In the Pearl River Delta (PRD), there is severe competition between container ports, particularly those in Hong Kong, Shenzhen, and Guangzhou, for collecting international maritime container cargo. In addition, the se...In the Pearl River Delta (PRD), there is severe competition between container ports, particularly those in Hong Kong, Shenzhen, and Guangzhou, for collecting international maritime container cargo. In addition, the second phase of the Nansha terminal in Guangzhou’s port and the first phase of the Da Chang Bay container terminal in Shenzhen opened last year. Under these circumstances, there is an increasing need to quantitatively measure the impact these infrastructure investments have on regional cargo flows. The analysis should include the effects of container terminal construction, berth deepening, and access road construction. The authors have been developing a model for international cargo simulation (MICS) which can simulate the movement of cargo. The volume of origin-destination (OD) container cargo in the East Asian region was used as an input, in order to evaluate the effects of international freight transportation policies. This paper focuses on the PRD area and, by incorporating a more detailed network, evaluates the impact of several infrastructure investment projects on freight movement.展开更多
Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct d...Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct detection.Thus,the detection has to be done in a short timescale with small numbers of muons to satisfy the demands of practical applications.Method In this paper,we propose an artificial neural network(ANN)algorithm for material discrimination using MST.The muon scattering angles were simulated using Geant4 to formulate the training set,and the muon scatter angles were measured by Micromegas detection system to create the test set.Results The ANN-based algorithm presented here ensures a discrimination accuracy of 98.0%between aluminum,copper and tungsten in a 5 min measurement of 4×4×4 cm^(3)blocks.展开更多
文摘In the Pearl River Delta (PRD), there is severe competition between container ports, particularly those in Hong Kong, Shenzhen, and Guangzhou, for collecting international maritime container cargo. In addition, the second phase of the Nansha terminal in Guangzhou’s port and the first phase of the Da Chang Bay container terminal in Shenzhen opened last year. Under these circumstances, there is an increasing need to quantitatively measure the impact these infrastructure investments have on regional cargo flows. The analysis should include the effects of container terminal construction, berth deepening, and access road construction. The authors have been developing a model for international cargo simulation (MICS) which can simulate the movement of cargo. The volume of origin-destination (OD) container cargo in the East Asian region was used as an input, in order to evaluate the effects of international freight transportation policies. This paper focuses on the PRD area and, by incorporating a more detailed network, evaluates the impact of several infrastructure investment projects on freight movement.
基金supported by the Program of National Natural Science Foundation of China Grant Nos.11805168 and 21805251
文摘Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct detection.Thus,the detection has to be done in a short timescale with small numbers of muons to satisfy the demands of practical applications.Method In this paper,we propose an artificial neural network(ANN)algorithm for material discrimination using MST.The muon scattering angles were simulated using Geant4 to formulate the training set,and the muon scatter angles were measured by Micromegas detection system to create the test set.Results The ANN-based algorithm presented here ensures a discrimination accuracy of 98.0%between aluminum,copper and tungsten in a 5 min measurement of 4×4×4 cm^(3)blocks.
