The Study Of The Deformation Ang Monitoring Of High-filled Loess Slope

With the development of economy and city construction in China,construction project in Loess Area goes into a rapid stage,loess high fill engineering is an unknown part.Therefore,the stability of loess embankment slope is one of the key research topic in rock and soil engineering,once the failure will bring disastrous consequences to the engineering construction and people's property security.Based on the background of Henan province Wulong community projects,this paper combines the previous survey data,and masters the profile of the study area geology and basic features;on the basis of field investigation and indoor test,it studies engineering geological conditions of the establishment of fill,establishes fill loading slope geological structure model;through the theory analysis of anti-slide pile and pile sheet pile retaining wall deformation mechanism,and then scene monitoring the deformation of supporting structure;finally,combined with the mathematical theory,it predicts the development trend of the deformation of the retaining structure.Through the above work,the main research results are as follows:?1?By combining the field test and laboratory test,we get the filler remodeling(Q₃^eol)compaction rate,the water content of Ma Lan loess and the compaction degree of Ma Lan loess,and they are lower than the standard.Through the contrast analysis,low moisture content and compaction degree will reduce the fill slope stability,and cause large settlement after construction,according to the settlement value of layer wise summation method prediction of embankment after construction.?2?According to the actual situation on site,calculating two kinds of supporting force?i.e.,soil pressure,residual sliding force?,through the theoretical mechanics research under different external support structure deformation mechanisms,combining with the actual deformation condition,it concludes the pile deformation force for wall back soil pressure;on this basis,combined with the pile wall deformation history,a"conceptual model"of crack evolution and the height of soil loading is established.?3?Based on the deformation phenomenon of fill slope,Using the IBIS-L system real-time monitoring of the deformation process,the system sets the step frequency continuous wave?SF-CW?technology,synthetic aperture radar?SAR?and differential interference measuring technology,compared with the traditional monitoring technology has the advantages of high precision,wide range of automation and monitoring.?4?After the first stage for nearly half a month of monitoring data analysis,generated by the displacement contours reflects the fill slope supporting structure showed obvious regional features;on this basis,selected 10 representative monitoring points Pix,compared to the deformation of the points,such as the amount of displacement of the cumulative growth,growth rate,derived deformation of supporting structure differences and unity.?5?The IBIS-L monitoring combined with the site temperature monitoring,it is concluded that the deformation displacement correlation with temperature change,namely the deformation displacement along with the rise and fall of temperature increase and decrease.Therefore,Using the displacement of statically determinate structure calculation principle when temperature changes,draw a point on the anti-slide pile deformation under the condition of the temperature changes?inflation?is proportional to the temperature difference,distance from the embedded solid quadratic distance relationship,the quantitative interpretation of concrete heat bilges cold shrink phenomenon.?6?In order to study the deformation trend of fill slope supporting structure,applying the grey system theory to the deformation of supporting structure prediction,respectively set up traditional grey GM?1,1?and metabolism grey GM?1,1?prediction model.Through the analysis of the reliability and adaptability of the model,it is concluded that in the long term forecast,metabolism grey GM?1,1?prediction model than traditional grey GM?1,1?prediction model prediction results more accurate.