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The working condition of the floating platform will be affected by wind and waves in the marine environment. Therefore, it is of great importance to carry out real-time prediction research on the mooring load for ensuring the normal operation of the floating platform. Current researches have focused on the real-time prediction of mooring load using the machine learning method, but most of the studies are about the application and generalization analysis of different models. There are few studies on the influence of data distribution characteristics on prediction accuracy. In view of the above problems, this paper investigates the effect of data skewness on the prediction performance for the deep learning model. The long short-term memory (LSTM) neural network is applied to construct the mooring load prediction model. The numerical simulation datasets of the deep water semi-submersible platform are employed in model training and data analysis. The prediction performance of the model is preliminarily verified based on the simulation results. Meanwhile, the distribution characteristics of mooring load data under different sea states are analyzed and a skewness processing method based on the Box-Cox Transformation (BCT) is proposed. The effect of data skewness on prediction accuracy is further investigated. The comparison results indicate that reducing the mooring load data skewness can effectively improve the prediction accuracy of LSTM model.

The pit structure optimized drip irrigation emitter (PODE) is a novel type of irrigation emitter that may provide shunts, quick diversion, and mixed flow to maximize energy loss. To study the influence of the geometric parameters of the flow channel on the hydraulic characteristics and energy loss effect, twenty-five sets of orthogonal test schemes were established. Using numerical simulation and verification tests, the flow index and energy loss coefficient were obtained. The results showed that the flow index of the PODE was 0.4632-0.5265, and its hydraulic performance was good. The energy loss coefficient under the pressure head of 5-15 m was 510-2221, which showed that the energy loss effect was obvious. The influence order of the geometric parameters on the flow index was B>P>C>D>A, the optimal solution was P0.6D1.4A85B0.25C0.12. The determination coefficient of the regression model based on geometric parameters and flow index was 0.85. In addition, the verification test showed that the relative error among the test value, simulated value, and estimated value were less than 5%, and the flow index can be estimated reliably. The research can provide a reference for the pre-research and evaluation of the hydraulic performance and energy loss effect of the PODE.

Wind turbine blades are prone to icing in cold environments, which leads to decreased aerodynamic performance, increased power loss, and even endangers the safe and stable operation of wind turbines. Electric heating anti-deicing method is the most effective solution because of its flexible control, rapid response, and high deicing efficiency. However, in the process of blade high-speed rotation, the complex flow field effect significantly affects the blade heat transfer performance, which leads to the problems of high energy consumption, low heat utilization, and uneven heating of traditional electric heating anti-icing/deicing methods, limiting their application effect in complex working conditions. Based on the physical mechanism and heat exchange characteristics of electric heating deicing of wind turbine blades, a coupled flow–heat transfer numerical model suitable for complex flow field conditions was constructed in this study, aiming to realize the dynamic simulation of the global temperature field and the phase transition process of ice sheets under different heating modes. Furthermore, the deicing efficiency characteristics of continuous heating and cyclic heating modes were compared and analyzed. The blade tip section of a Sinoma87.5 was taken as the experimental object, and the deicing experiment of blade by electric heating was carried out under artificial ice-covering laboratory conditions. The simulation and experimental results show that the deicing process by electric heating can be divided into three typical stages: initial temperature rise, stagnation, and rapid temperature rise. Under the influence of incoming flow conditions, the temperature rise of the front stagnation point region lags behind that of the windward side, and the steady-state peak temperature is lower. Compared with the cyclic heating mode, the continuous heating mode can enter and cross the stagnation period more quickly. The peak steady-state temperature of the continuous heating mode is 24.2 °C, and the deviation from the simulation result is only 2.8 °C, which is within the acceptable error range, effectively verifying the reliability of the numerical calculation model established.

GyroWheel is an innovative device that combines the actuating capabilities of a control moment gyro with the rate sensing capabilities of a tuned rotor gyro by using a spinning flex-gimbal system. However, in the process of the ground test, the existence of aerodynamic disturbance is inevitable, which hinders the improvement of the specification performance and control accuracy. A vacuum tank test is a possible candidate but is sometimes unrealistic due to the substantial increase in costs and complexity involved. In this paper, the aerodynamic drag problem with respect to the 3-DOF flex-gimbal GyroWheel system is investigated by simulation analysis and experimental verification. Concretely, the angular momentum envelope property of the spinning rotor system is studied and its integral dynamical model is deduced based on the physical configuration of the GyroWheel system with an appropriately defined coordinate system. In the sequel, the fluid numerical model is established and the model geometries are checked with FLUENT software. According to the diversity and time-varying properties of the rotor motions in three-dimensions, the airflow field around the GyroWheel rotor is analyzed by simulation with respect to its varying angular velocity and tilt angle. The IPC-based experimental platform is introduced, and the properties of aerodynamic drag in the ground test condition are obtained through comparing the simulation with experimental results.

Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting, that is, very-short-range forecasting (0–6 h). The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space–time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists. In this sense, pysteps has the potential to become an important component for integrated early warning systems for severe weather.The pysteps library supports various input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic and neighborhood forecast verification. The pysteps library is described and its potential is demonstrated using radar composite images from Finland, Switzerland, the United States and Australia. Finally, scientific experiments are carried out to help the reader to understand the pysteps framework and sensitivity to model parameters.

To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition,” i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. Storm-following nests are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Project, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC–TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multistorm nesting approach to improve the simulation of TC–TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multistorm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multistorm approach demonstrated TC intensity forecast improvements, including more realistic TC–TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

Aiming at the reasonable width of the narrow coal pillar of a fully mechanized caving face and the safety support of roadway, taking the coal pillar in the section between 110503 and 110505 face of the Yushuling Coal mine as the research background, a model of the hard basic roof fracture structure of fully mechanized caving face is established through theoretical analysis, and the roadway with narrow coal pillar is analyzed mechanically. Combined with the geological conditions of the working face, it is concluded that the low‐stress area is less than 3.29 m. When the internal stress field of the low‐stress environment is considered in the roadway layout, the influence of mining and the essential roof hardness should be considered. The reasonable size of the narrow coal pillar is 3 ~ 6 m, thinking that the load borne by the coal pillar is less than the ultimate strength of the coal pillar. The limit equilibrium theory calculates that the reasonable width of a coal pillar is at least 4 m. The stress and displacement of coal pillars with different widths of 3, 4, 5 and 6 m are analyzed by numerical simulation, and the 4 m narrow coal pillars are simulated and verified. Field industrial tests show that coal pillar and roadway surrounding rock deformation are small under asymmetric surrounding rock control. The research results have been successfully applied to engineering practice and can provide a reference for the research method of narrow coal pillar width under a hard basic roof. Layout of 110503 and 110505 working places

Ruelle predicted that the maximal amplification of perturbations in homogeneous isotropic turbulence is exponential $\\exp ({\\sigma \\sqrt {Re} \\,t})$ (where $\\sigma \\sqrt {Re}$ is the maximal Lyapunov exponent). In our earlier works, we predicted that the maximal amplification of perturbations in fully developed turbulence is faster than exponential and is given by $\\exp ({\\sigma \\sqrt {Re} \\sqrt {t} +\\sigma _1 t})$ where $\\sigma \\sqrt {Re} \\sqrt {t}$ is much larger than $\\sigma \\sqrt {Re} \\, t$ for small $t$. That is, we predicted superfast initial amplification of perturbations. Built upon our earlier numerical verification of our prediction, here, we conduct a large numerical verification with resolution up to $2048^3$ and Reynolds number up to $6210$. Our direct numerical simulation here confirms our analytical prediction. Our numerical simulation also demonstrates that such superfast amplification of perturbations leads to superfast nonlinear saturation. We conclude that such superfast amplification and superfast nonlinear saturation of ever existing perturbations suggest a mechanism for the generation, development and persistence of fully developed turbulence.

In order to improve the overall resilience of the urban infrastructures, it is required to conduct blast resistant design for important building structures in the city. For complex terrain in the city, it is recommended to determine the blast load on the structures via numerical simulation. Since the mesh size of the numerical model highly depends on the explosion scenario, there is no generally applicable approach for the mesh size selection. An efficient method to determine the mesh size of the numerical model of near-ground detonation based on explosion scenarios is proposed in this study. The effect of mesh size on the propagation of blast wave under different explosive weights was studied, and the correlations between the mesh size effect and the charge weight or the scaled distance was described. Based on the principle of the finite element method and Hopkinson-Cranz scaling law, a mesh size measurement unit related to the explosive weight was proposed as the criterion for determining the mesh size in the numerical simulation. Finally, the applicability of the method proposed in this paper was verified by comparing the results from numerical simulation and the explosion tests and was verified in AUTODYN.

This paper investigates the damaging effects of explosion shock waves in a semi-closed environment. A simulation model was constructed using the arbitrary Lagrangian–Eulerian (ALE) algorithm. The ALE algorithm analyzed the shock wave overpressure at different positions, and the simulation data from 1.5 to 2.6 ms were fitted to derive a formula for the first peak value of the shock wave overpressure. The accuracy of the simulation results is verified through numerical simulation and experimental validation. Experiments indicate that in semi-closed environments, explosion shock waves reflect off walls multiple times, resulting in multiple peaks in the overpressure curves at each measurement point. The fitting formulas for some measuring points agree with experimental values, but there are differences due to experimental conditions and the complexity of the flow field in the semi-closed environment. Although the experimental datum is limited and discrete, the fitting formula is generally consistent with the experimental data at certain measuring points.