Preparation of ZrB_2-SiC Powders via Carbothermal Reduction of Zircon and Prediction of Product Composition by Back-Propagation Artificial Neural Network

Phase pure ZrB2-SiC composite powders were prepared after 1 450℃/3 h via carbothermal reduction route,by using ZrSiO4,B2O3 and carbon as the raw materials.The influences of firing temperature as well as the type and amount of additive on the phase composition of final products were detailedly investigated.The results indicated that the onset formation temperature of ZrB2-SiC was reduced to 1 400℃by the present conditions,and oxide additive（including CoSO4·7H2O,Y2O3 and TiO2）was effective in enhancing the decomposition of raw ZrSiO4,therefore accelerating the synthesis of ZrB2-SiC.Moreover,microstructural observation showed that the as-prepared ZrB2 and SiC respectively had well-defined hexagonal columnar and fibrous morphology.Furthermore,the methodology of back-propagation artificial neural networks（BP-ANNs）was adopted to establish a model for predicting the reaction extent（e g,the content of ZrB2-SiC in final product）in terms of various processing conditions.The results predicted by the as-established BP-ANNs model matched well with that of testing experiment（with a mean square error in 10^（-3） degree）,verifying good effectiveness of the proposed strategy.

Thermodynamic prediction of the composition of Fe-based amorphous alloys

The liquidus univariant lines of the Fe-Nb-B ternary system have been thermodynamically calculated by means of CALPHAD method and Fe-based thermodynamic data. It is found that there are two eutectic reactions in the Fe-rich corner,that is,（1） L（Fe-3Nb-15B） →α＋γ＋ M2B （1430 K）,and （2） L（Fe-10Nb-27B） → FeB ＋ Lc14 ＋ M2B （1575 K）. Moreover,the eutectic points are very close to the compositions with high glass forming ability determined experimentally. This means that it is feasible to design the compositions of multicomponent bulk metallic glasses by looking for the eutectic points in the Fe-Nb-B system by means of thermodynamic calculation.

Multi-Level Inverter Linear Predictive Phase Composition Strategy for UPQC

The power system is facing numerous issues when the distributed gen-eration is added to the existing system.The existing power system has not been planned with flawless power quality control.These restrictions in the power trans-mission generation system are compensated by the use of devices such as the Static Synchronous Compensator(STATCOM),the Unified Power Quality Con-ditioner(UPQC)series/shunt compensators,etc.In this work,UPQC’s plan with the joint activity of photovoltaic(PV)exhibits is proposed.The proposed system is made out of series and shunt regulators and PV.A boost converter connects the DC link to the PV source,allowing it to compensate for voltage sags,swells,vol-tage interferences,harmonics,and reactive power issues.In this paper,the fea-tures of a seven-level Cascaded H-Bridge Multi-Level idea are applied to shunt and series active filter changeovers to reduce Total Harmonic Distortion and com-pensate for voltage issues.Despite its power quality capacity for common cou-pling,the proposed system can inject the grid’s dynamic power.During voltage interference,it can also provide a piece of delicate burden power.The simulation is carried out with the help of MATLAB/SIMULINK programming,and the results are compared to those of other conventional methods.