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The main purpose of the study is to develop a theoretical model being capable of analysing the sealing and hydrodynamic‐hydrostatic lubrication mechanisms occuring between the mating surfaces of mechanical face seals.

The theoretical model developed is based on solving the governing basic lubrication equation (Reynolds differential equation) by employing a finite difference method. The main lubrication machanism is assumed to be converging‐diverging wedge which is formed by the relative tilt of the sealing surfaces. The non‐dimensional Reynolds equation was solved to give the pressure distribution and consequently the load and moment acting on the movable seal ring. The aim of the model is to predict the non‐dimensional hydrodynamic and hydrostatic load carrying capacity of the system.

Theoretical model developed is capable of estimating the hydrodynamic and hydrostatic behaviour of mechanical radial face seals. It is shown that a converging‐diverging wedge mechanism produces hydrodynamic pressure which in turn maintains the seperation of the surfaces. The tilt appears to be caused mainly by bearing misalignment. It has been shown that hydrostatic load or pressure centre is an important parameter for load balance of moving seal ring. It is easy and useful to calculate the dimensional parameters defined taking into account the different geometrical and operating parameters.

This paper offers a quick and easy opportunity to examine the hydrodynamic behaviour of movable seal ring of a mechanical face seal and provides a considerable contribution to the lubrication and sealing research area. With the general theoretical model developed, the behaviour of the seal ring can be modelled and estimated.

A neural network is employed to analyze axial piston pump of hydrostatic circular recessed bearing. Owing to complexity of the system, the neural network is used to predict the bearing parameters of the experimental system. The system mainly consists of cylinder block, piston, slipper, ball‐joint and swash plate. The neural model of the system has three layers, which are input layer with one neuron, hidden layer with ten neurons and output layer with three neurons. It can be outlined from the results for both approaches neural network could be modeled bearing systems in real time applications.

The purpose of this paper is to investigate experimentally slippers, which have an important role on power dissipation in the swash plate axial piston pumps. Since slippers affect the performance of the system considerably, the effects of surface roughness on lubrication have been studied in slippers with varying hydrostatic bearing areas and surface roughness.

An experimental set‐up was designed to determine the performance of slippers, which are capable of increasing the efficiency of axial piston pumps, in different conditions.

The findings suggest that the frictional power loss has been caused by surface roughness, capillary tube diameter, and the size of the hydrostatic bearing area, supply pressure and the relative velocity. In the case of the 0.7 and 9.5 μm surface roughness more power is needed to overcome the friction force between slippers and slipper plates, but less power loss occurs with the slippers with surface roughness of 1.5 μm. The slippers with surface roughness of 1.5 μm are considered, because of the optimum power loss. Moreover, the power loss decreases with increasing capillary tube diameter and supply pressure.

In order to investigate slipper behaviour under different operating conditions, with different capillary tube size and supply pressure an experimental work was carried out for finding exact design parameters of the real time system.

The purpose of this paper is to experimentally and theoretically investigate slippers, which have an important role on power dissipation in the swash plate axial piston pumps.

The slipper geometry and working conditions affected on the slipper performance have been analyzed experimentally. The model of the slipper system has been established by original neural network (NN) method.

First, the effects of the slipper geometry with smooth and conical sliding surfaces on the slipper performance were experimentally analyzed. Smooth sliding surface slippers showed a better performance then the conical surface ones. According to the results, the neural predictor would be used as a predictor for possible experimental applications on modeling this type of system.

This paper discusses a new modeling scheme known as artificial NNs an experimental and a NN approach have been employed for analyzing axial piston pumps. The simulation results suggest that the neural predictor would be used as a predictor for possible experimental applications on modeling bearing system.

The main purpose of the research work carried out is to investigate the hydraulic balance conditions of the sealing ring of a mechanical radial face seal in terms of the residual load acting on the ring by employing the theoretical model developed mentioned in the first part of the investigation.

The end load balance conditions for the movable seal ring have been examined by considering the residual load acting on the ring under all running conditions. The main lubrication and sealing mechanism is assumed to be due to the existence of the relative tilt between the mating surfaces, which is formed by the bearing misalignment. The aim of the theoretical model developed is to predict the necessary minimum film thickness between the relatively moving surfaces by considering the non‐dimensional running (operating) conditions and the geometrical parameters defined. The theoretical model is based on the main differential equation (Reynolds' equation) which is achieved by adopting the standard finite difference form.

Under the combination of the hydrostatic clamping forces and hydrodynamic restoring forces, an equilibrium position is reached with the seal ring displaced from its central position. At a particular non‐dimensional pressure, the seal ring comes into contact with the stationary plate and this limits the upper value of pressure that can be resisted by the mechanical seal type examined without metal‐metal contact. With the theoretical model developed, it was found that the minimum film thickness between the realtively moving surfaces could be predicted.

This paper provides a considerable scientific contribution to the field of lubrication and sealing aspect of the mechanical radial face seals. The results presented in the first part of the investigation and the remarks outlined in this paper would be considered as a design tool for the seal designers with special reference to ring behaviour under hydrodynamic and hydrostatic conditions.

The purpose of this paper is to investigate the hydrodynamic performance of a single‐screw extruder with special reference to metering region.

The hydrodynamic analysis of a single screw extruder is carried out by dimensional and non‐dimensional parameters defining the polymer flow behaviour. The flow types formed in the extruder channel are defined and the relationship between the flow with the extruder geometry is examined.

The theoretical model developed is capable of estimating the hydrodynamic behaviour of extruder metering region. With the model developed, extruder geometry and polymer flow rate under different operating conditions can be predicted.

This paper offers a quick and easy opportunity to examine the hydrodynamic behaviour of extruder metering region. With the theoretical model developed, the behaviour of the flow in extruder can be modelled and estimated.

The purpose of this paper is to investigate the design dimensions in pressure or metering region of a single‐screw extruder by determining viscous power loss. The paper is the second part of a series.

Viscous power loss formed in the extruder screw channel and the radial clearance is determined and evaluated in terms of non‐dimensional parameters in order to obtain a theoretical model.

The theoretical model developed is capable of estimating the viscous power loss in the extruder metering region. With the model developed, extruder geometry and viscous power loss under different operating conditions can be predicted.

This paper offers a quick and easy opportunity to examine the viscous power loss in the extruder.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

To solve the problem, a mathematical model is proposed; it relies on a directed acyclic graph (DAG), in which arcs are used to indicate whether a pair of appointments can be assigned to the same route or not (and so to the same care worker). The proposed model aims at minimizing the personnel required to meet daily demand and balancing workloads among the workers while considering the varying traffic patterns derived from traffic congestion.

This paper aims at providing solution approaches for addressing the problem of assigning care workers to deliver home health-care (HHC) services, demanding different skills each. First, a capacity planning problem is considered, where it is necessary to define the number of workers required to satisfy patients' requests and then, patients are assigned to the care workers along with the sequence followed to visit them, thus solving a scheduling problem. The benefits obtained by permitting patients to propose multiple time slots where they can be served are also explored.

The results indicate that the problem can be efficiently solved for medium-sized instances, that is, up to 100 daily patient requests. It is also indicated that asking patients to propose several moments when they can receive services helps to minimize the need for care workers through more efficient route allocations without affecting significantly the balance of the workloads.

This article provides a new framework for modeling and solving a HHC routing problem with multiskilled personnel. The proposed model can be used to identify efficient daily plans and can handle realistic characteristics such as time-dependent travel times or be extended to other real-life applications such as maintenance scheduling problems.

This study aims to discover the general trends, the structural characteristics of the knowledge base, and developments in the field of internationalization of higher education (IHE) in Turkey. In this respect, the studies published in journals indexed by SSCI, SCI-Expanded, ESCI, and AHCI in Web of Science (WoS) between January 1, 1975, and November 20, 2021, were analyzed. The dataset included 260 articles. We administered descriptive analysis reflecting the topographical features and the dynamics of the related literature through Excel and the WoS analysis tools. We conducted bibliometric analyses to shed light on the current view of the literature and reveal the intellectual structure of the knowledge base and topical foci. The volume of the research in the field of IHE in Turkey and their yearly distribution suggests that this area of research is still in its infancy; however, there has been a rapid growth in the number of publications recently. Author co-citation analysis reveals four distinct schools of thought labeled as “Higher Education Policy Studies in EU,” “Global Socio-politics and Economics of IHE,” “Socio-cultural and Psychological Dimensions of Internationalization” and “Language Studies.” Finally, topical foci in the knowledge base emerged as “International Student Mobility,” “Psychological and Cultural Adaptation of International Students,” “Higher Education Policy Reforms,” “International Staff Mobility” and “Migration Related Issues.” The results are discussed with related review studies and suggestions for future research are provided.