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Based on deep learning MVS methods, neural networks suffered from a large number of parameters and high GPU memory consumption. To address this issue, a lightweight deep convolutional recurrent network recurrent network-based MVS method was proposed. Firstly, the original images passed through a lightweight multi-scale feature extraction network to obtain high-level semantic feature maps. Then, a sparse cost volume to reduce the computational workload was constructed. Next, GPU memory consumption was reduced by using a simple plane sweeping technique that utilized by a convolutional recurrent network for cost volume regularization. Finally, sparse depth maps were extended to dense depth maps using an extension module. With a refinement algorithm, the proposed approach achieved a certain level of accuracy. The proposed approach was compared to state-of-the-art methods on the DTU dataset including traditonal MVS methods Camp, Furu, Tola, and Gipuma, and also including deep learning- based MVS methods SurfaceNet, PU-Net, MVSNet, R-MVSNet, Point-MVSNet, Fast-MVSNet, GBI-Net, and TransMVSNet. The results demonstrated that the proposed approach reduced GPU consumption to approximately 3.1 GB during the prediction stage, and the differences in precision compared to other methods were relatively small. [ABSTRACT FROM AUTHOR]

In this study, the structural characteristics of TiN coatings deposited by DC magnetron sputtering on the surface of AISI 304 stainless steel were modulated by performing deposition at four different nitrogen flux ratios. The XRD results indicated that the coatings mainly contained face-centered cubic TiN phase. The experimental results showed that the nitrogen flux ratio played a major role in determining the microstructure and the mechanical and tribological properties of the TiN coatings. SEM images revealed that the thickness of the TiN coatings decreased linearly as the nitrogen flux ratio increased from 0.25 to 0.55. However, the grain size had a nonlinear relationship with the nitrogen flux ratio. When the nitrogen flux ratio was 0.45, the grain size was only 5.3 nm. Theoretical and experimental analysis showed that the TiN coating deposited at a nitrogen flux ratio of 0.45 had the best mechanical properties, which due to its minimum grain size and (111) orientation, and the best tribological performance under unlubricated conditions, may have been due to its higher fracture toughness and plastic deformation resistance among the four TiN coatings. [ABSTRACT FROM AUTHOR]

To explore the friction and wear properties of TiN coating under oil lubrication,TiN coatings were deposited on AISI304 stainless steel by magnetron sputtering technology.The effect of nitrogen flux ratio on the microstructure and mechanical properties of TiN coatings,as well as their tribological performance under lubrication of rapeseed oil were studied by using SEM,nano-scratch meter,XRD,XPS and tribotester.The experimental results show that the TiN coating deposited at the nitrogen flux ratio of 0. 45 has denser crystal structure and better mechanical properties.The friction coefficient and wear rate of TiN coatings decrease firstly and then increase with the increase of nitrogen flux ratio, and both of them are minimum when the nitrogen flux ratio is 0. 45 under lubrication of rapeseed oil. XPS analysis of the wear scar shows that the existence of oxidation layer on the surface of TiN coating increases the wettability of rapeseed oil on the surface of the coating,leading to good lubricating properties. Compared with olive oil, polyalphaolefin (PA06) base oil and 5W40 oil,TiN coating exhibits better lubrication performance when lubricated by rapeseed oil. [ABSTRACT FROM AUTHOR]

In order to solve the practical problems of streets, create a pleasant street space and improve the participation of designers and users, the process and method of street renewal based on innovative design thinking were put forward on the basis of the core idea of "user centered" design thinking. The main steps included: setting up workshop and establishing project, understanding and observation, synthesis, creativity, prototype and test feedback. Taking the streets around Anju Dongcheng Community in Handan City as an example, the main process included setting up workshops, carrying out research and data analysis, focusing on outstanding issues, putting forward a variety of renewal and transformation schemes, scheme testing and prototype expression. The whole practice process improved the designer's design thinking ability, enhanced the participation consciousness of street users, and provided a new idea for street renewal design. [ABSTRACT FROM AUTHOR]

Nanofluid minimum quantity lubrication is an environmental-friendly, resource-saving, and sustainable process compared with traditional flood lubrication. Especially, it is widely applied in difficult-to-cutting material, such as Ti-6Al-4V. However, optimized process parameters have not been obtained with considering grinding temperature, tangential grinding force, specific grinding energy, and surface roughness (Ra). And it is important for reaching the best surface quality and highest grinding efficiency. Henceforth, grinding parameters were set reasonably through an orthogonal experiment in this study and they were optimized preliminarily through a signal-to-noise analysis, getting four optimal groups of single grinding parameter. Next, a grey relational analysis was implemented based on the optimal signal-to-noise analysis of signal objective, getting two optimal combinations of multiple objectives. Finally, surface qualities in several groups of optimized experiments were characterized and analyzed by the profile supporting length ratio, surface morphology, and energy spectra. Furthermore, the grinding efficiency experiment was evaluated by material removal rate and specific grinding energy based on satisfying workpiece surface quality, and the optimal parameter combinations of surface quality and processing efficiency were gained. Research results provide theoretical basis for industrial production. [ABSTRACT FROM AUTHOR]