Ye Wan

The TiO₂-SiO₂-Al₂O₃ composite coatings were fabricated on the surfaces of Q235 carbon steel via the sol-gel method to improve its corrosion resistance. The effects of the sintering temperature and the layer number on the corrosion performances were explored. The coating morphology, microstructure and phase composition were analyzed by scanning electron microscopy (SEM) and X-ray diffractometer (XRD). Friction wear experiment, immersion experiment, and electrochemical impedance spectroscopy techniques were used to investigate the corrosion properties of the coatings as well. The results show that the sample with the TiO₂-SiO₂-Al₂O₃ coatings sintered at 850 °C are more uniform and denser and have better corrosion resistance and wear resistance than the other coatings. The Rp value of the 3 L coating sintered at 850 °C was about 114 kΩ·cm², and the average friction coefficient was about 0.36.

Degradability is vital for bone filling and plays an important role in bone regeneration. Evidence indicates that apatite-based calcium phosphate cement (ACPC) is a prospective biomaterial for bone repair with enhanced osteogenesis. However, poor degradability restricts their clinical application. In this study, MgZnCa-doped ACPC (MgZnCa/ACPC) composites were fabricated by adding 3 (wt) % amorphous MgZnCa powder in the solid phase of ACPC to enhance the biodegradation and bioactivity of the apatite ACPC. The chemical and the physical properties of the MgZnCa/ACPC composite were investigated and compared with the ACPC composite. The results showed that the incorporation of MgZnCa improved both the degradability and the compressive strength of the ACPC composite. X-ray diffraction and Fourier transform infrared spectrometry analysis suggested significant changes in the microstructures of the composites due to the incorporation and the anodic dissolution of MgZnCa alloy. These findings indicate that the MgZnCa/ACPC composite is capable of facilitating bone repair and regeneration by endowing favorable degradation property.

In this study, a novel composite membrane was developed by casting the mixed aqueous solution of chitosan (CS) and polyvinyl alcohol (PVA) on a glass fiber microporous membrane. The polymeric coating of a composite membrane containing amino groups and hydroxyl groups has a favorable CO₂ affinity and provides an enhanced CO₂ transport mechanism, thereby improving the permeance and selectivity of CO₂. A series of tests for the composite membranes were taken to characterize the chemical structure, morphology, strength, and gas separation properties. ATR-FTIR spectra showed that the chemical structure and functional group of the polymer coating had no obvious change after the heat treatment under 180 °C, while SEM results showed that the composite membranes had a dense surface. The gas permeance and selectivity of the composite membrane were tested using single gases. The results showed that the addition of chitosan can increase the CO₂ permeance which could reach 233 GPU. After a wetting treatment, the CO₂ permeance (454 GPU) and gas selectivity (17.71) were higher than that of dry membranes because moisture promotes the composite membrane transmission. After a heat treatment, the permeance of N₂ decreased more significantly than that of CO₂, which led to an increase in CO₂/N₂ selectivity (10.0).

Electrochemical and surface analysis methods were used to investigate the pitting susceptibility and propagation of as‐received and dry‐wet cycle exposed 5083 aluminum alloy (AA5083) specimens. We find that dry‐wet cycle exposure can reduce the corrosion potential, while increasing the corrosion current density, pitting potential (E_p), and passivation range. The pitting corrosion behavior during the dry‐wet cycle process depends on the exposure temperature and time. Increased exposure temperature and time result in reduced pitting percentage and corrosion altitude and decreased microhardness of the corrosion products, which promotes the pitting sensitivity of AA5083. The underlying pitting mechanism is proposed by employing the morphology and microstructures of the corrosion products.

There are many factors affecting the total construction duration of power transmission and transformation project, resulting in low accuracy of construction duration prediction. And the traditional construction duration prediction method has some limitations to a certain extent. The prediction results mainly rely on historical information materials and expert judgment, so it has always been the difficulty of prediction. Aiming at the existing problems, a total construction duration prediction method of power transmission and transformation project based on BP neural network theory is proposed. The theory has high generalization ability and the ability to solve nonlinear influencing factors, which can greatly improve the accuracy of construction duration prediction.

The purpose is to solve the problems of cumbersome calculation, low accuracy, poor timeliness, rigid data acquisition, high cost, large volume, and insufficient signal processing capacity of traditional vision sensor (VS) in Ningxia companies. Firstly, this paper designs an embedded smart VS based on advanced RISC machines (ARM) processor. Secondly, it proposes a cost estimation algorithm for power transmission and transformation project (PTTP) based on particle swarm optimization-least squares support vector regression (PSOLSSVR). Afterward, a cost estimation model of PTTP based on building information modeling (BIM) is proposed. Thirdly, historical cost data of PTTP of a Ningxia company within five years are selected as data samples to verify the accuracy of the PSO-LSSVR estimation algorithm and BIM model. The results show the following: (I) The measurement error of the designed smart VS is less than 4, with high accuracy, which is suitable for large-scale measurement in the construction site. (II) The error of the PSO-LSSVR algorithm in engineering cost prediction is less than 20, and the accuracy is higher than that of traditional support vector machine (SVM) and LSSVR algorithms. The optimization effect is remarkable and can be used for the feasibility analysis of PTTPs. (III) The proposed BIM-based PTTP cost estimation model error in the project cost estimation is controlled within 10. With high accuracy, it can be applied to the PTTP management of Ningxia company. The purpose is to provide important technical support for the upgradation of traditional VS technology and the realization of visual management and rapid cost estimation of PTTP of Ningxia companies.