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This paper aims to establish a lattice Boltzmann (LB) method for solid-liquid phase transition (SLPT) from the pore scale to the representative elementary volume (REV) scale. By applying this method, detailed information about heat transfer and phase change processes within the pores can be obtained, while also enabling the calculation of larger-scale SLPT problems, such as shell-and-tube phase change heat storage systems.

Three-dimensional (3D) pore-scale enthalpy-based LB model is developed. The computational input parameters at the REV scale are derived from calculations at the pore scale, ensuring consistency between the two scales. The approaches to reconstruct the 3D porous structure and determine the REV of metal foam were discussed. The implementation of conjugate heat transfer between the solid matrix and the solid−liquid phase change material (SLPCM) for the proposed model is developed. A simple REV-scale LB model under the local thermal nonequilibrium condition is presented. The method of bridging the gap between the pore-scale and REV-scale enthalpy-based LB models by the REV is given.

This coupled method facilitates detailed simulations of flow, heat transfer and phase change within pores. The approach holds promise for multiscale calculations in latent heat storage devices with porous structures. The SLPT of the heat sinks for electronic device thermal control was simulated as a case, demonstrating the efficiency of the present models in designing and optimizing SLPT devices.

A coupled pore-scale and REV-scale LB method as a numerical tool for investigating phase change in porous materials was developed. This innovative approach allows for the capture of details within pores while addressing computations over a large domain. The LB method for simulating SLPT from the pore scale to the REV scale was given. The proposed method addresses the conjugate heat transfer between the SLPCM and the solid matrix in the enthalpy-based LB model.

This study aims to focus on understanding how different jet angles and Reynolds numbers influence the phase change materials’ (PCMs) melting process and their capacity to store energy. This approach is intended to offer novel insights into enhancing thermal energy storage systems, particularly for applications where heat transfer efficiency and energy storage are critical.

The research involved an experimental and numerical analysis of PCM with a melting temperature range of 22 °C–26°C under various conditions. Three different jet angles (45°, 90° and 135°) and two container angles (45° and 90°) were tested. Additionally, two different Reynolds numbers (2,235 and 4,470) were used to explore the effects of jet outlet velocities on PCM melting behaviour. The study used a circular container and analysed the melting process using the hot air inclined jet impingement (HAIJI) method.

The obtained results showed that the average temperature for the last time step at Ф = 90° and Re = 4,470 is 6.26% higher for Ф = 135° and 14.23% higher for Ф = 90° compared with the 45° jet angle. It is also observed that the jet angle, especially for Ф = 90°, is a much more important factor in energy storage than the Reynolds number. In other words, the jet angle can be used as a passive control parameter for energy storage.

This study offers a novel perspective on the effective storage of waste heat transferred with air, such as exhaust gases. It provides valuable insights into the role of jet inclination angles and Reynolds numbers in optimizing the melting and energy storage performance of PCMs, which can be crucial for enhancing the efficiency of thermal energy storage systems.

The purpose of this study is to advance turbulent thermal convection inside the constant heat-flux round tube inserted by multiple perforated twisted tapes.

The novel design of this study is accomplished by inserting several twisted tapes and drilling some circular perforations near the tape edge (C1, C3, C5: solid tapes; C2, C4, C6: perforated tapes). The turbulence flow appearances and thermal convective features are examined for various Reynolds numbers (8,000–14,000) using the renormalization group (RNG) κ−ε turbulent model and Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) algorithm.

The simulated outcomes reveal that inserting more perforated-twisted tapes into the heated round tube promotes turbulent thermal convection effectively. A swirling flow caused by the twisted tapes to produce the secondary flow jets between two reverse-spin tapes can combine with the main flow passing through the perforations at the outer edge to enhance the vortex flow. The primary factors are the quantity of twisted tapes and with/without perforations, as the perforation ratio remains at 2.5 in this numerical work. Weighing friction along the tube, C6 (four reverse-spin perforated-twisted tapes) brings the uppermost thermal-hydraulic performance of 1.23 under Re = 8,000.

The constant thermo-hydraulic attributes of liquid water and the steady Newtonian fluid are research limitations for this simulated work.

The simulated outcomes will avail the inner-pipe design of a heat exchanger inserted by multiple perforated twisted tapes to enhance superior heat transfer.

These twisted tapes form tiny circular perforations along the tape edge to introduce the fluid flow through these bores and combine with the secondary flow induced between two reverse-spin tapes. This scheme enhances the swirling flow, turbulence intensity and fluid mixing to advance thermal convection since larger perforations cannot produce large jet velocity or the position of perforations is too far from the tape edge to generate a separated flow. Consequently, this work contributes a valuable cooling mechanism toward thermal engineering.

The purpose of this study is to analyse the magnetic field effect on Fe₃O₄/H₂O Ferrofluid flowing in a sudden expansion tube, which has specific behaviour in terms of rheology, with convex dimple fins. Because the investigation of flow separation is a prominent application in performance, the effect of magnetic field and convex dimple on the thermo-hydraulic performance of sudden expansion tube are examined, in detail.

During the solution of the boundary conditions of the sudden expansion tube, finite volume method was used. Analyses have been conducted considering the single-phase solution, steady-state, incompressible fluid and no-slip condition of the wall under forced convection conditions. In the analyses, it has been assumed that the flow was developing thermally and has been fully developed hydrodynamically.

The present study focuses on exploring the influence of the magnetic field, nanofluid concentration and convex dimple fins on the thermo-hydraulic performance of sudden expansion tube. The results indicate that the strength of the magnetic field, nanofluid concentration and convex dimple fins have a positive effect on the convective heat transfer in the system.

The authors conducted numerical studies, determining through a literature search that no one had yet investigated enhancing heat transfer on a sudden expansion tube using combinations of magnetic fields, nanofluids and convex dimple fins. The results of the numerical analyses provide valuable information about the improvement of heat transfer and system performance in electronic device cooling and heat exchangers.

To improve the speed and accuracy of turbine blade film cooling design process, the most advanced deep learning models were introduced into this study to investigate the most suitable define for prediction work. This paper aims to create a generative surrogate model that can be applied on multi-objective optimization problems.

The latest backbone in the field of computer vision (Swin-Transformer, 2021) was introduced and improved as the surrogate function for prediction of the multi-physics field distribution (film cooling effectiveness, pressure, density and velocity). The basic samples were generated by Latin hypercube sampling method and the numerical method adopt for the calculation was validated experimentally at first. The training and testing samples were calculated at experimental conditions. At last, the surrogate model predicted results were verified by experiment in a linear cascade.

The results indicated that comparing with the Multi-Scale Pix2Pix Model, the Swin-Transformer U-Net model presented higher accuracy and computing speed on the prediction of contour results. The computation time for each step of the Swin-Transformer U-Net model is one-third of the original model, especially in the case of multi-physics field prediction. The correlation index reached more than 99.2% and the first-order error was lower than 0.3% for multi-physics field. The predictions of the data-driven surrogate model are consistent with the predictions of the computational fluid dynamics results, and both are very close to the experimental results. The application of the Swin-Transformer model on enlarging the different structure samples will reduce the cost of numerical calculations as well as experiments.

The number of U-Net layers and sample scales has a proper relationship according to equation (8). Too many layers of U-Net will lead to unnecessary nonlinear variation, whereas too few layers will lead to insufficient feature extraction. In the case of Swin-Transformer U-Net model, incorrect number of U-Net layer will reduce the prediction accuracy. The multi-scale Pix2Pix model owns higher accuracy in predicting a single physical field, but the calculation speed is too slow. The Swin-Transformer model is fast in prediction and training (nearly three times faster than multi Pix2Pix model), but the predicted contours have more noise. The neural network predicted results and numerical calculations are consistent with the experimental distribution.

This paper creates a generative surrogate model that can be applied on multi-objective optimization problems. The generative adversarial networks using new backbone is chosen to adjust the output from single contour to multi-physics fields, which will generate more results simultaneously than traditional surrogate models and reduce the time-cost. And it is more applicable to multi-objective spatial optimization algorithms. The Swin-Transformer surrogate model is three times faster to computation speed than the Multi Pix2Pix model. In the prediction results of multi-physics fields, the prediction results of the Swin-Transformer model are more accurate.

The purpose of this paper is to investigate the performance of bio-based lubricants (BBL), namely, palm mid-olein (PMO) enriched with an antioxidant agent, tertiary-butylhydroquinone (TBHQ) and a viscosity improver, ethylene-vinyl acetate (EVA), in journal bearing (JB) applications.

Samples of the BBL were prepared by blending it with TBHQ and EVA at various blending ratios. The oxidative stability (OS) and viscosity of the BBL samples were examined using differential scanning calorimetry and a viscometer, respectively. Meanwhile, their performance in JB applications was evaluated through the use of a JB test rig with a 0.5 length-to-diameter ratio at various operating conditions.

It was found that the combination of PMO + TBHQ + EVA demonstrated a superior oil film pressure and load-carrying capacity, resulting in a reduced friction coefficient and a smaller attitude angle compared to the use of only PMO or VG68. However, it was observed that the addition of TBHQ and EVA to the PMO did not have a significant impact on the minimum oil film thickness.

The results would be quite useful for researchers generally and designers of bearings in particular.

This study used PMO as the base stock, and its compatibility with TBHQ and EVA was investigated in terms of its OS and viscosity. The performance of this treated BBL was evaluated in a hydrodynamic JB.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2023-0363/

The purpose of this study was to review the information on the scientific efforts and achievements in sustainable industrial textile applications of natural colourants. Then the paper suggests the ways of improving the industrial textile applications of plant-based colourants.

The literature on the chemistry, sources and extraction of plant-based natural colourants was reviewed. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested. Lastly, the current situation of industrial application of natural dyes in textiles is presented.

Despite the scientific achievement to overcome the challenges of natural colourants for textiles, the global industrial application of natural colourants is still low. Inadequate knowledge of the dyers results into poor performance of the natural dyed textile. The natural dyed textiles are expensive due to the scarcity of raw materials for manufacturing of natural colourants. The selection of suitable extraction, application methods and type of substrate should consider the chemistry of the particular colourant. The society should be educated about the benefits of natural dyed textiles. Cultivation of colourant-bearing plants should be promoted to meet the industrial material demand.

The paper provides a synthesized collection of information about the source, chemistry, extraction, textile application and challenges of plant-based natural colourants. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested.

This study aims to describe the design and synthesis of two novel azo and imine chromophores-based dyes derived from two different aldehydes with intramolecular colour matching that are pH sensitive.

The visible absorption wavelength (λ_max) was extended when azo chromophore was included in imine-based systems. The dyed patterns created sophisticated colour-changing paper packaging sensors with pH-sensitive chromophores using alum as a mediator or mordant. Due to the tight adhesive bonding, the dyes on paper’s cellulose fibres could not be removed by ordinary water even at extremely high or low pH, which was confirmed by scanning electron microscopy analysis. The dyed patterns demonstrated an evident, sensitive and fast colour-changing mechanism with varying pH, from pale yellow to red for Dye-I and from pale yellow to brown-violet for Dye-II.

The λ_max for colour changing was recorded from 400 to 490 nm for Dye-I, whereas from 400 to 520 for Dye-II. The freshness judgement of food was checked using actual experiments with cooked crab spoilage, where the cooked crab was incubated at 37 ^oC for 6 h to see the noticeable colour change from yellow to brown-violet with Dye-II. The colour-changing mechanism was studied with Fourier transform infrared (FTIR) spectra at different pH, and thin layer chromatography, nuclear magnetic resonance and FTIR spectroscopy studied the desired structure formation of the dyes. Potential uses for smart packaging sensors include quickly detecting food freshness during transportation or right before consumption.

1. Two novel azo-imine dyes have been synthesized with a pH-responsive effect. 2. The pH-responsive mechanism was studied. 3. The study was supported by computational chemistry using density functional theory. 4. The obtained dyes were used to make pH-responsive sensors for seafood packaging to judge the freshness.

This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.

This study aims to develop a green, economical and efficient ultrasonic-/microwave assisted extraction (UMAE) process for the extraction of anthocyanins.

After optimizing the extraction conditions by response surface methodology, three assays including DPPH, ABTS·+, FRAP were applied to analyze the antioxidant activity of the extracted anthocyanins. The stability under different temperatures, reductant concentrations and pHs was also discussed. The components of anthocyanins in blueberry were analyzed by HPLC-QTOF-MS2.

The optimal extraction parameters were ultrasonic power of 300 W, microwave power of 365.28 W and solid–liquid ratio of 30 (g/mL). The possible structures can be speculated as Delphinidin-3-O-galactoside, Delphinidin, Petunidin, Delphinidin-3-O-glucoside, Petunidin-3-O-glucoside, Cyanidin-3-O-glucoside. The results demonstrated that the UMAE can improve the yield of anthocyanins in shorter extraction time with higher activity.

The present study may provide a promising and feasible route for extracting anthocyanins from blueberries and studying their physicochemical properties, ultimately promoting the utilization of blueberry anthocyanins.