An analysis on the subject of “induced magnetic field effect on stagnation flow of a TiO2-Cu/water hybrid nanofluid over a stretching sheet” has been carried out in this paper. It should be noted ...that hybrid nanofluid consists of two or more types of nanoparticles along with a base fluid and it is used to increase the heat transfer. Furthermore, the non-linear differential equations modeling this issue are included in this article. In order to solve these equations numerically, Runge-Kutta Fehlberg method is used as a numerical method in this problem. The main objective of this paper is to investigate the effects of change in parameters of stretching ratio parameter (A∗), nanoparticles volumetric fractions (∅2), magnetic parameter (β) and reciprocal magnetic Prandtl number (λ) on the functions including velocity, induced magnetic field and temperature for both Cu-water nanofluid and TiO2-Cu/water hybrid nanofluid. Also Lorentz force which is derived from magnetic field is mentioned in this section. In addition, the impacts of (∅2), (β) and (λ) on the profiles of nanofluid and hybrid nanofluid temperature for three categories of nanoparticle shapes named brick, cylinders, and platelets are analyzed. At the end, the influences of (∅2), (β) and (λ) on skin friction coefficient (Cf) and Nusselt number (Nux) for Cu-water nanofluid and TiO2-Cu/water hybrid fluid for different nanoparticles shapes are discussed. In all of these studies it can be seen that applying platelets shaped nanoparticles is more effective.
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•TiO2‐Cu/H2O hybrid nanofluid is incorporated.•Analysis of thermal conductivity of hybrid nanofluid is highlighted.•Different shape factors for nanoparticles are addressed.•Nonlinear differential equations are solved numerically.
Super duplex stainless steels (SDSS), widely used in industries such as offshore oil and gas, offer a unique combination of high strength and corrosion resistance. However, surface hardening ...treatments are crucial to enhance their performance and extend service life. This work investigates the effect of plasma nitriding on the tribological behaviour of SDSS SAF 2507. Samples are treated without prior polishing (as received, AR) at ultra-low temperatures (250 and 300 °C) aiming to avoid detrimental CrN precipitation. Comprehensive microstructural characterization, corrosion studies, and tribological tests (scratch and ball-on-disc) are conducted on samples that do not present CrN (PN). Results indicate that the hardness of PN samples nearly doubles that of AR samples due to the presence of expanded austenite. Corrosion tests show improvements in passivity for PN samples. In scratch tests, while the AR material undergoes progressive plastic deformation, in PN material the nitrided layer breaks down only after reaching a critical load. In ball-on-disc test, wear rates are remarkably lower for PN condition compared to AR condition. Wear mechanism is tribo-oxidative and abrasive for the AR condition. Wear of PN samples is characterized by asperity break-off and ratcheting. The nitrided layer in PN samples exhibits an enhanced load-bearing capacity that improves wear resistance in both tests.
•SDSS without previous polishing (AR) was plasma nitrided at 250 °C and 300 °C.•Plasma nitrided AR at 250 °C (PN) does not present Cr nitrides.•PN has an expanded austenite layer of 2 μm thickness.•PN has enhanced passivity and hardness than that of untreated material.•The good load-bearing capacity of PN increased its wear resistance.
The accurate estimation of the tire–road friction coefficient plays a significant role in the vehicle dynamics control. The estimation method should be timely and reliable for the controlling ...requirements, which means the contact friction characteristics between the tire and the road should be recognized before the interference to ensure the safety of the driver and passengers from drifting and losing control. In addition, the estimation method should be stable and feasible for complex maneuvering operations to guarantee the control performance as well. A signal fusion method combining the available signals to estimate the road friction is suggested in this paper on the basis of the estimated ones of braking, driving and steering conditions individually. Through the input characteristics and the states of the vehicle and tires from sensors the maneuvering condition may be recognized, by which the certainty factors of the friction of the three conditions mentioned above may be obtained correspondingly, and then the comprehensive road friction may be calculated. Experimental vehicle tests validate the effectiveness of the proposed method through complex maneuvering operations; the estimated road friction coefficient based on the signal fusion method is relatively timely and accurate to satisfy the control demands.
•Simple method to estimate road friction for ABS, TCS and AYC for ground test.•No extra pressure sensors and other apparatus.•Combine the road friction for ABS, TCS and AYC to improve robustness and accuracy.•Tested under complex maneuvering operations.•Consider the driving and steering combined condition.
Flexible pipes are structures responsible for several operations in offshore playing a vital role and hold immense importance in oil extraction.
Modelling such pipes is not trivial, due to its ...layered structure. The helical wounded wires layers, which are responsible for handling axial loads, present a challenge in modelling in special. Another important factor for consideration are layer interactions, since they play a major role in pipe behavior.
To obtain the pipe response under various loads, the authors proposed the macroelement model: a finite element model in which elements take profit of the problem geometrical characteristics, simplifying the meshing process and contact treatment, while reducing memory use and processing time.
The present article is an excerpt of this research line and focuses on the understating of the frictional behavior in layer interactions by studying a flexible pipe. The model considers all the previous developed elements to simulate a four-layered flexible pipe, consisting of two tensile armor layers and two cylindrical ones. The loading considered is pressure combined with either tension or compression and the effects of the friction coefficient are investigated.
are compared to classical finite element for validation, showing excellent agreement, differences in performance and efficiency are highlighted.
•The macroelement model is a fast and reliable custom-made model.•Decrease in memory usage and increase in solution time when compared with commercial software.•Parametric analysis for a 4-layer flexible pipe that was possible due to the model characteristics.•Results are within an envelop defined by frictionless and bonded solutions.
Tribological investigations were performed on mineral oil containing Fe, Cu and Co nanoparticles and their combinations. The tribological tests showed that each set of nanoparticles significantly ...reduced the friction coefficient and wear (up to 1.5 times) of friction pairs. The use of Cu nanoparticles provides the most effective reduction of friction and wear in each combination of nanoparticles. Surface analysis shows that the constituent elements of nanoparticles precipitated on the contact surface during the use of the oils with nano-additives. Different structures formed on the friction surface are observed in the contact zone and over the remainder of the ball surface. The SEM micrographs and EDX chemical analysis confirm the formation of a tribo-layer composed of the elements from the nanoparticles.
► Oils with Fe, Cu and Co nanoparticles prepared by the new CEWLS method. ► Obvious reduction of friction and wear of friction pairs using the nano-additives. ► Efficiency of Cu nanoparticles and the use of mixtures of nanoparticles. ► Precipitation of nanoparticles' elements on the contact surface. ► Formation of protective layer of nanoparticle material during the operation.
Tribological properties and wear mechanisms of S32750 stainless steel/carbon fiber-reinforced polyetheretherketone (CFRPEEK) tribopair in seawater under different salinities, sliding speeds and loads ...were experimentally studied. A novel Physics-Informed constraint strategy has been originally developed and combined with sparrow search algorithm (SSA) to optimize a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model for predicting friction coefficient. The results indicate that an increase in seawater salinity and sliding speed enhances the tribological performance. Under high load, an increase in the PEEK transfer film leads to a slight decrease in friction coefficient. The Physics-Informed SSA (PISSA) offers enhanced performance through faster convergence, higher solution quality, and less computation time. Additionally, CNN-LSTM model optimized by PISSA (PISSA-CNN-LSTM) provides more accurate predictions of friction coefficient.
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•Impact of seawater salinity on tribological properties of S32750/CFRPEEK tribopair.•A novel Physics-Informed sparrow search algorithm for optimizing the CNN-LSTM model.•Verification and comparison of the proposed Physics-Informed constraint strategy.•Practical application of predicting the friction coefficient of the S32750/CFRPEEK tribopair.
•Fractal contact theory is adopted to calculate local contact deformation of spur gears.•Mesh characteristics of spur gears are investigated considering roughness and friction.•The influences of ...friction coefficient and fractal parameters on the mesh characteristics are analyzed and compared.•Multi-parameters impact analysis is conducted.
Considering the influence of roughness on the normal contact stiffness of gears, a fractal contact model suited for gear pair contact has been established. On the basis of modified fractal contact model, the asperity contact stiffness is calculated, thus the fractal contact compliance can be obtained. By substituting the nonlinear Hertz contact compliance with the fractal contact compliance, the effects of roughness on the time-varying mesh characteristics (including mesh stiffness (TVMS), loaded static transmission error (STE), load sharing ratio (LSR) and contact stress (CS)) of gears then can be discussed. The numerical simulation results show that the contact stiffness increases with the increment of the fractal dimension and the reduction of the fractal scale characteristic coefficient. In addition, the effect of friction on the mesh characteristics has also been investigated. As the coefficient of friction increases, the variation of the mesh characteristics in the single-tooth engagement region will increase correspondingly. Besides, the influence of multi-parameters on the mesh characteristics of gear pairs has been conducted. It can be found from the parametric studies that the amplitudes of gear mesh stiffness and contact stress are nonlinear with the changes of fractal parameter and friction coefficient.
The accurate knowledge of tire-road friction coefficient (TRFC) contributes to the optimization of driver maneuvers for further improving the safety of intelligent vehicles. The performance of the ...existing estimation methods would decline when a vehicle performs complex driving maneuvers. In addition, the mass parameter mismatch also deteriorates the estimation accuracy of TRFC. To address these problems, in this article, an integrated scheme for TRFC estimation is proposed by combining a strong tracking unscented Kalman filter and an interactive multiple model unscented Kalman filter. Real-time experiments are implemented on a mass-produced vehicle to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed approach has better estimation accuracy than the existing ones under various driving scenarios.
