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Neutron irradiation effects on the microstructure of nuclear graphite have been investigated by X-ray diffraction on virgin and low doses (∼1.3 and ∼2.2 dpa), high temperature (750° C) irradiated samples. The diffraction patterns were interpreted using a model, which takes into account the turbostratic disorder. Besides the lattice constants, the model introduces two distinct coherent lengths in the c-axis and the basal plane, that characterise the volumes from which X-rays are scattered coherently. The methodology used in this work allows to quantify the effect of irradiation damage on the microstructure of nuclear graphite seen by X-ray diffraction. The results show that the changes of the deduced structural parameters are in agreement with previous observations from electron microscopy, but not directly related to macroscopic changes.
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Neutron irradiation effects on the microstructure of nuclear graphite have been investigated by X-ray diffraction on virgin and low doses (∼1.3 and ∼2.2 dpa), high temperature (750° C) irradiated samples. The diffraction patterns were interpreted using a model, which takes into account the turbostratic disorder. Besides the lattice constants, the model introduces two distinct coherent lengths in the c-axis and the basal plane, that characterise the volumes from which X-rays are scattered coherently. The methodology used in this work allows to quantify the effect of irradiation damage on the microstructure of nuclear graphite seen by X-ray diffraction. The results show that the changes of the deduced structural parameters are in agreement with previous observations from electron microscopy, but not directly related to macroscopic changes.
Journal article(2017)
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Zhao Zhou, Bart De Schutter, S. Lin, Y. Xi
Network-wide control of large-scale urban traffic networks using a hierarchical framework can be more efficient and flexible than centralized strategies for reducing the traffic congestion in big cities, because it can adequately address some problems that occur in controlling such large systems, e.g., computational complexity, multiple control objectives, weak robustness to uncertainties, and so on. In this paper, we propose a two-level hierarchical control framework for large-scale urban traffic networks. At the upper level, based on decomposing a heterogeneous traffic network into several homogeneous subnetworks, a higher level optimization problem using the concept of macroscopic fundamental diagram is formulated to deal with the traffic demand-balance problem. At the lower level, the controller with a more detailed traffic flow model for each subnetwork determines the optimal signal timing within the given region under the guidance of the upper-level controller through communication. For the application of this architecture in real time, the model-based predictive control approach is utilized so as to obtain the best solutions for both levels. Moreover, in order to decrease the computational complexity, a distributed control scheme within each subnetwork is developed at the lower level. The proposed approach is evaluated by simulation under different scenarios on a hypothetical urban traffic network, and the performance is compared with that of other control strategies
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Network-wide control of large-scale urban traffic networks using a hierarchical framework can be more efficient and flexible than centralized strategies for reducing the traffic congestion in big cities, because it can adequately address some problems that occur in controlling such large systems, e.g., computational complexity, multiple control objectives, weak robustness to uncertainties, and so on. In this paper, we propose a two-level hierarchical control framework for large-scale urban traffic networks. At the upper level, based on decomposing a heterogeneous traffic network into several homogeneous subnetworks, a higher level optimization problem using the concept of macroscopic fundamental diagram is formulated to deal with the traffic demand-balance problem. At the lower level, the controller with a more detailed traffic flow model for each subnetwork determines the optimal signal timing within the given region under the guidance of the upper-level controller through communication. For the application of this architecture in real time, the model-based predictive control approach is utilized so as to obtain the best solutions for both levels. Moreover, in order to decrease the computational complexity, a distributed control scheme within each subnetwork is developed at the lower level. The proposed approach is evaluated by simulation under different scenarios on a hypothetical urban traffic network, and the performance is compared with that of other control strategies