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The purpose of this paper is to explore the possibility of an enhanced continuous liquid interface production (CLIP) with a porous track-etched membrane as the oxygen-permeable window, which is prepared by irradiating polyethylene terephthalate membranes with accelerated heavy ions.

Experimental approaches are carried out to characterize printing parameters of resins with different photo-initiator concentrations by a photo-polymerization matrix, to experimentally observe and theoretically fit the oxygen inhibition layer thickness during printing under conditions of pure oxygen and air, respectively, and to demonstrate the enhanced CLIP processes by using pure oxygen and air, respectively.

Owing to the high permeability of track-etched membrane, CLIP process is demonstrated with printing speed up to 800 mm/h in the condition of pure oxygen, which matches well with the theoretically predicted maximum printing speed at difference light expose. Making a trade-off between printing speed and surface quality, maximum printing speed of 470 mm/h is also obtained even using air. As the oxygen inhibition layer created by air is thinner than that by pure oxygen, maximum speed cannot be simply increased by intensifying the light exposure as the case with pure oxygen.

CLIP process is capable of building objects continuously instead of the traditional layer-by-layer manner, which enables tens of times improvement in printing speed. This work presents an enhanced CLIP process by first using a porous track-etched membrane to serve as the oxygen permeable window, in which a record printing speed up to 800 mm/h using pure oxygen is demonstrated. Owing to the high permeability of track-etched membrane, continuous process at a speed of 470 mm/h is also achieved even using air instead of pure oxygen, which is of significance for a compact robust high-speed 3D printer.

Endwall film cooling protects vane endwall by coolant coverage, especially at the leading edge (LE) region and vane-pressure side (PS) junction region. Strong flow impingement and complex vortexaa structures on the vane endwall cause difficulties for coolant flows to cover properly. This work aims at a full-scale arrangement of film cooling holes on the endwall which improves coolant efficiency in the LE region and vane-PS junction region.

The endwall film holes are grouped in four-holes constructal patterns. Three ways of arranging the groups are studied: based on the pressure field, the streamlines or the heat transfer field. The computational analysis is done with the k-ω SST model after validating the turbulence model properly.

By clustering the film cooling holes in four-holes patterns, the ejection of the coolant flow is stronger. The four-holes constructal patterns also improve the local coolant coverage in the “tough” regions, such as the junction region of the PS and the endwall. The arrangement based on streamlines distribution can effectively improve the coolant coverage and the arrangement based on the heat transfer distribution (HTD) has benefits by reducing high-temperature regions on the endwall.

A full-scale endwall film cooling design is presented considering interactions of different film cooling holes. A comprehensive model validation and mesh independence study are provided. The cooling holes pattern on the endwall is designed as four-holes constructal patterns combined with several arrangement choices, i.e. by pressure, by heat transfer and by streamline distributions.

Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.

Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.

Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.

This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.