【作者】 王伟；

【导师】 鲁彩凤；

【作者基本信息】 中国矿业大学 ， 结构工程， 2018， 硕士

【摘要】 近年来,建筑火灾的频发,不但危害了人类的生命财产安全,同时还对建筑结构本身产生了不利的影响。而在高层建筑和桥梁等工程结构中广泛使用的深受弯构件,其受力性能对整个结构具有较大的影响。因此,本文共设计并制作了17根深受弯梁,其中8根用于常温下的抗剪试验,9根用于火灾后的抗剪试验。分别研究了火灾高温、剪跨比和跨高比对深受弯构件受剪承载力、挠度、钢筋应变、最大裂缝宽度和破坏形态的影响;并结合ABAQUS有限元分析结果和粒子群神经网络算法分别建立了常温下及高温后深受弯构件的抗剪承载力预测模型。对常温下的深受弯构件进行了试验研究和ABAQUS有限元模拟,讨论和分析了跨高比和剪跨比对深受弯试件抗剪性能的影响。结果表明:(1)其他条件相同时,随着剪跨比的增大,深受弯试件的初裂剪力和极限剪力均是减小的;(2)当试件的跨高比相同时,在同一荷载作用下,试件的跨中挠度随着剪跨比的增大而逐渐增大;(3)对于深受弯试件的抗剪承载力,水平腹筋的作用大于竖向箍筋的作用;(4)对于跨高比不同的试件,剪跨比对试件裂缝宽度的影响是一致的,即在同一荷载作用下,试件的裂缝宽度随着剪跨比的增大而增大;(5)ABAQUS能较好的模拟出深受弯构件的受力情况,且模拟结果较好,与试验值和拉-压杆理论模型均吻合的较好。对火灾高温后的深受弯构件进行了试验研究,讨论和分析了火灾高温温度、跨高比和剪跨比对深受弯试件抗剪性能的影响。结果表明:(1)其他条件相同时,随着火灾高温的升高,深受弯试件的受剪承载力先增加后减小;且随着试件剪跨比和跨高比的增大,高温对试件受剪承载力的影响逐渐减弱;(2)在同一荷载作用下,随着受火温度的升高,试件的挠度总体上是逐渐增大的;在同一高温煅烧后,试件的挠度随着剪跨比和跨高的增大而逐渐增大。基于传热学理论及深受弯构件的抗剪理论,分别采用拉-压杆模型及我国混凝土结构设计规范中深受弯构件的抗剪规定对本文中火灾后深受弯构件的受剪承载力进行了计算,并与试验结果进行对比;结果表明:基于分层法的拉-压杆模型能够较好的预测火灾后深受弯构件的剩余受剪承载力,具有一定的适用性。针对BP神经网络易陷入局部最优、网络的鲁棒性和泛化能力较差等缺点,本文运用粒子群算法对BP神经网络的权值和阈值进行了优化。通过对大量试验结果数据的学习和训练,分别建立了深受弯构件抗剪承载力的BP神经网络预测模型和PSO-BP神经网络预测模型,并对两者的预测效果进行了比较。结果表明:与BP神经网络预测模型相比,PSOBP神经网络预测模型的预测精度较高,稳定性好,收敛速度快,在测试过程中其绝对误差率一直小于15%。更多还原

【Abstract】 In recent years,frequent building fires have caused huge losses.Fire not only causes loss of life and property,but also causes some damage to concrete in the buildings.Meanwhile,as deep flexural members are widely used in high-rise buildings and bridges,its mechanical performance has great influences on the whole structure.Therefore,in this paper,seventeen deep flexurnal members were designed and made,eight of which were used for shear test at ambient temperature,and nine of which were for shear test after fire.The effects of high temperature,shear span ratio and span-depth ratio on the shear bearing capacity,deflection,strains of steel,maximum crack width and failure mode of deep flexural members were investigated respectively.Combined with finite analysis results of ABAQUS and particle swarm optimization(PSO)neural network,the prediction model of shear capacity of deep flexural members at ambient temperature and after high temperature were established repectively.Experimental research and ABAQUS finite element simulation on deep flexural members at ambient temperature were carried out,and influence of span-depth ratio and shear span ratio on the shear behavior of deep flexural members was discussed and analyzed respectively.The results showed that when other condition are same,both the initial shear and ultimate shear strength of deep flexural member reduced with an increase in shear span ratio.When the spandepth ratio of specimens were same,under the same load,the mid span deflection of specimens increased with the increase of shear span ratio.Compared with the strain curves of longitudinal tensile steel bars,the strain curves of stirrups had positive and negative values and the changes along the horizontal axis were obvious.For the shear capacity of deep flexural members,the effect of horizontal web reinforcement was greater than that of vertical stirrups.For the specimens with different span-depth ratios,effect of the shear span ratio on the crack width of them were consistent.under the same load,the crack width of the specimen increased with the increase of the shear span ratio.ABAQUS can simulate the stress condition of the deep flexural members and the simulation results were better,which agreed well with the experimental value and strutand-tie model theory.Experimental researches on deep flexural members at ambient temperature were carried out,and influence of high temperature,span-depth ratio and shear span ratio on the shear behavior of deep flexural members was discussed and analyzed respectively.Results showed that when other condition are same,with the increase of high temperature,the shear capacity of specimens increased first and then decreased.Moreover,the effect of high temperature on the shear capacity of specimens weakened with the increase of shear span ratio and span-depth ratio.In general,under the same load,the deflection of specimen increased with an increase in high temperature,and the deflection of specimens increased with the increase of shear span ratio and span-depth ratio after same high temperature.The experimental data of this paper were analyzed based on the basic theory of heat transfer,shear theory of deep flexural members,strut-and-tie model and code for design of concrete structures.The results showed that the strut-and-tie model based on layered method could predict the shear capacity of deep flexural members after fire and had some applicability.In this paper,particle swarm optimization algorithm was used to optimize the weight and threshold of the BP neural network which was easy to fall into the local optimum and poor in robustness and generalization ability.By learing a large number of experimental data,the BP neural network prediction model and PSO-BP neural network prediction model for the shear bearing capacity of deep flexural members were established respectively,and performace of the two prediction model were compared.The results showed that compared with BP neural network prediction model,PSO-BP neural network prediction model had advantages of high prediction accuracy,fine stability and fast convergence speed.The absolute error rate of the test was always less than 15% throughout testing,which can meet the accuracy requirement of actual engineering.更多还原