Methodology for Neural Network-Based Material Card Calibration Using LS-DYNA MAT_187_SAMP-1 Considering Failure with GISSMO

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.

PEMODELAN REGRESI RIDGE ROBUST S,M, MM-ESTIMATOR DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi Kemiskinan di Jawa Tengah Tahun 2020)

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linier regression parameters. If there is a violation of assumptions such as multicolliniearity especially coupled with the outliers, then the regression with OLS is no longer used. One method can be used to solved the multicollinearity and outliers problem is Ridge Robust Regression. Ridge Robust Regression is a modification of ridge regression method used to solve the multicolliniearity and using some estimators of robust regression used to solve the outlier, the estimator including : Maximum likelihood estimator (M-estimator), Scale estimator (S-estimator), and Method of moment estimator (MM-estimator). The case study can be used with this method is data with multicollinearity and outlier, the case study in this research is poverty in Central Java 2020 influenced by life expentancy, unemployment number, GRDP rate, dependency ratio, human development index, the precentage of population over 15 years of age with the highest education in primary school, mean years school. The result of estimation using OLS show that there is a multicollinearity and presence an outliers. Applied the ridge robust regression to case study prove that ridge robust regression can improve parameter estimation. The best ridge robust regression model is Ridge Robust Regression S-Estimator. The influence value of predictor variabels to poverty is 73,08% and the MSE value is 0,00791.

Macroscopic rheology of non-Brownian suspensions at high shear rates: the influence of solid volume fraction and non-Newtonian behaviour of the liquid phase

Modelling the macroscopic rheology of non-Brownian suspensions is complicated by the non-linear behaviour that originates from the interaction between solid particles and the liquid phase. In this contribution, a model is presented that describes suspension rheology as a function of solid volume fraction and shear rate dependency of both the liquid phase, as well as the suspension as a whole. It is experimentally validated using rotational rheometry ($$\varphi$$ φ ≤ 0.40) and capillary rheometry (0.55 ≤ $$\varphi$$ φ ≤ 0.60) at shear rates > 50 s−1. A modified Krieger-Dougherty relation was used to describe the influence of solid volume fraction on the consistency coefficient, $$K$$ K , and was fitted to suspensions with a shear thinning liquid phase, i.e. having a flow index, $$n$$ n , of 0.50. With the calculated fit parameters, it was possible to predict the consistency coefficients of suspensions with a large variation in the shear rate dependency of the liquid phase ($$n$$ n = 0.20–1.00). With increasing solid volume fraction, the flow indices of the suspensions were found to decrease for Newtonian and mildly shear thinning liquid phases ($$n$$ n ≥0.50), whereas they were found to increase for strongly shear thinning liquid phases ($$n$$ n ≤0.27). It is hypothesized that this is related to interparticle friction and the relative contribution of friction forces to the viscosity of the suspension. The proposed model is a step towards the prediction of the flow curves of concentrated suspensions with non-Newtonian liquid phases at high shear rates.

A thermo-viscoplasticity model for metals over wide temperature ranges- application to case hardening steel

In this contribution, a model for the thermomechanically coupled behaviour of case hardening steel is introduced with application to 16MnCr5 (1.7131). The model is based on a decomposition of the free energy into a thermo-elastic and a plastic part. Associated viscoplasticity, in terms of a temperature-depenent Perzyna-type power law, in combination with an isotropic von Mises yield function takes respect for strain-rate dependency of the yield stress. The model covers additional temperature-related effects, like temperature-dependent elastic moduli, coefficient of thermal expansion, heat capacity, heat conductivity, yield stress and cold work hardening. The formulation fulfils the second law of thermodynamics in the form of the Clausius–Duhem inequality by exploiting the Coleman–Noll procedure. The introduced model parameters are fitted against experimental data. An implementation into a fully coupled finite element model is provided and representative numerical examples are presented showing aspects of the localisation and regularisation behaviour of the proposed model.

Effect of loading rate on tensile and fracture behavior of AA2050-T84 alloy at high temperature

AA2050-T84 alloy is commonly used in the fabrication of modern commercial aircraft wing parts. Load and temperature variation during aircraft take-off, flight, and landing at different environmental conditions is substantial. Mechanical properties variation of AA2050-T84 alloy at sub-zero and room temperatures are significant and well documented in the literature. In the present work, at a high temperature of 200°C, the effect of load rate variation on tensile and fracture properties of AA2050-T84 alloy are experimentally and numerically studied. The load rates represented in strain rates were applied at 0.01, 0.1, and 1s−1. Experimental tensile tests exhibited the positive strain rate dependency on the yield and ultimate strength of the alloy. 2D numerical elastic-plastic fracture analysis was carried out using Abaqus 6.14. Similar to tensile results, the fracture parameters dependency on strain rates was witnessed. Overall, higher strain rate causes the increased susceptibility of fracture failure with the increase in yield stress of the material.

Pore-water pressure development in a frozen saline clay under isotropic loading and undrained shearing

A systematical testing program on frozen Onsøy clay under isotropic loading and undrained shearing at different temperatures (− 3 ~ − 10 °C), strain rates (0.2~5%/h) and initial Terzaghi effective stress (20~400 kPa) was conducted with the focus on pore pressure development. It is meant to increase the understanding and facilitate the development of an ‘effective stress’-based model for multi-physical analysis for frozen soils. This study adopted the pore pressure measurement method suggested by Arenson and Springman (Can Geotech J 42 (2):412–430, 2005. https://doi.org/10.1139/t04-111) and developed a new testing procedure for frozen soils, including a ‘slow’ freezing method for sample preparation and post-freezing consolidation for securing hydraulic pressure equilibrium. The B-value of frozen soils is less than 1 and significantly dependent on temperature and loading history. The dilative tendency or pore pressure development in an undrained shearing condition is found to be dependent on both unfrozen water content and mean stress, which is consistent with unfrozen soils. Besides, the experimental results reported in the literature regarding uniaxial tests show that the shear strength does not share the same temperature- and salinity-dependency for different frozen soil types. The rate dependency of frozen soils is characterized between rate dependency of pure ice and that of the unfrozen soil and is therefore highly determined by the content of ice and the viscous behavior of ice (through temperature dependency). This paper also explains the pore pressure response in freezing and thawing is dependent on volumetric evolution of soil skeleton.

Loading-Rate Dependency of Young’s Modulus for Class I and Class II Rocks

Understanding the time-dependent behavior of rocks is important for ensuring the long-term stability of underground structures. Aspects of such a time-dependent behavior include the loading-rate dependency of Young’s modulus, strength, creep, and relaxation. In particular, the loading-rate dependency of Young’s modulus of rocks has not been fully clarified. In this study, four different types of rocks were tested, and the results were used to analyze the loading-rate dependency of Young’s modulus and explain the underlying mechanism. For all four rocks, Young’s modulus increased linearly with a tenfold increase in the loading rate. The rocks showed the same loading-rate dependency of Young’s modulus. A variable-compliance constitutive equation was proposed for the loading-rate dependency of Young’s modulus, and the calculated results agreed well with measured values. Irrecoverable and recoverable strains were separated by loading-unloading-reloading tests at preset stress levels. The constitutive equations showed that the rate of increase in Young’s modulus increased with the irrecoverable strain and decreased with increasing stress. The increase in the irrecoverable strain was delayed at high loading rates, which was concluded to be the main reason for the increase in Young’s modulus with an increasing loading rate.

Characterizing the Material Properties of the Kidney and Liver in Unconfined Compression and Probing Protocols with Special Reference to Varying Strain Rate

The liver and kidneys are the most commonly injured organs due to traumatic impact forces applied to the abdomen and pose a challenge to physicians due to a hard-to-diagnose risk of internal bleeding. A better understanding of the mechanism of injury will improve diagnosis, treatment, forensics, and other fields. Finite element modelling is a tool that can aid in this understanding, but accurate material properties are required including the strain rate dependency and the feasibility of using animal tissue properties instead of human. The elastic modulus in a probing protocol and the elastic modulus, failure stress, and failure strain in a compression protocol were found for both liver and kidney tissue from human and porcine specimens at varying strain rates. Increases in the elastic modulus were seen for both the human kidney and liver, but only for the porcine kidney, when comparing the unconfined compression and probing protocols. A strain rate dependency was found for both the liver and kidney properties and was observed to have a larger saturation effect at higher rates for the failure stress than for the elastic modulus. Overall, the material properties of intact liver and kidney were characterized, and the strain rate dependency was numerically modelled. The study findings suggest that some kidney and liver material properties vary from human to porcine tissue. Therefore, it is not always appropriate to use material properties of porcine tissue in computational or physical models of the human liver and kidney.

Experimental investigations of the human oesophagus: anisotropic properties of the muscular layer in large deformation

Technological advancements in the field of robotics have led to endoscopic biopsy devices able to extract diseased tissue from between the layers of the gastrointestinal tract. Despite this, the layer-dependent properties of these tissues have yet to be mechanically characterised using human tissue. In this study, the ex vivo mechanical properties of the passive muscularis propia layer of the human oesophagus were extensively investigated. For this, a series of uniaxial tensile tests were conducted. The results displayed hyperelastic behaviour, while the differences between loading the tissue in both the longitudinal and circumferential directions showcased its anisotropy. The anisotropy of the muscular layer was present at different strain rates, with the longitudinal direction being consistently stiffer than the circumferential one. The circumferential direction was found to have little strain-rate dependency, while the longitudinal direction results suggest pronounced strain-rate-dependent behaviour. The repeated trials showed larger variation in terms of stress for a given strain in the longitudinal direction compared to the circumferential direction. The possible causes of variation between trials are discussed, and the experimental findings are linked to the histological analysis which was carried out via various staining methods. Finally, the direction-dependent experimental data was simulated using an anisotropic, hyperelastic model.