What does this studio actually demonstrate?
One parametric model carrying a whole build-to-rent development, chapter by chapter. The engine generates four massing typologies inside the planning envelope and scores each for GFA, unit yield, facade area, cost index, solar access and wind exposure. The chosen form is then cut into real floorplates with a lift core sized from the units above it, two fire stairs, a 1.8 m double-loaded corridor and units placed to a mix target. One structural grid is solved across those plates, blades and shear walls are placed on it, any vertical that cannot run to ground is priced as a transfer, and the parking brief is packed into drawn bays. Facades panelise into a unitised kit, quantities drive a 4D delivery programme, and the pro forma closes the loop. Nothing is pre-baked: change the height limit in chapter one and the yield on cost in chapter seven moves.
How is yield on cost computed here?
Bottom up, from the geometry. The cost plan applies rates per square metre of GFA by element group (structure, facade, services, fitout) to the quantities the engine produced, adds preliminaries and escalation, and adds land, so total development cost is a consequence of the design rather than an input. Income is a rent roll built from the actual units cut on each plate at weekly rents by type, adjusted for the site, plus car parking and storage income, less vacancy and an operating expense ratio. Stabilised net operating income divided by total development cost gives yield on cost, and the sensitivity view swings rent, cost, programme and cap rate to show which one the return really depends on.
What does the structure and parking chapter actually compute?
One grid for the whole scheme, solved rather than drawn. The engine picks a module, sets it out from the widest footprint and shifts it to catch as many party walls between homes as it can, then publishes the share it actually caught instead of claiming a perfect fit. Blades and shear walls are placed on that grid and sized from the floors they carry, and every column that lands in habitable space is ringed on the plan and counted against the scheme. Where the podium or the ground plane asks for a clear span, the verticals that can no longer run to ground become a transfer: the studio measures the deck area, names the offending verticals with their offsets and tributary loads, and prices it in dollars and working days that flow into the cost plan and the delivery programme rather than into a footnote. Parking is packed as real 2.4 by 5.4 m bays with 6.0 m drive aisles, a ramp and hatched core exclusions in a basement or podium tank, and the number reported is the number drawn: any shortfall against the planning ratio, or a square metre per bay outside the healthy band, is stated on the drawing and in the board pack rather than rounded away.
What does DfMA panel repetition mean for delivery?
Repetition is what makes a facade a manufactured product instead of a construction activity. The studio panelises every elevation onto a 1.5 m module at 3.3 m floor to floor, assigns each bay a family (glazed, solid insulated, balcony or corner), then counts how few unique panel types deliver the whole building. High repetition means one panel is drawn, prototyped and tested once, then produced hundreds of times at a steady factory rate while the structure is still rising. In the programme chapter that shows up directly: unitised facade and bathroom pods compress the facade and fitout durations against the stick-built comparison, and the studio reports the weeks saved and what each week is worth.
How would this deploy into a client BIM ecosystem?
As an engine, not a website. The geometry, plates, panel schedule, programme and cost model are pure functions over a single configuration object, so the same code can drive a Revit or IFC exchange, publish quantities to a cost system, push panel families to a fabricator, or feed programme data to a scheduling tool. In client work we replace the distilled benchmark assumptions with the project's own planning controls, unit standards, cost plan and supplier rates, connect it to the live model and data environment, and land the results as native model elements and reports rather than screenshots.