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Bayesian optimization is a powerful tool in the kinematic design of bio-inspired flight, where expensive high-fidelity numerical simulations are required. However, the traditional single acquisition strategy cannot adapt to all design problems, which have various input–output characteristics. The hybrid acquisition strategy improves the robustness by utilizing three types of acquisition functions, and each acquisition function is assigned three different balance parameters. The kinematics of a gliding flat plate that oscillates along the spanwise direction has been optimized to enhance the power efficiency by using the Bayesian optimization method. The power factor under the optimal spanwise oscillation is 1.97 times as large as that without spanwise oscillation, which indicates the good capability of the optimization method for bio-inspired locomotion. [ABSTRACT FROM AUTHOR]

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The Cu-filling process in through-silicon via (TSV-Cu) is a key technology for chip stacking and three-dimensional vertical packaging. During this process, defects resulting from chemical–mechanical planarization (CMP) and annealing severely affect the reliability of the chips. Traditional methods of defect characterization are destructive and cumbersome. In this study, a new defect inspection method was developed using Mueller matrix spectroscopic ellipsometry. TSV-Cu with a 3-μm-diameter and 8-μm-deep Cu filling showed three typical types of characteristics: overdishing (defect-OD), protrusion (defect-P), and defect-free. The process dimension for each defect was 13 nm. First, the three typical defects caused by CMP and annealing were investigated. With single-channel deep learning and a Mueller matrix element (MME), the TSV-Cu defect types could be distinguished with an accuracy rate of 99.94%. Next, seven effective MMEs were used as independent channels in the artificial neural network to quantify the height variation in the Cu filling in the z-direction. The accuracy rate was 98.92% after training, and the recognition accuracy reached 1 nm. The proposed approach rapidly and nondestructively evaluates the annealing bonding performance of CMP processes, which can improve the reliability of high-density integration. [ABSTRACT FROM AUTHOR]

Accurate power load forecasting is the key foundation and important premise of urban power system planning. Considering that urban power load demand is closely related to economic development and meteorological conditions, and with the application and promotion of various energy coupling equipment and the promotion of electric energy substitution policy, the relationship between gas load and power load demand is increasing. However, most of the existing load forecasting methods only consider a single economic factor or a single meteorological factor, and fail to combine the coupling and complementarity between loads. Based on this, this paper first analyzes the coupling characteristics between power load and urban economic, meteorological, and gas load with Copula theory; Secondly, the key parameters of the least squares support vector machine (LSSVM) are solved by using the salp swarm algorithm (SSA), and the urban monthly power load forecasting model based on SSA-LSSVM is established; Finally, based on the macroeconomic data, meteorological observation data and monthly electrical load of a city in North China, the prediction model is verified. Through comparison with different prediction scenarios, it is confirmed that the built model can effectively improve the prediction accuracy and has good application effects. [ABSTRACT FROM AUTHOR]

The surface correction to the quadrupole source term of the Ffowcs Williams and Hawkings integral in the frequency domain suffers from the computation of high-order derivatives of Green's function. The far-field approximations to the derivatives of Green's function have been used without derivation and verification in previous work. In this work, we provide the detailed derivations of the far-field approximations to the derivatives of Green's function. The binomial expansions for the derivatives of Green's function and the far-field condition are employed during the derivations to circumvent the difficulties in computing the high-order derivatives. The approximations to the derivatives of Green's function are systemically verified by using the benchmarks two -dimensional convecting vortex and the co-rotating vortex pair. In addition, we provide the derivations of the approximations to the multiple integrals of Green's function by using the far-field approximations to the derivatives. [ABSTRACT FROM AUTHOR]

A novel method is proposed to combine the wall-modeled large-eddy simulation (LES) with the diffuse-interface direct-forcing immersed boundary (IB) method. The new developments in this method include: (i) the momentum equation is integrated along the wall-normal direction to link the tangential component of the effective body force for the IB method to the wall shear stress predicted by the wall model; (ii) a set of Lagrangian points near the wall are introduced to compute the normal component of the effective body force for the IB method by reconstructing the normal component of the velocity. This novel method will be a classical direct-forcing IB method if the grid is fine enough to resolve the flow near the wall. The method is used to simulate the flows around the DARPA SUBOFF model. The results obtained are well comparable to the measured experimental data and wall-resolved LES results. [ABSTRACT FROM AUTHOR]

The lattice Boltzmann method (LBM) is coupled with the multiple-relaxation-time (MRT) collision model and the three-dimensional 19-discrete-velocity (D3Q19) model to resolve intermittent behaviors on small scales in isotropic turbulent flows. The high-order scaling exponents of the velocity structure functions, the probability distribution functions of Lagrangian accelerations, and the local energy dissipation rates are investigated. The self-similarity of the space-time velocity structure functions is explored using the extended self-similarity (ESS) method, which was originally developed for velocity spatial structure functions. The scaling exponents of spatial structure functions at up to ten orders are consistent with the experimental measurements and theoretical results, implying that the LBM can accurately resolve the intermittent behaviors. This validation provides a solid basis for using the LBM to study more complex processes that are sensitive to small scales in turbulent flows, such as the relative dispersion of pollutants and mesoscale structures of preferential concentration of heavy particles suspended in turbulent flows. [ABSTRACT FROM AUTHOR]

Flapping-powered propulsion is used by many animals to locomote through air or water. Here we review recent experimental and numerical studies on self-propelled mechanical systems powered by a flapping motion. These studies improve our understanding of the mutual interaction between actively flapping bodies and surrounding fluids. The results obtained in these works provide not only new insights into biolocomotion but also useful information for the biomimetic design of artificial flyers and swimmers. [ABSTRACT FROM AUTHOR]

We propose a global optimization method to automatically search for the correlation peak instead of computing the entire cross-correlation map throughout an interrogation window (IW) using a fast Fourier transform (FFT)-based method. The proposed method, named globally optimized cross-correlation for particle image velocimetry (GOCCPIV), minimizes an objective function consisting of a residual term for cross-correlation and a penalty term for smoothness to solve the optimal velocity field. A very small IW is adopted in GOCCPIV to obtain a dense velocity field with a high spatial resolution. The proposed method is quantitatively validated on synthetic particle image pairs with different flow patterns and is compared with the mainstream FFT-based cross-correlation method (FFTCCPIV) and physical-based optical flow (OpticalFlow). We consider the influences of the IW size, particle concentration, particle image diameter, large displacements and image noise on the velocity measurements. Error analysis indicates that GOCCPIV outperforms FFTCCPIV in resolving small-scale vortices and reducing the measurement error. Finally, the proposed method is applied to a real PIV experiment with an impinging jet. The results indicate that GOCCPIV is more suitable than FFTCCPIV for resolving high-velocity-gradient regions. [ABSTRACT FROM AUTHOR]