Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Exploring the fluid flow mechanism in rock masses is of great significance for preventing water inrush during excavation of underground constructions such as tunnels. Quantitative descriptions of the hydraulic properties of single rock fracture subject to normal stresses and shear displacement are the basis for understanding the coupled hydro-mechanical processes in fractured rock masses; however, the quantitative relationships among stress, deformation, aperture, inertial coefficients have not been developed in previous works. Granite specimens with single fracture were prepared and flow tests with variable water heads were carried out, in which incremental normal stresses were applied at each fixed shear displacement to characterize the evolution of permeability. The surface morphology of fractures was digitalized using a three-dimensional high-resolution scanning system. A self-designed numerical code was employed to calculate the deformation of fractures under normal stresses based on the framework of variational principles in contact mechanics. The fracture deformation and void space variation under different shear displacements and normal stresses were investigated. By extracting the aperture data and solving Navier–Stokes equations using COMSOL software, a series of numerical simulations were performed to investigate the nonlinear flow behavior of fluids within fractures under different shear displacements and normal stresses. The relationships among shear displacement, normal stress, void space distributions and parameters describing the nonlinear flow were quantitatively analyzed. The results showed that the fracture surface damage areas obtained from the experiment agreed well with the numerical simulation results, which verified the reliability of the deformation calculation code. The normal stress and the shear displacement exhibited a decreasing power function and an increasing exponential function with the fracture aperture, respectively. The increase in the shear displacement resulted in the concentration of contact areas. The inertia coefficient B in the Forchheimer equation and the critical hydraulic gradient Jc could quantitatively characterize the nonlinear flow behavior. B and Jc exhibited decreasing power functions with the shear displacement. The increasing rates and ranges of Jc and B decreased gradually as shear advances. When the shear displacement increased from 2 to 8 mm, the range of Jc decreased from 6.10×10–3 to 1.20×10–3 by a rate of 80.32%. The range of B decreased sharply from 2.97×1014 Pa·s2·m–7 to 2.43×1013 Pa·s2·m–7 by a rate of 91.28%. A similar power function relationship existed between RSD～B and between RSD～Jc. Finally, a predictive function was proposed to quantify the onset of nonlinear fluid flow through fractures.

Thermal error prediction and compensation of CNC machine tools is an important technology to improve the machining accuracy and reliability of CNC machine tools. The thermal error of machine tool is time-varying and nonlinear. To improve the accuracy and robustness of thermal error prediction, a numerical control machine tool thermal error prediction model based on attention mechanism and deep learning network was proposed. Using the data conversion strategy, the original temperature data of CNC machine tool was transformed into temperature image, which could be directly used as the input of deep learning network. The complete information of the temperature field of the machine tool was retained by converting the temperature field data into the temperature image points. At the same time, the nonlinear and coupling problems between the temperature measuring points were avoided by using the deep learning modeling method. A recognition network of temperature sensitive points based on attention mechanism was proposed. According to the correlation degree between temperature measuring points and thermal error, different weights were given to each temperature measuring point to avoid the disadvantages of artificial selection of temperature measuring points. A 12–layer deep CNN learning prediction network was established to mine the nonlinear mapping relationship between temperature image and thermal error by using its powerful image feature learning ability. This method does not need to preselect the key temperature points, retained more relationship between thermal error and machine temperature characteristics, and can significantly improve the prediction accuracy of the model. In order to improve the accuracy and generalization ability of thermal error model, dropout regularization method and Adam optimization algorithm were introduced to optimize the structure and parameters of deep convolution neural network. The method shows high prediction accuracy in the thermal error verification of G460L CNC lathe. Compared with the thermal error models based on BP neural network, multiple regression and CNN network, the proposed method performs better in generalization performance.

Landslide dams are usually formed instantaneously by natural forces, the accumulation bodies have the characteristics of complex space structure, wide gradation of dam materials, poor dam stability, and they are easy to fail under the flow erosion. As a major natural disaster of flood and drought, safety evaluation and disaster prediction of landslide dams have been the focus of attention by the scholars around the world, but many questions remain unanswered, which are mainly manifested in: 1) Accumulation bodies are composed of natural wide-graded rockfill materials with significant state-dependent correlation, there is a lack of the state-dependent dilatancy theory and constitutive model of wide-graded rockfill materials. 2) After the formation of landslide dams, they would be affected by external loads, such as the rise of upstream water level of dammed lake, continuous unsteady seepage, landslide surge in the dammed lake, and earthquake, there is also a lack of standards and methods for stability evaluation. 3) Due to the lack of necessary flood relief facilities, the landslide dams are prone to fail; under the action of outburst flow, obvious nonlinear characteristics are manifested during the breach development, as well as strong unsteady flow characteristics of the hydraulic elements; there is a lack of numerical models for landslide dam breaching which can reflect the erosion mechanisms of wide graded materials. Therefore, it is necessary to conduct integrated scientific measures, such as field explorations, multi-scale physical model tests, and numerical simulation methods, so as to reveal the physical description, internal structure, macroscopic mechanical properties of the landslide dams and their spatial and temporal variations; and then, a state-dependent (i.e., gradation, pore ratio, and stress level) dilatancy equation for wide-graded landslide deposit will be presented, and a generalized elastic-plastic constitutive model that can adapt to complex stress paths and the limit equilibrium analysis method of landslide dam body will be established. Large-scale hydraulic model tests and centrifugal model tests of dam breaching will be conducted to reveal the dynamic erosion characteristics of landslide dam materials and the evolution law of breaches under the action of unsteady flow. Subsequently, the erosion equation of sand-laden flow under the dynamic boundary condition by the action of unsteady flow will be established, and the numerical model for dam breach process considering the fluid-solid interaction will be put forward to realize the numerical simulation of the characteristics of water flow movement, the law of dam material transport, the evolution process of breaches, and the structural instability of landslide dam in the whole process of overtopping and seepage failure. Integrating the reliability theory and numerical simulation method of dam breach process, an integrated numerical simulation platform for seepage, deformation, stability, and failure process of landslide dams considering fluid-solid will be developed; consequently, the theoretical system and method of safety evaluation and disaster prediction of the full-life cycle of the landslide dams will be established. The expected results achieved in the project will provide scientific theory and key technological support for improving the decision-making level of disaster prevention and reduction of landslide dams in China.

The mechanical properties of the interface between soil and structure have always been a hot topic in geotechnical engineering. In order to explore the interfacial shear characteristics of non-water reaction polymer and concrete, the effects of vertical stress and shear rate on shear strength and shear modulus of polymer concrete interface were studied based on monotonic direct shear test. The experimental results showed that: under the given vertical stress and shear rate, with the increase of shear displacement, the polymer concrete interface presented shear softening phenomenon. The shear rate had little effect on the interfacial shear strength, cohesion and friction angle, but had a significant impact on the interfacial shear modulus, and the shear modulus value decreased with the increase of shear rate, and the decrease amplitude was obvious; the vertical stress had a significant impact on the shear strength and shear modulus of polymer concrete interface, and the shear strength and shear modulus of polymer concrete interface changed with the increase of shear rate. The vertical stress increased continuously. At the same time, the hyperbolic constitutive model formula of polymer concrete interface was systematically deduced, and the validity of the model was preliminarily verified according to the relevant experimental results.

With the rise of development and utilization of marine resources, inclined pile foundation with good horizontal bearing capacity has been widely used as marine structures such as cross-sea bridge, offshore platform and high pile wharf. Under the action of strong nonlinear superposition of wave and current, severe local scour will occur around the inclined pile, which will reduce the safety of the structure and even lead to structural damage. In order to understand the influence of inclination angle on the scour characteristics of downstream inclined piles under different wave heights and flow velocities, and the difference from that of vertical piles, local scour tests under combined waves and current and pure current were carried out in the wave-current flume. By conducting tests on α=0°, 10°, 20° and 30° downstream inclined piles, the influence of inclination angle on scour duration, relative time scale and scour hole morphology was studied. The influence of dimensionless parameters Fr, KC and Ucw on maximum scour depth of downstream inclined pile was analyzed, and detailed comparison was made with previous vertical pile data. The results showed that when the pile was inclined to downstream, inclination angle had an important influence on the scouring characteristics of pile under combined waves and current. Compared with the vertical pile, with the increase of inclination angle, development rate of scour depth, scale and depth of scour hole gradually decreased, while ralative time scale increased gradually. For the 20° downstream inclined pile, when d50=0.403 mm，Uc=0.206 m/s，H=7 cm, the time for maximum scour depth point to be transferred from lateral front to front was about 60 min, which was much longer than that of a vertical pile. The dune of downstream inclined pile was distributed symmetrically along the central axis and had a bimodal structure, and the scour hole shape was obviously different from that of a vertical pile. Under the condition of moveable bed, regular sand waves were formed on the bed surface, the scour hole scale was further reduced, and the double peaks were more obvious. The relative scour depth of downstream inclined pile was the function of dimensionless parameters Fr, KC and Ucw, which was consistent with the trend for a vertical pile’s fitting curve.