A novel entropy production based full-chip TSV fatigue analysis

Through-silicon vias (TSVs) are subject to thermal fatigue due to stress over time, no matter how small the stress is. Existing works on TSV fatigue all rely on measurement-based parameters to estimate the lifetime, and cannot consider detailed thermal profiles. In this paper, we propose a new method for TSV fatigue prediction using entropy production during thermal cycles. By combining thermodynamics and mechanics laws, the fatigue process can be quantitatively evaluated with detailed thermal profiles. Experimental results show that interestingly, the landing pad possesses the most easy-to-fail region, which generates up to 50% more entropy compared with the TSV body. The impact of landing pad dimension and TSV geometries are also studied, providing guidance for reliability enhancement. Finally, full-chip fatigue analysis is performed based on stress superposition. To the best of the authors\u27 knowledge, this is the first TSV fatigue model that is free of measurement data fitting, the first that is capable of considering detailed thermal profiles, and the first framework for efficient full-chip TSV fatigue analysis. --Abstract, page iii

Large-scale Multi-layer Academic Networks Derived from Statistical Publications

The utilization of multi-layer network structures now enables the explanation of complex systems in nature from multiple perspectives. Multi-layer academic networks capture diverse relationships among academic entities, facilitating the study of academic development and the prediction of future directions. However, there are currently few academic network datasets that simultaneously consider multi-layer academic networks; often, they only include a single layer. In this study, we provide a large-scale multi-layer academic network dataset, namely, LMANStat, which includes collaboration, co-institution, citation, co-citation, journal citation, author citation, author-paper and keyword co-occurrence networks. Furthermore, each layer of the multi-layer academic network is dynamic. Additionally, we expand the attributes of nodes, such as authors' research interests, productivity, region and institution. Supported by this dataset, it is possible to study the development and evolution of statistical disciplines from multiple perspectives. This dataset also provides fertile ground for studying complex systems with multi-layer structures

Exploring the Design Space of Immersive Urban Analytics

Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft HoloLens. These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence. In this paper, we propose an theoretical model to characterize the visualizations in immersive urban analytics. Further more, based on our comprehensive and concise model, we contribute a typology of combination methods of 2D and 3D visualizations that distinguish between linked views, embedded views, and mixed views. We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations. Finally, based on existing works, possible future research opportunities are explored and discussed.Comment: 23 pages,11 figure

A method for analyzing the revolute joint wear of planar multibody systems and its application in unbalance loading working condition

This paper develops an efficient method to describe the evolution of the revolute joint wear during the process of the mechanism movement. In the framework of multibody systems formulation, the prediction method of the revolute joint wear in different motion time interval is established by considering the wear ranges between the pin and the bushing on the basis of the Archard’s wear model. Then a typical non-planar mechanism with unbalancing loads acting on single non-ideal revolute joint is used to illustrate the application of the method. Moreover, the corresponding experimental mechanism is tested to validate the predicting results of the proposed method. The analysis shows that the method proposed is of high efficiency and can guarantee enough predicting accuracy when the predicted wear depth is not big. Therefore, the method is practical to a certain degree in engineering