Effects of structural parameters on water film properties of transpiring wall reactor

Corrosion and salt deposition problems severely restrict the industrialization of supercritical water oxidation. Transpiring wall reactor can effectively weaken these two problems by a protective water film. In this work, methanol was selected as organic matter, and the influences of vital structural parameters on water film properties and organic matter removal were studied via numerical simulation. The results indicate that higher than 99% of methanol conversion could be obtained and hardly affected by transpiration water layer, transpiring wall porosity and inner diameter. Increasing layer and porosity reduced reactor center temperature, but inner diameter's influence was lower relatively. Water film temperature reduced but coverage rate raised as layer, porosity, and inner diameter increased. Notably, the whole reactor was in supercritical state and coverage rate was only approximately 85% in the case of one layer. Increasing reactor length affected slightly the volume of the upper supercritical zone but enlarged the subcritical zone.     

Self-healing,elastic and deformable novel composite phase change polymer based on thermoplastic elastomer SEBS for wearable devices

Journal of Materials Science - Form-stable composite phase change materials (C-PCMs) prepared by microencapsulation method and porous matrix adsorption method need for compression molding after...     

智能建造技术协同创新主体互动关系研究

文章分析智能建造技术创新主体的特点，界定并划分智能建造技术协同创新主体互动关系的范畴和类别，建立智能建造协同创新的多方演化博弈模型，揭示智能建造技术协同创新主体互动关系。主要结论为：①智能建造技术协同创新呈现级联性、函数性、动态平衡性、不确定性和指数性特征；②智能建造技术协同创新主体互动关系分为同质性的内部主体互动和异质性的内部主体与外部主体互动，表现出利益共生、成长进化和共享协同的特征；③创新主体之间的互动行为有利于对创新资源进行有效配置，推动智能建造技术的应用。     

有砟轨道路基翻浆冒泥模型试验系统的研发与应用

为研究既有线有砟轨道路基的翻浆冒泥机理，自主研发了一套能够模拟循环荷载–湿化耦合作用的模型试验系统。模型试样直径500 mm，由厚度分别为350 mm的路基土和200 mm的道砟组成，整个试样在高强度透明有机玻璃模型筒中制备完成。模型试验系统配备有监测荷载、位移、体积含水率和孔隙水压力的4种传感器，并通过高清相机对颗粒迁移过程进行图像捕捉。基于所研发的试验系统，针对辛泰铁路典型翻浆冒泥病害路段土样，开展翻浆冒泥模型试验。试验结果表明：动孔隙水压力是导致翻浆冒泥病害产生的关键因素。随着体积含水率的增加，动孔隙水压力引起的颗粒迁移量逐渐增加；在饱和状态下，会引起大量颗粒迁移，翻浆冒泥现象显著。试验结束时，道砟污染指数达到25%，在实际工程中已严重影响铁路的正常运营，有必要对污染道砟进行换填。     

Optimized decomposition and two-step nonlinear integration model with error correction strategy coupled interval prediction for digital currency price forecast

Digital currency price prediction is vital to both sellers and purchasers. Over these years, decomposition and integration models have been applied more and more to realize the goal of precise prediction, however, many of them tend to neglect the reconstruction of features or the residual series. Altogether, one of the biggest drawbacks of the decomposition and integration framework is the method applied requires manual parameter setting whether it is for decomposition or integration. Still, for the results, they are merely satisfied with the point prediction which brings high uncertainty. In this paper, an optimized feature reconstruction decomposition and two-step nonlinear integration method is proposed which gives consideration to feature reconstruction, nonlinear integration, optimization and interval prediction. The original data series is decomposed through improved variational mode decomposition based approximate entropy feature reconstruction system. Then, improved particle swarm optimization-gated recurrent unit (iPSO-GRU) is utilized in the first and second nonlinear integration part separately. Meanwhile, the residual series is given attention, if it is not a white noise series, the residual will be the input of iPSO-GRU whose result will be added back to the second integration result to form the point prediction result. Based on the point prediction result, interval prediction estimate will be generated as well via maximum likelihood function. This study chooses three kinds of digital currency as cases and the results show that the MAPE values of point prediction are all below 3.5%, and CP values of interval prediction are all 1 with suitable MWP. In addition, compared with other benchmark models, the proposed model shows better performance.

     

Gelling behavior of MgAl2O4 slurries with a common dispersant

MgAl₂O₄ transparent ceramics were shaped by a commonly used polyacrylic acid (PAA), which acted as both dispersant and gelling agent. The spinel slurries were prepared by ball-milling MgAl₂O₄ powder, PAA, and water in an attrition mill. The gelling of slurries happened at room temperature in air atmosphere without any other organic additive. The gelling mechanism was the formation of chelates between Mg²⁺ and carboxyl groups (-COO⁻) of PAA. The frequency-based testing method was applied to investigate the gelling process of the as-prepared slurry. In addition, a novel in situ characterization method based on a modified indentation testing was invented to better understand the strengthening of the wet green body with time and to guide when demolding could be carried out. After sintering, transparent MgAl₂O₄ ceramics with high in-line transmittance were resulted.