Frequency-domain Model Research Articles

A simple parameter configuration scheme for a simplified dynamic model of pipe-embedded wall

A pipe-embedded wall (PE-wall) can effectively reduce the building load through the water circulation in the embedding pipes. Using renewable energy as an alternative, the water may be produced by solar water heater, or by cooling tower etc. This PE-wall may be used to reduce the building energy consumption, which is beneficial to achieve nearly zero energy building (nZEB) target. In this study, a simple parameter configuration scheme is proposed for the RC simplified dynamic model of the PE-wall. Based on the wall geometry and thermal properties, the scheme can directly determine thermal resistance (R) values and thermal capacitance (C) values for a 5R3C simplified dynamic model. The finite element frequency domain (FEFD) models and time-domain CFD models of three typical (i.e., light-weight, medium-weight and heavy-weight) PE-walls are established as reference. The simplified 5R3C model with parameters determined by the configuration scheme is validated in terms of their thermal responses both in frequency domain and time domain. Under specified dynamic boundaries, mean relative errors of heat flow on the internal wall surface and internal pipe surface are less than 5 %. The comparison results indicate the good accuracy and reliability of the parameter configuration scheme for the RC simplified dynamic model.

A 17-point composite average-derivative optimal method for high-accuracy frequency-domain scalar wave modeling

The frequency-domain finite-difference (FD) technique, especially the average-derivative method (ADM), is widely utilized in wavefield modeling. However, conventional low-order FD techniques are insufficient for high-accuracy demands. Applying high-order FD operator and optimizing their coefficients are effective measures for improving the accuracy of seismic modeling. However, these approaches suffer from the limitations of constant density media and approximant perfectly matched layer (PML). To address this issue, we have developed a composite-ADM 17-point scheme for a scalar-wave equation. This novel scheme is based on the composition of ADM discretizations with different grid intervals, which successfully removes the above limitations and achieves high accuracy. To suppress the numerical dispersion, we take the L∞ norm to construct the objective function, which we minimize using the Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO) algorithms. Numerical analysis indicates that the composite-ADM greatly reduces phase velocity error compared with the traditional-ADM, requiring only 2.44 grid points per wavelength within a 1% phase velocity error. Using numerical examples in homogeneous and complex models, we demonstrate the accuracy and versatility of the composite-ADM 17-point scheme in variable density media with exact PML. Furthermore, we extend this optimal scheme to the case of 2D viscous and 3D scalar-wave equations, making it a more practical and versatile solution.

Quantifying vertical streambed fluxes and streambed thermal properties using heat as a tracer during extreme hydrologic events

As a natural tracer, heat has some remarkable advantages over competing test methods and has become a popular and widely used tool for quantifying streambed fluxes. In recent decades, extreme hydrological events have become intense and frequent, resulting in irregular or complex temperature changes at the stream-streambed interface. During extreme hydrological events, most existing analytical models with periodic changing top boundary conditions are inapplicable. In this study, we present a heat-based analytical model that accounts for the arbitrary top boundary and initial conditions to estimate time-variant vertical streambed fluxes (VSFs) and streambed effective thermal diffusivity using temperature–time series from streambed sediments during extreme hydrologic events. The particle swarm optimization is used to estimate the time-variant VSFs. The Morris global sensitivity analysis method is used to test the impacts of the input parameters on heat transport in the streambed. Results show that the output temperature data is most sensitive to VSFs, followed by the volumetric heat capacity of the streambed, thermal conductivity and thermal dispersivity. The performance of the new model is tested using a numerical model with time-variant VSFs associated with extreme hydraulic events such as hurricanes and dam-controlled river conditions. Results demonstrate that despite oscillations in the estimated VSFs and fluctuations being stronger when the VSFs begin to reverse and at the peak of the VSFs, the new model of this study captures changes in VSFs under extreme hydraulic events. In addition, the frequency domain model, LPMLEn, performs satisfactorily in estimating VSFs in hurricane conditions. Application to field data demonstrates that the temperature distribution can be effectively remodeled based on the estimated VSFs and streambed effective thermal diffusivity. Both the present model and LPMLEn model could be considered as alternatives to the traditional isotope-based method in estimating VSFs during extreme hydrologic events.

A Current Differential Protection Scheme for Distribution Networks with Inverter-Interfaced Distributed Generators Considering Delay Behaviors of Sequence Component Extractors

The high-level proliferation of inverter-interfaced distributed generators (IIDGs) in modern distribution networks (DNs) has changed system topologies and fault current signatures, which compromises the protective relays in DNs. Investigating IIDG fault behaviors-based protection scheme will benefit the grid’s safety and stability. This paper proposes a novel current differential protection (CDP) scheme that considers the delay behaviors of positive- and negative-sequence component extractors for IIDGs in DNs. A frequency-domain analytical model of the fault current for a grid-connected IIDG with the PQ control strategy and a low-voltage ride-through (LVRT) capability is investigated. The dynamic behavior of the IIDGs considering the sequence-component extractor based on the Pade approximation is presented, where the T/4 delay extractor of the IIDGs causes a two-stage behavior in the fault transient process. It is found that a 5 ms error between the measured and actual values after the fault will affect the transient characteristics of the IIDGs. The transient current generated by the IIDGs during grid faults contains a large number of low-order harmonic components within the range of 0–200 Hz, which is significantly different to the current provided by the power grid. Therefore, the proposed CDP scheme uses protective relays at both terminals to obtain the required transient electric quantity using the Prony method. By constructing the frequency-characteristics ratio (FCR) and the exchanging FCR between two terminal relays, the developed protection criteria are implemented. The accuracy of the fault analysis method, whose maximum computational error is below 0.1%, and the feasibility of the proposed protection scheme are demonstrated by using a 10 kV DN in a PSCAD/EMTDC simulation, which can be applied to various fault conditions and traditional DNs without IIDGs.

A frequency domain dynamic simulation method for heat exchangers and thermal systems

Dynamic simulation of thermal systems is crucial for their optimal control but facing the challenge of balancing calculation accuracy and efficiency, where numerically high-efficient and accurate heat exchanger (HX) modeling is a key. Herein, we propose a frequency domain model for HXs' dynamic simulation in the to meet this challenge. The governing equations of HXs are first converted to frequency domain through Fourier transform, and the analytical solution of the converted equations yields the frequency domain HX model in the form of transfer matrix that connects the inlet temperature variations and outlet temperature responses. Furthermore, integrating transfer matrices of HXs into the system's transfer matrix enables a high-efficiency thermal system simulation. Numerical cases of a single HX, a HX network, a district heating network, and a thermodynamic cycle are used to validate the developed method and demonstrate its efficacy by comparing it against finite difference/volume method. Results show that the proposed method could reduce the calculation time by 2–3 orders of magnitude, and the maximum deviation of node temperature is around 1 K. The proposed method can be a powerful tool for the analysis of thermal systems and potentially integrated energy systems.

Combined intra symbol frequency domain averaging channel estimation for polarization division multiplexed coherent optical OFDM/OQAM systems

Intrinsic imaginary interference (IMI) induced by chromatic dispersion (CD) and polarization mode dispersion (PMD) seriously degrades the performance of optical orthogonal frequency division multiplexing offset-quadrature amplitude modulation (O-OFDM/OQAM) systems. Therefore, effective channel estimations are required for such systems to maintain good transmission performance. In the previous publications, both the full loaded (FL) and the half loaded (HL) frequency-domain channel estimation methods for polarization-division-multiplexed (PDM) coherent optical OFDM/OQAM (CO-OFDM/OQAM) systems have been proposed. However, for these frequency-domain methods, the channel frequency-domain responses caused by the correlation of the amplified spontaneous emission (ASE) noise are not considered. In this paper, we systematically discuss the frequency-domain channel transmission model for PDM CO-OFDM/OQAM systems. With the analysis of the correlation of the ASE noise, we propose a combined intra symbol frequency-domain averaging (CISFDA) channel estimation method for PDM OFDM/OQAM systems. Compared with the full-loaded frequency-domain channel estimation (FL-FD) method, the CISFDA method promotes the system robustness against the ASE noise and fiber nonlinear effect significantly. The proposed method is validated by numerical Monte Carlo simulations of the PDM CO-OFDM/OQAM system. Our new algorithm outperforms the FL-FD method in the 36 Gb/s PDM OFDM CO-OFDM/OQAM system, and the transmission distance is improved by 500 km with the bit-error-rate (BER) target at 3.8×10-3.

Spectral modelling approach for crowd-rhythmic activities performed on steel-concrete composite floors

During the last decades, building floors have become sensitive to vibrations caused by human activities, especially when a group of individuals perform rhythmic activities in a coordinated manner. Resulting effects on floor occupants can range from a mere perception, can pass through discomfort and can even go so far to cause panic. The present paper proposes a spectral modelling approach for crowd-rhythmic activities applied on floor structures. The proposed model comprises a frequency domain model for a single person, combined with coordination factors to account for the lack of synchronization between individuals. The identification of this model was based on vibration experiments carried out on a floor specimen specifically designed for that purpose. Two particular types of rhythmic activity were investigated: jumping and skipping, and performed by up to 16 individuals, where realistic coordination stimulus was adopted. Using least-squares identification procedures, the single person load parameters were determined and predicted load models are in good agreement with their measured counterparts. Resulting parameters are dependent on the motion style of each investigated activity. Coordination factors are also derived from crowd forces and present a hyperbolic decrease by crowd size for jumping activities against an exponential decrease for skipping activities. Based on a closed-form expression using the established crowd model, a design-oriented method is proposed for a simplified evaluation of floor response due to crowd-rhythmic activities and verified against floor response measurements. Slight differences were found between measured and numerical responses due to the variabilities either encountered during experiments or resulting from the load identification process.

Optical properties reconstruction in nonhomogeneous participating medium based on an improved sequential quadratic programming

The reconstruction of optical parameters achieves functional imaging by providing characteristics closely related to the physiological state of biological tissues. With considerable research significance, this imaging technology has received increasing attention in the field of medical diagnosis and treatment. However, owing to the limited number of known measurement signals far less than the number of target parameters to be estimated, reconstruction requires a long ill-conditioned process, which is easily polluted by background noise so as to difficulties for achieving high imaging accuracy and efficiency. To conquer these deficiencies, an improved sequential quadratic programming (ISQP) is proposed in this work. In the ISQP, dual constraints of equality and inequality are added in the process of minimizing the objective functional, which avoids the time-consuming forward problem. Moreover, duality method, reduced Hessian matrix, and second-order correction are introduced in the subproblem. In addition, prior information of diagonal contiguous points is introduced to overcome the ill-posedness. The reconstruction performance of ISQP in different modes is discussed in depth. A time-frequency coupling model based on ISQP is constructed subsequently, of which the practical significance is demonstrated in the biological tissue-like medium model. The results show that in the established frequency domain model, ISQP significantly shortens the calculation time of the traditional method and improves the reconstruction quality of absorption parameters. The developed time-frequency coupling method effectively eliminates the influence of the background disturbance, and in the meantime improves the accuracy and efficiency when simultaneously estimating multi-parameters related to optics, with good robustness. The effectiveness of the ISQP combined with hybrid time-frequency model provides new referable ideas and application potential for the development and progress of medical, biology, photonics and other fields.

Hydroelastic analysis of offshore floating photovoltaic based on frequency-domain model

This paper presents a frequency-domain model for analyzing the hydroelastic response and the vulnerable area of floating photovoltaic structures under wave action. The structure is discretized into an array of modules connected by equivalent elastic beams, while the boundary element method is employed to solve the scattering and radiation problems of the modules. The structural stiffness matrix is assembled by employing coordinate transformations and matrix reorganization techniques. The hydrodynamic matrix and the structural stiffness matrix are combined to establish the frequency-domain motion equation for describing the flexibility of the structure. The maximum gradient index is introduced to evaluate the dynamics issues of floating photovoltaic structures. The vulnerable area of the structure is assessed using the equivalent stress based on the von Mises stress theory. The proposed numerical model is validated by comparing the results with benchmark experiment as well as classical numerical model results. With this method, the hydroelastic response of a 300m×300m offshore floating photovoltaic is investigated. The displacement and internal force of the structure under various wave conditions is analyzed. This work can deepen the understanding of the hydrodynamics of floating photovoltaic structures in marine environment.

WECs microarray effect on the coupled dynamic response and power performance of a floating combined wind and wave energy system

With numerous floating wind-wave hybrid system concepts proposed and studied on a large scale, multiple wave energy converters (WECs) are usually integrated in a hybrid system to spread the cost and obtain more power. The internal interactions between WECs and a platform are complex and difficult to assess. The effect of WECs microarray on the performance and interaction of hybrid systems has not been adequately studied. To bridge this gap, the frequency-domain and time-domain modelling considering the effect of WECs microarray is first established using the coupled AQWA-FAST simulation system. On this basis, this work studies the internal connection between the layout of the WECs, and interaction factors for hydrodynamic coupling between WECs microarrays and the platform. The relationship between the WECs microarray and the aerodynamic response of the wind turbine is analysed, as well as the relationship between the microarray layout and the disturbed wave field of the devices. Results show that the WECs outer microarray performs better in terms of pitch motion suppression and power output, while the inner microarray exerts a more positive influence on the dynamic response of the tower.

An experimental investigation on the effect of in-flow distortions of propeller noise

Propellers usually operate in non-uniform flow conditions, leading to significant levels of noise generation due to interaction with the leading edges of the propeller blades. Under these flow conditions, the noise generated can be substantially different from the rotor-alone self-noise generated under uniform mean flow conditions. This paper presents an experimental investigation aimed at studying the far-field noise due to a two-bladed propeller immersed in a controlled non-uniform flow with known characteristics. This paper presents the results of a parametric study with different degrees of flow non-uniformity generated from different geometric obstructions located in the jet nozzle, while maintaining constant thrust. Measurements of the radiated noise show that the incoming mean flow non-uniformities under investigation in this study cause a significant increase in tonal amplitudes of the blade passing frequencies of harmonic orders greater than 2. At the first two blade passing frequencies the tones are dominated by the rotor-alone ‘Gutin-type’ tones resulting from the steady blade loading.The measured noise spectra are compared with predictions from a simple frequency-domain flat plate model. The analytical model will be shown to capture the main features of the interaction tonal noise spectrum and directivity.

A line loss reduction optimization for renewable energy‐based distribution networks using a probabilistic approach

SummaryThe large integration of distributed generation (DG) and electric vehicles (EVs) facilitates daily life and reduces carbon emissions. However, it brings problems such as increased uncertainty and power electronic permeability to the distribution network. In this context, it is important to solve the line loss optimization problem as closely as possible to the real situation. Therefore, this paper solves the line loss optimization problem based on a probabilistic model of three‐phase unbalanced modern power electrical distribution network. Firstly, the paper proposes a frequency domain model of the distribution network and the optimization problem model. Then, to deal with the uncertainty of the system, the point estimation method (PEM) and Monte Carlo Simulation (MCS) are used. Finally, this paper proposes two optimization schemes considering the power quality when single and multiple DGs are integrated. The simulation results demonstrate that the PEM using the Gram–Charlier series expansion of the fourth‐order statistical moments to estimate the probability density function (PDF) is significantly less time consuming than the traditional MCS method while maintaining accuracy. The comparative analysis reveals that under the optimization scheme with single DG integration, the expected value of system line loss and expected line loss rate are reduced from 283.95 kW to 218.96 kW (22.89% reduction) and from 13.44% to 10.68%, respectively. Under the dual DG integrated optimization scheme, the expected value of line losses and expected line loss rate are reduced from 283.95 kW to 208.88 kW (26.4% reduction) and from 13.44% to 10.25%, respectively. However, after taking the uncertainty into account, the operational reliability of the system has been enhanced under different scenarios. In addition, it is found that the optimization approach incorporating multiple DG units can effectively mitigate the system line loss under diverse operational scenarios while enhancing the system's DG integration capability.

A robust poly-reference frequency-domain identification method to extract dynamic properties from vibration data

When performing vibration tests on structural systems, engineers face the challenge of extracting the dynamic properties from the measured data in an accurate and robust manner. Though several methods exist for this purpose, in some circumstances, they fail to provide clear estimates for these properties, particularly when applied to noise-contaminated data. Here we propose a robust and accurate method formulated in frequency-domain modal model for extracting dynamic properties from vibration data. The method is applied to three application examples, namely the vibrations simulated with the aid of a finite element model and the real-life vibration measurements of a platform specimen and of a full-scale concrete heritage court building. Its performance is thereafter assessed by the so-called stabilization diagrams, the relative error between estimated and exact properties, the modal assurance criterion, and by comparing the synthesized frequency functions to their measured counterparts. This assessment shows that the proposed approach tends to provide clearer and more accurate identification results than those from the state-of-the-art identification methods.

Design Optimization of Floating Offshore Wind Turbine Substructure Using Frequency Domain Modelling and Genetic Algorithm

Floating offshore wind turbines are becoming increasingly popular as a promising technology for producing cleaner energy. However, in order to be competitive with fixed offshore wind projects or even onshore wind projects, the costs associated with floating offshore wind turbines must be significantly reduced. To tackle this challenge, this paper presents a comprehensive framework for optimizing the design of floating offshore wind turbine substructures and their components. The innovative open-source frequency-domain dynamic model RAFT is used to take into account the aerodynamic, hydrodynamic and mooring forces that impact the stability and dynamics of the floating system. The numerical model is coupled with an efficient genetic algorithm to minimize the structural mass of the floating platform while maintaining its stability and dynamic performance. The geometrical parametrization of the substructure, the implementation of the numerical model, and the overall optimization process are all thoroughly detailed in this paper, along with preliminary results that demonstrate the potential cost reductions that can be achieved through this framework.

Analysis of a cusped helicon plasma thruster discharge

Experiments and simulations are used to analyze a compact helicon plasma thruster with a cusp in its internal magnetic field. The former rely on a compensated Langmuir probe and a Faraday cup, while the latter employ a hybrid PIC/fluid transport model combined with a frequency-domain electromagnetic field model. Measurements serve to tune the anomalous transport parameters of the model and overall show the same trends as the numerical results, including a secondary peak of electron temperature downstream in the magnetic nozzle, where electron cyclotron resonance conditions for the 13.56 MHz excitation frequency are met. The cusp plays a central role in determining the plasma losses to the walls and the profile of electron temperature, which in turn defines the excitation and ionization losses. While losses to the rear wall are reduced, losses to the lateral wall are increased, which, together with the low production efficiency, limit the performance of the device.

Objective Image Quality Optimization in Augmented Reality Using Spatial Frequency Domain Models.

Augmented reality (AR) blends the digital and physical worlds by overlapping a virtual image onto the see-through physical environment. However, contrast reduction and noise superposition in an AR head-mounted display (HMD) can substantially limit image quality and human perceptual performance in both the digital and physical spaces. To assess image quality in AR, we performed human and model observer studies for various imaging tasks with targets placed in the digital and physical worlds. A target detection model was developed for the complete AR system including the optical see-through. Target detection performance using different observer models developed in the spatial frequency domain was compared with the human observer results. The non-prewhitening model with eye filter and internal noise results closely track human perception performance as measured by the area under the receiver operating characteristic curve (AUC), especially for tasks with high image noise. The AR HMD non-uniformity limits the low-contrast target (less than 0.02) observer performance for low image noise. In augmented reality conditions, the detectability of a target in the physical world is reduced due to the contrast reduction by the overlaid AR display image (AUC less than 0.87 for all the contrast levels evaluated). We propose an image quality optimization scheme to optimize the AR display configurations to match observer detection performance for targets in both the digital and physical worlds. The image quality optimization procedure is validated using both simulation and bench measurements of a chest radiography image with digital and physical targets for various imaging configurations.

Stiffness profile spectral composition & geometry deterioration of railway tracks

This work addresses the contribution of the wavelength composition of the spectrum of the rail support stiffness profile to the expected long-term settlement. To that aim, purely harmonic stiffness variations of different wavelength are studied. The frequency-domain model with a double periodicity level previously developed by the first and last authors is adopted to embed the stiffness profile in one of the periodicity layers. Additional resonance velocities at which the resonance frequency of the track system coincides with the support-passing frequency or its multiples are found. The susceptibility to degradation is assessed both by quantifying the mechanical energy dissipated in the substructure under a moving train axle within one wavelength of the support stiffness variation, and the work performed by the wheel-rail contact force. It is shown that shorter wavelengths and larger standard deviations of varying ballast/subgrade stiffness result in an increasing energy dissipation in the substructure, and increase the work performed by the wheel-rail contact force, therefore leading to a reduced lifetime of the track. The energetic quantities increase for lower mean values of the stiffness profile, confirming the proneness of tracks on soft soils to degradation. The influence of varying stiffness vanishes for wavelengths of approximately 16 times the sleeper span, which is equivalent to a track length of about 10 m. High railpad stiffness values result in increased energy dissipation but the influence is limited. In general, an increasing train velocity amplifies the rate of track degradation, with no stabilizing trend in the high-speed regime (300 km/h).

Multi-center atrial fibrillation electrocardiogram (ECG) classification using Fourier space convolutional neural networks (FD-CNN) and transfer learning

There has been a proliferation of machine learning (ML) electrocardiogram (ECG) classification algorithms reaching >85% accuracy for various cardiac pathologies. Despite the high accuracy at individual institutions, challenges remain when it comes to multi-center deployment. Transfer learning (TL) is a technique in which a model trained for a specific task is repurposed for another related task, in this case ECG ML model trained at one institution is fine-tuned to be utilized to classify ECGs at another institution. Models trained at one institution, however, might not be generalizable for accurate classification when deployed broadly due to differences in type, time, and sampling rate of traditional ECG acquisition. In this study, we evaluate the performance of time domain (TD) and frequency domain (FD) convolutional neural network (CNN) classification models in an inter-institutional scenario leveraging three different publicly available datasets. The larger PTB-XL ECG dataset was used to initially train TD and FD CNN models for atrial fibrillation (AFIB) classification. The models were then tested on two different data sets, Lobachevsky University Electrocardiography Database (LUDB) and Korea University Medical Center database (KURIAS). The FD model was able to retain most of its performance (>0.81 F1-score), whereas TD was highly affected (<0.53 F1-score) by the dataset variations, even with TL applied. The FD CNN showed superior robustness to cross-institutional variability and has potential for widespread application with no compromise to ECG classification performance.

Wavefront coding image reconstruction via physical prior and frequency attention.

Wavefront coding (WFC) is an effective technique for extending the depth-of-field of imaging systems, including optical encoding and digital decoding. We applied physical prior information and frequency domain model to the wavefront decoding, proposing a reconstruction method by a generative model. Specifically, we rebuild the baseline inspired by the transformer and propose three modules, including the point spread function (PSF) attention layer, multi-feature fusion block, and frequency domain self-attention block. These models are used for end-to-end learning to extract PSF feature information, fuse it into the image features, and further re-normalize the image feature information, respectively. To verify the validity, in the encoding part, we use the genetic algorithm to design a phase mask in a large field-of-view fluorescence microscope system to generate the encoded images. And the experimental results after wavefront decoding show that our method effectively reduces noise, artifacts, and blur. Therefore, we provide a deep-learning wavefront decoding model, which improves reconstruction image quality while considering the large depth-of-field (DOF) of a large field-of-view system, with good potential in detecting digital polymerase chain reaction (dPCR) and biological images.

An improved frequency-domain model for the supercritical flow instability analysis in vertical tubes

In a supercritical water reactor, the density wave oscillation (DWO) may occur due to the dramatic changes in the density of the working fluid in the pseudo-critical region. Based on the frequency-domain method, this study proposes an improved model to study DWO. First, the latest partition method is used in this study. Second, in the derivation of the transfer function in the light fluid region, the density change of the fluid is considered. Moreover, the different states of the outlet fluid are handled differently. We use the Nyquist criterion to determine the flow stability and obtain the boundary heat flux (BHF) of different working conditions. After model verification, it is proved that the model accuracy is improved. We analyze the influence of pressure, inlet enthalpy, mass flow rate, inlet throttling coefficient, and tube parameter on the instability boundary. At a certain inlet enthalpy, a minimum BHF of flow instability exists.