Decarbonization Building

Objectives

To optimize decarbonization efficiency by minimizing re-entrainment of carbon-depleted air.
To conduct a parametric study on building configurations and airflow dynamics to identify effective designs.
To apply computational fluid dynamics (CFD) techniques for simulating velocity, pressure, and species transport.
To analyze the impact of boundary conditions and wind profiles on airflow around decarbonization buildings.
To evaluate pressure and velocity profiles to determine their role in re-entrainment and turbulence management.
To quantify the re-entrainment ratio and its effect on CO₂ capture efficiency across various configurations.
To prepare for future 3D simulations and dynamic environmental conditions to enhance real-world applicability.

Conducted simulations on decarbonization building geometries, maintaining a constant area for comparative analysis.
Implemented fractional step and finite difference methods for velocity and pressure computations.
Used staggered Cartesian meshes and dynamic time-stepping to ensure numerical stability and precision.
Evaluated performance using metrics like re-entrainment percentages, turbulence, and pressure gradients.

10x20 and 8x25 configurations minimized re-entrainment to 5.08% and 7.03%, demonstrating enhanced decarbonization efficiency.
Wider configurations like 20x10 resulted in higher re-entrainment (11.68%), highlighting geometry's critical role in airflow management.
Achieved streamlined velocity fields and reduced turbulence in taller structures, validating computational efficiency.

Expand simulations to 3D geometries and dynamic wind conditions for more robust predictions.
Explore hybrid configurations combining tall cores with optimized outlet designs for balanced efficiency and feasibility.
Develop predictive tools using AI for real-time optimization of building designs under varying environmental conditions.
Collaborate with multidisciplinary teams to translate findings into practical applications.