节点文献
摩擦桩极限承载力的数值研究
Numerical Research on Bearing Capacity of Frictional Piles
【作者】 荀东亮;
【导师】 沈成武;
【作者基本信息】 武汉理工大学 , 工程力学, 2003, 硕士
【摘要】 钻孔灌注桩是一种应用最广泛的深基础形式。近年来,我国应用钻孔灌注桩堪称世界之最,超过100万根/年,桩的埋深已达104米。在桩基的承载性状研究中,确定单桩承载力和沉降是重点。由于影响单桩极限承载力的因素很多且不稳定,合理地确定桩的极限承载力,充分提高桩基的经济技术效益,始终是工程设计人员和施工人员十分关心的问题。 近年来,人们逐步认识到研究桩基承载力时,应将桩和土视为一个复杂的系统来研究。具体分析方法包括弹性理论法、简化模型法、数值分析方法。模型简化法包括荷载传递法和剪切变形法。数值计算分析方法在工程实践中获得了广泛应用。有限单元法和边界单元法已经应用到桩基承载能力的分析中。 论文针对工程实例,利用ANSYS的参数化建模和二次开发技术,建立了单桩极限承载力的有限元计算模型。并分析了模型尺寸对分析结果的影响,结论表明,适当的选取模型参数,有利于分析的精度的提高。文章还通过改变不同的桩土系统参数,桩长,桩的直径,以及桩的弹性模量,得到了桩土系统的响应,绘制了P—S曲线,结论表明,对于摩擦桩而言,增大桩长,提高桩的直径,或者提高桩的弹性模量,有利于提高单桩的极限承载力。这个结论为设计提供了较为可靠的指导。 论文的实例来源于湖北省某些桥梁工程项目,其极限承载力是由静载试验确定的。静载试验法,尽管存在随机性和模糊性问题,但一般认为静载试验是最可靠的方法。静载试验完成后,可以得到P-S曲线。该P-S曲线没有明显的陡降点,属于典型的摩擦桩。论文利用现在较为流行的非线性处理方法——人工神经网络方法来拟合P-S曲线,以沉降为标准给出了单桩极限承载力。结果表明,该方法具有良好的处理能力,能够精确的根据P-S曲线给出单桩极限承载力。 论文提供的桩土系统数值分析模型,能够为桩基的进一步研究和工程实践提供有益的参考;用来确定单桩极限承载力的ANN方法适应性广、具有非线性处理能力、拟合精度高,具有良好的应用前景。
【Abstract】 Drilled grouting pile is one of the widely used type of the deep foundation. In the recent years,the number of the drilled grouting pile used in china exceeds 1000 000 per year.The depth of the pile under the earth is being to 104 meter.In research of the characteristic of the bearing capacity of the piles,how to specify the bearing capacity and the settlement is the key.Because of lots of factors is insable,how to specify the bearing capacity of the piles properly and make good economic efficiency is the concerned problem to the designer.As to bearing capacity research,suitable method is to view the pile-soil as a complex system. The pile analysis method includes elastic method, simplified model method,and shearing deformed method .Of course,as one type of numerical method,Finite Element Method is used more than Boundary Element Method.In this paper,ANSYS is been used as numerical method.Base on one example,FEM model is created by using parameterized modeling and the develop technique by ANSYS,The effect of the model size has been studied.lt has been certified that the proper parameter value of the model is helpful to develop the analysis accuracy.The length,the diameter and the elastic modulus of pile is changed to study their effect.The analysis shows that: as to frictional pile,big length,big diameter,and great modulus is helpful to develop the bearing capacity of piles.The example pile is the typist frictional pile. When the test is completed P-S curve can be drawn.From the P-S curve,we can’t specify the bearing capacity easily.In order to specify the bearing capacity accuracy,Artificial Neural Network method is used .The fitted P-S curve is approximately accordance with those analyzed by test.
【Key words】 bearing capacity of piles; numerical analysis; frictional pile; Artificial Neural Network;
- 【网络出版投稿人】 武汉理工大学 【网络出版年期】2003年 03期
- 【分类号】TU473.1
- 【被引频次】3
- 【下载频次】460