and 148.94 % compared to Al2O3/H2O (cylindrical), Al2O3/H2O (blade), CoFe2O4/H2O, Fe3O4/H2O, and Ag-MgO/H2O, respectively. From the results obtained, it was determined that Python-based Machine Learning approach which facilitates custom optimizations showed a significant performance with small margins of error in predicting the heat transfer parameters. The lowest error rates of machine learning and polynomial ridge regression models ranged from 0.2 % to 5.4 % for the unseen test set and the application of Python-based algorithms provided considerable savings in calculation time compared to conventional methods. On the other hand, using machine learning models with feature engineering has been found to increase model performance by at least 30 %. In these years when studies on the predictions of thermo-hydraulic studies are very rare in the literature, this study is intended to facilitate scientists, engineers and academicians who will further study on this subject.

Теплоотдача при движении воды в трубе при температурах, близких к температурам кипения в переходном режиме

Currently, there is a problem of developing effective methods to calculate heat and mass transfer processes during steam condensation from a vapor-gas mixture in industrial devices. This is due to the need to create new reliable and highly efficient designs of heat exchangers for various purposes. The finite element method has been used in the ANSYS Fluent software package during the numerical simulation. An experimental plant is tested in the pipeline of an industrial enterprise at the production site of the Technopolis KHIMGRAD industrial park (Kazan-city). The applicability of the Lee model to solve problems of water flow in a pipeline with partial evaporation is proved. This model allows you to accurately account for the processes of evaporation and condensation, which is important for the design of cooling and air conditioning systems. The authors have designed a three-dimensional model of the flow area of the experimental module and a CFD model to calculate temperatures, phase velocities and their concentrations, considering the peculiarities of the ongoing processes of heat and mass transfer. A slight effect on the heat flow of a 180° rotation during the flow of a liquid medium in the range of the Reynolds numbers 1800–2600 is shown. The developed model is verified with the results obtained at the experimental plant. It is established that the model reproduces experimental data well. An analysis of studies of heat and mass transfer processes during the fluid flow in channels in the presence of phase transitions is carried out. The problems of calculating the parameters of heat transfer during the movement of a fluid in a transient mode are revealed, especially at values of the Reynolds number close to 2000. The experimental plant diagram is presented. It is found that in the range of Reynolds numbers of 2600–3600, the calculated temperature values differ from the temperature values obtained experimentally by less than 0,42 %. During the partial transition of water into steam in the range of Reynolds numbers of 1800–2600, the deviations were less than 6 %, which confirms the adequacy of numerical modeling of calculating the heat transfer process in a pipe. It is shown that considering the influence of temperature on surface tension, the coefficient of thermal conductivity of water and the coefficient of dynamic viscosity of water is important to obtain accurate results. The proposed approach can be used to optimize the operating parameters of condensers and evaporators, as well as to accurately calculate the heat transfer coefficient and determine the areas of vapor formation. It will improve the energy efficiency of industrial installations and reduce the cost of equipment operation.

Improved yield of UV and heat-stable Monascus yellow pigment by statistical optimization of solid-state fermentation conditions and extraction process

Monascus species are well-known for their ability to produce biocolorants. A high-performing strain, M. purpureus F2–19, was recently developed by genome shuffling. Here, the entire bioprocess, starting from solid-state fermentation conditions to the extraction method, was statistically optimized to improve yellow pigment yield by the strain. Among culture conditions, monosodium glutamate concentration (used as nitrogen source), moisture content, and incubation period significantly influenced pigment production using less expensive broken rice as a substrate. Post-optimization, a yield of 1548.4 ± 14.6 AU/g was achieved, representing a 9.7-fold increase over the primary condition. The statistical model developed using central composite design of response surface methodology (CCD-RSM) is highly significant, with a P value of <0.0001. Similarly, a significant model (P < 0.0001) for extraction improved pigment yield further by 1.16-fold (actual output: 1796.4 ± 13.4 AU/g). The pigment remained highly stable with a preservation rate of ∼90 % after 2.5 h exposure to a high temperature of 100 °C or UV light (254 nm). Even autoclaving at 121 °C for 15 min preserved 96.9 % of the pigment. These values are higher than reported for other commercial microbial yellow pigments, riboflavin, β-carotene, or lutein, thus highlighting its potential as a natural food colorant. Liquid chromatography-mass spectrometry (LC-MS) of the pigment identified nine distinct yellow compounds, with monascin being the most abundant. Thus, the optimized bioprocess would facilitate economical large-scale production of the yellow pigment; but its implementation still requires efficient selection of bioreactors and optimizations of scaling-up, especially the heat and mass transfer parameters.

Coupled heat transfer and chemical kinetics in a calcium oxide/hydroxide fixed bed thermochemical energy storage reactor

Among energy storage technologies, thermochemical heat storage despite its unique advantages, remains at a nascent state due to varied technical challenges. One of the key unknowns in the otherwise well-studied calcium oxide/hydroxide chemistry, is a lack of understanding of the possible output power profiles. Here, we investigate the theoretical power output from a fixed-bed, modular, honeycomb-geometry thermochemical energy storage (TCS) reactor based on a calcium oxide/hydroxide, using finite element modeling of heat transfer coupled with reaction kinetics. We calculate the extent of reaction and temperature profiles in a lattice of honeycomb cells that make up the bed, while varying heat transfer related parameters. We find that the size of the unit cell can limit energy discharge, for example, increasing the time to completion for the reaction to ∼7 hours as the cell size increases to 6 cm, even though the reaction kinetics is fast at ∼2 mins. The time constant of the transient power profile increases by a factor of ∼4 as the cell size increases by a factor of ∼3, when considering cells in the nominal size range 2–6 cm. Besides cell size, we investigate how the power profile is affected by the following parameters: the thermal conductivity of the bed, the initial temperature, the material of the cell wall and the heat transfer coefficient of external flows. In particular, we identify the combination of parameters that can vary the power profile on demand to operate the same reactor as either a thermal capacitor or alternately, a thermal battery. This work informs future design possibilities with oxide-hydroxide, solid–gas reaction TCS and provides insight into critical heat transfer parameters.

Thermodynamic Modeling and Analysis of Boil-off Gas Generation and Self-Pressurization in Liquefied Carbon Dioxide Tanks

The importance of the safe transport of liquefied carbon dioxide (LCO2) is increasing owing to environmental issues. When transporting a low-temperature liquid, boil-off gas generation and self-pressurization occur due to heat ingress, affecting the holding time of a low-temperature liquid tank. This study developed and compared three thermodynamic self-pressurization models to estimate the holding time of LCO2: Thermal homogeneous model (THM), Thermal two-zone model (TTZM), and Thermal multi-zone model (TMZM). Thermodynamic differential equations were solved for THM, and software was used for TTZM. For TMZM, the parameters were optimized using experimental data to determine the heat ratio parameter f and heat transfer parameters K1 and K2. THM and TTZM estimated an unreasonably long holding time, approximately 42 days. The TMZM, however, showed a satisfactory holding time of 12–13 days. These results can help predict the self-pressurization in the storage tanks of LCO2 and be applied to actual LCO2 carrier cargo handling systems, with the modeling results indicating that the 12–13 days of LCO2 self-pressurization based on the TMZM appears to be the most suitable.

Experimental investigation of single slope solar still for culinary wastewater treatment

Solar still desalination (SD) offers a sustainable method for purifying contaminated water, despite its productivity limitations. This study proposes an effective treatment process for culinary wastewater (CWW), multilayer-filtered culinary wastewater (MFCWW), and borewell water. We conducted a comprehensive experimental analysis comparing key SD characteristics, including evaporative heat transfer, efficiency, productivity, exergy, and water quality parameters, across these water sources. Our findings reveal that integrating multilayer filtration with CWW significantly improves efficiency, productivity, turbidity reduction, and hardness removal compared with untreated CWW. Notably, MFCWW has emerged as the most promising modification, demonstrating enhanced solar still performance over conventional SD processes. This study highlights the potential of combining multilayer filtration with solar desalination as an innovative approach to improve water purification outcomes, particularly for culinary wastewater treatment.

Comparison of upward and downward flow in high-pressure bulk CO2 gas adsorption on NaY zeolite fixed bed

Adsorption is an appealing technology for the removing of CO2 from natural gas because it can handle high CO2 concentrations at high pressures. The determination of mono-component breakthrough curves provides heat and mass transfer parameters to assess separation effectiveness that can be used for simulation of swing adsorption separation processes (PSA, TSA etc.). However, in lab-scale fixed-bed adsorption, it may be challenging to perform this assessment due to low flow conditions that are usually employed, affecting the flow regimedepending on the operation conditions. In this sense, this work aimed to evaluate the effect of flow regime configurations and difference in gases densities by means of residence time distribution (RTD) analysis in the PSA of CO2 in a NaY zeolite fixed bed , in order to to collect information that satisfy pipeline specifications in industrial applications. A high-pressure lab-scale apparatus was used with NaY particles of 0.7250 mm mean diameter, a 10.5 cm bed height , and a tubular column of 2.0 cm internal diameter. The upward and downward flows were conducted under 528.82 ± 4.59 NmL min−1 inlet mass flow rate, 51 bar, and 30 °C. The RTD analysis was performed to verify the flow regime, and mass transfer zone (MTZ) length was estimated. It was observed that downward flow conditions promoted higher concentration spread than upward flow. RTD analysis showed that downward flow is dominated by laminar convection while the upward flow is dominated by dispersion. MTZ length increased from 0.64 cm in upward flow to 5.81 cm in downward flow. Therefore, assessing CO2 flow conditions and, additionally, the difference in gases densities, are important steps that should be taken when dealing with fluid adsorption under high pressure because different densities between fluid components severely changed and affected flow regime and, consequently, separation effectiveness.

Numerical Investigation on Enhanced Thermal Performance of Rectangular Microchannels with Triangular Ribs

Effective thermal management becomes crucial with the rising heat produced by electronic devices. Microchannel convection shows excellent potential as a cooling solution. This study employs numerical computational techniques to examine rectangular microchannels’ flow and heat transfer parameters on a semi-octagonal structure, specifically focusing on the Reynolds number (Re) ranging from 100 to 500. An extensive analysis evaluates the heat transfer design and hydraulic performance. Furthermore, the microchannel's diodic performance is assessed by comparing the Nusselt number (Nu) and the pressure drop in both the forward and backward directions. The study demonstrates the excellent performance of the microchannels within the microstructure under low Reynolds number (Re) conditions. Emphasizing the significance of preserving the fundamental geometric characteristics while improving the fluid dynamics within the microchannel. The semi-octagonal structure microchannel design surpasses the conventional design in bidirectional heat transfer by improving spatial fluid mixing. With a Reynolds number of 300, the Nusselt number of this microchannel surpasses that of the traditional rectangular design by a considerable margin. In addition, at this Reynolds number, the thermal diodicity (Dit) and pressure drop diodicity (Dip) showed significant improvements, with values of 1.16 and 1.45, respectively. Therefore, this study comprehensively compares the enhanced heat transfer of microchannel walls under constant heat flux, highlighting the advantages of semi-octagonal structural design in improving heat transfer and hydraulic performance. The results show that this innovative design has great potential to improve the efficiency of microchannel cooling and provides an important reference for the development of efficient thermal management systems.

Micro segment analysis and machine learning prediction for thermal-hydraulic parameters of propane condensation flow in a PCHE straight channel

In the LNG regasification process, the printed circuit heat exchangers(PCHE) is an ideal choice for vaporizer, with propane as the intermediate working medium in the hot side of PCHE. In this work, numerical simulations of propane condensation flow and heat transfer at different operating parameters was carried out in a semi-circular straight channel of PCHE. The micro-segment analysis method was used to present the local heat transfer coefficient and pressure drop in the channel. The results indicate that the propane condensation process can be divided into three stages: the “constant temperature condensation stage” in the droplet condensation state, the “varying temperature condensation stage” in the film condensation state, and the “subcooled stage” in the liquid phase state. Different operating parameters can affect the start and end position of each stage, as well as the parameter values in the same state. An artificial neural network method was used to predict the local heat transfer coefficient and pressure drop, with the predicting error of less than 5 % and 10 % respectively. This study provides a machine learning method to accurately predict the flow and heat transfer parameters for propane condensation flow in PCHE channel and valuable for future design of LNG vaporizer.

Novel 2D Layered MXene Nanofluids for Enhancing the Convective Heat Transfer Performance of Double-Pipe Heat Exchangers.

This paper proposes a new class of novel 2D layered structured materials, such as MXene (MX), for the synthesis of innovative nanofluids as coolants to evaluate the convective heat transfer performance of a double-pipe heat exchanger (DPHE). Convective heat transfer experiments were successfully conducted in lab-scale fabricated DPHE using low-concentration MXene nanofluids by varying the volume concentration of MXene nanoparticles (0.01-0.05 vol %) in different base fluids. The influence of the MXene nanofluids on various convective heat transfer parameters, such as LMTD, Nusselt number, heat transfer coefficient, and heat transfer rate without using any inserts in the DPHE was experimentally investigated. The results of the experiments revealed that the heat transfer coefficient and Nusselt number increase with increasing Reynolds number (Re) and concentration of MXene nanoparticles in the base fluids. Maximum enhancement in heat transfer coefficient (126%) was achieved for methanol-based MXene nanofluids at 0.05 vol %. Moreover, the Nusselt number exhibits a maximum enhancement of ∼50% for methanol- and water-based MXene nanofluids. In contrast, the thermal performance factor was also estimated, and it was observed that water- and methanol- based MXene nanofluids showed higher values than castor oil- and silicone oil-based MXene nanofluids. Finally, the LMTD and heat transfer coefficients were successfully validated using Aspen HYSYS 12.1 software.

Accurate identification of soil thermal parameters and groundwater flow from thermal response tests

The soil heat transfer parameters constitute the key information required for designing ground source heat pump (GSHP). Due to the simplification of the common analytical models, traditional methods are difficult to achieve accurate identification of soil thermal parameters and seepage velocity simultaneously. In this work, a high-precision method to simultaneously identify soil thermal conductivity, volumetric heat capacity, and seepage velocity based on deep neural network is proposed. Through the inversed orthogonal method, the training and validation samples are obtained from a large number of thermal response tests (TRTs) on a full-scale simulation platform. The accuracy of this method was verified by comparing identification results with the true values. Meanwhile, the uncertainty of identification results under different noise conditions was quantified, and the impact of test duration was discussed. The results showed that when the maximum random noise is 0.1 °C, the identification errors of the thermal conductivity, volumetric heat capacity, and seepage velocity are only 1.14 %, −4.34 %, and −3.08 %, respectively. The identification reliability can be improved by obtaining the average value of the results under multiple tests and extending the test duration. When the test duration increased from 50 to 100 h, the uncertainty of the identified parameters reduced by 54.57 %, 48.41 %, and 65.70 %, respectively.

Improved Heat Transfer Capabilities of Nanofluids—An Assessment Through CFD Analysis

AbstractConventional fluids used in fission‐based water‐cooled nuclear reactors have lower heat transfer coefficients (HTCs) and thermal conductivity, which has led researchers to explore high‐performance fluids that can enhance heat transfer in routine operation and prevent core meltdown in the case of accidents. It is important to investigate a wide range of fluids that can help designers improve thermal hydraulic characteristics, such as HTC, critical heat flux, and minimum departure from nucleate boiling ratio (MDNBR). In this study, the effectiveness of nanofluids in enhancing heat transfer parameters, including thermal conductivity and heat capacity, was investigated. Four different nanofluids (Al2O3–H2O, ZrO2–H2O, Ag–H2O, and Si–H2O) with pure water as the primary coolant in an HPR‐1000 nuclear reactor were compared using computational methods. Due to computational limitations, only the flow channel among four fuel rods with the highest power density in the core was simulated using Eulerian computational fluid dynamics. The results of this study show that silver water (Ag–H2O) nanofluid outperformed other nanofluids and pure water. It had a higher average HTC and MDNBR, with a 67.15 % and 45.23 % improvement, respectively, compared to pure water. The fuel rod wall temperature was also reduced by 28.5 K with Ag–H2O compared to water. Comparison of current simulated results with literature data shows a good agreement.

SAMPO-P: A prototypical scale low-temperature experiment on two-layer melt pool heat transfer in LWR lower head

To better understand the thermal behavior of a two-layer melt pool with a high Rayleigh number—a pattern observed in the RASPLAV study, which indicates a significant risk to pressure vessel integrity and the success of in-vessel retention (IVR) strategies—this paper reports experimental findings from a 2D, full-scale (1:1 ratio) prototypical stratified melt pool (SAMPO-P). A series of experimental tests were carried out with varying heating powers and top layer heights, achieving a Rayleigh number of 3.77×1015, comparable to that found in light water reactors (LWR). Water was used to simulate the bottom layer, while n-octanol represented the top layer. Internal decay heat was modeled in the bottom layer using electric heating rods. After analyzing the main heat transfer parameters from the experiment, this paper derived several useful heat transfer correlations. The normalized temperature and heat flux distributions remained consistent across different power levels, and the normalized heat flux in the bottom layer aligned well with existing experimental correlations. In the bottom layer, the downward heat transfer coefficient was lower compared to other single-layer correlations, likely due to increased upward heat transfer.

Analysis of thermal non‐equilibrium model on the Ree–Eyring nanofluid flow influenced by an inclined magnetic field

AbstractThis research seeks to explore the behavior of Ree–Eyring nanofluid over an extended surface influenced by an inclined magnetic field within a permeable medium. The local thermal non‐equilibrium between the particle, liquid, and solid phases is represented by a three‐temperature model. The problem is addressed numerically using bvp4c code in MATLAB software. The findings are displayed in the format of tables and graphs. The study shows that higher values of the interface heat transfer parameter led to a decrease and increase in the fluid phase and solid phase Nusselt number, respectively. The velocity and concentration distributions decrease with increasing porosity coefficient. Nevertheless, the fluid phase temperature distribution shows an opposing trend. Furthermore, increasing the non‐Newtonian fluid parameter leads to a raise in the surface drag coefficient.

Učinak naprednih izolacijskih materijala i strategija pasivne optimizacije na toplinsku udobnost u tradicionalnim kućama tijekom zime

This study proposed an interior thermal comfort test to enhance the interior thermal comfort of traditional houses in the Guan Zhong region of the Shaanxi Province during winter. The study was conducted in Xiaoliu village by employing field tests and a questionnaire survey. The field tests and analysis revealed that the thermal comfort of traditional houses in this region is poor, the spatial layout of the houses is unsuitable for conserving heat, the thermal properties of the enclosure walls are inadequate, and the mode of heating is inefficient. The heat transfer parameters, heat lost and gained through fabrics, and thermal properties of nanomaterials have been used to improve the thermal comfort analysis. Combined with the local economic conditions, passive design strategies such as optimizing the spatial layout, improving the thermal insulation performance of the enclosure walls, and using solar energy were implemented. The simulation results indicate that energy consumption can be significantly reduced, and the indoor thermal comfort of traditional houses can be enhanced by reasonably dividing the indoor space, increasing the thermal insulation performance of the enclosure walls, and making better use of solar energy and natural ventilation. Therefore, to improve thermal comfort and reduce the energy load of traditional houses in the Guan Zhong region, it is necessary to adopt passive optimisation strategies.

Sensitivity analysis and reasonable matching of key operating parameters of flow and heat transfer in liquid-cooling plate used for IGBT module of high-speed train traction inverters

High-power insulated gate bipolar transistors (IGBTs) are important components of traction inverter. It is important to ensure the suitable temperature of the IGBT module for keeping the operation of trains efficient and safe. Due to the significant differences in train operating environment and traction performance, the cooling requirements for IGBT are also different. Therefore, identifying and matching various parameters of operating parameters of flow and heat transfer in high-power-density IGBT module liquid-cooling plate is of great significance to achieve optimal energy efficiency. Based on the Reynolds-averaged Navier–Stokes equations, shear stress transport k–ω turbulence model, and orthogonal experimental design, the flow and heat transfer characteristics of the liquid-cooling plate were simulated, and the numerical method and settings were verified experimentally. The results show that the single-parameter mapping relationship between the operating parameters and cooling performance indices (pressure drop, temperature rise, and maximum surface temperature, corresponding to Δp, ΔT, and Tmax, respectively) of the liquid-cooling plate is clear, and the flow rate and physical properties of the cooling liquid have significant effects on the cooling performance. The multi-objective optimization method based on the radial basis function surrogate model and nondominated sorting genetic algorithm II can match operating parameters under the minimum of Δp, Tmax and maximum of ΔT. Considering the appropriate values of the three indexes comprehensively based on Pareto optimal solution set, the error between the calculated value and the predicted value is less than 8 % when the inlet flow rate is 20 L/min, the temperature is 330.68 K, the pressure is 2.2 bar and the calorific value is 75.2 kW/m2. The results can be to provide a method and database for engineers to design liquid-cooling plate for high-speed train IGBT to achieve the highest efficiency.

A variational multiscale stabilized finite element method for double diffusive incompressible flow with application to mixed convection in a heated staggered cavity under magnetic field

In this work, a novel stabilized finite element scheme in a subgrid multiscale variational framework is proposed to efficiently solve double-diffusive incompressible Newtonian fluid flow in a complex geometry occurring in several real-life applications. Here, the fine scale effects are transferred to the course scale problem following algebraic subgrid analysis, and then, the course scale equations are computed and the key stabilization parameters are derived following the Fourier analysis. The influence of flow, heat, and mass transfer parameters such as Reynold’s Number, Hartmann Number, Richardson Number, and Lewis Number are analyzed under a magnetic field, through the streamlines, isotherms, and the local heat fluxes to understand the double-diffusive mixed convective process in a complex staggered cavity, which is relevant to engineering applications such as ventilation and contamination assessment systems. The study finds that maximum species contamination together with the maximum Sherwood Number (12.54) occurs when the Richardson number is 10, and the minimum contamination together with the minimum Sherwood Number (0.71) occurs when the Lewis number is 0.1 when other parameters are varied within the operational range. The results are validated with previously existing literature for simple cases.

Influence of nozzle profile on submerged pipe jet impingement heat transfer

ABSTRACT Current work focuses on enhancing the performance of solar air heater by employing vertical submerged pipe jets featuring different profiles: circular, square, triangular, and rectangular. The study investigates parameters including jet diameter ratio d / D h ranging from 0.044 to 0.11 and the jet spacing ratio ( Sj / D h ) varying from 0.108 at 0.433 while keeping the streamwise ( X / D h ) and spanwise Y / D h pitch ratio fixed at 0.867. The Reynolds number Re ranges from 3,000 to 18,000. Initial results for all the profiles were obtained through CFD simulations, indicating that the circular pipe jet demonstrates superior heat transfer and thermo-hydraulic performance parameter (THPP). The experimental validation of circular profile pipe jet showed a maximum THPP of 2.69 achieved at a d / D h of 0.066 and Sj / D h of 0.217, with a Reynolds number of 15,000.