Occurrence and distribution of metals and porphyrins in Nigerian coal minerals

The metal contents of Nigerian coal minerals were analyzed using an atomic absorption spectrophotometer. Calcium, Na, and Fe occurred as the major elements with concentrations ranging from 9 782 μg/g for Ca to 432 μg/g for Na whereas K, Mg, Mn, Ni, Cr, Zn, Pb, and Cu, which occurred at trace levels ranged from 673.73 μg/g for Mg to 2.97 μg/g for Mn. The results of the quantitative analysis of porphyrins extracted from the coal minerals showed that Onyeama coal has the highest amount of porphyrins (ca～0.96 μg/g) while Okpara has the lowest (ca～0.30 μg/g). The porphyrins were qualitatively characterized by a combination of thin layer chromatography (TLC), infrared, and ultraviolet-visible spectrophotometers. The results of the mid infrared analysis (MIR) showed the presence of absorption bands at 3 440 cm～1～3 450 cm-1 and 1 640 cm-1～1 680 cm-1 , which are owing to the stretching vibrations of N - H and C = C of aromatics, with C- H out of plane (oop) bending vibrations at wavenumbers less than 900 cm-1, all of which are characteristic absorptions of porphyrin free base. The ultraviolet-visible data showed prominent peaks at ～400 nm(Soret band) and at wavelength ranges of 535 nm～550 nm(β-band) and 565 nm～ 600 nm (α-band) for the coal porphyrins analyzed. The geochemical significance of the metals and porphyrins in coal minerals are discussed.     

Pulverized coal plasma gasification

A number of experiments on the plasma-vapor gasification of brown coals of three types have been carried out using an experimental plant with an electric-arc reactor of the combined type. On the basis of the material and heat balances, process parameters have been obtained: the degree of carbon gasification (_c), the level of sulfur conversion into the gas phase (_s), the synthesis gas concentration (CO+Hz) in the gaseous products, and the specific power consumption for the gasification process. The degree of gasification was 90.5-95.0%, the concentration of the synthesis gas amounted to 84.7–85.7%, and the level of sulfur conversion into the gas phase was 94.3–96.7%. Numerical study of the process of plasma gasification of coals was carried out using a mathematical model of motion, heating, and gasification of polydisperse coal particles in an electric-arc reactor of the combined type with an internal heat source (arc). The initial conditions for a conjugate system of nonlinear differential equations of the gas dynamics and kinetics of a pulverized coal stream interacting with the electric arc and oxidizer (water vapor) agree with the initial conditions of the experiments. The computation results satisfactorily correlate with the experimental data. The mathematical model can be used for the determination of reagent residence time and geometrical dimensions of the plasma reactor for the gasification of coals.Nomenclature c _i volume concentration of components (kmol m^–3) - x longitudinal coordinate (m) - f _i source members, determined by variation of the ith component due to chemical reactions in unit volume in unit time (kmol m^–3s^–1) - velocity (m s^–1) - M _s ash mass in one particle (kg) - C _D particle drag coefficient - 3.14 - r _s particle radius (m) - d particle diameter (m) - density (kg m^–3) - C _p heat capacity of components (J mol^t– K^–1) - Q _j thermal effect of reaction (J kmol^–1) - E_j activation energy of reaction - N _l volume concentration of particles of thelth fraction (m^–3) - T temperature (K) - emissivity factor of coal particles - 5.67 × 10^–8, blackbody emissivity coefficient (W m^–2 K^–4) - P pressure (Pa) - S reactor cross section (m²) - D reactor diameter (m) - V reactor volume (m³) - L _R reactor length (m) - F _W friction force on the wall (N) - f _g friction coefficient - residence time (s) - Nu Nusselt number - Re Reynolds number - Pr Prandtl number - thermal conductivity of gas (J m^– s^–1 K^–1) - R 8.3 × 10³, universal gas constant (J kmol K^–1) - µ _i molecular mass of component (kg kmol^–1) - dynamic viscosity coefficient of gas (kg m^–1 s^–1) - thermal efficiency of plasma reactor - q_arc specific heat flow from arc (W m^–3) - P ₁ heat supplied in vapor at T = 405 K (W) - P ₂ heat loss to wall (W) - P ₃ heat loss in the gas and slag separator chamber (W) - P ₄ heat loss in the synthesis gas oxidation chamber (W) - P ₅ heat loss in the slag catcher (W) - P ₆ heat carried away in the off-gas (W) - P heat input of arc (W) - P _arc electric power of arc (W) - Q_sp specific power consumption (kw Hr kg^–1) - d _w specific heat flow to wall (W m^–2) - _c degree of carbon gasification (%) - _s level of sulfur conversion into gas phase (%)     

处理噪声问题的泰勒展开交替最小化算法

为了处理图像、计算机视觉和生物信息等领域中广泛存在的稀疏大噪声和高斯噪声问题,提出了一种利用交替方向最小化思想求解主成分追求松弛模型的泰勒展开交替最小化算法(TEAM).采用推广泰勒展开和收缩算子等技术推导出低秩矩阵和稀疏大噪声矩阵的迭代方向矩阵,加入连续技术提高算法的收敛速率,设计出TEAM算法的求解步骤.实验中,将TEAM算法与该领域的顶级算法作分析对比.结果表明,TEAM算法时间优势明显,误差优势略好.     

基于布谷鸟算法与BP神经网络的煤灰变形温度预测

以120种煤样为数据基础,采用布谷鸟算法(CS)优化BP(Back Propagation)神经网络,建立了CSBP模型对单煤、煤掺添加剂和配煤等3类样本的煤灰变形温度(DT)样本进行预测。模型以煤灰化学成分及其组合参数等13个变量作为输入量,以变形温度(DT)作为输出量。CSBP模型预测结果与BP神经网络模型预测结果进行对比发现,无论是单煤、煤掺添加剂还是配煤,CSBP模型较BP模型对煤灰变形温度(DT)的预测都更加精准,平均相对误差分别达到了3.11%、4.08%和4.22%。另外,对比3类样本预测结果发现,无论是CSBP模型还是BP模型,相比单煤预测而言,煤掺添加剂及配煤的预测误差都有明显的增加。     

煤中腐植酸与尿素相互作用机理的研究

采用化学法和波谱分析法对泥炭、褐煤、风化煤腐植酸（ＨＡ）与尿素的相互作用机理进行了研究。结果表明,ＨＡ与尿素之间发生了极其复杂的反应,包括离子化、络合配位、亲核加成、自由基反应及氢键缔合等,形成不同的化学键。羧基对反应深度的影响最大;含官能团（特别是羧基）最多的风化煤ＨＡ反应性最高。本项研究为有机长效尿素的研制提供了理论依据     

Linear low-rank approximation and nonlinear dimensionality reduction

We present our recent work on both linear and nonlinear data reduction methods and algorithms: for the linear case we discuss results on structure analysis of SVD of column-partitioned matrices and sparse low-rank approximation; for the nonlinear case we investigate methods for nonlinear dimensionality reduction and manifold learning. The problems we address have attracted great deal of interest in data mining and machine learning.     

强场下煤的13C NMR谱

由强场静态¹³C煤谱可以获得与低场魔角旋转高分辨谱相同的fa,从而避免了样品的快速旋转的要求,同时得到了高灵敏度。     

基于旋转变换和鲁棒主成分分析的车牌校正方法

本文研究了受到非高斯噪声污染及边框信息不完整的车牌图像校正的问题.利用鲁棒主成分分析与旋转变换结合的方法,获得了更具普适性的车牌矫正方法.并通过与主成分分析法、旋转投影法的矫正结果相比较,推广了本文方法具有更好的鲁棒性和普适性的结果.     

A new model for sparse and low-rank matrix decomposition

The robust principal component analysis (RPCA) model is a popular method for solving problems with the nuclear norm and $\ell_1$ norm. However, it is time-consuming since in general one has to use the singular value decomposition in each iteration. In this paper, we introduce a novel model to reformulate the existed model by making use of low-rank matrix factorization to surrogate the nuclear norm for the sparse and low-rank decomposition problem. In such case we apply the Penalty Function Method (PFM) and Augmented Lagrangian Multipliers Method (ALMM) to solve this new non-convex optimization problem. Theoretically, corresponding to our methods, the convergence analysis is given respectively. Compared with classical RPCA, some practical numerical examples are simulated to show that our methods are much better than RPCA.     

数据缺损矩阵低秩分解的正则化方法

数据缺损下矩阵低秩逼近问题出现在许多数据处理分析与应用领域. 由于极高的元素缺损率,数据缺损下的矩阵低秩逼近呈现很大的不适定性, 因而寻求有效的数值算法是一个具有挑战性的课题. 本文系统完整地综述了作者近期在这方面的一些研究进展, 给出了基本模型问题的不适定性理论分析, 提出了两种新颖的正则化方法: 元素约束正则化和引导正则化, 分别适用于中等程度的数据缺损和高度元素缺损的矩阵低秩逼近. 本文同时也介绍了相应快速有效的数值算法. 在一些实际的大规模数值例子中, 这些新的正则化算法均表现出比现有其他方法都好的数值特性.