Where Data Meets De
At its core, our approach to mixed-use tower design represents a paradigm shift – one that embraces efficiency-driven decision making across multiple scales. Rather than following traditional static design methods, we’ve developed a dynamic framework that continuously evaluates decisions through four key stages: initial data processing and site analysis, space planning and program distribution, program response optimization, and form generation with performance validation.
What makes this approach unique is its multi-scale operation. At the micro level, individual units adapt and optimize based on local conditions, while at the macro level, genetic algorithms ensure these local optimizations contribute to global performance targets.
This intelligence is built on extensively researched thresholds derived from authoritative sources: site constraints from the Council of Tall Buildings and FAR thresholds from US Land Development code, program size and density thresholds from BOMA Standards and IBC 2021 requirements, technical thresholds from KONE Planning Guides and ASME A17.1 Safety Codes, and economic thresholds based on RS MEANS City Cost Index and ASHRAE standards.
At the heart of our process lies a sophisticated computational ecosystem. While our topological structure reveals complex system interactions powered by Python backend processing, three key systems stand out:
- Monoceros: Handles space planning through advanced algorithms for optimizing unit layouts and program distribution
- WASP: Manages aggregation strategy, ensuring efficient unit combinations while maintaining optimal relationships
- Structural analysis through Karamba: Provides continuous feedback for optimization based on load distribution efficiency, wind patterns, and energy performance
This isn’t merely a process flow – it’s a living system that learns and adapts with each iteration, building upon previous insights to generate increasingly refined solutions.
The APEX method addresses three fundamental challenges in contemporary tower design. First, we tackle the universal challenge of plot adaptation and program distribution. Our algorithm processes site geometry to create optimized solutions for any given plot while maintaining target function percentages across programs.
Second, we optimize core-to-floor plate relationships through a parametric system that maintains optimal ratios while adapting to changing program requirements at different heights.
Finally, we innovate through a tailored facade system that operates on multiple levels:
- Through aggregation processes that control individual component outcomes
- Via a responsive skin system that adapts to environmental demands
- By integrating facade and structural systems for a cohesive program response
The APEX method’s strength lies in its modular intelligence. We’ve developed a comprehensive catalog of adaptive components that respond to both program requirements and overall efficiency. From efficient studios to luxury penthouses, each module is parametrically controlled to optimize layout efficiency while maintaining customization flexibility.
These aren’t just space planning elements – they’re intelligent components that understand their relationship to the whole system, automatically adjusting their configuration based on location, orientation, and adjacent units.
Our workflow represents a cyclical system of continuous optimization rather than a linear process. It begins with site analysis and program requirements input, creating a three-dimensional possibility space that maps all potential configurations.
Through multi-objective optimization, the algorithm iterates through these possibilities, learning from previous results to progressively refine solutions. The final output isn’t a single answer but a family of optimized options, each representing different performance criteria prioritizations.
Our optimized tower demonstrates seamless program integration in action. The structural system showcases how our computational process optimized the core-to-plate relationship, achieving exceptional efficiency ratios while maintaining program flexibility.
The aggregation distribution achieves target ratios while going beyond mere percentages – it creates optimal adjacencies and synergies between different building components, resulting in a truly integrated design solution.
What distinguishes The APEX method is its ability to generate multiple valid solutions within our optimization parameters. Each permutation responds to different input weighted priorities while maintaining consistent performance metrics. The tower morphology adapts while achieving program ratio targets, offering varied approaches to:
- Core efficiency
- Floorplate distribution
- Population density
- Morphological response
Every iteration represents a fully optimized solution, emphasizing different performance criteria while maintaining system integrity and target FAR.
The true power of our computational approach becomes evident in the plan layouts. On typical floors, the system demonstrates sophisticated unit distribution, consistently achieving high efficiencies in floor plate usage while maintaining target typological distribution and ratios. Core dimensions and placement, refined through multiple iterations, provide optimal service distances to all points.
These transitions reveal how the algorithm handles changes in floor plate requirements while maintaining structural and mechanical efficiencies.
To demonstrate our system’s adaptability, we analyzed two extreme scenarios: Singapore’s tropical climate with consistent high temperatures and humidity, and Reykjavik’s subarctic conditions with extreme seasonal variations.
Singapore Analysis:
- Year-round temperatures: 25-32°C
- Average humidity: 84%
- Critical solar gain: >1000 W/m² between 10 AM and 4 PM
- Density impact: Higher density (6X FAR) created 40% increase in solar exposure above 40th floor
Reykjavik Analysis:
- Temperature range: -3°C to 13°C
- Daylight variation: 4 to 21 hours
- Density impact: Improved thermal performance through urban heat islands but reduced daylight availability by up to 60% at lower levels
Our Singapore design responds to ambitious environmental challenges and regulatory requirements, particularly the SGBMP 80-80-80 requirements:
- 80% green-certified buildings
- 80% Super Low Energy rated new buildings
- 80% improvement in energy efficiency by 2030
Our performance-driven solution features:
- An interweaving balcony system creating self-shading facades, reducing solar gain by 78%
- Integrated ‘smart vertical habitats’ contributing to Green Plot Ratio requirements while providing natural cooling through evapotranspiration
Our Reykjavik design, HUIPPU, takes a different approach to environmental response, aligned with Iceland’s sustainability legislation requiring mandatory Life Cycle Assessments from 2025 and targeting 55% reduction in construction emissions by 2030.
The ‘Arctic Mesh’ facade system features a parametric diamond pattern that can be deployed statically or kinetically, adapting to extreme daylight variations while addressing Iceland’s LCA requirements and reducing heating demand compared to conventional facades.
The APEX method represents more than a computational design system – it embodies a fundamental shift in architectural intelligence. Through generational learning, each project enriches our solution database, where every design decision informs and improves future iterations.
This isn’t just about optimized building design – it’s about evolving architecture itself, creating structures that are grown rather than just constructed, truly intelligent rather than merely optimized. The APEX method points toward a future where computational design and architectural creativity merge to create more sustainable, efficient, and adaptable buildings.
