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Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ObjectivesWhen assessing the safety of the connectors of a multi-module offshore floating power generation platform, in order to compensate for the inability to carry out the real-time monitoring of the structural stress field across the whole domain due to a limited numbers of sensor, a digital twin method based on a simulation database is proposed that can rapidly predict the platform's stress field. MethodsBy downgrading the three-dimensional physical model of the connectors to a one-dimensional digital model, the stress field data is interpolated and deduced in digital space, thereby achieving the rapid prediction of the structural stress field across the whole domain and its visual display.ResultsThe results show that the simulation model is in good agreement with the test results, with a maximum absolute error of 8.61%; for the interpolation of data under different loading angles, when the interpolation step of the loading angle is 10°, the aver-age absolute error of stress is 1.98%; and for the interpolation of data under different loads, when the interpolation step of the load is 10 t, the average absolute error of stress is 1.28%, achieving the rapid prediction and visualization of the connectors' stress field distribution. Conclusions The digital twin-based model of connectors can provide useful references for the rapid dynamic perception and scientific prediction of the structural strength of offshore floating power generation platforms.

The high-fidelity numerical simulation is the basis for constructing digital twins of reactor cores and other engineering applications. However, the traditional numerical models, such as the finite element model and/or the finite volume model, usually adopt high-resolution grids. The high computation cost makes the traditional high-fidelity models unsuitable for the application of digital twins. Model order reduction is an effective approach to accelerate the simulation whenever a trade-off between computational cost and solution accuracy is a preeminent issue. In this paper, a reduced order model (ROM) which combined both the intrusive and the non-intrusive approaches was constructed for the parameterized thermal-flow problems. The intrusive approach adopted the Galerkin projection method and the non-intrusive approach adopted the radial basis function (RBF) interpolation method. To construct the ROM, some typical numerical solutions were firstly generated by using the finite volume method (also called full-order model, FOM) and then taken as learning samples (also called the snapshots) to generate the reduced bases by the proper orthogonal decomposition (POD) method. After that, the conservation equations of mass, momentum and energy were projected onto the space spanned by the reduced bases. As a result, the number of degrees of freedom is substantially reduced. In terms of the turbulent RANS simulation, the RBF interpolation instead of the Galerkin projection was applied to predict the eddy viscosity in ROM since there exists plenty of turbulent models and projection of those various governing equations would be unfeasible. By this data-driven approach, only the eddy viscosity was treated in the ROM. The parametrization of the Dirichlet boundary conditions was treated by the lift function method, in which a special control function was firstly subtracted from the snapshots of velocity and temperature to yield homogenous field snapshots. After the reduced solution over the inner region was solved by the ROM, the boundary value was patched according to the specified boundary condition. The transient heat transfer behavior of coolant flow in a helical cruciform fuel bundle was tested of which the inlet velocity and temperature were treated as parameters. The results show that this ROM can achieve a speedup of 3-4 orders of magnitude compared to the FOM, and meanwhile the relative errors of the velocity, the pressure and the eddy viscosity field remain less than 10%. However, the prediction of the transient evolution of temperature filed from ROM shows a significant difference with FOM. This may be caused by the modal analysis of transient snapshots, and further investigation would be necessary.

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The cost of obtaining a large amount of flow field information by traditional experiment or CFD is unacceptable,so it is of significance to develop faster forecasting calculation methods.Proper orthogonal decomposition(POD)is used to extract the dominant mode of the tandem flow field.Radial basis function network(RBFN)is used to respond to the coefficients of the POD basis functions to realize the construction of the reduced-order prediction model of the flow field.Then the adaptive sampling method is developed for the reduced order model.The prediction model is verified by the unsteady flow field data of a cascade.It is concluded that the hybrid method can be utilized to accurately predict the aerodynamics parameters and flow field of tandem cascade.Compared with static sampling,the number of samples required for adaptive sampling to achieve the same reconstruction accuracy is reduced by about 25%.

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The time cost is very high by direct fluid-structure interaction method for mistuned bladed disk structures, so aerodynamic loads generally are ignored or treated as small perturbations in traditional flutter analysis. In order to analyze the flutter characteristics of mistuned blade rapidly and accurately, this paper presents an efficient fluid-structure interaction method based on aerodynamic reduced order model. system identification technology and two basic assumptions are used to build the unsteady aerodynamic reduced order model. Coupled the structural equations and the aerodynamic model in the state space, the flutter stability of mistuned bladed disk can be obtained by changing the structural parameters. For the STCF 4 example, the response calculated by this method agrees well with the results obtained by the direct CFD, but the computational efficiency is improved by nearly two orders of magnitude. This method is used to study the stiffness mistuned cascade system, and the stability characteristics of the system are obtained by calculating the eigenvalues of the aeroelastic matrix. The results show that the stiffness mistuning can significantly improve the flutter stability of the system, and also lead to the localization of the mode. The mistuning mode, mistuning amplitude and fluid structure interaction can influence the flutter stability obviously.

A fast method based on the proper orthogonal decomposition(POD) technique for predicting oil and water flow in water-drive reservoir was proposed. The reduced order model of oil and water flow in water-drive reservoir was generated with the POD. An ensemble of 100 samples of pressure and water saturation snapshots in the time range of [0 d, 500 d] with an interval step of 5 d for the 2D water-drive reservoir model was obtained through numerical reservoir simulation, and the PO D was applied to extract a reduced set of POD basis functions from these snapshots. After the injection and production parameters were changed continuously, the obtained POD basis functions combined with the reduced order model were used to predict the new physical fields. The research results show that fast and accurate predictions can be achieved with the proposed POD-based method, for the given example, the prediction errors of pressure and water saturation are less than 1. 2%and 1. 5%, respectively. What’ s more, this POD-based method is 50 times faster in calculation than the traditional numerical reservoir simulation. [ABSTRACT FROM AUTHOR]