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Soil Compaction Models ter/air potential individually. There is some evidence that this appears to apply for both sand and clay soils. This conclusion can be drawn as Jennings and Burland (1962) experi- enced changes in soil behaviour which are not accounted for by the effective stress princi- ple. However, as it is possible to draw the influence of water content on soil physical prop- erties rather than on stress, effective stresses can be used again as pointed out in section 6.1.1. Therefore it is necessary to be able to adapt critical state soil mechanics parameters to the given moisture content. This requires the effective moisture content to stay constant during compaction which can be assumed for short term loadings such as from tyre passes in the field. Wheeler and Sivakumar (1995) showed that the intercept of VCL increases with an increase in suction, whereby the slope showed little variance with suction in the range of 100-300 kPa. But the slope falls significantly if the suction is reduced to zero. Toll and Ong (2003) developed a function which relates critical state soil mechanics parameters to the degree of saturation in a normalized form by referencing them to the saturated state. It can be a good way of adding the influence of water content on soil compaction and critical state soil mechanics parameters. A typical critical state soil mechanics modelling approach was undertaken by Blatz and Graham (2003), but the authors added the influence of soil moisture tension to the stress strain relationship and its recovery from swelling. A review of recent models which account for and do not account for the influence of soil water content is included in the paper by Gallipoli et al. (2003). Following the review the authors create a yield surface to incorporate changes in void ratio from drying and use it to account for different soil moisture contents. However, this approach is also based on triaxial tests. Ghezzehei and Or (2001) showed that wet soils have viscoplastic behaviour with a well defined yield stress and nearly constant plastic viscosity. However, rapid transient loading is often too short for complete viscous dissipation of the applied stress which results in an elastic component (viscoelastic behaviour) whereby low water contents and fast loadings increase the elastic component of displacement. In general high water contents decrease viscosity and shear modulus. The depth to which an increase in soil density is measurable is not influenced by the water content (Adam and Erbach, 1995) and thus the influence of the water content may be ig- nored to some extent, as under wet conditions the soil is compacted to the same depth, Ph.D. Thesis Dirk Ansorge (2007) 96
Soil Compaction Models however, the overlying layers can be compacted significantly more. The general influence of water content on predicted soil displacement was shown by Defossez et al. (2003) who further improved SOCOMO with respect to water content. Still with adjusted parameters, the deviation between measured and predicted values was larger than the 95%- CI. From all the studies into soil mechanical parameters, it can be concluded that an in-situ approach to determine VCL parameters from tyre passes would be beneficial. 6.1.4 Basic Considerations on the Modeling of Soil Compaction The fact that plenty of work was conducted concerning the prediction of soil compaction while at the same time no model is able to suit different conditions entirely rose the ques- tion why this is the case. Basically soil can be regarded as a granular media and it should obey the physical laws of granular media. Therefore the author did an extended literature review concerning the physics of granular media. A summary of the most recent findings was edited by Hinrichsen and Wolf (2004). Most research was done concerning the flow of granular media. At the peak of the review the author read an article by Haff (1997) concerning the difficulties in predicting the behavior of geological granular systems. Haff (1997) points out the fact that the prediction is difficult “not because of the lack of knowl- edge in physics of geologists, rather because of a complex behavior of environmental material (sand, soil, galaxies etc.)”. If a granular medium consists of a well grained and evenly shaped powder, physical laws can be developed and the material obeys these laws. However, as soon as either the powder is not well grained and/or not evenly shaped these physical laws cannot be transferred one to one onto a different powder as the variables triggering this behavior cannot be either specified accurately or even specified. The following example points out this behavior excellently. In pure water one molecule is identical with another. Each has the same shape, size and weight. However, already sand, which in soil scientist circles is regarded as uniform and “easy” to predict, differs from one grain to another in mass, size, shape, and friction. Thus all these values have to be averaged and a particular investigation in a controlled laboratory environment can be repeated as long as it is possible to keep the average values sufficiently close. The behavior of the naturally best sorted and particularly well grained sand dunes is difficult to predict even after in depth investigations. Thus, moving from sand to soil adds the difficulty of non identical grains as size distribution varies a lot and does not merely contain sand. Thus the shape of the parti- Ph.D. Thesis Dirk Ansorge (2007) 97
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Cranfield University School of Appl
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Abstract Ancillary experiments show
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Table of Contents TABLE OF CONTENTS
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Table of Contents 4.1.3 Analysis of
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Table of Contents 11.1.1.1 Comparis
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List of Figures and Tables Figure 3
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List of Figures and Tables Figure 1
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Nomenclature NOMENCLATURE Abbreviat
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Introduction 1 INTRODUCTION 1.1 Bac
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Introduction � Ansorge, D. and Go
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Introduction 1.2 Aim To elucidate t
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Introduction a) the soil compaction
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Experimental Methods 2.1.1.1 Test F
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Experimental Methods had been mount
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Experimental Methods track; the loa
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Experimental Methods 800/10.5/2.5 t
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Experimental Methods term. In the m
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Experimental Methods Soil Surface F
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Experimental Methods Depth (cm) 0 1
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Experimental Methods ence surface c
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Experimental Methods chine derives
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Experimental Methods depth. The dat
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Experimental Methods with water and
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Experimental Methods 2.4 Statistica
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Laboratory Studies Into Undercarria
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Page 61 and 62: Laboratory Studies Into Undercarria
Page 77 and 78: Field Study With Full Size Combine
Page 99 and 100: Alleviation of Soil Compaction Howe
Page 101 and 102: Alleviation of Soil Compaction not
Page 103 and 104: Alleviation of Soil Compaction in a
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Page 107 and 108: Soil Compaction Models sibilities t
Page 109 and 110: Soil Compaction Models depends on t
Page 111: Soil Compaction Models Wroth (1968)
Page 115 and 116: Soil Compaction Models level. Criti
Page 117 and 118: Soil Compaction Models Utilizing Ke
Page 119 and 120: Soil Compaction Models average of m
Page 121 and 122: Soil Compaction Models Depth (mm) -
Page 123 and 124: Soil Compaction Models ture content
Page 125 and 126: Soil Compaction Models with four ot
Page 127 and 128: Soil Compaction Models Predicted In
Page 129 and 130: Soil Compaction Models Depth (mm) -
Page 131 and 132: Soil Compaction Models and 13.7 % b
Page 133 and 134: Soil Compaction Models Rel. Density
Page 135 and 136: Soil Compaction Models VCL paramete
Page 137 and 138: Soil Compaction Models The approach
Page 139 and 140: Soil Compaction Models surface stay
Page 141 and 142: Soil Compaction Models This result
Page 143 and 144: Soil Compaction Models 6.6.1.3 Wate
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Page 147 and 148: Soil Compaction Models pressure to
Page 149 and 150: Soil Compaction Models The response
Page 151 and 152: Soil Compaction Models On medium so
Page 153 and 154: Soil Compaction Models SOILFLEX tak
Page 155 and 156: Ancillary Experiments 7 ANCILLARY E
Page 157 and 158: Ancillary Experiments Average conta
Page 159 and 160: Ancillary Experiments In order to c
Page 161 and 162: Ancillary Experiments contrary, the
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Ancillary Experiments Figure 102: S
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Ancillary Experiments track and the
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Ancillary Experiments even when hav
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Ancillary Experiments 7.3.2 Influen
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Ancillary Experiments The results f
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Ancillary Experiments Figure 117: S
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Ancillary Experiments Contact Press
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Ancillary Experiments Figure 123: F
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Ancillary Experiments Sinkage (mm)
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Ancillary Experiments model which o
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Ancillary Experiments 7.3.5 The Inf
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Ancillary Experiments 7.3.7 Discuss
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Ancillary Experiments Terzaghi (194
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Ancillary Experiments contact area.
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Ancillary Experiments soil forward
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Conclusions � The longitudinal so
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Bibliography 10 BIBLIOGRAPHY Aboaba
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Bibliography Defossez, P., Richard,
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Bibliography Gregory, A.S.; Whalley
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Bibliography Lamande, M., Schjonnin
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Bibliography Seig, D., 1985. Soil C
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Appendix 11 APPENDIX Ph.D. Thesis D
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Appendix Figure 32: VCL sample at t
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Appendix comparison at the deepest
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Appendix Estimated Pressure (kPa) 2
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Appendix 11.1.1.2.1 SOCOMO One of t
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Appendix by Seig (1985) who showed
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Appendix Soil water content 15 % an
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Appendix Adapting critical state so
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Appendix density is obtained by add
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Appendix Table 5: Values of constan
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Appendix choice of a concentration
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Appendix 11.1.3.1 Dense/Hard and Lo
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Appendix 11.1.3.2 Stratified Soil C
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Appendix To summarize the ability t
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Appendix In the following the predi
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Appendix concentration factor of 4,
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Appendix 11.1.5.1 Confining Pressur
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Appendix Figure 24. The VCL created
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Appendix Rel. Density 2 1,9 1,8 1,7
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Appendix relation of � 1 to � 2
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Appendix Rel. Density 2 1,9 1,8 1,7
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Appendix Rel. Density 1,7 1,68 1,66
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Appendix Depth (mm) 0,0 100,0 200,0
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Appendix Figure 42: Plate in cookin
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Appendix � z � � �� k c p
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Appendix Table 8: n and k depending
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Appendix to the plate sinkage equat
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Appendix with a slight deviation fr
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Appendix Table 12: DBD values for a
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