The classical panel method has been extensively used in external aerodynamics to calculate ideal flow fields around moving vehicles or stationary structures in unbounded domains. However, the panel method, as a somewhat simpler implementation of the boundary element method, has rarely been employed to solve problems in closed complex domains. This paper aims at filling this gap and discusses th...

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is unknown. Two approaches are considered — penalized least squares (PLS) for models without endogenous regress...

because of its extensive applications in financial analysis, stock market volatility modeling is a significantly important issue for stock market practitioners and academicians. using garch models to formulate the conditional variance heteroskedasticity and the taking advantages of panel data technique such as higher degrees of freedom, more flexibility in the control of the omitted or unobserv...

Load carrying capacity of flat double-layer space structures majorly depends on the structures' imperfections. Imperfections in initial curvature, length, and residual stress of members are all innately random and can affect the load-bearing capacity of the members and consequently that of the structure. The double-layer space trusses are susceptible to progressive collapse due to sudden buckli...

Low-frequency sound transmission has long plagued the sound isolation performance of lightweight partitions. Over the past 2 decades, researchers have investigated actively controlled structures to prevent sound transmission from a source space into a receiving space. An approach using active segmented partitions (ASPs) seeks to improve low-frequency sound isolation capabilities. An ASP is a pa...

Recently, complex shaped aluminium panels have been adopted in many structures to make them lighter and stronger. The vibro-acoustic behaviour of these complex panels has been of interest for many years but conventional finite element and boundary element methods are not efficient to predict their performance at higher frequencies. Where the cross-sectional properties of the panels are constant...

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...