Markets Property Buildings of the future People at the centre Designing for efficiency and ROI

Designing for efficiency and demonstrable ROI

The needs, movements and preferences of building occupants can’t be considered only after a building has been constructed. A building that has been designed for the end user doesn’t just happen. People-focused strategies need to be followed at every stage of the project, from design right through to construction and operation.

Design – enabling human centred design through collaborative design, rapid prototyping and ‘optioneering’

During the design phase, everyone from facility managers to the staff that will be using the building should be included in workshops so that designers and engineers understand their unique challenges, pain points, and daily tasks.

Leveraging visualisation and community engagement, expanding the application of design models, and understanding the end user sentiment requires an agile design approach. Visualisation also enables stakeholder engagement to be managed around the effect of massing and how a proposal fits into the existing environment and allows groups to come together to be bold and achieve a solution for all. Aurecon, for instance, used visualisation to explain building access and operation to the facilities management team for the Oman Across Ages Museum.

BOTF2 intro quote we only started to investigate the opportunities

Human centred design is enabled through collaborative design, rapid prototyping and optioneering. When the right stakeholders are brought in during the concept and design phase and you’re able to make ideas tangible and get quick feedback from the people that you are designing for, then the building designers and engineers can learn through producing.

Prototypes don’t have to be perfect from the get-go, they need to represent a concept that’s open to adjustments and optimisation. This type of optioneering lets you test ideas within a continuous feedback loop so that you can make sure you are on the right track. It’s essentially a practical, repeatable approach that will help us arrive at truly intelligent, human-centred buildings.

We've only started to investigate the opportunities that visualisation offers

Emotionally intelligent buildings will force us to better leverage our design data and communicate them in different types of visualisation scenarios, especially with regards to daylighting, indoor environmental quality and acoustics.

Some examples of this include auralisation, where acoustic modelling is used to simulate noise to optimise building designs and influence sound masking within buildings, Computational Fluid Dynamics (CFD) analysis to understand the efficacy of a building’s façade and HVAC system, for example, as well as digitised wayfinding and pedestrian modelling solutions.

While these visualisation options could be deemed costly, it must be put into the context of the overall cost of buildings of the future to translate a better return on investment for owners and developers.

Theory in action JMCO Accommodation

Aurecon’s JMCO Accommodation Design Team used virtual reality to supplement a design presentation at Lavarack Army Barracks in Townsville. While transporting and setting up our hardware, we were a little apprehensive as to how our ‘new toys’ might be perceived in the real world of defence.

What started out as a 30 per cent design presentation to just one stakeholder, soon turned into more than 15 people who’d joined the meeting to experience the virtual reality immersion. Using interactive controls, people were measuring space and clearances, enquiring about the objects’ properties, nudging and moving the objects, and marking up and commenting directly in the views.

The stakeholders were 'blown away' by the immersion, which in itself sped up the approval process, as well as resulting in overall time and cost savings.

Construction – bridging the gap between design and operations

During the construction and operation phase, data insights and sensors can be used to gain valuable feedback and target specific problems. These rapid insights can be used to justify larger, more costly adjustments to the design.

When building systems are installed, we need to investigate ways that machine learning will eventually be able to take data derived from these systems and enable a building to manage itself.

Theory in action Wynyard Station

When Aurecon was tasked with upgrading Wynyard Station, we used an unconventional solution involving 3D printing and virtual reality to create a simulated station environment to test possible design options that were unconventional or had only achieved limited success in the past.

In this case, prototyping and visualisation allowed the project team to take the client and stakeholders along the journey, starting from collaboration right through to a physical demonstration of the solution that all the stakeholders had collectively devised.

The exercise demonstrates the benefit of visualisation by using robotics, off-site construction and technology to create a more defined product without any added actual design costs.

Theory in action Sydney Airport T1 Northern Reclaim Project

The Sydney Airport Northern Reclaim project involved the creation of two new baggage reclaim carousels to cater for the larger A380 aircraft using the International Terminal T1. New plantrooms had to be constructed, and existing services diverted to allow the expanded baggage system to serve the new carousels. We were engaged to undertake all the engineering associated with the project.

During the course of our work, we learned two things worth sharing with the people scoping the Pier B North project: the point clouds are large and need management, and the process is anything but automatic!

To assist in our design coordination, Sydney Airport provided a point cloud survey of all the existing spaces which were affected – and we were asked to develop solid 3D models of the existing and proposed services.

Our 3D models were used effectively to inform the baggage designers of the available space for their conveyors and platforms. The model was used for detailed clash detection which was undertaken as part of the coordination exercise.

Our first takeaway from this project was how to best approach the gigabytes of data associated with point cloud files.

Whilst we were not aware of the process for procuring the point cloud data for the Airport, during the course of our works, we found that the supplied file was too large to be useful. In fact, it was almost unmanageable on our standard hardware. We drew on our own in-house scanning experts to divide the file into four smaller usable datasets.