nhui Li

A New Method to Evaluate Rock Mass Brittleness Based on Stress–Strain Curves of Class I

Brittleness is a key controlling parameter for rock engineering projects such as hydrocarbon production and other applications. In this paper, commonly used methods based on stress–strain curves of Class I for the calculation of rock brittleness are reviewed. In order to describe the rock brittleness more reasonable, the new index Bi was proposed based on the stress drop rate obtained from post-peak stress–strain curve and the ratio of elastic energy released during failure to the total energy stored before the peak strength. Then the validity of Bi is verified with experimental tests conducted on rock specimens drilled from the interlayer and oil layer through a well of Shengli Oilfield. Moreover, numerical simulation is performed to analyze the effects of primary mechanical parameters on the brittleness of rock masses. Based on experimental tests and numerical simulation results, the acoustic emission modes influenced by brittleness index Bi are summarized. At last, correlation between acoustic emission mechanism and index Bi is verified by comparing the acoustic emission modes of limestone under different levels of confining pressure and various types of coal.

Research on optimal control method of hybrid electric vehicles

Energy saving and environmental protection are the two main themes of today’s auto industry development. The hybrid electric vehicle (HEV) has become one of the most practical significant ways to solve energy and emission problems with good fuel economy and lower emissions. Aimed at the present HEV control methods, which have problems such as power loss, low efficiency of the system, the deterioration of the lubrication conditions, and so on, from the points of view of the overall efficiency of drive system, an optimal control method for a HEV is proposed to solve these problems. Firstly, all the possible operating modes are formulated. Then the efficiency evaluation equations of different modes are constructed. Next, according to the battery state of charge, this method determines the possible operating modes, and then the efficiency of different modes is calculated by means of the demand torque. Comparing the efficiency of different modes, the mode with the highest efficiency is obtained so that the engine torque and motor torque are distributed to enable the engine and motor output to correspond with this torque. Finally, the proposed method is simulated; the results show that it reduces system power loss and vehicle fuel consumption and emissions, and that it also protects the life of the transmission parts and lubrication conditions to some extent, achieving significant improvements.

A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

Fuzzy Sliding Mode Lateral Control of Intelligent Vehicle Based on Vision

The lateral control of intelligent vehicle is studied in this paper, with the intelligent vehicle DLUIV-1 based on visual navigation as the object of research. Firstly, the lateral control model based on visual preview is established. The kinematics model based on visual preview, including speed and other factors, is used to calculate the lateral error and direction error. Secondly, according to the characteristics of lateral control, an efficient strategy of intelligent vehicle lateral mode is proposed. The integration of the vehicle current lateral error and direction error is chosen as the parameter of the sliding mode switching function to design the sliding surface. The control variables are adjusted according to the fuzzy control rules to ensure that they meet the existence and reaching condition. The sliding mode switching function is regarded as the control objective, to ensure the stability of the steering wheel rotation. Simulation results show that the lateral controller can guarantee high path-tracking accuracy and strong robustness for the change of model parameters.

Traffic Scene Segmentation Based on RGB-D Image and Deep Learning

Semantic segmentation of traffic scenes has potential applications in intelligent transportation systems. Deep learning techniques can improve segmentation accuracy, especially when the information from depth maps is introduced. However, little research has been done on the application of depth maps to the segmentation of traffic scene. In this paper, we propose a method for semantic segmentation of traffic scenes based on RGB-D images and deep learning. The semi-global stereo matching algorithm and the fast global image smoothing method are employed to obtain a smooth disparity map. We present a new deep fully convolutional neural network architecture for semantic pixel-wise segmentation. We test the performance of the proposed network architecture using RGB-D images as input and compare the results with the method that only takes RGB images as input. The experimental results show that the introduction of the disparity map can help to improve the semantic segmentation accuracy and that our proposed network architecture achieves good real-time performance and competitive segmentation accuracy.

Investigation on the effect of pore pressure gradient on fracture propagation in rock materials

Abstract When rock is subjected to internal hydraulic pressure and external mechanical loading, the fluid flow properties will be altered by newly induced fractures. In turn, the fluid flow driven by pore pressure gradient can influence the fracturing behaviour. To better capture the complex hydraulic fractures in rock materials, a ‘pinch-off’ breaking test is numerically conducted to illustrate the tensile failure of a rock specimen within a uniform pore pressure field. A double-notched specimen, with water pressure in one notch while keeping another one open to the atmosphere, is numerically extended to investigate how the water flow direction or the pore pressure gradient will influence the fracturing behaviour. The simulation results indicate that both pore pressure magnitude and the orientation and distribution of pore pressure gradient surrounding the fracture tip can affect fracturing process and macroscopic strength behaviour of rock materials.

Research and design of doubly salient permanent magnet motor for hybrid electric vehicle based on the NdFeB permanent magnet material

Abstract The performance of hybrid electric vehicle motor directly affects its power performance and fuel economy. The high performance sintered NdFeB permanent magnet material is chosen as the core material of the hybrid vehicle motor for the design of the permanent magnet in this paper, and its size is also determined. A doubly salient permanent magnet motor is proposed here on the basis of the selected NdFeB permanent magnet material, and its structure size is designed. The finite element numerical calculation is carried out for the motor in particular rotor position angle on the basis of the field quantity to obtain the magnetic field distribution law in several typical rotor positions and the static characterise parameters of the motor are further obtained. Final, inspect the performance of the prototype objectively based on the bench experiment of the designed physical prototype, and the prototype experiment and finite element results both proved that the designed doubly salient permanent magnet motor could meet the requirements of hybrid electric vehicle, so as to achieve the purpose of the research and design of the doubly salient permanent magnet motor used in hybrid electric vehicle.