季冻区填土路基沉降预测及其附加应力分析
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摘要
季冻区路基沉降同时受到温度场、水分场及应力场影响，其变形过程中影响因素众多，主要受到季冻区地质条件、路基填土高度、填土材料、施工工艺以及气候条件等的综合影响。路基在各种影响因素共同作用下会造成不均匀沉降。不均匀沉降和季节性冻结和融化引起的路基路面不均匀变形已经成为路面结构破坏的主要原因。由于路基的不均匀变形将对路面结构层产生附加应力，叠加行车荷载产生的应力将使路面结构产生裂缝，容易引起路面结构的早期破坏。
论文以吉林省交通厅科技项目《国道102线路基冻融稳定性监测方法研究》为依托，以京哈线一级公路长春至德惠段试验路为研究对象，对季冻区填土路基沉降预测及其附加应力进行了分析研究，通过本文的研究取得了以下研究成果：
1.经过对国内外路基沉降监测技术与预测方法等研究现状进行综合分析的基础上，根据实际工程京哈线一级公路路基本身的特点，结合已有公路路基沉降监测情况制定试验路路基沉降监测的方案，并对所设监测点进行路基沉降监测。将各试验路段的现场实测数据结合路基沉降机理和路基沉降发展规律进行了详细的分析。
2.对基于实测数据的预测方法进行了总结，并对常用的静态预测法和动态预测法进行了介绍。依据试验路段的现场实测数据利用双曲线法、指数曲线法和灰色理论进行了实时预测研究，经过研究发现，应用的双曲线、指数曲线、GM(1,1)灰色理论预测模型预测结果与现场实测结果较好,说明这三种方法在道路路基沉降预测中具有一定的适用性。三者相比，双曲线、指数曲线预测方法方便简单，预测路基最终沉降量的计算程序简单易懂,计算内存需求量小。但是这种方法需满足某些特定的条件，不然预测精度会极度下降。灰色理论预测模型建立在严格的数学理论基础上,预测结果具有更高的精度。灰色理论预测中的参数是固定不变的，是不能受地质条件、外界环境因素等变化而变化的，而且数据量过大时，相应的计算量也会增大，减小了这种方法的实用性。
3.本文针对横向纵向沉降按空间曲面变化特点。提出路基路面横向沉降规律按抛物线变化，横向各测点随时间按双曲线或指数数规律变化来研究路面横断面的沉降规律。这一方法是根据已观测的沉降数据，利用最小二乘法确定路基横向沉降曲面，预测最终的沉降量。此方法能够综合横向影响因素，确定截面的最大沉降量，并且能够研究路面横向结构的不均匀沉降规律。
4.本文提出了指数曲线与神经网络混合建模法对道路路基沉降进行预测。依据该方法，认为路基沉降规律分为确定部分和不确定部分，确定部分用指数曲线法建模，不确定部分用神经网络建模，从而得到混合沉降模型。通过指数法利用了指数法简单快捷的特点，反映了路基沉降的主要规律，同时，又用神经网络法预测了路基沉降中的不确定部分，由于神经网络法只对沉降中的不确定部分进行预测，为达到相同的预测精度，混合建模中的神经网络模型相对于单独神经网络模型计算规模小，训练速度快。通过对一段试验路段实测数据的预测，证明将两种方法整合到一起，其预测结果更为精确，效率更高。为道路路基沉降预测提供了一种新的有效的方法。
5.针对季冻区路基不均匀沉降的影响因素和沉降规律，总结了两种路基沉降模式。并利用winkler地基模型对路基沉降引起的附加应力进行了分析。分析结果表明，最大沉降量对应力影响较大，地基系数值对横向应力的影响较小，无法通过提高地基系数来减少附加应力。地基模量和应力成线性关系，这说明，基层模量E越大，对路基的要求越高。利用三维有限元法对路基两种不均匀沉降模式进行了有限元法分析，分析结果和winkler地基梁分析结果基本一致。证明了winkler地基梁分析不均匀沉降的有效性。
Subgrade subsidence in season frozen area affected by the temperature field, moisturefield and stress field at the same time, in the process of its deformation affected by manyfactors, mainly from the season frozen area geological conditions, height of subgrade filling,filling materials, construction technology and the comprehensive influence of climateconditions etc. Subgrade under the effect of various factors affecting joint will cause unevensettlement. The uneven roadbed deformation caused by uneven settlement and seasonalfreezing and melting has become the main damage reason of the pavement structure. Due toinhomogeneous deformation of roadbed will generate additional stress of pavement structurelayer, superimposed stress produced by the action of vehicle load will make the pavementcracks, easy to cause pavement early damage.
The paper was based on the science and technology project come from communicationsdepartment of Jilin province “Monitoring methods study of Freeze-thaw stability of thenational highway102line” as the backing, with the study of Beijing-Harbin line first classhighway in Changchun to Dehui period of test road as the research object, analysised theroadbed settlement prediction and its additional stress in the season frozen area, through theresearch of this paper has the following findings:
1Based on the comprehensive analysis of roadbed subsidence monitoring technologyand the status of forecast methods, according to the practical engineering Beijing-Haerbinline first class highway roadbed itself characteristics and with the combination of existinghighway roadbed subsidence monitoring situation established the roadbed settlementmonitoring plan, and monitor the roadbed settlement monitoring point was set. All testsections of the measured data combining with the subgrade settlement mechanism and theroadbed settlement law of development are analyzed in detail.
2Summarized the forecast method based on the measured data, and introduced the prediction method of static and dynamic prediction method. According to the test section ofthe site measured data using the hyperbolic method, exponential curve method and greytheory to the real-time prediction research, with a study found that application of hyperbolaand exponential curve, GM (1,1) grey theory prediction model results with the fieldmeasured results is better, shows that the three methods in roadbed settlement prediction hascertain applicability. Compared the three, hyperbola and exponential curve predictionmethod is convenient and simple, the prediction of final subgrade settlement calculationprocedure is simple and easy to understand, and the memory footprint is small. But thismethod needs to meet certain conditions, or prediction accuracy will fell dramatically. Greytheory prediction model is established on the basis of strict mathematical theory, and theprediction results with higher precision. Grey theory forecast of the parameter is fixed, itwould not affected by geological conditions and external environment factors, but as the dataincreased the corresponding calculation also increased, thus reduced the practicability of thismethod.
3Based on the transverse longitudinal settlement according to the characteristic of spacecurved surface changes. Proposed settlement of roadbed transverse law according to theparabola change, lateral each measuring point number rule changes over time according tothe hyperbolic or index to study the settlement of road cross section are studied. This methodis based on has been observed settlement data, the least square method is used to determinethe settlement of roadbed lateral surface, forecast the final settlement. This method cancomprehensive transverse impact factors, determine the maximum settlement of section, andto study the transverse structure of uneven settlement rule.
4This paper presented index curve and neural network hybrid modeling method to predictroadbed settlement. According to the method that roadbed settlement rules are divided intoascertain and uncertainty, the ascertain part using the exponential curve method modelingand uncertainty using neural network modeling, and mixed sedimentation model is obtained.By using the index method’s characteristics of simple and quick, reflects the main law ofsubgrade settlement, at the same time, and use the neural network to predict the uncertainparts of roadbed settlement, due to the neural network only to forecast the settlement of uncertainty, to achieve the same accuracy, the calculation scale of hybrid neural networkmodel in the modeling is smaller to the single neural network model, the training speed isfast. Through the prediction of section of test section of the measured data, proved that takethe two methods together, the forecasting result will be more accurate and more efficient.Provides a new effective method for roadbed settlement prediction.
5For the influence factors of subgrade differential settlement and settlement rule,summarizes two roadbed settlement patterns in season frozen area. And use the Winklersubgrade model to analyzed the additional stress caused by roadbed settlement, and theanalysis results show that the maximum subsidence influenced the stress obviously, andsubgrade coefficient value's influence on the lateral stress is lesser, it can't reduce theadditional stress by increasing the subgrade coefficient. Subgrade modulus and stress has alinear relationship, this shows that the subgrade modulus E higher the greater requirement ofroadbed. Using three-dimensional finite element method to analyzed the subgradedifferential settlement of the two kinds of mode, the results of the analysis and the Winklersubgrade beam analysis results are basically identical. Proved that the validity of the Winklersubgrade beam analysis of uneven settlement.
论文以吉林省交通厅科技项目《国道102线路基冻融稳定性监测方法研究》为依托，以京哈线一级公路长春至德惠段试验路为研究对象，对季冻区填土路基沉降预测及其附加应力进行了分析研究，通过本文的研究取得了以下研究成果：
1.经过对国内外路基沉降监测技术与预测方法等研究现状进行综合分析的基础上，根据实际工程京哈线一级公路路基本身的特点，结合已有公路路基沉降监测情况制定试验路路基沉降监测的方案，并对所设监测点进行路基沉降监测。将各试验路段的现场实测数据结合路基沉降机理和路基沉降发展规律进行了详细的分析。
2.对基于实测数据的预测方法进行了总结，并对常用的静态预测法和动态预测法进行了介绍。依据试验路段的现场实测数据利用双曲线法、指数曲线法和灰色理论进行了实时预测研究，经过研究发现，应用的双曲线、指数曲线、GM(1,1)灰色理论预测模型预测结果与现场实测结果较好,说明这三种方法在道路路基沉降预测中具有一定的适用性。三者相比，双曲线、指数曲线预测方法方便简单，预测路基最终沉降量的计算程序简单易懂,计算内存需求量小。但是这种方法需满足某些特定的条件，不然预测精度会极度下降。灰色理论预测模型建立在严格的数学理论基础上,预测结果具有更高的精度。灰色理论预测中的参数是固定不变的，是不能受地质条件、外界环境因素等变化而变化的，而且数据量过大时，相应的计算量也会增大，减小了这种方法的实用性。
3.本文针对横向纵向沉降按空间曲面变化特点。提出路基路面横向沉降规律按抛物线变化，横向各测点随时间按双曲线或指数数规律变化来研究路面横断面的沉降规律。这一方法是根据已观测的沉降数据，利用最小二乘法确定路基横向沉降曲面，预测最终的沉降量。此方法能够综合横向影响因素，确定截面的最大沉降量，并且能够研究路面横向结构的不均匀沉降规律。
4.本文提出了指数曲线与神经网络混合建模法对道路路基沉降进行预测。依据该方法，认为路基沉降规律分为确定部分和不确定部分，确定部分用指数曲线法建模，不确定部分用神经网络建模，从而得到混合沉降模型。通过指数法利用了指数法简单快捷的特点，反映了路基沉降的主要规律，同时，又用神经网络法预测了路基沉降中的不确定部分，由于神经网络法只对沉降中的不确定部分进行预测，为达到相同的预测精度，混合建模中的神经网络模型相对于单独神经网络模型计算规模小，训练速度快。通过对一段试验路段实测数据的预测，证明将两种方法整合到一起，其预测结果更为精确，效率更高。为道路路基沉降预测提供了一种新的有效的方法。
5.针对季冻区路基不均匀沉降的影响因素和沉降规律，总结了两种路基沉降模式。并利用winkler地基模型对路基沉降引起的附加应力进行了分析。分析结果表明，最大沉降量对应力影响较大，地基系数值对横向应力的影响较小，无法通过提高地基系数来减少附加应力。地基模量和应力成线性关系，这说明，基层模量E越大，对路基的要求越高。利用三维有限元法对路基两种不均匀沉降模式进行了有限元法分析，分析结果和winkler地基梁分析结果基本一致。证明了winkler地基梁分析不均匀沉降的有效性。
Subgrade subsidence in season frozen area affected by the temperature field, moisturefield and stress field at the same time, in the process of its deformation affected by manyfactors, mainly from the season frozen area geological conditions, height of subgrade filling,filling materials, construction technology and the comprehensive influence of climateconditions etc. Subgrade under the effect of various factors affecting joint will cause unevensettlement. The uneven roadbed deformation caused by uneven settlement and seasonalfreezing and melting has become the main damage reason of the pavement structure. Due toinhomogeneous deformation of roadbed will generate additional stress of pavement structurelayer, superimposed stress produced by the action of vehicle load will make the pavementcracks, easy to cause pavement early damage.
The paper was based on the science and technology project come from communicationsdepartment of Jilin province “Monitoring methods study of Freeze-thaw stability of thenational highway102line” as the backing, with the study of Beijing-Harbin line first classhighway in Changchun to Dehui period of test road as the research object, analysised theroadbed settlement prediction and its additional stress in the season frozen area, through theresearch of this paper has the following findings:
1Based on the comprehensive analysis of roadbed subsidence monitoring technologyand the status of forecast methods, according to the practical engineering Beijing-Haerbinline first class highway roadbed itself characteristics and with the combination of existinghighway roadbed subsidence monitoring situation established the roadbed settlementmonitoring plan, and monitor the roadbed settlement monitoring point was set. All testsections of the measured data combining with the subgrade settlement mechanism and theroadbed settlement law of development are analyzed in detail.
2Summarized the forecast method based on the measured data, and introduced the prediction method of static and dynamic prediction method. According to the test section ofthe site measured data using the hyperbolic method, exponential curve method and greytheory to the real-time prediction research, with a study found that application of hyperbolaand exponential curve, GM (1,1) grey theory prediction model results with the fieldmeasured results is better, shows that the three methods in roadbed settlement prediction hascertain applicability. Compared the three, hyperbola and exponential curve predictionmethod is convenient and simple, the prediction of final subgrade settlement calculationprocedure is simple and easy to understand, and the memory footprint is small. But thismethod needs to meet certain conditions, or prediction accuracy will fell dramatically. Greytheory prediction model is established on the basis of strict mathematical theory, and theprediction results with higher precision. Grey theory forecast of the parameter is fixed, itwould not affected by geological conditions and external environment factors, but as the dataincreased the corresponding calculation also increased, thus reduced the practicability of thismethod.
3Based on the transverse longitudinal settlement according to the characteristic of spacecurved surface changes. Proposed settlement of roadbed transverse law according to theparabola change, lateral each measuring point number rule changes over time according tothe hyperbolic or index to study the settlement of road cross section are studied. This methodis based on has been observed settlement data, the least square method is used to determinethe settlement of roadbed lateral surface, forecast the final settlement. This method cancomprehensive transverse impact factors, determine the maximum settlement of section, andto study the transverse structure of uneven settlement rule.
4This paper presented index curve and neural network hybrid modeling method to predictroadbed settlement. According to the method that roadbed settlement rules are divided intoascertain and uncertainty, the ascertain part using the exponential curve method modelingand uncertainty using neural network modeling, and mixed sedimentation model is obtained.By using the index method’s characteristics of simple and quick, reflects the main law ofsubgrade settlement, at the same time, and use the neural network to predict the uncertainparts of roadbed settlement, due to the neural network only to forecast the settlement of uncertainty, to achieve the same accuracy, the calculation scale of hybrid neural networkmodel in the modeling is smaller to the single neural network model, the training speed isfast. Through the prediction of section of test section of the measured data, proved that takethe two methods together, the forecasting result will be more accurate and more efficient.Provides a new effective method for roadbed settlement prediction.
5For the influence factors of subgrade differential settlement and settlement rule,summarizes two roadbed settlement patterns in season frozen area. And use the Winklersubgrade model to analyzed the additional stress caused by roadbed settlement, and theanalysis results show that the maximum subsidence influenced the stress obviously, andsubgrade coefficient value's influence on the lateral stress is lesser, it can't reduce theadditional stress by increasing the subgrade coefficient. Subgrade modulus and stress has alinear relationship, this shows that the subgrade modulus E higher the greater requirement ofroadbed. Using three-dimensional finite element method to analyzed the subgradedifferential settlement of the two kinds of mode, the results of the analysis and the Winklersubgrade beam analysis results are basically identical. Proved that the validity of the Winklersubgrade beam analysis of uneven settlement.
引文
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