Figure 1.
Test site and layout of varied CPTU tests at Halsen-Stjørdal from NGU [19], modified by the authors.
Citation: Ekaterina Kldiashvili, Archil Burduli, Gocha Ghortlishvili. Application of Digital Imaging for Cytopathology under Conditions of Georgia[J]. AIMS Medical Science, 2015, 2(3): 186-199. doi: 10.3934/medsci.2015.3.186
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The presence of an unknown degree of partial consolidation during a piezocone penetration test (CPTU) in silts complicates the interpretation of geotechnical parameters in these soil deposits. It is well established that standard rate (20 mm/s) CPTU tests in clays are carried out under undrained conditions whereas CPTU tests conducted in sands follow a drained penetration behaviour. For intermediate soils such as silts the penetration behaviour is complex and choosing an appropriate penetration rate is not easy due to the development of an unknown degree of partial drainage during standard penetration. Furthermore, the composition and structure of silt deposits impede the collection of high-quality soil samples and hence high-quality laboratory soil data is rather difficult to achieve [1]. Neglecting the presence of partial drainage in these materials may lead to a significant risk of over- or underestimating the geotechnical design parameters. Consequently, the improvement of interpretation models of in-situ testing methods becomes even more important in soils where partial drainage is present.
Up to recently, the focus of research interest has been on rate dependency in clayey soils and the influence of penetration rate on derived estimated geotechnical parameters. Recently, attention has been drawn to the field of intermediate soil behaviour focusing mainly on centrifuge and laboratory studies rather than field research sites [2,3,4,5,6]. Thus, it appears that existing published field data is rather limited and only a few studies have been documented dealing with the consolidation behaviour of silt deposits and the interpretation of consolidation parameters in these complex soils [7,8,9,10].
In order to study the influence of penetration rate in silts on the interpretation of consolidation parameters and to establish recommendations on how to interpret them in partial drained soil deposits a comprehensive field and laboratory testing program has been conducted by the Norwegian University of Science and Technology (NTNU). The field study comprised CPTU tests with penetration rates varying between 0.5 mm/s up to 200 mm/s followed by numbers of dissipation tests at four different depths of interest in the affected silt layer (4 m to 14 m). Supporting the field results, soil samples have been taken in the silt layer using thin walled 54 mm steel sample tubes for the purposes of laboratory consolidation testing.
The present paper focuses on the interpretation of consolidation parameters from the silt site by using corresponding field and laboratory test results. Several methods have been applied to the data in order to establish t50 values (time for 50% dissipation of excess pore pressure) for non-standard dissipation tests [11,12,13,14]. In order to consider partial drainage effects on the coefficient of consolidation (ch), the method proposed by DeJong & Randolph [15] has been applied to the data set. Furthermore, the procedure proposed by Schnaid et al. [16] for intermediate materials has been used in order to study the drainage behaviour and degree of partial consolidation of the soil deposit. Based on the results from the Halsen-Stjørdal study, the recommended procedures have been applied to existing dissipation data from the silt at the Norwegian Geo-Test Site (NGTS) in Halden, Norway in order to support and verify the findings. Recommendations have been made for practicing engineers on how to consider partial drainage in silts when establishing design parameters.
The research investigation test site Halsen-Stjørdal which is used for the current study is situated about 35 km north-east from Trondheim in Norway (Figure 1). The ground conditions are dominated by a thick low plastic silt deposit which is overlain by a stiff, coarse 4 m top layer. The ground water level is at 2.8 m depth and hydrostatic ground conditions prevail. The geological history of the area is defined by the Quaternary period. Enormous masses of fine-grained material were transported by rivers of melt water into the sea during the last de-glaciation. The Halsen-Stjørdal test site is primary characterized by these materials, forming a very irregular soil deposit with layers and lenses of clay and coarser sand. Geological studies carried out in the area indicate a normally to light overconsolidated (OC) soil deposit [17]. The current site is about 500 m away from the well-known Halsen test site investigated by Sandven [18].
In order to study the material behaviour of the silt deposit an extensive laboratory and field-testing program was conducted. The layout of the test site (Figure 1) covers an area of about 11 m × 8 m. Several CPTU tests were performed using a standard 10 cm2 friction cone with measurements of the pore pressure at the u2 position. The penetration rates were varied between 0.5 mm/s and 200 mm/s throughout the 25 CPTU tests in order to study the drainage behaviour of the silt in detail, aiming to cover all drainage conditions varying from drained, partial drained to undrained. In addition, dissipation tests were carried out at four predetermined depths of interest where the penetration was paused, and the development of the pore pressure was measured over time. To avoid possible movement of the system during a dissipation test, the rods were clamped carefully during each test. In addition to the field measurements, thin walled 54 mm steel sample tubes were used to take series of continuous soil samples.
During the field-testing program a series of soil samples were taken from three boreholes down to a sampling depth of 14 m (Figure 1). To ensure highest possible soil sample quality, all samples were extruded and analyzed in the laboratory within 24 hours of sampling time. Bihs et al. [20] give a detailed description of the different test methods used, results obtained in the laboratory and discuss sample quality. The results reveal a rather irregular silt deposit with varied soil parameters with depth, reflecting the geological history of the material. The sample quality has been assessed by applying the clay based volume change criteria [21] as well as the strain energy compression ratio criteria [23], revealing reasonable sample quality for the present silt deposit [22].
Figure 2 shows the basic laboratory results indicating an upper and lower silt layer from 4 m to 8 m and from 8 m to 14 m respectively. The water content is rather constant with depth with an average value of about 24%. Sensitivity measurements using the falling cone test indicate a medium sensitive material deposit with slightly increasing values with depth from about 10 at the top of the upper silt layer down to 28 in the lower silt layer.
Grain size distribution measurements reveal a sandy and/or clayey SILT with an average clay, sand and silt content of 7%, 38% and 55% respectively by applying the Norwegian recommendations made by the Norwegian Geotechnical Society (NGF) to identify the soil type [24]. Furthermore, the results show an increase of clay and sand content with depth and a slight decrease of silt content.
A series of 1D consolidation constant rate of strain (CRS) have been carried out on 2 cm thick samples following the standard procedure described by Sandbæ kken et al. [25] and applying axial strain rates between 2 %/h to 5 %/h. Due to the silty nature of the material and some possible partial sample disturbance which occurred during sampling and extruding in the laboratory, the stress strain curves of the soil samples are of rather rounded character, not showing a distinct effective preconsolidation pressure (p'c) which is characteristic for silt deposits. Several researchers stated similar findings in silts, e.g. [26,27]. The well-known method proposed by Becker et al. [28] was applied to the measured data sets and revealed overconsolidation ratios (OCR) between 1–2, indicating a normally to lightly overconsolidated material deposit. These findings are supported by the geological history of the area and prior analyses carried out by Sandven [18] nearby the present test site. Vertical coefficients of consolidation (cv) were deduced using the method established by Janbu et al. [29]. Figure 3 A shows examples of cv varying with vertical effective stress (σv') for two different samples taken between 7.45 m and 9.7 m.
Figure 3B shows the variation of cv0 (taken at in-situ effective stress (σv0')) with depth for all samples analyzed, implying a rather irregular silt deposit. For the upper silt layer cv0 values are scattered and vary between 80 m2/year and 750 m2/year whereas the results for the lower silt layer are more consistent between 80 m2/year and 300 m2/year. Results from Sandven [18] indicate similar varied results stressing the influence of sample disturbance and irregular soil layering.
By following the procedure proposed by Berre [30], several anisotropically consolidated undrained triaxial compression tests (CAUC) have been carried out on samples from Halsen-Stjørdal. To achieve consistent test results, a shearing rate of 4 %/h is used and a backpressure of 200 kPa was applied to most of the samples. Due to the rather dilative behaviour of silts in triaxial compression, no unique maximum shear strength can be defined, resulting in a continuous increase of stress during shear. To establish undrained shear strength (su) profiles in these soils, Brandon et al. [31] proposed several criteria to determine su. Using criteria (5) where su is taken at the maximum measured pore pressure appeared to reveal most consistent results for this site and ensures a design strength being well below the fully mobilized strength at high strains [31]. Figure 4A shows the su profile with depth with an average value of about 55 kPa. Furthermore, values of the effective friction angles (φ') have been determined for the site with an average φ' of 36.9°.
To correctly determine consolidation parameters from CPTU tests, an evaluation of the rigidity index (IR = G/su) is required. A lot of research has been carried out to relate the size of the plastic failure zone that is generated during a CPTU test to IR [14,15]. With increasing IR the failure zone increases which influences the generation and development of excess pore pressures and in turn ch. Therefore, it is essential to determine a thorough design profile of IR for each test site when dealing with the interpretation of dissipation tests from CPTU and it needs to reflect the actual stress distribution around the penetrating cone [33]. Although several approaches are available to determine IR, use of high-quality laboratory data for G and su to establish a rigidity index profile is preferred. Shear strength values should represent the average strength around the cone whereas the shear modulus is often taken at 50 % mobilized strength (G50) in the CAUC test as it represents the average soil response of the affected soil volume around the cone [32].
A number of different approaches have been published over time to deduce IR. Keaveny & Mitchell [34] proposed an empirical relationship based on triaxial test data using a combination of OCR and plasticity index (IP). Furthermore, Kulhawy & Mayne [35] established a relation for IR based on a Cam-clay derivation. Later Mayne [36] reformulated the critical state soil mechanics approach and derived an expression for IR based on CPTU measurements. Agaiby & Mayne [37] formulated an expression for IR based on post-processing of CPTU data. Krage et al. [32] stated that the interpretation of IR in silty material is demanding due to the presence of partial drainage and the challenge of achieving high quality soil samples. Krage et al. [32] established two different methods to estimate IR. Method A is based on laboratory test results for su and empirical estimates for G50/ Gmax where Gmax represents the tangent modulus at low strains. Method B uses seismic CPTU data.
Figure 4B shows the application of method A and B as well as the laboratory data from triaxial test results for the Halsen-Stjørdal test site. The approaches suggested by Mayne [36] and Agaiby & Mayne [37] resulted in unreliable low values for IR and were neglected in the present study. IR values vary between 100 and 300, with an increasing tendency with depth. Method A falls in between the lower results from method B and the higher values for IR from triaxial tests. Carroll & Paniagua [38] applied the methods proposed by Krage et al. [32] to a silt test site and confirmed good agreement with values established from laboratory tests. For the following consolidation analysis, a rigidity index of 200 has been chosen for the upper silt layer whereas an average IR of 250 is applied to tests below 8 m depth. Table 1 summarizes results from research test sites studying CPTU dissipation tests in silts confirming that the IR from Halsen-Stjørdal falls in between the intervals used by others dealing with low plastic and lightly overconsolidated silts.
| Reference | soil type | OCR (-) | IP (%) | IR (–) |
| Suzuki et al. [39] | clayey silt | * | 21 | 150 |
| Holmsgaard et al. [7] | sandy silt | – | 1.5–4.1 | 275 |
| Garcia Martinez et al. [40,41] | clayey silt | * | 0–8 | 130 |
| Krage et al. [9] | sandy silt | 10–15 | 0–5 | 240 |
| Tonnie et al. [42] | clayey, sandy silt | 1–2 | 5–20 | – |
| Carroll & Paniagua [38] & Blaker et al. [8] | clayey silt | 1–1.3 | 6.6–9.3 | 126–147 |
| present study | clayey, sandy silt | 1–2 | 0 | 200–250 |
| Note: * lightly overconsolidated. | ||||
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During the field-testing program, several standard rate CPTU tests have been carried out with a penetration rate of 20 mm/s down to a depth of about 18 m. All tests were executed by following the international standard procedures according to ISO 22476–1 [43]. It was necessary to predrill through a 4 m hard and stiff top layer, so as to keep the pore water filters saturated during the penetration process. The results of the penetration tests are presented in terms of measured cone resistance (qt) corrected for out of balance pore water pressure effects, pore pressure at the u2 location (u2) and measured sleeve friction (fS). Furthermore, the ratio of measured excess pore pressure to net cone resistance (qt–σv0) is defined as the pore pressure parameter Bq and can be studied in Figure 5.
The results from the standard penetration rate tests reveal an irregular silty soil deposit with small layers and lenses with varying properties and indicating a coarse, sandy silt deposit. Measurements of qt are rather constant with an average value of about 1.5 MPa, although showing some peak values between 10 m and 12 m. Pore pressure readings are very scattered, measuring values around the hydrostatic line (u0) and even negative values are recorded. The results from the sleeve friction readings increase with depth, indicating a very irregular and scattered soil deposit. Bq values for the silt layer (4 m to 14 m) are very low and even negative due to the low u2 readings which make this parameter very sensitive to the measured results. Below 14 m the soil deposit becomes more clayey and less silty which is emphasized by more steady qt measurements, increasing u2 and decreasing fs readings. As a result of higher u2 values, Bq increases in this layer. Overall findings from the standard CPTU tests confirm the results from the laboratory investigations.
In addition to standard penetration rate CPTU tests, series of different rate tests have been carried out at the research test site by changing the rate between 0.5 mm/s and 200 mm/s but kept constant for each single test. By varying the penetration rate, it was aimed to cover all penetration conditions from drained to partially drained and finally undrained. A detailed analysis and evaluation of the varied penetration tests and drainage conditions at the Halsen-Stjørdal site can be found in Bihs et al. [10]. Figure 6 presents results for the silt layer between 4 m and 14 m by averaging the results for qt, excess pore pressure Δu2 (u2–u0) and fS over the upper and lower silt layer depth and plotting the results over the corresponding penetration rate (v).
The results show a clear rate dependency of the registered qt and u2 measurements. The cone resistance increases with decreasing penetration rate, with a maximum of 3.1 MPa for the slower tests. For fast penetration rates qt readings even out and are about 1.1 MPa at a minimum. The results for excess pore pressures indicate an opposite trend. For slow penetration rates, the values converge to a constant low level representing hydrostatic conditions. On the other hand, for fast penetration rates, Δu2 readings increase and reveal high negative measures for the fastest penetration rates. Due to the very scattered fs results, it was difficult to state a rate dependency for this parameter although it seems that fs decreases in general for higher penetration rates in a similar manner to qt.
Various dissipation tests have been conducted during the field program at Halsen-Stjørdal at different depth of interest (Figure 5), covering all rates of penetration. To ensure no movement of the CPTU system, it was important to ensure fixed clamps during each dissipation measurement. For clay soils in undrained conditions typical dissipation behaviour expected would follow a monotonic decrease in pore pressure over time, reaching the hydrostatic pore pressure limit after time. However, researchers have observed several different dissipation curves types especially in high OC soils and intermediate soil deposits that can be categorized into types according to Sully et al. [11]. Figure 7 illustrates the types of dissipation curve divided into Type II to V for pore pressure measurements taken at the u2 position. Type II and V represent dissipation tests that follow a monotonic decay of pore pressure over time although Type V represents the inverse of Type II starting below hydrostatic pore pressure level. Type III dissipation curves start above in-situ pore pressure, increase up to a maximum level and dissipate finally to the equilibrium in-situ condition. Type IV dissipation behaviour is like Type III although starting below in-situ level, increasing above and finally dissipating to the in-situ pore pressure level again. In the literature, dissipation test Type II is named a standard dissipation test whereas Types III to V are defined as non-standard or dilatory tests [36].
In normally consolidated soils standard dissipation behaviour is expected whereas in a highly overconsolidated, fissured or intermediate soil deposit, non-standard dissipation curves dominate the results [36]. Reasons for the appearance of these non-standard dissipation curves are numerous. Sully et al. [11] stated that the main reason for the rise in pore pressure before decay is mainly due to the redistribution of pore pressure directly after a stop in penetration. Usually the pore pressures at the tip are higher than directly behind the cone which result in a gradient of pore pressure towards the u2 location, causing a drainage flow from the tip to the shaft [44]. Factors influencing the rate of drainage are soil permeability and values of the pore pressure gradient. Furthermore, the strength and stiffness of the soil surrounding the cone influence the gradient and hence the rate of dissipation. Another reason for the occurrence of non-standard dissipation curves is the influence of shear induced pore pressures [44]. Shear induced dilatancy causes a reduction in excess pore pressure near the shoulder of the cone compared to the adjacent soil. When penetration is halted, the higher excess pore pressures in the adjacent zone will cause a redistribution of pore pressure towards the u2 position. Some researchers argue that poor saturation of the filter elements can cause the non-standard dissipation curves [12,45]. Although poorly saturated filters can cause a slow sensor response, it is now generally accepted that this is unlikely to be a significant reason for this dissipation behaviour [44].
Figures 8 to 10 reproduce the dissipation tests carried out at the site sorted by dissipation depth, rate of penetration and dissipation behaviour type. The difference in measured pore pressure before the start of the dissipation test and the first registered reading at the beginning of the test are small and hence neglectable. The y-axis scales are altered for clarity whereas the x-axis scales are kept the same. For dissipation test locations in the silt layer (4–14 m) the non-standard dissipation behaviour prevails whereas below in the more clayey layer, the standard dissipation behaviour dominates the results (Figure 8). The deepest location at 17.8 m is characterized by a monotonic behaviour for the slow and standard penetration rates whereas the fast tests produce non-standard dissipation tests, indicating less rate dependency than the dissipation tests in the more silty layer above (4–14 m). Figure 9 shows the dissipation tests divided into the different penetration rates. In general, the slow tests measure mainly hydrostatic in-situ pore pressures which is defined as drained penetration and supports the findings from the rate study in Bihs et al. [10]. Up to penetration rates of about 20 mm/s the standard dissipation curves predominate, whereas the dissipation tests carried out at faster penetration rates are characterized by a non-standard dissipation behaviour. Figure 10 groups the tests into the four different dissipation types. Type III and IV dissipation tests represent about half of the analyzed tests and are for the most part in the silt layer (4–14 m). Type II and V dominate for the soil unit below 14 m indicating that penetration tests carried in the more clayey layer are mainly represented by a monotonic dissipation behaviour.
In order to understand the mechanisms, it is necessary to study the composition of measured penetration pore pressures. It is well recognized that u2 is a combination of hydrostatic pore pressure (u0), change in octahedral normal stress or mean total stress (uoct) and change in shear (ushear) [46,47]. Although it is not possible to separate the measurements into the different components, a theoretical classification is possible according to (1):
|
$
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(1) |
Figure 11 represents a few dissipation tests with varied penetration rates from two locations in the silt layer by means of measured Δu2 over time. Equilibrium pore pressures are measured for the very slow rate test whereas the fastest tests at 100 mm/s and 200 mm/s respectively are characterized by a Type V, starting at a high negative excess pore pressure level and monotonically dissipating towards equilibrium. The medium rate penetration tests at 20 mm/s and 60 mm/s are represented by a Type III and IV dissipation test respectively. In general, it is evident that the negative shear component Δu2, shear increases with increased penetration rate. Schneider et al. [3] carried out a centrifuge piezocone study with different soil mixtures and achieved similar results for the normally consolidated samples of silty material. Furthermore, Chow et al. [48] presented penetrometer centrifuge studies in a reconstituted, normally consolidated, natural calcareous silt including dissipation tests after varied penetration rates. The investigation revealed comparable varied rate dissipation curves to this study which support the findings from the present study.
Dissipation tests are frequently used in engineering practice to estimate the coefficient of consolidation. However, the interpretation of dissipation tests from a soil deposit is complicated due to several reasons. These include the complexity of estimating the initial pore pressure distribution, soil disturbance due to the penetrating cone, which can create a zone of disturbed soil with lower permeability, and lastly dissipation of pore pressure is often influenced by soil anisotropy [49]. Dissipation tests in an undrained situation cause large strains in the adjacent soil immediately next to the CPTU, which is remoulded due to the penetration process, e.g. dissipation takes place in a partially remoulded soil element. In addition to the remoulding effect, large pore pressures are generated (especially in cohesive soils) due to the cavity expansion generated by the cone which causes a reduction in effective stress [45]. Upon a stop in penetration these excess pore pressures dissipate over time until reaching an equilibrium state. It is generally recognized that radial consolidation controls the conditions at the u2 position, concluding that the coefficient of consolidation in the horizontal direction (ch) dominates the consolidation process.
The interpretation solution most widely used was established by Teh & Houlsby [14] for soils in undrained dissipation conditions. The initial pore pressure distribution is idealized by large strain, finite element analysis in combination with the stress path method (SPM). A modified time factor T* is introduced as a theoretical solution for various degrees of consolidation, depending on the cone radius (r) and IR in the following way
| $ T^{*} = \frac{c_{h} \cdot t}{r^{2} \cdot \sqrt{I_{R}}} $ | (2) |
The process involves a plot of normalized excess pore pressure (U = Δut/Δuinitial) against log time (t) in order to select the time associated with 50% dissipation (t50) which is usually taken as a representative value for the estimation of ch.
Due to the existence of non-standard dissipation test curves in silts, it is necessary to adjust the initial pore pressure dissipation curve so that existing theories can be applied to the measured data. A first attempt to account for the non-standard behaviour was made by Burns & Mayne [12]. They based their solution on a cavity expansion-critical state model. Some important input parameters to their approach are OCR, IR and φ. To achieve a best fit of the theoretical curve to the measured data, iteration of ch and IR is required.
Furthermore, several correction methods to the original t50 have been established to consider the non-standard behaviour. Sully et al. [11] introduced several methods of fitting the measured curve to the theoretical one. The two most common approaches are the square root of time plot correction and the logarithm of time plot correction. The first approach uses extrapolation techniques to adjust the measured pore pressure curve to a new maximum pore pressure value at t = 0 and normalizes all values by this new maximum pore pressure. The later method is based on adjusting the curve to the measured maximum pore pressure value during a test by adjusting the time values according to tnew = 0 at that maximum u2 point. However, choosing one of the adjusting methods proposed by Sully et al. [11], one has to keep in mind, that the initial part of the dissipation curve is not considered. Later Chai et al. [13] suggested a new approach to adjust the t50 for non-standard dissipation curves by an empirical correction of the original t50 using cylindrical cavity expansion simulations, including IR and t50.
Recent research carried out in silty soil deposits reveal, that the presence of partial consolidation contradicts the assumption of undrained conditions during penetration and reduces the initial excess pore pressure compared to the undrained state. The existence of partial drainage causes an incorrect estimate of ch if undrained solutions are applied [15,50]. DeJong & Randolph [15] established a method to correct for partial drainage by modifying the original approach from Teh & Houlsby [14] for undrained penetration (based on a nonlinear soil model) and applying numerical (finite element analysis and cavity expansion) and field and centrifuge CPTU data. By accounting for different drainage conditions during dissipation tests, an underestimation of ch can be prohibited. It is recommended to apply the proposed equations if the deduced t50 values are less than 100 s [15].
Although the more recent developed methods that account for non-standard dissipation behaviour and partial consolidation are promising, they do not aim to provide a perfect solution to the complex problem. They provide a range of solutions as a framework for practicing engineers to adjust the design parameters according to a specific problem [51].
For further discussion, the layer between 4 m and 14 m will be referred to as one silt layer. Initially the data has been applied to the approach of Teh & Houlsby [14] resulting in t50 values for the site presented in Figure 12A for the Type II and V dissipation tests. The t50 values are widespread varying between 20 s and 260 s with an average value of 135 s, reflecting the rather layered and irregular structure of the soil deposit. To evaluate the t50 values for the Type III and IV dissipation tests, the approach proposed by Burns & Mayne [12] has been initially used. Unfortunately, the curve fitting procedure which is necessary to match theory with measured data resulted in unrealistic values for IR and ch hence this method is not further considered in this study. Paniagua et al. [52] and Carroll et al. [38] reported similar findings. Furthermore, correction methods by Sully et al. [11] and Chai et al. [13] have been used to deduce t50 values for the series of Type III and IV dissipation tests.
Figure 12B presents the data including the results for Type III and IV dissipation tests by Teh & Houlsby [14] showing an even more irregular profile than for the Type II and V dissipation tests shown in Figure 12A. Values of t50 vary between 30 s and 450 s and it can be seen that the results for the different methods are especially scattered in the silt layer. Below 14 m the results converge but no trend with depth can been recognized. The approach suggested by Chai et al. [13] led to a very irregular and widespread t50 profile, concluding that this approach is not as appropriate for the current test site. Centrifuge studies carried out by Mahmoodzadeh & Randolph [4] reported inconsistent results from the approach proposed by Chai et al. [13]. Comparing the two approaches by Sully et al. [11] Figure 12B indicates that the square root correction method revealed the most consistent results for the present site. Several researchers reported that the square root correction plot was the most successful one when dealing with the interpretation of Type III and IV dissipation curves in intermediate soils [4,48,53]. Overall, the approach by Teh & Houlsby [14] overestimates the t50 compared to the square root correction method by an average factor of 2.1 which emphasizes the fact that this method reveals unrealistic high values for these dissipation tests.
Figure 13 shows examples from the silt layer where the normalized excess pore pressure is plotted against T* demonstrating the fact that the theoretical solution from Teh & Houlsby [14] is not able to reproduce the measured results for dissipation curves of Type III and IV. Furthermore, the square root correction plot by Sully et al. [11] has been included showing that this method can adopt to the rise in pore pressure even though information about the pore pressure development before the maximum value is not considered.
Figure 14A shows the final design values for the Type III and IV dissipation tests from the square root correction plot together with the results from the Type II and V dissipation tests from Teh & Houlsby [14]. About 1/3 of the tests in the silt layer have a t50 < 100 s which is defined by DeJong & Randolph [15] as a limiting value for partial consolidation. If ignored, the results from interpreted ch values may be significantly underestimated. The development of t50 with penetration rate is presented in Figure 14B. Although showing rather scattered results, a clear trend of decreasing t50 with increasing penetration rate is observed. Paniagua et al. [52] carried out studies covering results from a natural silt deposit and laboratory studies on reconstituted natural silt samples, indicating the same trend as observed in the present study. Furthermore, Carroll et al. [38] reported decreased t50 values with increased rate, suggesting that the high negative excess pore pressures generated during very fast penetration tests lead to a significant increase in dissipation rate compared to the slower tests.
Even though the interpretation of ch in partial consolidated soils is complicated, an attempt has been made to establish an estimated design profile for the horizontal coefficient of consolidation. The tests influenced by partial consolidation (t50 < 100 s) have been analyzed separately from the remaining ones. First the conventional approach by Teh & Houlsby [14] has been applied to the data set. Furthermore, the correction method proposed by DeJong & Randolph [15] has been used in order to account for partial consolidation. Figure 15A presents results for the partially consolidated tests analyzed with the common approach by Teh & Houlsby [14] indicating values varying between 75 m2/year and 400 m2/year.
Furthermore, the separation line between typical ch values (95 m2/year) expected for clay and silt has been included in Figure 15, indicating that the approach by Teh & Houlsby [14] underestimated the coefficient of consolidation, defining the deposit towards the clayey like behaviour.
Applying the approach by DeJong & Randolph [15] to the partial consolidated dissipation tests revealed a ch profile according to Figure 15B showing minimum and maximum values of about 380 m2/year and 900 m2/year for the silt layer. By taking partial consolidation into account, the values for ch increase for the silt layer by about 1.3 and are located more in the silt region compared to the results from Figure 15A. It can be concluded, that the application of the approach proposed by Teh & Houlsby [14] is not recommendable for silty deposits with partial consolidation taking place during penetration.
DeJong & Randolph [15] established a graphical solution including the original theory proposed by Teh & Houlsby [14] plotted as straight lines into the logarithmic plot of ch over t50 together with the new solution of incorporating partial drainage presented in Figure 16 for a 10 cm2 cone [51]. The different lines represent different levels of IR. For undrained conditions, e.g. small ch values, the new method coincides with the method by Teh & Houlsby [14]. However, for values of t50 < 100 s partial consolidation increases and with increasing ch values the solutions diverge.
Dissipation tests with t50 < 100 s have been plotted into Figure 16. Figure 16A presents the solution proposed by Teh & Houlsby [14] revealing results plotted around the theoretical line of IR = 200 as expected. Whereas Figure 16B shows the theory applied by DeJong & Randolph (2012) taking partial consolidation into consideration. As t50 decreases, ch increases and the results plot close to the IR = 200 line proposed by DeJong & Randolph [15], supporting the fact the ch is underestimated in partial consolidated materials if drainage is not considered.
An estimated ch profile with depth has been established from the dissipation tests taken at the site. The results are presented in Figure 17A, indicating a more scattered profile for the silt layer and converging more for the deeper layer below 14 m, emphasizing the rather layered and irregular structure of the silt layer. Figure 17B shows average ratios of ch/cv0 which have been determined for the site revealing scattered result varying up to a maximum of 3.1, representing ranges similar to those reported in the literature [4,54]. Nevertheless, Randolph [55] stated that care needs to be taken when comparing cv0 from the laboratory with ch from the field since the link between the elasto-plastic compressional response of the soil and the field values is complicated. An attempt has been made by Mahmoodzadeh & Randolph [54] to overcome these issues by introducing an operative coefficient of consolidation. Furthermore, Figure 17C presents the rate dependency of ch for the deposit. High negative pore pressures recorded for high penetration rates lead to a slightly increased coefficients of consolidation hence an increase in rate of dissipation.
Nevertheless, care has to be taken when evaluating ch values for a deposit where partial drainage may occur. In the majority of cases, it is challenging to fit the measured results to the theory used which makes the achieved results less reliable. The irregular structure which is often present in natural silt deposits complicates the interpretation of consolidation parameters. The level of layering at the relevant depth of the dissipation test may influence the results significantly, leading to values that might not reproduce design values characterizing the soil deposit altogether [18]. A way of avoiding the analysis of the coefficient of consolidation is to directly use methods to deduce estimates of permeability (k) by applying an empirical correlation between t50 and k [51,56]. Furthermore, Robertson et al. [57] established a diagram which suggests values of k directly for certain values of t50 and normalized cone resistance Qtn.
DeJong et al. [50] implemented their theoretical solution into a field decision chart to check whether partial drainage is expected during a certain penetration rate with a given ch. The normalized penetration rate (V) can be defined by the following way [58,59]:
| $ \bar{V}_{h} = \frac{v \cdot d}{c_{h}} $ | (3) |
Lines for different normalized penetration rates are included as well as areas indicating drained, undrained and partially drained penetration behaviour. Figure 18 shows the data from the present test site (from Figure 17A) plotted into the ch versus penetration rate chart including the ch ranges proposed by DeJong & Randolph [15] for clay and silt respectively. Initially it can be seen that the majority of the data falls into the silt region, covering mostly partially drained penetration tests as concluded by studies carried out on the silt deposit by Bihs et al. [10].
To overcome problems in establishing reliable coefficient of consolidation values in partial consolidated soil deposits such as silts when evaluating the drainage situation of a soil deposit, Schnaid et al. [16] proposed a direct formulation of a new normalized penetration rate Vh which is independent of ch and just relies on penetration rate, diameter of the probe, IR and t50 in the following way:
| $ \bar{V}_{h} = \frac{v \cdot t_{50}}{d \cdot \sqrt[4]{I_{R}}} $ | (4) |
The suggested method has been applied to the existing data set in the upper silt layer (4 m to 8 m) presented in Bihs et al. [10] using the established t50 values from Figure 14A and a rigidity index of 200. Figure 19A & B show the results in terms of normalized cone resistance Qt ( = (qt-σv0)/σ'v0) and normalized excess pore pressure (Δu2/σ'v0) respectively as a function of log Vh. The data has been fitted by a hyperbolic fitting equation as suggested by House et al. [59] and Chung et al. [60]. The standard penetration rate (20 mm/s) has been plotted into Figure 19 corresponding to a Vh of 26. The results prove that the suggested method by Schnaid et al. [16] reveals promising and reliable results for soil deposits where partial consolidation during penetration is likely to occur. For Vh < 0.2–0.3 the penetration is likely to be drained whereas for penetration rates of Vh > 40–50 undrained conditions can be expected.
The consolidation study carried out at Halsen-Stjørdal showed that the square root correction method by Sully et al. [11] revealed the most consistent results for the determination of t50 values. In order to establish reliable ch values for the silt site, where partial drainage influences the results, the approach suggested by DeJong & Randolph has proven to provide reliable results. In order to verify the findings, data from the Norwegian Geo-Test Site (NGTS) for silts in Norway has been used and the methods proposed have been applied. The NGTS research site Halden is located about 120 km south of Oslo. The soil deposit consists of a low plastic, relatively uniform silt layer between 5 m and 15 m being characterized as a sandy, clayey silt. A detailed description about the ground conditions as well as laboratory and field tests carried out can be found in Blaker et al. [8]. Previous rate studies carried out on the silt indicate a tendency towards undrained conditions at V = 100 whereas drained conditions seem to occur at V < 1 [38].
A series of varied rate, high quality CPTU tests have been conducted supported by various dissipation tests at four different depth of interest in the silt layer (5 m, 6.5 m, 8.5 m and 10 m) [38,52]. In order to study the consolidation and drainage behaviour of the silt deposit and the rate dependency of the measured parameters, a few dissipation tests have been selected at depths of 6.5 m, 8.5 m and 10.5 m covering penetration rates varying between 1 mm/s up to 300 mm/s. Figure 20 shows the test data presented as measured pore pressure against registered time.
Overall, the slow dissipation tests show a close to monotonic dissipation behavior whereas the measured pore pressures increase with increased penetration rate, resulting in Type III dissipation curves for all tests except the slow ones. The dissipation tests at 6.5 m depth are quite varied with penetration rate, indicating a strong rate dependency on the consolidation behaviour of the deposit. For the deeper test locations, the dissipation curves converge more and get less dilative compared to the shallower ones. It is interesting to notice that no Type IV or V tests can be identified for the Halden test site, compared to the results presented for the Stjørdal-Halsen silt (Figure 11).
Values of t50 have been established according to the square root correction method by Sully et al. [11] for the Type III dissipation curves. Figure 21A shows a summary plot of the t50 values with depth comparing the approach by Teh & Houlsby [14] with the one by Sully et al. [11] revealing a significant overestimation of t50 by Teh & Houlsby [14] (see also Figure 22). Furthermore, a clear reduction of t50 with depth can be seen, indicating the presence of partial consolidation for tests located below 10 m depth as defined by DeJong and Randolph [15]. Figure 21B shows results of t50 with penetration rate, indicating a trend of slightly reduced t50 with increased penetration rate but not as clear as for the Halsen test site.
In order to estimate ch values for Halden silt, a rigidity index of 147 has been used for the tests carried out at 6.5 m depth, whereas a value of 126 has been applied to the deeper tests as reported by Carroll et al. [38]. For t50 < 100 s, partial consolidation has to be considered when calculating ch values for the silt deposit. Hence the approach by DeJong & Randolph [15] has been used for the relevant tests. Figure 23 represents a summary plot showing results of ch versus depth as well as ch versus penetration rate for the Halden silt deposit. Despite some scatter on the data a slightly increasing ch value with depth is recognized. Furthermore, no clear rate dependency is visible for the results.
Paniagua et al. [52] conducted an analysis of dissipation tests at 6.5 m depth from the same deposit, confirming the results described above. A clear trend of decreasing t50 values with increased penetration rate was also reported by Carroll et al. [38] who executed a study of dissipation tests between 5 m to 10 m. The study emphasized the success of applying the square root correction method by Sully et al. [11] for the Type III dissipation tests.
Although the rate dependency of the established consolidation parameters for the Halden silt deposit does not show the same clear tendency as for the Halsen-Stjørdal silt site, the methods suggested for silts could be applied successfully confirming the importance of considering the rate dependency of the geotechnical parameters in these deposits.
Existing dissipation models are developed for elastic-plastic material behaviour and homogeneous soil conditions which do not prevail in silty soil deposits. To understand and get an overview over the present partial consolidation conditions in a soil deposit are essential factors in understanding and interpreting dissipation tests in silts [18]. Furthermore, studies carried out showed that the inhomogeneous nature of silty material can cause an incorrect estimate of ch compared to a homogenous deposit as assumed by the theoretical interpretation methods [50,61]. In the absence of well-reviewed interpretation models and recommendations for silts together with only few existing field research silt sites, the present research project at NTNU has been conducted. Various field and laboratory investigations have been performed on a low plastic silt deposit at Halsen-Stjørdal in Norway to study the partial consolidation behaviour of the silt.
In order to correctly determine consolidation parameters from CPTU tests, an evaluation of IR is crucial, which needs to reflect the actual stress distribution around the penetrating cone [33]. The two different methods recommended by Krage et al. [32] alongside with the well-known approach of using laboratory data revealed consistent values between 200 and 250 for the present silt layer which are in accordance with values presented by other research sites on low plastic, light OC silts [7,8,9,39]. Furthermore, the varied CPTU tests indicated a strong rate dependency of the measured qt and u2 parameters [10].
The analysis of more than 44 dissipation tests revealed predominantly Type III and IV dissipation tests in the silt layer (4–14 m). Whereas in the more clayey zone below 14 m, Type II and V dissipation tests dominate the results. Furthermore, rate dependency of the dissipation test type could be observed. The very slow rate dissipation tests showed almost drained behaviour as already examined by Bihs et al. [10] whereas the faster rate dissipation tests showed a Type III and IV dissipation behaviour. Investigations carried out by Schneider et al. [3] and Chow et al. [48] support the findings from the present dissipation study.
The evaluation of representative t50 values for silt deposits is challenging due to the presence of unknown partial consolidation. For Type II and V dissipation curves, the well-known and accepted approach by Teh & Houlsby [14] has been used whereas for Type III and IV dissipation curves, the square root correction method proposed by Sully et al. [11] revealed the most consistent and reliable values for the Halsen-Stjørdal silt. The results showed a rather scattered t50 profile especially in the silt layer (4–14 m) with values varying between 30 s and more than 300 s. The lower, clayey silt layer indicated more consistent t50 results with a slightly decreasing trend with depth. Rate dependency studies showed that t50 decreases with increasing penetration rate. Similar trends have been reported by others studying the dissipation behaviour of silts [38,52]. Furthermore, the results showed partially drained layers predominantly in the silt layer with t50 values being less than 100 s which represents a limiting value according to DeJong & Randolph [15].
To evaluate the consolidation behaviour an attempt has been made to establish values of ch for the silt deposit. For tests with t50 values > 100 s, the approach by Teh & Houlsby [14] has been applied. Partial consolidation must be considered when evaluating ch values for tests with t50 values below 100 s. Therefore, the model proposed by DeJong & Randolph [15] has been successfully used in order to avoid an underestimation of ch for the layers where partial consolidation is present [50]. Opposite rate dependency trends have been reported for ch compared to t50. A slight increase in ch has been observed for increased penetration rates. Ratios of ch to cv0 have been deduced, showing values of up to 3.1 indicating higher consolidation values from the field tests as expected [4,55]. Great care should be taken when considering coefficient of consolidation values in silts due to the missing framework linking ch from the field to the elasto-plastic compressional soil response [54]. To overcome problems in establishing reliable coefficient of consolidation values in partial consolidated soil deposits, Schnaid et al. [16] proposed a direct formulation of a new normalized penetration rate Vh which is independent of ch. The application of Vh to the current test data showed borders for drained and undrained penetration behaviour which are in accordance with the ones established by Bihs et al. [10] using the standard approach for V. Finally, the experiences made in the Halsen-Stjørdal silt deposit have been used and the methods proposed have been applied to a dissipation data set available from a NGTS silt site in Norway. The results support the findings from the Halsen-Stjørdal site.
The present comprehensive study contributes to broadening the understanding of partially consolidated materials as silts and their consolidation behaviour. The recommendations and experiences made from two different silt sites are useful for practicing engineers in order to increase the awareness of the importance of considering partially drainage when establishing design consolidation values.
The authors would like to acknowledge the Norwegian Geo-Test Site project (No. 245650/F50) funded by the Research Council of Norway (RCN) for sharing the data on the Halden silt site.
All authors declare no conflict of interest.
| [1] |
Banta D (2003) The development of health technology assessment. Health Policy 63: 121-132. doi: 10.1016/S0168-8510(02)00059-3
|
| [2] | Chatman C (2010) How cloud computing is changing the face of health care information technology. J Health Care Compliance 12(3): 37-70. |
| [3] | Clamp S, Keen J (2007) Electronic health records: Is the evidence base any use? J Med Informatics Int Med 32: 5-10. |
| [4] | Coleman R (2009) Can histology and pathology be taught without microscopes? The advantages and disadvantages of virtual histology. J Acta Histochemica 111(1): 1-4. |
| [5] |
Detmer D (2000) Information technology for quality health care: a summary of United Kingdom and United States experiences. Quality in Health Care 9: 181-189. doi: 10.1136/qhc.9.3.181
|
| [6] | Detmer D (2001) Transforming health care in the internet era. World Hospital Health Ser 37: 2. |
| [7] | Dixon R, Stahl J (2008) Virtual visits in a general medicine practice: A pilot study. Telemed e-Health 14(6): 525-530. |
| [8] | Furness PN (1997) The use of digital images in pathology. J Patholo183: 15-24. |
| [9] | Haughton J (2011) Year of the underdog: Cloud-based EHRs. Healthcare Management Technolo 32(1): 9 |
| [10] | Hayrinen K, Saranto K, Nykanen P (2008) Definition, structure, content, use and impacts of electronic health records: A review of the research literature. Inter J Med Inform 77: 291-304. |
| [11] | Horbinski C, Wiley CA (2009) Comparison of telepathology systems in neuropathological intraoperative consultations. J Neuropatholo 19(2): 317-322. |
| [12] | Hufnagl P, Schluns K (2008) Virtual microscopy and routine diagnostics. A discussion paper. J Patholo 29(2): 250-254. |
| [13] | Kabachinski J (2011) What's the forecast for cloud computing in healthcare? Biomedical Instrumental Technolo 45(2): 146-150. |
| [14] | Kayser K, Hoshang SA, Metze K, et al. (2008) Texture- and object-related automated information analysis in histological still images of various organs. J Analytical Quantitative Cytolo Histo 30(6): 323-335. |
| [15] | Kobb R, Lane R, Stallings D (2008) E-learning and telehealth: Measuring your success. Telemedicine and e-Health 14(6): 576-579. |
| [16] | Lane K (2006) Telemedicine news. Telemedicine and e-Health 12(5): 507-511. |
| [17] | Lareng L (2002) Telemedicine in Europe. European J Int Med 13: 1-13. |
| [18] | Leong FJ, Graham AK, Schwarzmann P (2000) Clinical trial of telepathology as an alternative modality in breast histopathology quality assurance. J Telemed E-Health 6: 373-377. |
| [19] | Mencarelli R, Marcolongo A, Gasparetto A (2008) Organizational model for a telepathology system. J Diagnostic Patholo 15(3): S7. |
| [20] | Merell R, Doarn C (2008) Is it time for a telemedicine breakthrough? Telemed e-Health 14(6): 505-506. |
| [21] |
Moore D, Green J, Jay S, et al. (1994). Creating a new paradigm for CME: Seizing opportunities within the health care revolution. J Continuing Education in the Health Professionals 14: 4-31. doi: 10.1002/chp.4750140102
|
| [22] | Moura A, Del Giglio A (2000) Education via internet. Revist da Associacao Medica Brasileira, 46(1): 47-51. |
| [23] | Nannings B, Abu-Hanna A (2006) Decision support telemedicine systems: A conceptual model and reusable templates. Telemed e-Health 12(6): 644-654. |
| [24] | Pak H (2007) Telethinking. Telemed e-Health 13(5): 483-486. |
| [25] | Raab SS, Zaleski MS, Thomas PA (1996) Telecytology: diagnostic accuracy in cervical-vaginal smears. American J Clin Patholo 105: 599-603. |
| [26] | Riva G (2000) From telehealth to e-health: Internet and distributed virtual reality in health care. J CyberPsychology Behavior 3(6): 989-998. |
| [27] | Riva G (2002) The emergence of e-health: using virtual reality and the internet for providing advanced healthcare services. Int J Healthcare Technolo Management 4 (1/2): 15-40. |
| [28] | Rocha R, Vassallo J, Soares F, et al. (2009) Digital slides: present status of a tool for consultation, teaching, and quality control in pathology. J Patholo Res Prac 205(11): 735-741. |
| [29] | Rosenthal A, Mork P, Li MH, et al. (2010) Cloud computing: a new business paradigm for biomedical information sharing. J Biomed Inform 43(2): 342-353. |
| [30] | Sloot P, Tirado-Ramos A, Altintas I, et al. (2006) From molecule to man: Decision support in individualized E-Health. Computer 39(11): 40-46. |
| [31] | Van Ginneken AM (2002) The computerized patient record: Balancing effort and benefit. Int J Med Inform 65: 97-119. |
| [32] | Weinstein RS, Graham AR, Richte LC, et al. (2009) Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future. J Human Patholo 40(8): 1057-1069. |
| [33] | Bautista PA, Yagi Y (2010) Improving the visualization and detection of tissue folds in whole slide images through color enhancement. J Pathol Inform 1:25. |
| [34] | Bloom K (2009) The virtual consultative network. Presented at Pathol. Vis. Conf., San Diego. |
| [35] | Bruch LA, De Young BR, Kreiter CD, et al. (2009) Competency assessment of residents in surgical pathology using virtual microscopy. Hum Pathol 40: 1122–1128. |
| [36] | Chargari C, Comperat E, Magne N, et al. (2011) Prostate needle biopsy examination by means of virtual microscopy. Pathol Res Pract 207: 366-369. |
| [37] | Costello SS, Johnston DJ, Dervan PA, et al. (2003) Development and evaluation of the virtual pathology slide: a new tool in telepathology. J Med Int Res 5: e11. |
| [38] | Daniel C, Rojo MG, Klossa J, et al. (2011) Standardizing the use of whole slide images in digital pathology. Comput Med Imaging Graph 35: 496-505. |
| [39] | Dee FR (2009) Virtual microscopy in pathology education. Hum Pathol 40: 1112-1121. |
| [40] | Della Mea V, Bortolotti N, Beltrami CA (2009) eSlide suite: an open source software system for whole slide imaging. J Clin Pathol 62: 749-751. |
| [41] | DICOM Stand. Comm. Work. Group 26 Pathol. Specimen Module and Revised Pathology SOP Classes, suppl. 122., 2008. Available from ftp://medical.nema.org/medical/dicom/final/sup122_ft2.pdf |
| [42] | DICOM Stand. Comm. Work. Group 26 Pathol. Whole Slide Microscopic Image IOD and SOP Classes, suppl. 145, 2008. Available from ftp://medical.nema.org/medical/dicom/supps/sup145_ft.pdf. |
| [43] | Difranco MD, O'Hurley G, Kay EW, et al. (2011) Ensemble based system for whole-slide prostate cancer probability mapping using color texture features. Comput Med Imaging Graph 35: 629-645. |
| [44] | Evans AJ, Chetty R, Clarke BA, et al. (2009) Primary frozen section diagnosis by robotic microscopy and virtual slide telepathology: the University Health Network experience. Hum Pathol 40: 1070-1081. |
| [45] | Evans AJ (2011) Re: Barriers and facilitators to adoption of soft copy interpretation from the user perspective: lessons learned from filmless radiology for slideless pathology. J Pathol Inform 2: 8. |
| [46] | Evans AJ, Sinard JH, Fatheree LA, et al. (2011) Validating whole slide imaging for diagnostic purposes in pathology: recommendations of the College of American Pathologists (CAP) Pathology and Laboratory Quality Center. Anal. Cell Pathol 34: 169-203. |
| [47] | Evered A, Dudding N (2010) Accuracy and perceptions of virtual microscopy compared with glass slide microscopy in cervical cytology. Cytopatholo 22: 82-87. |
| [48] | Fallon MA, Wilbur DC, Prasad M (2010) Ovarian frozen section diagnosis: Use of whole-slide imaging shows excellent correlation between virtual slide and original interpretations in a large series of cases. Arch Pathol Lab Med 134: 1020-1023. |
| [49] | Fine JL, Grzybicki DM, Silowash R, et al. (2008) Evaluation of whole slide image immunohistochemistry interpretation in challenging prostate needle biopsies. Hum Pathol 39: 564–572. |
| [50] | Fonyad L, Gerely L, Cserneky M, et al. (2010) Shifting gears higher—digital slides in graduate education—4 years experience at Semmelweis University. Diagn Pathol 5: 73. |
| [51] | Fung KM, Hassell LA, Talbert ML, et al. (2012) Whole slide images and digital media in pathology education, testing, and practice: the Oklahoma experience. Anal Cell Pathol 35: 37-40. |
| [52] | Gabril MY, Yousef GM (2010) Informatics for practicing anatomical pathologists: marking a new era in pathology practice. Mod Pathol 23: 349-358. |
| [53] | Gilbertson JR, Ho J, Anthony L, et al. (2006) Primary histologic diagnosis using automated whole slide imaging: a validation study. BMC Clin Pathol 6: 4. |
| [54] | Graham AR, Bhattacharyya AK, Scott KM, et al. (2009) Virtual slide telepathology for an academic teaching hospital surgical pathology quality assurance program. Hum Pathol 40: 1129-1136. |
| [55] | Hassell LA, Fung KM, Chaser B (2011) Digital slides and ACGME resident competencies in anatomic pathology: an altered paradigm for acquisition and assessment. J Pathol Inform 2: 27. |
| [56] | Hede K (2008) Breast cancer testing scandal shines spotlight on black box of clinical laboratory testing. J Natl Cancer Inst 100: 836-844. |
| [57] | Hedvat CV (2008) Digital microscopy: past, present, and future. Arch Pathol Lab Med 134: 1666-1670. |
| [58] | Ho J, Parwani AV, Jukic DM, et al. (2006) Use of whole slide imaging in surgical pathology quality assurance: design and pilot validation studies. Hum Pathol 37: 322-331. |
| [59] | Ho J (2009) Validating digital slides for clinical use: When is image quality good enough? Presented at Pathol Vis Conf, San Diego. |
| [60] | Huisman A, Looijen A, van den Brink SM, et al. (2010) Creation of a fully digital pathology slide archive by high-volume tissue slide scanning. Hum Pathol 41: 751-757. |
| [61] | Jukic DM, Drogowski LM, Martina J, et al. (2011) Clinical examination and validation of primary diagnosis in anatomic pathology using whole slide digital images. Arch Pathol Lab Med 135: 372-378. |
| [62] | Isaacs M, Lennerz JK, Yates S, et al. (2011) Implementation of whole slide imaging in surgical pathology: a value added approach. J Pathol Inform 2: 39. |
| [63] | Kalinski T, Zwonitzer R, Sel S, et al. (2008) Virtual3Dmicroscopy usingmultiplane whole slide images in diagnostic pathology. Am J Clin Pathol 130: 259-264. |
| [64] | Krupinski EA, Tillack AA, Richter L, et al. (2006) Eye-movement study and human performance using telepathology virtual slides: implications for medical education and differences with experience. Hum Pathol 37: 1543-1556. |
| [65] | Krupinski EA (2009) Virtual slide telepathology workstation of the future: lessons learned from teleradiology. Hum Pathol 40: 1100-1111. |
| [66] | Li L, Dangott BJ, Parwani AV (2010) Development and use of a genitourinary pathology digital teaching set for trainee education. J Pathol Inform 1: 2. |
| [67] | Lopez AM, Graham AR, Barker GP, et al. (2009) Virtual slide telepathology enables an innovative telehealth rapid breast care clinic. Hum Pathol 40: 1082-1091. |
| [68] | Manion E, Cohen MB, Weydert J (2008) Mandatory second opinion in surgical pathology referral material: clinical consequences of major disagreements. Am J Surg Pathol 32: 732-737. |
| [69] | Massone C, Brunasso AM, Campbell TM, et al. (2008) State of the art of teledermatopathology. Am J Dermatopathol 30: 446-450. |
| [70] | Marchevsky AM, Khurana R, Thomas P, et al. (2006) The use of virtual microscopy for proficiency testing in gynecologic cytopathology: a feasibility study using ScanScope. Arch Pathol Lab Med 130: 349-355. |
| [71] |
McClintock DS, Lee RE, Gilbertson JR (2012) Using computerized workflow simulations to assess the feasibility of whole slide imaging full adoption in a high-volume histology laboratory. Anal Cell Pathol 35: 57-64. doi: 10.1155/2012/726526
|
| [72] | Merk M, Knuechel R, Perez-Bouza A (2010) Web-based virtual microscopy at the RWTH Aachen University: didactic concept, methods and analysis of acceptance by the students. Ann Anat 192: 383-387. |
| [73] | Mooney E, Hood AF, Lampros J, et al. (2011) Comparative diagnostic accuracy in virtual dermatopathology. Skin Res Technol 17: 251-255. |
| [74] | Nielsen PS, Lindebjerg J, Rasmussen J, et al. (2010). Virtual microscopy: an evaluation of its validity and diagnostic performance in routine histologic diagnosis of skin tumors. Hum Pathol 41: 1770-1776. |
| [75] | Pantanowitz L (2010) Digital images and the future of digital pathology. J Pathol Inform 1: 15. |
| [76] | Patterson ES, Rayo M, Gill C, et al. (2011) Barriers and facilitators to adoption of soft copy interpretation from the user perspective: lessons learned from filmless radiology for slideless pathology. J Pathol Inform 2: 9. |
| [77] | Paulsen FP, Eichhorn M, Brauer L (2010) Virtual microscopy: the future of teaching histology in the medical curriculum? Ann Anat 192: 378-382. |
| [78] | Raab SS, Nakhleh RE, Ruby SG (2005) Patient safety in anatomic pathology: measuring discrepancy frequencies and causes. Arch Pathol Lab Med 129: 459-466. |
| [79] | Raab SS, Grzybicki DM, Mahood LK, et al. (2008) Effectiveness of random and focused review in detecting surgical pathology error. Am J Clin Pathol 130: 905-912. |
| [80] | Ramey JP, Fung K, Hassell LA (2011) Validation of pathologist use of whole slide images for remote frozen section evaluation. Mod Pathol 24: 436 (Abstr.). |
| [81] | Ramey JP, Fung K, Hassell LA (2011) Use of mobile high resolution device for remote frozen section evaluation of whole slide images. Mod Pathol 24: 341 (Abstr.). |
| [82] | Reyes C, Ikpatt F, Nadiji M, et al. (2011) Is virtual microscopy ready for the prime time? A comparison with conventional microscopy. Mod Pathol 24: 454 (Abstr.). |
| [83] | Rodriguez-Urrego PA, Cronin AM, Al-Ahmadie HA, et al. (2011) Interobserver and intraobserver reproducibility in digital and routine microscopic assessment of prostate needle biopsies. Hum Pathol 42: 68-74. |
| [84] |
Sawai T, Uzuki M, Kamataki A, et al. (2010) The state of telepathology in Japan. J Pathol Inform 1: 13. doi: 10.4103/2153-3539.68327
|
| [85] | Schrader T, Niepage S, Leuthold T, et al. (2006) The diagnostic path, a useful visualisation tool in virtual microscopy. Diagn Pathol 1: 40. |
| [86] | Siegel EL, Kolonder RM (1999) Filmless Radiology. New York: Springer. |
| [87] | Spinosa JC (2008) Minute by minute, digital a boon to tumor board. Coll Am Pathol Today Arch.: Oct. |
| [88] | Stewart J, Miyazaki K, Bevans-Wilkins K, et al. (2007) Virtual microscopy for cytology proficiency testing: Are we there yet? Cancer 111: 203-209. |
| [89] | Stratman C (2009) Digital pathology in the clinical histology lab: a time and motion study. Presented at Pathol Vis Conf, San Diego. |
| [90] | Thrall M, Pantanowitz L, Khalbuss W (2011) Telecytology: clinical applications, current challenges, and future benefits. J Pathol Inform 2: 51. |
| [91] | Thorstenson S (2009) From the conventional microscope to the digital slide scanner in routine diagnostic histopathology. Presented at Pathol. Vis. Conf., San Diego. |
| [92] | Tsuchihashi Y, Takamatsu T, Hashimoto Y, et al. (2008) Use of virtual slide system for quick frozen intra-operative telepathology diagnosis in Kyoto, Japan. Diagn Pathol 3(Suppl. 1): 6. |
| [93] | van den Tweel JG, Bosman FT (2011) The use of virtual slides in the EUROPALS examination. Diagn Pathol 6(Suppl. 1): 23. |
| [94] | Velez N, Jukic D, Ho J (2008) Evaluation of two whole-slide imaging applications in dermatopathology. Hum Pathol 39: 1341-1349. |
| [95] | Weinstein RS, Graham AR, Richter LC, et al. (2009) Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future. Hum Pathol 40: 1057-1069. |
| [96] | Wilbur DC, Madi K, Colvin RB, et al. (2009) Whole-slide imaging digital pathology as a platform for teleconsultation: a pilot study using paired subspecialist correlations. Arch Pathol Lab Med 133: 1949-1953. |
| [97] | Williams S, Henricks WH, Becich MJ, et al. (2010) Telepathology for patient care: What am I getting myself into? Adv Anat Pathol 17: 130-149. |
| [98] |
Woolgar JA, Ferlito A, Devaney KO, et al. (2011) How trustworthy is a diagnosis in head and neck surgical pathology? A consideration of diagnostic discrepancies (errors). Eur Arch Otorhinolaryngol 268: 643-651. doi: 10.1007/s00405-011-1526-x
|
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| Reference | soil type | OCR (-) | IP (%) | IR (–) |
| Suzuki et al. [39] | clayey silt | * | 21 | 150 |
| Holmsgaard et al. [7] | sandy silt | – | 1.5–4.1 | 275 |
| Garcia Martinez et al. [40,41] | clayey silt | * | 0–8 | 130 |
| Krage et al. [9] | sandy silt | 10–15 | 0–5 | 240 |
| Tonnie et al. [42] | clayey, sandy silt | 1–2 | 5–20 | – |
| Carroll & Paniagua [38] & Blaker et al. [8] | clayey silt | 1–1.3 | 6.6–9.3 | 126–147 |
| present study | clayey, sandy silt | 1–2 | 0 | 200–250 |
| Note: * lightly overconsolidated. | ||||
DownLoad:
CSV
| Reference | soil type | OCR (-) | IP (%) | IR (–) |
| Suzuki et al. [39] | clayey silt | * | 21 | 150 |
| Holmsgaard et al. [7] | sandy silt | – | 1.5–4.1 | 275 |
| Garcia Martinez et al. [40,41] | clayey silt | * | 0–8 | 130 |
| Krage et al. [9] | sandy silt | 10–15 | 0–5 | 240 |
| Tonnie et al. [42] | clayey, sandy silt | 1–2 | 5–20 | – |
| Carroll & Paniagua [38] & Blaker et al. [8] | clayey silt | 1–1.3 | 6.6–9.3 | 126–147 |
| present study | clayey, sandy silt | 1–2 | 0 | 200–250 |
| Note: * lightly overconsolidated. | ||||
