Catalyx by Ramboll

This is a demonstration of our digital capabilities and how we use technology to support our experience and expertise in project delivery. We start with good data collected through our in house drone fleet, which is processed to develop key datasets to form a digital model. Onto this, we lay a site specific criteria. In this case, floodplains, streams, disturbance zones, easements, setbacks, and the like, to integrate the constraints together with the building and road components in three d geometry. Here, we have established eight independent degrees of freedom, global x, global y, global z, rotation, local z adjustment, separate, and slide. We define geometry parametrically so we can make real time changes while simultaneously regrading the site. This approach allows for the seamless control of geometry. We established the main building using an integrated systems approach in an effort to precoordinate as many of the multidisciplines as possible and encode parametric range within the structural frame to future proof our designs to down the road changes. In this way, the building geometry can respond as the assembly line criteria is being established. We set up objectives which promote good DNA within the structural frame and then use these to test and rank them the multiple possible geometries. This geometric optimization process is powered by artificial intelligence and seeks to find the best trade off solutions out of all the possibilities. This results in solutions with strong structural performance yet with lower cost than embodied carbon. With the steel frame optimized, we then bring in other key systems to test their integration as well as to look at the possibility of including sustainable strategies. As with the building, but now for the site, we define desirable objectives which we want to drive into the design. In this case, the objectives fall into two categories, cost and viability, and so we optimize the site in order to find the best minimum viable cost. The spider plot shows the process of machine learning algorithm as it tests multiple geometries and is looking to minimize the area of the graph. As it progresses, it starts to home in on foresight configurations, which have different blends of cost and viability. The insight we found shows that the most feasible solutions also had the highest earthworks cost potential and vice versa. We share this data with our clients so we can work together to better understand problems and find more desirable outcomes. We've developed sophisticated earthworks tools, which use our optimized output to develop three d cut fill sequences, and in this case, to incorporate the proposed construction phasing. This enables us to develop regrade plans within hours, not weeks, and helps make the design process more agile. Three d modeling from the outset allows us to render our geometries at any stage to give a good look and feel of the design as well as to carry out visual impact studies and support community engagement. All these tools and processes are used to augment our experience and expertise. We do not use these approaches as a shortcut rather as part of our process to uncover the best economic and environmental design possible. We host this platform so that our clients can immersively interact with their development in new ways and experience design like ever before.