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- 저자 : Junwei Fang (검색결과 3 건)
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Junwei Zhao,Huaimin Xu,Cui He,Lin Li,Zhen Yi,Huijing Fang,Zhicheng Lei 한국지질과학협의회 2017 Geosciences Journal Vol.21 No.2
The Junggar basin is rich in oil and gas resources, and recently, unconventional oil and gas reservoirs have become important targets. Significant amounts of oil and gas are located in Permian formations in the Shazhang–Dajing area, however, fewer studies have focused on unconventional oil and gas reservoirs, particularly on the factors controlling the distribution of unconventional reservoirs. In this study, a sequence stratigraphic framework of the study area was developed based on cores, well logs and seismic data. Source rock samples were analyzed, including tests of kerogen, vitrinite reflectance, chloroform bitumen, organic carbon and group composition. The physical properties and pore characteristics of reservoir samples were also analyzed using scanning electron microscope and high resolution electron microscope. The Permian Pingdiquan Formation comprises three thirdorder sequences in which individual sequence can be divided into a low-stand system tract (LST), a transgression system tract (TST), an early high-stand system tract (E-HST), and a late high-stand system tract (L-HST). Several source rock lithologies have high total organic carbon (TOC), and are matured, having excellent hydrocarbon generation potential. Clastic and dolomitic rocks are the main reservoirs, and nanometer-scale pores are the main reservoir space in the tight reservoirs. The distribution of tight oil is controlled by the sequence stratigraphy, palaeogeomorphic units, and sedimentary facies. The fine sediments, which were generally deposited near the initial flooding surface (FFS) and the maximum flooding surface (MFS), are favorable zones for tight oil. The distributions of the hydrocarbon source rocks are controlled by the depositional environment, depending on the palaeogeomorphic units; the deep depression in the Huoshaoshan area and the moderately-deep depression in the Shishugou area are two distinct hydrocarbon generating centers. The distribution of tight oil is clearly controlled by the sedimentary facies; the tight oil is mainly located in the fan delta front and lacustrine depositional environments. The distribution of tight oil in this area is summarized, and favorable areas of tight oil are proposed.
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Binrui Wang,Junwei Fang,Shunan Qi,Ling Wang,Xiaolong Liu,Haijun Ren 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.7
In order to solve the problem of lack of flexibility in direct teaching of industrial robots under complex working conditions, dynamic inertia term compensation is combined with the traditional force-free control algorithm to reduce the traction in the teaching process in this paper. Firstly, considering the multi-dimensional, strongly nonlinear and multi-parameter characteristics of the 6-DOF manipulator dynamic model, a step-by-step parameters identification method based on genetic algorithm is proposed. This method can effectively reduce the computational complexity and improve the optimization speed of industrial robot dynamic model identification. Secondly, based on the internal torque analysis of industrial robot joints, a forcefree compensation control algorithm based on the torque control is designed. Finally, the effectiveness of the step-by-step robot dynamic model parameter identification method is verified by a traction teaching experiment. In the verification experiment, the relative error rate between the predicted torque and the actual torque calculated from the identification results is 1.64 % to 5.99 %. After increasing the inertia term compensation, the traction force of the teaching process is reduced by 28.6 %. The experimental results show that the identification result is more accurate, and the proposed force-free control algorithm significantly improves the compliance of the teaching process.
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Cutting Parameter Optimization for Reducing Carbon Emissions Using Digital Twin
Lili Zhao,Yilin Fang,Ping Lou,Junwei Yan,Angran Xiao 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.5
With the exacerbation of global environmental concerns, manufacturing industries need to consider the impact of carbon emissions from manufacturing processes. The selection of the parameters in the machining process greatly influences on carbon emissions and machining efficiency. Hence dynamically optimizing the machining process parameters is a significant means to reduce carbon emissions according to the real-time perception of the machining conditions. In the paper, a method of cutting parameter optimization is presented on basis of the construction the digital twin of a CNC machine tool. In this method, an ontology on CNC machining process is established to be used as a communication bridge for understanding the semantic of the real-time interaction between the physical machine and the virtual twin. And a dynamic optimization method on cutting parameters is presented according to the simulation and optimization of the virtual twin with the dynamic perception of the machining conditions of the physical machine. At last, a case study is presented to validate this method for effectively optimizing the cutting parameters and decreasing carbon emissions.
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