A bibliography of geomorphometry with a topical key to the literature and an introduction to the numerical characterization of topographic form

1993 ◽  
Author(s):  
R.J. Pike
Keyword(s):  
Numerical Characterization

Experimental and Numerical Characterization of Lower Huron Shale as a Heterogeneous Material

2021 ◽  
Author(s):  
Ming Fan ◽  
Yanhui Han ◽  
Xinyu Tan ◽  
Liang Fan ◽  
Ellen S. Gilliland ◽  
...  
Keyword(s):  
Heterogeneous Material ◽  
Numerical Characterization

Experimental and numerical characterization of a polymeric Hopkinson bar by DTMA

2017 ◽  
Vol 103 ◽  
pp. 50-63 ◽  
Author(s):  
Marco Sasso ◽  
Michele Gabrio Antonelli ◽  
Edoardo Mancini ◽  
Mario Radoni ◽  
Dario Amodio
Keyword(s):  
Hopkinson Bar ◽  
Numerical Characterization

scholarly journals Numerical Characterization of Cohesive and Non-Cohesive ‘Sediments’ under Different Consolidation States Using 3D DEM Triaxial Experiments

Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1252
Author(s):  
Hadar Elyashiv ◽  
Revital Bookman ◽  
Lennart Siemann ◽  
Uri ten Brink ◽  
Katrin Huhn
Keyword(s):  
Mechanical Response ◽  
Burial Depth ◽  
Cohesive Sediments ◽  
Third Order ◽  
First Order ◽  
Numerical Characterization ◽  
Response To Stress ◽  
Bond Strengths ◽  
Individual Bond

The Discrete Element Method has been widely used to simulate geo-materials due to time and scale limitations met in the field and laboratories. While cohesionless geo-materials were the focus of many previous studies, the deformation of cohesive geo-materials in 3D remained poorly characterized. Here, we aimed to generate a range of numerical ‘sediments’, assess their mechanical response to stress and compare their response with laboratory tests, focusing on differences between the micro- and macro-material properties. We simulated two endmembers—clay (cohesive) and sand (cohesionless). The materials were tested in a 3D triaxial numerical setup, under different simulated burial stresses and consolidation states. Variations in particle contact or individual bond strengths generate first order influence on the stress–strain response, i.e., a different deformation style of the numerical sand or clay. Increased burial depth generates a second order influence, elevating peak shear strength. Loose and dense consolidation states generate a third order influence of the endmember level. The results replicate a range of sediment compositions, empirical behaviors and conditions. We propose a procedure to characterize sediments numerically. The numerical ‘sediments’ can be applied to simulate processes in sediments exhibiting variations in strength due to post-seismic consolidation, bioturbation or variations in sedimentation rates.

scholarly journals Modelling Degradation and Replication Kinetics of the Zika Virus In Vitro Infection

Viruses ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 547
Author(s):  
Veronika Bernhauerová ◽  
Veronica V. Rezelj ◽  
Marco Vignuzzi
Keyword(s):  
Mathematical Model ◽  
Viral Infection ◽  
Host Cell ◽  
Decay Time ◽  
Zika Virus ◽  
Infectious Virus ◽  
Numerical Characterization ◽  
The Mathematical Model

Mathematical models of in vitro viral kinetics help us understand and quantify the main determinants underlying the virus–host cell interactions. We aimed to provide a numerical characterization of the Zika virus (ZIKV) in vitro infection kinetics, an arthropod-borne emerging virus that has gained public recognition due to its association with microcephaly in newborns. The mathematical model of in vitro viral infection typically assumes that degradation of extracellular infectious virus proceeds in an exponential manner, that is, each viral particle has the same probability of losing infectivity at any given time. We incubated ZIKV stock in the cell culture media and sampled with high frequency for quantification over the course of 96 h. The data showed a delay in the virus degradation in the first 24 h followed by a decline, which could not be captured by the model with exponentially distributed decay time of infectious virus. Thus, we proposed a model, in which inactivation of infectious ZIKV is gamma distributed and fit the model to the temporal measurements of infectious virus remaining in the media. The model was able to reproduce the data well and yielded the decay time of infectious ZIKV to be 40 h. We studied the in vitro ZIKV infection kinetics by conducting cell infection at two distinct multiplicity of infection and measuring viral loads over time. We fit the mathematical model of in vitro viral infection with gamma distributed degradation time of infectious virus to the viral growth data and identified the timespans and rates involved within the ZIKV-host cell interplay. Our mathematical analysis combined with the data provides a well-described example of non-exponential viral decay dynamics and presents numerical characterization of in vitro infection with ZIKV.

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