Optimal Air Flow Modeling in Real Healthcare Facilities for Quick Removal of Contaminated Air

Background: Contaminated air can have a negative impact on patient recovery, leading to longer hospital stays, higher healthcare costs, and even death. Objective: Our study focuses on improving indoor air quality for patient recovery in healthcare facilities. Methods: We conducted computational analysis using the finite element modeling (FEM) technique to investigate the flow of contaminated air exhaled by a patient. Distinct models were examined: a neonatal intensive care unit (NICU) with two-beds and a coronavirus isolation room (CIR). Using ANSYS, we designed models using actual and real specifications of both NICUs and IRs from local hospitals. We determined the optimal dimensions and locations of outlet vents in NICUs and CIRs using simulations with ANSYS software drawing on our designed modeling of air flow. Outlet vent dimensions and locations were modified to achieve optimal air flow for quickly venting out contaminated air from a patient in a room. Results: The results show a substantial improvement in directly venting out the contaminated air from the patient. Conclusions: It can be concluded that the optimal design of outlet vent locations and dimensions using ANSYS simulation results in finding the optimal path for the quick removal of contaminated air flow from the patient in an NICU and CIR.