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Despite the reputation of the metal-based porous media for their ability to augment heat transfer as widely witnessed in the literature and practically operating heat exchanging applications, the coexisting penalty of the increased pressure drop demanding increased pumping power poses a major concern that invites the need for an alternate solution to handle this unsought outcome. Therefore, this study aims at providing a better solution to the existing cost and benefit scenarios to benefit a plethora of engineering applications including energy transfer, energy storage and energy conversion.

This work highlights on the property of stacked woven wire mesh porous media such as their stacking types, porous conditions and thickness scenarios that can potentially result in distinct trade-off scenarios. A vertical channel is numerical modelled by using REV scaled modelling technique using Darcy-Forchheimer and local thermal non-equilibrium models to illustrate the possibilities of this variety of trade off scenarios between the desirable heat transfer and the unsought flow resistance.

This work illustrates the advantages of wire mesh-based porous medium and its distinct potential in controlling the existing trade-offs between the cost and benefit aspects. It is found that by varying the features of wire mesh porous media, the interplay between the conflictingly existing characteristics can be much easily handled specific to distinct requirements associated with variety of engineering applications.

The study emphasizes on a new solution or methodology to handle the penalty of pressure drop associated with metal-based porous media. Through this study, a novel approach to control the ultimately costing pumping power at the benefit of increased heat transfer is provided considering various requirements that could be associated with any thermal management systems. Various possibilities and potentials of wire mesh porous media are illustrated highlighting on their benefit of ease with which the mentioned goals can be achieved.

Transient response of continuous composite material (CCM) fin made of high thermally conductive composite material is presented. The continuously varying effective properties of composite material such as thermal conductivity, heat capacity and density have been modelled using the Mori-Tanaka homogenization theory and rule of mixture. Additionally, temperature dependency of thermal conductivity, heat generation (composite materials) and convection coefficient (fluid properties) have also been incorporated. Different base boundary conditions are addressed such as oscillating heat flow, oscillating temperature, step-changing heat flow and step-changing temperature. At the other boundary, the fin is assumed to have a convective tip.

Lattice Boltzmann method is implemented using an in-house source code for obtaining the numerical solution of typical non-linear heat balance equation of the aforementioned problem under various transient base boundary conditions.

The effects of various thermal parameters such as material diffusivity ratio and conductivity ratio, area ratio and Biot number on transient response of fin and temperature distribution of fins are studied and interpreted. The heat transfer rate and time for attainment of steady state temperature of metal matrix composite (MMC) fin are found to be proportionally dependent on their diffusivity ratio. Additionally for higher values of area ratio and biot number, MMC fins are reported to dissipate the heat more efficiently in comparision to homogeneous fins in terms of time required to attain the steady state and surface temperature.

Response of transient fin associated with advanced class of material can facilitates the practicing engineers for designing high-performance and/or miniaturized thermal management devices as used in electronic packaging industries.

Studies of composite fin consisting of laminating second layer of material over the first layer have been reported previously, however transient response of CCM fin fabricated by continuously varying the volume fraction of two materials along the fin length has not been reported till date. Such material finds its application in thermal management and electronic packaging industries. Results are plotted in form of a graph for different application-wise material combinations that have not been reported earlier, and it can be treated as design data.

This study aims to study the formation mechanism of micro-arc oxidation (MAO) coating on AZ31 magnesium alloy and how the annealing process affects its corrosion resistance.

This study involved immersion experiments, electrochemical experiments and slow strain rate tensile experiments, along with scanning electron microscopy, optical microscopy observation and X-ray diffraction analysis.

The findings suggest that annealing treatment can refine the grain size of AZ31 magnesium alloy to an average of 6.9 µm at 300°C. The change in grain size leads to a change in conductivity, which affects the performance of MAO coatings. The MAO coating obtained by annealing the substrate at 300°C has smaller pores and porosity, resulting in better adhesion and wear resistance.

The coating acts as a barrier to prevent corrosive substances from entering the substrate. However, the smaller pores and porosity reduce the channels for the corrosive solution to pass through the coating. When the coating cracks or falls off, the corrosive medium and substrate come into direct contact. Smaller and uniform grains have better corrosion resistance.

This study focused on identifying critical factors governing the fire response of prestressed hollow-core slabs. The hollow-core slabs used as flooring units can be subjected to elevated temperatures during a fire. The fire response of prestressed hollow-core slabs is required to develop slabs with greater fire endurance. The present study aims to determine the extent to which the hollow-core slab can sustain load during a fire without undergoing progressive collapse under extreme fire and heating scenarios.

A finite element model was generated to predict the fire response of prestressed hollow core slabs under elevated temperatures. The accuracy of the model was predicted by examining thermal and structural responses through coupled temperature displacement analysis. A sensitivity analysis was performed to study the effects of concrete properties on prediction of system response. A parametric study was conducted by varying the thickness of the slab, fire and heating scenarios.

Thermal conductivity and specific heat of concrete were determined as sensitive parameters. The thickness of the slab was identified as a critical factor at a higher load level. Asymmetric heating of the slab resulted in higher fire resistance compared with symmetric heating.

This is the first study focused on studying the effect of modeling uncertainties on the system response by sensitivity analysis under elevated temperatures. The developed model with a parametric study helps in identifying critical factors for design purposes.

This study aims to understand the influence of raceway surface topography on the temperature rise characteristics of silicon nitride (Si₃N₄) full ceramic ball bearing and improve its service life.

The arithmetic average height S_a, skewness S_sk and kurtosis S_ku in the three-dimensional surface roughness parameters are used to quantitatively characterize the surface topography of the raceway after superfinishing. The bearing life testing machine is used to test the Si₃N₄ full ceramic ball bearing using polytetrafluoroethylene (PTFE) cage under dry friction conditions, and the self-lubricating full ceramic ball bearing heat generation model is established.

With the decrease of S_a and S_sk on the raceway surface and the increase of S_ku, the average height of the raceway surface decreases, and the peaks and valleys tend to be symmetrically distributed on the average surface, and the surface texture becomes tighter. This kind of raceway surface topography is beneficial to form a thin and uniform filamentous PTFE transfer film with a wide coverage area on the raceway surface based on consuming less cage materials and improving the temperature rise characteristics of hot isostatic pressing silicon nitride full ceramic ball bearings.

The research results provide a theoretical basis for the reasonable selection of Si₃N₄ ring raceway processing technology and have important significance for improving the working characteristics and service life of Si₃N₄ full ceramic ball bearings under dry friction conditions.

Two friction models of Fe-Fe and Diamond-like carbon (DLC)-Fe were established by molecular dynamics (MD) method to simulate the friction behavior of traditional fracturing pump plunger and new DLC plunger from atomic scale. This paper aims to investigate the effects of temperature and load on the friction behavior between sealed nitrile butadiene rubber (NBR) and DLC films.

In this study, MD method is used to investigate the friction behavior and mechanism of DLC film on plungers and sealing NBR based on Fe-Fe system and DLC-Fe system.

The results show that the friction coefficient of DLC-Fe system exhibits a downward trend with increasing load and temperature. And even achieve a superlubricity state of 0.005 when the load is 1 GPa. Further research revealed that the low interaction energy between DLC and NBR promoted the proportion of atoms with larger shear strain in NBR matrix and the lower Fe layer in DLC-Fe system to be much lower than that in Fe-Fe system. In addition, the application of DLC film can effectively inhibit the temperature rise of friction interface, but will occur relatively large peak velocity.

In this paper, two MD models were established to simulate the friction behavior between fracturing pump plunger and sealing rubber. Through the analysis of mean square displacement, atomic temperature, velocity and Interaction energy, it can be seen that the application of DLC film has a positive effect on reducing the friction of NBR.

This paper aims to reveal the influence of the grooved texture parameters on the lubrication performance of circular pocket-roller pairs in cylindrical roller bearings.

In this paper, the thermal elastohydrodynamic lubrication mathematical model of the grooved texture circular pocket-roller pair was established, the finite difference method and successive over-relaxation method were used to solve the model, the influence of texture quantity, texture depth and texture area ratio on circumferential bearing capacity, friction coefficient, maximum temperature rise, stiffness and damping of the circular pocket-roller pairs were analyzed.

The results show that texture quantity, texture depth and texture area ratio significantly influence the static and dynamic characteristics of circular pocket-roller pairs. The suitable surface groove texture parameters can dramatically improve the circumferential bearing capacity, reduce the friction coefficient, inhibit the maximum temperature rise and increase the stiffness and damping of the circular pocket-roller pairs.

The research in this paper can provide a theoretical basis for the optimization design of pockets in cylindrical roller bearings to reduce friction and vibration.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

The purpose of this study is to evaluate three types of textures designed to enhance the tribological performance of static and dynamic pressure thrust bearings.

To explore the effects of different types of textures on tribological performance, the Reynolds equation is modified using lubrication theory and computational fluid dynamics methods while considering the influence of cavitation and turbulence on the physical field. In addition, the tribological performance is optimized through an improved selection algorithm based on Pareto envelope (PESA).

The results indicate that textured thrust bearings exhibit superior tribological performance compared to untextured ones. The circular texture outperforms other textures in terms of load-bearing and friction performance, with improvements of approximately 28.8% and 18.9%, respectively. In addition, the triangular texture exhibits the most significant temperature improvement, with a reduction of approximately 1.93%.

The study proposes three types of textures and evaluates the friction performance of thrust bearings by modifying the Reynolds equation. In addition, the optimal texture design is determined using an improved selection algorithm based on PESA.

Regarding the broadening of the titanium alloy application field, the surface treatment coating of TC4 alloy has become an essential global research topic. This study aims to illustrate the titanium-based composite coating is created by laser cladding TC4+Ni60/hBN composite powder onto the surface of the TC4 alloy.

Different laser scanning speeds were initially selected to prepare TC4+Ni60/hBN titanium-based composite coating on the surface of TC4 alloy using RFL-C1000 Raycus fiber laser. Second, the cladding layers with different laser scanning speeds are composed of Ti₂Ni, TiN_0.3, TiC, TiB, α-Ti and other phases. Finally, precision balances, friction and wear testing machines were used to analyze and test the structure, phase, hardness, wear amount and friction coefficient of the composite coating and to study the effect of laser scanning speed on the microstructure and properties of the titanium-based composite coating.

It is evident that at the low laser scanning speed, the reinforcing phase agglomeration area is distributed in the substrate as a network. Increasing the laser scanning speed can reduce the cladding layer's friction coefficient and improve the cladding layer's hardness and wear resistance. But too high a laser scanning speed will cause defects such as pores and cracks in the cladding layer and also affect the cladding layer. The bonding performance of the layer and the substrate is optimal in this research at a laser scanning speed of 10 mm/s.

This research has practical value in improving the quality of surface treatment coating in modern aerospace and automotive companies.