Shedding vortex simulation method based on viscous compensation technology research

Owing to the influence of the viscosity of the flow field, the strength of the shedding vortex decreases gradually in the process of backward propagation. Large-scale vortexes constantly break up, forming smaller vortexes. In engineering, when numerical simulation of vortex evolution process is carried out, a large grid is needed to be arranged in the area of outflow field far from the boundary layer in order to ensure the calculation efficiency. As a result, small scale vortexes at the far end of the flow field cannot be captured by the sparse grid in this region, resulting in the dissipation or even disappearance of vortexes. In this paper, the effect of grid scale is quantified and compared with the viscous effect through theoretical derivation. The theoretical relationship between the mesh viscosity and the original viscosity of the flow field is established, and the viscosity term in the turbulence model is modified. This method proves to be able to effectively improve the intensity of small-scale shedding vortexes at the far end of the flow field under the condition of sparse grid. The error between the simulation results and the results obtained by using fine mesh is greatly reduced, the calculation time is shortened, and the high-precision and efficient simulation of the flow field is realized.     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Design,synthesis and evaluation of novel dehydroabietic acid-dithiocarbamate hybrids as potential multi-targeted compounds for tumor cytotoxicity

In the present study, novel representatives of the important group of biologically-active, dehydroabietic acid-bearing dithiocarbamate moiety, were synthesized and characterized by ¹H NMR, ¹³C NMR, HR-MS. The in vitro antiproliferative activity evaluation (MTT) indicated that these compounds exhibited potent inhibitory activities in various cancer cell lines (HepG-2, MCF-7, HeLa, T-24, MGC-803). Particularly, compound III-b possessed extraordinary cytotoxicity with low micromolar IC₅₀ values ranging from 4.07 to 38.84 µM against tested cancer cell lines, while displayed weak cytotoxicity on two normal cell lines (LO-2 and HEK 293 T). Subsequently, the potential mechanisms of representative compound III-b were elementarily investigated by Transwell experiment, which showed III-b can inhibit cancer cells migration. Annexin-V/PI dual staining showed that the compound can induce HepG-2 cells apoptosis in a dose-dependent manner. Meanwhile this apoptosis may be related to the upregulated protein expression of cleaved-caspase 3, cleaved-caspase 9, Bax and downregulated of Bcl-2 indicated by Western Blot. Later study further confirmed that ROS levels in HepG-2 cells increased significantly with the rise of concentrations. In addition, through the network pharmacology data analyzing, the core targets and signaling pathways of compound III-b for treatment of liver neoplasms were forecasted. Molecular docking model showed that compound III-b had high affinity with hub targets (CASP3, EGFR, HSP90AA1, MAPK1, ERBB2, MDM2), suggesting that compound III-b might target the hub protein to modulate signaling activity. Taken together, these data indicated that dehydroabietic acid structural modification following the “Molecular hybridization” principle is a feasible way to discover the potential multi-targeted antitumor compounds.     

Generalized Jacobi spectral Galerkin method for fractional pantograph differential equation

This work is concerned with the extension of the Jacobi spectral Galerkin method to a class of nonlinear fractional pantograph differential equations. First, the fractional differential equation is converted to a nonlinear Volterra integral equation with weakly singular kernel. Second, we analyze the existence and uniqueness of solutions for the obtained integral equation. Then, the Galerkin method is used for solving the equivalent integral equation. The error estimates for the proposed method are also investigated. Finally, illustrative examples are presented to confirm our theoretical analysis.     

改进型单晶炉提拉系统偏心平衡研究

随着光伏行业的快速发展, 对硅单晶的品质和长晶装备的稳定性的要求也不断提高。直拉法是生产硅单晶的主要方法,通过提高单晶炉副室的高度以扩大单晶硅的生产规模。由于副室高度的大幅增加,且单晶炉提拉头质心相对于旋转轴心有一定距离,对单晶炉整体稳定性有较大影响,从而降低了单晶硅的生产质量。针对此问题,对单晶炉建立可靠的力学分析模型,采用数值仿真方法,对单晶炉整体进行动力学响应分析,计算得到副室高度增加后的单晶炉工作时中钨丝绳下端晶棒的运动规律以及最大摆动幅度,为改进设计提供依据。数值仿真分析表明提高单晶炉副室高度后,提拉头较大的质心偏心是单晶炉提拉系统发生摆动的主要原因。在此基础上提出在提拉头上添加质心调节装置,通过控制系统调节可保证提拉头质心位置在旋转轴线上以降低提拉系统的摆动。     

Experimental and numerical simulation of effects of CO2/N2 concentration and initial temperature on combustion characteristics of biomass syngas

Biomass syngas is a form of renewable energy with very broad application prospects, and it has different combustion characteristics according to the fuel composition and processing technology of biomass syngas. The influence of combustion composition, diluent and temperature variation on combustion characteristics were studied in this paper. The FFCM-1 mechanism was used to investigate the combustion characteristics of CO/CH₄/H₂ under varied diluents CO₂/N₂ and temperature by using spherical expansion flame method and ANSYS CHEMKIN-PRO. The experimental laminar burning velocity was compared with the simulation results of FFCM-1 mechanism. The results reveal that the experimental data are in good agreement with the simulation results, which are somewhat different under the condition of rich fuel. The laminar burning velocity decreases significantly with the increase of diluent CO₂/N₂, with the effect of diluent CO₂ being more significant. The laminar burning velocity increase dramatically with the increase of initial temperature, and the adiabatic flame temperature also decreases with the increase of diluent. The reduction caused by diluent CO₂ is much larger than that caused by diluent N₂. The change of initial temperature also affects the adiabatic flame temperature, but the range of variation is not as pronounced as that of diluent. Not only was the interaction between the combustion characteristics of CO/CH₄/H₂ under different diluents and temperature changes explored in this paper, but the influence mechanism was also revealed in depth.