混合遗传算法在砂土液化势评价中的应用
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摘要
基于历史地震液化实例资料和现场实测 SPT值 ,建立了应用混合遗传算法的砂土液化势智能评价模型 ,并实际评判了特大型润扬长江公路大桥工程区的砂土液化 ,且进一步分析和研究了桥址区潜在液化层的空间分布规律和概率统计特征 ,并与规范判定法结果作了对比 ,取得了较好的成果。实例应用表明了该法是可行和可靠的 ,为大桥的设计和施工提供了科学依据 ,对基础工程的可靠性分析和最优设计具有重要实际意义
Based on the mixed genetic algorithms(GAs),the in-situ data of the standard penetration test(SPT) and examples of earthquake-induced liquefaction potential, the intelligent evaluation model is established in this paper. And liquefaction potential of soil layers in the area of the oversize Runyang Yangtze River Highway Bridge project is determined. Moreover, the results are compared with those obtained by using the specification method and other methods. The space distribution probability of the sand layer in potential liquefaction is investigated as well as the characteristics of the probability. The results obtained from the intelligent evaluation model are satisfying,which demonstrates that the presented method is feasible and reliable. This study provides a theoretical basis for the bridge design and construction,and it has great practical significance in the reliability analysis and optimal design of foundation projects.
Based on the mixed genetic algorithms(GAs),the in-situ data of the standard penetration test(SPT) and examples of earthquake-induced liquefaction potential, the intelligent evaluation model is established in this paper. And liquefaction potential of soil layers in the area of the oversize Runyang Yangtze River Highway Bridge project is determined. Moreover, the results are compared with those obtained by using the specification method and other methods. The space distribution probability of the sand layer in potential liquefaction is investigated as well as the characteristics of the probability. The results obtained from the intelligent evaluation model are satisfying,which demonstrates that the presented method is feasible and reliable. This study provides a theoretical basis for the bridge design and construction,and it has great practical significance in the reliability analysis and optimal design of foundation projects.
引文
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[2] 刘 颖,谢君斐.砂土震动液化[M].北京:地质出版社,1984.30-42.
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[4] 汪明武,罗国煜.最优化法在砂土液化势评价中的应用[J].岩土工程学报,1999,21(6):704-706.
[5] 吴世明,徐攸在.土动力学现状与发展[J].岩土工程学报,1998,20(3):125-131.
[6] AnthonyT C.Seismic liquefaction potential assessed by neural networks[J].Journal ofGeotechnicalEngineering,1994,120(9):1467-1480.
[7] 汪明武.区域稳定性智能评价与控制的模型及方法研究[D].南京:南京大学地球科学系,1999.
[8] JuangC H,ChenC J,TangW H,et al.CPT-based liquefaction analysis,Part1:Determination of lim it state function[J].Geotechnique,2000,50(5):583-592.
[9] 汪明武罗国煜.可靠性分析在砂土液化势评价中的应用[J].岩土工程学报,2000,22(5):542-544.
[10] JuangC H,RosowskyD V,TangW H.Reliability-based m ethod for assessing liquefaction potential of soils[J].Journal ofGeotechnical andGeoenvironm entalEngineering,1999,125(8):684-689.
[11] SeedH B,Tokim atsuK,HarderL F ,etal.Influence ofSPT procedures in soil liquefaction resistance evaluations[J].JGeotechEngrg,1985,111(12):1425-1445.
[12] TokimatsuK ,Yoshim iY .Em pirical correlation of soil liquefaction based onSPT N -value and fines content[J].SoilsFound,1983,23(4):56-74.
[13] 焦李成.神经网络系统理论[M].西安:西安电子科技大学出版社,1990.242-251.
[14] 周 明,孙国栋.遗传算法原理及应用[M].北京:国防工业出版社,1999.4-10.
[15] 金菊良,丁 晶.遗传算法及其在水科学中的应用[M].成都:四川大学出版社,2000.84-87.
[16] SeedH B,IdrissI M.Sim plified procedure for evaluating soil liquefaction potential[J].JGeotechEngrgDiv,1971,97(9):1249-1273.
[17] 刘恢先.唐山大地震震害(一)[M].北京:地震出版社,1988.301-429.
[18] 汪明武,李 丽,罗国煜.基于MonteCarlo模拟的砂土液化评估研究[J].工程地质学报,2001,9(2):214-217
[2] 刘 颖,谢君斐.砂土震动液化[M].北京:地质出版社,1984.30-42.
[3] 周 健,屠洪权,缪俊发.地下水位与环境岩土工程[M].上海:同济大学出版社,1995.101-112.
[4] 汪明武,罗国煜.最优化法在砂土液化势评价中的应用[J].岩土工程学报,1999,21(6):704-706.
[5] 吴世明,徐攸在.土动力学现状与发展[J].岩土工程学报,1998,20(3):125-131.
[6] AnthonyT C.Seismic liquefaction potential assessed by neural networks[J].Journal ofGeotechnicalEngineering,1994,120(9):1467-1480.
[7] 汪明武.区域稳定性智能评价与控制的模型及方法研究[D].南京:南京大学地球科学系,1999.
[8] JuangC H,ChenC J,TangW H,et al.CPT-based liquefaction analysis,Part1:Determination of lim it state function[J].Geotechnique,2000,50(5):583-592.
[9] 汪明武罗国煜.可靠性分析在砂土液化势评价中的应用[J].岩土工程学报,2000,22(5):542-544.
[10] JuangC H,RosowskyD V,TangW H.Reliability-based m ethod for assessing liquefaction potential of soils[J].Journal ofGeotechnical andGeoenvironm entalEngineering,1999,125(8):684-689.
[11] SeedH B,Tokim atsuK,HarderL F ,etal.Influence ofSPT procedures in soil liquefaction resistance evaluations[J].JGeotechEngrg,1985,111(12):1425-1445.
[12] TokimatsuK ,Yoshim iY .Em pirical correlation of soil liquefaction based onSPT N -value and fines content[J].SoilsFound,1983,23(4):56-74.
[13] 焦李成.神经网络系统理论[M].西安:西安电子科技大学出版社,1990.242-251.
[14] 周 明,孙国栋.遗传算法原理及应用[M].北京:国防工业出版社,1999.4-10.
[15] 金菊良,丁 晶.遗传算法及其在水科学中的应用[M].成都:四川大学出版社,2000.84-87.
[16] SeedH B,IdrissI M.Sim plified procedure for evaluating soil liquefaction potential[J].JGeotechEngrgDiv,1971,97(9):1249-1273.
[17] 刘恢先.唐山大地震震害(一)[M].北京:地震出版社,1988.301-429.
[18] 汪明武,李 丽,罗国煜.基于MonteCarlo模拟的砂土液化评估研究[J].工程地质学报,2001,9(2):214-217
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