Wave Analysis Method Research Articles

Perception and analysis of dynamic stiffness of cable-stayed bridges based on wave analysis

The vertical dynamic stiffness of long-span cable-stayed bridges under vehicle loading is a crucial concern due to their susceptibility to sustained vibrations with notable wave effects. This study investigates the dynamics stiffness perception and enhancement mechanisms of cable-stayed bridges based on fast wave analysis method, proposing wave-associated structural concepts (WSC) for designing stiffer cable-stayed bridges under traffic loading. Initially, the wave function characterizing cable-stayed bridge vibrations is introduced into the representation of the dynamic stiffness of cables and beams, and six WSC for enhancing structural dynamic stiffness are proposed. Subsequently, the fast establishment of the core module for wave function computation is achieved through modular construction of the wave propagation matrix. By employing wave decomposition to clarify the decoupling relationships among the wave components, a distributed algorithm is applied for efficient parallel solving of the wave function. Finally, the reliability and superiority of the proposed method are validated. Using wave analysis method, the stiffness enhancement mechanisms based on WSC and the criteria for implementing WSC in cable-stayed bridges are presented. The case study indicates that the structural dynamic stiffness is related to the wave characteristics which are influenced by both excitations and structural parameters. Enabling the rapid transmission of waves to the structural foundation promote uniform energy distribution and amplitude reduction of wave, thereby enhancing the dynamic stiffness. The beam section stiffness contributes to a dual-effect stiffness enhancement in cable-stayed bridges, effectively increasing the wave velocity. An alternative definition of structural dynamic stiffness is provided based on wave propagation.

Morphing control strategy of wide input voltage DR‐LLC converter for vehicle power supply

AbstractElectric vehicles have experienced substantial global growth. However, significant fluctuations in the output voltage of power batteries and abrupt changes in the input voltage of DC–DC converters pose major challenges to their safety and reliability, thereby impeding sustainable development. This paper proposes a frequency‐prediction‐based topology morphing control strategy (FPTMC) for a dual resonant cavity LLC (DR‐LLC) converter. The strategy aims to accommodate a wide range of input voltages while enhancing the reliability of the vehicle's power supply. Firstly, the topology of the DR‐LLC converter is introduced, utilizing a fundamental wave analysis method for modelling purposes. This analysis results in three distinct voltage gain models corresponding to various topology modes, thereby enabling the converter to manage a wide spectrum of input voltages. Then, a geometrically simplified state plane analysis is employed to derive switching frequency models for the three topology modes, facilitating real‐time prediction of the necessary switching frequency during topology transitions. The proposed control strategy, which relies on frequency prediction, effectively mitigates the problem of voltage spikes during these transitions. Finally, both simulation and experimental results validate the accuracy and feasibility of the proposed wide input voltage control strategy for DR‐LLC converters in vehicle power supply systems.

Fano resonance and exceptional point enhanced sensing in a grating coupled heterostructure

Fano resonance line shape performs ultrasensitive sensing characteristics as its ultrahigh quality factor. Here, we theoretically investigate the sensitivity and figure of merit (FOM) of a novel, to our knowledge, multilayered heterostructure as a sensor. The heterostructure is non-Hermitian and composed of one layer of gold grating, multilayer polyethylene, and polymethyl methacrylate. The rigorous coupled wave analysis method (RCWA) is used to investigate the reflection characteristics of the structure. Interference between the “dark mode,” excited by the grating, and the “bright mode,” excited by the central layers, produces Fano resonance in the forward reflection spectra. Adjustment on the structure parameters can reduce the valley value of the Fano peak to zero, giving rise to scattering exceptional points (EPs). At the wavelength of the EP, the ambient temperature and mechanical stress fluctuations will lift the reflection, available for sensing signal. The sensitivity is higher than that of the structure without Fano peaks and EPs. Moreover, we use the spectral shift for refractive index sensing with a FOM exceeding 200RIU−1.

Effects of foundation conditions on failure modes of jacket type offshore platforms using incremental irregular wave dynamic analysis

Quantitative assessment of environmental conditions and their loading effects is crucial for the optimal design of marine structures, especially offshore platforms subject to extreme environmental conditions. Wave load, particularly irregular wave load, significantly influences the structural response and ultimate strength of jacket-type offshore platforms (JTOPs) throughout their operational life. The dynamic nature of these irregular wave loads necessitates the use of advanced time history analysis to accurately capture their impact. This study aims to enhance the understanding of how foundation conditions impact failure modes and the structural response of JTOPs through an innovative incremental irregular wave dynamic analysis procedure. By focusing on an existing steel jacket-type platform in the Persian Gulf, this research evaluates six models with varying soil profiles and pile conditions to assess their effects on structural performance. The application of incremental irregular wave dynamic analysis provides a more precise and realistic modeling of wave impacts compared to traditional methods. The findings demonstrate that stronger soil profiles and improved pile conditions significantly enhance structural integrity, particularly under extreme loading conditions. Specifically, optimizing pile configurations is critical for enabling the structure to endure larger waves, whereas variations in the yield stress of steel material have a lesser impact on the platform's response. Additionally, the dynamic results are compared with pushover analysis, which serves as a benchmark to evaluate the accuracy and effectiveness of the pushover analysis compared to incremental irregular wave analysis method used in this study.

Degenerate bound states in the continuum in a grating waveguide: Method of infinite-grating eigenmodes vs numerical Rigorous Coupled Wave Analysis (RCWA)

Degenerate bound states in the continuum in a grating waveguide: Method of infinite-grating eigenmodes vs numerical Rigorous Coupled Wave Analysis (RCWA)

Near-surface Imaging Based on Cross-coherence Method with High-Speed-Train-Induced Vibrations

Abstract High-speed trains (HST) generate seismic waves that can serve as a powerful ambient noise source for near-surface imaging. To image the S-wave velocity of the near-surface using the HST seismic signals, we apply the seismic interferometry and compare the effects of two interferometry techniques: cross-correlation and cross-coherence. After processing the measured data, we recovered the Rayleigh wave data in the 1∼5Hz range from the original HST seismic data. The comparison shows that the cross-coherence technique produces surface wave data with a higher signal-to-noise ratio. We then process the obtained virtual shot gathers using the multi-channel surface wave analysis (MASW) method and invert them to obtain the S-wave velocity structure of the subsurface.

Arterial stiffness for predicting major adverse cardiovascular events in post-infarcted patients

Abstract Introduction According to recent 2021 ESC prevention guidelines arterial stiffness (aortic pulse wave velocity –PWV, augmentation index - Aix) predicts future major adverse cardiovascular events (MACE). Both parameters have a prognostic relevance in different patient population (hypertension, diabetes, chronic kidney disease), however in post-infarcted, very high cardiovascular risk population the exact prognostic value for PWV and Aix needs to be clarify. Purpose We evaluated PWV and Aix cut-off values for MACE prediction and validated the prognostic relevance of high stiffness parameters in post-infarcted patients. Methods Oscillometric based pulse wave analysis method (Arteriograph) was applied for calculating arterial stiffness. We aimed to evaluate PWV and Aix cut-off values for predicting MACE (comprising all-cause death, non-fatal myocardial infarction, ischemic stroke, hospitalization for heart failure and coronary revascularization) in post-infarcted, very high cardiovascular risk patient population. 114 patients (89 male, average age: 62,5±10,5 years) were investigated in this long term, median 16,2 (IQR: 6,5-17,4) years follow-up study. Results Strong, significant correlation was found between PWV and Aix values (Spearman rho: 0,648, p<0,001). Totally 140 MACE events occurred during the 16,2 years follow-up period. Optimized PWV and Aix cut-off values for MACE prediction were calculated (PWV: 9,84 m/s, AUC: 0,754 (95% CI: 0,66-0,85), p<0,001; Aix: 34,8 %, AUC: 0,67 (95% CI: 0,57-0,77), p<0,05) by ROC analysis (Figure 1.). Kaplan-Meier analysis in both parameters showed a significantly lower event-free survival in case of high PWV and Aix values (p<0,05; Figure 2.). Multivariate Cox regression analysis revealed PWV and Aix as an independent predictor of MACE (PWV HR: 1,32 (95% CI: 1,15-1,53), p<0,001; Aix HR:1,04 (95% CI: 1,01-1,08), p<0,05). Conclusions Arterial stiffness, particularly elevated PWV predicts MACE in post-infarcted, very high cardiovascular risk patient population. All these findings emphasize the clinical relevance for the future measurement of arterial stiffness might contribute to improve individual risk stratification in patients after myocardial infarction.ROC analysis for the prediction of MACEKaplan-Meier curves for MACE

Pilot study for non-invasive diabetes detection through classification of photoplethysmography signals using convolutional neural networks

Diabetes is a chronic disorder affecting vascular health, often altering pulse wave characteristics. Traditional pulse wave analysis (PWA) methods face challenges such as variability and complexity of signals. This study aims to overcome these limitations by leveraging deep learning models for more accurate and efficient classification. The methodology used in this study involves four key steps: data collection, data preprocessing, Convolutional Neural Network (CNN) model development, and model evaluation. Primary data were collected using a multipara patient monitor, including finger photoplethysmography (PPG) signals, blood pressure, mean arterial pressure, oxygen saturation, and pulse rate. Single pulse wave cycles from 60 healthy individuals and 60 patients with type 2 diabetes underwent preprocessing. The CNN model was trained using 50 PPG images from each group and achieved a training accuracy of 92%. The prediction capability of the model was evaluated using 20 unseen images, comprising 10 healthy and 10 diabetes PPG images. It attained a 90% overall test accuracy in distinguishing between PPG images of individuals with diabetes and those who are healthy. These findings suggest that CNN-based analysis of PPG signals provides a precise, non-invasive tool for diabetes screening. To further enhance accuracy, future studies should focus on increasing the dataset size and performing hyperparameter tuning to optimize the CNN model.

Multilayer Metamaterials with Vertical Cavities for High-Efficiency Transmittance with Metallic Components in the Visible Spectrum

Metasurfaces are opening promising flexibilities to reshape the wavefront of electromagnetic waves. Notable optical phenomena are observed with the tailored surface plasmon, which is excited by metallic components in the visible spectrum. However, metamaterial or metasurface devices utilizing metallic materials encounter the challenge of low transmission efficiency, particularly within the visible spectrum. This study proposes a multilayer design strategy to enhance their transmission efficiency. By incorporating additional metal layers for improvements in the transmission efficiency and dielectric layers as spacers, cavities are formed along the propagation direction, enabling the modulation of transmittance and reflection through a process mimicking destructive interference. An analytical model simplified with the assumption of deep-subwavelength-thick metal layers is proposed to predict the structural parameters with optimized transmittance. Numerical studies employing the rigorous coupled wave analysis method confirmed that the additional metal layers significantly improve the transmittance. The introduction of the extra metal and dielectric layers enhances the transmission efficiency in specific spectral regions, maintaining a controllable passband and transmittance. The results indicate that the precise control over the layers’ thicknesses facilitates the modulation of peak-to-valley ratios and the creation of comb-like filters, which can be further refined through controlled random variation in the thickness. Furthermore, when the thickness of the silver layer followed an arithmetic sequence, a multilayer structure with a transmittance of approximately 80% covering the entire visible spectrum could be achieved. Significantly, the polarization extinction ratio and the phase delay of the incident beams could still be modulated by adjusting the geometrical structure and parameters of the multilayer metamaterial for diversified functionalities.

Research on Cascaded On‐Board DC/DC Converter Based on Three‐Phase Interleaved LLC

ABSTRACTThe on‐board DC/DC converter proposed in this research consists of a Buck converter and a three‐phase interleaved LLC resonant converter. This paper analyzes the average current and output current ripple characteristics of the rear‐stage converter in addition to explaining the topology and working principles of the front‐stage Buck converter and the rear‐stage three‐phase interleaved LLC resonant converter. To establish a single‐phase fundamental equivalent circuit for the rear‐stage converter, apply the fundamental wave analysis method, and it is essential for comprehending the impact of relevant system parameters on voltage gain characteristics and resonant operating regions. Conducting research on the two‐stage on‐board DC/DC converter's control strategy involves establishing small‐signal circuit models for both front and rear stage converters, derivation of parameters for double closed‐loop control, and determination of the control strategy employing phase‐shifted current sharing for the rear‐stage converter in cases where significant tolerance exists in resonant components. The simulation for a two‐stage on‐board DC/DC converter results indicates that under various conditions of resonant component tolerance, the converter is capable of achieving balanced phase currents and demonstrates minimal output current ripple prior to capacitor filtering. A 1.5‐kW experimental prototype has been fabricated, and the experimental findings indicate that the output voltage remains stable at 13.8 V despite fluctuations in input voltage. The highest efficiency of the prototype is about 96.27%, and the utilization of phase‐shifting current balancing control results in a notable reduction in output current ripple. This provides more evidence that the design of a two‐stage on‐board DC/DC converter is correct.

Research on parameter deviation modelling of dual LCC wireless power transfer system

Abstract In this paper, parameter deviation modelling analysis is performed based on the dual LCC compensation network of wireless power transfer (WPT) system. Firstly, the mutual inductive coupling model of the dual LCC compensation circuit is derived based on the fundamental wave analysis method; secondly, the parameter deviation is introduced into the circuit model for the errors existing in the inductive and capacitive components of the compensation network circuit of the actual wireless charging system, and the relation between the deviation and the amplitude of the branch currents, the phase angle and the output characteristics of system are obtained through the establishment of derivation model and the resistive deviation correction term is introduced; finally, the parameter deviation is verified through the simulation. The establishment of parameter deviation model increases the accuracy of the whole circuit model and provides the theoretical basis to reduce the negative influence of parameter deviation on transmission characteristics. The value of parameter deviation can be inverted through the phase angle, thus providing a basis for adjusting the resonant state of the compensation circuit.

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.

A Keyphasor-Free Traveling Waves Analysis Method Based on Blade Tip Timing and Experimental Validation

Abstract Blade Tip Timing (BTT) emerges as a non-intrusive, promising method for assessing blade vibration. Despite its potential, BTT's inherent measurement limitations often result in the under-sampling of individual blade data. Assuming that the bladed-disk assembly vibrates in nodal diameter modes, traveling wave analysis (TWA) can overcome the limitations of under-sampling and identify the nodal diameter modes. Traditional TWA methods rely on a keyphasor or once-per-revolution (OPR) sensor to provide shaft reference signals. However, such a sensor could be damaged during operation or challenging to install due to limited space. In this paper, a new keyphasor-free TWA (KF-TWA) method is introduced, which is capable of measuring the order and nodal diameter of nodal diameter vibrations with as few as two sensors. Theoretical derivations reveal the method's resilience to the steady-state displacement of blades. The feasibility and effectiveness of the KF-TWA method are validated through numerical experiments and compressor tests. In the numerical experiments, blade detuning and nodal diameter vibration responses are simulated, leading to the development of a criterion for identifying nodal diameter vibrations. A compressor test rig, equipped with a 64-keyphasor disk and a sufficient number of circumferentially distributed sensors, is designed to provide blade vibration benchmark. In the experiments, the KF-TWA method successfully identified nodal diameter vibrations with amplitudes as low as 0.014 mm, consistently yielding identical results across multiple sensor pairs, which demonstrates a higher robustness compared to the traditional TWA method.

Experimental Study on Heat Release Performance for Sorption Thermal Battery Based on Wave Analysis Method

Recent developments in water-based open sorption thermal batteries (STBs) have drawn burgeoning attention due to their advantages of high energy storage density and flexible working modes for space heating. One of the main challenges is how to improve heat release performance, e.g., longer stable heat output and effective output temperature. This paper aims to explore the heat release performance of sorption thermal batteries based on wave analysis methods. Zeolite 13X is used for the experimental investigation in terms of the relative humidity of inlet gas, system air velocity, and the length of the reactor. The results demonstrate that the optimal stable temperature output time of the sorption thermal battery experimental rig is 80 min, and heat release per unit volume reaches 115.6 MJ for the most appropriate reactor length. Thus, the optimal heat release time of the STB under the condition of various relative humidity and air velocities is 152 min and 182 min, respectively, and the corresponding stable heat release could reach 161.1 MJ and 136.5 MJ, respectively. Therefore, the heat release performance of STBs could be adjusted by adopting the wave analysis method, which would facilitate the reactor design and system arrangement.

Near-surface velocity inversion and modeling method based on surface waves in petroleum exploration: a case study from Qaidam Basin, China

Surface waves are widely used in the study of underground structures at various scales because of their dispersion characteristics in layered media. Whether in natural seismology or engineering seismology, surface wave analysis methods have matured and developed for their respective fields. However, in oil and gas exploration, many data processors still tend to consider surface waves as noise that needs to be removed. To make more people pay attention to the application of surface waves and widely utilize surface waves carrying the near surface information in oil and gas exploration, this paper takes the data processing of LH site in Qinghai, China as an example to apply surface wave analysis methods to oil and gas exploration. We first preprocess and perform dispersion imaging method on the seismic record in the LH site to obtain frequency-phase velocity spectrum with good resolution and signal-to-noise ratio. Then, utilizing clustering algorithms, it automatically identifies and picks dispersion curves. Finally, through a simultaneous inversion algorithm of velocity and thickness, it inverts the dispersion curves and obtain S-wave velocity profiles in the depth range of 0–200 m. The near surface is divided into four zones based on velocity ranges and depth ranges. Additionally, we apply the surface waves inversion results as constraints to first-arrival tomography and obtain objectively accurate P-wave velocity profiles and Poisson’s ratio profiles. The results indicate that by applying surface wave analysis methods, the near surface velocity information carried by surface waves can be extracted, providing near surface velocity models for static correction and migration. At the same time, compared with the surface wave application in engineering seismology, the scale of oil and gas exploration is larger, so that the data processing of surface waves is particularly important, otherwise it will affect the picking of the dispersion curve and inversion.

Wave Analysis Method for Offshore Wind Power Design Suitable for Ulsan Area

Wave Analysis Method for Offshore Wind Power Design Suitable for Ulsan Area

Influence of Photonics and Plasmonics Effect on Ultrathin Amorphous Silicon Thin Film Solar Cell

Abstract Our recent surge in silicon derived materials has major demand in thin film photovoltaic (PV) modules and enhancing the significant numbers. The rigorous coupled wave analysis method is a simple and fast method also known as developed to determine the light absorption and cell efficiency. The optics of thin film solar cells (amorphous silicon) garnering crucial role in the photovoltaic market. In this work, an ultrathin thin film amorphous silicon solar cell PV performance investigated by periodically textured surfaces at the nanoscale level. This analysis of periodic textured substrate was deriving optimal surface textures. The nanogratings lead to light scattering mechanism with the higher order diffraction angle and enhanced the light absorption of the incidence spectrum. The influence of grating period and height, the collection of the charge carriers increased at various wavelengths from ultraviolet, visible and infrared spectral regions are discussed with the assistance of photonic and plasmonic modes. Finally, nanoscale engineering mechanism the optimized thin film amorphous silicon solar cell yielded the highest current densities (22.6 and 23.8 mA/cm2) in both polarization modes.

Angular uniformity improvement of diffractive waveguide display based on region geometry optimization.

Augmented reality (AR) near-eye displays have significantly progressed due to advances in nanostructure fabrication. However, for diffractive waveguide AR displays requiring exit pupil expansion, the angular uniformity of each exit pupil position still needs to improve. In this paper, an angular uniformity improvement method based on region geometry optimization is proposed. This optimization method essentially introduces the interaction number of the light with the grating as one of the variables to manipulate the energy distribution. This distribution is obtained by the rigorous coupled wave analysis (RCWA) method and ray tracing process and is further optimized by a multi-objective genetic algorithm. A model is built, and the feasibility of the proposed method is verified. The diffractive waveguide system has a 10m m×10m m exit pupil size at the eye relief of 25mm and a field of view (FOV) of 21∘×12∘. After the optimization, the overall optical efficiency of the central field and the angular uniformity at the center exit pupil position increased from 0.9% and 66% to 3.1% and 80%, respectively.

Method of automated extracting dispersion curves based on time-frequency distribution of seismic data

This paper discusses examples of testing a new implementation of the method of multi-channel surface wave analysis on synthetic data computed for elastic media with complex boundary geometry. The new implementation of the method includes developed algorithms for noise-resistant spectral analysis based on time-frequency domain filtering of seismograms and inversion of dispersion curves of phase velocities based on determination of ranges of possible transverse wave velocity models and application of artificial neural networks. Based on the results of synthetic data processing, the accuracy, lateral resolution limitations and applicability limits of the method under consideration are evaluated.

Mathematical Analysis on Dispersion Relation of Rayleigh Wave for an Initially Stressed Magneto-Poroelastic Material with Corrugated and Impedance Boundary

This study showcases the Mathematical modelling of elastic surface waves and the analysis of dispersion relations of Rayleigh-type of wave in an initially stressed homogeneous porous magneto-elastic material having corrugated and impedance boundary exhibitions. Adoption of the classical harmonic method of wave analysis, non-dimensionalization of the resulting equations of motion, and corrugated-impedance boundary conditions produced by the modeled problem are also captured. The dispersion equation was analytically and graphically presented. Effects of the contributing physical quantities, such as impedance and corrugated boundary parameters, on Rayleigh waves for the chosen material are analyzed. The magnetic field’s influences and the wavenumber associated with the corrugated boundary surfaces on the material increase the dispersion relations of the Rayleigh wave profile on the material. In addition, we noted that the dispersion relations of the wave increases for increasing phase velocity and some parameters of voids. Also, a void parameter triggered a decrease on the dispersion profile of the Rayleigh wave when increased while noting some uniform exhibitions from other voids coefficients. This work holds the potential to provide more insights into studies involving displacement distributions in earthquake sciences, stress-strain analysis in Structural Engineering materials, among others. Received: 17 October 2023 | Revised: 14 December 2023 | Accepted: 28 December 2023 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Augustine Igwebuike Anya: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration; Ugochukwu David Uche: Methodology, Software, Validation, Formal analysis, Investigation, Resources, Writing - original draft, Writing - review & editing, Visualization; Christian Nwachioma: Methodology, Software, Validation, Investigation, Resources, Writing - original draft, Writing - review & editing, Visualization.