A Novel Bond Anchor for Unidirectional FRP Member: Conceptual Design and Experimental Investigation

Fiber-reinforced polymer (FRP) is an advanced composite material with many advantages including light weight, high strength, and high fatigue and corrosion resistance, which makes unidirectional FRP suitable for tension members, such as cables, prestressing tendons, and tie rods. However, the unidirectional FRP is a typical isotropic material, which is difficult to be anchored and hence unable to give full play to the advantages of FRP. To solve the anchoring problem of unidirectional FRP member, a novel bond anchor, i.e., dissolution-rebond anchor, is proposed in this paper. In this novel anchorage system, the polymer matrix of two ends of the unidirectional FRP member is dissolved by solvent and the fibers in the anchorage length are directly bonded by the binder. Theoretical analysis was performed to illustrate the high anchorage bearing capacity of this dissolution-rebond anchor. Static tensile test was conducted to verify this novel anchor design and compare with traditional bond anchor. Results show that the novel dissolution-rebond anchor is feasible and its anchorage efficiency is significantly higher than the traditional bond anchor.

Fault Detection Method of Power Insulator Based on Deep Convolution Neural Network

Aiming at the problem of low detection accuracy of traditional power insulator fault detection methods, a power insulator fault detection method based on deep convolution neural network is designed. For the training of deep convolution neural network, the fault detection of power insulator based on deep convolution neural network is realized by anchor design, loss function design, candidate region selection mechanism establishment and sharing convolution features. The experimental results show that the fault detection method of power insulator based on deep convolution neural network is more accurate than the traditional method, and the detection time is less.

Design and analysis of plate anchors in sand

Plate anchors, as an efficient and reliable anchorage system, have been widely used to resist uplift forces produced by structures, such as transmission towers, offshore platforms, submerged pipelines, and tunnels. In order to design a plate anchor it is important to know the factors which influence the design and uplift behavior of anchors embedded in sand. In this report a number of model uplift tests and numerical investigations made by different authors are described and based on these readings the uplift behavior of anchors in sand is explored and anchor's design procedure is described. In addition, basic anchor types, failure modes in anchors, and design codes are mentioned. Based on this study, it is found that the failure plane and uplift capacity is significantly influenced by the soil density and embedment depth. Therefore, it is concluded that the influence of sand density and embedment depth should be considered in anchor design.

Design and analysis of plate anchors in sand

Plate anchors, as an efficient and reliable anchorage system, have been widely used to resist uplift forces produced by structures, such as transmission towers, offshore platforms, submerged pipelines, and tunnels. In order to design a plate anchor it is important to know the factors which influence the design and uplift behavior of anchors embedded in sand. In this report a number of model uplift tests and numerical investigations made by different authors are described and based on these readings the uplift behavior of anchors in sand is explored and anchor's design procedure is described. In addition, basic anchor types, failure modes in anchors, and design codes are mentioned. Based on this study, it is found that the failure plane and uplift capacity is significantly influenced by the soil density and embedment depth. Therefore, it is concluded that the influence of sand density and embedment depth should be considered in anchor design.

Effect of an Anchor Geometry on the Hydrodynamic Characteristics of a Nanofluid in Agitated Tank

In this paper, the flow of a shear thinning nanofluid in a mechanically stirred tank has been numerically analyzed. This tank is cylindrical with a flat bottom. It is filled with Al2O3 nanoparticles suspended in the base fluid and equipped with an anchor-type stirrer whose shape is tilted upwards at an angle α. The purpose of this research is to study the impact of the tilt angle (0≤α≤π/6) and the effect of the alumina nanoparticles concentration (0≤φ≤0.1) on the hydrodynamic behavior and energy consumption. In the new anchor design (α>0), the fluid volume that is swept during the rotation of the anchor is the same as that in the case of a standard anchor (α=0). The laminar flow of the nanofluid is governed by the continuity and momentum equations taking into account the physical properties of the nanofluid introduced through correlations cited in the literature. The results obtained have shown that the tilt angle significantly contributes to the reduction of the power number, and leads to a decrease in the intensity of the tangential flow at the level of the extreme transverse planes of the tank. However, this reduction in intensity is compensated by increasing the axial flow. The use of nanoparticles in this work aims to show the role of the new design of anchor in creating a vortex at the bottom of the tank and to avoid of particles sedimentation.

Dense-RefineDet for Traffic Sign Detection and Classification

Detecting and classifying real-life small traffic signs from large input images is difficult due to their occupying fewer pixels relative to larger targets. To address this challenge, we proposed a deep-learning-based model (Dense-RefineDet) that applies a single-shot, object-detection framework (RefineDet) to maintain a suitable accuracy–speed trade-off. We constructed a dense connection-related transfer-connection block to combine high-level feature layers with low-level feature layers to optimize the use of the higher layers to obtain additional contextual information. Additionally, we presented an anchor-design method to provide suitable anchors for detecting small traffic signs. Experiments using the Tsinghua-Tencent 100K dataset demonstrated that Dense-RefineDet achieved competitive accuracy at high-speed detection (0.13 s/frame) of small-, medium-, and large-scale traffic signs (recall: 84.3%, 95.2%, and 92.6%; precision: 83.9%, 95.6%, and 94.0%). Moreover, experiments using the Caltech pedestrian dataset indicated that the miss rate of Dense-RefineDet was 54.03% (pedestrian height > 20 pixels), which outperformed other state-of-the-art methods.