They were overall much smaller than the dominant animals - the dinosaurs - and their size and adaptability is seen as a key feature for their survival and thriving.. Moving away from the natural world into the world designed by Homo sapiens, there is a very different approach to scale.
There is an increasing amount of pressure growing in the construction industry to design net zero carbon buildings, both in terms of operational and embodied carbon.In this context, bodies such as the London Energy Transformation Initiative (LETI), RIBA, GLA and UKGBC, have developed guidance documents on embodied carbon, which include specific targets and roadmaps to achieving net zero carbon prior to 2050.. Based on LETI Climate Emergency Design Guide, a typical medium size residential building embodied carbon, would be 33% of the total carbon, whilst the operational carbon would be around 67%.
However, for an ultra-low energy building, like Passivhaus, the breakdown would be 77% embodied and 23% operational and this balance is likely to become more enhanced with the decarbonisation of the grid.This means that embodied carbon is becoming a more important focus for the sustainable design of buildings..Typical operational and embodied carbon breakdown for medium scale residential for a standard building (left) and for an ultra-low energy building.
Passivhaus standard has always been focused on operational energy, and it is only in recent years that the focus has grown to both operational carbon emissions and the embodied carbon within the building..Operational carbon in sustainable building design.
From an operational carbon perspective, Passivhaus’ low energy targets mean the dwellings are likely to achieve very low carbon emissions.
As a result, it becomes technically and financially feasible to offset any carbon emission through the use of building mounted, renewable technologies.production schedules, to specify the order in which truss types would be made.
throughput and timing data, such as processing times of stations, speed of conveyors and speed of cranes..The data itself was not hard-coded into the model and instead read from an external data file, which made running multiple simulations for differing parameters a rapid process.. Several different scenarios were simulated in the model that were made up from combinations of options.
This included different production schedules and whether transport timings were included, to test sensitivity of the system to these inputs.We also added scenarios for a +/- 20% variation on process timings (for example, the welding stations), using a triangular distribution.. We defined key outputs to measure performance of the system, including schedule completion time (i.e.