C Christian Struck

On the Application of Uncertainty and Sensitivity Analysis with Abstract Building Performance Simulation Tools

Building performance simulation (BPS) is a powerful measure to educate the building design process. However, its use in practice is to a large extent limited to the detailed design stage dedicated to the code compliance analysis of worked out design proposals. BPS is not much used to support the conceptual design stage. To date BPS tools are regarded as pure analysis tools, which do not provide design information. It is hypothesized that, when integrating uncertainty analysis techniques to existing BPS tools, following an incremental research approach, valuable design information can be provided. The article gives an update on the process to extend the capabilities of a tool specifically developed to support the conceptual design stage about uncertainty assessment. The resulting prototype should be capable of providing information about the variation of specific building performance metrics (simulation output) based on the propagated uncertainties of the building specification (simulation input). The main focus was herby the representation of material properties and their impact on the performance uncertainty of the building concept. The results also indicate the degree of impact, sensitivity, of the building specification parameters on the variation of the performance metrics as a result of their uncertainty.

An investigation of the option space in conceptual building design for advanced building simulation

This article describes research conducted to gather empirical evidence on size, character and content of the option space in building design projects. This option space is the key starting point for the work of any climate engineer using building performance simulation who is supporting the design process. The underlying goal is to strengthen the role of advanced computing in building design, especially in the early conceptual stage, through a better integration of building performance simulation tools augmented with uncertainty analysis and sensitivity analysis. Better integration will need to assist design rather than automate design, allowing a spontaneous, creative and flexible process that acknowledges the expertise of the design team members. This research investigates and contrasts emergent option spaces and their inherent uncertainties in an artificial setting (student design studios) and in real-life scenarios (commercial design project case studies). The findings provide empirical evidence of the high variability of the option space that can be subjected to uncertainty analysis and sensitivity analysis.

The integrated and evidence-based design of healthcare environments

The design of healthcare facilities is a complex and dynamic process, which can be supported by design support models. This process involves a large number of stakeholders, of whom some have specific health-related needs. Evidence-based design is an emerging approach for the design of healthcare facilities, basing design choices on scientific data. Apart from the problems accompanying the limited access to, and limited availability of, scientific evidence, the design of a building itself is characterised by dimensional, technological and stakeholder complexities that are derived from technology philosophy. This article deals with the derivation of performance indicators and design solutions for healthcare facilities and links this search to the foundations of evidence-based building. The In2Health design model is elaborated as a framework to steer this process and support architects, programmers and process managers. The applicability of the model in the evaluation and design processes of buildings is illustrated by two case studies concerning (i) the evaluation of the indoor environment for older people with dementia and (ii) the design process of the redevelopment of an existing hospital.