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The purpose of this study is analysis of deformation and vibrations of turbine blades produced by high electrolyte pressure during electrochemical machining.

An experimental setup was designed, experiments were conducted and the obtained results were compared with the finite element results. The deformations were measured according to various flow rates of electrolyte. In finite element calculations, the pressure distribution created by the electrolyte on the blade surface was obtained in the ANSYS® (A finite element analysis software) Fluent software and transferred to the static structural where the deformation analysis was carried out. Three different parameters were examined, namely blade thickness, blade material and electrolyte pressure on blade disk caused by mass flow rate. The deformation results were compared with the gap distances between cathode and anode.

Large deformations were obtained at the free end of the blade and the most curved part of it. The appropriate pressure values for the electrolyte to be used in the production of blisk blades were proposed numerically. It has been determined that high pressure applications are not suitable for gap distance lower than 0.5 mm.

When the literature is examined, it is required that the high speed flow of the electrolyte is desired in order to remove the parts that are separated from the anode from the machining area during electrochemical machining. However, the electrolyte flowing at high speeds causes high pressure in the blisk blades, excessive deformation and vibration of the machined part, and as a result, contact of the anode with the cathode. This study provides important findings for smooth electro chemical machining at high electrolyte flows.

The purpose of this paper is to introduce the simple synthesis process of thermal-insulation coating by using three different nanoparticles, namely, nano-zinc oxide (ZnO), nano-tin dioxide (SnO₂) and nano-titanium dioxide (TiO₂), which can reduce the temperature of solar cells.

The thermal-insulation coating is designed using sol-gel process. The aminopropyltriethoxysilane/methyltrimethoxysilane binder system improves the cross-linking between the hydroxyl groups, -OH of nanoparticles. The isopropyl alcohol is used as a solvent medium. The fabrication method is a dip-coating method.

The prepared S1B1 coating (20 Wt.% of SnO₂) exhibits high transparency and great thermal insulation property where the surface temperature of solar cells has been reduced by 13°C under 1,000 W/m² irradiation after 1 h. Meanwhile, the Z1B2 coating (20 Wt.% of ZnO) reduced the temperature of solar cells by 7°C. On the other hand, the embedded nanoparticles have improved the fill factor of solar cells by 0.2 or 33.33%.

Findings provide a significant method for the development of thermal-insulation coating by a simple synthesis process and low-cost materials.

The thermal-insulation coating is proposed to prevent exterior heat energy to the inside solar panel glass. At the same time, it can prevent excessive heating on the solar cell’s surface, later improves the efficiency of solar cell.

This study presents a the novel method to develop and compare the thermal-insulation coating by using various nanoparticles, namely, nano-TiO₂, nano-SnO₂ and nano-ZnO at different weight percentage.

This paper aims to study the influence of cylindrical texture parameters on the lubrication performance of static and dynamic pressure thrust bearings (hereinafter referred to as thrust bearings) and to optimize their lubrication performance using multiobjective optimization.

The influence of texture parameters on the lubrication performance of thrust bearings was studied based on the modified Reynolds equation. The objective functions are predicted through the BP neural network, and the texture parameters were optimized using the improved multiobjective ant lion algorithm (MOALA).

Compared with smooth surface, the introduction of texture can improve the lubrication properties. Under the optimization of the improved algorithm, when the texture diameter, depth, spacing and number are approximately 0.2 mm, 0.5 mm, 5 mm and 34, respectively, the loading capacity is increased by around 27.7% and the temperature is reduced by around 1.55°C.

This paper studies the effect of texture parameters on the lubrication properties of thrust bearings based on the modified Reynolds equation and performs multiobjective optimization through an improved MOALA.

The concept of sustainable product design (SPD) is gaining significant attention in recent research. However, due to inherent uncertainties associated with new product development and incorporation of multiple qualitative and quantitative criteria; SPD is a complex and challenging task. The purpose of this paper is to introduce a novel approach by integrating quality function deployment (QFD), multi-criteria decision making (MCDM) technique and Six Sigma evaluation for facilitating SPD in the context of Industry 4.0.

The customer requirements are evaluated through the neutrosophic-decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP)-based approach followed by utilizing QFD matrix to estimate the weights of the engineering characteristics (EC). The Six Sigma method is then employed to evaluate the alternatives’ design based on the ECs’ values.

The effectiveness of the suggested approach is illustrated through an example. The result indicates that utilization of the neutrosophic MCDM technique with integration of Six Sigma methodology provides a simple, effective and computationally inexpensive method for SPD.

The proposed approach is helpful in upstream evaluation of the product design with limited experimental/numerical data, maintaining a strong competitive position in the market and enhancing customer satisfaction.

This work provides a novel approach to objectively quantify performance of SPD under the paradigm of Industry 4.0 using the integration of QFD-based hybrid MCDM with Six Sigma method.

The emergence of the COVID-19 pandemic changed the way in which education was delivered in early 2020, and the impacts of these changes continue to be questionable. The aims of this study were to evaluate: (1) the results obtained by students of the Dentistry course in the progress test carried out both before and after the pandemic, (2) the results obtained by a specific group of students who took the test in 2019–2022, and compare their results and (3) subjects that showed a reduction in the percentage of correct answers when the two tests were compared.

The progress test consisting of 100 multiple choice questions was applied before and after the pandemic to all students in the Dentistry course. The analyses were performed using the IBM SPSS for Statistics v.26 software program. The level of significance of 5% was adopted (<0.05).

The test was applied to 320 students in 2019 and to 272 in 2022, of whom the sample of this study was composed. The mean score values in 2019 (M = 49.10; SD = 12.03) were significantly (p = 0.026) higher than those in the year 2022 (M = 46.97; SD = 12.15), with the disciplines in the area of specific knowledge showing a greater drop in the percentage of correct answers by students. This study showed that the emergency remote education had a negative effect on the academic performance of students, based on the progress testing as an evaluation method.

Many studies that assessed the impacts of the pandemic on teaching were focused on the opinions of students. However, the great advantage of our study was the use of a theoretical assessment tool to verify student performance. The post-pandemic landscape beckons for comprehensive inquiries into these domains. This type of research would be valuable for gathering evidence relative to the performance of students after the emergency remote education.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

The main objective of our study is to shed light on how perceived enjoyment influences the intricate relationship between value cocreation and consumer satisfaction, with a specific focus on the realms of tourist services.

To achieve the objective outlined in this research, an information survey was carried out on 400 consumers of tourist services who have participated in virtual cocreation processes through digital platforms. As a data analysis technique, the dynamic structural equation modeling (DSEM) analyzes the causal relationships between the elements under study.

Our extensive analysis draws upon the data collected through a survey spanning from 2018 to 2023, encompassing 400 participants who actively engaged in value cocreation processes in both physical and virtual settings. Our investigation considers two competing models to elucidate the role of perceived enjoyment. Our findings, established through DSEM illuminates that perceived enjoyment predominantly functions as a mediator, exerting a more pronounced influence on the connection between value cocreation and consumer satisfaction. Contrary to a moderating role, perceived enjoyment emerges as a significant mediator in our study.

The most significant addition is recognizing virtual value cocreation behaviors in tourist sector activities over time, primarily because it indicates the likelihood of negative repercussions of its usage. Furthermore, it must be capable of designing surroundings according to the characteristics of customers in terms of immersion and technology usage, preventing a rise in stress situations that might result in more negative consequences than planned. Another important insight is that virtual value cocreation initiatives have detrimental long-term implications, particularly in tourism.

This study establishes a method for predicting ground vibrations caused by railway tunnels in unsaturated soils with spatial variability.

First, an improved 2.5D finite-element-method-perfect-matching-layer (FEM-PML) model is proposed. The Galerkin method is used to derive the finite element expression in the ub-pl-pg format for unsaturated soil. Unlike the ub-v-w format, which has nine degrees of freedom per node, the ub-pl-pg format has only five degrees of freedom per node; this significantly enhances the calculation efficiency. The stretching function of the PML is adopted to handle the unlimited boundary domain. Additionally, the 2.5D FEM-PML model couples the tunnel, vehicle and track structures. Next, the spatial variability of the soil parameters is simulated by random fields using the Monte Carlo method. By incorporating random fields of soil parameters into the 2.5D FEM-PML model, the effect of soil spatial variability on ground vibrations is demonstrated using a case study.

The spatial variability of the soil parameters primarily affected the vibration acceleration amplitude but had a minor effect on its spatial distribution and attenuation over time. In addition, ground vibration acceleration was more affected by the spatial variability of the soil bulk modulus of compressibility than by that of saturation.

Using the 2.5D FEM-PML model in the ub-pl-pg format of unsaturated soil enhances the computational efficiency. On this basis, with the random fields established by Monte Carlo simulation, the model can calculate the reliability of soil dynamics, which was rarely considered by previous models.

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/

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.