Mechanical deicing is a method to remove the ice on the pavement surface, and the ice strength directly affects the difficulty and effectiveness of the mechanical deicing. This paper aims to investigate the compression strength of ice to facilitate the deicing equipment to crush ice. In this paper, a large-scale freezing laboratory is employed to simulate low-temperature environment, and the uniaxial unconfined compressive tests of artificial freshwater ice under different temperature conditions are carried out through the uniaxial loading system. The compressive strength and modulus of ice are obtained when the substrate is asphalt pavement. The test result shows that the ice compressive strength and modulus respectively distribute from 0.36 to 3.67 MPa and 11.7 to 359.1 MPa when ice temperature varies from −0.7 to −7.5 • C. The relations between ice temperature and compressive strength are approximately in a linear manner, while the relation of compressive modulus and ice temperature shows good power function and exponential relationships, respectively, when ice temperature ranges from −8 to −5 • C and from −5 to 0 • C. Furthermore, the failure mechanism of ice under relatively lower temperature is due to the development of cut-through cracks inside the ice. The failure mode divides into shear failure and ductile failure and the failure ice is mainly composed of large ice strips and bulks. For the ice with relatively higher temperature especially the ice close to melting point temperature, the ice failure mode is compressive and ductile, and the failure ice is mainly composed of granular ice crystals.

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Nodes in the Internet of Things of oil and gas pipelines are linearly distributed according to the direction of pipelines, so it is difficult to realize timely and large-scale battery replacement. Therefore, effective energy management has always been a key factor restricting the performance of the IoT of oil and gas pipelines.In addition, the end-to-end delay determines the response time of pipeline safety accidents and is also a key parameter to improve the real-time performance of the network. Considering energy effciency and delay comprehensively, this paper proposes PIOT-LPRP (Pipeline Internet of Things - Low Power Routing Protocol) protocol. The remaining energy of nodes and the distance between nodes and sink nodes are used as indicators to select candidate forwarding nodes in opportunistic routing to achieve energy balance in the network. The use of energy collection technology to extend the service life of the network. By choosing the node which is far away from the transmission as the forwarding node, the number of hops of data transmission can be effectively reduced, so as to reduce the end-to-end delay of the network. The simulation results show that PIOT-LPRP can effectively take into account the network life and network latency, and improve the network performance, by comparing with the classical opportunistic routing protocol EXOR, the same type of protocol RE-OR, and the HER protocol using energy harvesting technology.