WIT Press


Integrating Biological Optimisation Methods Into Engineering Design Process

Price

Free (open access)

Paper DOI

10.2495/DN020031

Volume

57

Pages

Published

2002

Size

582 kb

Author(s)

C. Mattheck & I. Tesari

Abstract

Integrating biological optimisation methods into engineering design process C. Mattheck & I. Tesari Institute for Materials Research II, Forschungszentrum Karlsruhe, Germany. Abstract Biological structures consist of mechanical load carriers, which are well adapted to their main loading conditions and highly optimised in terms of mechanical strength and minimum weight. A constant stress distribution on the surface of the biological component can be accepted as a significant biological design rule [1]. Based on this condition and by use of the Finite Element Method (FEM) three computer programs have been developed at Forschungszentrum Karlsruhe to transfer these biological optimisation mechanisms to mechanical engineering. The Soft Kill Option (SKO-method) simulates the biological optimisation mechanism of adaptive bone mineralisation to find an optimal design proposal. The Computer Aided Optimization Method (CAO-method) copies the principle of adaptive growth which biological structures, like trees, use to homogenise the stress distribution on their surface. And finally the Computer Aided Internal Optimization (CAIO-method) optimises the use of reinforced composite material due to an optimum fibre arrangement with minimised shear stresses in between the fibres, again mimicking the structure of trees. 1 Introduction The struggle for living space and energy is the motivation force for phenomena in nature which are called biological optimisation. Weak, non-optimised structures have little chance against their well-optimised competitors. The result of this natural selection over millions of years: the designing mechanisms and the structure of each biological load carrier is optimally adapted to its natural load. The biomechanical structures are adapted to the loads they experience by different strategies. First, the trial and error strategy, which creates better designs

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