arXiv subjects

Mohsen Hamedi

Publications and source records attributed to Mohsen Hamedi.

4 recordsLinked to original sources

arXiv2025

Far-Field Aeroacoustic Shape Optimization Using Large Eddy Simulation

This study presents a shape optimization framework that combines a Flux Reconstruction (FR) spatial discretization, Large Eddy Simulation (LES), the Ffowcs-Williams and Hawkings (FW-H) formulation, and the gradient-free Mesh Adaptive Direct Search (MADS) optimization algorithm. We emphasize the necessity of duplicating the data surface to achieve accurate far-field noise prediction in spanwise periodic problems using the FW-H formulation. The proposed parallel implementation of the optimization framework ensures consistent runtime per optimization iteration, regardless of the number of design parameters, thereby addressing a common limitation of many gradient-free algorithms. The framework is demonstrated through far-field aeroacoustic shape optimization of NACA 4-digit airfoils at a Reynolds number of $23,000$. The objective function minimizes the Overall Sound Pressure Level (OASPL) at a far-field observer positioned $10$ unit chords below the trailing edge, while preserving the mean lift coefficient and reducing the mean drag coefficient. The optimized airfoil achieves an OASPL reduction of $5.9~dB$ and over $14\%$ decrease in mean drag, while maintaining the mean lift coefficient. These results underscore the feasibility and effectiveness of the proposed approach for practical shape optimization applications.

physics.flu-dyn↗

arXiv2025

Near-Field Aeroacoustic Shape Optimization at Low Reynolds Numbers

We investigate the feasibility of gradient-free aeroacoustic shape optimization using the Flux Reconstruction (FR) approach to study two-dimensional flow at low Reynolds numbers. The Overall Sound Pressure Level (OASPL) is computed via the direct acoustic approach, and optimization is performed using the gradient-free Mesh Adaptive Direct Search (MADS) algorithm. The proposed framework is assessed across three problems. First, flow over an open cavity is investigated at a Reynolds number of $Re=1500$ and free-stream Mach number of $M_\infty = 0.15$, resulting in a $7.9dB$ noise reduction. The second case considers tandem cylinders at $Re=200$ and $M_\infty = 0.2$, achieving a $16.5 dB$ noise reduction by optimizing the distance between the cylinders and their diameter ratio. Finally, a NACA0012 airfoil is optimized at $Re=10,000$ and $M_\infty = 0.2$ to reduce trailing edge noise. The airfoil's shape is optimized to generate a new 4-digit NACA airfoil at an appropriate angle of attack to reduce OASPL while maintaining the baseline time-averaged lift coefficient and preventing an increase in the baseline time-averaged drag coefficient. The optimized airfoil is silent at $0dB$ and the drag coefficient is decreased by $24.95\%$. These results demonstrate the feasibility of shape optimization using MADS and FR for aeroacoustic design.

physics.flu-dyn↗

arXiv2025

Gradient-Free Aeroacoustic Shape Optimization Using Large Eddy Simulation

We present an aeroacoustic shape optimization framework that relies on high-order Flux Reconstruction (FR), the gradient-free Mesh Adaptive Direct Search (MADS) optimization algorithm, and Large Eddy Simulation (LES). Our parallel implementation ensures consistent runtime for each optimization iteration, regardless of the number of design parameters, provided sufficient resources are available. The objective is to minimize the Overall Sound Pressure Level (OASPL) at a near-field observer by computing it directly from the flow field. We evaluate this framework across three problems. First, an open deep cavity is considered at a free-stream Mach number of $M_\infty=0.15$ and Reynolds number of $Re=1500$, reducing the OASPL by $12.9~dB$. Next, we considered tandem cylinders at $Re=1000$ and $M_\infty=0.2$, achieving over $11~dB$ noise reduction by optimizing cylinder spacing and diameter ratio. Lastly, a baseline NACA0012 airfoil at $Re=23000$ and $M_\infty=0.2$ is optimized to generate a new 4-digit NACA airfoil at an appropriate angle of attack to minimize the OASPL while ensuring the baseline time-averaged lift coefficient is maintained and prevent any increase in the baseline time-averaged drag coefficient. The OASPL and mean drag coefficient are reduced by $5.7~dB$ and more than $7\%$, respectively. These results highlight the feasibility and effectiveness of our aeroacoustic shape optimization framework.

physics.flu-dyn↗

arXiv2021

Augmented reality applications in manufacturing and its future scope in Industry 4.0

Augmented reality technology is one of the leading technologies in the context of Industry 4.0. The promising potential application of augmented reality in industrial production systems has received much attention, which led to the concept of industrial augmented reality. On the one hand, this technology provides a suitable platform that facilitates the registration of information and access to them to help make decisions and allows concurrent training for the user while executing the production processes. This leads to increased work speed and accuracy of the user as a process operator and consequently offers economic benefits to the companies. Moreover, recent advances in the internet of things, smart sensors, and advanced algorithms have increased the possibility of widespread and more effective use of augmented reality. Currently, many research pieces are being done to expand the application of augmented reality and increase its effectiveness in industrial production processes. This research demonstrates the influence of augmented reality in Industry 4.0 while critically reviewing the industrial augmented reality history. Afterward, the paper discusses the critical role of industrial augmented reality by analyzing some use cases and their prospects. With a systematic analysis, this paper discusses the main future directions for industrial augmented reality applications in industry 4.0. The article investigates various areas of application for this technology and its impact on improving production conditions. Finally, the challenges that this technology faces and its research opportunities are discussed.

cs.CY↗