In recent years several new moving grid methods have shown promising potential for applications in the numerical solution of time dependent differential equations. In this paper, a deformation method is reviewed and some new developments related to the method are presented. In particular, the method is applied to grid morphing and adaptive grid generation on domains with moving boundary. The me...

It is well known that an accurate solution to the Euler equations requires more resolution in some parts of the flow field than others. Just where these regions are, and how fine the mesh spacing must be, depends on characteristics of the solution to be computed, and changes with different flow parameters, such as Mach number, angle of attack, etc. Therefore, it cannot be known in advance of th...

Owing to the evolution of the smart grid, the emergence of hybrid power systems (HPSs), and the proliferation of plug-in-hybrid electric vehicles, the development of efficient and robust maximum power point tracking (MPPT) algorithms for renewable energy sources due to their inherent intermittent nature has overwhelmed the power industry. In this paper, an incremental conductance (IC) based Her...

Due to overall popularity of the Internet, E-learning has become a lot methods of learning in recent years. Through the Internet, learners can freely absorb new knowledge without the restriction of time and place. Based on individual difference of learner’s abilities and preferred learning styles in hypermedia environment, the learning outcomes vary essentially. Meanwhile, with the development ...

Scientific workflows are dataand compute-intensive; thus, they may run for days or even weeks on parallel and distributed infrastructures such as grids, supercomputers, and clouds. In these high-performance computing infrastructures, the number of failures that can arise during scientific-workflow enactment can be high, so the use of fault-tolerance techniques is unavoidable. The most-frequentl...

I I of Partial A general survey of grid generation is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for such meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split LvetWee~; structured grids and unstructured meshes. A...

The effect of diverse sources of uncertainties and the intrinsically multi-scale nature of real-world physical systems poses a considerable challenge to analyze such systems. Such phenomena are particularly critical in material systems wherein microstructural variability and randomness at lower scales have a significant impact on the behavior of the system. Towards this goal, some of our accomp...

In a computational grid environment, a common practice is try to allocate an entire parallel job onto a single participating site. Sometimes a parallel job, upon its submission, cannot fit in any single site due to the occupation of some resources by running jobs. How the job scheduler handles such situations is an important issue which has the potential to further improve the utilization of gr...

In this paper, we address non preemptive online scheduling of parallel jobs on a Grid. The Grid consists of a large number of identical processors that are divided into several machines. We consider a Grid scheduling model with two stages. At the first stage, jobs are allocated to a suitable machine while at the second stage, local scheduling is applied to each machine independently. We discuss...

Bayesian network has been a successful tool in the decision support systems. In the changing world, the decision making demands adaptive Bayesian methods that are composed of Bayesian inferential and learning approaches. To achieve this goal, we propose a kind of grid-enabled Bayesian networks that intend to gridify Bayesian inferential and learning methods when the advanced grid computing tech...