CFD-based guidelines for selecting air purifiers to improve indoor air quality
Computational Fluid Dynamics (CFD) modeling service that simulates how air purifiers perform in real rooms, helping institutions and individuals choose the right device for cleaner indoor air. The work addresses a clear knowledge gap: no reliable guidelines exist for matching purifier type and placement to specific indoor environments.
Overview
Indoor air quality (IAQ) directly affects health, comfort, and productivity in schools, hospitals, offices, and homes. Although air purifiers are increasingly common, buyers lack clear, evidence-based guidance on which device to choose or where to place it for the best results. The complex airflow patterns inside real rooms make it difficult to predict purifier performance using traditional engineering methods.
This offering applies Computational Fluid Dynamics (CFD) simulation to model how air purifiers interact with the geometry, ventilation, pollution sources, heat, and moisture of a specific indoor space. The result is practical, room-specific guidance on purifier selection, placement, and operating parameters that measurably improves IAQ.
Technical specifications
Modeling and simulation approach:
- 3D geometry and flow domain built from as-built drawings of the target room
- Representation of pollution, heat, and moisture sources, plus the air purifier itself
- Grid independence testing to ensure reliable numerical results
- Carefully defined boundary conditions reflecting real operating scenarios
- Established numerical procedure with validation against experimental measurements
Factors investigated:
- Air purifier operating parameters and airflow characteristics
- Purifier location within the room
- Biological pollutant concentrations and behavior
- Influence of room layout, ventilation, and indoor climate conditions
Deliverables:
- Validated CFD model for the studied environment
- Comparative analysis of purifier configurations
- Written guidelines for selecting and using air purifiers in educational facilities, healthcare units, offices, and private residences
Technology readiness level
The research is at an advanced validation stage. The CFD methodology has been defined across geometry modeling, source definition, grid testing, boundary condition preparation, numerical setup, simulation, and result validation. The next step uses measured data to finalize a validated CFD model and translate findings into actionable selection guidelines for diverse institutions and consumers.
About Silesian University of Technology
Silesian University of Technology is a public technical university anchored in Gliwice with campuses in Katowice and Zabrze, serving the industrial Silesia region. Industry partners engage through co‑located laboratories and shared facilities and via Technopark Gliwice, a science and technology park co‑founded with the city and the Katowice Special Economic Zone. A long‑standing collaboration with the Special Economic Zone supports dual‑study pathways and an Industry 4.0 competence center that links companies to university talent and infrastructure. Research is backed by competitive European Union programmes and national agencies such as the National Centre for Research and Development. A dedicated technology transfer office and incubation services assist IP, licensing, and spin‑out formation.
Inquire about this partnering listing
Available for
Industry applications
delivered to your inbox.