ASCE GSP 301-2018 FUNDAMENTALS.pdf

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1、GEOTECHNICAL SPECIAL PUBLICATION NO. 301 PANAM UNSATURATED SOILS 2017 FUNDAMENTALS SELECTED PAPERS FROM SESSIONS OF THE SECOND PAN-AMERICAN CONFERENCE ON UNSATURATED SOILS November 1215, 2017 Dallas, Texas SPONSORED BY International Society of Soil Mechanics and Geotechnical Engineering The Geo-Inst

2、itute of the American Society of Civil Engineers EDITED BY Laureano R. Hoyos, Ph.D., P.E. John S. McCartney, Ph.D., P.E. Sandra L. Houston, Ph.D., D.GE William J. Likos, Ph.D. Published by the American Society of Civil Engineers Published by American Society of Civil Engineers 1801 Alexander Bell Dr

3、ive Reston, Virginia, 20191-4382 www.asce.org/publications | ascelibrary.org Any statements expressed in these materials are those of the individual authors and do not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein. No reference made in this publ

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8、 by locating a title in ASCEs Civil Engineering Database (http:/cedb.asce.org) or ASCE Library (http:/ascelibrary.org) and using the “Permissions” link. Errata: Errata, if any, can be found at https:/doi.org/10.1061/9780784481684 Copyright 2018 by the American Society of Civil Engineers. All Rights

9、Reserved. ISBN 978-0-7844-8168-4 (PDF) Manufactured in the United States of America. Preface The Second Pan-American Conference on Unsaturated Soils (PanAm-UNSAT 2017) was held in Dallas, Texas, November 12-15, 2017, featuring the latest research advances and engineeringpractice innovations in the a

10、rea of Unsaturated Geotechnics, with a focus on characterization, modeling, design, construction, field performance and sustainability. PanAm-UNSAT 2017 follows a now well-established series of regional and international conferences on Unsaturated Soils, bringing together researchers, practitioners,

11、 students and policy makers from around the world, particularly the Americas. The conference built upon the success of PanAm-UNSAT 2013 (First Pan-American Conference on Unsaturated Soils, Cartagena, Colombia), as well as that of previous conferences on unsaturated soils hosted in the United States,

12、 including UNSAT 2006 (Fourth International Conference on Unsaturated Soils, Carefree, Arizona) and EXPANSIVE92 (Seventh International Conference on Expansive Soils, Dallas, Texas, 1992). Proceedings of PanAm-UNSAT 2017 have been documented in four Geotechnical Special Publications (GSP) of ASCE inc

13、luding Volume 1: Plenary Session Papers; Volume 2: Fundamentals; Volume 3: Applications; and Volume 4: Swell-Shrink and Tropical Soils. Current Volume 2 (Fundamentals) consists of seven sections: Section I, Pore Fluid Retention, includes 8 papers dealing with the definition of the soil water retenti

14、on curve, role of different pore fluids, and interlinkages between water retention, volume change, and effective stress. These papers also discuss the role of new manufactured materials such as 3D printed porous media and challenging natural materials like loess and soils with different fabrics. Sec

15、tion II, Hydraulic Properties, includes 9 papers dealing with a focus on prediction and measurement of key hydraulic properties of unsaturated soils such as the soil water retention curve, hydraulic conductivity, and air permeability. Papers discuss challenging materials such as mine tailings, the r

16、ole of additions such as Xanthan gum to soils, as well as the behavior of silt/sand mixtures. The impact of variability and atmospheric boundary conditions are also characterized. Section III, Numerical Modeling: Flow and Deformation, includes 10 papers dealing with the importance of consideration o

17、f soil volume change in problems of unsaturated flow. Discussions in these papers include impacts of volume change on unsaturated soil hydraulic conductivity functions and other flow/deformation coupling aspects in numerical modeling of unsaturated flow. 3DQ$P8QVDWXUDWHG6RLOV*63 LLL$6 Farshid Vahedi

18、fard, Ph.D., P.E.2; and Xavier A. Rivera-Hernandez, P.E.3 1Senior Research Geotechnical Engineer, Engineer Research and Development Center, U.S. Army Corps of Engineers, 3909 Halls Ferry Rd., Vicksburg, MS 39180. E-mail: ghada.s.ellithyusace.army.mil 2Associate Professor, Dept. of Civil and Environm

19、ental Engineering, Mississippi State Univ., Mississippi State, MS 39762. E-mail: farshidcee.msstate.edu 3Research Civil Engineer, Engineer Research and Development Center, U.S. Army Corps of Engineers, 3909 Halls Ferry Rd., Vicksburg, MS 39180. E-mail: Xavier.A.Rivera-Hernandezusace.army.mil Abstrac

20、t Proper determination of the soil-water characteristic curve (SWCC) plays an important role in the accuracy of any modeling attempt involving variably saturated soils such as transient unsaturated seepage analysis. While the SWCC can be directly measured, several predictive models have been develop

21、ed over the past two decades and are employed in practice because of their simplicity, and the lower cost, and time needed to obtain their input parameters. The predictive models are commonly developed through multiple regression analysis over a large number of measured SWCCs to establish an empiric

22、al correlation between the SWCC model parameters and soil index properties such as grain size distribution and Atterberg limits. This study evaluates the performance of seven predictive models to estimate the van Genuchten SWCC model parameters a, n, and r that represent the air entry value (AEV), s

23、lope of the curve, and the residual water content, respectively. For this purpose, the transient release and imbibition method (TRIM) device is used in the laboratory to obtain the van Genuchten SWCC of silty sand samples collected from a setback levee. The van Genuchten model parameters measured in

24、 the laboratory are compared against those estimated using the predictive models. The comparison shows that using predictive models can lead to over two orders of magnitude difference in a, a ratio of r to s between 0.06 and 0.21, and an n value between 1.25 and 2.85 for the tested soil. The aforeme

25、ntioned differences can lead to significant variations in transient seepage analysis results, a factor which needs to be carefully taken into consideration when using predictive models in practice. INTRODUCTION A transient condition for a given seepage scenario indicates that input and output quanti

26、ties, such as soil hydraulic loading, gradient, and flow rate, vary with time. Transient seepage is commonly associated with unsaturated flow conditions where water flow occurs through soils with negative pore water pressures that are partially filled with water. However, the soil can remain saturat

27、ed for some distance above the phreatic surface under negative pore water pressures. Flow above 3DQ$P8QVDWXUDWHG6RLOV*63 $6 a small increment of 10 kPa and a large increment of 290 kPa. The matric suction is applied using the axis translation technique, which involves applying a positive air pressur

28、e while keeping the pore water pressure at zero. After equilibrium is reached at the large increment, the wetting cycle is tested through a sudden decrease in the matric suction. The transient outflow and inflow response is unique for each soil sample that is controlled by the diffusivity in the soi

29、l, the high air-entry stone, and the configuration of the system. The high-resolution transient response with time obtained during the drying and wetting cycles can then be used as an objective function for an inverse numerical model that solves Richards equation, where the soil parameters that defi

30、ne the SWCC can be identified. The soil tested in this study is classified as SM according to the unified soil classification system (USCS), with a specific gravity (Gs) of 2.75. The soil sample retrieved from a levee site had about 30% fine gravel, 55% sand and 15% non-plastic fines. To prepare the

31、 sample for TRIM testing, the soil was sieved on sieve #4 removing the fine gravel portion of the sample. The sample was compacted in the TRIM cell to dry density of 17 kN/m3 (108 pcf) and moisture content of about 10%, which is about 92% of optimum of standard Proctor compaction. The porosity of th

32、e sample was calculated as 0.36, and the average hydraulic conductivity was measured at about 2.0E-05 cm/sec. RESULTS AND DISCUSSION The modified grain size distribution curve for the sieved material (about 52% sand and 48% fines) was used as an input in an MS Excel spreadsheet (Ellithy, 2017) to es

33、timate the SWCC for the material. A fitting algorithm (Seki, 2007) was then applied to the generated SWCCs to estimate van Genuchtens parameters, a, n, as well as r. For the predictive models that fit the SWCC to Fredlund and Xing (1994) equation where r equals to zero at matric suction of 106 kPa,

34、the value of volumetric water content at a matric suction of 10.0E5 kPa was used instead to estimate r. For the Sleep (2011) model, van Gebuchtens a value was taken simply as the matric suction at the models average and 90% confidence limits at 100% saturation, r was estimated at 10% of the porosity

35、 based on the models assumptions, and n parameter is not applied to this model. Table 1 summarizes van Genuchtens parameters obtained from the predictive models as well as from the TRIM drying and wetting curves. Figures 3a and b show the SWCC as generated by the seven predictive models, and Figure

36、4 shows these curves dimmed with the TRIM drying and wetting curves plotted on top for comparison. It should be noted for the models that do not explicitly distinguish between the drying and the wetting curves, the SWCC represents the drying curve. As shown in Table 1 and Figure 3, van Genuchtens a

37、value for the drying curve varies between 0.95 to 358.74 kPa, and between 0.18 and 24.37 kPa for the wetting curve. The a value obtained from the TRIM tests was 12.80 and 5.00 kPa for the drying and wetting curves, respectively. The value of a is dependent on the AEV, and the water entry value (WEV)

38、 of the drying and wetting SWCC, respectively. The n value determines the rate at which the water is released from or adsorbed into the soil, while Benson et al. (2014) recommend a minimum value of 2, the other models predict values that range from 1.3 to 2.85. Typically, the n value for the wetting

39、 curve is higher than the drying curve indicating a slower rate of water adsorption compared to water release. The residual water content, r, varied between 0.023 and 0.077 from the predictive curves, with the TRIM test value being 0.078. 3DQ$P8QVDWXUDWHG6RLOV*63 $6 Sleep 2011) noted that while it i

40、s not conclusive that one predictive method is significantly more accurate than the others, the SWCC can probably be estimated about as accurately as it can be measured. However, using tests like filter paper or TRIM which is relatively quick and does not measure the full SWCC, can provide a more ac

41、curate determination of the SWCC main features. CONCLUSIONS Predictive models have been developed over the past two decades and are commonly used in practice to predict the SWCC based on basic soil properties. These models are preferred for their simplicity, and the lower cost and time needed to obt

42、ain their input parameters. In this paper, seven predictive models were used to estimate the SWCC of a silty sand material. The van Genuchten SWCC model parameters; a, n and r, which correspond to the SWCC three main features of the air entry value (AEV), slope of the curve, and the residual water c

43、ontent, respectively, were evaluated for the generated SWCCs and compared to the parameters obtained from Transient Release and Imbibition Method (TRIM) test on the same material. The comparison shows that using the predictive models can lead to over two orders of magnitude difference in the a param

44、eter, ratio of r to s between 0.06 and 0.21, and an n value between 1.25 and 2.85 for the tested soil. These differences can lead to significant variations in transient Figure 4. SWCC generated by predictive models compared to TRIM data VolumetricWaterContent, (cm3 /cm3 )3DQ$P8QVDWXUDWHG6RLOV*63 $6

45、Chang H. Kiang2; and Eduardo P. Dos Santos3 1Laboratrio de Estudo de Bacias, Departamento de Geologia, Universidade Estadual Paulista - UNESP, Rio Claro, SP, Brazil. E-mail: alfarorc.unesp.br 2Laboratrio de Estudo de Bacias, Departamento de Geologia, Universidade Estadual Paulista - UNESP, Rio Claro

46、, SP, Brazil. E-mail: changrc.unesp.br 3Laboratrio de Estudo de Bacias, Departamento de Geologia, Universidade Estadual Paulista - UNESP, Rio Claro, SP, Brazil. E-mail: Abstract This paper was designed to verify if effective saturation distribution for air-LNAPL systems obtained indirectly as sugge

47、sted by the American Petroleum Institute (2007) are adequate for soils of lateritic nature found in various territories of Brazil. The effective saturation of air-water systems were determined using hanging column tests for typical samples of the state of So Paulo (Brazil). These results were then c

48、ompared to the effective saturations obtained in similar tests for air-LNAPL systems. In both cases, the capillary pressure curves were typical of soils with multimodal pore-size distribution. Moreover, indirect models for effective saturation curves of air-LNAPL were coherent, as long as a tri-moda

49、l model was used. Further studies for the prediction of the specific volumes of contaminants in tropical soils are recommended due to the differential retention characteristics. INTRODUCTION Accidental spills of Light, Non-Aqueous Liquid Phase (LNALP) products are one of the most common causes of subsur