Simulation of thermal barrier coating spallation induced by the initiation/growth/coalescence of internal crack and interfacial crack based on a real image model

In the furnace cycle test, the growth of oxide film leads to the propagation and coalescence of multiple cracks near the interface, which should be responsible for the spallation of thermal barrier coatings (TBCs). A TBC model with real interface morphology is created, and the near-interface large pore is retained. The purpose of this work is to clarify the mechanism of TBC spallation caused by successive initiation, propagation, and linkage of cracks near the interface during thermal cycle. The dynamic growth of thermally grown oxide (TGO) is carried out by applying a stress-free strain. The crack nucleation and arbitrary path propagation in YSZ and TGO are simulated by the extended finite element method (XFEM). The debonding along the YSZ/TGO/BC interface is evaluated using a surface-based cohesive behavior. The large-scale pore in YSZ near the interface can initiate a new crack. The ceramic crack can propagate to the YSZ/TGO interface, which will accelerate the interfacial damage and debonding. For the TGO/BC interface, the normal compressive stress and small shear stress at the valley hinder the further crack propagation. The growth of YSZ crack and the formation of through-TGO crack are the main causes of TBC delamination. The accelerated BC oxidation increases the lateral growth strain of TGO, which will promote crack propagation and coalescence. The optimization design proposed in this work can provide another option for developing TBC with high durability.     

混凝土结构的压电声波检测分析

本文介绍了混凝土结构的压电体波和表面波检测的主要进展,对两种压电声波检测的优缺点进行了总结。体波检测设备一般埋入混凝土内部,需要选择合理的检测部位,检测结果较为精确;声表面波检测无需选择特定的部位,但是检测深度有限。在实际检测工作过程中,可以联合两种方法相互验证。     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

Preparation,microstructure and ion-irradiation damage behavior of Al4SiC4-added SiC ceramics

Single-phase Al₄SiC₄ powder with a low neutron absorption cross section was synthesized and mixed with SiC powder to fabricate highly densified SiC ceramics by hot pressing. The densification of SiC ceramics was greatly improved by the decomposition of Al₄SiC₄ and the formation of aluminosilicate liquid phase during the sintering process. The resulting SiC ceramics were composed of fine equiaxed grains with an average grain size of 2.0 μm and exhibited excellent mechanical properties in terms of a high flexure strength of 593 ± 55 MPa and a fracture toughness of 6.9 ± 0.2 MPa m^1/2. Furthermore, the ion-irradiation damage in SiC ceramics was investigated by irradiating with 1.2 MeV Si⁵⁺ ions at 650 °C using a fluence of 1.1 × 10¹⁶ ions/cm², which corresponds to 6.3 displacements per atom (dpa). The evolution of the microstructure was investigated by X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. The breaking of Si–C bonds and the segregation of C elements on the irradiated surface was revealed by XPS, whereas the formation of Si–Si and C–C homonuclear bonds within the Si–C network of SiC grains was detected by Raman spectroscopy.     

中国抗中子辐照钢的抗辐照设计与验证

聚变堆等未来先进核能系统要求材料在强流高能中子辐照下长期保持良好的结构稳定性和机械性能。为适应未来先进核能技术发展的需要，中国科学院核能安全技术研究所•凤麟团队牵头研发了具有我国自主知识产权的中国抗中子辐照钢--CLAM钢。CLAM钢的设计考虑了未来核能清洁性的要求，以及苛刻服役环境中材料抗辐照、耐高温、耐腐蚀等性能要求。通过中子学计算分析设计了低活化成分范围，基于选择性纳米相析出进行了抗辐照、耐高温性能优化设计。针对材料的抗辐照性能，利用国内外中子、离子、电子及等离子体辐照设施开展了系列辐照考验研究，通过多角度表征辐照前后材料的微观结构和宏观性能，综合评估了材料的辐照性能，并与国际上同类材料在相近或相同条件下的辐照性能进行了对比分析，结果表明CLAM钢具有良好的抗辐照性能。     

瞬态闭锁试验在0.13 μm大规模集成电路中引起的潜在损伤

瞬态剂量率辐射试验会引起集成电路发生损伤或失效，其原因至少有两种：闭锁大电流引起的电路内部金属互连熔融；累积电离总剂量引起的氧化层电荷造成阈值电压偏移。本文以一种0.13 μm体硅CMOS处理器为对象，研究了瞬态剂量率和稳态电离总剂量辐射效应规律。结果表明：瞬态剂量率闭锁效应对处理器造成了显著的潜在损伤，导致其总剂量失效阈值从1 030 Gy(Si)降低至600 Gy(Si)。研究结论对于大规模集成电路的可靠性评估和指导辐射加固设计有重要参考意义。     

Nonlinear modal analysis via non‐parametric machine learning tools

Modal analysis is an important tool in the structural dynamics community; it is widely utilised to understand and investigate the dynamical characteristics of linear structures. Many methods have been proposed in recent years regarding the extension to nonlinear analysis, such as nonlinear normal modes or the method of normal forms, with the main objective being to formulate a mathematical model of a nonlinear dynamical structure based on observations of input/output data from the dynamical system. In fact, for the majority of structures where the effect of nonlinearity becomes significant, nonlinear modal analysis is a necessity. The objective of the current paper is to demonstrate a machine learning approach to output‐only nonlinear modal decomposition using kernel independent component analysis and locally linear‐embedding analysis. The key element is to demonstrate a pattern recognition approach which exploits the idea of independence of principal components from the linear theory by learning the nonlinear manifold between the variables. In this work, the importance of output‐only modal analysis via “blind source” separation tools is highlighted as the excitation input/force is not needed and the method can be implemented directly via experimental data signals without worrying about the presence or not of specific nonlinearities in the structure.     

枪管结构对固有频率的影响

为了研究枪管结构对枪管固有频率的影响,针对枪管尤其是狙击枪管设计中约束长度、枪管外形、膛口装置以及膛线等不同结构,建立了相应的三维模型。采用以六面体为主的网格对枪管进行了网格划分,采用有限元方法对枪管进行了模态分析。计算获得了不同结构枪管的固有频率; 通过比较,得到了不同枪管结构对固有频率的影响。分析结果表明:枪管尾部螺纹长度越长,枪口振动幅度越低; 相同质量枪管,锥形外形枪管刚度最好; 加装膛口装置对枪管刚度和振动特性有不利影响。     

A robust locating multi-optima approach for damage identification of plate-like structures

This paper proposes a robust optimization approach for multiple damage identification of plate-like structures. Different from traditional particle swarm optimizations (PSOs), a combined PSO and niche technique (NPSO) is proposed to solve multimodal optimization problems, with the full consideration of subswarm creation, merging and absorbing mechanism. As a hypersensitive parameter to damage, the curvature mode shape is adopted to construct the objective function. Case studies are conducted to investigate the effectiveness and robustness of the algorithm on multi-damage identification. Simulation results show that the proposed algorithm exhibits robust search performance on identifying damage locations accurately with good convergence behavior. It is hoped that this study can provide guidance on robust damage detection, especially when the structure is subject to multiple damages and external disturbances.