Extension of the Air Distribution Network Design Optimization algorithm

implementation of fittings


  • Sandy Jorens University of Antwerp
  • Zakarya Kabbara University of Antwerp
  • Ehsan Ahmadian University of Antwerp
  • Ivan Verhaert University of Antwerp




Air distribution system design, ayout optimization, fittings, zeta values, heuristics, test case


The number of requirements that heating, ventilation, and air conditioning (HVAC) systems in buildings have to fulfill continues to rise. Design engineers are being challenged to design HVAC systems with high standards of performance considering, comfort and energy efficiency. These conflicting objectives have to be achieved within a limited budget and time. Presently, considerable reliance is still placed on rules of thumb and the designer’s experience, which often results in sub-optimal designs. More than ever, there is a need for practically usable design tools. Especially in the field of centralized air distribution system design, user-friendly tools are needed to support the design engineer. In previous research, an air distribution network design (ADND) optimization algorithm was developed. The ADND algorithm is a heuristic optimization algorithm that automatically generates numerous different air distribution system configurations (i.e., ductwork layout and sizing) for non-residential buildings while minimizing the material costs. Although the ADND algorithm shows promising results, some additions are still required before the algorithm can be used in practice. Currently, the objective function is limited to the minimization of material costs. However, other objectives, e.g., minimization of energy costs or noise levels, are not yet considered. Moreover, the generated configurations are based on the aeraulic performance of only circular and rectangular ducts. Fittings and other ventilation components (e.g. silencers and diffusers) are not yet included. In this research, the ADND optimization algorithm was improved by implementing fittings (i.e., bends, reducers, tees, and cross fittings) in the optimization algorithm. A practical test case demonstrates the extended ADND optimization algorithm.




How to Cite

Jorens, S., Kabbara, Z., Ahmadian, E., & Verhaert, I. (2022). Extension of the Air Distribution Network Design Optimization algorithm: implementation of fittings. CLIMA 2022 Conference. https://doi.org/10.34641/clima.2022.99

Conference Proceedings Volume