Heat Transfer Model Research Articles

Development of a doubly-fed compound control for hybrid ground source heat pump systems in hot summer and cold winter areas

In hot summer and cold winter areas, the impact of soil thermal accumulation is significant even for hybrid ground source heat pump systems (HGSHPs), especially after a long-term operation. To alleviate the energy performance degradation caused by soil temperature rise, a detailed temperature field heat transfer model of ground heat exchangers (GHXs) has been established and a doubly-fed compound control for HGSHPs is developed and integrated into a central controller module. The central controller can automatically control the loop flow distribution of units and achieve group activation of GHXs based on the load sequences forecasting feedforward and system variables feedback processes. Five control modes are included in the central controller, and the energy performances and soil temperature rise distribution of the HGSHPs with different control modes for fifteen years are compared. The results indicated that the HGSHPs performs best in terms of energy performance and soil thermal alleviation with Control Unit 13. Compared to the Normal control mode, the mean water temperature of GHXs, energy consumption of the chiller and heat pump decreased by 1.6 °C, 5.9 %, and 15.5 %, respectively, and the units COP increased by 11.3 %.

Austenite grain growth in tailored cooling rate experiment designed by numerical simulation for peritectic steel

The heat transfer model for steel solidification in Al2O3 crucial and permanent mold by finite element method was developed and validated by temperature measurement. The multi-gradient operation was novelly designed, and the tailored cooling rate in range of 0.1–10 °C/s was obtained at the target location. The simulation aided experiment with the large-sized samples was carried out, and the local cooling rate was verified by secondary dendrite arm spacing. The size of austenite grain decreases slightly as cooling rate increases from 0.15 °C/s to 0.31 °C/s, and then increases dramatically in the range of 0.31–0.48 °C/s, finally decreases with cooling rate increasing further to 9.76 °C/s. The relationship between austenite grain size and cooling rate was logarithmically regressed in the range of 0.48–9.76 °C/s, in which the kinetic equations on basis of cooling experiment and continuously cast slab can also work. However, the grain size decrease in 0.15–0.31 °C/s and then increase in 0.31–0.48 °C/s cannot be described. Based on the mechanism of peritectic solidification, the austenite grain growth is mainly controlled by diffusion at a low cooling rate smaller than 0.31 °C/s, and the final grain size is less than 1.0 mm. At a medium cooling rate between 0.48 and 3.60 °C/s, austenite grain growth is accelerated by the energy stored during massive type peritectic transformation previously, and the grain size is between 1.7 and 2.9 mm. At high cooling rate larger than 9.76 °C/s, austenite grains grow to about 0.9 mm in columnar shape. The time for grain growth is not adequate, although addition energy storage by massive transformation can also occur. The critical cooling rate for the onset of massive type peritectic transformation in the large-sized sample is between 0.31 and 0.48 °C/s. The growth velocity in the isothermal experiment is much smaller than that in continuous cooling process, confirming that the austenite grain evolution is significantly affected by previous peritectic solidification.

Model development and heat transfer characteristics in renewable energy systems conveying hybrid nanofluids subject to nonlinear thermal radiation

PurposeIn today’s world, the demand for energy to power industrial and domestic activities is increasing. To meet this need and enhance thermal transport, solar energy conservation can be tapped into via solar collector coating for thermal productivity. Hybrid nanofluids (HNFs), which combine nanoparticles with conventional heat transfer fluids, offer promising opportunities for improving the efficiency and sustainability of renewable energy systems. Thus, this paper explores fluid modeling application techniques to analyze and optimize heat transfer enhancement using HNFs. A model comprising solar energy radiation with nanoparticles of copper (Cu) and alumina oxide (Al2O3) suspended in water (H2O) over an extending material device is developed.Design/methodology/approachThe model is formulated using conservation laws to build relevant equations, which are then solved using the Galerkin numerical technique simulated via Maple software. The computational results are displayed in various graphs and tables to showcase the heat transfer mechanism in the system.FindingsThe results reveal the thermal-radiation-boost heat transfer phenomenon in the system. The simulations of the theoretical fluid models can help researchers understand how HNFs facilitate heat transfer in renewable energy systems.Originality/valueThe originality of this study is in exploring the heat transfer properties within renewable energy systems using HNFs under the influence of nonlinear thermal radiation.

Comparative Study of Temperature and Pressure Variation Patterns in Hydrogen and Natural Gas Storage in Salt Cavern

Clarifying the distribution of temperature and pressure in the wellbore and cavern during hydrogen injection and extraction is crucial for quantitatively assessing cavern stability and wellbore integrity. This paper establishes an integrated flow and heat transfer model for the cavern and wellbore during hydrogen injection and withdrawal, analyzing the variations in temperature and pressure in both the wellbore and the cavern. The temperature and pressure parameters of hydrogen and natural gas within the chamber and wellbore were compared. The specific conclusions are as follows. (1) Under identical injection and withdrawal conditions, the temperature of hydrogen in the chamber was 10 °C higher than that of natural gas, and 16 °C higher in the wellbore. The pressure of hydrogen in the chamber was 2.9 MPa greater than that of natural gas, and 2.6 MPa higher in the wellbore. (2) A comparative analysis was conducted on the impact of surrounding rock’s horizontal and numerical distance on temperature during hydrogen and natural gas injection processes. As the distance from the cavity increases, from 5 to 15 m, the temperature fluctuation in the surrounding rock diminishes progressively, with the temperature effect in the hydrogen storage chamber extending to at least 10 m. (3) The influence of rock thermal conductivity parameters on temperature during the processes of hydrogen injection and natural gas extraction is also compared. The better the thermal conductivity, the deeper the thermal effects penetrate the rock layers, with the specific heat capacity having the most significant impact.

Temperature prediction of geothermal drilling considering the drilling fluid thermophysical parameters

An increasing number of geothermal wells are being drilled to meet the growing demand for geothermal energy. Given that the harsh environment of geothermal wells exposes drill-following tools to the risk of high-temperature failure, scholars have developed thermo-mathematical models to predict the temperature field distribution in wellbore. To the best of authors' knowledge, most models ignore the interaction between the fluid thermophysical parameters and its temperature. They also overlook the fact that the actual structure of the drilling column causes changes in the convective heat transfer coefficients between the fluid and the well wall, which subsequently affects heat transfer from the wellbore. In this study, we tested the changes of thermal property parameters of drilling fluid with density and temperature. Based on the actual drill string structure and considering the variation in thermophysical parameters during drilling fluids’ circulation, we innovatively established a transient heat transfer model for geothermal horizontal wells with heat–fluid–solid coupling. Subsequently, a drilled geothermal well was used to simulate the temperature during drilling. The effects of the drilling fluid system, density, and displacement, rotary speed, and WOB during drilling on the wellbore temperature distribution were analyzed. Furthermore, suggestions for the selection of drilling fluid and parameters during the drilling process were given. The results of this study can help accurately predict the wellbore temperature of geothermal wells and high-temperature wells, which provides guidance for the rational selection of drilling tools for drilling operations.

Thermal characteristics analysis and cooling model optimization of motorized spindle

Aiming at the influence of poor cooling conditions and traditional cooling control strategy on motorized spindle temperature and machining performance. Firstly, the heat transfer model of the motorized spindle cooling system is studied. Secondly, the influence of coolant inlet flow rate and temperature on the thermal characteristics of the motorized spindle is studied. Then, a thermal network model is established to solve the temperature of each temperature measuring point. Finally, the thermal characteristic experiment of the motorized spindle is carried out, and the cooling fluid flow optimization model is established based on the particle swarm optimization algorithm and simulated annealing algorithm. The results show that the temperature difference of the motorized spindle does not exceed 45 °C, the thermal deformation does not exceed 40.2 μm, and the thermal elongation is inhibited by 36 %. The maximum error of the Thermal Network Method and Finite Element Method（FEM）is 14.24 %. The utilization of the average logarithmic temperature difference for assessing the cooling effectiveness of optimal flow rates revealed that the particle swarm optimization algorithm demonstrates a comparatively lower average logarithmic temperature difference in comparison to the simulated annealing algorithm. The heat exchange efficiency of the motorized spindle is higher under the optimal flow rate obtained by the particle swarm algorithm.

Longitudinal dispersivity estimation according to heat and mass groundwater transport model calibration for Baikalsk paper and mill site

The paper presents the results of the numerical three-dimensional model of groundwater heat and mass transfer in the territory of Baikalsk paper and mill site calibration based on the materials of groundwater composition and properties twenty-year monitoring, which showed that the longitudinal dispersion at heat transfer is an order of magnitude greater than at mass transfer.

Theoretical investigation of new composite based on metamaterial able to strongly attenuate heat and noise propagation for civil engineering

New design in civil engineering need reduction of cost of material. Engineers and researcher are focused on material parameter to improve proposed alternatives. In this work we are developed theoretical tool based on finite element method to evaluate transmission noise and heat transfer along composite wall for civil engineering. In this work, composite based metamaterial is used for wall elaboration. At first Time noise level in broad band high frequency level was extracted using frequency acoustic finite element method, and using advection, diffusion model heat transfer distribution was also extracted. Finally, combination of constitutive model with metaheuristic optimization enabled us optimal parameters of the material composite, for specific condition. Constitutive resulted and discussion will have detailed in the paper. Keywords: frequency acoustic analysis, advection diffusion, genetic algorithm, civil engineering, material science, metamaterial

Prediction of Evaporation Temperature in Air-Water Heat Source Heat Pump Based on Artificial Neural Network

To improve the low-temperature heating stability and performance of the air-source heat pump (ASHP), a heat transfer model was established for an air-water heat source heat pump(A-WSHP) in this study. Key factors affecting A-WSHP evaporating temperature were analyzed through simulation. An artificial neural network (ANN) prediction model for refrigerant evaporating temperature was developed using fin pitch, air velocity, air temperature, spray flow rate, spray water temperature, and droplet diameter as inputs. In the winter climate of Xiangtan City, this model predicts the refrigerant evaporating temperature and regulates it by adjusting various input parameters. Results indicate that fin pitch and droplet size significantly impact the refrigerant evaporating temperature, more so than fin thickness. The air temperature (34.78%) and spray water temperature (38.02%) have the highest weights, while fin thickness has the least influence, with a weight of 0.75%. The R2 value of the ANN refrigerant evaporating temperature prediction model is 0.974, indicating a good fit. By properly adjusting the heat pump fan and spray valve, changes in air velocity and spray flow rate can enhance the refrigerant evaporating temperature, leading to stable and efficient heat pump operation. This research not only provides a theoretical basis for the operational strategy of air-water heat pumps but also offers guidance for frost-free operation in low-temperature environments.

Non-isothermal simulation of wormhole propagation in fractured carbonate rocks based on 3D-EDFM

The current models of fractured carbonate acidizing are limited to 2D simulation or are solely applicable to the acidizing process in porous media with few fractures, neglecting the acid flow between intersecting fractures. In response to these issues, a coupled 3D thermal-hydro-chemical 3D-EDFM method is developed to simulate the acidizing process in fractured carbonate rock. The fractured carbonate acidizing model is coupled by 3D-EDFM, the two-scale continuum model and the heat transfer model in this paper. Numerical simulations of acidizing under different temperatures are performed, and the simulation results are consistent with previous experimental findings, thus verifying the accuracy of the model. Through simulations, we found that as the flow rate increases, the fracture plane transitions from acting as a “dissolution object of acid” to serving as a “transport channel of acid”. The density and inclination angle of the fracture plane significantly affect the wormholes propagation. The presence of fracture planes accelerates the pressure drop during acidizing and complicates the distribution of the acid-rock reaction heat. Unlike in the 2D model, we observe that when cold acid is injected into high-temperature fractured carbonate rock, the acid cools the rock from the inside out. Although higher rock temperatures lead to an increase in , the difference in the optimum injection rate remains minimal. Compared to porous media without fracture planes, the fracture plane increases the optimum injection rate, and appropriately increasing the injection rate can more effectively utilize the transport characteristics of natural fractures.

Three-dimensional analysis of multiple inclined borehole heat exchangers

This research develops and applies a numerical modelling method for inclined borehole heat exchangers (BHE) in ground-source heat pump systems. Inclined BHEs have the advantage of reducing the ground-level footprint of the overall BHE field. Computational modelling of the ground heat transfer using the commercial code COMSOL Multiphysics has revealed that inclined BHEs offer additional performance benefits compared to vertical BHE fields. When heat is injected constantly, both types of fields perform similarly at first, but over a longer period of time, the inclined BHE fields show significant benefits due to the increased ground volume in the deeper portion of the field. Similar conclusions are reached when transient loading conditions are considered. Notably, when cooling dominates, inclined BHE fields outperform vertical ones for a simulated period of 10 years. This indicates that inclined BHE fields are better equipped to handle imbalanced energy loads. To summarize, inclined BHE fields offer advantages in ground-volume utilization and resilience to energy load imbalances compared to vertical fields.

Improving heat transfer prediction across catalytic SiC interface through a multiscale framework leveraging machine learning and data fusion techniques

Accurate aerothermal prediction under hypersonic flow conditions is crucial for any thermal protection materials design and engineering. The surface catalytic effect, where dissociated atoms recombine into their molecular forms at the air-solid interface, is an exothermic reaction and plays an important role in high-enthalpy aerodynamic environment prediction. Taking SiC, a widely recognized high-temperature thermal protection material as an example, a multiscale fusion approach for aerothermal prediction is proposed. The approach utilizes reactive molecular dynamics method to construct an interface catalysis model, and the Bayesian maximum entropy to integrate experimental and simulational data into an optimized database. Subsequently, using the radial basis function neural network algorithm, a machine learning-based reaction kinetics model with precise analysis of surface catalysis is trained. The obtained catalytic recombination efficiency is used as a boundary input for computational fluid dynamics simulation, enabling rapid and accurate prediction of hypersonic thermal environment. The result shows that the predicted surface heat flux by this novel approach is consistent with the benchmark studies, but comes with significantly reduced computation time. The stagantion heat flux predictions based on the assumptions of full catalytic wall, finite rate catalytic wall (from the proposed multiscale fusion method), and non-catalytic wall are determined to be 8.65×106 W/m2, 7.51×106 W/m2, and 4.02×106 W/m2, respectively. Comparing these with the wind tunnel benchmark value of 7.48×106 W/m2, the error from the proposed multiscale fusion method is 0.30 %, indicating significant enhancement in prediction accuracy through the proposed upscaling method. The new approach could not only reveal complex exothermic reaction processes at the interface, but also enhance the prediction accuracy at much higher computational efficiency, providing an alternative for multiscale modeling of complex flow and heat transfer at the interface.

Thermal analysis of mathematical model of heat and mass transfer through bioconvective Carreau nanofluid flow over an inclined stretchable cylinder

In this proceeding the main focus to scrutinize the heat and mass transfer rate increment due to the involvement of motile microorganisms in the Carreau nanofluid flow through an inclined stretchable cylinder under the consequences of activation energy and thermal radiation. This phenomenon has many physical applications in the field of civil, mechanical and seismographic engineering. The research focuses on creating and analyzing new nanocomposites with applications in energy storage, showcasing the transformative impact of nanotechnology on the advancement of high-performance materials. First of all, for the numerical treatment of the above physical model mathematical model is developed in the form of partial differential equations (PDE's) by considering all involving quantities. The resultant model is highly nonlinear and of higher order. Appropriate similarity variables are defined to transform this system of PDE's into first order ordinary differential equations (ODE's). For numerical results we develop a numerical algorithm from nonlinear ODE's and use ‘bvp4c’ built in package of MATLAB. Numerical results are acquired from software in the form of graphical visuals and tabular data as narrated in the results and discussion section. Using this tabular data streamlines are constructed for the better understanding of heat and mass transfer through this phenomenon under the defined constraints. From results, velocity profile increased by the augmentation of values of curvature parameter. Thermal profile is stronger when values of thermophoresis parameter is boosted, Concentration of nanoparticle profile get smoother when temperature coefficient increased, and motile microorganism's density profile is enlarged upon inclining the values of bioconvection lewis number.

Analytical modelling of transient conduction heat transfer in tubes for industrial applications

Analytical modelling of transient conduction heat transfer in tubes for industrial applications

The potential of integrating solar-powered membrane distillation with a humidification-dehumidification system to recover potable water from textile wastewater

Textile production is energy- and water-intensive, and membrane distillation (MD) has shown potential for reclaiming potable water from textile wastewater. However, in the current state, the energy and water recovery potential of MD is lower compared to other conventional distillation technologies. To address these issues, this study proposes and assesses a novel solar-powered hybrid Sweeping Gas MD (SGMD) unit integrated with a humidification dehumidification (HDH) system. Real textile wastewater from bleaching and dyeing processes is treated in the hybrid SGMD-HDH system to recover freshwater. An optical-thermal sub-model for the parabolic trough collector and the heat and mass transfer model for the dehumidifier are developed and validated using experimental measurements. The results reveal that the hybrid SGMD-HDH can exhibit nearly 20% higher water flux and 50% higher gain output ratio (GOR) compared to the standalone MD system. The highest water production and average GOR for bleaching wastewater feed solution reached 11.72 kg/day and 0.64, respectively. The higher concentration of chemical contaminants in dyeing wastewater decreased water flux and GOR by up to 14% and 10%, respectively, compared to bleaching wastewater. Elemental analysis showed increased carbon concentrations on the polytetrafluoroethylene membrane surface arising from organic fouling.

Analysis of flow boiling incipience models in computational fluid dynamics

Recent advances in the computational fluid dynamics and heat transfer (CFD/HT) modeling of flow boiling have enabled a more detailed analysis and understanding of thermal management in relatively complex microsystems. Most advanced modeling approaches allow the transient analysis of two-phase flow and phase-change processes, providing the capability to post-process in detail the temperature, phase and pressure distributions in microscale applications with the use of moderate computational resources. Although these models have significantly evolved in recent years, there are still several idealizations and assumptions that have yet to be improved or better justified, the boiling incipience treatment being a commonly questioned topic. In the present investigation, a boiling incipience model is incorporated into an existing CFD/HT model for the analysis of flow boiling mechanisms, where the superheat temperature is derived from fundamental thermodynamic relations and compared to the original CFD/HT model that does not account for such effects. Results are compared using a non-trivial case of a silicon micro-cooling layer with variable density of pin fins that has been demonstrated to be an efficient thermal control device in high-power applications. The dielectric fluid HFE-7200 is used as the coolant in flow boiling conditions. The two-phase flow regimes and heat transfer results for both models are compared.

Operation prediction of open sun drying based on mathematical-physical model, drying kinetics and machine learning

In order to determine the moisture ratio of dried material whether the storage requirements are met, it was crucial to find an accurate prediction and convenient method in the open sun drying process. Therefore, the mathematical-physical model, drying dynamics model and machine learning methods were employed and compared in this study. The machine learning methods were first applied to predict the moisture ratio change of sweet potato during open sun drying. A large number of sweet potatoes drying experiments were carried out under open sun drying for theoretical analysis. The results shown that the drying kinetic model of sweet potato was also different under different drying climate conditions. The heat and mass transfer model of sweet potato was established and validated with R2 0.8990 and RMSE 0.0826. Different optimal machine learning prediction methods have be selected based on statistical metrics. Finaly, the machine learning prediction method was considered to be superior to the mathematical-physical model and the drying kinetic model in predicting moisture ratio. The results of this study can be analogized to drying process control of other agricultural products in the future.

Metamaterial-Based Radar-Infrared Camouflage Material for Building Insulation: Design and Performance Analysis

This study introduces a metamaterial microwave absorber (MMA)-lightweight envelope (LE), which is an innovative solution for integrating electromagnetic and infrared-compatible camouflage technologies into building structures. Specifically, MMA-LE incorporates a MMA into building designs for microwave/infrared-compatible camouflage. This study evaluated the microwave absorption performance, infrared camouflage capabilities, and energy-saving effects of MMA-LEs by analyzing the microwave absorption characteristics using the impedance matching theory and simulation software. A coupled heat and moisture transfer model was used to assess isothermal moisture absorption, heat transfer coefficients, and annual heating/cooling loads. Furthermore, infrared imaging tests verified the effectiveness of the camouflage. Two MMA-LE designs (single and double absorber layers) achieve over 90% microwave absorption in the 3.2–11.2 GHz and 1.85–12.67 GHz frequency ranges with relative bandwidths of 111.1% and 149%, respectively, and with polarization insensitivity. Moreover, the MMA-LE enhanced the wall heat and moisture transfer performance, reduced the relative humidity, and reduced the thermal load under Guangzhou's climate conditions. However, despite the improved moisture resistance, the double-layer MMA-LE increased the envelope moisture content, thus reducing thermal insulation. In addition, the limited absorbency of the substrate material results in a modest increase in the dielectric constant, consequently decreasing the resonant frequency of the hybrid structure compared to dry samples. Nevertheless, the thermal insulation properties of MMA-LEs effectively insulate the internal heat sources, achieving optimal infrared camouflage. In conclusion, this study provides a novel solution for microwave-infrared-compatible camouflage in building applications, offering significant theoretical and practical value.

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.

Simulating conjugate heat and mass transfer by the advanced perforated wall model for effusion cooling

Full-scale Computational Fluid Dynamics (CFD) numerical simulations can accurately predict the heat flux and metal wall temperature of gas turbine combustor liners, but they require considerable computational resources. In present work, an Advanced Perforated Wall model (A-PWM) has been developed to resolve the flow and heat transfer behaviors in this confined region. The geometric structure of the effusion cooling perforated plate is simplified, while the fluid-solid coupling heat transfer processes are still fully considered in details. The three-dimensional Reynolds Average Navier–Stokes simulations have been carried out for both a single-hole cooling plate and a multi-hole perforated cooling plate by using A-PWM. For simulations of the single-hole cooling plate, the cooling effectiveness in the downstream of the jet flow with the x/D ranging from 2 to 8 predicted by A-PWM shows good agreement with conjugate heat transfer model and experimental results. For multi-hole perforated cooling plate, the differences of cooling effectiveness between the prediction results by A-PWM and experimental results are just within 5%, confirming the developed model’s accuracy in predicting the effusion cooling. In addition, the A-PWM can also be employed to analyze the temperature distribution inside the solid zone. In simulations of both the single-hole cooling plate and the multi-hole perforated cooling plate, the use of the A-PWM model can lead to a reduction of over 35% in grid count compared to the conjugate heat transfer model, significantly reducing the computational time.