Prediction of mechanical properties of carbon nanotube-based composite is one of the important issues which should be addressed reasonably. A proper modeling approach is a multi-scale technique starting from nano scale and lasting to macro scale passing in-between scales of micro and meso. The main goal of this research is to develop a multi-scale modeling approach to extract mechanical propert...

The use of a stress-strain constitutive relation for the undamaged material and a traction-separation cohesive crack model with softening for cracking has been demonstrated to be an effective strategy to predict and explain the size-scale effects on the mechanical response of quasi-brittle materials. In metals, where ductile fracture takes place, the situation is more complex due to the interpl...

The constitution of multi-scale spatial databases is closely linked to map generalisation. Elements of a multi-scale spatial database include multi-scale data models, multi-scale data storage schemes, methods to generate multi-scale datasets and methods to access these datasets and present results. In this paper we proposed a formal multi-scale spatial data model with an information-rich struct...

One important issue associated with the complexity of dynamically evolving material interface is the scale-dependent dynamics which implies very different physical phenomena depending on the resolvability of the material interface. In this work we present a concept of multi-scale modeling where the interface interaction is modeled as being in mechanical non-equilibrium or in equilibrium, depend...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

This paper proposes a class-specified segmentation method, which can not only segment foreground objects from background at pixel level, but also parse images. Such class-specified segmentation is very helpful to many other computer vision tasks including computational photography. The novelty of our method is that we use multi-scale superpixels to effectively extract object-level regions inste...

technology foresight is a methodology for making the complexity and advanced nature of new technologies of future more comprehensible and transparent. the objective of this survey is to analyze and interpret weakness and strength of the current situation of iran organizations regarding utilization of foresight activities of developing new technologies and its influence over the country by usin...

in this study, a new efficient semi-analytical method is introduced to give approximate solutions of strongly nonlinear oscillators. the proposed method is based on combination of two different methods, the multi-step homotopy analysis method and spectral method, called the multi-step spectral homotopy analysis method (msham). in this method, firstly, we propose a new spectral homotopy analysis...