Edge Noise Reduction Research Articles

Numerical investigation of serration angle on trailing edge noise reduction

The influence of serration angle on the three-dimensional flow characteristics and noise attenuation mechanisms of a NACA6512-63 airfoil is explored in this research using large eddy simulation (LES) and spectral proper orthogonal decomposition (SPOD) methods. Analysis of the mean flow field reveals the formation of counter-rotating vortex pairs, resulting from the outward flow towards the serration edges and the downwash flow in the valleys. This flow modification alters the effective angle of the serration, which in turn impacts its noise reduction performance. Furthermore, the noise reduction mechanism is investigated by comparing the general solution of Lyu's semi-analytical equation with the SPOD mode results, and the frequency range associated with noise attenuation is analyzed. The findings indicate that the case with λ/h=0.15 demonstrates the most significant noise reduction effect. This research offers valuable insights into the interplay between serration geometry and the resulting flow characteristics and noise reduction mechanisms.

Enhanced low-light image fusion through multi-stage processing with Bayesian analysis and quadratic contrast function

This manuscript introduces an innovative multi-stage image fusion framework that adeptly integrates infrared (IR) and visible (VIS) spectrum images to surmount the difficulties posed by low-light settings. The approach commences with an initial preprocessing stage, utilizing an Efficient Guided Image Filter for the infrared (IR) images to amplify edge boundaries and a function for the visible (VIS) images to boost local contrast and brightness. Utilizing a two-scale decomposition technique that incorporates Lipschitz constraints-based smoothing, the images are effectively divided into distinct base and detail layers, thereby guaranteeing the preservation of essential structural information. The process of fusion is carried out in two distinct stages: firstly, a method grounded in Bayesian theory is employed to effectively combine the base layers, so effectively addressing any inherent uncertainty. Secondly, a Surface from Shade (SfS) method is utilized to ensure the preservation of the scene's geometry by enforcing integrability on the detail layers. Ultimately a Choose Max principle is employed to determine the most prominent textural characteristics, resulting in the amalgamation of the base and detail layers to generate an image that exhibits a substantial enhancement in both clarity and detail. The efficacy of our strategy is substantiated by rigorous testing, showcasing notable progressions in edge preservation, detail enhancement, and noise reduction. Consequently, our method presents significant advantages for real-world applications in image analysis.

A Deep Learning Approach to Optimize Airfoil Shape for Reduced Trailing Edge Noise in Urban Air Mobility Rotors

The objective of this research is to optimize the airfoil shape of UAM VTOL rotors for trailing edge noise reduction. Our study focuses on employing deep learning techniques for airfoil shape optimization with an emphasis on noise reduction. We implement a neural network that combines a Variational Autoencoder and Generative Adversarial Networks to learn the representation of airfoil shapes. The generated airfoil shapes are then evaluated for aerodynamic performance using XFOIL and trailing edge noise using acoustic diffraction model. The optimization process employs a Particle Swarm Optimization algorithm to find optimal latent features for airfoil generation. The results show that the optimized airfoil shapes have improved aerodynamic performance and reduced noise levels compared to the airfoil VR-12 used in NASA's conceptual UAM. These findings demonstrate that our optimization process has the potential to reduce trailing edge noise while ensuring enhanced aerodynamic performance, which warrants further investigation.

Experimental Study on Wind Turbine Airfoil Trailing Edge Noise Reduction Using Wavy Leading Edges

Aerodynamic noise produced by the rotating blade is an important hindrance for the rapid development of modern wind turbines. Among the various noise sources, the airfoil trailing edge noise contributes a lot to the wind turbine noise. The control of wind turbine airfoil trailing edge self-noise by bio-inspired sinusoidal wavy leading edges is experimentally studied in a semi-anechoic chamber. The noise radiated by the baseline NACA 0012 airfoil and various wavy airfoils is measured using a planar microphone array consisting of fifty-two microphones. The noise source identifications are achieved by using the CLEAN-SC method. The effects of velocity and angle of attack on noise radiation of the baseline airfoil are analyzed in detail. The noise control law of the wavy amplitude and wavelength on airfoil trailing edge noise is explored. Based on the acoustic beamforming results, the noise control effects of the wavy leading edges are intuitively demonstrated. In general, the wavy leading edge with a larger amplitude and smaller wavelength has a better effect on the airfoil trailing edge noise reduction. The maximum sound pressure level reduction can be up to 33.9 dB. The results of this study are expected to provide important information for wind turbine aerodynamic noise control.

EPLL image denoising with multi-feature dictionaries

The expected patch log likelihood (EPLL) is a patch-prior based denoising model that has become a popular tool in image restoration for its outstanding edge preservation and noise reduction abilities. However, without considering the geometrical feature of patches, the EPLL removes numerous important details and frequently suffers from the staircase effect, residual noise and artifacts. To preserve more detailed information and suppress the generation of artifacts, we propose a novel EPLL denoising model with multi-feature dictionaries (MFDs) and adaptive regularization parameters in this paper. In the proposed method, to exploit the statistical and geometrical characteristics of patches, two feature layers are designed before training the Gaussian mixture model (GMM). In the first layer, the within-class variance minimum (WCVM) method is used to learn the statistical features of patches. In the second layer, two geometrical characteristic dictionaries (GCDs) are trained. In the denoising phase, we select the corresponding dictionary for each patch. Then, each patch is denoised independently. Moreover, the mean localized spectral response (MLSR) based regularization parameters are employed in the proposed method, which is spatial self-adaptive and robust to noise. Extensive experiments demonstrate that our approach achieves desired performance in both detail preservation and artifact suppression compared to many existing denoising methods.

A computational study of trailing edge noise suppression with embedded structural compliance.

A unique concept for suppression of trailing edge noise scattering from a splitter plate in a low Reynolds number flow is proposed. The key idea of the concept is the adoption of a structural compliance system embedded with a finite number of elastic panels. Specific compliance system designs are devised for promotion of panel structural resonance that effectively absorbs broadband flow/acoustic fluctuation energy responsible for noise scattering. The concept is examined using high-fidelity direct aeroacoustic simulation together with spatiotemporal aeroacoustic-structural interaction analysis. The concept is confirmed feasible and outperforms many similar trailing edge noise reduction approaches reported in the literature.

Design of an optimized fuzzy system for edge detection in images

Edge Detection is the first stage in the image division into separate parts. Image division is the partitioning of a digital image to the different zones or the set of pixels. Edge detection is one of the techniques applied in digital image processing often. The purpose of detecting pixels is to match the edges in the image. Filtering, Enhancement, and Detection are three steps in edge detection. Images are usually destroyed by casual changes in intensity intervals called noise or confusion. some noise variations include salt and pepper, pulse, and Gaussian. However, there is a relation between edge detection power and noise reduction. Using filters to the noise reduction causes the loss of edge detection power. For facilitating the edges detection, it is essential for the determination of pixels’ intensity constraints in their neighborhood. Many points in an image have a nontransparent slope, and all of them are not the edges of the joint space. Therefore, some of the linear and nonlinear methods such as Sobel, Prewitt, and Robert have to be used to determine the edge points. The fuzzy logic and the system based on it, is one of the most effective methods for edge detection. This paper presents an optimized rule-based fuzzy inference system and designs the efficiency mask matric. The simulation results for edge detection are presented using the traditional edge detection techniques, including Binary Filter, Sobel Filter, Prewitt Filter, and Robert Filter. Also, it is presented using the fuzzy approach. The simulation results show that the designed fuzzy system has been able to detect the edges of the image more accurately and help to increase the sharpness and quality of the edges. Therefore, the proposed method has more accurate and more reliable results and reduces false edge detection comparison to the traditional methods.

Broadband trailing edge noise reduction through porous velvet-coated serrations

This study experimentally investigates the potential of using combinations of trailing edge serrations and thin porous membrane/velvet structures for turbulent boundary layer trailing edge noise reduction. The experiments were conducted in an anechoic wind tunnel, with a flat plate model as the baseline model. The chord-based Reynolds number ranged between 2×105 and 5×105, and the boundary layers were fully tripped near the leading edge. Two different installation methods were tested, where the serration structure was aligned/misaligned with the undisturbed wake flow. It was observed that the noise reduction capability of the conventional serrations deteriorates significantly when the serrations are misaligned with the flow, while the performances of the combined structures are only slightly affected by flow misalignment. A novel combined treatment is developed, in which the trailing edge serrations are surrounded by serrated porous velvet structures. This treatment is found to outperform the unmodified serrations and can achieve approximately 10 dB noise reduction in both flow-aligned and flow-misaligned conditions, within a wide frequency range corresponding to a boundary layer thickness-based Strouhal number Stδ between 0.3 to 1. A 30%–40% increase in the aerodynamic drag due to the velvet structures was observed. Further hotwire wake survey revealed the possible mechanisms for the additional noise reduction capability of the combined treatments.

Trailing-edge noise reduction potential of a locally applied shallow dimpled surface

There is a strong need for airframe noise reduction methods that preserve the aerodynamic performance of lift-generating airframe components. Inspired by the drag reduction studies of van Nesselrooij et al. (2016) and Spalart et al. (2019), the current study explored the trailing-edge noise reduction potential of shallow dimples applied near the trailing edge of a NACA0012 airfoil (approximately the latter 18% of the chord). The effect of shallow dimples on the aerodynamic coefficients is studied by Reynolds Averaged Navier–Stokes (RANS). To investigate the noise reduction credentials of dimples, high-fidelity Overset-Large Eddy Simulations are carried out for a chord based Reynolds number Rec of 4.2 ×105 at zero angle of attack. Near-field analysis revealed that this local application of dimples eliminated the tonal vortex shedding noise, which is otherwise present in the reference configuration without dimples. Furthermore, the application of shallow dimples resulted in the breakdown of the span-wise coherence in the low-to-mid frequency range and a reduction in the convective velocity of the stream-wise convecting eddies. These effects have a favourable impact on the trailing edge noise reduction with a modest 1.8% increase in the overall drag (less than 1 drag count). The far-field sound characteristics revealed that the dimple treatment resulted in the reduction of overall sound pressure levels in the downstream radiation direction (≈ 5.5 dB) and an increase in the upstream radiation direction (≈ 3.5 dB). In a nutshell, this manuscript argues for the inclusion of shallow dimples to the list of potential candidates for passive noise reduction methods, such as serrations, porous materials, and finlets.

Numerical investigation of leading edge noise reduction on a rod-airfoil configuration using porous materials and serrations

A lattice-Boltzmann method has been employed to study the aeroacoustics and aerodynamics of airfoils equipped with leading edge treatments, namely the porous leading edge and leading edge serrations. The present study aims to identify the differences in noise reduction mechanisms between the two treatments. Within the context of turbomachinery applications, the airfoils undergo aerodynamic excitation due to the impingement of turbulent wake shed by an upstream rod. Two airfoil profiles are considered: NACA 0012 and NACA 5406; the latter mimics geometrical features and aerodynamic loading distribution of the outlet-guide vane in a turbofan test rig. Simulations are carried out at a freestream Mach number of 0.22, corresponding to Reynolds number based on the rod diameter of 48 000. The serrations are designed to follow a sinusoidal planform shape, whereas the porous leading edge is based on a Ni-Cr-Al metal-foam with homogeneous and isotropic properties. It is found that the porous leading edge attenuates noise by dampening surface pressure fluctuations due to the reduced blockage effect compared to the solid one. Differently, the leading edge serrations promote destructive interference of noise sources along the span. When applied against turbulent inflow with tonal characteristic, such as that induced by the impingement of Kàrmàn vortex street in the rod wake, the latter is more effective. On the other hand, both treatments are found to produce similar broadband noise reduction. When comparing aerodynamic performances, it is found that under a lifting condition, cross-flow is present through the porous material which results in lift reduction and drag increase. A serrated porous leading edge is then proposed to combine the benefits of the two leading edge treatments. This results in optimal noise reduction performances and lower aerodynamic penalty with respect to the fully porous leading edge.

Numerical investigation of porous materials for trailing edge noise reduction

In the framework of the German Collaborative Research Center CRC 880: Fundamentals of High Lift for Future Civil Aircraft porous materials as a means towards the reduction of airfoil trailing edge noise are investigated. At DLR, both experimental and numerical approaches are pursued to understand the physics behind the noise reduction. The present paper focuses on the numerical investigations, for which the experimental data serves as an evaluation basis. From the analysis of homogeneous materials, first steps are made towards the design of aeroacoustically tailored materials. It is assumed that materials with locally varying permeability may be suitable to achieve maximum noise reduction, as they provide a smooth transition from the solid airfoil to the free flow in the wake. The simulation results support this understanding, however it is revealed that high local gradients in the material properties themselves may act as acoustic sources.

Uniform flow injection into a turbulent boundary layer for trailing edge noise reduction

The hydrodynamic effects of inclined uniform continuous blowing on a turbulent boundary layer are investigated experimentally. A laminar flow is introduced into the boundary layer through a fence on a flat plate at a distance of 3.38δ0 upstream of the trailing edge. The effects of this open-loop technique of flow control are examined at different angles of injection and at different blowing rates. Surface pressure fluctuations acquired from flush-mounted microphones are used to estimate the trailing edge noise. Injection angles of 70° and 90° in combination with strong blowing rates enable a noise reduction of up to 15 dB at mid and high frequencies, f > 300 Hz. Similar aeroacoustic performances are obtained at a blowing angle of 50° but at lower blowing rates. At low frequencies, a penalty is expected, with the trailing edge noise increasing for all the injection angles and blowing rates under analysis. Mean velocity profiles from hot-wire anemometry reveal that high injection angles and strong blowing rates induce a flow separation, which is expected to deteriorate the aerodynamic performances. When applying a uniform blowing at 50°, however, no flow separation occurs. From an aeroacoustic and aerodynamic point of view, uniform blowing applied at 50° and at intermediate blowing rates is found to be the most promising setting.

Numerical study of 3-D finlets using Reynolds-averaged Navier–Stokes computational fluid dynamics for trailing edge noise reduction

This paper uses Reynolds-averaged Navier–Stokes computational fluid dynamics to study trailing edge noise reduction with 3-D finlets. Reynolds-averaged Navier–Stokes computational fluid dynamics provides boundary layer parameters near a trailing edge for an empirical wall pressure spectrum model, and then an acoustic model predicts far-field noise based on pressure fluctuations obtained from the wall pressure spectrum model. First, this numerical approach is validated against experiments. Second, a comprehensive trend analysis is conducted to give insight into the design of 3-D finlets under different flow conditions. A data-driven turbulence spanwise length scale model is developed to tackle finlets with small spacing. Combined with acoustic results, detailed computational flow field results are analyzed to understand the physical mechanism of noise reduction. While the major part of the proposed mechanism is the same as prior work, several new observations are shown which better understand the physical mechanism of noise reduction with 3-D finlets. The goals of the current paper are to provide an efficient Reynolds-averaged Navier–Stokes-based approach to predict trailing edge noise of 3-D finlets, to give complete trend analysis results with various finlets under different flow conditions, and to advance an understanding of the underlying physics.

An Effective Hybrid Algorithm for De-Speckling the Speckle Noise in SAR Images

Image Processing has emerged as an essential lookup domain in circuit branches for quite a few decades. SAR is a type of Radar. It is connected to pics of articles like scene. It applies e SAR receiving wide development to the target for acquiring better spatial resolution than what is got through customary beam-scanning radars. In digital image processing field, processing Synthetic Aperture Radar is unexpectedly gaining focus. Very similar to all image processing methods, issues such as edge detection, enhancement and noise reduction are vital lookup troubles in SAR images also. Of late, speckle noise has emerged as a massive issue. Because of its presence, the SAR Images are classified as robust and multiplicative noises. Effecting speckle noise reduction in Synthetic Aperture Radar photographs is pretty challenging. Synthetic Aperture radar and its description is used in the utility of Flood prediction mapping. In this paper we implemented a better methodology for de-speckling Synthetic Aperture Radar imagery by way of using Fuzzy Discontinuity adaptive Non neighborhood potential filter. Application of fuzzy strategy to Importance sampling unscented kalman filter produces better end result than compared with fuzzy frost filter and also the TMAV and ATMAV produces higher end result therefore it can be a satisfactory filter for de-speckling.

Airfoil Trailing Edge Noise Reduction Using a Boundary-Layer Bump

This paper presents a new idea of reducing airfoil trailing edge noise using a small bump in the turbulent boundary layer. First, we develop and validate a new computational approach to predict airfoil trailing edge noise using steady RANS CFD, an empirical wall pressure spectrum model, and Howe's diff raction theory. This numerical approach enables fast and accurate predictions of trailing edge noise, which is used to study the noise reduction from the bump for various airfoil geometries and flow conditions at high Reynolds numbers. Three types of bumps, the suction-side bump, pressure-side bump, and both-side bumps, are studied. The results show that all types of bumps are able to reduce far-field noise up to 10 dB compared to clean airfoils, but their impacts are diff erent in terms of the eff ective frequency range. Also, bumps with four diff erent heights are compared with each other to investigate the eff ect of the height of bumps on noise reduction. It is demonstrated that a bump causes velocity deficit within the boundary layer near the wall. This velocity deficit results in reduced turbulence kinetic energy near the wall, which is responsible for trailing edge noise reduction. Overall, this paper demonstrates the potential of a boundary-layer bump in trailing edge noise reduction and sheds light on the physical mechanism of noise reduction with boundary-layer bumps.

Numerical investigation of noise reduction mechanisms in a bio-inspired airfoil

This paper presents a numerical analysis of an airfoil geometry inspired by the down coat of the night owl. The objective is to understand the mechanisms of airfoil trailing edge noise reduction that has been observed with such designs in previous experiments. The bioinspired geometry consists of an array of finlet “fences” that are applied near the trailing edge of the baseline (NACA 0012) airfoil. Wall-resolved large eddy simulations are performed over the baseline and the bioinspired airfoil geometries and the aeroacoustic performance of the two geometries are contrasted. Both models are simulated at chord-based Reynolds number Rec = 5 × 105, flow Mach number, M∞ = 0.2, and angle of attack, α = 0°. Unsteady surface pressure spectra near the airfoil trailing edge show large reductions at high frequencies but an increase in low frequencies with the bioinspired airfoil, consistent with previous measurements. Farfield noise spectra comparisons between the baseline and the bioinspired airfoil show reductions of up to 10 dB with the fences. The simulations reveal that the fences lift the turbulence eddies away from the airfoil trailing (scattering) edge hence reducing the scattering efficiency. These findings suggest that one of the mechanisms of noise reduction is the increased source-scattering edge separation distance. Two-point correlations show that the fences reduce the spanwise coherence at low frequencies for separation distances greater than a fence pitch. Reduction in spanwise coherence is another potential mechanism of farfield noise reduction at low frequencies.

CT image denoising using NLM and its method noise thresholding

Computed Tomography (CT) is one of the major tools to identify diagnose in medical science. The quality of CT images is dependent of X-ray amount. If X-ray dose is higher, the quality of CT image is better but it may generate bed impact to the patients. Low dose CT images are noisy due to some major reasons such as statistical uncertainty in all physical measurements. If noise can be reduced or removed from low dose CT images, then quality of low dose CT images can be improved without increasing dose. Hence in this paper, a method is proposed in which Non-local means (NLM) filter and wavelet packet based thresholding are processed. For better edge preservation and noise reduction, method noise concept is used. The results of proposed method is analyzed and also compared with some existing methods. From comparative result analysis, it was observed that performance of the proposed scheme is superior to the existing methods in terms of visual quality, Image Quality Index (IQI), PSNR and Entropy Difference (ED).

Segmentation of the lumen and media‐adventitial borders in intravascular ultrasound images using a geometric deformable model

This study presents a geometric deformable model-based segmentation approach to segmentation of the intima and media-adventitial (MA) borders in sequential intravascular ultrasound (IVUS) images. The initial estimation of the vessel borders was done manually only for the first frame of each sequence. After the border initialisation, pre-processing including edge preservation, noise reduction, and dead zone preservation was successively performed on each IVUS frame. To improve segmentation performance, the image masks were determined preliminarily by local binary pattern-based mask initialisation. Then, the inner and outer borders were approximated using a modified distance regularised level set evolution model. The results showed superior performance of the suggested approach for estimating intima and MA layers from the IVUS images. The corresponding correlation coefficients of area, vessel perimeter, maximum vessel diameter, and maximum lumen diameter were r = 0.782, r = 0.716, r = 0.956, and r = 0.874 for the 20 MHz images, respectively, and r = 0.990, r = 0.995, r = 0.989, and r = 0.996 for the 45 MHz images, respectively. In addition, linear regression analysis indicated that the manual segmentation had significantly high similarity at r > 0.967 and r > 0.993 for 20 and 45 MHz images, respectively.

Multi-Tracer Guided PET Image Reconstruction.

Multi-tracer positron emission tomography (PET) has the potential to enhance PET imaging by providing complementary information from different physiological processes. However, one or more of the images may present high levels of noise. Guided image reconstruction methods transfer information from a guide image into the PET image reconstruction to encourage edge-preserving noise reduction. In this work we aim to reduce noise in poorer quality PET datasets via guidance from higher quality ones by using a weighted quadratic penalty approach. In particular, we applied this methodology to [18F]fluorodeoxyglucose (FDG) and [11C]methionine imaging of gliomas. 3D simulation studies showed that guiding the reconstruction of methionine datasets using pre-existing FDG images reduced reconstruction errors across the whole-brain (-8%) and within a tumour (-36%) compared to maximum likelihood expectation-maximisation (MLEM). Furthermore, guided reconstruction outperformed a comparable non-local means filter, indicating that regularising during reconstruction is preferable to post-reconstruction approaches. Hyperparameters selected from the 3D simulation study were applied to real data, where it was observed that the proposed FDG-guided methionine reconstruction allows for better edge preservation and noise reduction than standard MLEM. Overall, the results in this work demonstrate that transferring information between datasets in multi-tracer PET studies improves image quality and quantification performance.

Noise Suppression by Discontinuity Indicator Controlled Non-local Means Method

The non-local means (NLM) method and its variances have been proved to be effective for noise suppression. However, the traditional NLM method and its variances cannot guarantee to obtain a global optimum solution owing to a globally fixed bandwidth parameter for the entire image is used when computing similarity weight function. To address this problem, this paper proposes an adaptive NLM method based on a novel discontinuity indicator, which can get a good tradeoff between edge preservation and noise reduction. In our method, a novel discontinuity indicator based on the structure tensor is proposed, which can effectively distinguish edges from noises and smooth regions. Furthermore, the bandwidth parameter is adaptively chosen according to the proposed discontinuity indicator. As a result, the bandwidth parameter depends continuously on the local characteristic of each pixel. Experimental results demonstrate that our proposed method outperforms several mainstream methods.