• technology findings
• durability & life extension
• product & system optimisation
• multi-physics & analysis technology
• education and dissemination

Product and System Optimisation

This covers the need for simulation technology which allows the “system” to be optimised for a wide range of criteria and conditions. It includes for example improved methods of topology and weight optimisation, methods for treating uncertainties more rationally (e.g. reliability-based design optimisation) in addition to the detailed treatment of non-linear effects such as contact, friction, buckling etc. Other areas of interest are large strain effects encountered in modern forming and production processes and many others, impact modelling (including deformational response with large kinematics).

The quest of all engineering processes is to make things better. In the area of Computational Mechanics there have been huge advances in the last 30 years with parallel developments in computers and computational algorithms. Finite Element Analysis has evolved to such a stage of competency that the engineer/physicist can analyse any defined physical situation, linear or non-linear provided the material properties are known.

In the last ten years there has been significant academic research in the area of Structural Optimization to the stage where the algorithms needed for size, shape, topology and topography optimization are becoming more reliable and robust. We are now starting to see some limited commercial uptake of these analytical optimizers replacing the traditional engineering intuitively/heuristic driven iterative design optimization methods.

The eventual goal of all structural optimization systems it to be able to deliver on the design wish list of structural goals such as;

• Totally general and multiple load environments
• Totally general multiple support environments
• Totally general shape in 2D or 3D
• Multiple material environments
• Multiple modelling environments eg. static, dynamic and stability, separate or together
• Material and geometric non-linearity
• Multiple optimality conditions (Pareto) for all or portions of the structure in different combinations.
• Design must be manufacturable

None of the software products currently available deliver this whole list. None of them even address the last item in any realistic way. Currently there are two main computational techniques for structural optimization, mathematical programming with design variables (which can be the presence of an element, rather than a geometric entity) and heuristic methods. Several commercial FEA vendors offer one or both of these capabilities and there are several in-house proprietary codes. There is still much research and development to be done and much training of practicing engineers before Design and Structural Optimization becomes a routine part of the design process. The status at the moment is akin to that of FEA in the 1980’s.

Equally as important, but still significantly lacking, is the integration of manufacturing process models into the design optimization loop. Indeed if we are to be commercially serious for the product under consideration then we should also include financial, marketing, environmental, support and service and retirement into the design optimization.

Each of these activities has different analysis processes and data structures and responsibility resides in different locations in any commercial organization. Even between analysis and manufacturing models there are significant integration problems. This gap becomes even greater when other commercial processes are involved.

The challenge is therefore to guide the development and uptake of these new integrated analytical processes into true design optimization and to provide direction to all parties involved; code developers, researchers, designers and manufactures as to how the Computational Mechanics community should proceed from here.

Project Reports

Summary of the Project Findings relating to Product & System Optimisation
(as presented at the project review meeting in Malta, May 2005) (PDF Format)

D3602 - The use of Design of Experiments (DOE) and Response Surface Analysis(RSA) in PSO (PDF, 1.6Mb)
Prof. Carlo Poloni, Dr. Valentino Pediroda, Dr. Alberto Clarich - University of Trieste, Prof. Grant Steven, University of Durham

D3608a - General Purpose FEA vs Single Purpose Design Optimisation (PDF, 6.5Mb)
Prof. Grant Steven, University of Durham

D3608b - Product and System Optimisation in Engineering Simulation (PDF, 2.3Mb)
Prof. Grant Steven, University of Durham

D3611 - The use of Robust Design and Game Theory in PSO (PDF, 2.3MB)
Prof. Carlo Poloni, Dr. Valentino Pediroda, Dr. Alberto Clarich - University of Trieste

D3614 - The use of Optimisation algorithms in PSO (PDF, 5.2Mb)
Prof. Carlo Poloni, Dr. Valentino Pediroda, Dr. Alberto Clarich - University of Trieste, Prof. Grant Steven, University of Durham

 

Project Workshops