Three kinds of nano-concrete, i.e., 2.0% nano-SiO2 doped, 2.0% nano-CaCO3 doped and 1.0% nano-SiO2-1.0% nano-CaCO3 co-doped concretes (NS, NC, NSC) were prepared for a study on static property and dynamic property under different strain rates (50–130 s−1) using HYY series hydraulic servo test system and Φ100 mm split Hopkinson pressure bar test system, and a comparison with plain concrete (PC) as well. The results have shown that under static load, as compared with PC, NC has both strength and elastic modulus increased obviously, while NS has strength decreased and elastic modulus increased, and under dynamic load, there is an obvious strain rate effect for the dynamic compressive strength, impact toughness, energy dissipation and impact failure mode of concrete. Under the same strain rate, the dynamic compressive strength, peak strain, impact toughness and energy dissipation of NC are significantly increased, while its dynamic elastic modulus is decreased. Compared with PC, NS has dynamic compressive strength, peak strain, impact toughness and energy dissipation decreased, and dynamic elastic modulus increased, NC has static and dynamic mechanical properties improved, NS has static and dynamic mechanical properties weakened, and NSC is between PC and NC in static and dynamic mechanical properties, but generally improved. Doped with nano-CaCO3, NC has compactness improved, weak areas reduced, and pore size distribution optimized, while doped with nano-SiO2, NS has obvious internal weak areas, with pore structure degraded.

As an important part of scientific management, network planning technique has a very wide range of applications. In big data environment, network planning technique still has a significant role. The estimation of the activity time is the important aspects of the network planning technique. The three-point time estimation method is a commonly used method to estimate the time of activity. However, there are many shortcomings in the estimation method. On the basis of the traditional estimation method and the big data environment, this paper proposes a method based on cluster analysis. In this paper, the method of estimating the time of activity in the big data environment are beneficial to estimate the activity time so as to shorten the construction period.

In order to improve the microwave deicing efficiency of airport road surface concrete, the method of incorporating carbon fiber materials of different doping amounts and lengths into concrete is proposed. The test method is optimized by using a fiber-optic temperature sensor and a self-developed open microwave deicing vehicle, and the effect of the coupling effect of different carbon fiber doping and length on the microwave deicing efficiency of concrete is studied. The results of the study show that the appropriate amount of carbon fiber blended into the concrete can significantly improve the microwave deicing efficiency, and the reasonable use of carbon fiber-modified concrete can achieve the purpose of efficient deicing of the airport road surface. By analyzing the temperature rise curve, temperature rise rate curve, deicing effect, and infrared thermography of the microwave deicing process, combined with the “heat generation-heat dissipation” theory, the microwave deicing is divided into four stages: concrete wave absorption, water layer formation, ice thinning, and ice breaking and ice melting. In the process of microwave deicing of concrete, changing the length of carbon fiber and the amount of doping will have a greater impact on the rate of temperature rise and deicing range, but the shape of deicing remains basically the same, mainly spindle-shaped. When the length of carbon fiber is short, it is not conducive to the absorption of microwave by concrete, and with the increase of fiber length and doping amount, the wave absorption performance of carbon fiber-modified concrete on the airport road surface is gradually improved; when the fiber length is 0.6 cm and the fiber doping amount is 2‰, the wave absorption performance is the best, and the deicing rate is 1.82 times of ordinary concrete, and the deicing area is 1.2 times of ordinary concrete.