标题: 利用类神经网路探讨建物砖墙提供之劲度
The Study of Brick Wall-Stiffness in Building by ANN
作者: 宋嘉修
Sung, Chia-Hsiu
郑复平
Fu-Ping Cheng
土木工程学系
关键字: 砖墙;类神经网路;劲度;Brick Wall;ANN;Stiffness;network
公开日期: 1996
摘要: 在房屋进行结构分析时,砖墙常是被忽略的。但是砖墙的存在使得其四周梁、柱之受
力情形改变,当大地震来袭时,极可能因而发生脆性破坏。砖墙在房屋结构中之分布并不
规则,若要一一考虑,不仅复杂且极为不便。影响结构物反应之因素有构件挠曲刚度EI、
楼层质量、接头刚域、结构物之阻尼比等,本文针对构件挠曲刚度EI、楼层质量及砖墙劲
度三个因素来研究。
本研究以类神经网路为方法,利用类神经网路最佳化的功能,求得近似实际结构量测
所得振动讯号时之砖墙等值斜撑杆件有效宽度、构件挠曲刚度及楼层质量。
当神经网路完成学习之后,以其求得等值斜撑有效宽度、构材挠曲刚度、楼层质量
。其结果显示,等值斜撑有效宽度应为0.2429倍之等值斜撑长度;构材之挠曲刚度EI需提
高至1.207倍;结构物之楼层质量应提高为1.2倍。
Brick wall is usually ignored in structure analysis of a building. But the
existence of brick wall will make the change of beams or columns around it,
and the brittle failure will happen when it undergoes earthquakes. The
distribution of brick wall in a structure of building is too irregular to
concern individually. The factors that influence the response of structure a
reflexure rigidity EI, mass of floor, rigid zone of beam-column, damping ratio
and so on. This thesis only considers EI, mass of floor and stiffness of bric
kwall.
This thesis aims to find the equivalent bracing width of brick wall, EI and
mass of floor which match the measured value by using optimization o
fArtificial Neural Network(ANN).
When ANN completes the learning, it will output the three values above.F
rom the results, it is noted that the equivalent bracing width should equal to
0.2429 times the equivalent bracing length; EI should be risen to 1.207 times
, and the mass of floor should be risen to 1.2 times.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT850015039
http://hdl.handle.net/11536/61410
显示于类别:Thesis