Microstructure,mechanical, tribological,and oxidizing properties of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings with different modulated thicknesses

Multilayer structure design is one of the most promising methods for improving the comprehensive performance of AlCrN-based hard coatings applied to cutting tools. In this study, four types of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings, with different modulated thicknesses, were deposited to investigate their microstructure, mechanical, tribological, and oxidizing properties. All multilayer coatings exhibited grain growth along the crystallographic plane of (200) with a NaCl-type face-centered cubic (FCC) structure. The results show that, as the modulation thickness decreases from ～35 nm to ～10 nm, (1) the grain refinement effect is increasingly evident; (2) all multilayer coatings show a hardness of >30 GPa and an elastic modulus of >300 GPa. Both the ability to resist elastic strain to failure and the plastic deformation of multilayer coatings increase. In addition, their resistance to cracking reduces; (3) the wear rates of these multilayer coatings reduce successively from 1.78 × 10^?16 m³ N^?1 m^?1 to 7.7 × 10^?17 m³ N^?1 m^?1. This is attributed to an increase in self-lubricating VO_x and a decrease in adhesives from the counterparts; (4) the best high-temperature oxidation resistance was obtained for the multilayer coating with a modulated thickness of ～15 nm.     

Thermomechanical stability and inelastic energy dissipation as durability criteria for fuel cell gas diffusion media with pre-assembly effects

In this article, pre-assembly hot-press pressure and thermal expansion effects in gas-diffusion layers (GDLs) are addressed to explore the practicalities of the constitutive model reported in the companion article. A facile technique is proposed to include deformation history dependent residual strain effects. The model is implemented in the numerical environment and compared with widely followed conventional models such as isotropic and orthotropic material models. With the normal and accelerated thermal expansion effects no significant variation in stresses or strains is reported with the compressible GDL model in contrast to the conventional incompressible form of the GDL model. The present work identifies the critical differences with advanced and extended variants of the model along with conventional GDL material models in terms of planar stress/strain distribution and the membrane response. Finally, the model is simulated for micro-cyclic stress loads of varying amplitudes that imitate the real working conditions of fuel cell. The inelastic energy dissipation in GDLs is predicted using the proposed model, which is utilized further to distinguish the safe (elastic) and unsafe (inelastic shakedown) operating limits. The inelastic collapse of GDLs is shown to be a active function of high amplitude micro-cyclic load with high initial clamping load.     

PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation

This paper investigates PID control design for a class of planar nonlinear uncertain systems in the presence of actuator saturation. Based on the bounds on the growth rates of the nonlinear uncertain function in the system model, the system is placed in a linear differential inclusion. Each vertex system of the linear differential inclusion is a linear system subject to actuator saturation. By placing the saturated PID control into a convex hull formed by the PID controller and an auxiliary linear feedback law, we establish conditions under which an ellipsoid is contractively invariant and hence is an estimate of the domain of attraction of the equilibrium point of the closed-loop system. The equilibrium point corresponds to the desired set point for the system output. Thus, the location of the equilibrium point and the size of the domain of attraction determine, respectively, the set point that the output can achieve and the range of initial conditions from which this set point can be reached. Based on these conditions, the feasible set points can be determined and the design of the PID control law that stabilizes the nonlinear uncertain system at a feasible set point with a large domain of attraction can then be formulated and solved as a constrained optimization problem with constraints in the form of linear matrix inequalities (LMIs). Application of the proposed design to a magnetic suspension system illustrates the design process and the performance of the resulting PID control law.      

Study on ice-melting performance of gradient gas diffusion layer in proton exchange membrane fuel cell

In this study, a three-dimensional model was established using the lattice Boltzmann method (LBM) to study the internal ice melting process of the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC). The single-point second-order curved boundary condition was adopted. The effects of GDL carbon fiber number, growth slope of the number of carbon fibers and carbon fiber diameter on ice melting were studied. The results were revealed that the temperature in the middle and lower part of the gradient distribution GDL is significantly higher than that of the no-gradient GDL. With the increase of the growth slope of the number of carbon fiber, the temperature and melting rate gradually increase, and the position of the solid-liquid interface gradually decreases. The decrease in the number of carbon fibers has a similar effect as the increase in the growth slope of the number of carbon fibers. In addition, as the diameter of the carbon fiber increases, the position of the solid-liquid interface gradually decreases first and then increases.     

Analysis of surface and interior degradation of gas diffusion layer with accelerated stress tests for polymer electrolyte membrane fuel cell

The effects of surface and interior degradation of the gas diffusion layer (GDL) on the performance and durability of polymer electrolyte membrane fuel cells (PEMFCs) have been investigated using three freeze-thaw accelerated stress tests (ASTs). Three ASTs (ex-situ, in-situ, and new methods) are designed from freezing ?30 °C to thawing 80 °C by immersing, supplying, and bubbling, respectively. The ex-situ method is designed for surface degradation of the GDL. Change of surface morphology from hydrophobic to hydrophilic by surface degradation of GDL causes low capillary pressure which decreased PEMFC performance. The in-situ method is designed for the interior degradation of the GDL. A decrease in the ratio of the porosity to tortuosity by interior degradation of the GDL deteriorates PEMFC performance. Moreover, the new method showed combined effects for both surface and interior degradation of the GDL. It was identified that the main factor that deteriorated the fuel cell performance was the increase in mass transport resistance by interior degradation of GDL. In conclusion, this study aims to investigate the causes of degraded GDL on the PEMFC performance into the surface and interior degradation and provide the design guideline of high-durability GDL for the PEMFC.     

Symmetric and asymmetric membranes based on La0.5Sr0.5Fe0.7Ga0.3O3-δ perovskite with high oxygen semipermeation flux performances and identification of the rate-determining step of oxygen transport

This work focuses on identifying the rate-determining step of oxygen transport through La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes with symmetric and asymmetric architectures. The best oxygen semipermeation fluxes are 3.4 10⁻³ mol. m^-2.s^-1 and 6.3 10⁻³ mol. m^-2.s^-1 at 900 °C for the symmetric membrane and asymmetric membrane with a modified surface. The asymmetric membrane with a modified surface leads to an increase of approximately 7 times the oxygen flux compared to that obtained with the La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ dense membrane without surface modification. This work also shows that the oxygen flux is mainly governed by gaseous oxygen diffusion through the porous support of asymmetric La_0.5Sr_0.5Fe_0.7Ga_0.3O_3-δ membranes.     

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition-based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters.     

Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

A signal adaptive diffusion filter for video coding: Mathematical framework and complexity reductions

In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished.