采用热重红外联用技术对油页岩干馏过程中产生的两种固体废弃物油页岩干馏残渣和含油污泥进行混烧实验,通过分析燃烧特性曲线、燃烧特性参数、混烧协同作用、样品中各组分的燃烧特性、混烧动力学参数及气体产物的析出特性,对两种固体废...采用热重红外联用技术对油页岩干馏过程中产生的两种固体废弃物油页岩干馏残渣和含油污泥进行混烧实验,通过分析燃烧特性曲线、燃烧特性参数、混烧协同作用、样品中各组分的燃烧特性、混烧动力学参数及气体产物的析出特性,对两种固体废弃物的混烧特性进行了研究。结果表明,油页岩干馏残渣和含油污泥的混烧过程可分为三个阶段。含油污泥的掺入改善了干馏残渣的燃烧状况。干馏残渣与含油污泥的混烧协同作用主要发生在第一阶段和第二阶段。干馏残渣和含油污泥在不同燃烧条件下会出现相互促进或相互抑制的现象。高斯分峰拟合结果表明,混烧过程可分为五个燃烧子反应。基于高斯分峰拟合的Coats-Redfern法计算结果表明,各样品以及各样品中各组分的活化能均不同。含油污泥比例的变化对5个燃烧子反应的影响不同。Friedman法计算结果表明,三个混烧阶段的活化能分别处于50～150、150～200、250～350 k J/mol内。含油污泥促进了干馏残渣的前期和中期的燃烧,但没有改善其后期的燃烧。红外技术分析结果表明,各样品的气体析出规律一致。CO与CO_2排放量的相对值与含油污泥比例不成正比,表明高含油污泥比例不利于充分燃烧。展开更多
In this paper the Hamming distance is used to contr ol individual difference in the process of creating an original population, and a peak-depot is established to preserve information of different peak-points. So me n...In this paper the Hamming distance is used to contr ol individual difference in the process of creating an original population, and a peak-depot is established to preserve information of different peak-points. So me new methods are also put forward to improve optimization performance of genet ic algorithm, such as point-cast method and neighborhood search strategy around peak-points. The methods are used to deal with genetic operation besides of cr ossover and mutation, in order to obtain a global optimum solution and avoid GA ’s premature convergence. By means of many control rules and a peak-depot, the new algorithm carries out optimum search surrounding several peak-points. Alon g with evolution of individuals of population, the fitness of peak-points of pe ak-depot increases continually, and a global optimum solution can be obtained. The new algorithm searches around several peak-points, which increases the prob ability to obtain the global optimum solution to the best. By using some example s to test the modified genetic algorithm, the results indicate what we have done makes the modified genetic algorithm effectively to solve both of linear optimi zation problems and nonlinear optimization problems with restrictive functions.展开更多
文摘采用热重红外联用技术对油页岩干馏过程中产生的两种固体废弃物油页岩干馏残渣和含油污泥进行混烧实验,通过分析燃烧特性曲线、燃烧特性参数、混烧协同作用、样品中各组分的燃烧特性、混烧动力学参数及气体产物的析出特性,对两种固体废弃物的混烧特性进行了研究。结果表明,油页岩干馏残渣和含油污泥的混烧过程可分为三个阶段。含油污泥的掺入改善了干馏残渣的燃烧状况。干馏残渣与含油污泥的混烧协同作用主要发生在第一阶段和第二阶段。干馏残渣和含油污泥在不同燃烧条件下会出现相互促进或相互抑制的现象。高斯分峰拟合结果表明,混烧过程可分为五个燃烧子反应。基于高斯分峰拟合的Coats-Redfern法计算结果表明,各样品以及各样品中各组分的活化能均不同。含油污泥比例的变化对5个燃烧子反应的影响不同。Friedman法计算结果表明,三个混烧阶段的活化能分别处于50～150、150～200、250～350 k J/mol内。含油污泥促进了干馏残渣的前期和中期的燃烧,但没有改善其后期的燃烧。红外技术分析结果表明,各样品的气体析出规律一致。CO与CO_2排放量的相对值与含油污泥比例不成正比,表明高含油污泥比例不利于充分燃烧。
文摘In this paper the Hamming distance is used to contr ol individual difference in the process of creating an original population, and a peak-depot is established to preserve information of different peak-points. So me new methods are also put forward to improve optimization performance of genet ic algorithm, such as point-cast method and neighborhood search strategy around peak-points. The methods are used to deal with genetic operation besides of cr ossover and mutation, in order to obtain a global optimum solution and avoid GA ’s premature convergence. By means of many control rules and a peak-depot, the new algorithm carries out optimum search surrounding several peak-points. Alon g with evolution of individuals of population, the fitness of peak-points of pe ak-depot increases continually, and a global optimum solution can be obtained. The new algorithm searches around several peak-points, which increases the prob ability to obtain the global optimum solution to the best. By using some example s to test the modified genetic algorithm, the results indicate what we have done makes the modified genetic algorithm effectively to solve both of linear optimi zation problems and nonlinear optimization problems with restrictive functions.
