Ni3Al-based superalloys have excellent mechanical properties which have been widely used in civilian and military fields. In this study, the mechanical properties of the face-centred cubic structure Ni3Al were investigated by a first principles study based on density functional theory (DFT), and the generalized gradient approximation (GGA) was used as the exchange-correlation function. The bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio of Ni3Al polycrystal were calculated by Voigt-Reuss approximation method, which are in good agreement with the existing experimental values. Moreover, directional dependences of bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio of Ni3Al single crystal were explored. In addition, the thermodynamic properties (e.g., Debye temperature) of Ni3Al were investigated based on the calculated elastic constants, indicating an improved accuracy in this study, verified with a small deviation from the previous experimental value.

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With the increase of the resolution of modern radars and other detection equipments, one target may produce more than one measurement. Such targets are referred to as extended targets. Recently, multiple extended target tracking (METT) has drawn a considerable attention. However, one crucial problem is how to partition the measurement sets accurately and rapidly. In this paper, an improved METT algorithm is proposed based on the Gaussian mixture probability hypothesis density (GM-PHD) filter and an effective partition method using spectral clustering technique. First, the density analysis technique is introduced to eliminate the disturbance of clutter, and then the spectral clustering technique based on neighbor propagation is used to partition the measurements. Finally, the GM-PHD filter is implemented to achieve the METT. Simulation results show that the proposed algorithm has a better performance, especially a better real-time performance, than the conventional distance partition and K-means++ methods.

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A new kind of industrial high temperature radar has been developed, which is used for real-time monitoring of the burden surface under the harsh environment inside blast furnace (BF) and observing the decline rate of the burden surface. This radar technology is also used for determination of the burden profile through multi-point arrangement of the radars. The 26GHz frequency radar is introduced with the FMSW structure of the hardware model, as well as the heat and dust resistant solid burden surface algorithm with the monitoring range of 0-100 meter and the measurement accuracy of 1%, a specially designed ceramic antenna with the temperature range of 0-600 degree, and the drift < 0.1% / year. Six industrial high temperature radars have been installed on the top of the BF at the industrial field, and optimized the radar installation location through electromagnetic simulation. The real-time image of the burden surface has been obtained by surface fitting and digital simulation of the data from the six-point radars. The effective application of this technology has improved significantly the fluctuation of burden surface, the production of BF, the energy saving and gas emission reduction.

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