Teaching building performance simulation: ever done an autopsy?

In previous papers we have presented a continuous learning cycle that includes exposure to theories and the application of tools from the start for effectively teaching BPS and we have described the course we have developed based upon this cycle. The important role played by the simulation autopsy in this cycle is the focus of the current paper. This is accomplished by examining the teaching methods we use for 2 of our course’s 15 topics: determining the distribution of solar heat gains to internal building surfaces, and predicting solar irradiance on external building surfaces

Teaching building performance simulation through a continuous learning cycle

During the past decades building performance simulation tools have become complex. Alternate methods are offered for resolving many of the significant heat and mass transfer processes and energy conversion systems. At the same time, modern user interfaces allow users to quickly ascend the learning curve to operate tools in order to produce simulation predictions, although the prediction of accurate results is perhaps becoming more challenging. This paper argues that a complete and continuous learning cycle that includes exposure to theories and the application of tools from the start can be used to effectively teach building performance simulation. Examples of the application of the various stages of this learning cycle are provided and recommendations are made for the further development of pedagogical methods

Developing and testing a new course for teaching the fundamentals of building performance simulation

During the past decades building performance simulation (BPS) tools have become complex. Alternate methods are offered for resolving many of the significant heat and mass transfer processes and energy conversion systems. At the same time, modern user interfaces allow users to quickly ascend the learning curve to operate tools in order to produce simulation predictions, although the prediction of accurate results is perhaps becoming more challenging. In a previous paper we proposed a continuous learning cycle that includes exposure to theories and the application of tools from the start for effectively teaching BPS. This involves having the students actively experiment with BPS tools to support the theoretical study of modelling and simulation theory. This paper presents the pedagogical basis, the intended learning objectives, and the procedure for such a course. This contains a series of simulation exercises we have developed for supporting the teaching of models for simulating heat and mass transfer processes and convective heat transfer pertinent to the indoor environment. It also presents the feedback provided by the first two groups of students that have piloted these exercises

Investigating the potential impact of stakeholder preferences in Passivhaus design

Low-energy buildings have a major role to play in achieving carbon emission reduction targets. The Passivhaus standard is driven by improved thermal comfort and has stringent targets for limiting energy consumption. Such constraints can be difficult to achieve with aesthetically pleasing results. In early stage building design, decisions are often made based on preferences, without assessing their impact on energy performance. Multi-criteria decision-making provides a technique of evaluating competing criteria using a robust framework. However, existing research in building performance focusses on quantitative measures, leaving a research gap in the subjective area of design preferences. This paper applies a modelling technique that incorporates user preferences, alongside quantitative building performance measures, by applying multi-criteria decision-making to a Passivhaus case study. Potential building forms are evaluated using dynamic simulation, then the impact of stakeholder preferences is assessed

Robust building scheme design optimization for uncertain performance prediction

Design exploration is a vital part of the building design process that aims at identifying the best-performing design with regard to the requirements of the client and building regulations. Building performance simulation can support this “explorative” process, its potential however being restricted by the fact that all design parameters are subject to uncertainty. In addition, while the need for an efficient exploration of the design space has resulted in the integration of optimization into the design process, the majority of existing research treats uncertainty quantification and optimization as separate processes. Finally, candidate designs are commonly evaluated with respect to only one or two design criteria, while the multi-dimensionality of real-world problems calls for integrated design solutions that meet several – often-conflicting – objectives. A new approach is thus developed that aims to help designers identify robust Pareto-optimal solutions that satisfy several design criteria, while remaining optimal regardless of the uncertainty in boundary conditions. Through its implementation to a real-world case-study building, the novel approach is found to be able to identify optimum solutions that preserve their optimality over the entire range of uncertain performance scenarios

The properties of our everyday spectral microclimate

The CIE illuminant D65 is widely adopted as defining the standard spectral power distribution (SPD) for ‘average’ daylight. Thus daylight indoors is generally assumed to approximate the SPD for D65. The weight of research on the non-visual effects of light now suggests that a key consideration for the long-term health and well-being of occupants should be the amount, duration, timing and, importantly, the spectral profile of illumination received at the eye. Measurements of the SPD of illumination were made at a number of locations outdoor and indoors. In an outdoor environment, the spectral properties of the visible sky dictate the resultant SPD largely irrespective of the surrounding built environment. Only those indoor locations with close proximity to windows exhibit a spectral microclimate comparable to daylight, while all others are dominated by the artificial light sources. Early findings indicate the need to carry out further research to more clearly understand the experienced spectral microclimate

A proposed method for generating high resolution current and future climate data for Passivhaus design

The sensitivity of low energy and passive solar buildings to their climatic context creates a requirement for accurate local climate data. This situation takes on increasing importance in the context of modelling Passivhaus buildings where the absence of conventional oversized heating and cooling systems implies a greater reliance upon fabric and system optimisation. Conversely, future climatic changes may also pose serious implications for super insulated buildings with inadequate solar shading. Currently, many widely used building performance simulation (BPS) tools still rely on very limited sources of climate data. The following research examines the need for regional and, in some cases, micro-regional climatic data when designing ultra-low energy Passivhaus buildings in the UK. The paper proposes a new methodology for generating this data in PHPP format. The data generated is compared to alternative sources, and the implications discussed in the context of three case studies examining a certified Passivhaus dwelling in a mountainous region of Wales as well as two locations, in close proximity, within London. If correctly implemented the use of such data should provide a more robust basis for future cost and performance optimisation in low energy and passive building design

A critical software review - how is hot water modelled in current building simulation ?

In a changing climate and with ever increasing energy standards that lead to low and zero energy buildings, the provision of hot water in buildings will become more significant in relation to the overall energy consumption. Higher demand on the provision of hot water consumption has been documented and will occur around activities such as laundry, dishwashing, food preparation, bathing and cleaning activities. The accurate prediction and simulation of hot water in building design is therefore crucial and we need to rethink how we estimate the amount of hot water in our buildings. This paper will investigate how hot water demand and provision in homes is simulated via a number of different tools. The input and output differences with respect to hot water are compared to measured data of a building in the UK

Opening the black box: Enhancing community design and decision making processes with building performance simulation

It is widely acknowledged that faced with diverse future impacts (including climatic changes, economic instability and energy supply vulnerabilities) buildings and communities’ worldwide need to become increasingly resilient. The work presented in this paper investigates how Community Design and Decision Making (CDDM) processes can be enhanced through the use of design thinking techniques involving Building Performance Simulation (BPS). The research presented is based on findings from a real-world case study project involving the design of a mixed-use zero carbon community welcome centre planned for the Findhorn Eco-Community, in Scotland, UK. Throughout the conceptual and early design stages the community played a crucial part in the decision making process. Extensive consultation and community engagement exercises formed the basis from which initial design concepts were produced and evaluated. BPS results and in particular the use of sensitivity analysis (SA) techniques played a major contributing role in establishing a multicriteria evidence base from which to inform the CDDM process

Influence of input reflectance values on climate-based daylight metrics using sensitivity analysis

The insertion of climate-based daylight metrics as a requirement in several design guidelines calls for a better understanding of their effectiveness. This paper draws attention to the sensitivity of annual daylight metrics to changes in input reflectance values. The uncertainties related to the choice of guidelines and of simulation techniques were also considered. Total Annual Illumination (TAI) showed the most consistent correlation and the highest sensitivity to variations in reflectance (up to ±60% from the benchmark), independently of the geometrical characteristics of the space. Other annual metrics were less sensitive, or showed a poorer correlation. The deviations among different simulation techniques varied with the chosen metric too (NRMSD≤ 15% for TAI), but all techniques were equally affected by variations in reflectance. The results highlighted the importance of selecting appropriate metrics for annual climate-based daylight evaluations