Efficient stimuli-driven global sensitivity analysis of acoustic metamaterials using radial basis function interpolation

Six strategies for defeating the Runge Phenomenon in Gaussian radial basis functions on a finite interval

In this paper, a method to establish a decision criterion to evaluate the quality of small window motors using sound quality (SQ) metrics is suggested. Although the sound level radiated from the motor is relatively small compared to other sounds in a car, the sound from an abnormal motor gives an uncomfortable feeling and the impression of abnormal operation, which can lead to customer complaints. To construct an objective decision criterion, the correlation between the SQ metrics and the subjective decision on the passing or failure of the motor were investigated. Four representative SQ metrics, viz., loudness, sharpness, roughness, and fluctuation strength, were calculated for the collected samples. It was observed that the loudness and roughness of the motor sample group classified as abnormal was higher than those of the normal motors. For a single figure rating for motor quality, an evaluation index for the motor sound was generated by combining the correlated SQ metrics with proper weightings. Evaluation results on the specimens that were not employed in generating the quality evaluation index showed a reasonable agreement with the subjective test at 73%. The suggested quality check method can replace the current subjective decision procedure to identify the faulty motors.

The data interpolation is an essential part of Bidimensional Empirical Mode Decomposition (BEMD) of an image. In the decomposition process, local maxima and minima of the image are extracted at each iteration and then interpolated to form the upper and lower envelopes, respectively. Because of the properties of radial basis function (RBF) interpolators, they are good candidates for use in BEMD. However, only one or two of the RBF interpolators have been utilized for BEMD so far. This paper employs many RBF interpolators for BEMD, compares their performances, and finds out the useful ones for BEMD especially in the image filtering application. We propose to apply the BEMD approach with the adequate interpolation function in the image denoising domain. After that, we combine the BEMD with the DWT to improve the BEMD denoising method. The analysis is done using real images. Simulations are made to focus mainly on the effect of interpolation methods by providing less or negligible control on the other parameters of the BEMD process. The study is believed to work as a guideline in the area of BEMD based real image in the filtering application.

Preserving details while restoring images highly corrupted by impulsive salt and pepper noise remains a challenging problem. The authors proposed an algorithm based on radial basis functions (RBFs) interpolation which estimates the intensities of corrupted pixels by their neighbours. In this algorithm, intensity values of noisy pixels in the corrupted image are first estimated using RBFs. Next, the image is smoothed. The proposed algorithm can effectively remove the highly dense, impulsive salt and pepper noise. Experimental results show the superiority of the proposed algorithm both in noise suppression and details preservation in comparison to the recent similar methods. Extensive simulations show better results measured by peak signal-to-noise ratio and structural similarity index, especially when the image is corrupted by very highly dense impulse noise.

A 2‐D divergence‐free interpolator is presented which is demonstrated to give more realistic values between sparse velocity data than interpolating velocity components independently. The interpolator enforces physical dependence between the velocity components by ensuring mass is conserved. Tests using data for a synthetic eddy show that independent interpolation of components can give unrealistic velocities between widely spaced data. However, divergence‐free interpolation can reproduce the eddy almost as well with sparse data as with dense data. In the synthetic tests the divergence‐free radial basis function (RBF) interpolator performed as well as, or better than, optimal interpolation. A significant advantage of the “greedy fit” RBF interpolator implemented here is the small number of coefficients required to describe the interpolating surface. For large data sets this gives the interpolator a significant computational advantage over techniques, like Optimal Interpolation, which require one coefficient per data point. The RBF's economy of parameters and imposing physics with the divergence‐free constraint makes RBF interpolation of sparse data much more resistant to following the noise. The 2‐D divergence‐free interpolator can be used to interpolate geostrophic velocities or the horizontal transport of high‐frequency flows such as tidal currents. Tests with data from the local dynamics experiment moorings and from moving vessel acoustic Doppler current profiler measurements of tidal flow show the divergence‐free interpolator is better able to reproduce data left out of the interpolation than interpolating velocity components independently.

A meshless numerical scheme combining the operator splitting method (OSM), the radial basis function (RBF) interpolation, and the method of fundamental solutions (MFS) is developed for solving transient nonlinear bioheat problems in two-dimensional (2D) skin tissues. In the numerical scheme, the nonlinearity caused by linear and exponential relationships of temperature-dependent blood perfusion rate (TDBPR) is taken into consideration. In the analysis, the OSM is used first to separate the Laplacian operator and the nonlinear source term, and then the second-order time-stepping schemes are employed for approximating two splitting operators to convert the original governing equation into a linear nonhomogeneous Helmholtz-type governing equation (NHGE) at each time step. Subsequently, the RBF interpolation and the MFS involving the fundamental solution of the Laplace equation are respectively employed to obtain approximated particular and homogeneous solutions of the nonhomogeneous Helmholtz-type governing equation. Finally, the full fields consisting of the particular and homogeneous solutions are enforced to fit the NHGE at interpolation points and the boundary conditions at boundary collocations for determining unknowns at each time step. The proposed method is verified by comparison of other methods. Furthermore, the sensitivity of the coefficients in the cases of a linear and an exponential relationship of TDBPR is investigated to reveal their bioheat effect on the skin tissue.

Today's globalized world depends on civil air transportation, which has been continuously growing over the last decades. Nevertheless, the sustainability of this expansion is a challenge due to environmental problems. Along with greenhouse gas emissions, noise represents a severe hazard for human health, and consequently, noise regulations limit the airport capacity and impose night curfews. Noise is therefore an important design driver for future aircraft, and accurate noise predictions are essential at an early design stage. The total noise emission of an aircraft poses a complex problem, as the distinct components emit noise with different characteristics. High fidelity methods are computationally demanding and time-consuming at an early design phase and less complex solutions, such as semi-empirical methods, are often considered to be more suitable. This thesis focuses on aspects that can improve noise predictions for a new generation of silent aircraft. The concept of noise shielding is present in many future aircraft designs, in which engine noise is partially shielded by the airframe, resulting in a noise reduction on the ground. The noise shielding predictions presented in this work use a theory based on the Kirchhoff integral and the Modified Theory of Physical Optics. This method was extended to consider other noise source radiations patterns than the monopole and to calculate the creeping rays originated by smooth edges. Experiments in the wind tunnel were used to validate these methods and showed that the values of noise shielding are strongly dependent on the source directivity and the shape of the obstacle. Flyover measurements of rear engined aircraft were compared with predictions of noise shielding. The good agreement obtained considering a sharp-edged wing in the predictions was further improved by considering the curvature of the leading edge. A low-noise variation of the Boeing 747-400 is explored using noise shielding predictions, and the optimal engine positions were found to be different when considering the wing leading edge as sharp and with a curvature. This analysis shows how the design of an aircraft is affected by the approximations adopted in the noise shielding predictions, therefore also affecting its performance. For conventional aircraft, the noise emission is commonly estimated using semi-empirical methods. These models are based on experimental data and require detailed input of the aircraft geometry and engine settings. This work uses experimental data to test the limitations of such empirical methods during take-off and landing. The efforts to reduce aircraft noise are only meaningful when resulting in a decrease of annoyance. Traditional metrics such as the Effected Perceived Noise Level are used to assess the annoyance caused by aircraft flyovers but do not provide information about the sound characteristics, such as tonal content and fast and slow amplitude oscillations. Sound quality metrics provide a more complete characterization of a sound and can be combined in psychoacoustics annoyance metrics. Flyover measurements of different aircraft types during take-off and landing were used to investigate the correlation between the sound quality metrics and the aircraft geometry and propulsion system. Strong correlations were found between the sound quality metrics and a number of aircraft characteristics, indicating that psychoacoustic metrics can be used to drive the design process, similarly to existing methods that apply traditional metrics for the same purpose. The variability of the sound quality metrics and psychoacoustic annoyance within the same aircraft type was also investigated. This variability was attributed to the aircraft operating conditions.

Radial basis function based mesh deformation applied to simulation of flow around flapping wings

Comparison between A-weighted sound Pressure Level (SPL) and sound quality metrics on automobile air-conditioning unit is studied in this paper. The result shows sound quality metrics are better because they are unanimous with the subjective feeling of human being. A satisfied sound quality result is obtained under controlling the vibration of the compressor. Some valuable conclusions are obtained through this experiment.

Background: Implicit surface is a kind of surface modeling tool, which is widely used in point cloud reconstruction, deformation and fusion due to its advantages of good smoothness and Boolean operation. The most typical method is the surface reconstruction with Radial Basis Functions (RBF) under normal constraints. RBF has become one of the main methods of point cloud fitting because it has a strong mathematical foundation, an advantage of computation simplicity, and the ability of processing nonuniform points. Objective: Techniques and patents of implicit surface reconstruction interpolation with RBF are surveyed. Theory, algorithm, and application are discussed to provide a comprehensive summary for implicit surface reconstruction in RBF and Hermite Radial Basis Functions (HRBF) interpolation. Methods: RBF implicit surface reconstruction interpolation can be divided into RBF interpolation under the constraints of points and HRBF interpolation under the constraints of points and corresponding normals. Results: A total of 125 articles were reviewed, in which more than 30% were related to RBF in the last decade. The continuity properties and application fields of the popular global supported radial basis functions and compactly supported radial basis functions are analyzed. Different methods of RBF and HRBF implicit surface reconstruction are evaluated, and the challenges of these methods are discussed. Conclusion: In future work, implicit surface reconstruction via RBF and HRBF should be further studied in fitting accuracy, computation speed, and other fundamental problems. In addition, it is a more challenging but valuable research direction to construct a new RBF with both compact support and improved fitting accuracy.

It is hypothesized that sound quality metrics, particularly loudness, sharpness, tonality, impulsiveness, fluctuation strength, and roughness, could all be possible indicators of the reported annoyance to helicopter noise. To test this hypothesis, a psychoacoustic test was conducted in which subjects rated their annoyance levels to synthesized helicopter sounds. After controlling for loudness, a previous analysis using linear regression identified sharpness and tonality as important factors in predicting annoyance, followed by fluctuation strength. The current work focuses on multilevel regression techniques in which the regression slopes and intercepts are assumed to take on normal distributions across subjects. The importance of each metric is evaluated, and the variation of regression parameters among subjects is evaluated using simple models. Then more complete models are investigated, which include the combination of selected metrics and subject-specific effects. While the conclusions from linear regression analysis are affirmed by multilevel analysis, other important effects emerge. In particular, subject-specific intercepts are shown to be more important than subject-specific slopes. In addition, subject-specific slopes for fluctuation strength and sharpness are more important than for tonality. Using a multilevel framework, the relative importance of sound quality metrics is reexamined, and the potential for modeling human annoyance to helicopter noise based on sound quality metrics is explored.

<div class="htmlview paragraph">This paper describes the development of a model for the predicted quality assessment of power seat mechanisms. This model was based on the statistical correlation of objective popular sound quality metrics (and their associated distribution statistics) to a set of subjective results obtained in a previously reported [<span class="xref">1</span>] semantic differentials evaluation experiment. More important then the model itself, the greatest surprises were in the statistical analyses of the subjective response data and the statistical significance and independence of the various commercial software generated sound quality metrics. Step-wise regression was used to identify a sub-set of independent variables that best fit the subjective response data and determine the appropriate model coefficients. This resultant model showed significantly better correlation to this population of subjective response data than other overall sound quality metrics e.g., Loudness, UBA, Pleasantness, etc.</div>

Typically, metrics crucial for assessing sound quality are derived from high-quality audio samples obtained in controlled environments. However, due to the sensitive nature of workplace settings, recording audio samples on-site becomes impractical. Privacy emerges as a significant concern for all when collecting audio samples. Consequently, best practice would require that all analyses must occur either locally on a device used to record audio or in the cloud, utilizing a purely mathematical approach. The paper aims to formulate methodologies for determining psycho-acoustic sound quality metrics without the need to analyze audio data directly. This can be achieved by collecting and analyzing data in small batches. The variation of these metrics over these smaller samples can serve as an indicator of sound quality. Initiating the determination of values for psycho-acoustic sound quality metrics such as loudness (N), sharpness (S), roughness (R) and fluctuation strength (FS) in short and ultra-short batches, followed by monitoring their variation over an extended period (e.g., 5 minutes), provides additional insight into the sound characteristics of the space. Using the obtained psycho-acoustic sound quality metrics, we will explore the perceived annoyance among occupants through indoor soundscape assessments.

Evaluation of meshless radial basis collocation method (RBCM) for heterogeneous conduction and simulation of temperature inside the biological tissues

To select an appropriate standard floor impact source to simulate real floor impacts, objective and subjective evaluations of the floor impact sounds were conducted in a box-frame-type structure with reinforced concrete slab floors. The sounds simulated in the test were those that would result from an adult walking barefoot, children running and jumping (represented by a heavy-weight impact source, such as a bang machine or an impact ball), as well as those of a person walking in high-heels or a lightweight object being dropped (represented by a tapping machine). Similarity tests between human-made impact sounds and standard heavy-weight impact sounds were performed. Sound quality (SQ) metrics were used to predict the results of the similarity tests. These results showed that the impact sound of an impact ball is more similar to a human-made impact sound than the sound of a bang machine. A multiple regression analysis showed that loudness and roughness are significant factors describing the results of similarity judgment among SQ metrics. Much of the data from the standard impact sources, measured in reinforced concrete floors with rigid floor coverings, have been collected. An empirical relationship was established to convert the impact pressure sound level from the bang machine or tapping machine to that from the impact ball. This study indicates that the use of an impact ball is reliable for simulating human impact sounds.