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This study aims to propose and numerically assess different ways of discretising a very weak formulation of the Poisson problem.

We use integration by parts twice to shift smoothness requirements to the test functions, thereby allowing low-regularity data and solutions.

Various conforming discretisations are presented and tested, with numerical results indicating good accuracy and stability in different types of problems.

This is one of the first articles to propose and test concrete discretisations for very weak variational formulations in primal form. The numerical results, which include a problem based on real MRI data, indicate the potential of very weak finite element methods for tackling problems with low regularity.

The purpose of this study is to adapt the incompressible smoothed particle hydrodynamics (ISPH) method with artificial intelligence to manage the physical problem of double diffusion inside a porous L-shaped cavity including two fins.

The ISPH method solves the nondimensional governing equations of a physical model. The ISPH simulations are attained at different Frank–Kamenetskii number, Darcy number, coupled Soret/Dufour numbers, coupled Cattaneo–Christov heat/mass fluxes, thermal radiation parameter and nanoparticle parameter. An artificial neural network (ANN) is developed using a total of 243 data sets. The data set is optimized as 171 of the data sets were used for training the model, 36 for validation and 36 for the testing phase. The network model was trained using the Levenberg–Marquardt training algorithm.

The resulting simulations show how thermal radiation declines the temperature distribution and changes the contour of a heat capacity ratio. The temperature distribution is improved, and the velocity field is decreased by 36.77% when the coupled heat Cattaneo–Christov heat/mass fluxes are increased from 0 to 0.8. The temperature distribution is supported, and the concentration distribution is declined by an increase in Soret–Dufour numbers. A rise in Soret–Dufour numbers corresponds to a decreasing velocity field. The Frank–Kamenetskii number is useful for enhancing the velocity field and temperature distribution. A reduction in Darcy number causes a high porous struggle, which reduces nanofluid velocity and improves temperature and concentration distribution. An increase in nanoparticle concentration causes a high fluid suspension viscosity, which reduces the suspension’s velocity. With the help of the ANN, the obtained model accurately predicts the values of the Nusselt and Sherwood numbers.

A novel integration between the ISPH method and the ANN is adapted to handle the heat and mass transfer within a new L-shaped geometry with fins in the presence of several physical effects.

As the crucial support component of the propeller power system, the reliability of the operation of submersible pumps is influenced by the lubrication performance of water-lubricated thrust bearings. When the water-lubricated thrust bearings are under start-stop or heavy load conditions, the effect of surface morphology is crucial as the mixed lubrication regime is encountered. This paper aims to develop one mixed lubrication model for the water-lubricated thrust bearings to predict the effects of surface skewness, kurtosis and roughness orientation on the loading carrying capacity and tribological behavior.

This paper developed one improved mixed lubrication model specifically for the water-lubricated thrust bearing system. In this model, the hydrodynamic model was improved by using the height of the rough surface and its probability density function, combined with the average flow model. The asperity contact model was improved by using the equation for the Pearson system of frequency curves to characterize the non-Gaussian aspect of surface roughness distribution.

According to the results, negative skewness, large kurtosis and lateral surface pattern can improve the tribological performance of water-lubricated thrust bearings. Optimizing the surface morphology is a reasonable design method that can improve the performance of water-lubricated thrust bearings.

In this paper, one mixed lubrication model specifically for the water-lubricated thrust bearing with the effect of surface roughness into consideration was developed. Based on the developed model, the effect of surface morphology on tribological behavior can be evaluated.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0247/

This paper aims to present the approximate limit pressure solutions for thin-walled shape-imperfect 90° pipe bends. Limit pressure was determined by finite element (FE) limit analysis with the consideration of small geometry change effects.

The limit pressure of 90° pipe bends with ovality and thinning has been evaluated by geometric linear FE approach. Internal pressure was applied to the inner surface of the FE pipe bend models. When von-Mises stress equals or just exceeds the yield strength of the material, the corresponding pressure was considered as the limit pressure for all models. The current FE methodology was evaluated by the theoretical solution which has been published in the literature.

Ovality and thinning produced a significant effect on thin-walled pipe bends. The ovality weakened pipe bend performance at any constant thinning, while thinning improved the performance of the bend portion at any constant ovality. The limit pressure of pipe bends under internal pressure increased with an increase in the bend ratio and decreased with an increase in the pipe ratio. With a simultaneous increment in bend radius and reduction in wall thickness, there was a reduction in limit pressure. A new closed-form empirical solution was proposed to evaluate limit pressure, which was validated with published experimental data.

The influences of structural deformation (ovality and thinning) in the limit pressure analysis of 90° pipe bends have not been investigated and reported.

This paper aims to investigate the effect of frictional heat on the wear of high-speed rotary lip seals in engines.

In this research paper, the authors focus on the high-speed rotating lip seal of aircraft engines. Using the hybrid lubrication theory, a thermal-fluid-solid coupled numerical simulation model is established to investigate the influence of parameters such as contact pressure distribution, temperature rise and leakage rate on the sealing performance under different operating conditions. By incorporating the Rhee wear theory and combining simulation results with experimental data, a method for predicting the wear of the rotating seal lip profile is proposed. Experimental validation is conducted using a high-speed rotating test rig.

The results indicate that as the speed increases, the rise in frictional heat leads to a decrease in the sealing performance of the lip seal contact region. The experimental results show a similar trend to the numerical simulation results, and considering the effect of frictional heat, the predicted wear of the lip seal profile aligns more closely with the actual wear curve. This highlights the importance of considering the influence of frictional heat in the analysis of rotating seal mechanisms.

This study provides a reference for the prediction of wear profiles of engine high-speed rotary lip seals.

The purpose of this paper is to study haemodynamic flow characteristics and entropy analysis in a bifurcated artery system subjected to stenosis, magnetohydrodynamic (MHD) flow and aneurysm conditions. The findings of this study offer significant insights into the intricate interplay encompassing electro-osmosis, MHD flow, microorganisms, Joule heating and the ternary hybrid nanofluid.

The governing equations are first non-dimensionalised, and subsequently, a coordinate transformation is used to regularise the irregular boundaries. The discretisation of the governing equations is accomplished by using the Crank–Nicolson scheme. Furthermore, the tri-diagonal matrix algorithm is applied to solve the resulting matrix arising from the discretisation.

The investigation reveals that the velocity profile experiences enhancement with an increase in the Debye–Hückel parameter, whereas the magnetic field parameter exhibits the opposite effect, reducing the velocity profile. A comparative study demonstrates the velocity distribution in Au-CuO hybrid nanofluid and Au-CuO-GO ternary hybrid nanofluid. The results indicate a notable enhancement in velocity for the ternary hybrid nanofluid compared to the hybrid nanofluids. Moreover, an increase in the Brinkmann number results in an augmentation in entropy generation.

This study investigates the flow characteristics and entropy analysis in a bifurcated artery system subjected to stenosis, MHD flow and aneurysm conditions. The governing equations are non-dimensionalised, and a coordinate transformation is applied to regularise the irregular boundaries. The Crank–Nicolson scheme is used to model blood flow in the presence of a ternary hybrid nanofluid (Au-CuO-GO/blood) within the arterial domain. The findings shed light on the complex interactions involving stenosis, MHD flow, aneurysms, Joule heating and the ternary hybrid nanofluid. The results indicate a decrease in the wall shear stress (WSS) profile with increasing stenosis size. The MHD effects are observed to influence the velocity distribution, as the velocity profile exhibits a declining nature with an increase in the Hartmann number. In addition, entropy generation increases with an enhancement in the Brinkmann number. This research contributes to understanding fluid dynamics and heat transfer mechanisms in bifurcated arteries, providing valuable insights for diagnosing and treating cardiovascular diseases.

The vibration of the rails is a significant source of railway rolling noise, often forming the dominant component of noise in the important frequency region between 400 and 2000 Hz. The purpose of the paper is to investigate the influence of the ground profile and the presence of the train body on the sound radiation from the rail.

Two-dimensional boundary element calculations are used, in which the rail vibration is the source. The ground profile and various different shapes of train body are introduced in the model, and results are observed in terms of sound power and sound pressure. Comparisons are also made with vibro-acoustic measurements performed with and without a train present.

The sound radiated by the rail in the absence of the train body is strongly attenuated by shielding due to the ballast shoulder. When the train body is present, the sound from the vertical rail motion is reflected back down toward the track where it is partly absorbed by the ballast. Nevertheless, the sound pressure at the trackside is increased by typically 0–5 dB. For the lateral vibration of the rail, the effects are much smaller. Once the sound power is known, the sound pressure with the train present can be approximated reasonably well with simple line source directivities.

Numerical models used to predict the sound radiation from railway rails have generally neglected the influence of the ground profile and reflections from the underside of the train body on the sound power and directivity of the rail. These effects are studied in a systematic way including comparisons with measurements.

The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.

The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.

A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.

The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.

To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.

Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF₆), to enable a higher dielectric strength compared to e.g. air. However, under high voltage direct current conditions, charge accumulation and electric field stress may occur, which may lead to partial discharge or system failure. Therefore, numerical simulations are used to design the system and determine the electric field and charge distribution. Although the gas conduction shows a more complex current–voltage characteristic compared to solid insulation, the electric conductivity of the SF₆ gas is set as constant in most works. The purpose of this study is to investigate different approaches to address the conduction in the gas properly for numerical simulations.

In this work, two approaches are investigated to address the conduction in the insulating gas and are compared to each other. One method is an ion-drift-diffusion model, where the conduction in the gas is described by the ion motion in the SF₆ gas. However, this method is computationally expensive. Alternatively, a less complex approach is an electro-thermal model with the application of an electric conductivity model for the SF₆ gas. Measurements show that the electric conductivity in the SF₆ gas has a nonlinear dependency on temperature, electric field and gas pressure. From these measurements, an electric conductivity model was developed. Both methods are compared by simulation results, where different parameters and conditions are considered, to investigate the potential of the electric conductivity model as a computationally less expensive alternative.

The simulation results of both simulation approaches show similar results, proving the electric conductivity for the SF₆ gas as a valid alternative. Using the electro-thermal model approach with the application of the electric conductivity model enables a solution time up to six times faster compared to the ion-drift-diffusion model. The application of the model allows to examine the influence of different parameters such as temperature and gas pressure on the electric field distribution in the GIL, whereas the ion-drift-diffusion model enables to investigate the distribution of homo- and heteropolar charges in the insulation gas.

This work presents numerical simulation models for high voltage direct current GIL, where the conduction in the SF₆ gas is described more precisely compared to a definition of a constant electric conductivity value for the insulation gas. The electric conductivity model for the SF₆ gas allows for consideration of the current–voltage characteristics of the gas, is computationally less expensive compared to an ion-drift diffusion model and needs considerably less solution time.