A syncretic railway network (SRN) that comprises the railway, regional railway, and urban rail transit is the cornerstone for the socio-economic development of urban agglomerations. Most existing research studies consider a syncretic network as a single network, and therefore, they cannot capture the interdependent patterns in the network. Thus, the characteristics of interdependent node/edges and robustness of the interdependent critical infrastructure of the SRN remain under-researched. In this study, we investigated the critical infrastructure interdependent networks (CIINs) of the SRN. To this end, we designed a cascading failure model based on the real data of the CIINs of the SRN in the Chengdu–Chongqing urban agglomeration, and we examined the cascading failure in both the syncretic and single networks. Our results indicate that robustness decreased with increasing the number of layers for a targeted attack on the highest connected nodes of the theoretical coupled network. The robustness of the theoretical coupled network was inferior to that of the single-layer network, whereas the robustness of the actual network was contrary to this result. The robustness of the CIINs in the SRN with different coupled modes increased with an increase in the number of nodes/sections of the single-layer network forming the interdependent network. However, it decreased with an increasing number of interdependent nodes/sections. Further, the robustness of a load-based SRN was found to be extremely sensitive to the failure of higher-load stations, therefore, it is important to facilitate decision-making processes in the daily operations and emergency management of the SRN.

Train timetables play an important role in improving passenger services and transportation efficiency. The arrangement of maintenance windows directly affects the maintenance quality, which in turn interacts with the train timetable. In this study, we investigated the integrated optimization of maintenance windows and train timetables. We creatively abstracted the occupation of track capacity for maintenance activities as arcs and constructed an integrated space-time network for maintenance activities and trains. The initial model was converted into a multicommodity network flow model containing multiple types of arcs. Furthermore, we divided the problem into two subproblems: (1) the arrangement of major maintenance activities. (2) the integrated optimization of maintenance windows and train timetables for fixed maintenance activities. Heuristic algorithms based on the customized variable neighborhood search and the alternation direction method of multipliers framework were designed respectively to solve the aforementioned subproblems. The effectiveness and efficiency of the proposed model and algorithm are demonstrated through a series of practical case studies using data from the Wuchang-Zhuzhou Conventional railway.

The different rail transit systems, such as regional railway and urban rail transit, cooperate to form the syncretic railway network (SRN). With the rapid development of SRN, the limited transportation capacity is inadequate to meet the booming passenger flow during peak hours, where cascading failures caused by large passenger flow become a threat to SRN. This paper adopts a state equation to depict the failure‐restoration process and investigates detailed restoration strategies considering the characteristics of recoverable and repeatable failures of stations. Specifically, three different restoration strategies—spontaneous restoration strategy (SRS), active restoration strategy (ARS), and hybrid restoration strategy (HRS)—are proposed, and the varying effects of restoration time, restoration probability, restoration objective, and restoration priority for SRN with ARS are compared. These restoration strategies are applied to the actual SRN in Chengdu, where it is found that HRS has a better effect than other strategies. Furthermore, stations in the metro network with higher passenger flow allocate more restoration resources to improve the robustness of SRN, while the restoration effect of SRN increases noticeably with the restoration coefficient and the reserve coefficient. The restoration strategies presented in this paper can improve the safety management of SRN.

To study the performance and mutual influence of a syncretic railway network (SRN) that comprises high-speed railway, regional railway, and urban rail transit under the condition of traffic overload during peak hours, we discuss the interdependent characteristics on cascading overload failure of SRNs under the cooperative organization from the perspective of an interdependent network. However, most existing research on cascading failure in interdependent network ignores the inconsistency between the physical structure and transportation organization of the subnetwork in an actual network, in addition to the restrictions on the load redistribution strategy of stations and sections in the load-capacity model of the interdependent network; especially, the influence of transfer behavior on the load redistribution inter subnetwork. In this study, we investigate the robustness of an interdependent SRN under overload and risk propagation. We propose a partially interdependent network model of a multimode rail transit, develop a novel cascading overload failure model with tunable parameters of load redistribution inter subnetwork, and analyze interdependent characteristics, cascade failure process, and robustness of an SRN under multiscene conditions, i.e., different attack and load distribution strategies, via simulations. A case study of an SRN in the metropolitan area of Chengdu, China is presented; the results indicate that, when the reserve coefficient of the metro subnetwork is 0.4 and the overload coefficient of the regional railway subnetwork is greater than 1.2, the station reserve capacity and overload capacity of the SRN is appropriately improved. When passenger load increases to a certain range, the reserve and overload capacities of stations in the regional railway subnetwork do not considerably contribute to robustness. Thus, a surplus load distribution strategy is recommended to improve robustness. The results of this paper have considerable significance for the planning, structural optimization, and operation safety of SRNs.

It is challenging to precisely measure the slow interseismic crustal-deformation rate from Synthetic Aperture Radar (SAR) data. The long-wavelength orbital errors, owing to the uncertainties in satellite orbit vectors, commonly exist in SAR interferograms, which degrade the precision of the Interferometric SAR (InSAR) products and become the main barrier to extracting interseismic tectonic deformation. In this study, we propose a novel temporal-network orbital correction method that is able to isolate the far-fault tectonic deformation from the mixed long-wavelength signals based on its spatio–temporal characteristic. The proposed approach is straightforward in methodology but could effectively separate the subtle tectonic deformation from glaring orbital errors without ancillary data. Both synthetic data and real Sentinel-1 SAR images are used to validate the reliability and effectiveness of this method. The derived InSAR velocity fields clearly present the predominant left-lateral strike-slip motions of the Tuosuo Lake segment of the Kunlun fault in western China. The fault-parallel velocity differences of 5–6 mm/yr across the fault between areas ~50 km away from the fault trace are addressed. The proposed method presents a significantly different performance from the traditional quadratic approximate method in the far field. Through the implementation of the proposed method, the root mean square error (RMSE) between the LOS_GPS and our derived descending InSAR LOS (line of sight) measurements is reduced to less than one-third of the previous study, suggesting its potential to enhance the availability of InSAR technology for interseismic crustal-deformation measurement.