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This paper describes a study carried out to develop and apply Madymo models combining multibody and finite element components to simulate accidents between vehicles and pedestrians. The work is in ...

The adoption of knowledge-based systems (KBS) technology into engineering design presents a massive opportunity to companies in search of new ways to improve their product introduction process (PIP). However, past experience has shown that such promise has not been realized in the adoption of expert systems technology. The failure of the introduction of KBS technology under the banner of expert systems can frequently be attributed to the inappropriate selection of suitable applications. Despite these past experiences, history seems poised to repeat itself with the adoption of knowledge-based engineering (KBE) technology within the product development process. Therefore, the ability to identify ‘winner’ applications would be of considerable benefit. This paper outlines the consolidation of past experience relating to KBS development and outlines a method for the selection of suitable KBE design applications.

SUMMARY This paper discusses an approach to programming computers to expand their use within the design function, using artificial intelligence (AI) techniques. The design process is discussed, along with the type of problems encountered and the attributes required of the designer for the solution of such problems. AI programming techniques are introduced as an extension to the field of computer-aided design (CAD) and the case for automatic design is presented. The design process is considered in terms of the theoretical model which is used as a basis for programming automatic design systems. A simple demonstration of the approach is given in the form of the selection of a solution principle for a pump problem and the development of that solution into a functional unit by design rules. A central theme of the method is the iterative use of the model, illustrating the concept at all levels of design decision-making.

Optimization techniques are applied to the design of both hydrodynamic journal and tilting pad thrust bearings. Fletcher's adaptation of Davidon's gradient search method is further modified to deal with non-linear constraints in journal bearing design. A form of the Sequential Simplex is used for tilting pad thrust bearings. Penalty functions and variable transformations are used in both cases. Composite objective functions are included and the effect of weighting on each component of the composite function is investigated.