基于GA-NN和不可逆热力学的钢中氧化物夹杂预报模型
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摘要
钢中存在的大多数夹杂物,尤其是脱氧生成的氧化物夹杂的性质直接影响到钢的性能。在现有技术条件下完全去除钢中的夹杂物是不可能的,只要钢中有氧的存在,就不可能避免生成新的夹杂物。因此,通过物理化学的方法控制夹杂物的成分从而达到减小夹杂物对钢性能的有害性变得尤为重要。本论文在考察了大量国内外文献的基础上,主要围绕中夹杂物成分控制的热力学和动力学开展研究。
本论文首先对前人建立的活度机理模型进行了考察,发现这些模型都是建立在很多假设的基础上,对活度组元体系进行了简化,因此应用领域往往受到限制。同时,机理模型在计算方法上,通常采用线性拟合、最小二乘法等传统数学方法进行回归,但是这些方法进行的参数估计不是无偏估计量,拟合精度往往不高。因此,本论文采用了对国际上比较权威的活度实验数据进行离散化的方式,用遗传算法改进BP神经网络的权值和阈值,基于实验数据建立了一种通用的实际溶液组元活度模型。
通过将遗传神经网络模型引入夹杂物体系,本论文对MnO-SiO_2、CaO-SiO_2-Al_2O_3和MnO-SiO_2-Al_2O_3系夹杂物进行了研究,提出了将其控制在低熔点区域的方法,并对CaO-Al_2O_3-SiO_2顶渣覆盖下的不同脱氧方式进行分析。
结合实际生产,本论文对合金化、精炼及钙处理过程中的夹杂物成分控制进行了研究,分析了不同情况下夹杂物的产生及成分变化机理,提出解决措施。
针对前人对非平衡态下的夹杂物成分变化动力学研究较少及遗传神经网络模型只能研究平衡态夹杂物成分及形态的情况,本论文将不可逆热力学引入夹杂物动力学计算,从化学反应和扩散两个方面对夹杂物从生成初始及冶炼过程中不同时期的夹杂物状态进行分析,从机理上阐述夹杂物生成过程,并建模推导出夹杂物成分变化的通用动力学方程式。通过在实验室条件下模拟LF过程,得出动力学方程的唯象系数,并验证了不可逆热力学在夹杂物组元计算的可行性。
The nature of majority of inclusions in steel, in particular the deoxy-generated oxide inclusions directly affect the performance of steel. Under the conditions of existing technology, it is impossible to full remove inclusions in steel. As long as the existence of oxygen in steel, the generation of new inclusions can not be avoid. Therefore, in order to achieve the target of reduction of the harmful effects on performance of steel, the control of inclusions' composition by physical-chemistry methods becomes especially important. In this paper, the thermodynamics and kinetics for controlling inclusions composition are mainly concentrated, based on the invetigation of many domestic and international literatures.
The eatablishment of previous mechanism models is investigated firstly in this paper. It finds that these models are based on a lot of assumptions. Due to the simplified architecture of the activity of components, the application fields are always be restricted. At the same time, mechanism models always use linear fitting, least-squares procedure and so on to regress in the methods of calculation. But parameter estimation of these traditional mathmatics methods is not unbiased estimators, the fitting accuracy is often not high. Therefore, this paper takes the method of modeling discrete activity data which is the authority of international and obtained from experiment. By using genetic algorithms(GA) to improve the weights and thresholds of BP neural nets(NN), a general activity model of actual solution is established based on experimental data.
By introducing GA-NN model to inclusions systems, the inclusions of MnO-SiO_2、CaO-SiO_2-Al_2O_3 and MnO-SiO_2-Al_2O_3 have been studied in this paper. The control methods in low-melting-point region of these inclusions have been put forword, and the different ways of deoxidization with CaO-SiO_2-Al_2O_3 slag covering are analyzed.
Combination of actual production, the control of inclusion components during the process of alloying, refining and calcium treatment is studied. An analysis of the generation and variational mechanism of inclusions at different circumstances is obtained, and a solution is proposed.
For there's little study on the kinetics of the inclusions' components variation under non-equilibrium state, and GA-NN model can only be applied to the study of the equilibrium composition and morphology of inclusions, irrevisible thermodynamics is introduced to kinetics calculation of inclusions in this paper. From the aspects of chemical reaction and diffusion, the status of inclusions at different period from generation to refining process is stdudied. The formation of inclusions is described from mechanism and a general kinetics equation for describing the components variation of inclusions is obtained by modeling. By the simulation of LF process under laboratory conditions, the phenomenological coefficients of kinetics equations are obtained, and the feasibility of applying irrevisible thermodymics to inclusions calculation is verified.
本论文首先对前人建立的活度机理模型进行了考察,发现这些模型都是建立在很多假设的基础上,对活度组元体系进行了简化,因此应用领域往往受到限制。同时,机理模型在计算方法上,通常采用线性拟合、最小二乘法等传统数学方法进行回归,但是这些方法进行的参数估计不是无偏估计量,拟合精度往往不高。因此,本论文采用了对国际上比较权威的活度实验数据进行离散化的方式,用遗传算法改进BP神经网络的权值和阈值,基于实验数据建立了一种通用的实际溶液组元活度模型。
通过将遗传神经网络模型引入夹杂物体系,本论文对MnO-SiO_2、CaO-SiO_2-Al_2O_3和MnO-SiO_2-Al_2O_3系夹杂物进行了研究,提出了将其控制在低熔点区域的方法,并对CaO-Al_2O_3-SiO_2顶渣覆盖下的不同脱氧方式进行分析。
结合实际生产,本论文对合金化、精炼及钙处理过程中的夹杂物成分控制进行了研究,分析了不同情况下夹杂物的产生及成分变化机理,提出解决措施。
针对前人对非平衡态下的夹杂物成分变化动力学研究较少及遗传神经网络模型只能研究平衡态夹杂物成分及形态的情况,本论文将不可逆热力学引入夹杂物动力学计算,从化学反应和扩散两个方面对夹杂物从生成初始及冶炼过程中不同时期的夹杂物状态进行分析,从机理上阐述夹杂物生成过程,并建模推导出夹杂物成分变化的通用动力学方程式。通过在实验室条件下模拟LF过程,得出动力学方程的唯象系数,并验证了不可逆热力学在夹杂物组元计算的可行性。
The nature of majority of inclusions in steel, in particular the deoxy-generated oxide inclusions directly affect the performance of steel. Under the conditions of existing technology, it is impossible to full remove inclusions in steel. As long as the existence of oxygen in steel, the generation of new inclusions can not be avoid. Therefore, in order to achieve the target of reduction of the harmful effects on performance of steel, the control of inclusions' composition by physical-chemistry methods becomes especially important. In this paper, the thermodynamics and kinetics for controlling inclusions composition are mainly concentrated, based on the invetigation of many domestic and international literatures.
The eatablishment of previous mechanism models is investigated firstly in this paper. It finds that these models are based on a lot of assumptions. Due to the simplified architecture of the activity of components, the application fields are always be restricted. At the same time, mechanism models always use linear fitting, least-squares procedure and so on to regress in the methods of calculation. But parameter estimation of these traditional mathmatics methods is not unbiased estimators, the fitting accuracy is often not high. Therefore, this paper takes the method of modeling discrete activity data which is the authority of international and obtained from experiment. By using genetic algorithms(GA) to improve the weights and thresholds of BP neural nets(NN), a general activity model of actual solution is established based on experimental data.
By introducing GA-NN model to inclusions systems, the inclusions of MnO-SiO_2、CaO-SiO_2-Al_2O_3 and MnO-SiO_2-Al_2O_3 have been studied in this paper. The control methods in low-melting-point region of these inclusions have been put forword, and the different ways of deoxidization with CaO-SiO_2-Al_2O_3 slag covering are analyzed.
Combination of actual production, the control of inclusion components during the process of alloying, refining and calcium treatment is studied. An analysis of the generation and variational mechanism of inclusions at different circumstances is obtained, and a solution is proposed.
For there's little study on the kinetics of the inclusions' components variation under non-equilibrium state, and GA-NN model can only be applied to the study of the equilibrium composition and morphology of inclusions, irrevisible thermodynamics is introduced to kinetics calculation of inclusions in this paper. From the aspects of chemical reaction and diffusion, the status of inclusions at different period from generation to refining process is stdudied. The formation of inclusions is described from mechanism and a general kinetics equation for describing the components variation of inclusions is obtained by modeling. By the simulation of LF process under laboratory conditions, the phenomenological coefficients of kinetics equations are obtained, and the feasibility of applying irrevisible thermodymics to inclusions calculation is verified.
引文
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