This paper provides an approximate analysis of quadrilateral slabs having various cases of aspect ratios and boundary conditions based on actual two-way action. Nine slabs with different boundary conditions, each having 11 aspect ratios were analyzed using SAP2000 software, thereafter, robustly validated against mathematical solutions. In this article, the hydrostatic point phenomenon was established as a reference point for identifying the slabs with actual two-way action and as a growth reference for other cases. This allows for the use of growth models for the hydrostatic and deviatoric moment tensors. The innovative selection of the extreme positive point moment facilitates the introduction of materials nonlinearity into the design. The plate shorter dimension was used for moment normalization in both directions to preserve the directional influence of the dimensions and to isolate the hydrostatic phenomenon. Through starting at a point of hydrostatic phenomenon occurrence and via fixing one of the plate’s dimensions and extending the other (for any boundary conditions), the extreme point’s Mohr circle develops from the hydrostatic point phenomenon as a growth in the hydrostatic component and drastic growth in the deviatoric component. Subsequently, the largest principal moment develops a higher magnitude as the aspect ratio increases. Furthermore, the non-identical boundary conditions on two perpendicular directions result in a deviation of the two-way action.
The continuous expansion of seismic catalogs is increasingly challenging the validity of existing ground motion prediction equations. For such real-time data, the transition of ground motion modeling toward automation became eminent. This article put forth a dynamic intelligent ground motion prediction system, automated through a novel hybridization of neural networks with a multi-objective swarm intelligence optimization to facilitate updated predictions. Under the proposed framework, acceleration data are parsed from catalogs in real-time and the continuous stream of seismic data is analyzed to both (i) optimize model predictions and (ii) minimize its computational demand. Though built adaptive to different geographical locations, the system in this article is presented in the context of Turkey. Therefore, real-time strong ground-motion records are obtained from the AFAD database, where the peak ground acceleration (PGA), velocity (PGV), and displacement (PGD) are examined against various seismic variables including earthquake magnitude, source to site distance, average shear-wave velocity, and focal mechanism. The model predictions were verified against a broad testing sample and predictions by various GMPE models for Turkey. Thereafter, the model stability was examined through an investigation into the sensitivity of the PGA, PGV, and PGD predictions to data and parameters' discrepancies. Finally, this article discusses the future potentials and challenges facing the developed framework.
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