Research On Ningbo Railway Hub Deformation Forecasting Combined By Finite Element Simulation And Excavation Monitoring

Monitoring and prediction are the key links and the bases of controlling in the process ofdeep foundation pit construction. Because the deep foundation pit engineering itself iscomplicated, there is a big difference between the engineering practice and the results thatcalculated by the existing mechanical models, the reason for this is that the model itself issimilar, including the complicated factors which are difficult to be modeled completely andthe inaccuracy of choosing the model parameters. Nowadays the foundation pit monitoringtechnology has reached a higher level. However, prediction methods which relies solely onmeasured data still exist technical problems, the reason is that mutation may happen in thedeformation process when working conditions or external factors change greatly. In this paper,I combine real-time monitoring and finite element simulation together to do some researchabout deformation prediction, and take the deep foundation pit construction process in Ningborailway hub as an engineering example to carry our experiment. The main research results inthis paper are as follows:1. Systematically elaborated the mechanism of deformation of deep foundation pit andcalculation method, analyzed main influence factors of the deep foundation pit deformation,and on this basis, the deep foundation pit deformation control measures are summarized.2. Took the deep foundation pit construction process in Ningbo railway hub as anexample, studied and analyzed the deformation monitoring method and data, got thedeformation rule and data to provide useful data for deformation prediction.3. Considered the main factors such as operating mode changes, carried out finiteelement simulation of the construction process of deep foundation pit. Deformation ofretaining structure was calculated under different construction nodes and compared with themonitoring data.4. Simply using the measured data to predict is difficult to overcome the effect ofmutations caused by conditions change. When conditions change seriously, stationary randomcharacteristics of deformation process will be destroyed and the prediction error will increasessignificantly. The finite element simulation is difficult to consider all the factors and thecorresponding parameters could not be so exactly, which will lead to the differences betweencalculated and measured value inevitably. Based on the practical project, this paper combinedthe finite element method with the measured values to predict, firstly used the finite elementto simulate the impact of changes in conditions, then used the neural network method to predict the change trend of the differences between them, lastly recovered the differencesbetween the predicted and the finite element simulation values to the actual deformationforecast. Because the differences between them are not affected by changes in workingconditions, this forecast is better than the traditional methods.5. Took the deep foundation pit construction process in Ningbo railway hub as anconstruction case, used the new method provided in this paper to do deformation predictionexperiments and got good results: compared with the predicted results of simply using themeasured data, usually the new method could reduce the average prediction error by about50%, verified the effectiveness of the new method.In this thesis, it has practical significance to ensure the safety of foundation pitconstruction and confirm the design of the supporting structure.