tension compression asymmetry
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Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 643
Author(s):  
Paul Meißner ◽  
Jens Winter ◽  
Thomas Vietor

A neural network (NN)-based method is presented in this paper which allows the identification of parameters for material cards used in Finite Element simulations. Contrary to the conventionally used computationally intensive material parameter identification (MPI) by numerical optimization with internal or commercial software, a machine learning (ML)-based method is time saving when used repeatedly. Within this article, a self-developed ML-based Python framework is presented, which offers advantages, especially in the development of structural components in early development phases. In this procedure, different machine learning methods are used and adapted to the specific MPI problem considered herein. Using the developed NN-based and the common optimization-based method with LS-OPT, the material parameters of the LS-DYNA material card MAT_187_SAMP-1 and the failure model GISSMO were exemplarily calibrated for a virtually generated test dataset. Parameters for the description of elasticity, plasticity, tension–compression asymmetry, variable plastic Poisson’s ratio (VPPR), strain rate dependency and failure were taken into account. The focus of this paper is on performing a comparative study of the two different MPI methods with varying settings (algorithms, hyperparameters, etc.). Furthermore, the applicability of the NN-based procedure for the specific usage of both material cards was investigated. The studies reveal the general applicability for the calibration of a complex material card by the example of the used MAT_187_SAMP-1.


Géotechnique ◽  
2021 ◽  
pp. 1-34
Author(s):  
Zhong-Sen Li ◽  
Matthieu Blanc ◽  
Luc Thorel

Two model piles with outer diameter D = 50 mm are loaded laterally at 100×g in a large-beam geotechnical centrifuge. The normal strains on both the tensile and compressive sides are measured using fibre Bragg gratings. An incremental method is introduced to define the pivot point. The testing and analytical program enables the effect of the embedding depth and load eccentricity to be quantified. The key findings are as follows. 1) The piles generate asymmetric tensile and compressive strains during bending, and the tension-compression asymmetry becomes more pronounced at the pile toe and for shorter piles. 2) The piles transition from flexure to rotation as the embedding depth is decreased from 9D to 3D, where the uniqueness of the ground-level rotation and deflection (θg–yg) relationship disappears. 3) The reaction and deflection (P–y) relationship flattens with increasing embedding depth but seems independent of the load eccentricity.


Author(s):  
Qiang Li ◽  
Jian Wang ◽  
Haiyan Wang ◽  
Xinghang Zhang

Abstract Al alloys often suffer from low mechanical strength and lack high-temperature microstructural and mechanical robustness. A series of binary and ternary nanocrystalline (NC) Al transition metal alloys with supersaturated solid solution and columnar nanograins have been recently developed by using magnetron sputtering, manifesting a new realm of mechanical properties and thermal stability. Distinct solutes cause evident differences in the phase transformations and efficiencies for grain refinement and crystalline-to-amorphous transition. Certain sputtered Al-TM alloys have shown room-temperature mechanical strengths greater than 2 GPa and outstanding thermal stability up to 400 °C. In addition, the NC Al alloys show mechanical anisotropy and tension–compression asymmetry, revealed by micromechanical tests. Through the process encapsulating various compositionally distinct systems, we attempt to illuminate the solute effects on grain refinement and properties and more importantly, tentatively unravel the design criteria for high-strength and yet thermally stable NC Al alloys. Graphic Abstract


2021 ◽  
pp. 117392
Author(s):  
J. Suryawanshi ◽  
Gaurav Singh ◽  
S. Msolli ◽  
Mark H. Jhon ◽  
U. Ramamurty

Author(s):  
Jiaxiang Li ◽  
Qinghuan Huo ◽  
Chunyu Wang ◽  
Yuxiu Zhang ◽  
Zhirou Zhang ◽  
...  

Materials ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5415
Author(s):  
Alireza Ostadrahimi ◽  
Fathollah Taheri-Behrooz ◽  
Eunsoo Choi

This paper aims to analytically derive bending equations, as well as semi-analytically predict the deflection of prismatic SMA beams in the martensite phase. To this end, we are required to employ a simplified one-dimensional parametric model considering asymmetric response in tension and compression for martensitic beams. The model takes into account the different material parameters in martensite twined and detwinned phases as well as elastic modulus depending on the progress of the detwinning process. In addition, the model considers the diverse slope of loading and unloading in martensite detwinned phases favored by tension and compression. To acquire general bending equations, we first solve the pure bending problem of a prismatic SMA beam. Three different phases are assumed in the unloading procedure and the effect of neutral fiber distance from the centerline is also considered during this stage. Then according to the pure bending solution and employing semi-analytical methods, general bending equations of an SMA beam are derived. Polynomial approximation functions are utilized to obtain the beam deflection–length relationship. To validate the attained analytical expressions, several three- and four-point bending tests were conducted for rectangular and circular SMA beams. Experimental data confirm the reasonable accuracy of the analytical results. This work may be envisaged to go deep enough in investigating the response of SMA beams under an arbitrary transverse loading and stress distribution during loading and unloading, as well as findings may be applicable to a good prediction of bending behavior.


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