A New Response Surface Stochastic Analysis Method for Spatial Structure Stability—The Reticulated Shell Structure as an Example

For a long time, spatial structures have been widely used. However, compared with the high strength of their material, their stability is weak, and especially sensitive to damage and defects. This feature has increased the engineering industry’s high requirements for their stability analysis. As we all know, this problem is more prominent for the reticulated shell structure, which is a classic representative of the spatial structure. However, in the current analysis methods for the stability of reticulated shells, the deterministic analysis method cannot consider the random characteristics of defects. Other random methods, such as the random defect modal method, and many improved methods, require more samples and calculation time. This unfavorable situation makes its engineering application greatly restricted. In addition, the random modal superposition method and derivation method based on Monte Carlo has not fundamentally changed this limitation. In order to fundamentally overcome this traditional shortcoming, this paper comprehensively studies the advantages of the high accuracy of the random defect modal method and the improved method, and at the same time, investigates the speed advantage of the response surface method, and then creates a new stochastic analysis method based on the response surface method. Finally, the analysis results of the calculation examples in this paper prove that it successfully balances and satisfies the dual requirements of accuracy and speed required for calculating the stability of the reticulated shell structure. Moreover, it has universal applicability to different forms of reticulated shells, such as classic 6-point flat domes, traditional reticulated shell structures, and bionic reticulated shell structures, and even other types of spatial structures.

Early Inline Detection of Systematic Defects Using ATPG and Commonality Analysis on Product-Like Logic Yield Learning Vehicle

This paper presents the successful use of the novel inline product-like logic vehicle (PATO) during the last technology development phases of IBM's 22nm SOI technology node. It provides information on the sequential PATO inline test flow, commonality analysis procedure, and commonality signature trending. The paper presents examples of systematic defects uniquely captured by the product-like back end of the line layout. Moreover, this complex logic vehicle also uncovered a rich Pareto of more than 20 types of systematic and random defect mechanisms across the front end of the line, the middle end of the line, and the back end of the line. And more importantly, the non-defect found rate was kept below 20%. This achievement was possible by: leveraging high volume inline test ATPG scan fail data through the novel commonality analysis approach; and selecting the highest ATPG confidence defects representing a known commonality signature to physical failure analysis.

BRITTLE FRAGMENTATION OF AN EXPANDING RING BY MOLECULAR DYNAMICS

In this paper, the brittle fragmentation of an expanding ring is numerically studied by a simple atomistic model. We investigate the statistical distribution of fragment spanned over a wide range of strain rates when damage related to broken bond reaches a steady state. It is shown that at low strain rate limited number of heavy fragments can be generated because of anisotropic behavior while for high strain rate fragment can be well fitted with Weibull distribution. The physical mechanism of fragmentation process reveals that damage accompanying with numerous microcracks is found to initiate in the inner regime of the expanding ring. Furthermore, we discuss the effect of random defect on the fragmentation process.