饱和块状混合回填土地基的一维固结分析

用块状渣土置换软弱地基和回填低洼谷地等是处置工程渣土的有效途径。为了分析饱和块状混合回填土地基的固结性状，运用混合物理论建立了其一维固结模型。首先，假定块状土固相和充填土固相之间满足等应变条件，获得了饱和块状混合回填土中各相应变与块状土孔隙变形和充填土孔隙变形的关系式。其次，在小应变条件下，根据自由能势函数方程建立了饱和块状混合回填土的一维线弹性本构方程，再结合达西定律和应力平衡方程获得了一维固结控制方程。再次，利用分离变量法得到一维固结解析解，通过退化本文模型与已有模型进行对比，验证了本文模型的正确性。最后，基于所得解析解，分析了充填土孔隙渗透系数、块状土孔隙渗透系数以及流体交换参数等因素对饱和块状混合回填土地基固结性状的影响。分析结果表明：充填土孔隙渗透系数对饱和块状混合回填土地基整体固结性状起主导作用；在固结初期，块状土超孔压会有一定程度的上升，且3个参数具有相似的作用机理。     

Effect of the particle size ratio on macro- and mesoscopic shear characteristics of the geogrid-reinforced rubber and sand mixture interface

As a new type of material for civil engineering projects, the rubber and sand mixture is widely used in roadbed fillers, offering environmental benefits over traditional tyre disposal methods. This study uses a large-scale direct shear apparatus to examine the interface shear properties of the geogrid-reinforced rubber and sand mixture, considering different particle size ratios (r), rubber contents, and normal stresses. Based on indoor tests, direct shear models of the mixture with different values of r are established in PFC^3D, revealing the meso-mechanical mechanism of the mixture in the direct shear process. The results show that when r is greater than 1, incorporating a certain amount of rubber particles can increase the shear strength of the mixture. The r values of 15.78, 7.63, and 3.98 correspond to an optimal rubber content of 30%, 10%, and 20%, respectively. When r is less than 1, mixing rubber particles can only reduce the shear strength of the mixture. When the rubber content is low, the smaller the value of r, the greater is the thickness of the shear band. Furthermore, the normal and tangential contact forces are greater. The fabric anisotropy evolution law of the mixture is consistent with the change in the contact force distribution.     

Development of Minimal Diguanosinyl Motif toward RNA G-Quadruplex-Like Structures in Solution

Among the non-canonical structures of B-DNA, the G-quadruplex is of particular interest because of its well-defined conformation, high stability, and versatility. Herein we report our studies on the development of an amide-linked minimal diguanosinyl motif that forms a G-quadruplex-like structure in solution in the presence of potassium cations; various linear guanosine amino acid dimers were synthesized with linkers of different chain lengths to investigate the optimum flexibility required to form such structures.     

等离子体改性海绵铁活化过硫酸盐处理含酚废水

采用低温等离子体技术对海绵铁表面进行改性，并将其用于活化过硫酸盐（PS）处理含酚废水。通过氮气等温吸附（BET）、X射线衍射（XRD）和扫描电子显微镜（SEM）等手段对改性前后的海绵铁进行表征分析。以苯酚为目标污染物，通过静态实验考察催化剂投加量、催化剂/PS摩尔比、pH和苯酚初始浓度对等离子体改性海绵铁活化PS处理含酚废水的影响。结果表明，改性后的海绵铁比表面积、孔容及孔径均有增大，活化PS能力显著提高；在最佳反应条件（等离子改性海绵铁的投加量为0.4g/L，催化剂/PS摩尔比为1∶15，溶液pH为2，苯酚的初始浓度为250mg/L）下，苯酚的去除率可达95%；反应过程符合二级反应动力学，主要是硫酸根自由基和羟基自由基起氧化作用。等离子体技术改性海绵铁活化过硫酸钠可有效去除水中苯酚，为实际含酚废水的处理提供一些思路。     

改型Wollaston棱镜干涉光谱仪的调制度研究

改型Wollaston棱镜(MWP)无需中继,可构建微型傅里叶变换光谱仪。回顾了MWP的基本原理,从调制度定义出发,计算得到准单色光源的复相干度,找到调制度的影响因素——扩展视场、剪切结构、焦面探测等。建立一般的干涉定域分析模型后,由像点逆光路追迹给出MWP的厚度计算公式,代入调制度约束参数得到不同参量的误差容限。通过FRED记录不同视场扩展情况的灰度与辐照度,结果显示,调制度为0.9时,视场与理论估算值1.24°基本相符;不同剪切量的灰度与辐照度变化特性表明,结构角会使定域垂直系统光轴的入射角发生变化,与晶轴倾角共同影响双折射率差;2.5和8μm像元探测采样表现出调制度差异,描述了定域深度或离焦的影响。以准单色光源、复相干度表示调制度,可将不同影响因素统一至约束参数中,相关变量误差容限可作为MWP-FTS的设计依据。     

飞灰固结体在沥青混合料中应用研究

通过对新型固结剂固化飞灰生成的固结体研磨成微粉全部或部分替代矿粉作为沥青混合料进行试验探究。试验结果表明,当微粉替代矿粉时,混合料的物理性能、水稳定性及高温稳定性得到了提高,确定了微粉替代矿粉最佳替代率。微粉在沥青混合料中重金属的存在状态采用多级提取的方法进行分析,试验结果进一步证明了微粉中重金属在沥青混合料中的长期稳定性。为焚烧垃圾飞灰固化稳定化和资源化利用提供了一定的理论指导。     

基于修正幂律模型流体的柳叶形扶正器旋流规律及应用

为提高注水泥过程中水泥浆顶替效率，国内外愈来愈多地使用旋流扶正器。但是，目前旋流扶正器结构参数主要靠经验设计，缺乏理论基础也没有相关行业标准。针对依据文丘里效应设计的柳叶形旋流扶正器，基于修正幂律流体模型，构建了旋流扶正器旋流长度计算模型。通过数值模拟对旋流扶正器井下旋流规律进行研究，推导出了旋流扶正器在修正幂律流体条件下，周向平均速度和完全顶替的临界速度公式。基于旋流扶正器井下旋流规律，分析了井眼环空结构、流体性能、井下井壁附着力对水泥浆顶替效率的影响，优化了柳叶形旋流扶正器旋流角、扶正棱长度、扶正棱有效体积和扶正器高度等设计参数。对比分析了柳叶形与常规旋流扶正器在不同工况下的旋流长度，柳叶形扶正器的旋流长度比常规扇形平均提升了32%，比常规梯形扶正器平均提升了47%。柳叶形扶正器在新疆顺北油田顺北3井等20多井次超深井应用，应用井固井质量明显优于常规扇形的旋流扶正器。     

Chemical process fault diagnosis based on enchanted machine‐learning approach

In the chemical industry, fault diagnosis is a challenging task due to the complexity of chemical equipment. This paper proposes a machine learning‐based approach to achieve the goal of fault diagnosis. First, in order to reduce the impact of redundant features, support vector machine recursive feature elimination (SVMRFE) is used to select important features. The trained probabilistic neural network (PNN) is then used for fault diagnosis. Considering that the diagnostic performance is affected by its hidden layer element smoothing factor (σ), the modified bat algorithm (MBA) is used to optimize the PNN to obtain optimal global parameter values. The MBA adopts a better optimization mechanism than the basic algorithm and achieves excellent global convergence. It can globally optimize the smoothing factor, which effectively improves the fault diagnosis ability of the PNN. During the testing of the Tennessee Eastman (TE) process data set, we evaluate the performance of the proposed model by comparing the F₁‐score and accuracy of the different methods. The charts provided describe the fault diagnostic results and classification for the different models. The results indicate that the MBA has a better optimization ability than other traditional optimization algorithms. At the same time, the combination method proposed in this paper is also superior to others and can significantly improve the accuracy of TE process fault diagnosis.