<p dir="ltr">The CFD-CAA method combines computational fluid dynamics (CFD) and computational aeroacoustics (CAA) techniques to analyze the interaction between fluid flow and the generation and propagation of sound. CFD is primarily concerned with simulating fluid flow patterns, while CAA focuses on predicting noise generation and its propagation in fluids. The CFD-CAA method provides a powerful tool for understanding and predicting the acoustic behavior of turbulent flows. By combining the strengths of CFD and CAA, this approach provides more precise and comprehensive analyses across various fields, thereby contributing to enhanced designs and noise control strategies.</p><p dir="ltr">Within industrial applications, a primary concern is noise source identification. This process enables engineers to locate and quantify the strength of noise sources within a system, facilitating the implementation of more effective strategies during the design process. A novel methodology, computational statistically optimized near-field acoustic holography (C-SONAH), is proposed to virtually identify aeroacoustic sources. Initially, sound pressure is obtained using the CFD-CAA method, followed by the application of the SONAH algorithm to locate acoustic sources and predict the sound field. C-SONAH offers computational advantages over direct CAA methods for simulating sound produced by systems with rotating elements, as CAA analyzes sources on the moving elements, making sound field calculation computationally expensive. The SONAH procedure converts these rotating sources into a series of equivalent stationary planar or cylindrical waves, reducing the number of sources and the time required to compute the sound field from each source. This methodology was demonstrated by characterizing the aerodynamic noise produced by a bladeless fan. The sound pressure level obtained by C-SONAH method was validated by the data predicted by the direct CFD-CAA method. Acoustic maps were reconstructed at different locations and frequencies, revealing that the C-SONAH method can predict noise sources generated by airflow and rotating components within the fan. Thus, it serves as an effective tool for understanding the aeroacoustic noise generation mechanism and guiding the design optimization of similar products.</p><p dir="ltr">The CFD-CAA method is also a powerful tool for design optimization. Computational simulations are typically less expensive and time-consuming than building and maintaining experimental setups, particularly for large or complex projects. Additionally, simulations reduce the need for multiple physical prototypes, which can shorten the development cycle. CFD-CAA simulations provide detailed flow and acoustic field data, including variables that may be difficult or impossible to measure experimentally, such as pressure distributions, velocity fields, and turbulent structures. In this dissertation, aeroacoustic characteristics and flow field information of vortex whistles were investigated using the CFD-CAA method. The simulation results clearly illustrate the swirling motion created in the vortex whistle cylinder and also demonstrate the linear frequency versus flow rate relationship characteristic of the whistle. The design of the vortex whistle was optimized based on the acoustic response and flow resistance by both simulations and experiments. The results suggest that the whistle with a thin inlet exhibits the best performance at high flow rates, while the whistle with a scale of 0.5 is the most sensitive to low flow rates, making it suitable for pediatric applications.</p><p dir="ltr">In CFD-CAA simulations, the time step typically cannot be too small due to limited computational resources. This constraint results in an aliasing error in spectral analysis. Consequently, an anti-aliasing operation prior to sampling is necessary to eliminate such errors from the acoustic source terms. In the present study, an anti-aliasing filter based on the compact finite difference formulation was designed within a time-domain, compact filter scheme. This filter was directly applied to the Navier-Stokes solver prior to sampling for CAA analysis. A cavity flow case was simulated to validate this mitigation strategy. The results indicate that the artificial spectral peak induced by aliasing error is removed without affecting other signature peaks. The anti-aliasing filter was also applied to more complex cases for predicting the acoustic field of a vortex whistle. The acoustic field around the vortex whistle, with both constant and variable inlet flow rates, was simulated, and the aliasing peak was successfully removed. Although the peak magnitudes decreased slightly due to the filter, the signature frequencies remained unchanged. Thus, the simulation with anti-aliasing operation can predict acoustic features without introducing aliasing errors, even if the time step is not sufficiently small, thereby significantly reducing simulation time.</p><p dir="ltr">In engineering applications, once noise sources are identified, the subsequent concern is noise reduction. An effective strategy for noise reduction involves acoustical absorbing materials to minimize noise emissions from components. Traditionally, experiments in engineering applications have focused on surface treatments to explore noise control techniques. However, the CFD-CAA method commonly assumes smooth and purely reflective wall surfaces. Consequently, there is growing interest in incorporating impedance boundary conditions into the CFD-CAA method. Since impedance boundary conditions are defined in the frequency domain, while CFD-CAA simulations operate in the time domain, direct implementation is not feasible. To address this issue, several methods have been proposed to define time-domain impedance boundary conditions in simulations. In the present study, a wall softness model was implemented in the CFD-CAA method and to examine a vortex whistle featuring an acoustically permeable surface. In simulations, an impedance boundary condition representing the properties of melamine foam was defined over the surface of a cylindrical cavity. The simulation results were validated against experimental data obtained from a vortex whistle with melamine foam. The findings revealed that the impedance of the melamine foam contributed to noise reduction at high frequencies. Additionally, at low airflow rates, the impedance boundary condition enhanced the signal-to-noise ratio for the low-frequency peak, which is advantageous in clinical applications.</p>