Dynamic strength of distill water and lake water ice at high strain rates

Modeling of heterogeneous materials at high strain rates with machine learning algorithms trained by finite element simulations

Journal of Micromechanics and Molecular Physics ◽

10.1142/s2424913021500016 ◽

2021 ◽

pp. 2150001

Author(s):

Xu Long ◽

Minghui Mao ◽

Changheng Lu ◽

Ruiwen Li ◽

Fengrui Jia

Keyword(s):

Machine Learning ◽

Mechanical Properties ◽

High Strain ◽

Dynamic Strength ◽

Dynamic Mechanical Properties ◽

Strain Rates ◽

High Strain Rates ◽

Dynamic Mechanical ◽

Concrete Materials ◽

Meso Scale

Great progress has been made in the dynamic mechanical properties of concrete which is usually assumed to be homogenous. In fact, concrete is a typical heterogeneous material, and the meso-scale structure with aggregates has a significant effect on its macroscopic mechanical properties of concrete. In this paper, concrete is regarded as a two-phase composite material, that is, a combination of aggregate inclusion and mortar matrix. To create the finite element (FE) models, the Monte Carlo method is used to place the aggregates as random inclusions into the mortar matrix of the cylindrical specimens. To validate the numerical simulations of such an inclusion-matrix model at high strain rates, the comparisons with experimental results using the split Hopkinson pressure bar are made and good agreement is achieved in terms of dynamic increasing factor. By performing more extensive FE predictions, the influences of aggregate size and content on the macroscopic dynamic properties (i.e., peak dynamic strength) of concrete materials subjected to high strain rates are further investigated based on the back-propagation (BP) artificial neural network method. It is found that the particle size of aggregate has little effect on the dynamic mechanical properties of concrete but the peak dynamic strength of concrete increases obviously with the content increase of aggregate. After detailed comparisons with FE simulations, machine learning predictions based on the BP algorithm show good applicability for predicting dynamic mechanical strength of concrete with different aggregate sizes and contents. Instead of FE analysis with complicated meso-scale aggregate pre-processing, time-consuming simulation and laborious post-processing, machine learning predictions reproduce the stress–strain curves of concrete materials under high strain rates and thus the constitutive behavior can be efficiently predicted.

Download Full-text

A study of the compressive mechanical properties of defect-free, porous and sintered water-ice at low and high strain rates

Icarus ◽

10.1016/j.icarus.2020.113940 ◽

2020 ◽

Vol 351 ◽

pp. 113940

Author(s):

Ryan S. Potter ◽

Joseph M. Cammack ◽

Christopher H. Braithwaite ◽

Philip D. Church ◽

Stephen M. Walley

Keyword(s):

Mechanical Properties ◽

High Strain ◽

Strain Rates ◽

High Strain Rates ◽

Water Ice

Download Full-text

Research on the Mechanical Behavior of Styropor Concrete at High Strain Rates

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.168-170.2086 ◽

2010 ◽

Vol 168-170 ◽

pp. 2086-2091

Author(s):

Ze Bin Hu ◽

Jin Yu Xu ◽

Jie Zhu ◽

Qiang He ◽

Gang Li ◽

...

Keyword(s):

Elastic Modulus ◽

Strain Rate ◽

Mechanical Behavior ◽

High Strain ◽

Dynamic Strength ◽

Strain Rates ◽

Average Strain ◽

High Strain Rates ◽

Average Strain Rate ◽

The Impact

Mechanical behavior of Styropor concrete(EPSC) added with various volumetric fractions of EPS subjected to high strain rates were studied by using the Large-Diameter-SHPB. The infection of volumetric fractions and average strain rate to dynamic properties of EPSC were investigated. The experimental results show that under high strain rate condition, the dynamic strength, dynamic strength increase factor(DIF) and limit strain of EPSC are strain rate dependent, the strain rate effect can be expressed by linear approximations, and the relationship between elastic modulus and average strain rate is independent.With the addition of volumetric fractions of EPS, the impact compressive strength and elastic modulus of EPSC declines, and the toughness of EPSC is reinforced.

Download Full-text

Effects of strain rate and surface cracks on the mechanical behaviour of Balmoral Red granite

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2016.0179 ◽

2017 ◽

Vol 375 (2085) ◽

pp. 20160179 ◽

Cited By ~ 3

Author(s):

Ahmad Mardoukhi ◽

Yousof Mardoukhi ◽

Mikko Hokka ◽

Veli-Tapani Kuokkala

Keyword(s):

Strain Rate ◽

High Strain ◽

Experimental Testing ◽

Dynamic Strength ◽

Fractal Dimensions ◽

Rate Sensitivity ◽

Tensile Behaviour ◽

Strain Rates ◽

Surface Cracks ◽

High Strain Rates

This work presents a systematic study on the effects of strain rate and surface cracks on the mechanical properties and behaviour of Balmoral Red granite. The tensile behaviour of the rock was studied at low and high strain rates using Brazilian disc samples. Heat shocks were used to produce samples with different amounts of surface cracks. The surface crack patterns were analysed using optical microscopy, and the complexity of the patterns was quantified by calculating the fractal dimensions of the patterns. The strength of the rock clearly drops as a function of increasing fractal dimensions in the studied strain rate range. However, the dynamic strength of the rock drops significantly faster than the quasi-static strength, and, because of this, also the strain rate sensitivity of the rock decreases with increasing fractal dimensions. This can be explained by the fracture behaviour and fragmentation during the dynamic loading, which is more strongly affected by the heat shock than the fragmentation at low strain rates. This article is part of the themed issue ‘Experimental testing and modelling of brittle materials at high strain rates’.

Download Full-text