Uncertainty quantification plays a crucial role in the design, monitoring, and risk assessment of earth dams. To reduce the computational burden, we employ a combination of finite difference method and soft computing ...
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Uncertainty quantification plays a crucial role in the design, monitoring, and risk assessment of earth dams. To reduce the computational burden, we employ a combination of finite difference method and soft computing techniques to investigate material uncertainties in earth dams during the initial impoundment stage. The findings of sensitivity analysis with the Tornado diagram indicate that key material properties such as dry density, elasticity modulus, friction angle, and Poisson's ratio significantly influence the displacements and stress analysis. In our study, we explore four variants of extreme learning machines (ELMs): the standalone ELM, hybridized versions with the improved grey wolf optimizer algorithm, ant colony optimization for continuous domains, and artificial bee colony. These methods are assessed across various training sizes to predict multiple parameters, including horizontal and vertical displacements, stresses, and the factor of safety (FoS). The hybridized ELM with the improved grey wolf optimizer algorithm emerges as the superior choice for most of the response variables. A minimum of 200 numerical simulations is required to establish a stable and accurate meta-model with an average prediction error of less than 3% for responses and the FoS.
A simplified technique for searching for the initial costate values using evolutionary strategies (ES) was presented. A representative low-Earth-orbit (LEO) to geostationary-Earth-orbit (GEO) transfer problem with con...
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A simplified technique for searching for the initial costate values using evolutionary strategies (ES) was presented. A representative low-Earth-orbit (LEO) to geostationary-Earth-orbit (GEO) transfer problem with constant continuous thrust acceleration was examined. The use of ESs for an optimal orbit transfer problem from LEO to GEO was achieved using various searching domain widths. It was concluded that ESs appear to be capable of finding initial sets of adjoint variables, although they do not always find the global solution due to the randomized process in the algorithms.
A compressive nonstationary near-field acoustic holography based on time-domain plane wave superposition method is proposed to precisely reconstruct the instantaneous sound field using the fewer measurement points. In...
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A compressive nonstationary near-field acoustic holography based on time-domain plane wave superposition method is proposed to precisely reconstruct the instantaneous sound field using the fewer measurement points. In the proposed method, by means of an instantaneous propagation kernel, a time-domain convolution superposition formula is established for relating the timevariant pressure of the hologram plane to the pressure time-wavenumber spectra of the virtual source plane. Next, compressed sensing theory and sparse representation framework are introduced into the time-marching solving inverse process of the established formula, and the smoothed l0 norm and revised Newton optimization algorithm are employed to solve the serious cumulative ill-posed problem over time for acquiring the pressure time-wavenumber spectra. The key is to approximately replace the discontinuous l0 norm by using a suitable continuous function, and the revised Newton algorithm is applied to minimize the continuous function for obtaining the optimal solution. Finally, with the aid of a time-domain convolution formula, the solved pressure time-wavenumber spectra are employed to calculate the time-variant pressure on the reconstruction plane. The proposed method not only can evidently suppress the ill-posed problem of time-marching solving inverse process for improving the reconstruction accuracy, but also can greatly reduce the measurement points and microphone number for drastically decreasing the measurement cost on the premise of ensuring the reconstruction accuracy and spatial resolution. A numerical simulation is conducted, and the simulation effects prove that the proposed method can accurately reconstruct the instantaneous sound field with the fewer measurement points in time-space domains. The reconstruction results are also compared to those of time-domain plane wave superposition method with Tikhonov regularization to verify the superiority of the proposed method with fewer measureme
Induction motors are key equipments widely used in modern industries. Fault diagnosis of broken rotor bar (BRB) timely and accurately is very important to ensure the reliable operation of induction motors (IMs). In th...
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Induction motors are key equipments widely used in modern industries. Fault diagnosis of broken rotor bar (BRB) timely and accurately is very important to ensure the reliable operation of induction motors (IMs). In this study, a multivariate relevance vector machine with multiple Gaussian kernels (MKMRVM) and principal component analysis (PCA) are developed to construct a classification model. Then an improved bacterial foraging optimization combining with Levy fight mechanism, named LBFO, is employed to tune the kernel parameters of MKMRVM to obtain the optimal fault diagnosis model. Finally, The LBFO-based MKMRVM classification model is used to identify the diagnosis of BRB of IMs. The performance is assessed based on a comprehensive experiment of fault diagnosis of BRB. The experimental results demonstrate that the proposed method may achieve high diagnosis accuracy for different noise levels of diagnosis signals and is superior to other related fault diagnosis techniques.
Real-time localization and quantitative assessment of hull girder damage are indispensable for subsequent decisions. To deal with the difficulties that ship damages are hard for real-time assessment, this paper propos...
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Real-time localization and quantitative assessment of hull girder damage are indispensable for subsequent decisions. To deal with the difficulties that ship damages are hard for real-time assessment, this paper proposes an indirect damage identification method based on Probabilistic Neural Network (PNN), utilizing the natural frequency changes to indirectly identify the damage. The natural frequency database of the damaged hull girder is created by the transfer matrix method, and the normalization method is applied to optimize the database characteristics. Based on the Particle Swarm optimization algorithm (PSO) and Genetic algorithm (GA), the influence of different parameters of the optimization algorithms on the smooth factor is discussed. On this basis, the best smoothing factor of the PNN is searched to improve the identification accuracy and efficiency. Results show that the optimal results of the two optimization algorithms are close. And the GA owns higher iterative efficiency. The PNN optimized by the optimization algorithms has higher damage identification accuracy. The method proposed in this paper provides a novel approach for the real-time identification of hull girder damage and contributes reference significance for engineering application.
作者:
Wang, LinxiShen, YiYan, ZhiguoTongji Univ
State Key Lab Disaster Reduct Civil Engn 1239 Siping Rd Shanghai 200092 Peoples R China Tongji Univ
Dept Geotech Engn 1239 Siping Rd Shanghai 200092 Peoples R China
Accurate temperature distribution of the tunnel lining under a fire scenario is crucial for conducting reliable thermal-mechanical investigations, as it directly impacts thermal stress and property degradation. In thi...
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Accurate temperature distribution of the tunnel lining under a fire scenario is crucial for conducting reliable thermal-mechanical investigations, as it directly impacts thermal stress and property degradation. In this regard, achieving consistency between simulation and actual response is imperative. However, the precision of most simulated temperature fields is hindered by a phenomenon known as the 'temperature platform', which occurs around the vaporization point of water. To this end, a Condition Fitting Method (CFM) is proposed in this paper. In CFM, optimal parameters are adjusted based on local historical measurements, enabling the acquisition of a detailed temperature field for the entire tunnel structure in real-time or even forward time step. Based on a preliminary segment fire test, the implementation of CFM successfully captures the temporal characteristics of the temperature platform on certain survey points. The results of both the current and forward time steps obtained from CFM demonstrate close agreement with the reference measurements obtained from the fire test, indicating consistency throughout the entire process. The maximum average error of the calculation result on survey points is 50.4 degrees C while the value for prediction result is 65.3 degrees C. For further investigation, a parametric study is conducted to identify the most crucial parameters. Additionally, numerical verification is performed to assess the feasibility of the proposed method and to compare the efficiency of different optimal algorithms. The results indicate that the proposed method has overcome the drawback of conventional simulation method that the temperature deviate from actual values at early stage. This achievement ensures that the proposed method provides a reliable temperature field for further investigations.
SPACE tethers have been suggested for many important applications, such as study of the planetary atmosphere, space construction, energy transmission, space debris capture, and deployment of satellites [1]. The contro...
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In front of the offset, gain, timing, and bandwidth mismatch errors, time-interleaved analog-to-digital convert-ers (TIADCs) are usually calibrated to achieve satisfying performance. In this paper, we propose a new di...
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In front of the offset, gain, timing, and bandwidth mismatch errors, time-interleaved analog-to-digital convert-ers (TIADCs) are usually calibrated to achieve satisfying performance. In this paper, we propose a new digital calibration approach for TIADCs, including the direction-distance search algorithm and multiplier-free gradient descent method. Compared to state-of-the-art multiplication-less techniques, this approach significantly reduces time complexity by minimizing search space dimension, subtracting the number of searches, and varying iteration step size. Notably, no multiplier is needed in the mismatch estimation, resulting in a much lower computational complexity than in previous work. For a 12-bit 4-channel TIADC, simulation results show that the signal-to-noise-and-distortion ratio is improved from 25 dB to 65 dB within the duration of 1600 samples. The proposed calibration circuit is synthesized targeting standard 28-nm technology, occupying the area of 0.014 mm2 and dissipating the power of 19 mW at 2.8 GHz clock frequency.
A networked microgrid (NMG) is a novel cyber-physical system that provides power to urban and rural communities. The benefits of NMG that coupled with hierarchical energy management system (EMS) include increased rene...
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A networked microgrid (NMG) is a novel cyber-physical system that provides power to urban and rural communities. The benefits of NMG that coupled with hierarchical energy management system (EMS) include increased renewable energy utilization, reliability, system efficiency, and flexibility in inter-microgrid (MG) power exchange (PX). Nevertheless, achieving secure and optimal NMG operation would require hierarchical EMS strategies that can manage uncertainties such as renewable generation fluctuations, load variation, energy prices, and flexible bidirectional PX. This paper outlines the NMG concept and various power balance methods. Subsequently, a comprehensive review of hierarchical EMS designs for NMG is presented. Four NMG models are introduced, and a comparison of various EMS strategies based on objectives, constraints, and optimization methods is also elaborated. Additionally, this paper addresses flexible bidirectional power flow between multiple MGs and the utility grid (UG) within three PX scenarios (MG -to -MG, MG-to-UG, and UG-to-MG). The advantages and challenges of hierarchical EMS for NMG with bidirectional power flow are also discussed considering grid stability, economic viability, and environmental impact. Finally, future research directions for enhancing the NMG model for optimal inter-MG PX are established. It highlights the efficient hierarchical EMS strategies and optimization algorithms for more reliable, affordable, and sustainable NMG operation.
Inspired by the online alternating direction multiplier method (OADM), we propose an efficient online quantum state estimation (QSE) algorithm (QSE-OADM) for recovering time-varying quantum states in this paper. Speci...
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Inspired by the online alternating direction multiplier method (OADM), we propose an efficient online quantum state estimation (QSE) algorithm (QSE-OADM) for recovering time-varying quantum states in this paper. Specifically, in QSE-OADM, the density matrix recovery subproblem and measurement noise minimization subproblem are divided and solved separately without running the algorithm iteratively, which makes the proposed method much more efficient than all previous works. In the numerical experiments, for a 4-qubit system, the proposed algorithm can achieve more than 97.57% (fidelity) estimation accuracy after 71 samples, and the average runtime of per estimation is (4.19 +/- 0.41) x 10(-4) seconds, which reveals its superior performance comparing with existing online processing algorithms. (C) 2020 Elsevier B.V. All rights reserved.
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