Recent Advances on Carbon Nanotubes and Graphene Reinforced Ceramics Nanocomposites

Open Access articleCeramics suffer the curse of extreme brittleness and demand new design philosophies and novel concepts of manufacturing to overcome such intrinsic drawbacks, in order to take advantage of most of their excellent properties. This has been one of the foremost challenges for ceramic material experts. Tailoring the ceramics structures at nanometre level has been a leading research frontier; whilst upgrading via reinforcing ceramic matrices with nanomaterials including the latest carbon nanotubes (CNTs) and graphene has now become an eminent practice for advanced applications. Most recently, several new strategies have indeed improved the properties of the ceramics/CNT nanocomposites, such as by tuning with dopants, new dispersions routes and modified sintering methods. The utilisation of graphene in ceramic nanocomposites, either as a solo reinforcement or as a hybrid with CNTs, is the newest development. This article will summarise the recent advances, key difficulties and potential applications of the ceramics nanocomposites reinforced with CNTs and graphene.Research Center of College of Engineering, Deanship of Scientific Research, King Saud University, Riyadh, Kingdom of Saudi Arabi

Estimation of near fault ground motion based on a hybrid source model and a theoretical Green’s function method

One of the most important challenges in seismic evaluation of structures comes from wide variability of possible motions that a specific site may experience. This variability arises from the intrinsic randomness of seismic motions (aleatory uncertainty) and lack of knowledge about the physical process behind an earthquake (epistemic uncertainty). The epistemic uncertainty in estimating ground motion can be properly characterized by providing an understanding of the physical aspects of earthquake source models. In this paper, a combination of the theoretical-based Green’s function method and hybrid slip source model is used to reduce the source uncertainty. The procedure is implemented on the 1994 Northridge earthquake as a case study. For this purpose, the method is validated against recordings stations through demonstrating a good agreement between the elastic response spectra corresponding to the simulated and recorded data, confirming the reliability of the procedure. A simple additive weighting algorithm is used to select the best fit amongst simulated waveforms and optimal source model

A Bayesian approach for seismic recurrence parameters estimation

Recurrence models apply historical seismicity information to seismic hazard analysis. These models that play an important role in the obtained hazard curve are determined by their parameters. Recurrence parameters estimation has some features that lie in missing-data problems category. Thus, the observed data cannot be used directly to estimate model parameters. Furthermore discussion about results reliability and probable conservatism is impossible. The present study aims at offering an approach for Gutenberg-Richter parameters (a and b-values) estimation and determine their variation. Applying the proposed method to analyses of the heterogeneous data sets of seismic catalog, one would calculate valid estimates for recurrence parameters. This method has the capability to reflect all known sources of variability. The results of the case study clearly demonstrate applicability and efficiency of the proposed method, which can easily be implemented not only in advanced but also in practical seismic hazard analyses