基于改进云推理算法的塔架结构损伤识别

为了解决塔架结构的损伤识别问题,提出了基于应变能和改进云推理算法的损伤识别方法。首先描述了云模型的基本理论和数字特征,并给出了模态应变能的基本公式;然后分析了X条件云发生器和Y条件云发生器的基本算法和运行步骤,借助灰云模型建立相应的前件云和后件云规则,考虑了测量噪声的影响,利用云发生器生成多组云滴,并利用多模式下云滴的确定度和生成值构建了基本云推理算法及其损伤识别指标。基本云推理算法中常会产生不均匀发散的云滴,从而使计算结果产生一定的偏差,为了降低云滴发散产生的偏差影响,提出了基于损伤模式数量加权的云推理改进策略。计算结果表明:云推理算法可以较好地应用于塔架结构的损伤识别,其识别结果明显优于传统的应变能耗散率指标方法;而改进云推理算法进一步提高了识别的精度,优于基本云推理算法。     

基于L1正则化的随机梁式结构静力损伤识别方法

提出了一种结合摄动法和L1正则化方法的随机梁式结构静力损伤识别方法。考虑初始模型误差和测量误差的影响,建立了关于随机损伤指数的控制方程,并将摄动法和L1正则化方法相结合,对随机损伤指数的控制方程进行求解,进而从概率的角度对结构的损伤进行识别。损伤试验结果表明,和传统的最小二乘求解法相比,本文方法能够更为准确地识别多处局部损伤的位置及大小,对实际结构损伤检测具有较好的参考价值。     

Experimental Investigation of the Effect of Purge Flow and Main Flow Interaction in a Low-Speed Turbine Cascade Passage

In order to protect the vulnerable turbine components from extreme high temperature, coolant flow is introduced from the compressor to the disk cavity, inevitably interacting with the main flow. This paper describes an experimental investigation of the interaction between the main flow and the purge flow in a low-speed turbine cascade with three purge flow rates, Cm = 0, Cm = 1%, and Cm = 2%. In order to study the effect of the interaction between the main flow and the purge flow on the secondary flows, a Rortex method developed by Liu Chaoquan is introduced to identify the vortex in the flow field. In the meantime, a method to calculate the mean entropy production rate based on the particle image velocimetry (PIV) result is adopted to investigate the flow loss. The PIV result indicates that the purge flow has a prominent impact on the flow field of the cascade passage, changing the velocity distribution that induces a local blockage area. The results of vortex identification show that the purge flow promotes the generation of the passage vortex near the suction side. In addition, the purge flow makes the passage vortex migrate to the tip wall direction, enlarging the region affected by the secondary flow. The mean entropy production (MEP) result shows that the flow loss is mainly caused by the passage vortex. The coincidence of the high-MEP region and the location of the passage vortex indicates that the purge flow increases the secondary flow loss by affecting the formation and the migration of the passage vortex.     

纸基PVA无芯片RFID湿度传感器

传统湿度传感器制造工艺复杂、需有线连接信号,对此,文中提出一种纸基无芯片射频识别(Radio Frequency Identification, RFID)湿度传感器。为提升传感器谐振特性,选择非对称开口环内部分布式加载金属碎片作为传感器结构,聚乙烯醇(PVA)作为湿敏材料,使用遗传算法和HFSS射频仿真软件来设计并优化传感器结构。以喷墨打印技术制作传感器样品,采用滴涂法在传感器表面分别制备了5%、10%、15%三种质量浓度比的PVA薄膜。湿敏特性仿真及测试结果一致表明：PVA与纸基底协同作用可显著提高传感器灵敏度。随PVA浓度增加灵敏度增加,15%PVA传感器灵敏度最高,高湿灵敏度达到12.22 MHz/%RH,但随PVA浓度增加恢复特性变差,5%PVA湿度传感器具有良好的恢复特性,恢复度达83.87%。通过长期多次实验验证了PVA纸基湿度传感器具有良好的温度稳定性与中长期稳定性。与同类研究成果对比,文中设计在感湿范围及灵敏度方面有优势且制造工艺更简单,为低成本湿度传感器的大规模使用提供了可能。     

自动化质谱图解卷积和鉴定系统用于鉴定含痕量杂原子的石油馏分（英文）

Here we present a simple yet effective gas chromatography-mass spectrometry (GC-MS) identification approach for the detection of heteroatom-containing compounds (HACCs) in petroleum fractions. The MS/AMDIS (Automated Mass Spectral Deconvolution and Identification System) program was used to identify parts per million (ppm) HACC concentrations in petroleum fractions in place of traditional techniques (extraction and standard injection). Polycyclic aromatic sulfur heterocycles (S-PAHs) were used as model compounds to confirm the validity of the AMDIS identifiers, which were compared with extracted results using the off-line X-calibur software. AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate. There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate. AMDIS was also used to detect nitrogen-containing compounds (NCCs) and alkylphenols in oil condensate. Our results confirmed the presence of 2-methylbenzothiazole, carbazole, and 2,4-ditertbutyl phenol. In a crude oil sample, AMDIS identification of m/z=191 biomarkers was consistent with empirical results. Therefore, AMDIS can help to reduce the number of experimental steps in identification protocols.     

基于线上线下结合的无机定性分析实验教学

针对在实验室开设定性分析实验受到的制约,设计并开设了"无机化合物的性质与鉴定"虚拟实验,以作为常规无机定性分析实验的重要补充和扩展。虚拟实验和传统实验一并开设,构成线上线下结合的教学模式,完善知识体系,全面培养学生的无机定性分析能力。     

钳蝎毒中抗癫痫肽、镇痛肽和抗肿瘤肽的快速同时分离和鉴定

采用Shim-Pack WCX-1型阳离子交换高压色谱柱对中国东亚钳蝎全蝎毒进行了分离，在鉴定了其中的抗癫痫肽、镇痛肽和抗肿瘤肽活性峰的基础上，应用Shim-Pack DIOL-300型凝胶排阻高压色谱柱对它们进行了进一步分离和鉴定，可以得到较纯的3种多肽。在高压色谱所提供的全蝎毒分离信息的基础上，应用与Shim-Pack WCX-1色谱柱具有相同交换基团的、具有较大吸附容量的CM Sepharose CL-6B软胶介质在低压色谱上对全蝎毒进行了分离，并分别对其中的抗癫痫肽、镇痛肽和抗肿瘤肽进行了鉴定。     

大鼠体内复方清开灵代谢物的分析

建立了复方中药清开灵代谢物的液相色谱-质谱/质谱分析方法。采用Phenomenex Luna C18色谱柱,以0.1%甲酸(A)及V(甲醇)∶和V(乙腈)=4∶1混合液(B)作流动相,采用梯度洗脱(0 min,B为0%;33min,B为60%;66 min,B为88%;75 min,B为100%),流速:0.5 mL/min,离子阱质谱负离子模式进行检测。通过差谱方法对可能的代谢物进行快速搜索。对发现的重要的代谢物根据分子量以及多级质谱的碎片离子数据,结合体内代谢反应规律,进行指认和结构鉴定。共鉴定了3个主要的代谢物,其中一个为黄芩苷的代谢物,另两个为绿原酸的代谢物,后两个代谢物未见文献报道。本实验为研究复方中药复杂体系体内的代谢产物提供了一个有效而且快捷的模式。     

高效毛细管电泳法分析蓝色签字笔字迹色痕种类及相对形成时间

选用毛细管区带电泳分离模式,对13种市售蓝色签字笔样品字迹色痕进行了分析。当电压为15 kV、柱温为25 ℃时,以0.03 mol/L 四硼酸钠水溶液(外加10%(体积分数)的甲醇)为缓冲液,所有样品都可以得到良好的区分;依据紫外区检测结果,样品可以分为三大类、五小类;依据可见区检测结果,样品可以分为四类;两种分析结果相结合有助于增大不同样品之间的区分度;选择3种样品进行暗处保存老化制样,根据字迹中色料成分相对含量的变化,对字迹的相对形成时间进行了初步探讨。研究还发现纸张类型对于上述研究结果无影响。     

土壤重金属污染来源及其解析研究进展

土壤重金属污染问题是环境和土壤科学研究者关注的热点问题。对土壤重金属污染物来源的鉴别是准确、有效控制和治理污染源的前提。根据近年来国内外对土壤重金属污染的相关研究报道,综述了土壤中污染物的工业、农业和交通因子三大主要来源,重点阐述了目前解析土壤重金属污染来源所运用的化学形态研究、剖面分布、同位素示踪、空间分析和多元统计等方法,并就存在的问题和今后的研究重点进行了总结。