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首页> 外文期刊>Arabian Journal for Science and Engineering. Section A, Sciences >Reliability Evaluation of Dynamic Characteristics of Clean Sand Soils Based on Soft Computing Methods
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Reliability Evaluation of Dynamic Characteristics of Clean Sand Soils Based on Soft Computing Methods

机译：基于软计算方法的清洁砂土动态特性可靠性评价

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摘要

This study was conducted to estimate the dynamic characteristics of clean sand under lowstrains using fuzzy expert systems and neural network approximations. A series of resonant column tests were conducted on clean sand specimens to create a large database. The effects of various factors,such as effective pressure,saturation,void ratio and shear strain levels,were simulated using fuzzy expert systems and neural networks. The neuro-fuzzy inference method was employed to predict the initial shear modulus of clean sand samples as a substitute for time-consuming laboratory testing. Additionally,the maximum shear modulus results were compared with the existing empirical relationships. From these observations,it can be observed that certain relationships significantly underestimate the initial shear modulus. Simple empirical relationships to estimate the initial shear modulus were formulated. It is concluded that neuro-fuzzybased models provide useful guidelines for the preliminary estimation of the dynamic shear modulus for clean sand soils.
机译：采用模糊专家系统和神经网络近似进行该研究以估计Lowstrows下清洁砂的动态特性。在清洁砂试样上进行一系列共振柱测试，以创建大型数据库。使用模糊专家系统和神经网络模拟各种因素，例如有效压力，饱和度，空隙率和剪切应变水平的影响。使用神经模糊推断方法预测清洁砂样的初始剪切模量作为耗时的实验室测试的替代品。另外，将最大剪切模量结果与现有的经验关系进行比较。从这些观察结果来看，可以观察到某些关系显着低估了初始剪切模量。制定了估计初始剪切模量的简单实证关系。结论是，神经模糊的模型提供了有用的初步估计清洁砂土的动态剪切模量的有用指导。

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