Geophysical mass flows are not only critical surface processes and landscape features on the Earth and other planets,but also rank among the most frequent and hazardous natural disasters on the Earth,posing significan...Geophysical mass flows are not only critical surface processes and landscape features on the Earth and other planets,but also rank among the most frequent and hazardous natural disasters on the Earth,posing significant threats to life,property,and the environment.Numerical simulation is one of the most effective methods for understanding the mobility characteristics of geophysical mass flows and assessing the associated risks.In this study,a sliding-block model is proposed,based on mixture theory and continuum mechanics.The model employs a simplified framework that integrates the principles of material characteristic homogenization,mechanical behavior differentiation,and property parameter inheritability.The model's performance has been validated through comparisons with the analytical solution of a one-dimensional dam-break problem,experimental results from aluminum bar collapse tests,USGS debris flow flume experiments,and a loess flowslide involving entrainment.The findings demonstrate the model's ability to accurately replicate key aspects,including the accumulation patterns of dry noncohesive grain collapse,the dynamics of saturated debris flows,and the behavior of loess flowslides.Crucial motion characteristics,such as accumulation thickness,runout distance,front position,front arrival time,and the location and depth of erodible material,are effectively captured.Direct comparisons and error analyses reveal that the model performs exceptionally well across all scenarios tested.The homogenized sliding-block model shows strong potential as a robust tool for simulating dynamic processes and assessing landslide risks.展开更多
We propose a trellis-compressed maximum likelihood sequence estimation(TC-MLSE)-assisted sliding-block decision feedback equalizer(DFE)to suppress the error propagation resulting from the DFE in high-speed systems.We ...We propose a trellis-compressed maximum likelihood sequence estimation(TC-MLSE)-assisted sliding-block decision feedback equalizer(DFE)to suppress the error propagation resulting from the DFE in high-speed systems.We use an out-ofrange detector to detect the end of burst errors from the DFE and activate the optional TC-MLSE to correct burst errors.We conduct experiments to transmit a 201-Gbit/s PAM-8 signal.The results show that the proposed method achieves a bit error rate of 3.65×10^(-3),which is close to that of MLSE.The optional MLSE is only activated when needed and processes 11.4%of the total symbols.Moreover,the proposed method compresses the maximum length of burst errors from 19 to 5.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42090053)the National Key Research and Development Program of China(Grant No.2022YFC3003401).
文摘Geophysical mass flows are not only critical surface processes and landscape features on the Earth and other planets,but also rank among the most frequent and hazardous natural disasters on the Earth,posing significant threats to life,property,and the environment.Numerical simulation is one of the most effective methods for understanding the mobility characteristics of geophysical mass flows and assessing the associated risks.In this study,a sliding-block model is proposed,based on mixture theory and continuum mechanics.The model employs a simplified framework that integrates the principles of material characteristic homogenization,mechanical behavior differentiation,and property parameter inheritability.The model's performance has been validated through comparisons with the analytical solution of a one-dimensional dam-break problem,experimental results from aluminum bar collapse tests,USGS debris flow flume experiments,and a loess flowslide involving entrainment.The findings demonstrate the model's ability to accurately replicate key aspects,including the accumulation patterns of dry noncohesive grain collapse,the dynamics of saturated debris flows,and the behavior of loess flowslides.Crucial motion characteristics,such as accumulation thickness,runout distance,front position,front arrival time,and the location and depth of erodible material,are effectively captured.Direct comparisons and error analyses reveal that the model performs exceptionally well across all scenarios tested.The homogenized sliding-block model shows strong potential as a robust tool for simulating dynamic processes and assessing landslide risks.
基金This work was supported by the National Natural Science Foundation of China(NSFC)(Nos.62301128,61871082,and 62111530150)the Open Fund of IPOC(BUPT)(No.IPOC2020A011)+1 种基金the STCSM(No.SKLSFO2021-01)the Fundamental Research Funds for the Central Universities(Nos.ZYGX2020ZB043 and ZYGX2019J008).
文摘We propose a trellis-compressed maximum likelihood sequence estimation(TC-MLSE)-assisted sliding-block decision feedback equalizer(DFE)to suppress the error propagation resulting from the DFE in high-speed systems.We use an out-ofrange detector to detect the end of burst errors from the DFE and activate the optional TC-MLSE to correct burst errors.We conduct experiments to transmit a 201-Gbit/s PAM-8 signal.The results show that the proposed method achieves a bit error rate of 3.65×10^(-3),which is close to that of MLSE.The optional MLSE is only activated when needed and processes 11.4%of the total symbols.Moreover,the proposed method compresses the maximum length of burst errors from 19 to 5.
