Raymond Ambs

Validation of a CAA formulation based on Lighthill's Analogy using AcuSolve and ACTRAN/LA on an Idealized Automotive HVAC Blower and on an axial fan

The purpose of this work is to evaluate a Computer Aided Engineering (CAE) method in which computational aero acoustics (CAA) techniques are used to predict the noise level from automotive fans. The engineering objective is to ensure that the noise level in an automotive cooling system or an air handling system is sufficiently low for all operating conditions. In fact, automobile manufacturers are placing increased emphasis on the reduction of cabin noise level so that this noise reduction has become a critical design consideration. This has resulted in more stringent noise requirements for air handling systems and other cooling systems. For most operating conditions, the blower is the major noise contributor for the cabin noise level. In this paper we use the extended version of the variational formulation of Lighthill’s analogy, as presented in Caro et al. This formulation is ideally suited to the finite element method (FEM). It accounts for aerodynamic sources through two source terms. The first term accounts for volume sources; the second term accounts for sources defined on control surfaces, i.e., surfaces where the normal flow velocity does not vanish. An important contribution of the present work is an innovative approach for transferring information from the CFD mesh to the CAA one. This problem has a significant practical importance because CFD ∗Contact: robert@pioneersolutionsinc.com †Corresponding author: stephane.caro@fft.be Copyright c

Prediction of flow-induced noise in automotive HVAC systems using a combined CFD/CA approach

Noise emission from automotive HVAC systems has become an important factor for passenger comfort. Consequently, efforts are made during the design phase to minimize noise generation, and to improve sound quality. Predictive tools for the aeroacoustic behavior of components, subsystems and whole systems early on in the design phase are therefore desirable. In this paper a combined Computational Fluid Dynamics (CFD) and Computational Acoustics (CA) approach for the prediction of sound generation and propagation is investigated. Three different experimental setups, ranging from a more academic example to examples relevant in the design process of climate control systems, have been devised to provide test data for the evaluation. Experimental and numerical results are presented and discussed.