Introduction and Reading Guide
Modelling – a many centuries old activity – has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering. The driving forces behind such a development are scientific knowledge, technological development and cheaper information technologies that deliver massive computer power and data availability. Essential to any modelling approach, the issues of proper qualification, calibration and control of associated error, as well as uncertainty or deviations from reality have arisen simultaneously as the subjectof growing interest and as areas of new expertise in themselves.
Indeed, the search for more advanced management of uncertainty in modelling, design and risk assessment has developed greatly in large-scale industrial and environmental systems with the increase in safety and environmental control. Even more so, an appetite for more accountable decision-making and for greater confidence in predictions has found a general audience in the fields of weather forecasting, health and public policy. In parallel, robust design approaches and the valuation of flexibility through option-based decision-making are more and more disseminated in various industrial sectors in the quest for an increase in customer satisfaction, design and manufacturing cost reduction and market flexibility.
Faced by such demands, a systematic approach to uncertainty linked to the modelling of complex systems proves central in establishing ...
