GasTurbnLab: a multidisciplinary problem solving environment for gas turbine engine design on a network of nonhomogeneous machines

Gas turbine engines are very complex (with 20-40,000 parts) and have extreme operating conditions. The important physical phenomena take place on scales from 10-100 microns to meters. A complete and accurate dynamic simulation of an entire engine is enormously demanding. Designing a complex system, like a gas turbine engine, will require fast, accurate simulations of computational models from multiple engineering disciplines along with sophisticated optimization techniques to help guide the design process. In this paper, we describe the architecture of an agent-based software framework for the simulation of various aspects of a gas turbine engine, utilizing a "network" of collaborating numerical objects through a set of interfaces among the engine parts. Moreover, we present its implementation using the Grasshopper agent middleware and provide simulation results that show the feasibility of the computational paradigm implemented. (C) 2002 Published by Elsevier Science B.V

Similarity search of flexible 3d molecules combining local and global shape descriptors

In this paper, a framework for shape-based similarity search of 3D molecular structures is presented. The proposed framework exploits simultaneously the discriminative capabilities of a global, a local, and a hybrid local-global shape feature to produce a geometric descriptor that achieves higher retrieval accuracy than each feature does separately. Global and hybrid features are extracted using pairwise computations of diffusion distances between the points of the molecular surface, while the local feature is based on accumulating pairwise relations among oriented surface points into local histograms. The local features are integrated into a global descriptor vector using the bag-of-features approach. Due to the intrinsic property of its constituting shape features to be invariant to articulations of the 3D objects, the framework is appropriate for similarity search of flexible 3D molecules, while at the same time it is also accurate in retrieving rigid 3D molecules. The proposed framework is evaluated in flexible and rigid shape matching of 3D protein structures as well as in shape-based virtual screening of large ligand databases with quite promising results. © 2015 IEEE

Parallel Numerical Algorithms and Software

this article is two fold. First we review the various parallelization techniques proposed to speed up the existing computational PDE models, that are based on the divide and conquer computational paradigm and involve some form of decomposition of the geometric or algebraic data-structures associated with these computations. Second, we review the parallel algorithms proposed to solve various classes of algebraic systems which are applicable to discrete PDE systems. For the sake of brevity of this exposition we focus on computational models derived from elliptic PDE models. Most of the parallelization techniques presented here are applicable to general semi-discrete and steady-state models. Specifically, we consider PDE models consisting of a PDE equation Lu = f , defined on some region\Omega and subject to some auxiliary condition Bu = g on the boundary of\Omega (= @\Omega\Gamma

Softlab: A Virtual Laboratory Framework for Computational Science

this paper we present a software framework for a virtual laboratory and report on our experiences in designing and implementing two software prototyping laboratories, microelectronics material (MicroSoftLab) and bioseparation (BioSoftLab) chemical engineering laboratories. Introduction to SoftLab 2 of 25 SoftLab : A virtual laboratory framework for computational scienc