Conventional methods of seismic rehabilitation with steel bracing could not be a proper method for upgrading of buildings with these methods due to the cost and time expenses. Therefore, an innovative passive control system called braced damper for steel frames has been introduced in this study. Thus, for investigating the behavior of this structural damper, a single-bay steel frame is formed without rotary brace damper device. Later, the frame is equipped with rotary brace damper and subjected to monotonic and cyclic loading. Few response parameters are regarded, and the performance of the rotary brace damper in reducing each response has been measured. In terms of methodology, ANFIS (Adaptive neuro-fuzzy inference system) is used in data analysis in a variable selection processing to distinguish the predominant values that influence the strength of this damper. The process is on the basis of the variable search method that has been later applied to measure how the four parameters of (1) displacement, (2) diameter (3) thickness, and (4) plate thickness influence the strength of damper. As a result, displacement is the most effectual parameter in forcing prediction and best predictor of accuracy.

中文翻译：

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估计影响旋转支撑阻尼器的最有影响的参数

由于成本和时间费用，使用钢支撑进行地震修复的传统方法不能是使用这些方法升级建筑物的合适方法。因此，本研究中引入了一种称为钢框架支撑阻尼器的创新被动控制系统。因此，为了研究这种结构阻尼器的行为，形成了一个没有旋转支撑阻尼器装置的单跨钢框架。后来，框架配备了旋转支撑阻尼器，并受到单调和循环加载。很少考虑响应参数，并测量了旋转支撑阻尼器在减少每个响应方面的性能。在方法论上，ANFIS（自适应神经模糊推理系统）用于变量选择处理中的数据分析，以区分影响该阻尼器强度的主要值。该过程基于变量搜索方法，该方法后来用于测量（1）位移，（2）直径（3）厚度和（4）板厚度四个参数如何影响阻尼器强度。因此，位移是强制预测中最有效的参数和准确度的最佳预测器。