A refined representation method of the particle size distribution curve based on grading entropy
Source abstract
Abstract
The particle size distribution (PSD) curve is an important expression of the basic properties of the soil. The characteristic parameters such as median particle size D 50, effective particle size D 10, and some combinations of characteristic parameters can only represent some points of the PSD curve, failing to represent all information of the PSD curve. In this paper, a fraction characteristic parameter F that could reflect the fraction size variation of the PSD curve was introduced based on grading entropy. And a new presentation method of the A-B-F three parameters was proposed for a refined representation of the PSD curve. It was found that the newly constructed model not only better represents the differences in the width of PSD curves but also has a higher sensitivity than the A-B two-parameter model proposed by Lőrincz. For PSD curves with similar distributions, the new presentation method has a higher degree of discrimination than that of the D 50- C u- C c three-parameter or the four-parameter combination G c proposed by Arshad. Finally, the application of this new method in describing the spatial nonuniformity distribution of depositions and predicting the soil hydraulic conductivity was discussed. The research results can provide a reference for the refined representation of PSD curves.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Soil and Unsaturated Flow · Landslides and related hazards · Dam Engineering and Safety
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (56)
Show source-provided references
1. Evolution of hydraulic conductivity models for sandy soils10.1680/jgeen.18.00062 ↗
2. The pattern of natural size distributions10.1111/j.1365-3091.1980.tb01170.x ↗
3. Concepts of" fractals" in soil science: Demixing apples and oranges10.2136/sssaj1998.03615995006200050046x ↗
4. The pore–solid fractal model of soil density scaling10.1046/j.1365-2389.2003.00481.x ↗
5. Effects of the particle shape and size of sands on the hydraulic conductivity
6. Goodbye, hazen; hello, kozeny-carman10.1061/(ASCE)1090-0241(2003)129:11(1054) ↗
7. Predicting the saturated hydraulic conductivity of sand and gravel using effective diameter and void ratio10.1139/t04-022 ↗
8. Assessing internal erosion with the modal decomposition method for grain size distribution curves10.1007/s11440-019-00865-z ↗
9. Re-interpreting ‘segmented’ grain-size curves10.1017/S001675680002793X ↗
10. Understanding coastal morphodynamics using stability methods
11. Influence of grain size distribution on dynamic shear modulus of sands10.1515/eng-2017-0036 ↗
12. Observations on internal stability of cohesionless soils10.1680/geot.2006.56.7.497 ↗
13. Permeability assessment of some granular mixtures10.1680/jgeot.17.T.039 ↗
14. Particle-size distribution in soils: A critical study of the fractal model validation10.1016/j.geoderma.2006.03.008 ↗
15. The statistical analysis of ‘mixed’grain size distributions from aeolian sands in the Libyan Pre-Desert using log skew Laplace models10.1144/GSL.SP.1987.035.01.18 ↗
16. An equation to represent grain-size distribution10.1139/t00-015 ↗
17. Optimal definition of class intervals for frequency tables10.1080/02726358308906373 ↗
18. Representation of soil aggregate-size distribution by a logarithmic-normal distribution10.2136/sssaj1956.03615995002000020003x ↗
19. Enzyme-triggered deep tumor penetration of a dual-drug nanomedicine enables an enhanced cancer combination therapy10.1016/j.bioactmat.2023.02.015 ↗
20. EF_Unique: An improved version of unsupervised equal frequency discretization method10.1007/s13369-018-3144-z ↗
21. The hyperbolic shape triangle as a tool for discriminating populations of sediment samples of closely connected origin10.1111/j.1365-3091.1992.tb02145.x ↗
22. Clustering methods with qualitative data: A mixed-methods approach for prevention research with small samples10.1007/s11121-015-0561-z ↗
23. Models for estimating soil particle-size distributions10.2136/sssaj2002.1143 ↗
24. Case studies and benchmark examples for the use of grading entropy in geotechnics10.3390/e14061079 ↗
25. Some comments on the entropy-based criteria for piping10.3390/e17042281 ↗
26. Geometrical assessment of internal instability potential of granular soils based on grading entropy10.1007/s11440-020-01118-0 ↗
27. An image-based gradation calculation method considering crushed stone morphology10.1155/2022/7291223 ↗
28. Internal stability of granular filters: Reply10.1139/t86-068 ↗
29. On environment-sensitive grain-size parameters10.1111/j.1365-3091.1968.tb01911.x ↗
30. Particle size distributions of South Tunisian soils erodible by wind10.3166/ga.24.37-47 ↗
31. Comparison of two different approaches of sensitivity analysis10.1016/S1474-7065(02)00049-9 ↗
32. A unified expression for grain size distribution of soils10.1016/j.geoderma.2016.11.011 ↗
33. Depositing characteristics of landslide dams and advances in the model test for seepage failure10.15244/pjoes/151601 ↗
34. Recent advances in development of dendriticpolymer-based nanomedicines for cancer diagnosis
35. Fractality of grain composition of debris flows10.1360/gs050309 ↗
36. Lőrincz · 1986
37. The grading entropy-based criteria for structural stability of granular materials and filters10.3390/e17052781 ↗
38. Grading entropy variation due to soil crushing10.1061/(ASCE)1532-3641(2005)5:4(311) ↗
39. GSH-sensitive polymeric prodrug: Synthesis and loading with photosensitizers as nanoscale chemo-photodynamic anti-cancer nanomedicine10.1016/j.apsb.2021.05.003 ↗
40. Volumetric consequences of particle loss by grading entropy
41. Factorial sampling plans for preliminary computational experiments10.1080/00401706.1991.10484804 ↗
42. Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases10.1016/S0016-7061(99)00014-2 ↗
43. Determination of soil permeability coefficient following an updated grading entropy method10.1680/jgere.19.00036 ↗
44. On measures of entropy and information
45. Implementation of equal width interval discretization on smarter method for selecting computer laboratory assistant
46. Methoden zur Bestimmung der Durchlässigkeit des Bodens10.1007/BF01341054 ↗
47. Properties of laterite soils from sources near Nibong Tebal, Malaysia
48. Uncertainty and sensitivity analysis of SWMM model in computation of manhole water depth and subcatchment peak flood10.1016/j.sbspro.2010.05.205 ↗
49. Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R10.1016/j.jhydrol.2013.08.047 ↗
50. A unifying quantitative analysis of soil texture10.2136/sssaj1984.03615995004800010026x ↗
51. Singh · 2014
52. Breakage and shape analysis of ballast aggregates with different size distributions10.1016/j.partic.2017.02.004 ↗
53. The strength of concrete, its relation to the cement aggregates and water
54. A simple particle-size distribution model for granular materials10.1139/cgj-2017-0098 ↗
55. A fractal entropy-based effective particle model used to deduce hydraulic conductivity of granular soils10.3390/fractalfract6090474 ↗
56. A two-parameter Weibull function to describe airborne dust particle size distributions10.1002/(SICI)1096-9837(199909)24:10<943::AID-ESP30>3.0.CO;2-9 ↗