工艺参数对动态流量控制法挤压弯管应力的影响

采用有限元模拟和实验研究了挤压钛合金弯曲管件。通过实验验证了工件的形状和尺寸精度,并通过有限元模拟分析了工艺参数对挤出过程中变形体的平均压应力分布情况和挤出弯管件的曲率半径的影响规律。结果表明:有限元模拟中,弯管件的曲率半径误差为6.03%,弯管直径误差为3.82%;在靠近定径带处,平均压应力呈非均匀分布;在焊合腔内,靠近细分流孔区域的平均压应力小于靠近粗分流孔区域的平均压应力,平均压应力的大小顺序在通过粗、细分流孔前后相反;在模具结构固定不变时,弯管件的曲率半径随挤压速度的减小而增大,不随挤压温度的变化而变化。     

梯度铝蜂窝夹芯板的力学行为

梯度分层铝合金蜂窝板是一种有效的吸能结构,本工作在梯度铝蜂窝结构的基础上根据梯度率的概念,通过改变蜂窝芯层的胞壁长度,设计了4种质量相同、梯度率不同的铝蜂窝夹芯结构。通过准静态压缩实验,并结合非线性有限元模拟准静态及冲击态下梯度铝蜂窝夹芯结构的变形情况及其力学性能,分析对比了相同质量下梯度铝蜂窝夹芯结构在准静态下的变形模式以及冲击载荷下分层均质蜂窝结构和不同梯度率的分层梯度蜂窝结构的动态响应和能量吸收特性。结果表明:在准静态压缩过程中,铝蜂窝梯度夹芯板的变形具有明显的局部化特征,蜂窝芯的变形为低密度优先变形直至密实,层级之间的密实化应变差随芯层密度的增大而逐渐减小;在高速冲击下,梯度蜂窝板并非严格按照准静态过程中逐级变形直至密实,而是在锤头冲击惯性及芯层密度的相互作用下整体发生的线弹性变形、弹性屈曲、塑性坍塌及密实化;另外,在本工作所设计的梯度率中,当梯度率为γ₁=0.0276时,梯度蜂窝夹芯板的吸能性达到最好,相较于同等质量下的均质蜂窝夹芯板,能量吸收提高了10.63%。     

Optimization of PEMFC system operating conditions based on neural network and PSO to achieve the best system performance

PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power.     

Data-driven diagnosis of the high-pressure hydrogen leakage in fuel cell vehicles based on relevance vector machine

The hydrogen pressure inside tanks and its adjacent pipes can reach up to 70 MPa in fuel cell vehicles. This is the weak links of hydrogen leakage. The diagnosis time of mainstream hydrogen leakage diagnosis method based on hydrogen concentration sensors (HCSs) is easily affected by the number and location of installed sensors. In this study, a data-driven diagnosis method is proposed for the high-pressure hydrogen leakage. Fisher discrimination analysis and linear least squares fitting are used for data preprocessing, relevance vector machine is used for pattern recognition. When the total volume of tanks is 82 L and the hydrogen leakage flow rate is larger than 2 g/s, the diagnosis accuracy of the proposed method is higher than 95% and the diagnosis time is constant. When the leakage location is far away from HCSs, the proposed method can the diagnose hydrogen leakage in a shorter time than mainstream method.     

长距离越野带式输送机静动态分析

针对长距离越野带式输送机运输线路复杂、输送带上物料分布不均匀等特点,利用 Belt Analyst 分析软件,建立了 5 种出现概率较高的工况模型,静态分析了这 5 种工况下带式输送机圆周驱动力、电动机轴功率、张紧力等参数的差异,确定了最恶劣工况。同时对带式输送机启动、停车和制动期间输送带关键点张力、滚筒合力、张紧小车位移和速度、驱动滚筒紧松边张力比等参数进行了动态分析,调整了最终滚筒合力参数。经过一年多时间的运行检验,该系统各项参数满足稳定运行要求,对长距离越野带式输送机设计具有一定的参考意义。     

Study on the influence of segmented fuel cell by grooving method and its application in oxygen starvation diagnosis

The oxygen starvation in fuel cells is an important reason for the deterioration of durability. The segmented fuel cell is a method to study the gas distribution inside the fuel cell. In order to study the influence of the grooving method on segmented fuel cell and its application in oxygen starvation diagnosis, a five-serpentine-channel three-dimensional two-phase simulation model is established by FLUENT. Through steady-state simulation, the effect of grooving method on fuel cell performance is studied. The overall performance (polarization curve) of the fuel cell drops slightly, but the current density distribution on the anode graphite plate changes greatly due to the grooves. The “current concentration” phenomenon is proposed based on the current density distribution. Through dynamic simulation, the oxygen starvation under current load mode and voltage load mode is simulated, and the “starvation coefficient” is defined as an oxygen starvation diagnostic index. In the current load mode, the “starvation coefficient” never exceed 15%, because when the oxygen starvation is severe, the simulation cannot converge or even cannot maintain, which corresponds to the voltage reversal in reality. However, in the voltage load mode, the “starvation coefficient” can reach up to 100%. The conclusions have important guiding significance for the judgment of the internal reaction uniformity of the segmented fuel cell by grooving method and provide a theoretical basis for judging whether a fuel cell is out of oxygen by segmented fuel cell.     

A numerical study of dynamic behaviors of a unitized regenerative fuel cell during gas purging

The gas purging states affect electricity output and energy storage capacity of unitized regenerative fuel cells. In this study, a model of unitized regenerative fuel cell is established. Cell voltages and operating temperatures influences on the dynamic distribution of thermal fluid during purging process and the discharge of residual liquid water in electrolytic cell mode are investigated. The motivation of the present study is better understanding the gas purging characteristics and its effect on reaction behaviors of unitized regenerative fuel cells. Simulation results reveal a significant influence of purging gas temperature on the water flooding and a great effect of operating voltage on the water diffusion. The operating temperature of electrolytic cell model almost has little effect on purging results at different cell temperature and the same purging gas temperature. When the purging gas temperature is changed, higher temperatures of cell and purging gas facilitate liquid water discharging out from the cell regions. In cell water flooding situation, when having large liquid content, the purging gas has little effects on the water expelling process.     

Acid–base transport model depicting the dynamic pH response of interfacial reactions

Acid–base transport is integral to many important interfacial reactions in various fields of chemistry, but its theoretical foundation is lacked. Herein, a common acid–base transport model is established owing to the success in deriving buffer transport equations. This model is applicable to most buffer systems by flexibly integrating the transport equations in terms of buffer components, and is verified through the model relationships of buffer transport limiting current by using hydrogen evolution reaction experiments. Based on model calculations, two diagram approaches are proposed to depict the dynamic pH response and aid buffer operation optimizations. The model and methods allow us to quantify the rate-limiting effect of acid–base transport on interfacial reactions and to precisely control the effect through medium regulations. Furthermore, the model has laid the foundation of dynamic pH effect on species transformation and process mechanism, which can be of wide interest in the chemistry encompassing interfacial reactions.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

基于光谱尺度空间与管道滤波的红外目标检测

为了准确地从复杂干扰背景下检测出真实弱小目标，本文引入视觉显著性，设计了基于快速光谱尺度空间与动态管道滤波的红外目标检测算法。基于真实目标与背景内容之间的整体差异，引入快速光谱尺度空间与阈值分割技术，设计视觉显著性机制，对红外图像完成处理，输出全局显著性映射，以高效过滤干扰背景内容。考虑目标与背景的局部特征差异，构建自适应局部对比度增强机制，对粗检测结果实施处理，获取对应的局部显著性映射，改善视觉显著性区域内目标的对比度。引入高斯差分理论，通过估算每一帧红外图像中的目标像素直径，形成动态管道滤波，充分消除虚警，准确识别出弱小目标。多组实验数据显示：较已有的红外目标检测技术而言，在各种不同的复杂背景干扰下，所提算法呈现出更好的检测能力，拥有更理想的接收机工作特性ROC曲线。