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In this paper, the complex flow evaporation process of droplet impact on the liquid film in a horizontal falling film evaporator is numerically studied based on smoothed particle hydrodynamics (SPH) method. The purpose of this paper is to present the mechanism of the water treatment problem of the falling film evaporation for the high salinity mine water in Xinjiang region of China.

To effectively characterize the phase transition problem, the particle splitting and merging techniques are introduced. And the particle absorbing layer is proposed to improve the nonphysical aggregation phenomenon caused by the continuous splitting of gas phase particles. The multiresolution model and the artificial viscosity are adopted.

The SPH model is validated qualitatively with experiment results and then applied to the evaporation of the droplet impact on the liquid film. It is shown that the larger single droplet initial velocity and the smaller single droplet initial temperature difference between the droplet and liquid film improve the liquid film evaporation. The heat transfer effect of a single droplet is preferable to that of multiple droplets.

A multiphase SPH model for evaporation after the droplet impact on the liquid film is developed and validated. The effects of different factors on liquid film evaporation, including single droplet initial velocity, single droplet initial temperature and multiple droplets are investigated.

Water jet propulsion is widely used in various military and civilian fields due to its advantages of simple structure and high propulsion efficiency. The process of mooring involves utilizing specially designed equipment to secure a ship at a designated berth. During the process of water jet propulsion, the single propeller operates within a complex and turbulent three-dimensional flow. Hence, studying the coupling between the water jet propeller and the hull is critical to comprehending the characteristics of the device and the distribution of the flow field in detail.

Firstly, we conducted computational fluid dynamics (CFD)-based self-propulsion calculations to evaluate the interaction between the hull and the propeller. We subsequently analyzed the propeller's performance and the forces acting on the hull to understand how the presence or absence of the hull influenced the water jet propeller. Finally, we performed calculations and analysis of the cavitation characteristics of the coupling between the hull and the water jet propeller, considering different rotational speeds and water depths at the bottom of the pool.

The study demonstrated that the presence of the hull boundary layer under the hull-propeller coupling condition led to reduced uniformity of propeller inlet flow and lower efficiency of the propulsion pump. However, it also increased the bias toward low-flow conditions. Additionally, increasing the impeller speed led to a gradual increase in the cavitation volume within the water jet propeller, resulting in a gradual decrease in the propeller's performance.

This research provides the technical support required for effective design and operation of water jet propulsion systems. This paper involves studying and analyzing the performance and flow field of the coupling between the hull and propeller under mooring conditions with a specified hull model.

The purpose of this study is to explore numerical scrutinization of micropolar and Walters-B non-Newtonian fluids motion under the influence of thermal radiation and chemical reaction.

The two fluids micropolar and Walters-B liquid are considered to start flowing from the slot to the stretching sheet. A magnetic field of constant strength is imposed on their flow transversely. The problems on heat and mass transport are set up with thermal, chemical reaction, heat generation, etc. to form partial differential equations. These equations were simplified into a dimensionless form and solved using spectral homotopy analysis method (SHAM). SHAM uses the basic concept of both Chebyshev pseudospectral method and homotopy analysis method to obtain numerical computations of the problem.

The outcomes for encountered flow parameters for temperature, velocity and concentration are presented with the aid of figures. It is observed that both the velocity and angular velocity of micropolar and Walters-B and thermal boundary layers increase with increase in the thermal radiation parameter. The decrease in velocity and decrease in angular velocity occurred are a result of increase in chemical reaction. It is hoped that the present study will enhance the understanding of boundary layer flow of micropolar and Walters-B non-Newtonian fluid under the influences of thermal radiation, thermal conductivity and chemical reaction as applied in various engineering processes.

All results are presented graphically and all physical quantities are computed and tabulated.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Flow induced by rotating disks is of great practical importance in several engineering applications such as rotating heat exchangers, turbine disks, pumps and many more. The present research has been freshly displayed regarding the implementation of an engine oil-based Casson tri-hybrid nanofluid across a rotating disk in mass and heat transferal developments. The purpose of this study is to contemplate the attributes of the flowing tri-hybrid nanofluid by incorporating porosity effects and magnetization and velocity slip effects, viscous dissipation, radiating flux, temperature slip, chemical reaction and activation energy.

The articulated fluid flow is described by a set of partial differential equations which are converted into one set of higher-order ordinary differential equations (ODEs) by using convenient conversions. The numerical solution of this transformed set of ODEs has been spearheaded by using the effectual bvp4c scheme.

The acquired results show that the heat transmission rate for the Casson tri-hybrid nanofluid is intensified by, respectively, 9.54% and 11.93% when compared to the Casson hybrid nanofluid and Casson nanofluid. Also, the mass transmission rate for the Casson tri-hybrid nanofluid is augmented by 1.09% and 2.14%, respectively, when compared to the Casson hybrid nanofluid and Casson nanofluid.

The current investigation presents an educative response on how the flow profiles vary with changes in the inevitable flow parameters. As per authors’ knowledge, no such scrutinization has been carried out previously; therefore, our results are novel and unique.

This paper aims to compare the wear behavior, surface roughness, friction coefficient and volume loss of high-velocity oxy-fuel (HVOF) sprayed WC–Co and WC–Cr₃C₂–Ni coatings on AISI 1095 steel with spraying times of 10 and 15 s.

In this study, the pin-on-disc testing technique was used to evaluate the wear characteristics at a speed of 0.24 m/s, load of 40 N and test time of 60 min under dry conditions at room temperature. The wear characteristics were examined and analyzed by scanning electron microscopy and energy dispersive X-ray spectroscopy. The surface roughness of a coated surface was measured, and microhardness measurements were performed on the cross-sectioned and polished surfaces of the coating.

Spraying time and powder material affected the hardness of HVOF coatings due to differences in the porosity of the coated layers. The average hardness of the WC–Cr₃C₂–Ni coating with a spaying time of 15 s was approximately 14% higher than that of the WC–Cr₃C₂–Ni coating with a spraying time of 10 s. Under an applied load of 40 N, the WC–Co coating with a spraying time of 15 s had the lowest variation in the friction coefficient compared with the other coatings. The WC–Co coating with a spraying time of 10 s had the lowest average and variation in volume loss compared to the other coatings. The WC–Cr₃C₂–Ni coating with a spraying time of 10 s exhibited the highest average volume loss. The wear features changed slightly with the spraying time owing to variations in the hardness and friction coefficient.

This study investigated tribological performance of WC–Co; WC-Cr₃C₂-Ni coatings with spraying times of 10 and 15 s using pin-on-disc tribometer by rotating the relatively soft pin (C45 steel) against hard coated substrate (disc).

Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint torque.

The proposed model optimized the LSTM with PSO algorithm to accurately predict the IRs joint torque. The authors design an excitation trajectory for ABB 1600–10/145 experimental robot and collect its relative dynamic data. The LSTM model was trained with the experimental data, and PSO was used to find optimal number of LSTM nodes and learning rate, then a torque prediction model is established based on PSO-LSTM deep learning method. The novel model is used to predict the robot’s six joint torque and the root mean error squares of the predicted data together with least squares (LS) method were comparably studied.

The predicted joint torque value by PSO-LSTM deep learning approach is highly overlapped with those from real experiment robot, and the error is quite small. The average square error between the predicted joint torque data and experiment data is 2.31 N.m smaller than that with the LS method. The accuracy of the novel PSO-LSTM learning method for joint torque prediction of IR is proved.

PSO and LSTM model are deeply integrated for the first time to predict the joint torque of IR and the prediction accuracy is verified.

The purpose of this paper is to investigate the effect of NaCl solution with different concentrations on impact-sliding fretting corrosion behavior of Inconel 690TT steam generator heat transfer tubes.

The optical 3D profiler was used to measure the wear profile and calculated the wear volume. Corrosion behavior was studied using open circuit potential monitoring and potentiodynamic polarization testing. The morphologies and elemental distributions of wear scars were analyzed using scanning electron microscopy and energy-dispersive spectroscopy. The synergism of wear and corrosion was analyzed according to the ASTM G119 standard.

The corrosion tendency reflected by OCP and the corrosion current calculated by Tafel both increased with the increase of NaCl concentration. The total volume loss of the material increased with concentration, and it was known from the synergism that the volume loss caused by corrosion-enhanced wear accounted for the largest proportion, while the wear-enhanced corrosion also made a greater contribution to volume loss than tangential fretting corrosion. Through the analysis of the material morphologies and synergism of wear and corrosion, the damage mechanism was elucidated.

The research findings can provide reference for impact-sliding fretting corrosion behavior of Inconel 690TT heat transfer tubes in NaCl solution with different concentrations.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

Inclination angle has been reported to have an enhancing effect on the thermal-hydraulic characteristics and entropy of some thermal systems. Therefore, this paper aims to numerically investigate the effects of inclination angle, volume concentration and Reynolds number on the thermal and hydraulic characteristics and entropy generation rates of water-based Al₂O₃ nanofluids through a smooth circular aluminum pipe in a turbulent flow.

A constant heat flux of 2,000 Watts is applied to the circular surface of the tube. Reynolds number is varied between 4,000 and 20,000 for different volume concentrations of alumina nanoparticles of 0.5%, 1.0% and 2.0% for tube inclination angles of ±90o, ±60o, ±45o, ±30o and 0o, respectively. The simulation is performed in an ANSYS Fluent environment using the realizable kinetic energy–epsilon turbulent model.

Results show that +45o tube orientation possesses the largest thermal deviations of 0.006% for 0.5% and 1.0% vol. concentrations for Reynolds numbers 4,000 and 12,000. −45o gives a maximum pressure deviation of −0.06% for the same condition. The heat transfer coefficient and pressure drop give maximum deviations of −0.35% and −0.39%, respectively, for 2.0% vol. concentration for Reynolds number of 20,000 and angle ±90o. A 95%–99.8% and 95%–98% increase in the heat transfer and total entropy generation rates, respectively, is observed for 2.0% volume concentration as tube orientation changes from the horizontal position upward or downward.

Research investigating the effect of inclination angle on thermal-hydraulic performance and entropy generation rates in-tube turbulent flow of nanofluid is very scarce in the literature.