Estimating the charge burning velocity within a hydrogen-enriched gasoline engine

This paper proposed a feasible method for estimating the turbulent burning velocity of gasoline/hydrogen blends in a spark-ignited (SI) engine based on the cumulative heat release fraction, engine speed and engine geometry. The experiment was conducted on a naturally-aspirated port-injection gasoline engine equipped with a hydrogen injection system. The engine was run at 1400 rpm with different loads and hydrogen volume fractions in the intake gas. The test results showed that the addition of hydrogen benefited increasing the burning velocity and advancing the relevant crank angle for the peak burning velocity, due to the high burning and diffusion velocities of hydrogen. At 1400 rpm, a manifolds absolute pressure of 61.5 kPa and stoichiometric conditions, the peak burning velocity was raised from 11.6 to 12.3 and 14.6 m/s, and the relevant crank angle for the peak burning velocity was advanced from 21.0 to 14.0 and 8.6 ^oCA when the hydrogen volume fraction in the intake increased from 0% to 3% and 6%, respectively. Moreover, the effect of hydrogen addition on enhancing the burning velocity of a gasoline engine was more pronounced at low loads than that at high loads.     

黄金冶炼萃余液废水资源化及中和渣减量技术研究

黄金湿法冶炼行业铜萃余液中含有大量铜锌有价金属,现有处理工艺无法对有价金属进行回收,且产生大量中和渣,实现废水的资源化利用以及中和渣减量是未来的发展趋势。本文以某黄金湿法冶炼企业产生的萃余液废水为原水,采用“石膏+硫化收铜+硫化收锌+HDS中和”工艺实现有价金属有效回收和中和渣减量。实验结果表明：萃余液石膏pH为2、第一步0.5倍理论投加量硫化、第二步1倍理论投加量硫化可以最大限度实现铜锌的回收和中和渣减量,硫化铜渣铜品位为45.2%,符合《铜精矿》(YST 318-2007)中“铜精矿三级标准”,硫化锌渣锌品位为57.6%,符合《锌精矿》(YS/T 320-2014)中“锌精矿二级产品”标准,中和渣减量可达30%。     

Effects of starting powder on microstructure and thermal conductivity of pressureless-sintered fully ceramic microencapsulated fuels

The effects of the starting SiC powder (α or β) with the addition of 5.67 wt% AlN–Y₂O₃–CeO₂–MgO additives on the residual porosity and thermal conductivity of fully ceramic microencapsulated (FCM) fuels were investigated. FCM fuels containing ～41 vol% and ～37 vol% tristructural isotropic (TRISO) particles could be sintered at 1870 °C using α-SiC and β-SiC powders, respectively, via a pressureless sintering route. The residual porosities of the SiC matrices in the FCM fuels prepared using the α-SiC and β-SiC powders were 1.1% and 2.3%, respectively. The thermal conductivities of FCM pellets with ～41 vol% and ～37 vol% TRISO particles (prepared using the α-SiC and β-SiC powders, respectively) were 59 and 41 Wm^?1K^?1, respectively. The lower porosity and higher thermal conductivity of FCM fuels prepared using the α-SiC powder were attributed to the higher sinterability of the α-SiC powder than that of the β-SiC powder.     

湿式细磨技术研究进展

在介绍湿式细磨技术在矿物加工行业细磨作业流程中重要作用的基础上，重点对湿式细磨中的能量耗散和研磨介质运动状态的理论进行了分析，对基于CFD、DEM、PEPT的模拟仿真过程及结果进行了探讨。在简述湿式细磨技术与装备的应用进展的基础上，总结了典型湿式细磨技术与装备的结构研发、技术优化和应用进展，以期能为湿式细磨技术和装备的研究、推广提供帮助，为实现矿物加工行业的节能高效细磨奠定基础。      

Phase equilibria and thermodynamic re-assessment of the Cu–Ti system

Several as-cast and annealed Cu–Ti alloys were prepared for microstructural, compositional, structural and thermal characterizations. The formation of CuTi₂ was congruent and CuTi₃ was not found in both as-cast and annealed specimens. The temperatures of nine invariant reactions were determined. The Cu–Ti system was thermodynamically re-assessed according to the experimental phase equilibria and thermochemical properties from this work and the literature. The solution phases Liquid (L), fcc-A1 (Cu), bcc-A2 (βTi) and hcp-A3 (αTi) were treated as substitutional ones. The intermetallics compounds Cu₂Ti, Cu₃Ti₂, Cu₄Ti₃ and CuTi₂ with negligible solubility were described as line ones with the formula Cu_pTi_q, while βCu₄Ti and CuTi with remarkable solubility were modeled with the formula (Cu,Ti)_r(Cu,Ti)_s. A group of reliable thermodynamic parameters of the Cu–Ti system were obtained. The calculated results agreed reasonably well with the experimental ones.     

Steels classification by machine learning and Calphad methods

Steels of different classes (austenitic, martensitic, pearlitic, etc.) have different applications and characteristic areas of properties. In the present work two methods are used to predict steel class, based on the composition and heat treatment parameters: the physically-based Calphad method and data-driven machine learning method. They are applied to the same dataset, collected from open sources (mostly steels for high-temperature applications). Classification accuracy of 93.6% is achieved by machine learning model, trained on the concentration of three elements (C, Cr, Ni) and heat treatment parameters (heating temperatures). Calphad method gives 76% accuracy, based on the temperature and cooling rate. The reasons for misclassification by both methods are discussed, and it is shown that the part of them caused by ambiguity/inaccuracy in the data or limitations of the models used. For the rest of cases reasonable classification accuracy is demonstrated. We suggest that the reason of the supremacy of machine learning classifier is the small variation in the data used, which indeed does not change the steel class: the properties of steel should be insensitive to the details of the manufacturing process.     

Tailoring thermal and mechanical properties of rare earth niobates by coupling entropy and composite engineering

In this paper, a series of high-entropy rare earth niobates, including fluorite RE₃NbO₇ (HE317), monoclinic RENbO₄ (HE114) and RENbO₄/RE₃NbO₇ composite (HE-composite), are prepared via solid state reaction, following by a study about their thermal and mechanical properties. The high-entropy rare earth niobates exhibit excellent phase stability after thermally exposed to 1300 °C for 100 h, indicating entropy can stabilized high-entropy rare earth niobates. Compared with the single element rare earth niobates, high-entropy rare earth niobates have higher fracture toughness and hardness. The high-entropy RENbO₄/RE₃NbO₇ composite has the best mechanical properties, with a fracture toughness of 2.71 ± 0.17 MPa·m^1/2 and hardness of 9.46 ± 0.24 GPa, respectively. The high-entropy niobates exhibit high coefficients of thermal expansion which is close to 7 wt% Y₂O₃ stabilized ZrO₂. It is also proved that the configurational entropy has little effect on the critical temperature from monoclinic to tetragonal phase transition. The thermal conductivity of HE-composite is lower than HE114, indicating the combination of HE114 and H317 is a more efficient strategy to decrease the thermal conductivity of HE114 than entropy engineering.