Good dielectric performance and broadband dielectric polarization in Ag,Nb co-doped TiO2

Due to the demand of miniaturization and integration for ceramic capacitors in electronic components market, TiO₂-based ceramics with colossal permittivity has become a research hotspot in recent years. In this work, we report that Ag⁺/Nb⁵⁺ co-doped (Ag_1/4Nb_3/4)_xTi_1−xO₂ (ANTOx) ceramics with colossal permittivity over a wide frequency and temperature range were successfully prepared by a traditional solid–state method. Notably, compositions of ANTO0.005 and ANTO0.01 respectively exhibit both low dielectric loss (0.040 and 0.050 at 1 kHz), high dielectric permittivity (9.2 × 10³ and 1.6 × 10⁴ at 1 kHz), and good thermal stability, which satisfy the requirements for the temperature range of application of X9R and X8R ceramic capacitors, respectively. The origin of the dielectric behavior was attributed to five dielectric relaxation phenomena, i.e., localized carriers' hopping, electron–pinned defect–dipoles, interfacial polarization, and oxygen vacancies ionization and diffusion, as suggested by dielectric temperature spectra and valence state analysis via XPS; wherein, electron-pinned defect–dipoles and internal barrier layer capacitance are believed to be the main causes for the giant dielectric permittivity in ANTOx ceramics.     

Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

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.     

Effect of mass transfer on the deactivation model and GPLE parameters of Co/γ-Al2O3 catalysts in the Fischer Tropsch synthesis

The activity of catalysts with various sizes was compared in a fixed-bed Fischer–Tropsch reactor under similar operating conditions by determining the deactivation model. Catalyst size had no impact on the type of deactivation model. The smaller catalyst showed a smaller deactivation constant of catalyst (k_d) and a lower deactivation rate in the initial stage. The decline in the activities of the catalyst with a mesh size of 40 was lower than the other catalysts, suggesting its higher long-term stability (a_ss). Larger catalyst sizes led to the fouling of carbon and heavy hydrocarbons, decreasing the specific surface of the catalyst, thus increasing the pore diffusion resistance and further decrementing the catalyst activities.     

Investigation of liquid water heterogeneities in large area proton exchange membrane fuel cells using a Darcy two-phase flow model in a multiphysics code

Proper management of the liquid water and heat produced in proton exchange membrane (PEM) fuel cells remains crucial to increase both its performance and durability. In this study, a two-phase flow and multicomponent model, called two-fluid model, is developed in the commercial COMSOL Multiphysics® software to investigate the liquid water heterogeneities in large area PEM fuel cells, considering the real flow fields in the bipolar plate. A macroscopic pseudo-3D multi-layers approach has been chosen and generalized Darcy's relation is used both in the membrane-electrode assembly (MEA) and in the channel. The model considers two-phase flow and gas convection and diffusion coupled with electrochemistry and water transport through the membrane. The numerical results are compared to one-fluid model results and liquid water measurements obtained by neutron imaging for several operating conditions. Finally, according to the good agreement between the two-fluid and experimentation results, the numerical water distribution is examined in each component of the cell, exhibiting very heterogeneous water thickness over the cell surface.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

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.      

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。