硫化矿石堆自热过程的非线性及数值仿真研究
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摘要
硫化矿石自燃火灾会诱发一系列的安全与环境问题,同时给矿山企业带来巨大的经济损失。迄今为止,国内外学者对硫化矿石的自燃机理、自燃倾向性评价、预防及控制技术等领域进行了大量研究,但由于硫化矿石堆自热过程的高复杂性和强非线性,使问题未能得到根本解决。随着浅层资源的逐渐匮乏,我国金属矿山逐步进入深部开采阶段。采深增大导致开采过程中面临的高地温问题变得愈发严重,地温的升高将增大矿石自燃的可能性。因此,对硫化矿石堆氧化自热过程的非线性及渗流场和温度场的数值仿真展开研究,是硫化矿石自燃防治研究的一个发展趋势,具有重大的理论意义和实际应用价值。
论文在检索国内外研究成果并进行系统分析的基础上,采用理论分析、室内模拟实验以及数值模拟相结合的研究方法对硫化矿石堆的动态自热过程、硫化矿石堆氧化自热过程的非线性特征以及渗流场和温度场的变化规律等进行了系统研究。论文的主要工作和取得的成果如下：
(1)在实验室内对硫化矿石堆动态自热过程进行了模拟,揭示了矿石堆温度与时间的关系、矿石堆温度离散程度与时间的关系、平均升温率与深度的关系以及矿石堆对环境温度变化响应的空间差异,基于实测温度对矿石堆温度场进行了二维重构,探明了矿石堆内自热层的范围。
(2)将小波技术与近似熵方法引入到矿石堆自热过程的研究上来,提出室内实测温度序列的低频成分反映的是梯度升温对矿石堆温度变化的影响,而自热过程的复杂信息则蕴藏在高频成分中这一概念,分析了矿石堆近似熵分布规律,同时对不同区域的自热过程进行了近似熵检测,从动力学角度证实了矿石堆自热层的存在。
(3)采用混沌动力学方法对矿石堆自热过程进行了分析,探明了室内实验采用的梯度升温方式在一定程度上减弱了矿石堆自热过程的混沌程度,确定了矿石堆硫化物含量、氧气浓度、矿石堆温度、氧化反应速度和放热强度作为描述矿石堆自热动力学性态的5个变量,揭示了关联维数和最大Lyapunov指数与自热效果存在正相关性。
(4)提出了将实测矿石堆温度序列拆分为趋势项、混沌项和随机项的概念。根据现场试验硫化矿石堆的自热升温特征建立了矿石堆温度的趋势预测模型,在对趋势预测结果的差值序列进行混沌识别之后,采用优选出的加权一阶局域法建立混沌预测模型,再以二者叠加构成趋势—混沌组合预测模型,最后应用室内实测温度数据对预测模型进行了检验。结果表明,建立的趋势—混沌组合预测模型具有很高的预测精度,能够很好地适用于硫化矿石堆自燃早期预测。
(5)采用数字图像处理和有限元技术相结合的方法,进行了矿石堆孔隙内空气渗流的数值仿真研究,探明了不同粒径下空气流速和压力在孔隙内的分布规律,定性解释了矿石堆内存在自热层的原因。发展了有效导热系数法在矿石堆温度场数值仿真中的应用,分析了矿石堆温度场的变化规律,计算得出矿石堆自燃起始时间,探明了矿石堆自燃区域随时间的变化特征及矿石堆截面积、表面空气流速以及矿石堆高度对矿石堆温度场的影响规律。
Spontaneous combustion of sulfide ores can induce a series of safety and environment problems, and cause great economic loss in mining enterprises. Nowadays, the mechanism of spontaneous combustion, evaluation of spontaneous combustion tendency, prevention and control technology were carefully analyzed by many scholars over the world. However, the problem was not solved ultimately because of the high complexity and strong nonlinearity of self-heating process of sulfide ore heap. With the increasing scarcity of resources in shallow layer, metal mines in China enter the stage of deep mining gradually. The mining depth increasing can lead the high ground temperature problem during mining process to become more serious than before. Ground temperature rising will increase the possibility of spontaneous combustion of sulfide ores.
Therefore, research on nonlinearity of the oxidation and self-heating process, and numerical simulation of seepage field and temperature field is a trend in spontaneous combustion prevention research of sulfide ores, which has great theoretical significance and practical value.
On the basis of reviewing the previous papers at home and abroad, research methods combining the theoretical analysis, laboratory simulation and numerical simulation were used to systematically analyze the dynamic self-heating process and its nonlinear characteristics, and the variation of seepage field and temperature field. The main works and achievements of the thesis are as follows:
(1) The dynamic self-heating process of sulfide ore heap was simulated in the laboratory. The relationship between temperature and time, relationship between temperature discrete degree and time, relationship between average temperature rise rate and depth, and spatial difference of the ore heap responding to ambient temperature changes were revealed. The temperature field was two dimensional reconstructed based on measured temperature, and the range of the self-heating layer in the ore heap was proved.
(2) The wavelet technology and approximate entropy method were used to analyze the self-heating process of sulfide ore heap. The concept that low frequency component of measured temperature series in the laboratory reflects the effects of gradient increased temperature to the ore heap and the complicated information of self-heating process is embedded in the high frequency component was proposed. The approximate entropy distribution of the ore heap was analyzed and the self-heating process of different regions was detected based on approximate entropy method, which confirms the existence of self-heating layer from dynamics view.
(3) The self-heating process was analyzed based on chaotic dynamics methods. The results indicate that gradient increased temperature weakens chaotic degree of self-heating process to some extent. The sulfide content, oxygen concentration, temperature, oxidation rate and heat liberation intensity of the ore heap were determined as the5variables to describe the self-heating process. Correlation dimension and maximum Lyapunov exponent positively correlated with self-heating effect were proved.
(4) The concept that measured temperature series of the ore heap can be divided into three parts:trend item, chaos item and stochastic item was proposed. The trend model for temperature prediction was established according to the temperature rising characteristics of sulfide ore heap from field test. The chaos prediction model for difference series of trend prediction was established by means of the adding-weight one-rank local-region method through optimization after chaotic identification. Then, the trend and chaos prediction model was established by the superposition of these two models and it was tested based on measured temperature data in the laboratory. The results indicate that the trend and chaos prediction model is very precise. As a result, it can be used to predict spontaneous combustion of sulfide ore heap during early stage.
(5) Coupled with digital image processing technology and finite element method, the air seepage field in pores of the ore heap was analyzed. The distribution of air velocity and pressure in pores was proved at different granularity, which explains the reason for self-heating layer existing in the ore heap qualitatively. The effective thermal conductivity method applied to the numerical simulation for temperature field of the ore heap was developed. The variation of temperature field was analyzed and the starting time of spontaneous combustion was calculated. The change characteristics of spontaneous combustion region varying with time, and the variation of temperature field affected by sectional area, air velocity and the height of the ore heap were proved.
论文在检索国内外研究成果并进行系统分析的基础上,采用理论分析、室内模拟实验以及数值模拟相结合的研究方法对硫化矿石堆的动态自热过程、硫化矿石堆氧化自热过程的非线性特征以及渗流场和温度场的变化规律等进行了系统研究。论文的主要工作和取得的成果如下：
(1)在实验室内对硫化矿石堆动态自热过程进行了模拟,揭示了矿石堆温度与时间的关系、矿石堆温度离散程度与时间的关系、平均升温率与深度的关系以及矿石堆对环境温度变化响应的空间差异,基于实测温度对矿石堆温度场进行了二维重构,探明了矿石堆内自热层的范围。
(2)将小波技术与近似熵方法引入到矿石堆自热过程的研究上来,提出室内实测温度序列的低频成分反映的是梯度升温对矿石堆温度变化的影响,而自热过程的复杂信息则蕴藏在高频成分中这一概念,分析了矿石堆近似熵分布规律,同时对不同区域的自热过程进行了近似熵检测,从动力学角度证实了矿石堆自热层的存在。
(3)采用混沌动力学方法对矿石堆自热过程进行了分析,探明了室内实验采用的梯度升温方式在一定程度上减弱了矿石堆自热过程的混沌程度,确定了矿石堆硫化物含量、氧气浓度、矿石堆温度、氧化反应速度和放热强度作为描述矿石堆自热动力学性态的5个变量,揭示了关联维数和最大Lyapunov指数与自热效果存在正相关性。
(4)提出了将实测矿石堆温度序列拆分为趋势项、混沌项和随机项的概念。根据现场试验硫化矿石堆的自热升温特征建立了矿石堆温度的趋势预测模型,在对趋势预测结果的差值序列进行混沌识别之后,采用优选出的加权一阶局域法建立混沌预测模型,再以二者叠加构成趋势—混沌组合预测模型,最后应用室内实测温度数据对预测模型进行了检验。结果表明,建立的趋势—混沌组合预测模型具有很高的预测精度,能够很好地适用于硫化矿石堆自燃早期预测。
(5)采用数字图像处理和有限元技术相结合的方法,进行了矿石堆孔隙内空气渗流的数值仿真研究,探明了不同粒径下空气流速和压力在孔隙内的分布规律,定性解释了矿石堆内存在自热层的原因。发展了有效导热系数法在矿石堆温度场数值仿真中的应用,分析了矿石堆温度场的变化规律,计算得出矿石堆自燃起始时间,探明了矿石堆自燃区域随时间的变化特征及矿石堆截面积、表面空气流速以及矿石堆高度对矿石堆温度场的影响规律。
Spontaneous combustion of sulfide ores can induce a series of safety and environment problems, and cause great economic loss in mining enterprises. Nowadays, the mechanism of spontaneous combustion, evaluation of spontaneous combustion tendency, prevention and control technology were carefully analyzed by many scholars over the world. However, the problem was not solved ultimately because of the high complexity and strong nonlinearity of self-heating process of sulfide ore heap. With the increasing scarcity of resources in shallow layer, metal mines in China enter the stage of deep mining gradually. The mining depth increasing can lead the high ground temperature problem during mining process to become more serious than before. Ground temperature rising will increase the possibility of spontaneous combustion of sulfide ores.
Therefore, research on nonlinearity of the oxidation and self-heating process, and numerical simulation of seepage field and temperature field is a trend in spontaneous combustion prevention research of sulfide ores, which has great theoretical significance and practical value.
On the basis of reviewing the previous papers at home and abroad, research methods combining the theoretical analysis, laboratory simulation and numerical simulation were used to systematically analyze the dynamic self-heating process and its nonlinear characteristics, and the variation of seepage field and temperature field. The main works and achievements of the thesis are as follows:
(1) The dynamic self-heating process of sulfide ore heap was simulated in the laboratory. The relationship between temperature and time, relationship between temperature discrete degree and time, relationship between average temperature rise rate and depth, and spatial difference of the ore heap responding to ambient temperature changes were revealed. The temperature field was two dimensional reconstructed based on measured temperature, and the range of the self-heating layer in the ore heap was proved.
(2) The wavelet technology and approximate entropy method were used to analyze the self-heating process of sulfide ore heap. The concept that low frequency component of measured temperature series in the laboratory reflects the effects of gradient increased temperature to the ore heap and the complicated information of self-heating process is embedded in the high frequency component was proposed. The approximate entropy distribution of the ore heap was analyzed and the self-heating process of different regions was detected based on approximate entropy method, which confirms the existence of self-heating layer from dynamics view.
(3) The self-heating process was analyzed based on chaotic dynamics methods. The results indicate that gradient increased temperature weakens chaotic degree of self-heating process to some extent. The sulfide content, oxygen concentration, temperature, oxidation rate and heat liberation intensity of the ore heap were determined as the5variables to describe the self-heating process. Correlation dimension and maximum Lyapunov exponent positively correlated with self-heating effect were proved.
(4) The concept that measured temperature series of the ore heap can be divided into three parts:trend item, chaos item and stochastic item was proposed. The trend model for temperature prediction was established according to the temperature rising characteristics of sulfide ore heap from field test. The chaos prediction model for difference series of trend prediction was established by means of the adding-weight one-rank local-region method through optimization after chaotic identification. Then, the trend and chaos prediction model was established by the superposition of these two models and it was tested based on measured temperature data in the laboratory. The results indicate that the trend and chaos prediction model is very precise. As a result, it can be used to predict spontaneous combustion of sulfide ore heap during early stage.
(5) Coupled with digital image processing technology and finite element method, the air seepage field in pores of the ore heap was analyzed. The distribution of air velocity and pressure in pores was proved at different granularity, which explains the reason for self-heating layer existing in the ore heap qualitatively. The effective thermal conductivity method applied to the numerical simulation for temperature field of the ore heap was developed. The variation of temperature field was analyzed and the starting time of spontaneous combustion was calculated. The change characteristics of spontaneous combustion region varying with time, and the variation of temperature field affected by sectional area, air velocity and the height of the ore heap were proved.
引文
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