The application of modified adaptive landscapes to heuristic modelling of engine concept designs using sparse data

Abstract

The automotive internal combustion engine industry operates in a sector that relies on high production volumes for economies of scale, and dedicated production equipment for efficiency of operations and control of quality, yet is subject to the vagaries of a dynamic marketplace, with the need for constant change. These circumstances place pressure on engine designs to be optimised at launch to be competitive and meet market needs, yet be adaptable to uncertain requirements for change over their production life. Engine designers therefore need concept configuration evaluation tools that can assess architectures for resilience to geometric change over the production life of the product. The problem of being resource efficient whilst having the capacity to adapt tochanging environments is one that has been addressed in nature. Natural systems have evolved strategies of satisficing conflicting requirements whilst being resource efficient. The theory of adaptive landscapes helps us to visualise the adaptive capacity of potential morphological forms. A concept attribute analysis methodology based on satisficing and adaptive landscapes has been developed and tested for application to engine concept design. The Plateau, Flooded Adaptive Landscape technique (PFAL),has been evaluated against exemplar engine life histories and shows merit in aiding the decision-making process for concept designers working with sparse data. The process lets the designer visualise the attribute map, enabling them to make better trade-off decisions and share these with non-expert stakeholders to gain their input in final concept choices.