Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Thermal properties of hierarchical YSZ and LZO ceramic microspheres with multi-scaled voids investigated by using theoretical,experimental and simulation methods

Heat transfer within ceramic feedstock powders is still unclear, which impedes optimization of the thermal and mechanical properties of the thermal sprayed coatings. The microspheres (yttria-stabilized zirconia YSZ and lanthanum zirconate LZO) were prepared via the electro-spraying assisted phase inversion method (ESP). The thermal properties of the two ESP microspheres and a commercial hollow spherical powder (HOSP) were investigated by using theoretical, experimental, and simulation methods. Thermal conductivity of the single microsphere was estimated via a novel nest model that was derived from the Maxwell-Eucken 1 and the EMT model. Thermal conductivity of a single YSZ/LZO-ESP microsphere prepared at 1100–1200 °C was within 0.36–0.75 W/m K, which was ～ 20 % lower than that of a single YSZ-HOSP microsphere with a similar porosity. Heat flux simulation showed that high tortuosity around the multi-scaled voids of the ESP microsphere led to a more efficient decrease in thermal conductivity compared with total porosity.     

Comments on “Study and application of discharge calibration for submerged radial gates” by Guo X., Guo Y., Wang T., Fu H., Li J. Flow Meas. Instrum. 78 (2021) 101912, https://doi.org/10.1016/j.flowmeasinst.2021.101912

This paper discusses the capability of Guo et al.'s (2021) equations to determine the discharge of radial gates under submerged flow conditions. It was concluded that Guo et al.'s (2021) equations are associated with error reduction compared to the Incomplete Self-Similarity (ISS) theory and the calibration method. However, it does not have a significant advantage over Energy-Momentum (E-M) approach. Employing E-M principles, new equations were proposed to determine the discharge of radial gates, which has some advantages compared to Guo et al. (2021), such as (1) error reduction under partially and fully submerged flow conditions, (2) least dependence on the empirical constants, (3) uniformity of form over the entire submerged condition, and (4) no need to classify the submerged flow. Field calibration showed that the proposed equations in the present study for a single gate predict the discharge of parallel radial gates with a mean absolute error of less than 4.5% subject to the submerged operation of all open gates.     

优化GD-模糊规则的滑坡预报模型研究

为了提高滑坡灾害预报准确率，改善传统的滑坡监测和预报中存在的参数选取困难及模糊控制系统作为预报模型精确度不高的问题，首先采用山体结构稳定性分析法进行滑坡灾害参数的选取，得出降雨量、含水率、土压力及岩土表面位移增量作为预报参数的结论；其次将选取的参数作为模糊系统的输入，建立滑坡灾害发生概率模型，并引入优化的GD算法修正预报模型中的动态参数，使模糊控制模型具有自适应性；同时与未优化的模糊控制模型以及单独模糊控制模型进行仿真对比，仿真结果表明，该控制算法收敛速度快，具有很好的收敛性；最后将该模型在某滑坡重点灾区实验区进行实验测试，实验结果显示该模型具有较好的收敛性，且预报精度达到90%。     

碳纳米管@球形氮化碳核壳结构光催化剂的构筑及其性能

以二氰二胺和三聚氯氰为原料，以碳纳米管 (CNT)为核，采用溶剂热法成功制备了一系列不同CNT质量的可见光响应的碳纳米管@球形氮化碳 (CNT@CNMS) 核壳结构催化剂。采用X射线衍射光谱（XRD）、傅里叶变换红外（FT-IR）、透射电子显微镜（TEM）、紫外可见光谱(UV-vis)、X射线光电子能谱(XPS)、电化学阻抗（EIS）和光致发光光谱（PL）等分析方法对催化剂进行了表征。通过电化学表征计算出CNMS的价带与导带位置。结果表明，CNMS均匀的生长到管状CNT表面，形成CNT@CNMS核壳结构；制备的CNT@CNMS核壳催化剂比表面积增大，且可见光吸收性能明显增强。光催化性能试验表明，当CNT质量为20 mg时，制备的催化剂性能最高，反应120 min，4 - 硝基苯酚的降解率高达54.44%，其降解效果明显高于CNMS。该研究对于采用溶剂热法制备核壳结构基氮化碳催化剂治理油田废水中酚类污染物提供了理论基础。     

径向不耦合装药爆破效果的数值研究

为了研究径向不耦合条件下爆破效果的影响因素,利用AUTODYN-2D对比不耦合系数、不耦合介质、炸药种类对爆破效果的影响规律。结果表明,与耦合装药相比,径向不耦合装药条件下炮孔压力明显降低。对比水介质和空气介质下的爆破效果可知,水介质不耦合条件下,炸药爆炸能量的传递效率更高。炮孔压力与炸药种类密切相关,TNT产生的炮孔压力最大,但作用时间较短,而ANFO和乳化炸药的作用时间较长。     

球形碳酸钙的控制合成研究

以硼酸为控制剂，氯化钙和碳酸钠为原料，采用共沉淀法制备了方解石型碳酸钙球形晶体。研究了控制剂浓度、反应温度、反应时间、反应物浓度等因素对碳酸钙粒径和形貌的影响。结果表明：在硼酸浓度为0.4 mol/L、氯化钙浓度为0.1 mol/L、20 ℃饱和碳酸钠溶液滴速为4.9 mL/min、反应时间为60 min、陈化时间为60 min、反应温度为50 ℃、氯化钙与碳酸钠物质的量比为1∶1条件下，制备的球形碳酸钙颗粒大小均匀，平均粒径为1.57 μm。     

油水混合对径向滑动轴承润滑性能的影响

基于流体动压润滑基础理论,利用数值计算方法,在MATLAB软件中建立径向滑动轴承油水混合动压润滑的数学模型,对比分析润滑油中不同含水量对径向滑动轴承润滑性能的影响。结果表明:润滑油中混入少量的水对滑动轴承液膜的厚度和压力产生了一定的影响,最小液膜厚度随含水量的增加而减小,最大液膜压力随含水量的增加而增加;润滑油中混入少量水使得液膜合力和摩擦力变大,将不利于轴承的动压润滑,从而导致轴承润滑性能变差,并且加大轴承的摩擦磨损,降低径向滑动轴承的使用寿命。     

On the numerical solution of Fredholm integral equations utilizing the local radial basis function method

The current investigation describes a computational technique to solve one- and two-dimensional Fredholm integral equations of the second kind. The method estimates the solution using the discrete collocation method by combining locally supported radial basis functions (RBFs) constructed on a small set of nodes instead of all points over the analysed domain. In this work, we employ the Gauss–Legendre integration rule on the influence domains of shape functions to approximate the local integrals appearing in the method. In comparison with the globally supported RBFs for solving integral equations, the proposed method is stable and uses much less computer memory. The scheme does not require any cell structures, so it is meshless. We also obtain the error analysis of the proposed method and demonstrate that the convergence rate of the approach is high. Illustrative examples clearly show the reliability and efficiency of the new method.     

First principles computational studies of spontaneous reduction reaction of Eu(III) in eutectic LiCl‐KCl molten salt

Using first principles calculations, we study fundamental mechanism of spontaneous reduction reaction of Eu³⁺ to Eu²⁺ in eutectic LiCl‐KCl molten salt. We decouple the reaction Gibbs free energy into enthalpy and entropy contributions by using rigorous thermodynamic formalism. Key structural features of the solvation shell are characterized by the radial distribution function and the coordination number. Compared with Eu²⁺, the Eu³⁺ ion has a more rigid framework of the solvation shells, corroborating its stronger electrostatic interaction with neighboring ligands of Cl^? ions and a more favorable state on the aspect of enthalpy. Computations on vibrational frequency, however, pose significant contribution of vibrational entropy to the reaction Gibbs free energy for the reduction. Vibration frequency of Eu²⁺ is smaller than that of Eu³⁺, driving a more positive change of the entropy in the reduction reaction. Furthermore, an Eu²⁺ diffuses more quickly than an Eu³⁺ in the LiCl‐KCl molten salt with switching mechanism of ligand Cl^? ions in the solvation shell. Our results propose that the spontaneity of the reduction reaction is driven by the entropic contribution by overcoming the penalty of the reaction enthalpy.