Search

In this article, a universal and concise theoretical model is proposed to quantify the effect of gravity on packaging warpage by considering the competition between the thermal and chemical shrinkage of packaging materials and the flexural stiffness of packaging structures. Experimental study and finite element simulation for the warpage distributions of two fan-out panel-level packaging structures with sizes of 310 mm × 320 mm are carried out to verify the effectiveness of the proposed model. Under the ideal gravity-free condition, the warpage is proportional to the square of the packaging structure size. Under the gravity effect, the warpage follows a brief quartic expression of the packaging structure size. The gravity can reduce the bending moment in the structure and thereby lead to the decrease of the total warpage. For larger-size structures, the effect of gravity on warpage is more pronounced. It is found that the predictions by the model fit well with both experimental and simulation results. The theoretical model in our work can provide an effective tool to predict the warpage with consideration of the gravity effect and will promote further development and design of large-scale packaging structures. [ABSTRACT FROM AUTHOR]

Delay/disruption tolerant networking (DTN) was proposed as a networking architecture for reliable data delivery in space vehicle communications despite long propagation delays and/or lengthy link disruptions. As one of the main data transport protocols of DTN, Licklider transmission protocol (LTP) was proposed by the NASA for reliable data delivery in challenging space environments in which the existing transport protocols of DTN, TCP, and UDP do not perform effectively. Pair-wise comparisons among LTP, TCP, and UDP running in the DTN stack have previously been done using statistical methods; evaluation results and performance analysis are available in the existing LTP research literature. However, there is as yet no solid analytical model of LTP performance in the presence of link disruptions. In this paper, we present an analytical method to predict transmission performance of LTP for reliable file delivery in space vehicle communications with focus on the expected file delivery delay (or latency) over space channels characterized by random link disruptions. Realistic file-transmission experiments using a PC-based infrastructure are presented to validate the analytical models. The analysis and study results presented in this paper are expected to be useful in understanding the impact of transmission conditions and configurations, on the efficiency of LTP when deployed for reliable data delivery in space missions using communication links that are subject to frequent and random interruptions. [ABSTRACT FROM AUTHOR]

Delay/disruption tolerant networking (DTN) was proposed as a networking architecture for reliable data delivery despite an extremely long propagation delay and frequent/lengthy link disruptions. The challenging problem of mission control and data delivery in deep-space explorations is a typical application scenario of the DTN technology. Reliable data delivery of DTN relies heavily on its core bundle protocol (BP). Performance evaluation and improvement of BP for deep-space communications are presently underway. The setting of the retransmission time-out (RTO) timer of BP is critical for reliable and highly efficient file transfer in a deep-space communication environment. In this paper, we present analytical modeling of an optimal RTO timer interval for the best goodput performance of BP in deep-space communications characterized by a very long signal propagation delay and lossy data links. A model is developed to compute the RTO timer interval that will result in the best goodput performance of BP normalized with respect to the total data load transmitted in order to achieve successful delivery of an entire file. Experimental validation using a PC-based testbed indicates that the RTO timer interval indicated by the model achieves the best normalized goodput performance of BP. The model predicts performance in all the experimented scenarios. [ABSTRACT FROM AUTHOR]