A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model. © 2011 Elsevier Ltd.

A workbook-based methodology for implementing concurrent engineering

Concurrent Engineering demands a new way of working and many organisations experience difficulty during implementation. The research described in this paper has the aim to develop a paper-based workbook style methodology that companies can use to increase the benefits generated by Concurrent Engineering, while reducing implementation costs, risk and time. The three-stage methodology provides guidance based on knowledge accumulated from implementation experience and best practitioners. It encourages companies to learn to manage their Concurrent Engineering implementation by taking actions which expose them to new and valuable experiences. This helps to continuously improve understanding of how to maximise the benefits from Concurrent Engineering. The methodology is particularly designed to cater for organisational and contextual uniqueness, as Concurrent Engineering implementations will vary from company to company. Using key actions which improve the Concurrent Engineering implementation process, individual companies can develop their own 'best practice' for product development. The methodology ensures that key implementation issues, which are primarily human and organisational, are addressed using simple but proven techniques. This paper describes the key issues that the majority of companies face when implementing Concurrent Engineering. The structure of the methodology is described to show how the issues are addressed and resolved. The key actions used to improve the Concurrent Engineering implementation process are explained and their inclusion in the implementation methodology described. Relevance to industry. Implementation of Concurrent Engineering concepts in manufacturing industry has not been a straightforward process. This paper describes a workbook-style tool that manufacturing companies can use to accelerate and improve their Concurrent Engineering implementation. © 1995.

Dynamic programming solutions for decentralized state-feedback LQG problems with communication delays

This paper presents explicit solutions for a class of decentralized LQG problems in which players communicate their states with delays. A method for decomposing the Bellman equation into a hierarchy of independent subproblems is introduced. Using this decomposition, all of the gains for the optimal controller are computed from the solution of a single algebraic Riccati equation. © 2012 AACC American Automatic Control Council).