Semilinear functional difference equations with infinite delay

We obtain boundedness and asymptotic behavior of solutions for semilinear functional difference equations with infinite delay. Applications to Volterra difference equations with infinite delay are shown. (C) 2011 Elsevier Ltd. All rights reserved.

The boundedness of penalty parameters in an augmented Lagrangian method with constrained subproblems

Augmented Lagrangian methods are effective tools for solving large-scale nonlinear programming problems. At each outer iteration, a minimization subproblem with simple constraints, whose objective function depends on updated Lagrange multipliers and penalty parameters, is approximately solved. When the penalty parameter becomes very large, solving the subproblem becomes difficult; therefore, the effectiveness of this approach is associated with the boundedness of the penalty parameters. In this paper, it is proved that under more natural assumptions than the ones employed until now, penalty parameters are bounded. For proving the new boundedness result, the original algorithm has been slightly modified. Numerical consequences of the modifications are discussed and computational experiments are presented.

Development of a 3D Game Engine

This paper presents the development history and specification of a 3D game engine titled "Spark Engine". The term "engine" is used to describe a complex graphics software suite that streamlines application development and provides efficient rendering functionality. A game engine specifically provides tools to simplify game development. Spark Engine is fully shader driven and is built on top of Microsoft's XNA Framework. It is a reusable and flexible platform that can be used to build any type of graphics application ranging from gaming to simulation. The engine was released as open source software under the New BSD License with an interest in furthering its development.

Self-learning of fault diagnosis identification

A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.

Information integration: generating functional models from structural ones

Information integration is a very important topic. Reusing the knowledge and having common representations have been (and it is) an active research topic in the process systems community. Conventional (structural) But only structural models have been dealt with so far. In this paper the issue of integration is related with two types of different knowledge, functional and structural. Functional representation and analysis have proved very useful, but still it is developed and presented in a completely isolated way from the classic structural description of the process. This paper presents an architecture to integrate both representations.

HAZOP studies using a functional modeling framework

In this paper we present a tool to perform guided HAZOP studies using a functional modeling framework: D-higraphs. It is a formalism that gathers in a single model structural (ontological) and functional information about the process considered. In this paper it is applied to an industrial case showing that the proposed methodology fits its purposes and fulfills some of the gaps and drawbacks existing in previous reported HAZOP assistant tools.