Handling uncertainty in housing stock models

Housing stock models can be useful tools in helping to assess the environmental and socio-economic impacts of retrofits to residential buildings; however, existing housing stock models are not able to quantify the uncertainties that arise in the modelling process from various sources, thus limiting the role that they can play in helping decision makers. This paper examines the different sources of uncertainty involved in housing stock models and proposes a framework for handling these uncertainties. This framework involves integrating probabilistic sensitivity analysis with a Bayesian calibration process in order to quantify uncertain parameters more accurately. The proposed framework is tested on a case study building, and suggestions are made on how to expand the framework for retrofit analysis at an urban-scale. © 2011 Elsevier Ltd.

An optimal design process for an adequate product?

The 'optimal' or 'best' design process may be the shortest or cheapest process, or the one that leads to a particularly desirable product, or to a reliable and maintainable product, or to a manufacturable product, or some combination of all of these. It is likely to satisfy the aspirations of the organisation to invest an appropriate amount of resource in the development of a specific new market opportunity, set in the context of longer-term business goals. This paper describes the progress made in over ten years of research on process modelling undertaken at the Cambridge Engineering Design Centre to identify an 'optimal' design process with which to develop an 'adequate' product.