Energy storage performance of 0.55Bi0.5Na0.5TiO3-0.45SrTiO3 ceramics doped with lanthanide elements (Ln = La,Nd, Dy,Sm) using a viscous polymer processing route

Lead-free bismuth sodium titanate-strontium titanate (NBT-ST) dielectric ceramic materials have been extensively investigated energy storage materials because of their relaxor characteristics. In this study, four different lanthanide elements were introduced into the ferroelectric NBT-ST ceramic to improve their relaxor properties. The introduction of the lanthanide resulted in an increase in disorder at location A within the perovskite lattice and improved relaxor characteristics, leading to a stored energy density of more than 3.5 J/cm³. In particular, an ultrahigh recoverable stored energy density of 4.94 J/cm³ and efficiency of 88.45% were achieved at 440 kV/cm when the NBT-ST ceramic was modified with neodymium. The modified ceramic also exhibited good thermal stability in the range of 30–120 °C, as well as a fast discharge time of ～153 ns, indicating that Nd-incorporated NBT-ST is a promising candidate for electrical energy storage ceramic.     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.     

On global Hessenberg based methods for solving Sylvester matrix equations

In the first part of this paper, we investigate the use of Hessenberg-based methods for solving the Sylvester matrix equation $AX+XB=C$. To achieve this goal, the Sylvester form of the global generalized Hessenberg process is presented. Using this process, different methods based on a Petrov–Galerkin or on a minimal norm condition are derived. In the second part, we focus on the SGl-CMRH method which is based on the Sylvester form of the Hessenberg process with pivoting strategy combined with a minimal norm condition. In order to accelerate the SGl-CMRH method, a preconditioned framework of this method is also considered. It includes both fixed and flexible variants of the SGl-CMRH method. Moreover, the connection between the flexible preconditioned SGl-CMRH method and the fixed one is studied and some upper bounds for the residual norm are obtained. In particular, application of the obtained theoretical results is investigated for the special case of solving linear systems of equations with several right-hand sides. Finally, some numerical experiments are given in order to evaluate the effectiveness of the proposed methods.     

道路用聚氨酯改性沥青的制备工艺探讨

结合不同改性剂掺量单因素试验,确定了采用88mm叶轮、115mm容器、圆盘锯齿式搅拌器(转速1400r/min)、175℃共混温度、改性剂掺量4.27%、单次搅拌300g的制备工艺参数。在此条件下制备的聚氨酯改性沥青具有优异的水稳定性、储存稳定性且耐老化、耐高温,拥有比普通聚合物改性沥青更高的车辙因子G*/sinδ和15℃动态模量,基本满足高模量沥青要求。     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.     

Two-step method to deposit ZrO2 coating on carbon fiber: Preparation,characterization, and performance in SiC composites

Recently, ceramic matrix composites reinforced by short carbon fibers (CFs) attracted increasing attentions. To further improve mechanical properties and oxidation resistances, CFs were subjected to oxidation and acidification followed by sol-gel dip-coating to deposit ZrO₂ on their surfaces. ZrO₂-C_f/SiC composites were fabricated by joint hot compression molding and sintering, compared to C_f/SiC and SiC prepared by the same method. Microstructural analyses indicated that ZrO₂ coatings were successfully deposited on CF surfaces, formed strong bonding and interfaces between CF and the matrix. Meanwhile, CFs were found uniformly distributed in SiC matrix with random orientations. Flexural curves of ZrO₂-C_f/SiC and C_f/SiC revealed the presence of “false plasticity” regions after sharp drops, which were quite different from brittle flexural behavior of SiC ceramic. Compression strength of the three samples showed step-up growth. ZrO₂-C_f/SiC exhibited the highest value, indicating the introduction of CFs and ZrO₂ coatings do have great influence on mechanical performances. After heat treatment, ZrO₂-C_f/SiC exhibited better oxidation resistance than C_f/SiC, with weight loss ratios estimated to ??3.76% and ??6.43%, respectively. These improved properties indicated that ZrO₂-C_f/SiC would be excellent alternatives to other existence materials under ultra-high temperature environments.     

Cost-minimization analysis of a working vacation queue with N-policy and server breakdowns

This paper investigates the N-policy M/M/1 queueing system with working vacation and server breakdowns. As soon as the system becomes empty, the server begins a working vacation. The server works at a lower service rate rather than completely stopping service during a vacation period. The server may break down with different breakdown rates during the idle, working vacation, and normal busy periods. It is assumed that service times, vacation times, and repair times are all exponentially distributed. We analyze this queueing model as a quasi-birth–death process. Furthermore, the equilibrium condition of the system is derived for the steady state. Using the matrix-geometric method, we find the matrix-form expressions for the stationary probability distribution of the number of customers in the system and system performance measures. The expected cost function per unit time is constructed to determine the optimal values of the system decision variables, including the threshold N and mean service rates. We employ the particle swarm optimization algorithm to solve the optimization problem. Finally, numerical results are provided, and an application example is given to demonstrate the applicability of the queueing model.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.