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面向MOOC的知识模型及可视化方法研究
引用本文:熊剑.面向MOOC的知识模型及可视化方法研究[J].湖南科技大学学报(自然科学版),2017,43(1):50-58.
作者姓名:熊剑
作者单位:1.中国矿业大学 力学与建筑工程学院,江苏 徐州 221116;2.中国矿业大学 深部岩土力学与地下工程国家重点实验室,江苏 徐州 221116;3.湖南科技大学 煤矿安全开采技术湖南省重点实验室,湖南 湘潭 411201
基金项目:国家自然科学基金资助项目(11502229,51404266,51574228);湖南省教育厅资助科研项目(14C0427)
摘    要:利用一种岩石裂隙水沙渗透试验系统开展了水沙在平面平行裂隙中流动的滞后性的试验研究,分析了渗流速度-压力梯度闭环曲线的特征,解释了滞后现象的原因.试验结果表明:当渗流速度由零增大到1.77 mm/s再减小到零时,渗流速度-压力梯度曲线自行封闭,形成滞环;由于裂隙开度、粗糙度、沙粒径和沙浓度的不同,滞回曲线呈现凸镜形、月牙形、"8"字形、勺形和裂缝形等多种形状;水沙混合液与岩石裂隙面的接触角变化引起回程中渗透速度沿裂隙宽度方向分布变化,这是岩石裂隙中水沙渗透存在滞后现象的主要原因;沙粒在岩石裂隙面的沉积、水沙在岩石裂隙中运动形态的转变、水沙混合液的粘塑性是岩石裂隙中水沙渗透存在滞后现象的重要原因.

关 键 词:滞回性  岩石裂隙  水沙混合液  渗透速度  渗流速度
收稿时间:2016/7/23 0:00:00
修稿时间:2016/9/7 0:00:00

Research on knowledge model and visualization method for MOOC
XIONG Jian.Research on knowledge model and visualization method for MOOC[J].Journal of Hunan University of Science & Technology(Natural Science Editon),2017,43(1):50-58.
Authors:XIONG Jian
Institution:1.School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China;2.State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China; 3.Hunan Provincial Key Laboratory of Safe Mining Techniques of Coal Mines, Hunan University of Science and Technology, Xiangtan 411201,China
Abstract:In view of the phenomenon that the traditional network teaching lacks individual learning and deep learning, this article proposes a design scheme of knowledge model for MOOC, which is based on the theory of constructivism, classifies the knowledge from the visual angle, and on this basis, gives the conceptual structure and mathematical formulation of the knowledge model. Finally, based on the knowledge model, this article discusses the visual method of its static characteristics and dynamic characteristics. It is proved that the network teaching process based on knowledge model for MOOC can be built for different learners, which can form individual teaching, and can not only achieve the teaching of basic knowledge, but also cultivate meta-cognitive ability, to achieve the purpose of deep learning.
Keywords:hysteresis  rock fracture  water-sand mixture  permeate velocity  seepage velocity
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