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1

Iskander, Magued. Behavior of Pipe Piles in Sand. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-13108-0.

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2

United States. Federal Highway Administration. and Atkinson-Noland & Associates., eds. Centrifugal testing of model piles and pile groups. McLean, Va: U.S. Dept. of Transportion, Federal Highway Administration, 1985.

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3

Munch-Andersen, Jørgen. Silo model tests with sand. Hørsholm: Danish Building Research Institute, 1992.

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4

Miedema, Sape A. The Delft sand, clay & rock cutting model. Amsterdam: IOS Press, 2014.

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5

Larson, Magnus. SBEACH: Numerical model for simulating storm-induced beach change. Vicksburg, Miss: U.S. Army Engineer Waterways Experiment Station, 1989.

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6

Hannigan, Kevin. The sand cone model: Achieving multiple objectives in the Irish chemical and pharmaceutical industry. Dublin: University College Dublin, 1996.

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7

Groen, Klaas P. Pesticide leaching in polders: Field and model studies on cracked clays and loamy sand. Lelystad: Ministerie van Verkeer en Waterstaat, Directoraat-General Rijkswaterstaat, Directie Ijsselmeergebied, 1997.

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8

M, Rubin David. Measurements of sand thicknesses in Grand Canyon, Arizona, and a conceptual model for characterizing changes in sand-bar volume through time and space. [Menlo Park, CA]: U.S. Geological Survey, 1994.

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9

Bekbasarov, Isabay. Study of the process of driving piles and dies on models. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1074097.

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The monograph presents the results of experimental and theoretical studies conducted using models of driven piles and tape dies. The influence of the cross-section size, length, shape of the trunk and the lower end of the piles on their submergability, energy intensity of driving and load-bearing capacity was evaluated. The design and technological features of new types of piles are considered. A method for determining the load-bearing capacity of a pile model based on the results of dynamic tests has been developed. Similarity conditions and formulas are presented that provide modeling of the pile driving process in the laboratory. The influence of the shape of the tape dies on their submersibility, energy consumption of the driving and the bearing capacity of the foundations arranged in the vyshtampovannyh pits was evaluated. The method of determining the load-bearing capacity of a belt Foundation model based on the results of pit vyshtampovyvaniya is described. Recommendations on the choice of optimal parameters of piles and foundations, arranged in vystupovani pits. Recommended for researchers, specialists of design and construction organizations, doctoral students, postgraduates, undergraduates and students of construction and water management specialties.
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10

Peck, Lindamae. Heat transfer and frost-thaw penetration in soil surrounding an inclusion of sand: Numerical model results relevant to electromagnetic sensor system performance. [Hanover, N.H]: US Army Corps of Engineers, Cold Regions Research & Engineering Laboratory, 1995.

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11

Peck, Lindamae. Heat transfer and frost-thaw penetration in soil surrounding an inclusion of sand: Numerical model results relevant to electromagnetic sensor system performance. [Hanover, N.H]: US Army Corps of Engineers, Cold Regions Research & Engineering Laboratory, 1995.

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12

Peck, Lindamae. Heat transfer and frost-thaw penetration in soil surrounding an inclusion of sand: Numerical model results relevant to electromagnetic sensor system performance. [Hanover, N.H]: US Army Corps of Engineers, Cold Regions Research & Engineering Laboratory, 1995.

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13

Voronin, Lois M. Evaluation of saltwater intrusion and travel time in the Atlantic City 800-foot sand, Cape May County, New Jersey, 1992, by use of a coupled-model approach and flow-path analysis. West Trenton, N.J: U.S. Dept. of the Interior, U.S. Geological Survey, 1996.

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14

Robinson, R. B. Piles in sand and in sand overlying clay. 1989.

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15

Jardine, Richard, Fiona Chow, Zhongxuan Yang, and Wangbo Guo. Comprehensive Database of Tests on Axially Loaded Piles Driven in Sand. Elsevier Science & Technology Books, 2015.

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16

Comprehensive Database of Tests on Axially Loaded Piles Driven in Sand. Elsevier Science & Technology Books, 2015.

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17

Siraty, A. Behaviour of model foundations on sand. 1992.

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18

A Comprehensive Database of Tests on Axially Loaded Piles Driven in Sand. Elsevier, 2016. http://dx.doi.org/10.1016/c2015-0-01032-2.

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19

Ungaro, Ronald. Development of design parameters for H-piles in sand using static analysis. 1988.

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20

Behavior of Pipe Piles in Sand Springer Series in Geomechanics and Geoengineering. Springer, 2011.

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21

Iskander, Magued. Behavior of Pipe Piles in Sand: Plugging & Pore-Water Pressure Generation During Installation and Loading. Springer, 2011.

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22

Iskander, Magued. Behavior of Pipe Piles in Sand: Plugging & Pore-Water Pressure Generation During Installation and Loading. Springer, 2014.

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23

Iskander, Magued. Behavior of Pipe Piles in Sand: Plugging and Pore-Water Pressure Generation During Installation and Loading. Springer, 2011.

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24

Lake, G. C. The development of shaft friction and end bearing resistance for dynamically-driven model piles. 1986.

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25

Extended Load/Unload/Reload Hyperbolic Model for Interfaces: Parameter Values and Model Performance for the Contact Between Concrete and Coarse Sand. Storming Media, 2000.

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26

Zachar, Peter, and Richard J. McNally. Vagueness, the sorites paradox, and posttraumatic stress disorder. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198722373.003.0009.

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This chapter explores the vagueness inherent in the conceptual structure of posttraumatic stress disorder (PTSD). Although psychopathologists have developed precise diagnostic criteria for PTSD, concepts such as traumatic, severe, and impaired generate borderline cases. As in the sorites paradox, where difficult to distinguish but successively smaller piles of sand may be called heaps, in PTSD similar but successively milder traumatic events may produce PTSD symptoms. The vagueness that bedevils PTSD is of two sorts: the degree vagueness manifested in gradual transitions between subtraumatic and traumatic stressors; and vagueness between normal and abnormal reactions. Also discussed here is an alternative causal systems approach in which the symptoms of PTSD are causally related parts of PTSD. Such mereological structures produce combinatorial vagueness in which there are borderline cases between PTSD and other psychiatric syndromes.
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27

Yust, Jason. Structural Networks and the Experience of Musical Time. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.003.0005.

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The network model of temporal structure allows for many generalized concepts of musical time that can be applied across different modalities (rhythmic, tonal, and formal). This chapter defines network depths, distances, paths, centers, skew, and bias, and partially classifies network types such as piles, tortoises, and starfish. A splitting operation on networks is defined and applied to the problem of relating networks in different modalities and finding true disjunctions.
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28

Bokulich, Alisa. Searching for Non-Causal Explanations in a Sea of Causes. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198777946.003.0008.

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In the spirit of explanatory pluralism, this chapter argues that causal and non-causal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. First the chapter reviews the author’s model-based account of scientific explanation, which can accommodate causal and non-causal explanations alike. Then it distills from the literature an important core conception of non-causal explanation. This non-causal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining the formation of regularly-spaced sand ripples. The chapter concludes that even when it comes to everyday “medium-sized dry goods” such as sand ripples, where there is a complete causal story to be told, one can find examples of non-causal scientific explanations.
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