Abstract
Building performance evaluation is generally carried out through a non-automated process, where computational models are iteratively built and simulated, and their energy demand is calculated. This study presents a computational tool that automates the generation of optimal building designs in respect of their Life Cycle Carbon Footprint (LCCF) and Life Cycle Costs (LCC). This is achieved by an integration of three computational concepts: (a) A designated space-allocation generative-design application, (b) Using building geometry as a parameter in NSGA-II optimization and (c) Life Cycle performance (embodied carbon and operational carbon, through the use of thermal simulations for LCCF and LCC calculation). Examining the generation of a two-storey terrace house building, located in London, UK, the study shows that a set of building parameters combinations that resulted with a pareto front of near-optimal buildings, in terms of LCCF and LCC, could be identified by using the tool. The study shows that 80% of the optimal building’s LCCF are related to the building operational stage (σ = 2), while 77% of the building’s LCC is related to the initial capital investment (σ = 2). Analysis further suggests that space heating is the largest contributor to the building’s emissions, while it has a relatively low impact on costs. Examining the optimal building in terms compliance requirements (the building with the best operational performance), the study demonstrated how this building performs poorly in terms of Life Cycle performance. The paper further presents an analysis of various life-cycle aspects, for example, a year-by-year performance breakdown, and an investigation into operational and embodied carbon emissions.
Highlights
The environmental efficiency of buildings has gained increasing global importance, especially since its introduction as a compliance requirement for the construction of new buildings in major economies around the world.[1,2] The improvement of the environmental efficiency of buildings is the result of a complex design process which UCL, London, UKInternational Journal of Architectural Computing 0109(03)involves passive and active design techniques and requires the consideration of various building properties, such as the building geometry, envelope characteristics or building systems
While in the UK, the government policy is mainly focused on targeting operational CO2 emissions, a Life Cycle Performance approach may be more suitable in examining the full impact of buildings on their environment.[3,4]
This paper introduces an early-stage design tool that integrates several techniques and computational frameworks (Generative design, mathematical optimisataion methods, thermal simulation and Life Cycle Performance) to optimise the design of a case study building, in terms of Life Cycle Carbon Footprint (LCCF) and Life Cycle Cost (LCC)
Summary
The environmental efficiency of buildings has gained increasing global importance, especially since its introduction as a compliance requirement for the construction of new buildings in major economies around the world.[1,2] The improvement of the environmental efficiency of buildings is the result of a complex design process which UCL, London, UKInternational Journal of Architectural Computing 0109(03)involves passive and active design techniques and requires the consideration of various building properties, such as the building geometry (e.g. aspect ratio, orientation, spatial arrangement), envelope characteristics (e.g. buildup, window-to-wall ratio) or building systems (e.g. radiators, HVAC). Frameworks for evaluating the environmental efficiency of buildings have been in use across the built environment discipline since the 1990’s, and have been widely discussed in literature.[5,6,7] Improving buildings environmental efficiency is still regarded as a challenging task that often involves an iterative process of modelling and simulation This iterative process is mostly carried out in a non-automated manner, where a single computational model is built and simulated, its performance assessed and changes are made to the design as required.[8]. While successful frameworks have been developed and used extensively for optimising buildings in terms of daylight performance or energy consumption,[16] generating optimal buildings to improve their Life Cycle Performance (carbon and cost) is still challenging This is partly due to the need to integrate a range of analysis tools and techniques, namely: generative design, optimisation, thermal simulation and life cycle performance (environmental and economic), which are typically explored independently from one another. This means that not all spatial arrangements are explored, and that some optimal solutions may be missed out
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