Consolidation considering increasing soil column radius for dredged slurries improved by vacuum preloading method

Soil column is often investigated in the improvement of dredged slurries. Different from the smear zone, the soil column forms gradually and has extremely low permeability. This study presents an analytical solution for soil consolidation considering the increasing radius of the soil column and time-dependent discharge capacity. Based on the solution, the influence of the radius' increase on the consolidation behavior is found significant when the soil column has low permeability and large final radius, and the increase of formation time can lead to the increase of consolidation speed and final consolidation degree.     

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.     

Pullout testing and Particle Image Velocimetry (PIV) analysis of geogrid reinforcement embedded in granular drainage layers

The paper investigates the feasibility of using fine-grained soil as backfill material of geosynthetic-reinforced walls and slopes, through a laboratory study on pullout behavior of geogrids in granular layers. A series of pullout tests was carried out on an HDPE uniaxial geogrid in thin sand and gravel layers that were embedded in clay specimens.Aside from different soil arrangements, the influences of moisture content and overburden pressure on the geogrid pullout behavior is assessed and discussed. The tests were carried out at four different gravimetric water contents (GWC) on the dry and wet sides of the clay optimum moisture content (OMC), and overburden pressure values within the range σ_v = 25–100 kPa. Particle Image Velocimetry (PIV) was used to capture digital images during the tests, which were processed to help with the interpretation and improved understanding of the soil-geogrid interactions at different GWC values. Results show that embedding geogrid reinforcement in layers of sand or gravel can significantly increase the pullout resistance in an otherwise moist clay backfill, and this improved pullout efficiency is greater at higher overburden pressures. The improvement in pullout capacity was observed in clay specimens compacted at both the dry and wet sides of the OMC.     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

基于BIM超高层密集布筋区埋入式型钢混凝土柱脚施工技术

以漳州市某超高层项目为例,针对超高层密集布筋区埋入式型钢柱脚与钢筋的深化设计、地脚螺栓的定位预埋、型钢柱脚支撑体系设计、节点钢筋穿插连接施工、埋入式型钢柱脚安装等方面,提出切实可行的施工方法,解决了埋入式型钢混凝土柱脚的地脚螺栓精准预埋、与底板密集钢筋穿插连接施工、悬空支撑稳定等一系列施工技术难题,既满足了设计方案的要求,又可为类似工程提供借鉴。     

Integrated LaB6/g-C3N4 solar absorber for solving dye accumulation during solar steam generation

Solar steam generation has attracted considerable interest due to its easy accessibility and sustainability. However, dye molecules were gradually concentrated on bulk water or the surface of solar absorbers during the disposal of dye wastewater. Herein, LaB₆/g-C₃N₄ composites were immobilized on porous cotton cloth, served as a solar absorber resistant to dye clogging. The optimal solar absorber possessed solar harvesting of 92.3% and showed great application potential in the field of the treatment of dye wastewater. This study presented a new approach for the treatment of dye wastewater.     

“方变圆”变径筒状结构滑模施工技术

为解决塔式光热的核心构筑物吸热塔"方变圆"变径超高筒体结构施工难题,选用一套可变形的滑模平台系统,通过操作系统上可调千斤顶支座、门架横向液压千斤顶装置、多处可调节模板角度和收缩模板的丝杆等,使得滑模根据施工需求可在一定的范围内调节模板倾角、间距,并逐步完成收缩变形,其理论滑模允许偏角20°,最终高效完成异形结构施工。该滑模系统刚度大、承载及堆料能力强、空间大、机械化程度高,施工操作简单,安全性高,适应沙漠极端环境。全过程仅需使用一套滑模体系,就能完成方形段、方变圆的变形段及圆形段施工,大大提高了施工效率,为类似环境下相似结构的施工提供了一定的参考。     

Synthesis of thermoresponsive copolymer/silica-coated magnetite nanoparticle composite and its application for heavy metal ion recovery

To enhance chemical stability and suppress of aggregation of magnetite nanoparticles (MNPs), which are used as a support for thermoresponsive copolymer immobilization, silica coating of the MNPs is applied via the electrooxidation method. Although the resulting silica coated-MNPs also formed aggregates, the size distribution of the aggregate shifted to smaller size range. Because of that, the surface area available for copolymer immobilization increased approximately 6.7 times at maximum as compared with that of the uncoated MNPs. It contributed to the increase of the amount of the immobilized copolymer on the silica-coated MNPs, which is approximately four times larger than that on the uncoated MNPs. Fe₃O₄ dissolution test confirmed enhancement of chemical stability of MNPs. The thermoresponsive copolymer immobilized on the silica-coated MNPs shows the ability to recycle Cu(II) ion from Cu(II) containing solution by changing temperature with significantly shorter time than those in other thermoresponsive adsorbents in gel form.