Development of Computational Methods for Inlet Optimisation in Centrifugal Ventilation Units

Legislation introduced to increase the efficiency of energy-using products, such as fans and ventilation units offered to market presents ever greater challenges in the development of products that meet both minimum efficiency requirements and the needs and expectations of customers. Airflow performance and efficiency of a ventilation unit can be improved though careful consideration of the path the conveyed air takes through a housing or enclosure, and suitably guiding the air to reduce internal pressure losses. Physical performance test iterations to optimise air path geometry are time consuming and require significant materials. Optimisation of air path geometry through computational fluid dynamics (CFD) reduces the number of physical test iterations and introduces a greater control over the test environment; however, this requires a certain level of machine capability, operator skill and understanding to sufficiently set up and review results. This project consider factors affecting performance and efficiency in HVAC units and embarks on the development of a simple spreadsheet-based tool to predict performance, facilitating optimisation of inlet conditions. This tool is developed through benchmarking a ventilation unit with 315mm inlet spigot, comprising an enclosure or rectangular cross section and a single backward curved centrifugal EC motorised impeller mounted on an inclined bulkhead (of known performance characteristics). A series of CFD studies are run to determine which of the key variables (such as height-width of cross section & degree of bulkhead incline) affect the airflow performance and efficiency of the ventilation unit and from this a parametric optimisation of upper and lower variable limits defined. The result of these studies are used to generate a series of enclosure loss polynomial curves which are then developed into a spreadsheet-based tool for future performance estimation against various scenarios. A potential benefit of this tool is the reduction in physical prototype and computational fluid dynamics (CFD) iterations required in the design of new product ranges, allowing for quicker development cycles.