Sharif Digital Repository

An analytical solution is presented that reconstructs residual stress field from limited and incomplete data. The inverse problem of reconstructing residual stresses is solved using an appropriate form of the airy stress function. This function is chosen to satisfy the stress equilibrium equations together with the boundary conditions for a domain within a convex polygon. The analytical solution is demonstrated by developing a reference solution from which selected "measurement" points are used. An artificial error is then randomly added to "measurement" points for studying the stability of the reconstruction method utilizing Tikhonov- Morozov regularization technique. It is found that there... 

Identifying and measuring the impact and value of scientific output plays an important role in today's world of information overload. On one side, governments are trying to distribute research funds in ways that support research in strategically important fields, on the other side, researchers and scientists are seeking to access only relevant and quality information that have mainly worthy of their attention. Nowadays, countries are evaluated not only by their national products, military power, geographical area, etc., but also by such factors as the production and consumption of scientific information. Scientometric approaches are used to provide appropriate tools for evaluating scientific... 

In this paper an analysis is presented to determine the distribution of a residual stress field from a limited incomplete set of measurements obtained from shot-peened round steel bars. Using an Airy stress function as the primary unknown the axisymmetric stress equations are solved directly. In this new method there exists the flexibility to impose physical conditions that govern the behavior of residual stress to achieve a meaningful complete stress field. This new method aims to achieve the best agreement between the model prediction and limited measured stress components in the sense of least squares approximation. The power of this new method is demonstrated by analyzing experimental... 

Sparse representation can be extended to high dimensions and can be used in many applications, including three-dimensional (3D) Inverse synthetic aperture radar (ISAR) imaging. In this study, the high-dimensional sparse representation problem and a recovery method called high-dimensional smoothed least zero-norm (HDSL0) are formulated. In this method, the theory and computation of tensors and approximating L0 norm using Gaussian functions are used for sparse recovery of high-dimensional data. To enhance the performance of HDSL0, modified regularised high-dimensional SL0 (MRe-HDSL0) algorithm, which benefits from the regularised form of SL0 and an additional hard thresholding step, is... 

In this study, the anticorrosive effect of dodecylbenzenesulfonicacid-doped polyaniline nanoparticles [n-PANI (DBSA)] as a conductive polymer was investigated using electrochemical impedance spectroscopy (EIS) and X-ray photoelectron spectroscopy (XPS) techniques. Initially, the n-PANI (DBSA) were successfully synthesized via inverse microemulsion polymerization leading to the spherical nanoparticles with an average diameter less than 30 nm. Two coating systems including 1 wt% n-PANI(DBSA) blended epoxy ester (n-PANI(DBSA)/EPE) and neat epoxy ester (EPE) were coated on the carbon steal substrate. The anticorrosion performance of the prepared coatings was studied using EIS measurement in 3.5%... 

As a non-invasive method, photographic imaging techniques offer some interesting potentials for characterization of soil moisture content in unsaturated porous media, enabling mapping at very fine resolutions in both space and time. Although less explored, the wealth of soil moisture data provided by photographic imaging is also appealing for the estimation of unsaturated soil hydraulic parameters through inverse modeling. However, imaging data have some unique characteristics, including high susceptibility to noise, which can negatively affect the parameter estimation process. In this study a sequential data assimilation approach is developed to simultaneously update soil moisture content...