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In view of the development status of high-reliability and low-cost cooling technology for radial turbine of micro-gas turbine or vehicle turbocharger, the impingement cooling technology of the radial turbine back disc was proposed, and the improvement of the cooling efficiency and thermal stress of the turbine back disc was numerically simulated. The results show that the impingement cooling technology can greatly improve the cooling efficiency of the turbine back disc and reduce the stress level. When the relative cooling flow is 1.0%–3.0%, the average cooling efficiency of the lower part of the turbine back disc is increased by 258%–486% compared with no cooling, which can reduce the thermal stress at the fillet of the back disc by 140–216 MPa. Both the average cooling efficiency and the fillet stress of the back disc increase slightly as the relative position of the jet hole moves outward. When the relative cooling flow is controlled within 2.0%, the effect of this cooling technology on the performance of the turbine can be ignored.

Deep understanding of biological superposition compound eye provides great opportunities in developing imaging systems with features beyond current planar detector array based imaging devices. However, artificial superposition compound eyes are designed on the basis of a planar detector array and that subsequently leads to the complex optical design and degradation of imaging quality inevitably. We propose a single-pixel superposition compound eye (SPSCE), whose imaging resolution has been improved two orders of magnitude than the number of ommatidia without subsequent image processing. SPSCE has the ability to capture the whole acceptable image of objects even if almost one-third of ommatidia at random positions are not working, which makes it possible to operate reliably even in the damaged state. SPSCE has the capacity to image beyond the actual visual field of the target without observing directly. With only one lateral sub-eye working and deviating from the visual field of the target by 20 . 41 ∘ , SPSCE obtains the complete and recognizable image of the target independently through the diffuse reflection optical information of the surrounding environment. The unique super-robust character of SPSCE with its super-resolution property contributes to developing anti-interference artificial compound eyes, unlocking the limit toward development of much higher imaging resolution artificial superposition compound eyes.

Due to the substantial reflection information of the surrounding environment, it is difficult for a conventional camera to directly capture the distinct image behind without interference from the reflected virtual image through semi-reflective media such as an acrylic plate, glass, or water. Traditional reflective artifact removal methods either demand a major commitment of calculations or constrained photography conditions such as the use of a polarizer, which often degrades the performance of the reflection removal process and imposes a limitation on the application area. A different reflection removal method is investigated, where the interfering light rays can be attenuated effectively based on a differential calculation with a Fourier single-pixel imaging method. Experiments show that this method eliminates the interference caused by reflection from interfering objects and obtains clear images through an acrylic plate (with thicknesses of 1 mm, 2 mm, and 3 mm), glass (5 mm), and even transparent water (100 mm). Another experiment has been carried out to effectively image the target by removing the reflection through the glasses, which have the same thickness (1.1 mm) but different reflectivity (20%, 30%, 40%, and 50%).

Single-pixel imaging (SPI), which uses a photodetector to detect the reflected total light intensity of a set of structured illumination patterns modulated by a target scene, provides a method for visible waveband imaging, hyperspectral imaging, and terahertz imaging. However, it faces a challenge when the scene to be imaged has specular reflections. To deal with this problem, a multi-angle method without feature matching is presented. With this method, the location of the detector does not affect image reconstruction, and the results of reconstruction at each location are matched at the pixel level automatically. In simulations, with the original image as a reference, the structural similarity index value of the picture obtained by the proposed method is 10% higher than the picture obtained from a single angle. The signal-to-noise ratio value of the picture obtained by the proposed method is 4.424, which is higher than 1.577 of the maximum value of the reconstruction result from a single angle. To evaluate the method, a metal key and an aircraft engine blade with specular reflections are taken as the target scene and are reconstructed from four different imaging perspectives, giving results that are matched at the pixel level. The final reconstructed image is obtained using the principal component analysis algorithm or the fourth-order partial differential equations and principal component analysis algorithm. Compared with the image obtained from a single angle, the correlation coefficient between the image obtained by the proposed method and the reference image is increased from the minimum value of 0.3139 to 0.7050, and the power ratio is increased from 4.52% to 73.63%. The proposed method has great potential specifically for improving the quality of SPI for scenes exhibiting specular reflections.

Near-infrared spectroscopy coupled with kernel partial least squares-discriminant analysis was used to rapidly screen water containing malathion. In the wavenumber of 4348 cm-1 to 9091 cm-1, the overall correct classification rate of kernel partial least squares-discriminant analysis was 100% for training set, and 100% for test set, with the lowest concentration detected malathion residues in water being 1 μg·ml-1. Kernel partial least squares-discriminant analysis was able to have a good performance in classifying data in nonlinear systems. It was inferred that Near-infrared spectroscopy coupled with the kernel partial least squares-discriminant analysis had a potential in rapid screening other pesticide residues in water.

This report describes a rapid, onsite method to analyze the dichlorvos pesticide in water. Dichlorvos is a broad-spectrum pesticide that has been used worldwide. As an organophosphorus pesticide, dichlorvos disrupts the nervous system by inhibiting the activity of acetyl cholinesterase. Traditional analysis of dichlorvos by chromatography is time-consuming and environmentally unfriendly. Therefore, rapid, on-site methods to analyze dichlorvos are needed. Here, we used for the first time Fourier transform near infrared spectroscopy combined with partial least square-discriminant analysis to determine the dichlorvos directly in water samples. Results were compared with traditional high-performance liquid chromatography data as reference. We found that over 9,000–8,333 cm−1, the new method had a good performance with a classification accuracy of 100 % and a correlation coefficient of 0.92 between measured and reference data. The new method can also be used as a “concentration sieve” by setting up different levels of boundary, a parameter of partial least square-discriminant analysis, thus allowing rapid on-site screening.