压弯钢筋混凝土柱正截面极限承载力的预测——基于BP神经网络技术
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摘要
提出双向压弯钢筋混凝土柱正截面极限承载力的预测模型.以影响钢筋混凝土柱正截面极限承载力的主要因素(如:截面尺寸、混凝土强度、加载角度及配筋率等)为参数,用数值模拟结果为训练样本,建立了柱正截面极限承载力的BP神经网络预测模型.经验证,该模型对双向压弯钢筋混凝土柱正截面极限承载力具有良好的预测效果.
A model is presented to forecast the terminal bearing capacity in the sections of reinforced concrete (RC) columns under bi-axial bending and compression. By taking the main factors affecting the bearing capacity, such as the section dimension, the concrete strength, the loading angle and the reinforce ratio, as the model parameters, and by using the numerical simulation results as the training specimens, a forecasting model is established based on BP neural network. It is verified that the proposed model is of excellent forecasting ability for the terminal bearing capacity of RC columns under bi-axial bending and compression.
A model is presented to forecast the terminal bearing capacity in the sections of reinforced concrete (RC) columns under bi-axial bending and compression. By taking the main factors affecting the bearing capacity, such as the section dimension, the concrete strength, the loading angle and the reinforce ratio, as the model parameters, and by using the numerical simulation results as the training specimens, a forecasting model is established based on BP neural network. It is verified that the proposed model is of excellent forecasting ability for the terminal bearing capacity of RC columns under bi-axial bending and compression.
引文
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[2] KwanKH,LiauwTC.Computerizedultimatestrength analysisofreinforcedconcretesectionsubjectedto axialcompressionandbiaxialbending[J].Computers&Structures,1985,21(6):1119-1127.
[3] NourySIA,ChenWF.Behavioranddesignof reinforcedandcompositeconcretesections[J].Journal oftheStructuralDivision,1982,108(6):1266-1284.
[4] YeYing hua,DiaoBo.Nonlinearanalysisofconcrete structure[M].哈尔滨:哈尔滨工业大学出版社,1996.
[5] JiaoJun ting,YeYing hua,DiaoBo.Thebearing capacityanalysisofreinforcedconcreteL shaped cross sectionsunderbiaxialeccentriccompression[J].ProgressinNaturalScience,2003,13(6):429-433.
[6] 李永靖,王强,高平.基于改进BP神经网络的路基材料性能预测[J].辽宁工程技术大学学报,2004,23(1):57-58.LiYong jing,WangQiang,GaoPing.Forecastof propertiesofroadbedmaterialbasedonimprovableBP nervernetwork[J].JournalofLiaoningTechnical University,2004,23(1):57-58.
[7] 杨天才,刘鸿,程绍佳,等.一种神经网络模型在混凝土配比设计中的应用[J].武汉工程职业技术学院学报,2003,15(2):21-23.YangTian cai,LiuHong,ChengShao jia,etal.Design aboutburdenrationofconcretebasedonneuralnetwork[J].JournalofWuhanEngineeringInstitute,2003,15(2):21-23.
[8] 魏星,黄茂松,虎旭林.采用神经网络材料本构模型的智能有限元及其算法[J].宁夏大学学报,2002,23(3):237-240.WeiXing,HuangMao song,HuXu lin.Thediscussionof theintelligenceFEMbasedonneuralnetworkandits algorithm[J].JournalofNingxiaUniversity,2002,23(3):237-240.
[9] 范颖芳,周晶.受腐蚀钢筋混凝土梁极限承载力神经网络预测[J].大连理工大学学报,2003,43(3):349-353.FanYing fang,ZhouJing.Predictiononultimateload bearingcapacityofcoorodedreinforcedconcretebeams usingneuralnetworks[J].JournalofDalianUniversity Technology,2003,43(3):349-353.
[10] 雷汲川,白绍良.人工神经网络在双向板弹性内力计算中的应用[J].重庆建筑大学学报,2002,24(4):31-34.LeiJi chuan,BaiShao liang.Applicationofartificial neuralnetworkinelasticinternalforceanalysisoftwo wayslab[J].JournalofChongqingJiazhouUniversity,2002,24(4):31-34.
[11] 饶文碧,程洪斌,方复兴.结构损伤神经网络辨识系统的实现[J].武汉理工大学学报,2002,24(1):28-30.RaoWen bi,ChengHong bin,FangFu xing.Structuraldamageidentificationsystembasedon neuralnetwork[J].JournalofWuhanUniversityof Technology,2002,24(1):28-30.
[12] 吴波,李英民.基于神经网络的结构地震反应仿真[J].世界地震工程,2003,19(3):144-149.WuBo,LiYing min.Simulationofstructuralseismic responsesbasedonneuralnetworks[J].World EarthquakeEngineering,2003,19(3):144-149.
[13] 焦俊婷,叶英华,刁波.钢筋混凝土偏压构件截面非线性分析高斯积分[J].北京航空航天大学学报,2003,29(4):370-373.JiaoJun ting,YeYing hua,DiaoBo.Gaussnumerical integrationinnonlinearanalysisofreinforcedconcrete membersundereccentriccompressionloading[J].JournalofBeijingUniversityofAeronauticsand Astronautics,2003,29(4):370-373.
[14] 蒋宗礼.人工神经网络导论[M].北京:高等教育出版社,2001.
[15] 闻新,周露,王丹力,等.MATLAB神经网络应用设计[M].北京:科学出版社,2000.
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