scholarly journals ENERGY BALANCE-BASED RESPONSE PREDICTION METHOD FOR FIRST LAYER CONSIDERING DEGREE OF PLASTICITY OF PASSIVE CONTROLLED BUILDING MAINFRAME WITH HYSTERETIC DAMPERS

2018 ◽  
Vol 83 (752) ◽  
pp. 1411-1421
Author(s):  
Daiki SATO ◽  
Takatoshi IWAMORI ◽  
Yusuke MATSUZAWA ◽  
Haruyuki KITAMURA ◽  
Michio YAMAGUCHI ◽  
...  
Keyword(s):  
Energy Balance ◽  
Prediction Method ◽  
Response Prediction ◽  
Hysteretic Dampers

scholarly journals SEISMIC RESPONSE PREDICTION OF STEEL FRAMES WITH HYSTERETIC DAMPERS BASED ON ENERGY BALANCE

2004 ◽  
Vol 69 (582) ◽  
pp. 147-154 ◽  
Author(s):  
Takashi HASEGAWA ◽  
Isao NISHIYAMA ◽  
Akiyoshi MUKAI ◽  
Tadashi ISHIHARA ◽  
Hisaya KAMURA
Keyword(s):  
Energy Balance ◽  
Seismic Response ◽  
Steel Frames ◽  
Response Prediction ◽  
Hysteretic Dampers

Response Prediction and Dynamic Substructuring for Coupled Structures in the Frequency Domain

2020 ◽  
Vol 36 (6) ◽  
pp. 867-879
Author(s):  
X. H. Liao ◽  
W. F. Wu ◽  
H. D. Meng ◽  
J. B. Zhao
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Dynamic Properties ◽  
Main Idea ◽  
Prediction Method ◽  
Response Prediction ◽  
Synthesis Methods ◽  
Dynamic Substructuring ◽  
Coupled Structures

ABSTRACTTo evaluate the dynamic properties of a coupled structure based on the dynamic properties of its substructures, this paper investigates the dynamic substructuring issue from the perspective of response prediction. The main idea is that the connecting forces at the interface of substructures can be expressed by the unknown coupled structural responses, and the responses can be solved rather easily. Not only rigidly coupled structures but also resiliently coupled structures are investigated. In order to further comprehend and visualize the nature of coupling problems, the Neumann series expansion for a matrix describing the relation between the coupled and uncoupled substructures is also introduced in this paper. Compared with existing response prediction methods, the proposed method does not have to measure any forces, which makes it easier to apply than the others. Clearly, the frequency response function matrix of coupled structures can be derived directly based on the response prediction method. Compared with existing frequency response function synthesis methods, it is more straightforward and comprehensible. Through demonstration of two examples, it is concluded that the proposed method can deal with structural coupling problems very well.

Prediction of Changes in System Vibration Response Using Empirical Sensitivity Functions

2010 ◽  
Author(s):  
Chulho Yang ◽  
Douglas E. Adams
Keyword(s):  
Prediction Method ◽  
Response Prediction ◽  
System Response ◽  
Design Modification ◽  
Mass Distributions ◽  
Sensitivity Functions ◽  
Design Variables ◽  
Parameter Modification ◽  
Noise Vibration ◽  
The Cost

To improve noise, vibration, and harshness (NVH) performance in a mechanical system, engineers make changes in the mass, damping, or stiffness properties of components in the system. A system response prediction method using a sensitivity function is suggested to reduce the cost in the design modification process. Embedded sensitivity functions derived solely from empirical data have been applied to identify optimal design modifications for reducing vibration resonance problems. In this paper, those sensitivity functions are used to predict the changes in vibration behavior of a system with respect to the design parameter modification. The cost and time for building many prototypes and testing actual parts can be reduced by identifying the best parameters to be changed and determining the amount of modification in those design variables through the prediction of the system response before actual components are built. The method is applied to a single degree of freedom analytical model to study the accuracy of the predictions. Finite element analyses are then conducted on a three-story structure with modifications to the stiffness and mass distributions to demonstrate the feasibility of these predictions in applications to more complicated structural systems.

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