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1 – 7 of 7Dongju Chen, Yupeng Zhao, Kun Sun, Ri Pan and Jinwei Fan
To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus…
Abstract
Purpose
To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus on the impact of graphene nano-lubricating oil hydrostatic bearing temperature rise at various speeds and eccentricities.
Design/methodology/approach
The thermal conductivity of graphene nano-lubricating oil was calculated by molecular dynamics method and based on the viscosity–temperature effect, the coupled heat transfer finite element model of hydrostatic bearing was established; temperature rise of pure lubricating oil and graphene nano-lubricating oil hydrostatic bearing were analysed at different speed and eccentricity based on computational fluid dynamics method.
Findings
With the increase of speed and eccentricity, the temperature rise of 0.2% graphene nano-lubricating oil bearings is lower than that of pure lubricating oil bearings; in addition with the increase of graphene mass fraction, the temperature rise of graphene nano-lubricating oil bearings is always higher than that of pure lubricating oil bearings, and the higher the speed, the more obvious the phenomenon.
Originality/value
The effects of graphene as a lubricant additive on the thermal conductivity of nano-lubricating oil and the variation of the temperature rise of graphene nano-lubricating oil bearings compared to pure lubricating oil bearings were analysed by combining micro and macro methods.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0388
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Vishal Singh and Arvind K. Rajput
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal…
Abstract
Purpose
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal bearing (MHJB) system.
Design/methodology/approach
To simulate the behaviour of PVP lubricant in clearance space of the MHJB system, the modified form of Reynolds equation is numerically solved by using finite element method. Galerkin’s method is used to obtain the weak form of the governing equation. The system equation is solved by Gauss–Seidal iterative method to compute the unknown values of nodal oil film pressure. Subsequently, performance characteristics of bearing system are computed.
Findings
The simulated results reveal that the location of pressurised lubricant inlets significantly affects the oil film pressure distribution and may cause a significant effect on the characteristics of bearing system. Further, the use of PVP lubricant may significantly enhances the performance of the bearing system, namely.
Originality/value
The present work examines the influence of pocket orientation with respect to loading direction on the characteristics of PVP fluid lubricated MHJB system and provides vital information regarding the design of journal bearing system.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0241/
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Xiaodong Yu, Guangqiang Shi, Hui Jiang, Ruichun Dai, Wentao Jia, Xinyi Yang and Weicheng Gao
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…
Abstract
Purpose
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.
Design/methodology/approach
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).
Findings
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.
Originality/value
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.
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Qingyang Wang, Weifeng Wu, Ping Zhang, Chengqiang Guo and Yifan Yang
To guide the stable radius clearance choice of water-lubricated bearings for single screw compressors, this paper aims to analyze the effects of turbulence and cavitation on…
Abstract
Purpose
To guide the stable radius clearance choice of water-lubricated bearings for single screw compressors, this paper aims to analyze the effects of turbulence and cavitation on bearing performance under two conditions of specified external load and radius clearance.
Design/methodology/approach
A modified Reynolds equation considering turbulence and cavitation is adopted, based on the Jakobsson–Floberg–Olsson boundary condition, Ng–Pan model and turbulent factors. The equation is solved using the finite difference method and successive over-relaxation method to investigate the bearing performance.
Findings
The turbulent effect can increase the hydrodynamic pressure and cavitation. In addition, the turbulent effect can lead to an increase in the equilibrium radius clearance. The turbulent region exhibits a higher load capacity and cavitation rate. However, the increased cavitation negatively impacts the frictional coefficient and end flow rate. The impact of turbulence increases as the radius clearance decreases. As the rotating speed increases, the turbulence effect has a greater impact on the bearing characteristics.
Originality/value
The research can provide theoretical support for the design of water-lubricated journal bearings used in high-speed water-lubricated single screw compressors.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0029/
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Aying Zhang, Ziyu Xing and Haibao Lu
The purpose of this paper is to study the mechanochemical effect and self-growth mechanism of double-network (DN) gel and to provide a quasiperiodic model for rubber elasticity.
Abstract
Purpose
The purpose of this paper is to study the mechanochemical effect and self-growth mechanism of double-network (DN) gel and to provide a quasiperiodic model for rubber elasticity.
Design/methodology/approach
The chemical reaction kinetics is used to identify the mechanochemical transition probability of host brittle network and to explore the mechanical behavior of endosymbiont ductile network. A quasiperiodic model is proposed to characterize the cooperative coupling of host–endosymbiont networks using the Penrose tiling of a 2 × 2 matrix. Moreover, a free-energy model is formulated to explore the constitutive stress–strain relationship for the DN gel based on the rubber elasticity theory and Gent model.
Findings
In this study, a quasiperiodic graph model has been developed to describe the cooperative interaction between brittle and ductile networks, which undergo the mechanochemical coupling and mechanical stretching behaviors, respectively. The quasiperiodic Penrose tiling determines the mechanochemistry and self-growth effect of DNs.
Originality/value
It is expected to formulate a quasiperiodic graph model of host–guest interaction between two networks to explore the working principle of mechanical and self-growing behavior in DN hydrogels, undergoing complex mechanochemical effect. The effectiveness of the proposed model is verified using both finite element analysis and experimental results of DN gels reported in literature.
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Kunpeng Shi, Guodong Jin, Weichao Yan and Huilin Xing
Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel…
Abstract
Purpose
Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.
Design/methodology/approach
A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.
Findings
The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R2) is 0.93 for the validation set, and the R2 for the test set A and test set B are 0.93 and 0.94, respectively.
Originality/value
This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.
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Vaishnavi Pandey, Anirbid Sircar, Kriti Yadav and Namrata Bist
This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to…
Abstract
Purpose
This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.
Design/methodology/approach
This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.
Findings
The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.
Research limitations/implications
If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.
Practical implications
The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.
Originality/value
The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.
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