The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and...The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.展开更多
Kirchhoff integral migration imaging is widely used in industrial production due to its advantages of not being limited by observation systems,good target imaging effects,and high computational efficiency.Vertical tra...Kirchhoff integral migration imaging is widely used in industrial production due to its advantages of not being limited by observation systems,good target imaging effects,and high computational efficiency.Vertical transversely isotropic(VTI)media,as a typical anisotropic media,has always been a primary focus of anisotropic migration imaging research.We focus on the problems of low accuracy and efficiency in travel-time calculations associated with conventional Kirchhoff integral migration for VTI media.A travel-time calculation method based on physical-informed neural network(PINN)for VTI media is introduced into the process of Kirchhoff integral migration imaging.Model experiments and field data processing have shown that the travel-time calculation based on PINN can significantly improve both the accuracy and efficiency when compared to traditional finite difference algorithms,there-by enabling high-precision Kirchhoff integral migration imaging for VTI media.展开更多
A new seismic ray-tracing method is put forward based on parabolic travel-time interpolation(PTI) method, which is more accurate than the linear travel-time interpolation (LTI) method. Both PTI method and LTI method a...A new seismic ray-tracing method is put forward based on parabolic travel-time interpolation(PTI) method, which is more accurate than the linear travel-time interpolation (LTI) method. Both PTI method and LTI method are used to compute seismic travel-time and ray-path in a 2-D grid cell model. Firstly, some basic concepts are introduced. The calculations of travel-time and ray-path are carried out only at cell boundaries. So, the ray-path is always straight in the same cells with uniform velocity. Two steps are applied in PTI and LTI method, step 1 computes travel-time and step 2 traces ray-path. Then, the derivation of LTI formulas is described. Because of the presence of refraction wave in shot cell, the formula aiming at shot cell is also derived. Finally, PTI method is presented. The calculation of PTI method is more complex than that of LTI method, but the error is limited. The results of numerical model show that PTI method can trace ray-path more accurately and efficiently than LTI method does.展开更多
Travel-time prediction has gained significance over the years especially in urban areas due to increasing traffic congestion. In this paper, the basic building blocks of the travel-time prediction models are discussed...Travel-time prediction has gained significance over the years especially in urban areas due to increasing traffic congestion. In this paper, the basic building blocks of the travel-time prediction models are discussed, with a small review of the previous work. A model for the travel-time prediction on freeways based on wavelet packet decomposition and support vector regression (WDSVR) is proposed, which used the multi-resolution and equivalent frequency distribution ability of the wavelet transform to train the support vector machines. The results are compared against the classical support vector regression (SVR) method. Our results indicated that the wavelet reconstructed coefficient when used as an input to the support vector machine for regression performed better (with selected wavelets only), when compared with the support vector regression model (without wavelet decomposition) with a prediction horizon of 45 minutes and more. The data used in this paper was taken from the California Department of Transportation (Caltrans) of District 12 with a detector density of 2.73, experiencing daily peak hours except most weekends. The data was stored for a period of 214 days accumulated over 5-minute intervals over a distance of 9.13 miles. The results indicated MAPE ranging from 12.35% to 14.75% against the classical SVR method with MAPE ranging from 12.57% to 15.84% with a prediction horizon of 45 minutes to 1 hour. The basic criteria for selection of wavelet basis for preprocessing the inputs of support vector machines are also explored to filter the set of wavelet families for the WDSVR model. Finally, a configuration of travel-time prediction on freeways is presented with interchangeable prediction methods.展开更多
In this paper,we derived the relationships between the travel time difference of sPn and Pn and the local earthquake focal depth.In these equations,the travel time difference of sPn and Pn is not related to the epicen...In this paper,we derived the relationships between the travel time difference of sPn and Pn and the local earthquake focal depth.In these equations,the travel time difference of sPn and Pn is not related to the epicentral distance,but depends only on the regional crustal mode and the focal depth.According to the equations,we provided a simple and accurate method to determine local earthquake focal depth by using the travel time difference between phase sPn and Pn.This method has been used to determine the focal depths of two earthquake of MS6.1 and MS5.6 which occurred at the junction of Panzhihua and Huili,Sichuan on August 30 and 31,2008.The results were compared to those from other sources such as the China Earthquake Networks Center,and the comparison shows that the results are accurate and reliable.展开更多
Teleseismic receiver functions and travel-time residuals along the north Hi-Climb broadband seismic array in the central-southern Qinghai-Tibet Plateau show that the lithosphere structures in the central and western Q...Teleseismic receiver functions and travel-time residuals along the north Hi-Climb broadband seismic array in the central-southern Qinghai-Tibet Plateau show that the lithosphere structures in the central and western Qinghai-Tibet Plateau are different. In the central Qinghai-Tibet Plateau, the Indian Plate is northward subducted beneath the Qiangtang block and arrives at the greatest depth beneath the central-southern Qiangtang block. The delaminated Indian lithospheric slab remains beneath the central Lhasa block to a depth possibly greater than that of the upper interface of the mantle transform zone. In the western Qinghai-Tibet Plateau, the Indian lithospheric plate is gently northward subducted and may have arrived to the south of Tarim plate. Due to the resistance from the gently northward subduction of the Indian mantle lithosphere in the western Qinghai-Tibet Plateau, the upwelling mantle material be-neath the Qiangtang block moves mostly toward the east to bring about the lateral eastward flow of the deep mantle hot material in the central Qinghai-Tibet Plateau.展开更多
【目的】随着网联自动驾驶技术的不断发展,未来较长一段时间内将呈现网联自动驾驶汽车(connected and autonomous vehicle, CAV)与人工驾驶汽车(human driven vehicle, HDV)混行的交通环境。由于CAV与HDV的驾驶特性及路径选择行为存在...【目的】随着网联自动驾驶技术的不断发展,未来较长一段时间内将呈现网联自动驾驶汽车(connected and autonomous vehicle, CAV)与人工驾驶汽车(human driven vehicle, HDV)混行的交通环境。由于CAV与HDV的驾驶特性及路径选择行为存在较大差异,加之实际交通需求是随机变化的,为准确预测网络均衡流模式,本文开展人机混驾环境下考虑随机需求的混合交通分配研究。【方法】首先,假定交通需求服从对数正态分布,分析了CAV和HDV两类用户的路径流量与路段流量分布特征,并基于BPR(Bureau of Public Roads)型路段阻抗函数推导了对数正态需求下的路径出行时间预算。然后,假定CAV和HDV分别基于实际出行时间预算和感知出行时间预算选择路径,针对人机混驾环境,构建了考虑全局需求弹性的基于可靠性的用户均衡与随机用户均衡(reliability-based user equilibrium and reliability-based stochastic user equilibrium, RUE-RSUE)混合交通分配变分不等式模型,并设计了双层循环算法对模型进行求解。最后,采用Nguyen-Dupuis网络对本文构建的模型与算法进行验证,并分析了CAV市场渗透率、出行时间可靠度需求及交通需求变异系数对网络均衡流模式的影响。【结果】本文设计的双层循环算法能有效求解考虑全局需求弹性的RUE-RSUE混合交通分配模型;出行时间预算随CAV市场渗透率的增加而减少,随交通需求变异系数和出行时间可靠度需求的增加而增加,但受CAV市场渗透率和交通需求波动的影响较显著;交通需求随出行时间可靠度需求的提高而降低,提高CAV市场渗透率会增加相同敏感度下的交通需求,但出行时间可靠性敏感度对交通需求的影响更为显著。【结论】本研究提出的RUE-RSUE混合交通分配模型能够刻画需求随机性对CAV和HDV两类用户路径选择的影响,可为智能网联交通系统的规划与管理提供决策依据。展开更多
基金supported by the National Key Research and Development Program of China(2023YFC3008605)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021002)the Seismological Research Foundation for Youths of Guangdong Earthquake Agency(Open Funding Project of Key Laboratory of Earthquake Monitoring and Disaster Mitigation Technology,China Earthquake Administration)(GDDZY202309)。
文摘The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network,relative to the 1D South China travel-time model,were determined using joint hypocentral determination(JHD)and statistical analysis methods.The travel-time corrections for the Pg phase of 72 stations range between-0.25 s and 0.14 s,while the corrections for the Sg phase range between 0.27 s and 0.35 s,and those for the Pn phase are between-0.86 s and 0.07 s.The spatial distribution of travel-time corrections for Pg,Sg,and Pn phases of 72 stations correlates well with the geological structure in this region.This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model.These corrections empirically compensate for systematic travel-time errors arising from such discrepancies.The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt.These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho.By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm,test results showed an obvious improvement in location accuracy and origin time precision for explosion events.The variation of horizontal distance between repeating earthquake pairs has also improved,with 86%of the repeating earthquake pair spacing being more accurately estimated after correction.This suggests the crucial significance of travel-time correction in earthquake location,and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.
基金funded by the Open Fund of No.1 Institute of Geology and Mineral Resources of Shan-dong Province(No.2022DY03)the National Natural Sci-ence Foundation of China(Nos.42074138 and 42206195)the Wenhai Program of the ST Fund of Laoshan Labo-ratory(No.LSKJ202204803).
文摘Kirchhoff integral migration imaging is widely used in industrial production due to its advantages of not being limited by observation systems,good target imaging effects,and high computational efficiency.Vertical transversely isotropic(VTI)media,as a typical anisotropic media,has always been a primary focus of anisotropic migration imaging research.We focus on the problems of low accuracy and efficiency in travel-time calculations associated with conventional Kirchhoff integral migration for VTI media.A travel-time calculation method based on physical-informed neural network(PINN)for VTI media is introduced into the process of Kirchhoff integral migration imaging.Model experiments and field data processing have shown that the travel-time calculation based on PINN can significantly improve both the accuracy and efficiency when compared to traditional finite difference algorithms,there-by enabling high-precision Kirchhoff integral migration imaging for VTI media.
文摘A new seismic ray-tracing method is put forward based on parabolic travel-time interpolation(PTI) method, which is more accurate than the linear travel-time interpolation (LTI) method. Both PTI method and LTI method are used to compute seismic travel-time and ray-path in a 2-D grid cell model. Firstly, some basic concepts are introduced. The calculations of travel-time and ray-path are carried out only at cell boundaries. So, the ray-path is always straight in the same cells with uniform velocity. Two steps are applied in PTI and LTI method, step 1 computes travel-time and step 2 traces ray-path. Then, the derivation of LTI formulas is described. Because of the presence of refraction wave in shot cell, the formula aiming at shot cell is also derived. Finally, PTI method is presented. The calculation of PTI method is more complex than that of LTI method, but the error is limited. The results of numerical model show that PTI method can trace ray-path more accurately and efficiently than LTI method does.
文摘Travel-time prediction has gained significance over the years especially in urban areas due to increasing traffic congestion. In this paper, the basic building blocks of the travel-time prediction models are discussed, with a small review of the previous work. A model for the travel-time prediction on freeways based on wavelet packet decomposition and support vector regression (WDSVR) is proposed, which used the multi-resolution and equivalent frequency distribution ability of the wavelet transform to train the support vector machines. The results are compared against the classical support vector regression (SVR) method. Our results indicated that the wavelet reconstructed coefficient when used as an input to the support vector machine for regression performed better (with selected wavelets only), when compared with the support vector regression model (without wavelet decomposition) with a prediction horizon of 45 minutes and more. The data used in this paper was taken from the California Department of Transportation (Caltrans) of District 12 with a detector density of 2.73, experiencing daily peak hours except most weekends. The data was stored for a period of 214 days accumulated over 5-minute intervals over a distance of 9.13 miles. The results indicated MAPE ranging from 12.35% to 14.75% against the classical SVR method with MAPE ranging from 12.57% to 15.84% with a prediction horizon of 45 minutes to 1 hour. The basic criteria for selection of wavelet basis for preprocessing the inputs of support vector machines are also explored to filter the set of wavelet families for the WDSVR model. Finally, a configuration of travel-time prediction on freeways is presented with interchangeable prediction methods.
基金funded by the special support projectentitled "Sorting out and processing of seismic data " of central public-interest basic scientific and technological research of Institute of Crustal DynamicsChina Earthquake Administration (ZDJ2007-4)
文摘In this paper,we derived the relationships between the travel time difference of sPn and Pn and the local earthquake focal depth.In these equations,the travel time difference of sPn and Pn is not related to the epicentral distance,but depends only on the regional crustal mode and the focal depth.According to the equations,we provided a simple and accurate method to determine local earthquake focal depth by using the travel time difference between phase sPn and Pn.This method has been used to determine the focal depths of two earthquake of MS6.1 and MS5.6 which occurred at the junction of Panzhihua and Huili,Sichuan on August 30 and 31,2008.The results were compared to those from other sources such as the China Earthquake Networks Center,and the comparison shows that the results are accurate and reliable.
基金the National Basic Research Program of China (Grant No.2004CB418401)
文摘Teleseismic receiver functions and travel-time residuals along the north Hi-Climb broadband seismic array in the central-southern Qinghai-Tibet Plateau show that the lithosphere structures in the central and western Qinghai-Tibet Plateau are different. In the central Qinghai-Tibet Plateau, the Indian Plate is northward subducted beneath the Qiangtang block and arrives at the greatest depth beneath the central-southern Qiangtang block. The delaminated Indian lithospheric slab remains beneath the central Lhasa block to a depth possibly greater than that of the upper interface of the mantle transform zone. In the western Qinghai-Tibet Plateau, the Indian lithospheric plate is gently northward subducted and may have arrived to the south of Tarim plate. Due to the resistance from the gently northward subduction of the Indian mantle lithosphere in the western Qinghai-Tibet Plateau, the upwelling mantle material be-neath the Qiangtang block moves mostly toward the east to bring about the lateral eastward flow of the deep mantle hot material in the central Qinghai-Tibet Plateau.
文摘【目的】随着网联自动驾驶技术的不断发展,未来较长一段时间内将呈现网联自动驾驶汽车(connected and autonomous vehicle, CAV)与人工驾驶汽车(human driven vehicle, HDV)混行的交通环境。由于CAV与HDV的驾驶特性及路径选择行为存在较大差异,加之实际交通需求是随机变化的,为准确预测网络均衡流模式,本文开展人机混驾环境下考虑随机需求的混合交通分配研究。【方法】首先,假定交通需求服从对数正态分布,分析了CAV和HDV两类用户的路径流量与路段流量分布特征,并基于BPR(Bureau of Public Roads)型路段阻抗函数推导了对数正态需求下的路径出行时间预算。然后,假定CAV和HDV分别基于实际出行时间预算和感知出行时间预算选择路径,针对人机混驾环境,构建了考虑全局需求弹性的基于可靠性的用户均衡与随机用户均衡(reliability-based user equilibrium and reliability-based stochastic user equilibrium, RUE-RSUE)混合交通分配变分不等式模型,并设计了双层循环算法对模型进行求解。最后,采用Nguyen-Dupuis网络对本文构建的模型与算法进行验证,并分析了CAV市场渗透率、出行时间可靠度需求及交通需求变异系数对网络均衡流模式的影响。【结果】本文设计的双层循环算法能有效求解考虑全局需求弹性的RUE-RSUE混合交通分配模型;出行时间预算随CAV市场渗透率的增加而减少,随交通需求变异系数和出行时间可靠度需求的增加而增加,但受CAV市场渗透率和交通需求波动的影响较显著;交通需求随出行时间可靠度需求的提高而降低,提高CAV市场渗透率会增加相同敏感度下的交通需求,但出行时间可靠性敏感度对交通需求的影响更为显著。【结论】本研究提出的RUE-RSUE混合交通分配模型能够刻画需求随机性对CAV和HDV两类用户路径选择的影响,可为智能网联交通系统的规划与管理提供决策依据。
