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.     

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.     

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。     

Thermo-adjusted self-healing epoxy resins based on Diels–Alder dynamic chemical reaction

Micro-damage in materials could be repaired by endowing materials with self-healing performance. Herein, an epoxy resin with excellent self-healing performance grounded on thermo-reversible Diels–Alder dynamic chemical reaction was developed. Results showed that the bending strength and adhesive behavior of epoxy resin were influenced dramatically upon treatment with various temperatures. More importantly, damages created in epoxy resin could be repaired completely after suitable heat treatments. What is more, the healed epoxy resin exhibited much higher bending strength and adhesive performance than the pristine one did. The materials could be damaged and then repaired repeatedly. Meanwhile, the as-prepared self-healing epoxy resin exhibited excellent thermal reversibility and controllable adhesion. The thermo-adjusted self-healing performance endowed epoxy resin with recyclable and reusable performance. Therefore, the research made it possible of recycling waste epoxy resins.     

Combination of dynamic features with a new mask to optimize neural network speech enhancement

Concerning the problem that the Neural Network speech enhancement algorithm cannot fully represent the nonlinear structure of speech due to feature selection,which leads to speech distortion.This paper proposes the combination of dynamic features with a new mask to optimize neural network speech enhancement.First,three features of noisy speech are extracted and spliced to obtain static features.Then,the first and second difference derivatives are obtained to capture the instantaneous signals of speech and fuse them into dynamic features.The combination of dynamic and static features completes internal complementarity of features and reduced speech distortion.Second,in order to enhance the intelligibility and clarity of speech at the same time,an adaptive mask is proposed,which can adjust the energy ratio of speech and noise as well as the ratio of the traditional mask and the square root mask.The Gammatone channel weight is used to modify the mask value in each channel to simulate the human auditory system and further improve the speech intelligibility.Finally,the simulation of multiple voices under different noise backgrounds shows that compared with different literature algorithms,the algorithm has a higher SNR,subjective speech quality and short-term objective intelligibility,which verifies the effectiveness of the algorithm.     

动态高压微射流处理对方竹笋膳食纤维理化及结构特性的影响

以方竹笋中提取的膳食纤维为研究对象，采用动态高压微射流（dynamic high-pressure micro-fluidization, DHPM）在不同压力条件（0，50，100，150，200 MPa）下进行处理，探究其对竹笋膳食纤维（bamboo shoots dietary fiber, BSDF）理化和结构特性的影响。结果表明，随着处理压力的增大，BSDF粒径先增大后减小，当处理压力为150 MPa时，粒径最小，为（370±11） nm，此条件下BSDF的持水力、持油力和膨胀力达到最大，较对照组分别提高了47.74%，50.54%，61.27%，且差异显著（P<0.05）。红外光谱分析表明DHPM处理不会改变BSDF的官能团，但会使BSDF内部的部分氢键断裂和半纤维素、木质素等发生降解；X射线衍射和热重分析表明DHPM处理不会引起BSDF的晶体结构改变，但晶体有序度会下降，进而导致其热稳定性降低；微观结构分析显示DHPM处理会使BSDF颗粒尺寸减小、表面粗糙、组织松散，且当处理压力为200 MPa时，颗粒发生团聚。综上，DHPM可以有效改善BSDF的理化性质，在膳食纤维改性方面具有一定的应用价值。     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.