In this paper , based on resisting force model and load model , the limit state equations of rc bridge are established , thus the time - dependent relationship of rc bridge reliability is analyzed 本文在抗力衰减模型及桥梁荷载模型的基础上，通过建立耐久性极限状态方程，分析计算桥梁可靠度随时间的变化情况。
Therefore , studies on analysis and design method of cement concrete pavements in ultimate states based on actual composition of road traffic and temperature conditions become more important 因此,根据公路实际的交通组成和温度状况,研究水泥混凝土路面结构极限状态的分析和设计方法成为迫切需要解决的问题。
The random - fuzzy reliability model was built by taking the bar length , interception parameters as random variables and taking the fuzziness of safety state into consideration 摘要将弹性连杆机构的杆长、截面尺寸均视为随机变量，并考虑机构安全的极限状态的模糊性，建立了弹性连杆机构广义刚度可靠性分析模型。
The performance of highly nonlinear mapping for neural network was adopted to supply an explicit expression , so the method such as firstorder reliability method can be used again 该方法利用神经网络的非线性映射能力，构造出显式表达的极限状态方程，从而可以很方便的引入一次二阶矩等其他基本求解方法进行结构可靠度分析。
Examples indicate that the method is available and exact for implicit expressed performance function , and it is a new and effective way for structure reliability analysis 实例数值结果表明，基于神经网络将隐式函数转化为明确表达的极限状态方程是可行的，同时该方法具有较高的精度，为结构可靠度计算提供了新的有效思路和手段。
Concentrating on the questions and developmental directions of engineering structure reliability , the applicability of building steel structures that is studied relatively less is analyzed and studied 围绕工程结构可靠性发展中的存在问题及其发展方向，对研究相对较少的建筑钢结构适用性（正常使用极限状态）方面进行了相应的分析和研究。
According to the problem that performance functions for structures are difficult to be explicit expressed , a method based on neural network was utilized to transform the implicit function into an explicit expression 摘要针对结构可靠度分析中极限状态方程不能明确表达的情况，结合神经网络技术，提出了隐式极限状态方程转换为显式表达式的方法。
