Porous SiC using polycarbosilane/camphene solutions: Roles of freeze casting parameters

In order to control the pore characteristics and macroscopical performance of porous ceramics, roles of the freeze casting parameters are the key points. Herein, aligned dendritic porous SiC was fabricated by freeze casting of PCS-camphene solutions with different solid loading, freeze front velocity, temperature gradient, and freezing temperature. Influence of these parameters on the microstructure and compressive strength of porous SiC was investigated. With increasing the PCS content, freeze temperature, freeze front velocity or temperature gradient, degree of undercooling of the camphene was increased, resulting in the formation of smaller pore size, decreased porosity and increased compressive strength. Compared to variables of freeze temperature and temperature gradient, increased freeze front velocity was more efficiency in improving the compressive strength of porous SiC, owing to the formation of smaller pore size and longer secondary dendritic crystals. Promising micron-sized porous SiC with high porosity (79.93 vol%) and satisfactory strength (15.84 MPa) was achieved for 10% PCS-camphene solution under optimized freezing conditions.     

An ultrasonic study on ternary xPbO–(45-x)CuO–55B2O3 glasses

A series of xPbO–(45-x)CuO–55B₂O₃ glasses (5 ≤ x ≥ 40 mol %) were prepared by the melt-quenching technique. The X-ray diffraction (XRD) patterns of the prepared glasses are found to have amorphous structure. An extensive ultrasonic study has been made to explore the structural role of PbO and CuO in the borate network. Various elastic properties were calculated from the measured data of density and ultrasonic velocity. Ultrasonic velocity and elastic moduli revealed broad humps at about 20 mol % PbO, which are attributed to the borate anomaly. Below 20 mol % PbO, all Pb²⁺ ions are considered to be entering the borate network as a glass modifier. This results in the transforms the borate network from an open structure to a denser three-dimensional structure due to BO₃ → BO₄ conversion. Beyond 20 mol, addition of PbO results in the formation of metaborate, pyroborate, and orthoborate units with NBOs. This weakness the glass structure and decrease both ultrasonic velocity and elastic moduli. The elastic properties were predicted and quantitatively analyzed by taking into account the effect of boron coordination number on the compositional and structural parameters involved in Makishima–Mackenzie's theory, ring deformation model and bond compression model. An excellent agreement between the computed theoretical and experimental elastic moduli, micro-harness and Poisson's ratio was achieved for majority of samples.     

Self-Adaptive Control System for Additive Manufacturing Using Double Electrode Micro Plasma Arc Welding

Wire arc additive manufacturing(WAAM)has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost.However,in the process of automatically manufacturing the high-quality metal parts by WAAM,several problems about the heat build-up,the deposit-path optimization,and the stability of the process parameters need to be well addressed.To overcome these issues,a new WAAM method based on the double electrode micro plasma arc welding(DE-MPAW)was designed.The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically.The effects between the parameters,wire feed rate and torch stand-off distance,in the process of WAAM were investigated experimentally.In addition,a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance.Finally,a series of tests were performed to evaluate the con-trol system's performance.The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system.Further,the deposition paths about the metal part's layer heights in WAAM are simplified.Finally,the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.     

复杂地质条件下地下厂房吊车梁岩壁成型控制爆破

针对雅安小关子水电站地下厂房吊车梁岩壁的特点 ,提出了对岩壁保护层的双层光面爆破方案及主要的爆破参数。爆破效果表明 ,所确定的控制爆破方案及设计参数是正确的 ,为类似的控制爆破工程提供了有益的经验     

5万m~2地下特大型支撑爆破拆除

介绍了在复杂环境下爆破拆除一地下特大钢筋混凝土支撑的技术难点。由于合理选取爆破参数,采取孔内高段、孔外低段毫秒微差起爆网路,安全防护采取覆盖、近体、保护性三种措施,有效地阻止了飞石对周围建筑物的损害,并对爆破可能产生的危害进行了科学验算,最后分多次爆破圆满完成拆除任务。     

Double-layer fuzzy adaptive NMPC coordinated control method of energy management and trajectory tracking for hybrid electric fixed wing UAVs

The energy management and trajectory tracking control are crucial to realize long-endurance autonomous flight for hybrid electric UAVs. This study aims to comprehensively consider energy management and trajectory tracking for hybrid electric fixed wing UAVs with photovoltaic panel/fuel cell/battery. A double-layer fuzzy adaptive nonlinear model predictive control method (DFNMPC) is proposed. Separated by the surplus demand power, energy management and trajectory tracking problem are decoupled into the high-layer fuzzy adaptive nonlinear model predictive controll problem (H-FNMPC) and low-layer fuzzy adaptive nonlinear model predictive controll problem (L-FNMPC). H-FNMPC solves the trajectory tracking and navigation control probelm for the greatest benefit of solar energy. L-FNMPC solves the power allocation problem of hybrid energy system for minimum equivalent hydrogen consumption. A fuzzy adaptive prediction horizon adjustment method based on UAV maneuvering degree is proposed to effectively improve proposed method adaptability to different mission profiles. Analogously, a fuzzy adaptive equivalent hydrogen consumption factor adjustment method in L-FNMPC is proposed to ensure the flexible utilization of battery. In addition, an equivalent hydrogen flow rate calculation method based on the real-time current ratio is proposed for PV/FC/Battery hybrid energy system. Numerical simulation results including a spiral trajectory tracking and a quadrilateral trajectory tracking, demonstrate that DFNMPC can simultaneously handle energy management and trajectory tracking problem for hybrid electric UAVs. Compared to hierarchical fuzzy state machine strategy, DFNMPC can save 13.3% hydrogen for the spiral trajectory tracking, and 56.9% for the quadrilateral trajectory tracking. It indicates that the energy efficiency can be improved from both levels of energy management and flight motion. The proposed method prospected for exploring high-energy-efficiency autonomous flight of hybrid electric UAVs in the future.     

Three-dimensional and anisotropic numerical analysis of a PEM fuel cell

In this study, the effects of cell temperature and relative humidity on charge transport parameters are numerically analyzed. In order to perform this analysis, three-dimensional and anisotropic numerical models are developed. The numerical models are integrated into the experimental values for anisotropic electrical conductivities, as depending on cell temperature and relative humidity, that were obtained from our previous study. The achieved results indicate that the values of current densities in the in-plane direction increase with increasing cell temperature and relative humidity, while the current densities reach a maximum in the rib regions for both the numerical model at the through-plane direction. The behaviors of electrolyte potentials are similar with changes in the cell temperature and relative humidity. In addition, the cathode electrical potentials in both the in-plane direction and through-plane direction do not change to a considerable amount with increasing cell temperature and relative humidity.     

From modification to mechanism: Supercritical hydrothermal synthesis of nano-zirconia

Nano-zirconia has been widely applied due to its excellent physical and chemical properties (e.g., high strength, corrosion resistance, oxygen ion conductivity). Existing preparation methods of nano-zirconia tend to require long reaction time, and the sizes of final particles are large with uneven distributions. Sub-/supercritical hydrothermal synthesis of nanoparticles is favored by researchers owing to controllable reaction process, uniform particle size distribution, good reproducibility, short reaction time, high conversion rate and harmlessness to environment. In this paper, the characteristics and mechanisms of dissolution, crystallization and growth of nano-zirconia during sub-/supercritical hydrothermal synthesis are systematically reviewed. The influences of process and material parameters on the size and purity of particles are analyzed. Then, the reaction mechanism and product phase transition mechanism during hydrothermal synthesis of zirconia are summarized to provide a theoretical reference for the oriented preparation. Finally, the improvement and commercialization of sub-/supercritical hydrothermal synthesis technology are evaluated, and the future research topics are proposed.     

Molecularly imprinted macroporous polymer monolithic layers for L-phenylalanine recognition in complex biological fluids

In present work, the development of macroporous monolithic layers bearing the artificial recognition sites toward L-phenylalanine has been carried out. The set of macroporous poly(2-aminoethyl methacrylate-co-2-hydroxyethyl methacrylate-co-ethylene glycol dimethacrylate) materials with average pore size ranged in 340–1200 nm was synthesized. The applicability of Hildebrand's and Hansen's theories for the prediction of polymer compatibility with porogenic solvents was evaluated. The dependences of average pore size on theoretically calculated parameters were plotted. The linear trend detected for Hansen's theory has indicated the high suitability of this approach to select appropriate porogens. The synthesized monolithic MIP layers were tested toward the ability to rebind phenylalanine-derivative in microarray format. The influence of such factors as average pore size of the material, the concentration of template molecule in polymerization mixture, interaction time of analyte with its imprinted sites on binding efficiency were studied. The developed materials demonstrated good analyte rebinding from buffer solution with recognition factors 2.5–3.4 depending on the MIP sample. The comparable rebinding efficiency was also detected when the analysis was carried using complex biological media. The selectivity of phenylalanine binding from the equimolar mixture of structural analogues was 81.9% for free amino acid and 91.2% for labeled one.     

A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.