Seismic Collapse Probability and Life Cycle Cost Assessment of Isolated Structures Subjected to Pounding With Smart Hybrid Isolation System Using a Modified Fuzzy Based Controller

The possibility of pounding on isolated structures with surrounding moat walls is one of the concerns in the design of isolation systems, especially in pulse-type near-field earthquakes. This paper puts forward the seismic probability assessment of structures equipped with passive and smart hybrid isolation systems by considering pounding possibilities. This investigation is performed on isolated structures equipped with a high damper rubber bearing (HDRB) considering stiff moat walls around the structure. In the Hybrid isolation system, magnetorheological dampers (MR) are considered an adaptive dissipation energy device along with isolators using an optimized novel interval Type-2 fuzzy logic controller with adaptive red-zone function (IT2FS+RZF) to reduce pounding possibilities. The fragility curves of the building for various cases are determined using IDA analysis, and possible damage costs are evaluated by using exceedance probability in each damage level. This study concludes that the collapse probability of the isolated structures with restrains at the code-based distance is over the acceptable limit of ASCE 7-22. The smart additional damping system with the proposed controller reduces the possible damage cost of the building by about 64% compared to the uncontrolled system and puts the collapse probability of the structure in the acceptable range.

A hybrid MRE isolation system integrated with ball-screw inerter for vibration control

Magnetorheological elastomer (MRE), as a field-dependent smart material, has been widely applied on base isolation for vibration reduction. However, the MRE isolation system often experiences large drift during strong earthquake, which may cause mechanical failure. Additionally, its performance among low frequency range is still limited. To tackle these problems, this paper proposes a hybrid vibration isolation system which is composed of four stiffness softening MRE isolators and a passive ball-screw inerter. A simulation was developed to prove the effectiveness of the hybrid isolation system before the earthquake tests. A scaled three-storey building was developed based on the scaling laws as the isolated objective in earthquake experiments. Besides, a linear quadratic regulation (LQR) controller was utilised to control the mechanical properties of the hybrid MRE isolation system. Finally, the evaluation experiments of the building under a scaled Kobe earthquake excitation were conducted. The experimental results show that the simulation and the experimental results were in agreement, validating that the hybrid isolation system could provide a better vibration mitigation performance, in the meanwhile, reduce the displacement amplitude of the isolation system.

Framework for Enhancing the Performance of Classification by RCOS and HiForest

This framework includes two novel approaches to choose the outlier from various datasets. First one being Relative Cosine-based Outlier Score (RCOS).It's proposed to measure the deviation score of the objects in which each single attribute deviation is calculated and multiplied to get the entire object deviation. Initially we set the threshold. If the calculated score is greater than the threshold, then the instance is considered as an outlier. These are identified and removed since outliers are not required for classification. Now, the remaining normal objects are subjected to different methods of classification. The second method is Hybrid Isolation Forest (HiForest). It is an enhanced version of isolation forest. Similar to method outliers are identified and removed. An experimental analysis is performed on synthetic real time data sets considered from weka and UCI repository. Classification models are built and the generated results are tabulated and accuracy is recorded. The results obtained by the above methods are compared and graphs are plotted for visualization