基于显示连通贝叶斯网络的机场塔台地震易损性分析

将基于性能的多维易损性分析方法,结合显示连通贝叶斯网络,应用于机场塔台的多维易损性分析。考虑地震激励的不确定性,通过非线性时程分析获得结构响应数据;将塔台结构分为三个层次,每个层次按包含的层数分为相应的子层次。根据功能特性确定子层次的评价指标和极限状态,建立服从多元对数正态分布的概率地震需求模型;考虑各种极限状态之间的相关性,建立极限状态方程,确定失效域,通过蒙特卡洛法求得构件的超越概率;建立塔台结构的显示连通贝叶斯网络模型,利用层次分析法获得中间节点的条件概率表,利用MATLAB进行贝叶斯网络的推理计算,实现从单一层次的易损性到整体易损性的推理。     

Real-time assessment of carbon nanotube alignment in a polymer matrix under an applied electric field via polarized Raman spectroscopy

A technique has been developed utilizing polarized Raman spectroscopy to measure alignment of carbon nanotubes in situ in a polymer matrix under an applied electric field. Previous studies of alignment have been restricted to optically transparent solvents or polymerized specimens that prevent accurate analyses of alignment dynamics in polymers. The effects of electric field strength on the degree of alignment and the time to achieve an aligned state are discussed. The use of in situ, real-time polarized Raman spectroscopy provides a non-invasive technique for assessing carbon nanotube alignment, which can assist in determining processing conditions to improve the mechanical and electrical properties of aligned nanocomposites.     

Artificial Intelligence Computation to Establish Relationships Between APS Process Parameters and Alumina–Titania Coating Properties

Modeling the behavior of air plasma spray (APS) process, one of the challenges nowadays is to identify the parameter interdependencies, correlations and individual effects on coating properties, characteristics and influences on the in-service properties. APS modeling requires a global approach which considers the relationships between coating characteristics/ in-service properties and process parameters. Such an approach permits to reduce the development costs. This is why a robust methodology is needed to study these interrelated effects. Artificial intelligence based on fuzzy logic and artificial neural network concepts offers the possibility to develop a global approach to predict the coating characteristics so as to reach the required operating parameters. The model considered coating properties (porosity) and established the relationships with power process parameters (arc current intensity, total plasma gas flow rate, hydrogen content) on the basis of artificial intelligence rules. Consequently, the role and the effects of each power process parameter were discriminated. The specific case of the deposition of alumina–titania (Al₂O₃–TiO₂, 13% by weight) by APS was considered.     

Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.     

Atomically Dispersed Iron Regulating Electronic Structure of Iron Atom Clusters for Electrocatalytic H2O2 Production and Biomass Upgrading

The integration of highly active single atoms (SAs) and atom clusters (ACs) into an electrocatalyst is critically important for high-efficiency two-electron oxygen reduction reaction (2e⁻ ORR) to hydrogen peroxide (H₂O₂). Here we report a tandem impregnation-pyrolysis-etching strategy to fabricate the oxygen-coordinated Fe SAs and ACs anchored on bacterial cellulose-derived carbon (BCC) (FeSAs/ACs-BCC). As the electrocatalyst, FeSAs/ACs-BCC exhibits superior electrocatalytic activity and selectivity toward 2e⁻ ORR, affording an onset potential of 0.78 V (vs. RHE) and a high H₂O₂ selectivity of 96.5 % in 0.1 M KOH. In a flow cell reactor, the FeSAs/ACs-BCC also achieves high-efficiency H₂O₂ production with a yield rate of 12.51±0.18 mol g_cat⁻¹ h⁻¹ and a faradaic efficiency of 89.4 %±1.3 % at 150 mA cm⁻². Additionally, the feasibility of coupling the produced H₂O₂ and electro-Fenton process for the valorization of ethylene glycol was explored in detail. The theoretical calculations uncover that the oxygen-coordinated Fe SAs effectively regulate the electronic structure of Fe ACs which are the 2e⁻ ORR active sites, resulting in the optimal binding strength of *OOH intermediate for high-efficiency H₂O₂ production.     

基于AHP-DEMATEL法的权重计算方法研究

权重是重要程度的体现形式,常用于系统评价过程.AHP就是一种将定性问题定量化,既简单又灵活的权重计算方法,但将复杂问题简单化会常常忽略因素之间的相互影响,可能造成结果的偏差.围绕系统评价中权重计算问题,提出了改进的AHP-DEMATEL的方法,通过计算初始权重和影响度、被影响度,并将被影响度融入到影响权重中,从而获得综合权重.方法不仅考虑了各风险因素在风险指标系统中对上层指标的作用,而且考虑了风险因素之间的依存关系避免单个专家意见的局限性,也降低了信息过渡使用所带来的评价误差.将改进后的方法用于物流信息集成风险的因素关系分析的实例,实证表明,改进方法在物流信息集成风险分析中的应用不仅简化了计算过程而且更加逼近现实情况,为决策者提供更为科学、准确的决策依据.     

基于层次分析法的风洞试验装备全寿命健康因素量化评价方法研究

针对风洞试验装备健康管理面临的实际问题,基于层次分析法(AHP)确定装备全寿命过程中影响装备健康的因素体系,并计算各类因素所占的权重,建立了量化评价模型和反馈修正方法,并给出了该方法在风洞试验装备健康管理工作中的实际应用流程。     

The effects of ultrasound on micromixing

The Villermaux–Dushman reaction is a widely used technique to study micromixing efficiencies with and without sonication. This paper shows that ultrasound can interfere with this reaction by sonolysis of potassium iodide, which is excessively available in the Villermaux–Dushman solution, into triiodide ions. Some corrective actions, to minimize this interference, are proposed. Furthermore, the effect of ultrasonic frequency, power dissipation, probe tip surface area and stirring speed on micromixing were investigated. The power and frequency seem to have a significant impact on micromixing in contrast to the stirring speed and probe tip surface area. Best micromixing was observed with a 24 kHz probe and high power intensities. Experiments with different frequencies but a constant power intensity, emitter surface, stirring speed, cavitation bubble type and reactor design showed best micromixing for the highest frequency of 1135 kHz. Finally, these results were used to test the power law model of Rahimi et al. This model was not able to predict micromixing accurately and the addition of the frequency, as an additional parameter, was needed to improve the simulations.     

Optimising reaction performance in the pharmaceutical industry by monitoring with NMR

Quality assurance and process understanding are assuming increasing importance in the production of Active Pharmaceutical Ingredients (APIs). NMR has the potential to report on physical processes, quantities, structures, and speciation as chemical reactions progress. Following the progression of chemical reactions by placing the sample in an NMR tube, one can perform a large number of useful studies that provide chemical and mechanistic insight. But this simple approach can have limitations, and we have therefore constructed an apparatus comprising a laboratory reactor coupled with an NMR flow cell. The reactor duplicates the exact reaction conditions that will apply with large-scale production. This reaction mixture is sampled and pumped to a high-resolution NMR flow cell where the spectrum is recorded through the course of the reaction. We demonstrate the utility of reaction monitoring using NMR both for simple cases where tubes can be used, and describe the design of the on-flow apparatus and highlight its utility with an example.     

Calibration transfer strategy to compensate for instrumental drift in portable quadrupole mass spectrometers

We report the use of a calibration transfer strategy to correct for drift in the quantitative sensitivity of a portable quadrupole mass spectrometer (QMS) aimed at process monitoring applications. Gas mixtures of CH₄/Ar/C₂H₆/CO₂ were studied with calibration phase measurements made of the pure gases for a univariate analysis and of 40 multi-component mixtures for a multivariate approach. To evaluate calibrations, test set spectra of a CH₄/Ar/C₂H₆/CO₂ gas mixture were recorded bi-weekly over a period of 12 months. As part of the strategy a standard of pure argon was measured during both calibration and test phases so that correction factors could be calculated for each measurement day. It was shown that in the absence of a calibration transfer strategy quantifications of test set spectra could be inaccurate by more than an order of magnitude over 12 months. Furthermore, due to the effects of drift in the sensitivity over the 6 days required to record the training set in the calibration phase it was found that the multivariate analysis quantified test spectra less accurately than the univariate analysis. However, by applying the calibration transfer strategy across all measurements (both calibration and test phases) it was shown that the errors in prediction using the multivariate analysis previously seen after 2 weeks were not observed until approximately 12 months later.