Transfer Function Method Research Articles

Mesh registration-based boundary element method of head-related transfer function: unification of hair impedance boundary conditions

In the calculation of Head-Related Transfer Functions (HRTFs) using the Boundary Element Method (BEM), the head surface of a subject needs to be discretized into boundary elements with specific impedance. To simplify HRTF calculation, a method for coupling Mesh Registration and BEM (MR-BEM) is proposed in this work, which means that a template mesh for calculation is established to register and generate the calculation mesh of a new head model, to replace the tedious operations of boundary conditions configuration. To validate the proposed method, the widely-used KEMAR artificial head model was adopted to compare the HRTFs of two groups of calculation meshes manually assigned and automatically registered impedance boundary conditions, respectively. Based on the inherent similarities in head shape and hair regions across individuals, the non-rigid impedance was set only for the hair region. Although the reflections from the non-rigid impedance of hair and clothes were shielded by pinnae in practice, this work just aims to validate the feasibility of the MR-BEM, which is significant for the simplification of BEM-based HRTF calculation.

Robotic arm, 3D vision and geometric matching for an efficient implementation of inverse Patch Transfer Function method

The inverse patch transfer function method was developed to reconstruct the acoustic fields (velocity, pressure, intensity) at the surface of a vibrating source with a complex geometry using the concept of a virtual acoustic domain. This method can be used to manage sources with complex shapes in a non-anechoic acoustic environment, even in the presence of masking objects. However, this method is quite demanding experimentally as it requires a large number of measurement positions with good spatial positioning accuracy. This article presents a dedicated experimental platform developed to simplify and automate the entire measurement process. First, a 3D camera placed on a robotic arm constructs a point cloud characterising the source and its environment. Using a geometric matching algorithm, the CAD of the object under test is detected in the cloud of points, enabling the different coordinate systems (CAD, robot and physical part) to be matched. Secondly, the measurement points required to apply iPTF can be defined directly in the CAD and reproduced in near-real time on the test rig, regardless of the type of antenna used, providing an efficient means of applying iPTF and opening the way to many advanced applications.

In silico data-based comparison of the accuracy and error source of various methods for noninvasively estimating central aortic blood pressure

Background and objectivesThe higher clinical significance of central aortic blood pressure (CABP) compared to peripheral blood pressures has been extensively demonstrated. Accordingly, many methods for noninvasively estimating CABP have been proposed. However, there still lacks a systematic comparison of existing methods, especially in terms of how they differ in the ability to tolerate individual differences or measurement errors. The present study was designed to address this gap. MethodsA large-scale ‘virtual subject’ dataset (n = 600) was created using a computational model of the cardiovascular system, and applied to examine several classical CABP estimation methods, including the direct method, generalized transfer function (GTF) method, n-point moving average (NPMA) method, second systolic pressure of periphery (SBP2) method, physical model-based wave analysis (MBWA) method, and suprasystolic cuff-based waveform reconstruction (SCWR) method. The errors of CABP estimation were analyzed and compared among methods with respect to the magnitude/distribution, correlations with physiological/hemodynamic factors, and sensitivities to noninvasive measurement errors. ResultsThe errors of CABP estimation exhibited evident inter-method differences in terms of the mean and standard deviation (SD). Relatively, the estimation errors of the methods adopting pre-trained algorithms (i.e., the GTF and SCWR methods) were overall smaller and less sensitive to variations in physiological/hemodynamic conditions and random errors in noninvasive measurement of brachial arterial blood pressure (used for calibrating peripheral pulse wave). The performances of all the methods worsened following the introduction of random errors to peripheral pulse wave (used for deriving CABP), as characterized by the enlarged SD and/or increased mean of the estimation errors. Notably, the GTF and SCWR methods did not exhibit a better capability of tolerating pulse wave errors in comparison with other methods. ConclusionsClassical noninvasive methods for estimating CABP were found to differ considerably in both the accuracy and error source, which provided theoretical evidence for understanding the specific advantages and disadvantages of each method. Knowledge about the method-specific error source and sensitivities of errors to different physiological/hemodynamic factors may contribute as theoretical references for interpreting clinical observations and exploring factors underlying large estimation errors, or provide guidance for optimizing existing methods or developing new methods.

Analytical modeling of piezoelectric meta-beams with unidirectional circuit for broadband vibration attenuation

Broadband vibration attenuation is a challenging task in engineering since it is difficult to achieve low-frequency and broadband vibration control simultaneously. To solve this problem, this paper designs a piezoelectric meta-beam with unidirectional electric circuits, exhibiting promising broadband attenuation capabilities. An analytical model in a closed form for achieving the solution of unidirectional vibration transmission of the designed meta-beam is developed based on the state-space transfer function method. The method can analyze the forward and backward vibration transmission of the piezoelectric meta-beam in a unified manner, providing reliable dynamics solutions of the beam. The analytical results indicate that the meta-beam effectively reduces the unidirectional vibration across a broad low-frequency range, which is also verified by the solutions obtained from finite element analyses. The designed meta-beam and the proposed analytical method facilitate a comprehensive investigation into the distinctive unidirectional transmission behavior and superb broadband vibration attenuation performance.

Multi-model transfer function approach tuned by PSO for predicting stock market implied volatility explained by uncertainty indexes

This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical threats to the CBOE Volatility Index (VIX). In this study, the relationship between the various uncertainty metrics throughout the period 2012—2022, using a multi-model transfer function technique optimized by particle swarm optimization (PSO) is estimated. Furthermore, we utilize PSO for parameter optimization within the multi-model framework, improving model performance and convergence speed. According to empirical findings, the CBOE Volatility Index reacts nonlinearly to the uncertainty indices. Specifically, the conclusions of the performance metrics show that the OVX index (MAPE: 4.1559%; RMSE: 1.0476% and W: 96.74%) outperforms the geopolitical risk index, the Bloomberg energy index, and the economic policy uncertainty index in predicting the volatility of the US equities market. Although individual models have generated respectful performance, results from the aggregate simulation show that when all predictors are combined, they simultaneously provide better performance indicators (MAVE: 2.7511 %; RMSE: 0.7361%; R2: 98.93%) than when they are estimated separately. In addition, results provide evidence that, when considering non-linear patterns in the data, the multi-model transfer function technique calibrated using PSO demonstrates its outperformance over autoregressive baseline models, traditional econometric models, and deep learning techniques. The effectiveness and accuracy of the multi-model transfer function method tuned by PSO as a forecasting tool are confirmed by the convergence analysis of the cost function. Our methodology innovates by employing a multi-model transfer function technique, which captures the complex and nonlinear relationships between uncertainty indicators and the VIX more comprehensively than traditional single-model approaches. These results are important for traders in terms of hedging as well as portfolio diversification by investing in defensive equities and for policymakers in terms of reliability and preciseness of volatility forecasts.

Effect of Perforated Aluminum on Calotropis Gigantea Fiber Material’s Ability to Absorption Sound

Plants fibers such as Calotropis gigantea (CG) are very suitable as noise reduction material. Therefore, this research aims to determine the sound absorption coefficient of CG in the 20 mm test sample and the effect of the perforated aluminum layer on its ability. It was carried out using a test sample made with a thickness of 20 mm and 100 mm in diameter. The thickness of aluminum was 0.3 mm with hole diameters of 1 mm, 1.5 mm, and 2.5 mm. During the experiment, every sample was heated and pressed in a mold for 10 minutes at 200oC. The test equipment used is a Bruel Kjaer Type 4206 impedance tube with 100 mm in diameter. The sample was tested using the transfer function method ISO 10534-2:1998 at a frequency of 1/1 octave. The results indicated that the uncoated sample absorbed noise α = 0.01-0.07 (1-7)% higher than the sample coated with perforated aluminum. This showed that the Noise Reduction Coefficient (NRC) without aluminum coating can reduce noise by 29%, and the measured sample is categorized in class D.

Synchronization and stability of a vibrating system with two rigid frames driven by two groups of coaxial rotating exciters

This article explores the synchronization, stability and motion characteristics of the generalized dynamical model with two rigid frames (RFs) driven by two groups (even number) of coaxial rotating exciters. In light of this system’s generalized coordinates, we use Lagrange’s equations to derive the generalized differential equation of motion. The responses of absolute and relative motion of the generalized system are obtained using the transfer function method. The synchronization and stability criteria of multiple exciters are derived using the average method and Hamilton’s theory, respectively. Taking a dynamical model driven by two pairs of exciters as an example, the localized studies of generalized results are carried out. The stable synchronous solutions for phase differences and excitation frequency, the stability ability coefficient curves and the response curves are graphically presented considering the effect of two crucial dimensionless parameters on the stable synchronous states. The simulation results of the specific system are obtained using the fourth-order Runge-Kutta algorithms and compared with the numerical qualitative analysis results to reveal the high consistency between them and clarify the used methods’ effectiveness. The strength of this work stems from its use in the field of high power and large scale self-synchronization vibrating machines.

The impact mechanisms of intermediate water depth on the coupled dynamic responses of large-capacity floating wind turbines

ABSTRACT The currently planned floating wind farms in China mostly have water depths in the intermediate range. Therefore, investigating the impact mechanisms of intermediate water depths on the coupled dynamic responses of floating wind turbines is of significant importance. In comparison to deep water, mooring systems in intermediate water depths are more prone to experiencing catenary shape loss and stiffness. The contribution of difference-frequency effects increases with decreasing water depth, resulting in a more substantial impact on low-frequency responses. The Full Quadratic Transfer Function (QTF) method accurately captures low-frequency responses. Placing clump weights in the bottom section of the mooring line effectively restricts the displacement range of floating turbines while maintaining average fairlead tensions at levels similar to the other two forms. On this basis, focusing on the most optimal mooring system performance, experiments were conducted to validate the coupled dynamic responses of floating wind turbines in intermediate water depths.

Free vibration analysis of closed and open horizontal cylindrical shells utilizing coupled transfer function method and differential transform method

This article aims to analyze the free vibration of closed and open horizontal circular cylindrical shells based on the concept of state-space transformation in conjunction with the differential transform method (DTM). The governing equations of the cylinders were developed based upon Sanders’ thin shell theory. Then, the set of coupled governing differential equations transformed into nine first-order differential equations. Afterwards, the well-established semi-analytical scheme so-called DTM was employed to solve the differential equations. The numerical investigation of the present method was also comprehensively carried out by analyzing some closed and open cylindrical shells with different boundary and compatibility conditions. To ensure the correctness of the results, the outcomes were compared with experimental and other numerical results, especially with the well-known finite element method. Furthermore, some plots of two-dimensional and three-dimensional mode shapes for the first and second axial modes are depicted.

Classification of mental workload with EEG analysis by using effective connectivity and a hybrid model of CNN and LSTM

Estimation of mental workload from electroencephalogram (EEG) signals aims to accurately measure the cognitive demands placed on an individual during multitasking mental activities. By analyzing the brain activity of the subject, we can determine the level of mental effort required to perform a task and optimize the workload to prevent cognitive overload or underload. This information can be used to enhance performance and productivity in various fields such as healthcare, education, and aviation. In this paper, we propose a method that uses EEG and deep neural networks to estimate the mental workload of human subjects during multitasking mental activities. Notably, our proposed method employs subject-independent classification. We use the “STEW” dataset, which consists of two tasks, namely “No task” and “simultaneous capacity (SIMKAP)-based multitasking activity”. We estimate the different workload levels of two tasks using a composite framework consisting of brain connectivity and deep neural networks. After the initial preprocessing of EEG signals, an analysis of the relationships between the 14 EEG channels is conducted to evaluate effective brain connectivity. This assessment illustrates the information flow between various brain regions, utilizing the direct Directed Transfer Function (dDTF) method. Then, we propose a deep hybrid model based on pre-trained Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) for the classification of workload levels. The accuracy of the proposed deep model achieved 83.12% according to the subject-independent leave-subject-out (LSO) approach. The pre-trained CNN + LSTM approaches to EEG data have been found to be an accurate method for assessing the mental workload.

Experimental Study of the Absorption Coefficient of Acoustic Insulators for Undergraduate University Students

Objective: This study investigates the techniques for measuring the acoustic absorption coefficient that use an impedance tube, to evaluate their use by students of scientific-technical degrees. Theoretical Framework: This topic presents the concept of absorption coefficient and how it is obtained using impedance tubes. Method: The absorption coefficient of an acoustic insulator is measured as a function of frequency, thickness and density, with an experimental system that uses the transfer function method in an impedance tube. Results and Discussion: The results reveal that the absorption coefficient varies with frequency, being lower at low frequencies. An increase in thickness and/or density produces better acoustic absorption performance. The results are compared with others obtained with an experimental system that uses the standing wave method in an impedance tube. The agreement between the two methods is quite good. Research Implications: The advantages and disadvantages of the two methods are discussed, and their use by students of scientific-technical degrees is assessed. It is recommended to use the transfer function method when students work more autonomously, for example, in final degree projects. Originality/Value: This work offers teachers information related to the experimental study of the acoustic absorption coefficient, which allows them to choose the most appropriate method for each student based on their ability to work autonomously and their knowledge.

Experimental and numerical evaluation of the influence of voids on sound absorption behaviors of 3D printed continuous flax fiber reinforced PLA composites

This study aims to quantitatively analyze the effects of voids on sound absorption properties of 3D printed continuous flax fiber reinforced PLA composites (CFFRCs). Three kinds of flax yarns with different linear density were employed to prepare CFFRCs via 3D printing technology. The sound absorption performances of these composites were measured using the impedance tube based on the two-microphone transfer function method. The microstructure morphologies including cross-sections of flax yarns, voids shape and distributions of the composites were observed via ultra-depth microscope and micro-computed tomography to reconstruct the exact structures in simulation. Mercury intrusion porosimetry was applied to measure the voids dimensions of CFFRCs. The influence of voids on sound absorption mechanisms of CFFRCs were revealed based on thermoviscous acoustics theory by conducting the simulation in COMSOL software. The experimental results demonstrated that CFFRCs exhibited excellent sound absorption coefficients (close to 1) within the frequency range of 150–350 Hz and 350–550 Hz, resulting from the voids inside and between the flax yarns respectively. With the increase of linear density (diameter of the yarn), the contents of voids inside and between the flax yarns both increased. The dimensions of voids inside the flax yarns improved while those between flax yarns remained unchanged. The existence of the voids between the flax yarns resulted in a decrease in the sound absorption coefficient of CFFRCs, while more voids inside flax yarns led to the increase of the sound absorption frequency. Numerical results indicated that voids between the flax yarns contributed to a more uniform change in sound speed, reducing sound absorption performance. Whereas, voids inside the flax yarns could improve viscous friction of soundwaves due to narrow structures, enhancing sound absorption capabilities. This study is anticipated to provide a guidance for the design of integration of structure and function of 3D printed CFFRCs.

Mask 3D parameter optimization for improving imaging contrast of plasmonic lithography

Based on plasmonic lithography (PL) technology, and aiming at the special nano-optical effect of metal/dielectric multilayer composites and mask three-dimensional (M3D) effect, a method for optimizing mask parameters is proposed. As a common analytic formula, the optical transfer function method has been introduced to analyze the imaging process. In order to include the M3D effect, FDTD is used to quantitatively calculate the PL imaging results, and the aerial image (AI) intensity and the light intensity contrast of AI in the photoresist layer can be obtained. The simulation results suggest that the imaging resolution and light intensity contrast can be improved by optimizing the M3D parameters such as the sidewall angle, thickness, and material of the mask absorber. For the line space test pattern with critical dimension = 150 nm and pitch = 300 nm, the results indicate that the optimal sidewall angle is 40°, resulting in an increase in the light intensity contrast of 344%. The light intensity contrast with a mask thickness of 70 nm is improved by 11% when compared to a mask thickness of 60 nm. The use of Ta and opaque MoSi on glass as the mask absorber material improves the light intensity contrast to varying degrees compared to the Cr mask.

A physics-informed Bayesian data assimilation approach for real-time drilling tool lateral motion prediction

In this study, a Bayesian data assimilation method that fuses physics with motion sensor data is demonstrated to infer the dynamic states at points of interest on the bottomhole assembly (BHA) with proper uncertainty quantification. A 4.75 inch-LWD (Logging-while-drilling) tool has been used as a use case, where the dynamic states at the formation evaluation sensor can be predicted in real time with the measurements at the motion sensor as the required inputs. This was achieved with a developed transfer function that utilizes unscented Kalman filtering technique. The robustness of the transfer function was evaluated with synthetic data obtained from finite element analysis (FEA) simulations for various BHA configurations and drilling conditions. It was found that the prediction by the transfer function agrees favorably well with the true states of motion at the formation evaluation sensor. Specifically, using the developed transfer function can help reduce the relative errors for the motion trajectories at the formation evaluation sensor by a factor of 3, and can significantly enhance measurement quality risk classification. The developed transfer function method was further assessed with experimental roll test data, which is considered as close to drilling conditions. The prediction by the transfer function was found consistently close to the ground truth in the presence of backward whirl. The developed modeling method can potentially have broader impacts by enabling fit-for-basin virtual V&V (Verification and Validation) to accelerate LWD tool development, or enabling future drilling optimization.

Artificial Neural Network Accuracy Optimization Using Transfer Function Methods on Various Human Gait Walking Environments

A bionic leg with ergonomic functionality can increase the user’s independence. However, an ergonomic bionic leg can be challenged to be developed. One of its challenges is related to functionality, where the bionic leg motor can be rugged to adapt to the user. One of the solutions for the bionic leg challenge is the application of a motor driver controlled by the user’s muscle signal. EMG signal can be utilized as the user’s signal source. The EMG signal is then fed back into the motor device. EMG signals obtained during a natural walking environment can result in smooth and natural movement. This study classifies EMG signals into 8 classes: a controlled walking environment (treadmill walking with various speeds) and a natural walking environment (ground walking, upstairs and downstairs walking). This research aims to optimize the ANN method using transfer function variations. The best method will be used to train EMG-driven motors for future studies related to bionic legs. The best ANN parameter in this research using Levenberg-Marquardt backpropagation as a training algorithm with transfer function pairing of the exponential function: Hyperbolic tangent sigmoid transfer function and SoftMax transfer function with 98.8% accuracy and 0.036 MSE value. The best method from the experiment and ANN classification can be used as a training method for a bionic leg in future research.

Sound Absorption Evaluation and Analysis Of Different Hemp Fiber Types

In recent years, the global conversation surrounding sustainable practices and environmentally friendly alternatives has gained significant momentum. Hemp fiber presents a compelling alternative to conventional sound-absorbing materials, such as fiberglass, foam, and mineral wool. Hemp fiber offers a plethora of positive environmental aspects from mitigating deforestation to reducing carbon emissions. In this study, six different types of hemp fiber samples were tested: Bleached hemp fiber (BHF), Cottonized hemp fiber (CHF), Boiled Cottonized hemp fiber (BCHF), Decorticated well stripped hemp fiber (DWSHF), Decorticated short, not combed hemp fiber (DSNCHF) and Decorticated short hemp fiber with 40% hurds (DSHFH). The sound absorption was measured using the impedance tube, transfer function method in accordance with ISO 10534-2 standard. The hemp fiber samples were changed in thickness of 20, 40, 60 mm and density from 50 to 250 kg/m3 in steps of 50 kg/m3. It has been found that all of hemp fiber types absorbs sounds of medium (600-2000 Hz) and high (2500-5000 Hz) frequencies very well. The sound absorption coefficient reaches up to 0.99 at medium and high frequencies. Absorption peaks occur at frequencies of 1000, 1250, 1600, 2500, 3150, 4000, 5000 Hz, depending on the measured fiber thickness, density, and type of measured fiber. It has been determined that in all cases, increasing the thickness of the hemp fiber sample increases sound absorption at lower frequencies. Sound absorption at lower frequencies also generally increases when using denser fibers, but this also depends on the type of hemp fiber being studied. Peaks in the sound absorption coefficient of 0.96-0.99 were mostly achieved when testing fibers with densities of 50, 100, and 150 kg/m3.

Investigation of Frequency-Dependent Characteristics of Wire Rope under Tension Based on Transfer Function Method

Wire rope is a complex structure made by twisting wires of various sizes in the longitudinal direction. It is used to support or move engineering structures and is subject to various tensions. Dynamic properties are important parameters to evaluate the resistance to bending deformation and vibration reduction of various structures. They are affected by the magnitude of tension. In this study, an experimental method for measuring the frequency-dependent characteristics of wire rope under tension is proposed. The study analyzed flexural wave propagation employing a vibration transfer function. Experimental results showed that the transfer function of wire rope under tension is affected by tension and bending stiffness. The Newton–Raphson method was employed to numerically measure wavenumbers of the wire rope. The bending stiffness and loss factor were determined from the wavenumbers. Changes in the bending stiffness and loss factor as the tension increased were explained by the dynamic behavior of the structure under tension. As the tension increased, the bending stiffness increased, and the loss factor decreased. Hysteresis analysis indicated that the energy dissipation of wire rope is greater than that of a steel beam due to the friction between the wires. Statistical analysis confirmed a significant correlation between dynamic characteristics and tension in wire rope.

Modeling and Experiment of the Vibro-Acoustic Response of Cylindrical Shells With Internal Substructures

Abstract This study investigates the theoretical and experimental aspects of the vibro-acoustic characteristics of cylindrical shells with internal substructures. On the theoretical side, a hybrid calculation method is proposed, which combines the condensed transfer function method with the direct stiffness method and the precise transfer matrix method. The cylindrical shell with internal substructures is decoupled, and the governing equations for the cylindrical shell substructure and the internal substructure are separately established. Furthermore, the coupling forces between the cylindrical shell substructure and the plate substructure are solved based on the condensed transfer function method. These coupling forces are then incorporated into the overall transfer equation of the cylindrical shell to obtain the vibro-acoustic response of the coupled structure. Compared with the finite element calculation results, the validity of the calculation method in this paper is verified. In terms of experiments, the natural frequency, mode, and vibration acoustic response of the model were tested and compared with the theoretical results, which was in good agreement. The study demonstrates that the proposed hybrid calculation method based on the condensed transfer function is effective in predicting the vibro-acoustic characteristics of cylindrical shells with internal substructures.

Bayesian estimation of dissipation and sound speed in tube measurements using a transfer-function model.

This study discusses acoustic dissipation, which contributes to inaccuracies in impedance tube measurements. To improve the accuracy of these measurements, this paper introduces a transfer function model that integrates diverse dissipation prediction models. Bayesian inference is used to estimate the important parameters included in these models, describing dissipation originating from various mechanisms, sound speed, and microphone positions. By using experimental measurements and considering a hypothetical air layer in front of a rigid termination as the material under test, Bayesian parameter estimation allows a substantial enhancement in characterization accuracy by incorporating the dissipation and sound speed estimates. This approach effectively minimizes residual absorption coefficients attributed to both boundary-layer effects and air medium relaxation. The incorporation of dissipation models leads to a substantial reduction (to 1%) in residual absorption coefficients. Moreover, the use of accurately estimated parameters further enhances the accuracy of actual tube measurements of materials using the two-microphone transfer function method.

Enhancing seismic resilience of nonlinear structures through optimally designed additional mass dampers

Reducing dynamic responses in structures subjected to external excitations like earthquakes and strong winds is crucial for ensuring safety and serviceability. Conventional tuned mass dampers (CTMDs) have limitations in mitigating nonlinear vibrations efficiently. This research proposes the use of additional mass dissipation (AMD) devices to control nonlinear dynamic responses more effectively than CTMDs. The AMD concept involves installing an auxiliary mass–damper system atop the primary structure. An analytical approach is developed to determine the optimal design parameters of AMDs for linear and nonlinear single-degree-of-freedom systems using H2 and H∞ optimization techniques. Transfer function and harmonic balance methods are employed to evaluate the dynamic response reduction capabilities. Compared to optimally designed CTMDs, the proposed H2 and H∞ optimized AMDs demonstrate remarkably superior vibration mitigation achieving up to 77 % and 73.71 % greater reductions in dynamic responses, respectively. The Newmark-beta numerical validation confirms AMDs outperforming CTMDs by 16.06 % in minimizing structural vibrations. The novel AMD concept, coupled with the derived optimal design formulations, offers a highly effective vibration control strategy for both linear and nonlinear structural systems under harmonic and random excitations. This analytical solution paves the way for implementing AMDs in practice to enhance structural safety and longevity against external dynamic loads.