Experience from using recently implemented enhancements for Material 36 in LS-DYNA 971 performing a virtual tensile test. Authors: Correspondence:

Similar documents
SPRING-BACK PREDICTION FOR STAMPINGS FROM THE THIN STAINLESS SHEETS

Anisotropic plasticity, anisotropic failure and their application to the simulation of aluminium extrusions under crash loads

Material parameter identification for the numerical simulation of deep-drawing drawing of aluminium alloys

SIMPLIFIED MODELING OF THIN-WALLED TUBES WITH OCTAGONAL CROSS SECTION AXIAL CRUSHING. Authors and Correspondance: Abstract:

DEVELOPMENT OF A CONTINUUM PLASTICITY MODEL FOR THE COMMERCIAL FINITE ELEMENT CODE ABAQUS

Neural Network Prediction of Nonlinear Elastic Unloading for High Strength Steel

THE HYDRAULIC BULGE TEST AND ITS IMPORTANCE FOR THE VEGTER YIELD CRITERION

Plane Strain Test for Metal Sheet Characterization

WORKSHOP Introduction to material characterization

On the nonlinear anelastic behaviour of AHSS

INCREASING RUPTURE PREDICTABILITY FOR ALUMINUM

Numerical simulation of sheet metal forming processes using a new yield criterion

ScienceDirect. Bauschinger effect during unloading of cold-rolled copper alloy sheet and its influence on springback deformation after U-bending

Significance of the local sheet curvature in the prediction of sheet metal forming limits by necking instabilities and cracks

Characterizations of Aluminum Alloy Sheet Materials Numisheet 2005

IDENTIFICATION OF SHEET METAL PLASTIC ANISOTROPY, AND OPTIMIZATION OF INITIAL BLANK SHAPE IN DEEP DRAWING

*MAT_PAPER and *MAT_COHESIVE_PAPER: Two New Models for Paperboard Materials

Lecture #10: Anisotropic plasticity Crashworthiness Basics of shell elements

Outline. Tension test of stainless steel type 301. Forming including the TRIP-effect

Formability assessment of a cup drawing under complex nonlinear strain paths

Research Article Process of Identifying Stress Fields from Strain Fields in the Specimen with a Hole

On Springback Prediction In Stamping Of AHSS BIW Components Utilizing Advanced Material Models

EFFECT OF ANISOTROPIC YIELD CRITERION ON THE SPRINGBACK IN PLANE STRAIN PURE BENDING

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

HERCULES-2 Project. Deliverable: D4.4. TMF model for new cylinder head. <Final> 28 February March 2018

Stress Analysis Report

UNIT I SIMPLE STRESSES AND STRAINS

EQUIVALENT FRACTURE ENERGY CONCEPT FOR DYNAMIC RESPONSE ANALYSIS OF PROTOTYPE RC GIRDERS

STRESS UPDATE ALGORITHM FOR NON-ASSOCIATED FLOW METAL PLASTICITY

Recent Developments in Damage and Failure Modeling with LS-DYNA

Nonlinear Analysis of the Enclosure of the Pulley

THE S-S CURVE APPROXIMATION FOR GFRP TENSILE SPECIMEN BY USING INVERSE METHOD AND OPTIMIZATION

USER S MANUAL 1D Seismic Site Response Analysis Example University of California: San Diego August 30, 2017

ASPECTS CONCERNING TO THE MECHANICAL PROPERTIES OF THE GLASS / FLAX / EPOXY COMPOSITE MATERIAL

IMPACT PROPERTY AND POST IMPACT VIBRATION BETWEEN TWO IDENTICAL SPHERES

NORMAL STRESS. The simplest form of stress is normal stress/direct stress, which is the stress perpendicular to the surface on which it acts.

SIMULATIONS OF HYPERVELOCITY IMPACTS WITH SMOOTHED PARTICLE HYDRODYNAMICS

Particle Blast Method (PBM) for the Simulation of Blast Loading

CHAPTER 3 THE EFFECTS OF FORCES ON MATERIALS

Direct (and Shear) Stress

**********************************************************************

Card Variable MID RO E PR ECC QH0 FT FC. Type A8 F F F F F F F. Default none none none 0.2 AUTO 0.3 none none

Probabilistic Assessment of a Stiffened Carbon Fibre Composite Panel Operating in its Postbuckled Region Authors: Correspondence:

MATERIAL MODELS FOR THE

MEG 795 COURSE PROJECT

NUMERICAL SIMULATION OF DAMAGE IN THERMOPLASTIC COMPOSITE MATERIALS

X has a higher value of the Young modulus. Y has a lower maximum tensile stress than X

COMPRESSION TESTING BY MEANS OF CHARPY PENDULUM

6.37 Determine the modulus of resilience for each of the following alloys:

Fundamentals of Durability. Unrestricted Siemens AG 2013 All rights reserved. Siemens PLM Software

Authors: Correspondence: ABSTRACT:

CHAPTER 7 FINITE ELEMENT ANALYSIS OF DEEP GROOVE BALL BEARING

Parameter identification of damage parameters of LS-DYNA GURSON material model from a tensile test. Lectures. Johannes Will

Thick Shell Element Form 5 in LS-DYNA

Modeling non-isothermal thermoforming of fabricreinforced thermoplastic composites

Chapter Two: Mechanical Properties of materials

A Constitutive Model for DYNEEMA UD composites

Name :. Roll No. :... Invigilator s Signature :.. CS/B.TECH (CE-NEW)/SEM-3/CE-301/ SOLID MECHANICS

Simulation of the anisotropic material properties in polymers obtained in thermal forming process

Optimization of blank dimensions to reduce springback in the flexforming process

Crash and Vibration Analysis of rotors in a Roots Vacuum Booster

Mechanical properties 1 Elastic behaviour of materials

INVERSE METHOD FOR FLOW STRESS PARAMETERS IDENTIFICATION OF TUBE BULGE HYDROFORMING CONSIDERING ANISOTROPY

Abstract. 1 Introduction

Modelling of ductile failure in metal forming

Experimentally Calibrating Cohesive Zone Models for Structural Automotive Adhesives

Upon Impact Numerical Modeling of Foam Materials

Lateral Crushing of Square and Rectangular Metallic Tubes under Different Quasi-Static Conditions

University of Sheffield The development of finite elements for 3D structural analysis in fire

GISSMO Material Modeling with a sophisticated Failure Criteria

Elastic Properties of Solid Materials. Notes based on those by James Irvine at

ALGORITHM FOR NON-PROPORTIONAL LOADING IN SEQUENTIALLY LINEAR ANALYSIS

Volume 2 Fatigue Theory Reference Manual

ANALYTICAL PENDULUM METHOD USED TO PREDICT THE ROLLOVER BEHAVIOR OF A BODY STRUCTURE

The design of a formula student front impact attenuator

A pragmatic strategy to take into account metal materials scatter in FEA

Enhancing Prediction Accuracy In Sift Theory

USER S MANUAL 1D Seismic Site Response Analysis Example University of California: San Diego August 30, 2017

HOT MIX ASPHALT CYCLIC TORQUE TESTS FOR VISCOELASTIC BULK SHEAR BEHAVIOUR

GATE SOLUTIONS E N G I N E E R I N G

DD3MAT - a code for yield criteria anisotropy parameters identification.

Study on the Energy Absorption and the Local Buckling of the Expansion Tubes

IDENTIFICATION OF THE ELASTIC PROPERTIES ON COMPOSITE MATERIALS AS A FUNCTION OF TEMPERATURE

Regupol. Vibration

Rebound Property in Low Velocity Impact of Two Equivalent Balls

Chapter 6: Mechanical Properties of Metals. Dr. Feras Fraige

Regufoam. Vibration 270 Plus.

NUMERICAL SIMULATION OF ELECTROMAGNETIC FORMING PROCESS USING A COMBINATION OF BEM AND FEM

Authors: Correspondence: ABSTRACT: Keywords:

Thomas Johansson DYNAmore Nordic AB. Drop Test Simulation

ANSYS Mechanical Basic Structural Nonlinearities

Inverse identification of plastic material behavior using. multi-scale virtual experiments

INSTRUMENTED HOLE EXPANSION TEST

Activity Tensile Testing SIM

Theory at a Glance (for IES, GATE, PSU)

3D MATERIAL MODEL FOR EPS RESPONSE SIMULATION

PERIYAR CENTENARY POLYTECHNIC COLLEGE PERIYAR NAGAR - VALLAM THANJAVUR. DEPARTMENT OF MECHANICAL ENGINEERING QUESTION BANK

AN ANISOTROPIC PSEUDO-ELASTIC MODEL FOR THE MULLINS EFFECT IN ARTERIAL TISSUE

2 Experiment of GFRP bolt

Elastic Properties of Solids (One or two weights)

Transcription:

Experience from using recently implemented enhancements for Material 36 in LS-DYNA 971 performing a virtual tensile test Authors: Michael Fleischer BMW Group Thomas Borrvall Engineering Research Nordic AB Kai-Uwe Bletzinger Technische Universität München Correspondence: Michael Fleischer BMW Group Phone +49 89 382 0 Email michael.ma.fleischer@bmw.de ABSTRACT: In today s automotive industry the development of car bodies considerably depends on the use of computer-aided tools to meet the challenges of rising product complexity and growing number of variants. Today, enabled by modern simulation software, improved material models and numerical methods, simulation has become essential for the evaluation of sheet-metalstamping processes before press tools are manufactured. Though modern material models are available, some effects are not described correctly, because some parameters are assumed to be constant. In reality, a lot of these constant values must be considered variable. To better represent the real material behaviour, some enhancements for the standard material models have to be implemented to get a more realistic simulation. In this paper we present the results of virtual tensile tests, comparing input- and outputparameters, using the first LS-DYNA material model with variable Lankford coefficients / R-values, yield curves, volume and Young s modulus. All these features are now available in one material model LS-DYNA 971 Material 36. KEYWORDS: Material model, LS-DYNA 971, Material 36, R-Values, Young s modulus 1.5.1 1.141

INTRODUCTION Nowadays there are numerous requirements for the development of new cars. Especially for the production of single car body parts, innovative design with complex geometries, increasing product functionality, variety of variants, reduction of car body weight, innovative materials and production techniques, shortening of tool development times and cost reduction in general are essential demands. To satisfy all requirements, modern simulation software is used during the development to simulate the sheet-metal-stamping process, before the stamping tools are manufactured. In a sheet-metal-stamping simulation, the material behaviour is described by using material models, such as Hill 48 or Barlat 89 [2], [3]. Current models are based on assumptions like constant parameters in order to reduce its complexity. Consequently the real material behaviour is not described exactly. Hence, in current material models, only a few input-parameters are necessary for the mathematical description of the material behaviour. In the material models Hill 48 and Barlat 89, these input-parameters are: One constant Young s modulus E. Three constant Lankford coefficients / R-values R_00, R_45 and R_90. One yield curve k f (ϕ plast ). REQUIREMENTS Recently it has been proven that the Young s modulus is not constant, but strain dependent [5]. The R-values are not constant either; but also strain-dependent [4]. For new materials like TRIP-steels, the assumption of a constant volume during the forming is not correct, because there is a change in the microstructure. To get a more realistic mathematical description of the real material behaviour, we present a material model with the following enhancements: Variable R-values. Variable Young s modulus. Variable volume. Three independent yield curves for 00, 45 and 90 rolling direction. 1.142 1.5.1

Further, with virtual tensile tests we examine whether the material input-parameters are reproduced exactly by the mathematical description. IMPLEMENTATION OF THE ENHANCEMENTS FOR THE MATERIAL MODEL IN LS-DYNA 971 IN MATERIAL 36 T. Borrvall [8] integrated the following enhancements into LS-DYNA 971 Material 36 [1], to get a more realistic mathematical description of the material behaviour: R _ XX = R _ XX ( ϕ ) ; XX for 00, 45 and 90 (Eq. 1) plast E = ϕ ) (Eq. 2) E( plast V = V ( ϕ plast ) (Eq. 3) k _ XX = k _ XX ( ϕ ) ; XX for 00, 45 and 90 (Eq. 4) f f plast VIRTUAL TENSILE TEST WITH LS-DYNA 971 IMPLICIT The tensile test is described in DIN EN 10002 [7] and the geometry of the specimen is defined in DIN50125 [6]. Based on the real tensile test, virtual tensile tests are used to analyse the quality of the new enhancements in a virtual test loop. In this virtual test loop, input- and output-parameters are compared, see Figure 1. The virtual tensile test also uses a test specimen, see Figure 2, and the following parameters are determined: Resulting forces F. Change in length ΔL. Change in width ΔB. With these determined parameters, the output-parameters yield curve, R-value and Young s modulus from the virtual tensile test specimen are calculated. 1.5.1 1.143

Figure 1: Virtual test loop for comparison of input- and output-parameters Figure 2: Virtual tensile test specimen with defined measurement MATERIAL INPUT-DATA FOR THE VIRTUAL TENSILE TEST According to standard deep drawing steel, the following input-parameters were chosen for the virtual test-material: R_00 = 1.7, R_45 = 1.3 and R_90 = 1.9. E 0 = 210000 N/mm 2. One standard yield curve, see Figure 3. Figure 3: Yield curve for 00 rolling direction 1.144 1.5.1

To test the recently implemented enhancements, the following parameters are assumed for the test-material. None of the following values have been measured. Three different yield curves (Figure 4) 00 yield curve (Figure 4) is multiplied with the factor 1.1 for 45 yield curve and multiplied with the factor 1.2 for 90 yield curve. Three variable R-values (Figure 5) functions for R_00, R_45 and R_90 starting at R_XX = 1 and stabilizing at ϕ plast = 0.1 to R_00 = 1.7, R_45 = 1.3 and R_90 = 1.9. plast Change in volume (Figure 6): = 1 a ( e 1 ) (Eq. 5) V rel with a = 0.3. Change in Young s modulus (Figure 7) [1], [5]: a ϕ (Eq. 6) E = E ( E 0 E A )(1 e 0 plast with E 0 = 210000 N/mm 2, E A = 180000 N/mm 2 and a = 10. ) ϕ Figure 4: Yield curves for 00, 45 and 90 Figure 5: R-Values for 00, 45 and 90 Figure 6: Volume correction curve Figure 7: Variable Young s modulus 1.5.1 1.145

RESULTS OF THE VIRTUAL TENSILE TEST Virtual tensile tests are used to analyse the quality of the new enhancements in a virtual test loop, see Figure 1. Five different virtual tests are performed to describe the behaviour of a standard material model and to propose the new possibilities to define the material behaviour numerically. The following test-settings are used: Test 1: Standard Barlat 89 material model with varying M-parameter. Test 2: Three identical and three different yield curves with constant R-values. Test 3: Three different yield curves and three variable R-values. Test 4: Standard Barlat 89 material model with volume correction. Test 5: Standard Barlat 89 material model with variable Young s modulus. TEST 1: RESULTS FROM VIRTUAL TENSILE TEST USING STANDARD MATERIAL 36 - BARLAT 89 - WITH VARYING M- PARAMETER Based on the virtual tensile tests in 00, 45 and 90 rolling direction using a standard Barlat 89 material model (input-parameters: one yield curve and three constant R- values) with varying M-parameter, the resulting output-parameters yield curves, see Figure 8, and R-values, see Table 1 are presented. Input M = 2 M = 4 M = 6 M = 8 R_00 1.7 1.71 1.72 1.75 1.78 R_45 1.3 1.31 1.31 1.33 1.35 R_90 1.9 1.92 1.93 1.96 2.00 Figure 8: Input- and output- yield curves from virtual tensile test for 00, 45 and 90 Table 1: Input- and output- R-values from virtual tensile test M- dependent 1.146 1.5.1

The yield curve for the 00 direction is reproduced well. The problem with the resulting yield curves for 45 and 90 is that they are scaled by the R-values, because they are not independent from each other. In addition resulting R-values are M-dependent. see [2]. With standard material models, material behaviour of materials with nearly identical or absolutely not identical yield curves in 00, 45 and 90 direction and different R-values can not be described exactly. TEST 2: RESULTS FROM VIRTUAL TENSILE TEST USING THREE IDENTICAL AND THREE DIFFERENT YIELD CURVES For the second test, three identical, see Figure 3 and three different, see Figure 4 yield curves for the rolling directions 00, 45 and 90 are used. Figure 9 and Table 2 show the input- and output- yield curves and R-values from the virtual tensile test using three identical yield curves. Figure 10 and Table 3 show the input- and output- yield curves and R-values from the virtual tensile test using three different yield curves. Figure 9: Input- and output- yield curves from virtual tensile test using three identical yield curves Figure 10: Input- and output- yield curves from virtual tensile test using three different yield curves Input Output R_00 1.7 1.71 R_45 1.3 1.30 R_90 1.9 1.90 Input Output R_00 1.7 1.72 R_45 1.3 1.32 R_90 1.9 1.92 Table 2: Input- and output- R-values from virtual tensile test using three identical yield curves Table 3: Input- and output- R-values from virtual tensile test using three different yield curves In this test the input-parameters match well with the output-parameters. In both cases - three identical and three different yield curves - the input-parameters for yield curves 1.5.1 1.147

and R-values are reproduced very well. With the option of defining three yield curves, it is possible to define three yield curves that will be reproduced exactly in the virtual tensile test, because R-values and yield curves are independent here. TEST 3: RESULTS FROM VIRTUAL TENSILE TEST USING THREE DIFFERENT YIELD CURVES AND THREE VARIABLE R-VALUES In the third test, three different yield curves for the rolling directions 00, 45 and 90, see Figure 4, and three varying R-values, see Figure 5, are used. Because of the independency of yield curves and R-values in this test, the yield curves are reproduced exactly as in the second test, see Figure 11. Figure 12 shows the variable input- and output- R-values for this test. Figure 11: Input- and output- yield curves from virtual tensile test using three different yield Figure 12: Variable input- and output- R-values from virtual tensile test using three different yield The variable R-values are reproduced very well. The R-values start decreasing at ϕ plast 0.15 because the specimen starts necking at this point. This test shows that yield curves and R-values can be defined independently with constant or varying R-values. TEST 4: RESULTS FROM VIRTUAL TENSILE TEST USING VOLUME CORRECTION In the fourth test, the standard input (one yield curve and three constant R-values) and a volume correction curve, see Figure 6, are used to show the effects of a volumetric change during the forming process. Figure 13 shows the dependency of ϕ 3 from the material model (Barlat 89 with M = 2) and the material behaviour in the specimen with 1.148 1.5.1

and without volume correction. Table 4 shows the input- and output- R-values for the test with and without volume correction. Input Output - with volume correction R_00 1.7 1.66 1.71 Output without volume correction Figure 13: Resulting ϕ 3 from virtual tensile with and without a volumetric change Table 4: Input- and output- R_00 values with and without a volumetric change With a standard material model (Barlat 89 with M = 2) ϕ 3 can be calculated with the assumption of a constant volume. But that is not correct for a material with a volumetric change. With the volume correction, a larger absolute value of ϕ 3 for the specimen is resulting for the tensile test. ϕ 3 is directly measured here. The input R_00 value is reproduced well for the simulation with the volume correction, see Table 4. TEST 5: RESULTS FROM VIRTUAL TENSILE TEST USING VARIABLE YOUNG S MODULUS In the fifth test, the standard input (one yield curve and three constant R-values) and a variable Young s modulus, see Figure 7, are used to show the effects of a strain dependent Young modulus during the forming process. Figure 14 shows a stretched specimen with plastic strain displayed. The simulation is stopped at certain stages to perform a springback-simulation. In each springbacksimulation the actual Young s modulus is calculated from change in length ΔL and actual stress. 1.5.1 1.149

Figure 14: Stretched specimen from virtual tensile test plastic strain value displayed Figure 15: Input- and output- Young s modulus Figure 15 shows the changing input Young s modulus and the resulting Young s modulus from the springback-simulations. The input values are reproduced exactly. SUMMARY AND CONCLUSIONS In this paper we presented a virtual tensile test using some modifications and enhancements for a standard material model. In contrast to the implemented standard material models in LS-DYNA 971, we use more variable parameters to describe the material behaviour of a virtual test-material. We showed that the new implementations, variable R-values, variable Young s modulus, variable volume and yield description with 3 independent yield curves numerically worked well for the virtual tensile test and are able to reproduce the input-parameters very well. This gives the user more possibilities to model the material behaviour with one material model. The material model worked fine on a virtual tensile test. Future work includes some other easy tests and a real deep drawing part. REFERENCES [1] LS-DYNA Keyword User's Manual Version 971, Livermore Software Technology Corporation, Livermore, (2007) [2] Barlat, F.; Lian, J.: Plastic Behavior and Stretchability of Sheet Metals, Part I: A Yield Function for orthotropic Sheets under Plane Stress Conditions, International Journal of Plasticity, Vol. 5, 51-66, (1989) 1.150 1.5.1

[3] Hill, R.: A Theory of yielding and plastic Flow of anisotropic metals, Proc. Roy. Soc. London, A193, 281-297, (1947) [4] Vogel, C.: Erweiterte Beschreibung des Umformverhaltens von Blechwerkstoffen, Technisch Universität München, Dissertation, (2001) [5] Yoshida, F. and Uemori, T., A Model of Large-Strain Cyclic Plasticity and its Application to Springback Simulation, International Journal of Mechanical Sciences, Vol. 45, 1687-1702, (2003) [6] DIN50125 [7] DIN EN 10002, Part 1 [8] T. Borrvall, Engineering Research Nordic AB - http://www.erab.se/ 1.5.1 1.151

1.152 1.5.1