不同应力状态下的高强钢板断裂机理及预测

板料成形过程的宏观断裂行为依赖于其微观断裂机理，因此成形过程模拟中的断裂准则的准确选择对于断裂预测具有重要意义。以高强钢TRIP780板料为研究对象，设计从剪切到拉伸应力状态的五种断裂试验，结合宏观拉伸试验和扫描电子显微镜（Scanning electron microscope，SEM）分析研究不同应力状态下TRIP780板料的断裂机理，得到不同应力状态下正应力和切应力与断裂机理的关联关系，引入正应力与切应力的影响构建MMC断裂准则，应用于板料压剪应力区间的断裂行为预测。结果表明，反映断裂机理的MMC准则能适用于板料压剪和拉剪变形应力状态下断裂失效的准确预测。     

平板集热器(倾角)变化工况数值模拟

运用FLUENT数值模拟软件分析了平板集热器(倾角)变化对集热器传热特性的影响,保证其结构参数不变,通过对5组不同倾角(0°、30°、45°、60°、75°)的数值模型进行非稳态模拟,对模拟数据进行分析,得出了平板集热器不同倾角对集热器传热性能变化的影响。     

固态去耦合器在解决阀室阴保漏电问题中的应用

干线埋地管道均为强制电流+外防腐层联合保护方式,这就要求被保护管道有良好的绝缘性能。阀室内管道与电气之间采用绝缘卡套进行绝缘,放空管与阀室内管道间也存在绝缘接头。基于电气安全考虑,阀室电气设备均有接地,如果管道与接地网搭接或绝缘失效,将会造成阀室管道电位偏正,阴保处于欠保护状态。因此针对运行的阀室,做好绝缘排查,消除阴保电流流失,确保阀室埋地管道处于良好的阴极保护状态尤为重要。本文通过对某输油线某阀室阴保漏电进行原因排查并采用了固态去耦合器解决了阀室阴极保护漏电,对解决阀室阴极保护漏电提供了一种全新的思路和方法。     

Integrated process design,scheduling, and model predictive control of batch processes with closed-loop implementation

Simultaneous evaluation of multiple time scale decisions has been regarded as a promising avenue to increase the process efficiency and profitability through leveraging their synergistic interactions. Feasibility of such an integral approach is essential to establish a guarantee for operability of the derived decisions. In this study, we present a modeling methodology to integrate process design, scheduling, and advanced control decisions with a single mixed-integer dynamic optimization (MIDO) formulation while providing certificates of operability for the closed-loop implementation. We use multi-parametric programming to derive explicit expressions for the model predictive control strategy, which is embedded into the MIDO using the base-2 numeral system that enhances the computational tractability of the integrated problem by exponentially reducing the required number of binary variables. Moreover, we apply the State Equipment Network representation within the MIDO to systematically evaluate the scheduling decisions. The proposed framework is illustrated with two batch processes with different complexities.     

后处理对爆轰纳米金刚石表面官能团的影响

分别在高锰酸钾与浓硫酸的混合溶液、空气、氢气、真空以及氩气中对爆轰纳米金刚石进行后处理,研究了后处理方法对其表面官能团的影响。采用X射线衍射仪、高分辨透射电子显微镜、傅立叶变换红外光谱仪和差示扫描量热仪对后处理前后纳米金刚石的微观结构、性能和表面状态进行了研究。结果表明:纳米金刚石颗粒形状为球形或椭球形,平均粒径约为5 nm,在空气中的起始氧化温度约为550 ℃,在氢气、真空和氩气中的石墨化温度分别约为284 ℃、1 146 ℃和1 184 ℃。纳米金刚石在后处理前表面含有大量的官能团,如-OH、-CH₃、-CH₂、CO₂、-C==O、-COOH和-C-O-C等。在氢气中对纳米金刚石进行处理,可使部分官能团从表面解吸而由氢取代,悬键与氢结合可有效防止二次吸附,是去除爆轰纳米金刚石表面官能团的低成本、高效方法。     

五流中间包稳态及非稳态试验

为改善国内某钢厂五流中间包流场,降低非稳态换包过程的负面影响,获得高品质洁净钢,通过水模拟试验进行稳态及非稳态换包过程的研究。试验结果表明,采用方案3的稳流器结构对该中间包稳态浇铸的流场更加有利,该试验条件下的死区体积比例为10.46%;非稳态换包过程的最佳工艺条件为换包液位350 mm、充包流量12 m3/h。     

Effect of Sn content on microstructure and tensile properties of as-cast and as-extruded Mg−8Li−3Al−(1,2,3)Sn alloys

The effects of Sn content on microstructure and tensile properties of as-cast and as-extruded Mg−8Li−3Al− (1,2,3)Sn (wt.%) alloys were investigated by X-ray diffractometry (XRD), optical microscopy (OM), scanning electron microscopy (SEM) and tensile test. It is found that, as-cast Mg−8Li−3Al−(1,2,3)Sn alloys consist of α-Mg+β-Li duplex matrix, MgLiAl₂ and Li₂MgSn phases. Increasing Sn content leads to grain refinement of α-Mg dendrites and increase in content of Li₂MgSn phase. During hot extrusion, complete dynamic recrystallization (DRX) takes place in β-Li phase while incomplete DRX takes place in α-Mg phase. As Sn content is increased, the volume fraction of DRXed α-Mg grains is increased and the average grain size of DRXed α-Mg grains is decreased. Increasing Sn content is beneficial to strength but harmful to ductility for as-cast Mg−8Li−3Al−(1,2,3)Sn alloys. Tensile properties of Mg−8Li−3Al− (1,2,3)Sn alloys are improved significantly via hot extrusion and Mg−8Li−3Al−2Sn alloy exhibits the best tensile properties.     

State of charge estimation for lithium-ion battery based on an intelligent adaptive unscented Kalman filter

Adaptive unscented Kalman filter (AUKF) has been widely used for state of charge (SOC) estimation of lithium-ion battery. The noise covariance of the conventional AUKF method is updated based on the innovation covariance matrix (ICM), which is estimated using the error innovation sequence (EIS). However, the distribution of EIS changes due to the time-varying noise, load current dynamics and modelling error, which will lead to inaccurate ICM estimation. Therefore, an intelligent adaptive unscented Kalman filter (IAUKF) method is proposed to detect the distribution change of EIS. Then, the ICM is estimated based on the EIS after the distribution change. Results show that the IAUKF method can improve SOC estimation accuracy significantly. Compared with that of the AUKF method, the root mean squared error and the mean absolute error of SOC based on the IAUKF method decrease by 43.70% and 72.37% under random walk discharge condition, respectively. In addition, the computation time of the IAUKF method slightly increases by 6.27% compared with that of AUKF method. Finally, the effect of initial parameters on the SOC estimation accuracy was analysed. The results indicate that proper algorithm tuning, such as initial window length of EIS for ICM update and the threshold value, can further improve the SOC accuracy based on the proposed IAUKF method. The proposed IAUKF method also shows high robustness against initial measurement noise covariance.     

Effectiveness of PEMFC historical state and operating mode in PEMFC prognosis

As a high efficiency and environmental friendly energy conversion technique, proton exchange membrane fuel cell (PEMFC) system faces challenges of limited durability and performance decay during long-term operation. Prognosis estimates the remaining useful life (RUL) of the system, from which maintenance policy can be scheduled to extend its useful life. However, parameters related to either PEMFC historical state or operating mode are used in most existing PEMFC prognostic studies, while their effects on PEMFC predictions are not clarified, this brings great challenge in selecting appropriate parameters for reliable PEMFC prognosis in practical applications subjected to complex operating conditions. In this paper, the effectiveness of PEMFC historical behavior and operating mode on PEMFC future performance at both static and non-static conditions are investigated, using back propagation neural network (BPNN) and adapted neural fuzzy inference system (ANFIS), respectively. From the findings, PEMFC historical state and operating mode make varying contributions to PEMFC prognostic results at different operating scenarios. At static operating condition, PEMFC predictions are dominated by its historical state, since constant operating mode is applied in this scenario, thus reliable prediction can be made by using only parameters representing PEMFC historical state. However, at non-static operating condition, the varying operating mode makes more contribution to the PEMFC predictions, and accurate prognosis should be provided by including variables representing varying operating mode in the prognostic analysis. The results can be beneficial in selecting appropriate parameters in prognostic analysis at practical PEMFC applications, where complex operating conditions may be experienced.     

双磁极式磁粒研磨机理分析及试验研究

目的解决平面磁粒研磨中压力不均匀和需要反复调整研磨间隙的问题,设计双磁极式研磨方法。方法首先对双磁极式研磨方法机理进行分析,并对研磨区域单颗磨粒进行受力分析,寻找影响研磨压力的主要因素;其次利用Ansoft Maxwell软件对两种研磨方法进行磁场仿真,分析两种研磨方法的研磨区域磁场梯度变化,通过面积积分法对比磁感应强度的影响程度;最后设计试验装置,通过试验对理论分析及有限元分析的结果进行验证,对比研磨前后工件表面粗糙度及微观形貌变化。结果双磁极式研磨方法中磨粒的研磨压力完全由磁场力提供,与研磨区域磁感应强度成正比,研磨区域磁感应强度比"铣削式"研磨方法提高约34.56%。两种方法在相同试验条件下对SUS304不锈钢板研磨40 min,双磁极式研磨方法研磨后,工件表面原始纹理基本被去除,表面粗糙度值由原始的0.25μm下降至0.16μm,下降率为36%,比"铣削式"研磨方法提高约80%,粗糙度曲线波动平缓,波峰波谷高度差变化均匀且表面形貌光滑平整。结论双磁极式研磨方法研磨区域磁场梯度变化明显,利于磨粒流动更新,研磨压力相对稳定,表面粗糙度下降率高,研磨后工件表面形貌光整,与"铣削式"研磨方法相比具有较明显的优势。