scholarly journals Problems with collapsible soils: Particle types and inter-particle bonding

2019 ◽  
Vol 11 (1) ◽  
pp. 829-836
Author(s):  
Ian Smalley ◽  
Samson Ng’ambi

Abstract A collapsible soil is composed essentially of a packing of mineral particles and a set of interparticle bonds holding the system together. Failure requires the bond system to fail and the soil structure to collapse. A natural hazard is presented. The soil structure may collapse inwards (consolidate), as in loess failure, or it may collapse outwards (disperse, disintegrate), as in the failure of quick-clays, some collapsing sands, some silty estuarine deposits, and in wind erosion of silty soils by saltating sand grains. Generalising about bonding systems allows two types of interparticle bond to be recognized: long range bonds and short range bonds. Long range bonds are found in clay mineral systems and allow the occurrence of plasticity. They are represented by c in the standard Coulomb equation. Short range bonds are found in inactive particle systems. These are soil systems where the constituent particles do not have a significant electrical charge. A slight deformation of a short-range bonded system causes much loss of strength. It is short range bonds which tend to dominate in collapsing soil systems, although in the complex case of loess the bond failure is initially mediated by long range bonds at the interparticle contact regions. A collapse failure involves a large scale remaking of the soil structure, and thus total failure of the bonding system. Generalising again- it can be claimed that five types of particle make up engineering soils: A active clay mineral particles (the smectites), B inactive clay mineral particles (e.g. kaolinite, illite), C very small inactive primary mineral particles (close to the comminution limit in size- mostly in the quick-clays), D silt (usually quartz silt), and E sand (usually quartz sand). The nature of type D particles contributes to the collapse of loess soils, the most widespread of the collapsing soil phenomena. The nature of type C particles controls the behaviour of quick-clays. C and D systems are essentially dominated by short-range bonds.

Nature ◽  
2021 ◽  
Author(s):  
Siyu Chen ◽  
Linda Lee ◽  
Tasmin Naila ◽  
Susan Fishbain ◽  
Annie Wang ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Roman Sherrod ◽  
Eric C. O’Quinn ◽  
Igor M. Gussev ◽  
Cale Overstreet ◽  
Joerg Neuefeind ◽  
...  

AbstractThe structural response of Dy2TiO5 oxide under swift heavy ion irradiation (2.2 GeV Au ions) was studied over a range of structural length scales utilizing neutron total scattering experiments. Refinement of diffraction data confirms that the long-range orthorhombic structure is susceptible to ion beam-induced amorphization with limited crystalline fraction remaining after irradiation to 8 × 1012 ions/cm2. In contrast, the local atomic arrangement, examined through pair distribution function analysis, shows only subtle changes after irradiation and is still described best by the original orthorhombic structural model. A comparison to Dy2Ti2O7 pyrochlore oxide under the same irradiation conditions reveals a different behavior: while the dysprosium titanate pyrochlore is more radiation resistant over the long-range with smaller degree of amorphization as compared to Dy2TiO5, the former involves more local atomic rearrangements, best described by a pyrochlore-to-weberite-type transformation. These results highlight the importance of short-range and medium-range order analysis for a comprehensive description of radiation behavior.


Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1384
Author(s):  
Yin Dai ◽  
Yifan Gao ◽  
Fayu Liu

Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentation, and lesion detection. CNN has great advantages in extracting local features of images. However, due to the locality of convolution operation, it cannot deal with long-range relationships well. Recently, transformers have been applied to computer vision and achieved remarkable success in large-scale datasets. Compared with natural images, multi-modal medical images have explicit and important long-range dependencies, and effective multi-modal fusion strategies can greatly improve the performance of deep models. This prompts us to study transformer-based structures and apply them to multi-modal medical images. Existing transformer-based network architectures require large-scale datasets to achieve better performance. However, medical imaging datasets are relatively small, which makes it difficult to apply pure transformers to medical image analysis. Therefore, we propose TransMed for multi-modal medical image classification. TransMed combines the advantages of CNN and transformer to efficiently extract low-level features of images and establish long-range dependencies between modalities. We evaluated our model on two datasets, parotid gland tumors classification and knee injury classification. Combining our contributions, we achieve an improvement of 10.1% and 1.9% in average accuracy, respectively, outperforming other state-of-the-art CNN-based models. The results of the proposed method are promising and have tremendous potential to be applied to a large number of medical image analysis tasks. To our best knowledge, this is the first work to apply transformers to multi-modal medical image classification.


1977 ◽  
Vol 38 (C7) ◽  
pp. C7-202-C7-206 ◽  
Author(s):  
R. MORET ◽  
M. HUBER ◽  
R. COMÈS

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
R. S. Markiewicz ◽  
J. Lorenzana ◽  
G. Seibold ◽  
A. Bansil
Keyword(s):  

2021 ◽  
pp. 115738
Author(s):  
KyoHoon Jin ◽  
JeongA Wi ◽  
EunJu Lee ◽  
ShinJin Kang ◽  
SooKyun Kim ◽  
...  

2002 ◽  
Vol 14 (03) ◽  
pp. 273-302 ◽  
Author(s):  
HERIBERT ZENK

We give a short summary on how to combine and extend results of Combes and Hislop [2] (short range Anderson model with additional displacements), Kirsch, Stollmann and Stolz [13] and [14] (long range Anderson model without displacements) to get localization in an energy interval above the infimum of the almost sure spectrum for a continuous multidimensional Anderson model including long range potentials and displacements.


2014 ◽  
Vol 45 (1) ◽  
pp. 33-47 ◽  
Author(s):  
Xue Lin ◽  
Chengguo Wang ◽  
Meijie Yu ◽  
Zhitao Lin ◽  
Yuzhen Liu

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