一种变角度水翼的约束入水实验装置

ZL202010060877.5一种变角度水翼的约束入水实验装置-黄仁芳、王一伟、张

一种自由发射水翼实验装置

本发明实施例涉及一种自由发射水翼实验装置，包括：发射件，横翼，连接组件以及水翼组件；所述发射件的一端与所述横翼的中部连接，所述横翼的两端与所述连接组件连接，所述连接组件与所述水翼组件可拆卸连接，通过所述连接组件使所述水翼组件在航行过程中产生上下对称的升力，从而保证所述自由发射水翼实验装置的稳定性。由此，本发明通过上下对称的水翼实现对自由面边界下绕水翼空泡流动的研究，能够有效地解决现有的试验中装置稳定性差导致水翼起飞的问题

一种基于低湍流度水槽的气泡产生和融合实验装置及方法

本发明公开了一种基于低湍流度水槽的气泡产生和融合实验装置,包括：低湍流度循环水槽、通气设备及气泡图像采集分析系统,低湍流循环水槽与通气设备连通,气泡图像采集分析系统设置于所述低湍流循环水槽侧面,低湍流度循环水槽提供产生气泡以及产生的大量气泡融合的水环境；通气设备用于向所述低湍流循环水槽通入气体产生气泡；气泡图像采集分析系统用于对所述低湍流循环水槽内气泡图像进行采集和分析,得到气泡形态变化规律、气泡生长周期变化规律和气泡融合规律。还公开了采用此装置进行气泡产生和融合实验方法。解决了小尺度范围内气泡融合形成气层的实验装置以及实验方法匮乏的问题,为开展气泡-气层流态转变研究以及气层稳定性研究提供数据基础

盐析与疏水层析相结合快速分离提纯猪胰激肽释放酶

将疏水层析技术用于从猪胰脏中分离纯化激肽释放酶,建立了一种简便、快速的分离提纯方法:将粗品溶解后经过硫酸铵沉淀处理,然后经过Butyl Sepharose FF疏水层析后得到目标蛋白,分析其纯度大于500U/mg,盐析和疏水两步纯化的收率大于85.0%.同时比较了Phenyl Sepharose FF,Octyl Sepharose FF和Butyl Sepharose FF三种疏水介质分离纯化胰K的效果.本实验工艺与传统工艺相比,具有操作简单、快速、回收率和纯化倍数高等优点,有望成为一种从动物组织中快速分离纯化药用蛋白质的有效技术平台

Energy performance prediction of the centrifugal pumps by using a hybrid neural network

It is of great significance to rapidly and accurately predict the energy performance of centrifugal pumps for the macro-control of the entire electric power system. However, some challenges are encountered, for example, the numerical simulation requires huge computing resources and calculating time, the theoretical loss model needs to improve the prediction accuracy, etc. Based on the multiple geometrical parameters and operation conditions, a hybrid neural network is proposed to predict the energy performance (i.e. the head, power and efficiency) of centrifugal pumps, where the theoretical loss model is incorporated into the back propagation neural network and then the neural network structure is optimized by automatically determining the node number of hidden layers. When compared with the experiments, the energy performance is well predicted by using the hybrid neural network with the mean-square-error (MSE) for the head, power and efficiency of 0.0062, 8.4E-4, 0.020, respectively. Besides, by considering the theoretical loss model, the hybrid neural network demonstrates a dramatic decrease in the head MSE and the efficiency MSE when compared with the original neural network. Furthermore, the hybrid neural network performs much better than the traditional linear regression in a wide flow-rate range for multiple centrifugal pumps

盐析与疏水层析相结合快速分离提纯猪胰激肽释放酶

将疏水层析技术用于从猪胰脏中分离纯化激肽释放酶，建立了一种简便、快速的分离提纯方法：将粗品溶解后经过硫酸铵沉淀处理，然后经过Butyl Sepharose FF疏水层析后得到目标蛋白，分析其纯度大于500U／mg，盐析和疏水两步纯化的收率大于85．0％，同时比较了Phenyl Sepharose FF,Octyl Sepharose FF和Butyl Sepharose FF三种疏水介质分离纯化胰K的效果，本实验工艺与传统工艺相比，具有操作简单、快速、回收率和纯化倍数高等优点，有望成为一种从动物组织中快速分离纯化药用蛋白质的有效技术平台

Data-driven turbulence model for unsteady cavitating flow

Unsteady Reynolds-averaged Navier-Stokes (URANS) equations have been widely used in engineering fields to investigate cavitating flow owing to their low computational cost and excellent robustness. However, it is challenging to accurately obtain the unsteady characteristics of flow owing to cavitation-induced phase transitions. In this study, we propose an implicit data-driven URANS (DD-URANS) framework to analyze the unsteady characteristics of cavitating flow. In the DD-URANS framework, a basic computational model is developed by introducing a cavitation-induced phase transition into the equations of Reynolds stress. To improve the computational accuracy and generalization performance of the basic model, the linear and nonlinear parts of the anisotropic Reynolds stress are predicted through implicit and explicit methods, respectively. A data fusion approach, allowing the input and output of characterized parameters at multiple time points, is presented to obtain the unsteady characteristics of the cavitating flow. The DD-URANS model is trained using the numerical results obtained via large-eddy simulation. The training data consist of two parts: (i) the results obtained at cavitation numbers of 2.0, 2.2, and 2.7 for a Venturi flow, and (ii) those obtained at cavitation numbers of 0.8 and 1.5 for a National Advisory Committee for Aeronautics (NACA) 66 hydrofoil. The DD-URANS model is used to predict the cavitating flow at cavitation numbers of 2.5 for a Venturi flow and 0.8 for a Clark-Y hydrofoil. It is found that the DD-URANS model is superior to the baseline URANS model in predicting the instantaneous periodic shedding of a cavity and the mean flow fields

绕弹性水翼空化流动及其流激振动特性研究

该文采用基于径向基函数的流固耦合方法，对不同空化数下绕刚性水翼/弹性水翼的空泡形态及其流激振动特性进行了数值模拟。结果表明，绕弹性水翼空泡形态具有三个典型特征：(1)靠近翼尖前缘的附着空泡形态为三角形；(2)翼尖出现梢涡空化，梢涡空化随着空化数的降低而逐渐明显；(3)回射流作用下水翼存在云状空泡的周期性脱落。对不同空化数下弹性水翼的振动特性进行分析发现，随着空化数的下降，水翼振动的平均振幅及振幅波动值先增大再减小，平均振幅和振幅波动由大到小依次是：云空化>超空化>片空化