Publications

The ABAQUS finite element software is used to calculate the vertical bearing capacity of single piles in Tianjin, and the finite element results are compared with the data gained through the in-situ static load pile foundation tests. It is found that the Young’s modulus of the soil at the bottom of the pile could have a important role in improving the vertical bearing capacity of single piles.

This article describes the factors which affect the transparency in grinding process of translucent soap production from designing the formula to controlling the parameter of process, to packetting and storning the product etc, esp emphasise the relation between FA content (w %) of the soap-drops, melting point of the formula, temperature of the process and transparency, then discuss the effect of other relative factors for transparency of product, including refined-grind, plodder, water-chilled, cooling-soap, soaps shape, package and storage, etc moreover, give the relative parameter of the process control and the method controlling these factors

The study of the slurry reinforcement mechanism is mainly focused on the interaction between slurry and soil. The seepage effect of the slurry always exists no matter what way the slurry interacts with the soil around the pile. In the process of slurry diffusion, the porosity of the soil, the permeability of the slurry, and the slurry pressure vary due to some cement particles being blocked by the soil particle skeleton. Therefore, the study of the slurry filtration effect is of great significance for predicting the permeation and diffusion law of slurry. In this paper, a macroscopic linear filtration model was introduced and the changes of slurry properties in the permeation diffusion process were considered. Firstly, a spherical (cylindrical) permeation diffusion model, which takes the linear filtration effect and the variation of slurry viscosity into account, was derived based on the conservation of mass. Furthermore, in order to more accurately reflect the influence of the filtration effect on the slurry permeation diffusion model, a polynomial nonlinear filtration model was proposed, and the numerical solution for the permeation diffusion model was derived using finite difference and finite element methods. Finally, the numerically simulated values, the measured values, and the values from the spherical permeation diffusion model that does not consider slurry viscosity variations were compared. The results indicate that the grout pressure is inconsistent with the measured value without considering the effect of the filtration. The initial grouting pressure calculated by the model in this paper is slightly larger, and the required grouting pressure over time is greater than that without considering the filtration effect, regardless of whether the grout diffuses in a spherical or cylindrical manner. The results of this study can contribute to a better understanding of grouting engineering and provide some theoretical guidance for actual grouting.

The aerodynamic performance and wake structure of dandelion seed pappus have been numerically studied based on a simplified quasi-dandelion pappus (QDP) model with its filaments represented by rectangular cylinders. The filament width is chosen as the major geometric parameter for investigation. A rigorous measuring strategy is developed for the identification of the recirculation region width in the wake of the QDP model. Three regimes are distinguished as the filament width increases, i.e., a dandelion-like regime, a transition regime, and a disk-like regime. In the dandelion-like regime, the recirculation region widths are relatively large and monotonously decrease with the increase in Reynolds number. In the transition regime, the recirculation region widths are moderate and first decrease sharply at low Reynolds number and subsequently maintain an approximately invariant value. In the disk-like regime, the recirculation region widths are relatively small. The Reynolds number based on the recirculation region width is defined, and its correlation to the drag coefficient in a different regime is also discussed. In addition, as the QDP model turns from the dandelion-like regime to the disk-like regime, the pressure distribution in the wake turns from the recirculation region type to the flow stagnation type. The current study may provide a reference for the design of more efficient dandelion-like aircraft.

Shot boundary detection is an important fundamental process toward automatic video indexing, retrieval, editing, etc. After a critical review of most approaches seeking to solve this problem, we propose a novel shot boundary detection. To improve the performance of the algorithm and reduce the computational cost, frames that are clearly not shot boundaries are first removed from the original video. After that, a novel SIFT keypoint matching algorithm based on SVM is proposed, which is used to capture the changing statistics of different kinds of shot transitions so as to identify, not only abrupt transitions, but also gradual transitions(fade, dissolve, wipe) accordingly. At last, our system use different algorithms for different kinds of shot transitions to help us to get a better solution for shot boundary detection problem. Numerical experiments in the evaluation of TRECVID and a variety of film videos demonstrate that our method is capable of accurately detecting shot transitions, and could greatly reduce the computational cost.

Vibration displacement of civil structures is crucial information for structural health monitoring (SHM). The challenges and costs associated with traditional physical sensors make displacement measurement not always straightforward owing to difficulties such as inaccessibility. While recent computer vision based methods for displacement measurements offer simplicity, unfortunately they lag in terms of accuracy and robustness. This paper introduces a monocular camera system designed to measure out-of-plane vibration displacement. Compared to existing monocular-camera based methods, the proposed monocular vision-based measurement technique significantly enhances accuracy and robustness. This boost can be attributed to the generation of a vast and precise dataset and augmented by employing advanced techniques for object segmentation and background elimination. Experimental tests are conducted in the laboratory to investigate the feasibility of the proposed system. The results demonstrate that the proposed monocular 3D displacement system can produce highly accurate full-field out-of-plane displacement measurement.

Abstract Accurate measurement data are a basic prerequisite for effective structural health monitoring (SHM). However, data loss are inevitable in the long‐term monitoring of large‐scale structures. To solve this problem, this research proposes a transformer‐based generative adversarial network (GAN) to reconstruct lost measurements from observed measurements. The generator of GAN is an encoder‐decoder structure using transformer as the backbone combined with discrete wavelet transform. Skip connections are used between the encoder part and decoder part to promote multi‐scale information flow. A novel discriminator is designed to assess the reality of wavelet spectra of reconstructed samples. To deceive the discriminator, the generator must generate samples that are accurate over the full frequency band. The developed model is used to reconstruct linear responses of a footbridge under pedestrian excitations and nonlinear responses of a suspension bridge under typhoon events. Experimental results demonstrate that lost responses can be reconstructed accurately, even when a large proportion of data are lost. The effectiveness of the proposed method is further verified by comparing the reconstruction accuracy of the proposed model with those of other three state‐of‐the‐art models. The results demonstrate that an improved performance of applying the proposed approach for dynamic structural response reconstruction is achieved and validated with in‐field testing data under ambient and extreme excitation conditions.

Machine learning methods based on statistical principles have proven highly successful in dealing with a wide variety of data analysis and analytics tasks. Traditional data models are mostly concerned with independent identically distributed data. The recent success of end-to-end modelling scheme using deep neural networks equipped with effective structures such as convolutional layers or skip connections allows the extension to more sophisticated and structured practical data, such as natural language, images, videos, etc. On the application side, vector fields are an extremely useful type of data in empirical sciences, as well as signal processing, e.g. non-parametric transformations of 3D point clouds using 3D vector fields, the modelling of the fluid flow in earth science, and the modelling of physical fields. This review article is dedicated to recent computational tools of vector fields, including vector data representations, predictive model of spatial data, as well as applications in computer vision, signal processing, and empirical sciences.