数值模拟铸件充型过程中的液/固两相流动

铸造过程中熔融金属内的固体渣粒的运动轨迹是非常重要的。文中给出了粒子传输轨迹的数学模型,该数学模型采用显示法来确定粒子的位置。模拟研究结果与用其它数学模型的模拟结果比较,吻合良好。该模型可用于固体粒子位置的确定,并应用到SUTCAST软件中。     

Flexible multibody simulation using hybrid integration scheme

One issue in the dynamic simulation of flexible multibody system is poor computation efficiency, which is due to high frequency components in the solution associated with a deformable body. Standard explicit numerical methods should take very small time steps in order to satisfy the absolute stability condition for the high frequency components and, in turn, the computational efficiency deteriorates. In this study, a hybrid integration scheme is applied to solve the equations of motion of a flexible multibody system for achieving better computational efficiency. The computation times and simulation results are compared between the hybrid scheme and conventional methods. The results demonstrate that the efficiency of a flexible multibody simulation can be improved by using the hybrid scheme.     

Challenges in Liquid‐Phase Exfoliation,Processing, and Assembly of Pristine Graphene

Recent developments in the exfoliation, dispersion, and processing of pristine graphene (i.e., non‐oxidized graphene) are described. General metrics are outlined that can be used to assess the quality and processability of various “graphene” products, as well as metrics that determine the potential for industrial scale‐up. The pristine graphene production process is categorized from a chemical engineering point of view with three key steps: i) pretreatment, ii) exfoliation, and iii) separation. How pristine graphene colloidal stability is distinct from the exfoliation step and is dependent upon graphene interactions with solvents and dispersants are extensively reviewed. Finally, the challenges and opportunities of using pristine graphene as nanofillers in polymer composites, as well as as building blocks for macrostructure assemblies are summarized in the context of large‐scale production.     

Enhancing level set brain tumor segmentation using fuzzy shape prior information and deep learning

Magnetic resonance imaging (MRI) brain tumor segmentation is a crucial task for clinical treatment. However, it is challenging owing to variations in type, size, and location of tumors. In addition, anatomical variation in individuals, intensity non-uniformity, and noises adversely affect brain tumor segmentation. To address these challenges, an automatic region-based brain tumor segmentation approach is presented in this paper which combines fuzzy shape prior term and deep learning. We define a new energy function in which an Adaptively Regularized Kernel-Based Fuzzy C-Means (ARKFCM) Clustering algorithm is utilized for inferring the shape of the tumor to be embedded into the level set method. In this way, some shortcomings of traditional level set methods such as contour leakage and shrinkage have been eliminated. Moreover, a fully automated method is achieved by using U-Net to obtain the initial contour, reducing sensitivity to initial contour selection. The proposed method is validated on the BraTS 2017 benchmark dataset for brain tumor segmentation. Average values of Dice, Jaccard, Sensitivity and specificity are 0.93 ± 0.03, 0.86 ± 0.06, 0.95 ± 0.04, and 0.99 ± 0.003, respectively. Experimental results indicate that the proposed method outperforms the other state-of-the-art methods in brain tumor segmentation.     

Fabrication and electrical characterization of integrated nano-scale fluidic channels

We present the fabrication and characterization of nanoscale fluidic channels with embedded electrodes. Arrays of 2.25 μm long and 60 nm tall nanochannels with widths ranging from 60 to 500 nm were microfabricated in SiO₂ with Au electrodes embedded inside and outside of the nanochannels. The built-in electrodes were able to probe nanochannel conductance via a redox reaction of \textFe(\textCN)₆^{3 - /4 -} {\text{Fe}}({\text{CN}})_{6}^{3 - /4 - } . Amperometric characterization showed that conductance of nanochannel arrays varied linearly both with the width and number of nanochannels and was in the 10–100 pS range. Further, we show that electrical current was largely diffusion based and could be predicted from channel geometry using standard diffusion equations. We also discuss the potential of such nanochannel arrays as electronic biomolecular sensors and show preliminary streptavidin detection results.     

Changes in the structure of hematite by extended dry grinding in relation to imposed stress energy

The effect of extended dry milling in different mills on the structural changes of hematite concentrate has been investigated using a combination analysis of XRD line broadening, BET and particle size measurements. Structural changes were followed by XRD line broadening analysis using integral breadth method and Warren-Averbach approach. For analysis, the stress energy was estimated by considering different grinding variables in different mills and changes in the structure discussed in terms of stress energy.Within comparable range of stress energy, lower BET surface area was produced by grinding in the vibratory mill. The maximum surface area increased to 18,400 m²/kg in the vibratory mill after releasing 51,300 kJ/kg energy. The conversion of the 80% of initial hematite to amorphous phase during extended dry grinding by tumbling, planetary and vibratory mills, needs 4000, 8500 and 50,000 kJ/kg energy respectively. It was understood that vibratory mill introduces the minimum lattice strain and gives the largest crystallites when applying the same level of stress energy. The smallest crystallites with grinding in tumbling, vibratory and planetary mills were obtained about 17.3, 13.5 and 5.6 nm after releasing 5230, 51,300 and 15,600 kJ/kg respectively. For these levels of stress energy, in turn, the microstrain <ε_L=10 nm²>^1/2 exceeds 4.4 × 10^− 3, 3.9 × 10^− 3 and 5.3 × 10^− 3.It was further revealed that higher concentrations of defects (Amorphization and excess energy) per unit surface area were induced by grinding in the planetary and tumbling mills. A theoretical calculation of the energy contribution to the long-lived defects indicated that products from tumbling and planetary mills have higher excess energy compared to the products from vibratory mill for the same stress energy. The maximum theoretical excess energy was estimated about 75.4, 80.0 and 81.3 kJ per mole of the ground hematite with tumbling, vibratory and planetary mills after releasing 5230, 51,300 and 15,600 kJ/kg of stress energy respectively. Grinding in vibratory mill needs much more energy to reach the same effect as the other used mills. A comparison of specific energy input and stress energy among the used mills points out that for generation of the same levels of stress energy, the planetary mill consumes more energy than the other used mills.     

Nano levels detection of beryllium by a novel beryllium PVC-based membrane sensor based on 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy

A novel poly(vinyl chloride)-based 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy (PBC) with sodium tetraphenyl borate (NaTPB) as an anion excluder, benzyl acetate (BA), acetophenon (AP) and o-nitrophenyloctyl ether (NPOE) as plasticizing solvent mediators was prepared and investigated as a beryllium selective sensor. The best performance was observed with the membrane having the PVC–NaTPB–NPOE–PBC composition 30%:3%:62%:5%, which worked well over a very wide concentration range (1.0×10⁻⁷ M to 1.0×10⁻¹ M). The sensor exhibits a Nernstian slope of 29.9 mV per decade of Be²⁺ activity. The detection limit of the sensor is 7.0×10⁻⁸ M (630 ppt). The proposed electrode shows excellent discriminating ability toward Be²⁺ ion with regard to alkali, alkaline earth, transition and heavy metal ions. It was successfully applied to the determination of beryllium in a mineral sample.     

Modelling of foam degradation in lost foam casting process

In this investigation a new model was developed to calculate gas pressure at the melt/foam interface (Gap) resulting from foam degradation during mould filling in the lost foam casting (LFC) process. Different aspects of the process, such as foam degradation, gas elimination, transient mass, heat transfer, and permeability of the refractory coating were incorporated into this model. A computational fluid dynamic (CFD) code was developed based on the numerical technique of the SOLution Algorithm-Volume of Fluid (SOLA-VOF) utilizing model, for the simulation and prediction of the fluid flow in the LFC process. In order to verify the computational results of the simulation, a thin plate of grey iron was poured into a transparent foam mould. The mould filling process was recorded using a 16 mm high-speed camera. Images were analysed frame by frame, in order to measuring foam depolymerization rate and the gap volume during mould filling. Comparison between the experimental method and the simulation results, for the LFC filling sequence, has shown a good agreement.