Based on the hypothesis of the fractal distribution of crack sizes in brittle materials and the weakest link principle, the relationship between the fractal dimension of the size-frequency distribution of cracks and t...Based on the hypothesis of the fractal distribution of crack sizes in brittle materials and the weakest link principle, the relationship between the fractal dimension of the size-frequency distribution of cracks and the Weibull Modulus is derived, which reveals the geometrical nature of the Weibull Modulus. The influences of the size distribution and the orientation distribution of cracks as well as the irregularity of the crack propagation on the strength are all taken into account. Finally, a general expression for the statistical strength of brittle materials in complex tensile stress state is obtained.展开更多
With the rapid evolution of WSNs technology,it is very important to evaluate link quality quickly and accurately,so that the routing protocols can take relevant strategies in time to keep the entire network working st...With the rapid evolution of WSNs technology,it is very important to evaluate link quality quickly and accurately,so that the routing protocols can take relevant strategies in time to keep the entire network working steadily and efficiently. However,the issue of improving link quality assessment methods on physical layer is still open to research. To tackle this issue,a novel link quality assessment metric called S 3 LQA is proposed,which estimates the link quality of wireless sensor networks by CC2420 wireless radio frequency transceiver principles and free space propagation theory. The metric adopts both complete and incomplete packages to improve the evaluation performance effectively based on IEEE802. 15. 4 frame format and DSSS-O-QPSK mechanism. The experimental results show that the proposed method can improve energy cost and achieves better real-timing performance than traditional counting-based ( PRR) link quality assessment metric.展开更多
A novel link adaptation scheme using linear Auto Regressive (AR) model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the...A novel link adaptation scheme using linear Auto Regressive (AR) model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength (RSS) is measured and the time when rate is selected. The best rate is selected based on data pay load length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed scheme.展开更多
文摘Based on the hypothesis of the fractal distribution of crack sizes in brittle materials and the weakest link principle, the relationship between the fractal dimension of the size-frequency distribution of cracks and the Weibull Modulus is derived, which reveals the geometrical nature of the Weibull Modulus. The influences of the size distribution and the orientation distribution of cracks as well as the irregularity of the crack propagation on the strength are all taken into account. Finally, a general expression for the statistical strength of brittle materials in complex tensile stress state is obtained.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61262020)Aeronautical Science Foundation of China(Grant No.2010ZC56008 and 2012ZC56006)Key Technology R&D Program of Jiangxi Province(Grant No.2009BGA01000 and 20111BBE50030)
文摘With the rapid evolution of WSNs technology,it is very important to evaluate link quality quickly and accurately,so that the routing protocols can take relevant strategies in time to keep the entire network working steadily and efficiently. However,the issue of improving link quality assessment methods on physical layer is still open to research. To tackle this issue,a novel link quality assessment metric called S 3 LQA is proposed,which estimates the link quality of wireless sensor networks by CC2420 wireless radio frequency transceiver principles and free space propagation theory. The metric adopts both complete and incomplete packages to improve the evaluation performance effectively based on IEEE802. 15. 4 frame format and DSSS-O-QPSK mechanism. The experimental results show that the proposed method can improve energy cost and achieves better real-timing performance than traditional counting-based ( PRR) link quality assessment metric.
基金Partly supported by the National Hi-Tech Research and Development Program of China (863 Program) (No.2003AA143040).
文摘A novel link adaptation scheme using linear Auto Regressive (AR) model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength (RSS) is measured and the time when rate is selected. The best rate is selected based on data pay load length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed scheme.
基金financial support from the National Natural Science Foundation of China(NSFC,21875155)the support of National Key Research and Development Program of China(2021YFA1201502)the support of Nanqiang Young Top-notch Talent Fellowship in Xiamen University。