参数平移相关类的形不变势的多参数变形

证明了对参数平移相关的所有一维形不变势，都可以求得其多参数变莆而以ｑ作为变形参数。     

隧道开挖超小变形监测与数值仿真分析

为有效预测和控制隧道开挖引起的地表超小变形，首先基于随机介质理论和MATLAB软件编写反分析程序，对地表沉降的实测数据进行拟合，反演断面收敛面积ΔA和地层影响角β,并研究ΔA与隧道埋深Z以及ΔA与tanβ的关系。其次，基于滚动预测的方法建立反向传播(back propagation, BP)神经网络，并预测隧道断面DM-1未来的地表超小变形值。结果表明：ΔA的取值较离散，随着隧道埋深Z的增加，ΔA呈逐渐减小趋势，地层损失也随之减小，当隧道埋深约为20.53 m时，收敛面积ΔA接近0。随着ΔA的逐渐增大，tanβ逐渐减小，当隧道埋深约为20.53 m时，tanβ约为0.447。通过滚动预测的方法建立的BP神经网络误差值较小，可以很好地预测隧道开挖引起的地表超小变形值，对类似的工程具有较好的指导意义。     

薄壁网孔工件在数控冲床加工中的变形分析

为了避免数控转塔冲床加工薄壁网孔工件时的表面翘曲变形，实验中从控制加工网孔工件的平整度、增大板料压紧力和选择合适冲切方向与顺序3个方面来减小薄壁网孔工件的变形量．结果表明，1m×2m以上的产品，通过以上方法，变形量由原来的4～5mm成功地控制到1mm的范围内，能让数控机床正常工作，达到产品质量要求．     

米仓山南缘基底断裂带上两段有限应变和形成条件

采用有限应变测量方法对上两断裂带变形作了全面而系统的分析 ,在断裂带变形特征、变形条件、变形机制等方面取得了一系列重要的认识 ,提供了大量的定量参数 ,大大深化了前人对该区的认识。     

强夯处治粉煤灰路基的显式动力非线性数值模拟

基于显式动力非线性有限元分析方法,利用ANSYS/LS-DYNA软件对强夯问题进行分析,得出了显式动力非线性数值模拟方法的一般步骤.结合某路基强夯实例建立三维立体模型,对碰撞过程进行数值模拟,得到了强夯加固范围及夯后土体的应力场、位移场.通过与现场实测数据的比对,验证了显式动力非线性有限元数值模拟方法在强夯问题中的适用性.在此基础上,研究和探讨了岳阳地区强夯处治粉煤灰路基中的夯锤参数选取问题,分析比较了夯后土体的沉降,结果表明同能级下重锤低落距有更好的加固效果.     

三次指数平滑法在基坑地表沉降变形分析中的应用

根据某地铁车站基坑施工过程中地表沉降监测的实测资料,应用三次平滑指数法进行沉降变形的预测,充分证实了在地表沉降变形分析中该预测法的可行性;研究结果表明:在现有地铁车站基坑地表沉降14期观测数据参与建模条件下,三次指数平滑法与时间序列ARIMA(1,1,1)模型相比,其均方误差MSE较小,模型的预测值与吻合较好,平均残差值为-0.010 1,平均相对误差为-0.219 0,确保了地铁车站的正常施工及安全使用,为后续工程建设提供保障。     

基于概率积分法的重复采动地表变形GJ-CB预计算法

煤炭资源开采必然对地表产生影响,准确预计开采后地表变形程度是实现地表建筑物安全的重要举措.多学科多领域的结合对煤矿科学安全开采起到了很大的促进作用,以概率积分法为基础,应用距离幂次反比法对其进行改进,形成了一套完整的重复采动地表变形GJ-CB预计算法.并以GJ-CB预计算法为基础开发了《重复采动条件下地表变形叠加系统》,通过某矿的应用检验,得出将该系统和算法预计精度较高,结果可靠.     

基于VTK的地下矿开采沉陷预计研究与实现

为对地表沉陷进行方便准确的预计,以大型可视化工具包VTK为开发平台,对VTK过滤器进行扩展,将开采沉陷预计算法写入VTK过滤器,实现地下矿开采沉陷预计及三维可视化.首先设计vtk Conforming Delaunay2D类,实现相容Delaunay三角化,得到高质量的地表模型;再根据沉陷预计模型,设计开采沉陷预计过滤器vtk Subsidence Filter,实现沉陷计算;然后基于VTK实现属性提取和后处理,进而实现沉陷地表的动态更新;最后建立VTK流水管线,将结果三维可视化.该方法突破了以往VTK主要用于三维可视化的局限,通过扩展VTK过滤器,拓宽了其专业应用.研究成果可用于地下煤矿与金属矿开采沉陷预计、开采沉陷的土地资源管理与复垦以及自然崩落法放矿的矿岩接触面模拟.     

Prediction of hot deformation behavior in Ni-based alloy considering the effect of initial microstructure

High temperature heat treatments were conducted for as-cast N08028 alloy to obtain various microstructures with different amounts of σ-phase,and then hot compression tests were carried out using Gleeble-3500 thermo-mechanical simulator in deformation temperature range from 1100 to1200 ℃ and strain rate range from 0.01 to 1 s-1. For the same initial microstructure, the flow stress was observed to increase with increasing the strain rate and decreasing the deformation temperature, while for the same deformation condition, the flow stress was found to increase with increasing the amount of σ-phase in the initial microstructure. Moreover, dynamic recrystallization was found to be the main dynamic soften mechanism. On this basis, Arrhenius-type constitutive equations and artificial neural network(ANN) model with back-propagation learning algorithm were established to predict hot deformation behavior of the alloy. Furthermore, the parameters of constitutive equations were found to be dependent on the initial microstructure, which was also as one of the inputs for the ANN model. Suitability of the two models was evaluated by comparing the accuracy, correlation coefficient and average absolute relative error, of the prediction. It is concluded that the ANN model is more accurately than the constitutive equations.     

Hot deformation behavior and the processing map of Zr–1.0Be alloy in single α phase

The hot deformation behavior,hot workability and dynamic recrystallization evolution of Zr-1.0(wt%) Be alloy in single a phase were investigated by conducting hot compression tests.The strain rates ranging from 10~(-3) s~(-1) to 10° s~(-1) and testing temperatures varying from 650 ℃to 850℃ were used.Flow stress was found to increase with increasing strain rate and decrease with the increment of the deformation temperature.A constitutive equation of flow behavior was established to describe the dependence of flow stress on strain rate and deformation temperature.The activation energy for deformation of Zr-1.0Be alloy was determined to be Q= 301 kJ/mol.The processing map of Zr-1.0Be alloy was constructed at strain rates ranging from 10~(-3) s~(-1) to 10° s~(-1) and deformation temperatures varying from 650 ℃ to 850 ℃ at the true strain of 0.7.A processing map was used to identify the best domains of thermal processing,including a domain at a temperature of 650 ℃ and strain rate of 10~(-3) s~(-1) as well as another domain at deformation temperatures ranging from 800 ℃ to 850 ℃ and strain rates varying from 10~(-3) s~-~(-1) to 10~(-1) s~(-1).Microscopic analysis of Zr-l.OBe alloy showed that the flow instability and kink were very obvious at low temperatures and high strain rates.At high temperatures and low strain rates,the dynamic recrystallization became the main softening mechanism during hot working.