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Modeling Multifractal Features of Soil Particle Size Distributions with Kolmogorov Fragmentation Algorithms

机译:用Kolmogorov破碎算法模拟土壤粒度分布的分形特征。

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We have developed a new type of fragmentation algorithm that was inspired by a theoretical question raised by A.N. Kolmogorov—and still unanswered after 60 yr—regarding the characteristics of fragment size distributions when the size of the fragments, r beta, exhibits a power-law dependence on the size of the original material, r, with 0 ≤ beta ≤ 1. Our fragmentation algorithm uses beta and N (which denotes the number of particles produced in the fragmentation) as input parameters and was used for various simulations performed with N values of 2, 3, and 4 and beta values from 0 to 1. Simulations with beta = 0 resulted in lognormal distributions according to the Kolmogorov–Smirnov goodness-of-fit test at a confidence level of 95%. On the other hand, simulations with fractional values of beta > 0 gave highly heterogeneous distributions exhibiting multifractal characteristics. Rényi dimensions (Dq ) and Holder exponents [α(q)] at q = 0 and 1 were defined with coefficients of determination R 2 >0.95 in 78.3% of samples. The resulting α(0), box dimension D 0, and entropy dimension D 1 = α(1) values spanned the ranges 0.55 to 1.82, 0.52 to 1, and 0.48 to 0.94, respectively, and were thus suggestive of a multifractal nature in the simulated fragment size distributions. The multifractal characteristics of the simulated distributions were consistent with similar analyses performed on actual soil particle size distributions. These results suggest that the new algorithm can be useful for modelingnatural fragmentation processes.
机译:我们开发了一种新型的碎片算法,其灵感来自A.N.提出的理论问题。当碎片尺寸r beta表现出幂律对原始材料r的幂律依赖性,且0≤beta≤1时,关于碎片尺寸分布的特征,Kolmogorov(至今仍未解决60年)仍未得到解答。碎片算法使用beta和N(表示碎片产生的粒子数)作为输入参数,并用于N值为2、3和4且beta值为0到1的各种模拟。根据Kolmogorov–Smirnov拟合优度检验,0导致对数正态分布,置信度为95%。另一方面,分数> 0的分数的模拟给出了高度异质的分布,表现出多重分形特征。用78.3%的样品的测定系数R 2> 0.95定义q = 0和1时的Rényi尺寸(Dq)和Holder指数[α(q)]。所得的α(0),框尺寸D 0和熵尺寸D 1 =α(1)值分别在0.55至1.82、0.52至1和0.48至0.94的范围内,从而暗示了的多重分形性质。模拟的片段大小分布。模拟分布的多重分形特征与对实际土壤粒径分布进行的类似分析一致。这些结果表明,新算法可用于对自然片段化过程进行建模。

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