No abstract

Graphene oxide (GO) has obvious desensitizing effect on the thermal decomposition of energetic materials such as HMX, CL-20, etc. 4,4′-Azo-1,2,4-triazole (ATRZ) is known as a new type of energetic material with high N content; the underlying thermal decomposition mechanism of graphene oxide−ATRZ (GO−ATRZ) complex with low sensitivity has not been studied. The present work studies the thermal decomposition mechanisms of GO, ATRZ,and the GO−ATRZ complex (the number of carboxyl groups on GO:ATRZ = 2:1) by the ReaxFF molecular reactive dynamic simulations and kinetics calculations. As a result, it has been found that the main decomposition pathway of GO is the exfoliation of hydroxyl and carboxyl groups on the graphene sheet, whereas ATRZ breaks its fivemembered ring as the main decomposition path, and the ring further decomposes into small molecules, such as CHN, N 2 , HN 2 , H 2 N 2 , etc. The major effect of GO on ATRZ is probably derived from the stable graphene sheet, which has a space effect on ATRZ, and the strong oxidizing hydroxyl groups produced during GO decomposition, which results in the formation of CON and CHON. By calculating the activation energy of N 2 generation in the reactions, it can be concluded that the addition of GO can increase the decomposition activation energy of ATRZ (41.1 kJ•mol −1 ) in comparison with that of its pure substance (25.0 kJ•mol −1 ). Therefore, GO can be combined with ATRZ as a desensitizer where GO can improve the molecular stability of ATRZ.

Control melt flow in tundish is very important for clean steel production. To explore the fluid flow mechanism, the RTD curves and its data, velocity vector fields and streamlines of the molten steel, and the relationship between the RTD curves and flow pattern in a single-strand slab caster tundish with a capacity of 30 tons have been investigated by both hydrodynamic and mathematical simulations. The RTD data and flow field of the original tundish have been studied in a 1:3 reduced scale hydrodynamic model. Meanwhile, the streamlines, velocity vector fields and the RTD data of the ratio of width to length (W/L) in tundish are mathematically simulated. In order to descript the flow pattern better, a new method is proposed to calculate the data of RTD curves with double peaks. The results showed that the RTD curves changed from double peaks to single peak with the increasing of the W/L in tundish. Both hydrodynamic and mathematical simulations results suggest that the W/L in tundish is the most important factor to change the flow pattern actually, that is, the short-circuiting flow disappeared with the increase of the W/H in tundish gradually. Furthermore, we have elaborated the mechanism the RTD curves change from double peaks to single peak. With increasing W/L, the wide-side walls play an important role to retard the short-circuiting flow on the inlet-outlet plane straight towards the outlet. Meanwhile, the dead region and its volume fraction are also the objects of our attention and exploration.KEY WORDS: tundish; a single-strand slab caster; flow mechanism; RTD curve; single peak; double peaks.

In this work, the primary thermal decomposition mechanism of 1,1-diamino-2,2-dinitroethylene (FOX-7) was studied by ReaxFF molecular dynamics simulations and online photoionization mass spectrometry.

Adverse geologies are often encountered during tunnel construction, which could seriously endanger the construction. To ensure the safety, it is essential to detect adverse geologies and their water‐bearing situation ahead the tunnel face. Ground‐penetrating radar is a suitable instrument, but the accurate interpretation of its detection results is difficult. In this paper, at first, an improved back projection imaging algorithm is proposed, which can make reflection waves closer to the real geological boundaries with few artificial clutters. And then, forward modelling of ground‐penetrating radar is carried out for typical adverse geologies, such as karst caves, faults, fractured rock masses, fracture network, and water‐bearing body. Their corresponding response features are obtained, accumulating experience for geological interpretation. The above two methods provide the basis for target identification and geological interpretation. In the last part, the application of the above two methods in several engineering cases are given, and their effectiveness is verified.