辐射板强化喷管换热与红外抑制效果试验研究

试验研究了在发动机喷管中加装金属辐射板前后,喷管壁面温度、热喷流温度与喷管红外辐射特征的变化。结果表明,加装金属辐射板后,热喷流与喷管壁面之间的热量传递显著增强,热喷流中心温度降低,壁面温度明显升高,在90°方向上,热喷流3～5μm波段的红外辐射强度降低了38.5%。文中从热喷流、喷管壁面以及金属辐射板等相关部件的温度变化情况对红外辐射强度的变化原因进行了解释。      

Dispersion modeling approach for quantification of methane emission rates from natural gas fugitive leaks detected by infrared imaging technique

Recently, infrared optical imaging has been applied in the oil and gas industry as a method to detect potential leaks in pipelines, components and equipment. The EPA suggested that this impending technique is considered as a smart gas LDAR (leak detection, monitoring and repair) for its rapid recognition of leaks, accuracy and robustness. In addition, compared to the conventional method using Total Vapor Analyzer (TVA) or gas sniffer, it has several other advantages, such as the ability to perform real-time scanning and remote sensing, ability to provide area measurement instead of point measurement, and provide an image of the gas which is not visible to naked eye. However, there is still some limitation in the application of optical imaging techniques; it does not give any measurement of gas emissions rates or concentrations of the leaking gas. Infrared cameras can recognize a target gas and distinguish the gas from its surrounding up to a certain concentration, namely the minimum detectable concentration. The value of the minimum detectable concentration depends on the camera design, environmental conditions and surface characteristics when the measurement is taken. This paper proposed a methodology to predict gas emissions rates from the size of the dispersed gas plume or cloud to the minimum detectable concentration. The gas emissions rate is predicted from the downwind distance and the height of the cloud at the minimum detectable concentration for different meteorological conditions. Gas release and dispersion from leaks in natural gas pipeline systems is simulated, and the results are presented.     

傅里叶红外光谱分析在环境试验中的应用

本文简要介绍了傅里叶红外光谱仪的原理和构造，综述了傅里叶红外光谱分析在环境试验中的应用以及分析、研究方法和技术。     

Removal and recycling of copper from aqueous solutions using treated Indian barks

Removal of copper from aqueous solutions containing 100–1000 ppm, using different Indian bark species, was performed on laboratory scale. The percentage removal of metal ions depends on the solution pH, bark species and time. The efficiency of copper removal by the used raw barks increases with a rise of solution pH and reaches a maximum of about 65–78% around pH 4–5. However, the decontaminated aqueous solutions were colored due to the dissolution of soluble organic compounds contained in the raw bark. This increases the biological and chemical oxygen demand (BOD and COD) of the solutions as well as the total organic carbon content (TOC). For this reason, raw bark should be treated either by chemical or biological means. Such treatment will allow the extraction of the soluble organic compounds and increase the chelating capacity and efficiency of the treated bark. Depending on the pH value, the chelating efficiency of treated barks is about 1.2–2.2 times that of the raw ones. Moreover, the retention capacity of the Indian treated bark varies from about 42–51 mg/g of dry bark. It is equal to or higher than that of common European species. About 1.8 mols of H₃O⁺ are released, by the treated barks, for every mol of chelated copper ions. Moreover, scanning electron microscopy (SEM) observations show uniform distribution of metal ions throughout the copper saturated bark. Infra red (IR) spectra suggest that the copper ions are chelated to hydroxyl and/or carboxyl functional groups of organic compounds contained in the treated bark. It seems that the interaction of the copper ions with the bark follows a cation exchange mechanism. This hypothesis is supported by elution experiments that allow recovery of about 99% of the contained copper. The retention capacity of the treated bark is almost constant after five cycles of chelation–elution, suggesting that the ‘life time cycle' is sufficiently long for continuous industrial application. The spent copper loaded barks can either be incinerated or pyrolysed. It generates solids containing either ≈80% of CuO or ≈14% of Cu°, respectively. Such materials can be used either in the secondary or primary copper production, thus offering a friendly environmental solution of effluents' treatment. The suggested process can be used as an alternative to the classical technologies for effluent decontamination. It is also efficient for polishing effluents treated by other methods.     

Infrared spectroscopic probing of dimethylamine clusters in an Ar matrix

Amines have many atmospheric sources and their clusters play an important role in aerosol nucleation processes. Clusters of a typical amine, dimethylamine (DMA), of different sizes were measured with matrix isolation IR (infrared) and NIR (near infrared) spectroscopy. The NIR vibrations are more separated and therefore it is easier to distinguish different sizes of clusters in this region. The DMA clusters, up to DMA tetramer, have been optimized using density functional methods, and the geometries, binding energies and thermodynamic properties of DMA clusters were obtained. The computed frequencies and intensities of NH-stretching vibrations in the DMA clusters were used to interpret the experimental spectra. We have identified the fundamental transitions of the bonded NH-stretching vibration and the first overtone transitions of the bonded and free NH-stretching vibration in the DMA clusters. Based on the changes in vibrational intensities during the annealing processes, the growth of clusters was clearly observed. The results of annealing processes indicate that DMA molecules tend to form larger clusters with lower energies under matrix temperatures, which is also supported by the calculated reaction energies of cluster formation.     

Microfluidic photomechanic infrared receptors in a pyrophilous flat bug

Infrared (IR) receptors are so far known only in boid and crotalid snakes and in three genera of pyrophilous beetles that seek out forest fires. Pyrophilous insects can also be found in other orders, however, so it can be hypothesised that IR receptors also occur in some of these species. We investigated the pyrophilous Australian flat bug Aradus albicornis and found a small number of dome-shaped sensilla (diameter 13 microm) on the prothorax, which have previously not been described. Ultrastructural investigations revealed that the sensilla are characterised by a fluid-filled inner compartment enclosed in a round cuticular shell. The cuticular apparatus is innervated by the dendrite of a ciliary mechanoreceptor, which is fluidically coupled to the inner compartment. Electrophysiological recordings demonstrated that the sensilla respond to brief warming by red laser light or to broadband IR radiation. Depending on the radiation intensity (4.4-549 mW/cm(2) tested, threshold measured as 11.3 mW/cm(2)), first spike latencies varied between 3.4 and 7.5 ms. Thus, our findings demonstrate that A. albicornis most probably possesses photomechanic IR sensilla resembling the metathoracic IR sensilla of buprestid beetles of the genus Melanophila. In the Melanophila sensillum, IR radiation causes thermal expansion of a fluid, which rapidly deforms the dendritic membrane of a mechanosensory cell. The existence of photomechanic IR receptors in both beetles and bugs demonstrates a remarkable convergent evolution towards this particular biophysical transduction mechanism and suggests that it provides selective advantages over other possible solutions.     

应用红外方法探讨耐镉菌株高积累Cd2+的机理

从安徽某冶炼厂污染土壤中分离出一株能耐高浓度镉的菌株(J5),经初步鉴定为假单胞菌属(Pseudomonas sp.).该菌株在液体培养基中耐受40 mmol·L-1 CdSO4,在固体培养基上耐受75mmol·L-1 CdSO4.培养基中Cd2+、Zn2+、Pb2+、Cu2+浓度分别为100 mg·L-1和Mn2+浓度为275mg·L-1时,菌株生长正常.在重金属Cu2+、Pb2+、Zn2+、Mn2+存在时,采用红外光谱与原子吸收光谱分析菌株对Cd2+的积累,结果表明,在低浓度Cd2+溶液中菌株细胞对Cd2+的积累,主要靠细胞壁上-NH2与Cd2+配位结合;在高浓度Cd2+溶液中,细胞壁上-NH2、-OH、-COOH、-PO43-、-M-O(O-M-O)基团吸附Cd2+的能力显著.Mn2+可以增加细胞壁上有效官能团活性,提高Cd2+积累率;但当有Zn2+、Pb2+、Cu2+重金属离子共存时,即使有Mn2+存在,菌体对Cd2+吸附积累能力未见提高.     

红外光谱法监测水中矿物油含量

本文提出了一种快速和准确监测水中矿物油环境污染指标的新方法。用多元线性回归和逐步回归法建立测油数学模型,对标准样液在３０００～２８００ｃｍ－１间的四个强吸收峰的光谱数据进行回归处理。对６３件用６种矿物油配制而成的浓度为０～４００ｍｇ／Ｌ的四氯化碳标准液进行了测定。实验结果表明,本文建立的红外光谱法测油模型对宽量程内的矿物油污染量有较好适应性。     

Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste. ● Feature selection methods were used to improve models’ prediction accuracy. ● The best model predicted C, H, and N contents with accuracy R ² ≥ 0.93, 0.87, 0.97. ● Some suitable models showed insensitivity to spectral noise. ● Under moisture interference, the models still had good prediction performance. Elemental composition is a key parameter in solid waste treatment and disposal. This study has proposed a method based on infrared spectroscopy and machine learning algorithms that can rapidly predict the elemental composition (C, H, N, S) of solid waste. Both noise and moisture spectral interference that may occur in practical application are investigated. By comparing two feature selection methods and five machine learning algorithms, the most suitable models are selected. Moreover, the impacts of noise and moisture on the models are discussed, with paper, plastic, textiles, wood, and leather as examples of recyclable waste components. The results show that the combination of the feature selection and K-nearest neighbor (KNN) approaches exhibits the best prediction performance and generalization ability. Particularly, the coefficient of determination (R²) of the validation set, cross validation and test set are higher than 0.93, 0.89, and 0.97 for predicting the C, H, and N contents, respectively. Further, KNN is less sensitive to noise. Under moisture interference, the combination of feature selection and support vector regression or partial least-squares regression shows satisfactory results. Therefore, the elemental compositions of solid waste are quickly and accurately predicted under noise and moisture disturbances using infrared spectroscopy and machine learning algorithms.