"Material testing and hyperelastic material model curve fitting for Ogden, Polynomial and Yeoh models"
By Michael Rackl, Technische Universität München for ScilabTEC 2015
This is my Lab Report of Tensile Test when I was conducting engineering material lab in Sampoerna University. Feel free to download for a reference.
I know it is not a good report, but I hope this share might help you to find something you need.
Thank you.
Tensile testing is one method routinely used to determine the mechanical properties of plastics. This piece presents an example of measuring the mechanical properties of acrylonitrile butadiene styrene (ABS), Polyoxymethylene (POM), Polyethylene terephthalate (PET) and polystyrene (PS)
Tensile, Impact and Hardness Testing of Mild SteelGulfam Hussain
The main purpose of this report is to study the mechanical properties and
failure mode of mild steel. Three types of standard tests i.e. tensile test, impact
test, and hardness test were conducted on the standard specimens of mild steel.
From the tests, results were obtained; Tensile strength, Impact strength, and
hardness were calculated. It was observed that Tensile Strength, Impact Strength
and Hardness of MS specimen were 1450.833 N/mm², 29.5 J & 59.25 HRB.
Strength of material lab, Exp 2: Tensile test Osaid Qasim
by using our “UTM” machine that
operates on the basis of applying a load in our specimen , so if
we take this force and compare it with change in the length of
specimen “Deformation” we can obtain a (Load-Deformation
diagram) , and by applying this force and divide it by the
specimen cross sectional area we get the Stress ( σ), and divide
the “Deformation” by the original length of the specimen we
will get the Strain (ϵ) , and comparing the stress with strain
results a very Important curve that is characteristic of the
properties of the material and it’s the (Stress-Strain Diagram),
In the material testing laboratory, Tensile test was done on a mild steel specimen as figure 4 to identify the young’s modulus, ultimate tensile strength, yield strength and percentage elongation. The results were as table 1
Strength of material lab, Exp 3&4: Compression and impact testsOsaid Qasim
- Utilization the UTM machine and know the different
ways that could test the material’s properties.
2- Knowing the different types of failure in the compression.
3- Determining Young's modulus “E” and Passion’s ratio
“υ” and Yield/Proof stress σ y.
1. Finding the impact load effect on the materials.
2. Finding the relative toughness of the different materials.
3. Distinguish between static and dynamic loads and how differently they
effect in the material.
4.Knowing the different methods to preform the impact test (Charpy,
IZOD, Impact tensile).
Model Development for Estimation of Failure Loads: A Case Study of Composite ...ijsrd.com
This paper deals with the study of failure loads of glass vinylester composite plates with a circular hole subjected to a traction force by a rigid pin. These are investigated for two variables, the ratio of distance from the free edge of the plate (E) to the diameter of the hole (D) and the ratio of width of the plate (W) to the diameter of the hole (D). The work consists of a numerical study of different specimens using finite element analysis package ANSYS. Also, a mathematical model has been developed to determine the failure loads of different geometry plates. The results obtained from the numerical study and the mathematical models are compared with experimental results from the existing literature and the correlations are observed for both. A comparison of the experimental results with the numerical model shows that the numerical model gives results with correlation co-efficient 0.96. A comparison of the experimental results with the mathematical model shows that the mathematical model gives results with correlation co-efficient 0.99. For estimation of the failure loads within the range of E/D and W/D considered for the study, the mathematical model developed, i.e., Full Cubic Model proves to be more efficient with the observed values of correlation co-efficient, Root Mean Square Error and Maximum Absolute Error.
Hyperelastic material models in finite element analysis of polymersKartik Srinivas
This paper describes the Hyperelastic material models and strain energy functions used in the finite element analysis (FEA) of polymers. Material characterization testing
1018 Steel and PLA Tensile Test and Hardness ReportTobyBarrons
Details findings from 1018 Steel and PLA tensile and hardness testing. Provides detailed theory and experimental procedure. Skip to results for findings.
This is my Lab Report of Tensile Test when I was conducting engineering material lab in Sampoerna University. Feel free to download for a reference.
I know it is not a good report, but I hope this share might help you to find something you need.
Thank you.
Tensile testing is one method routinely used to determine the mechanical properties of plastics. This piece presents an example of measuring the mechanical properties of acrylonitrile butadiene styrene (ABS), Polyoxymethylene (POM), Polyethylene terephthalate (PET) and polystyrene (PS)
Tensile, Impact and Hardness Testing of Mild SteelGulfam Hussain
The main purpose of this report is to study the mechanical properties and
failure mode of mild steel. Three types of standard tests i.e. tensile test, impact
test, and hardness test were conducted on the standard specimens of mild steel.
From the tests, results were obtained; Tensile strength, Impact strength, and
hardness were calculated. It was observed that Tensile Strength, Impact Strength
and Hardness of MS specimen were 1450.833 N/mm², 29.5 J & 59.25 HRB.
Strength of material lab, Exp 2: Tensile test Osaid Qasim
by using our “UTM” machine that
operates on the basis of applying a load in our specimen , so if
we take this force and compare it with change in the length of
specimen “Deformation” we can obtain a (Load-Deformation
diagram) , and by applying this force and divide it by the
specimen cross sectional area we get the Stress ( σ), and divide
the “Deformation” by the original length of the specimen we
will get the Strain (ϵ) , and comparing the stress with strain
results a very Important curve that is characteristic of the
properties of the material and it’s the (Stress-Strain Diagram),
In the material testing laboratory, Tensile test was done on a mild steel specimen as figure 4 to identify the young’s modulus, ultimate tensile strength, yield strength and percentage elongation. The results were as table 1
Strength of material lab, Exp 3&4: Compression and impact testsOsaid Qasim
- Utilization the UTM machine and know the different
ways that could test the material’s properties.
2- Knowing the different types of failure in the compression.
3- Determining Young's modulus “E” and Passion’s ratio
“υ” and Yield/Proof stress σ y.
1. Finding the impact load effect on the materials.
2. Finding the relative toughness of the different materials.
3. Distinguish between static and dynamic loads and how differently they
effect in the material.
4.Knowing the different methods to preform the impact test (Charpy,
IZOD, Impact tensile).
Model Development for Estimation of Failure Loads: A Case Study of Composite ...ijsrd.com
This paper deals with the study of failure loads of glass vinylester composite plates with a circular hole subjected to a traction force by a rigid pin. These are investigated for two variables, the ratio of distance from the free edge of the plate (E) to the diameter of the hole (D) and the ratio of width of the plate (W) to the diameter of the hole (D). The work consists of a numerical study of different specimens using finite element analysis package ANSYS. Also, a mathematical model has been developed to determine the failure loads of different geometry plates. The results obtained from the numerical study and the mathematical models are compared with experimental results from the existing literature and the correlations are observed for both. A comparison of the experimental results with the numerical model shows that the numerical model gives results with correlation co-efficient 0.96. A comparison of the experimental results with the mathematical model shows that the mathematical model gives results with correlation co-efficient 0.99. For estimation of the failure loads within the range of E/D and W/D considered for the study, the mathematical model developed, i.e., Full Cubic Model proves to be more efficient with the observed values of correlation co-efficient, Root Mean Square Error and Maximum Absolute Error.
Hyperelastic material models in finite element analysis of polymersKartik Srinivas
This paper describes the Hyperelastic material models and strain energy functions used in the finite element analysis (FEA) of polymers. Material characterization testing
1018 Steel and PLA Tensile Test and Hardness ReportTobyBarrons
Details findings from 1018 Steel and PLA tensile and hardness testing. Provides detailed theory and experimental procedure. Skip to results for findings.
Modeling an ODE: 3 different approaches - Part 3Scilab
In this tutorial we show how to model a physical system described by ODE using the Modelica extensions of the Xcos environment. The same model has been solved also with Scilab and Xcos in two previous tutorials.
Customizing Xcos with new Blocks and PaletteScilab
In this tutorial, we show how to create and customize Xcos blocks and palettes. Moreover, we use the "Xcos toolbox skeleton" for a better result. The LHY model in Xcos scheme (already developed in other tutorials) is used as a starting point.
"Keynote - Preserving Software: Challenges and Opportunities for Reproducibility of Science and Technology"
By Roberto Di Cosmo, Irill for ScilabTEC 2015
"Using Scilab in the Radiation Thermometry Laboratory of Inmetro"
By Ricardo Sohn, Instituto Nacional de Metrologia, Qualidade e Tecnologia - Inmetro for ScilabTEC 2015
In this tutorial the reader can learn about data fitting, interpolation and approximation in Scilab. Interpolation is very important in industrial applications for data visualization and metamodeling.
"Can programming of multi-core systems be easier, please? The ALMA Approach"
By Oliver Oey, Karlsruhe Institute of Technologie - KIT for ScilabTEC 2015
ScilabTEC 2015 - Bavarian Center for AgricultureScilab
"Development of a diagnostic tool for performance analysis during the testing of agricultural implements"
By Zoltan Gobor, Bavarian State Research Center for Agriculture for ScilabTEC 2015
The aim of this paper is to show the possibilities offered by Scilab/Xcos to model and simulate aeraulic and HVAC systems. In particular we develop a new Xcos module combined with the use of Modelica language to show how aeraulic systems can be modeled and studied. In this paper we construct a reduced library composed by few elements: hoods, pipes and ideal junctions. The library can be easily extended to obtain a more complete toolbox. The developed library is tested on a simple aeraulic circuit.
The purpose of this tutorial is to show that Scilab can be considered as a powerful data mining tool, able to perform the widest possible range of important data mining tasks.
Modeling an ODE: 3 different approaches - Part 1Scilab
In this tutorial we show how to model a physical system described by ODE using Scilab standard programming language. The same model solution is also described in Xcos and Xcos + Modelica in two other tutorials.
Modeling an ODE: 3 different approaches - Part 2Scilab
In this tutorial we show how to model a physical system described by ODE using Xcos environment. The same model solution is also described in Scilab and Xcos + Modelica in two other tutorials.
In this Scilab tutorial, we introduce readers to the Control System Toolbox that is available in Scilab/Xcos and known as CACSD. This first tutorial is dedicated to "Linear Time Invariant" (LTI) systems and their representations in Scilab.
Hydraulic Scilab toolbox for water distribution systemsScilab
The purpose of this paper is to show the possibilities offered by Scilab/Xcos to model hydraulic time-dependent systems. In particular, we develop a new Xcos module combined with the use of Modelica language to show how water distribution systems can be modeled and studied. In this paper we construct a reduced library composed by few elements: reservoirs, pipes and nodes. The library can be easily extended to obtain a more complete toolbox. The developed library is tested on a simple well-known hydraulic circuit.
Thank you for the presentation, there are some things I would like.docxmattinsonjanel
Thank you for the presentation, there are some things I would like to point out that I don't think are mentioned in the power point slides you prepared.
For questions 3 it says that I have to give three suitable examples to discuss the importance of shape and materials in the design and manufacture of engineering structures to achieve their mechanical functions and optimal performance -> you only mentioned one or two examples only it says that we need three examples, so can please make them three examples and explain more about each example according to the question that has been asked?
For question 4 it says that we need to propose a novel materials with cross section shape / structure function which we think they have higher bending resistance and torsion resistance per unit area, 2 concepts for each case explaining where your ideas came from and the rationale behind them, ways to test them and targeted applications -> you have mentioned two examples however you did not mention where your ideas came from and the rationale behind them. You also mentioned ways of testing them and their targeted applications; however you did not go in depth. So can I ask you please to do the slides in a way that answers every components mentioned in the question and include the missing parts that you did not include in the presentation.
OVERALL
hello I asked my teacher and he told me there is a mistakes in point 3 and 4. 3. Using suitable examples (at least three), discuss the importance of shape and materials in the design and manufacture of engineering structures in order to achieve their mechanical functions and optimal performances (3-5 slides). (30%)
you can use this example 1-tennis racket 2-bicycle frame.3-pressure vessel.
4. Latest development of 3D printing and composite materials have opened up the possibility to produce very complex shapes/structures which can’t be produced through traditional manufacture process (e.g. machining), propose potential novel materials with new cross-section shape/ structure/functions, which you think may give a higher bending resistance and torsion resistance per unit area. (Minimum 2 concepts each case, ideally in solid work sketch). Explain where your ideas come from and the rational behinds them, propose ways to test your ideas and targeted applications (4-8 slides) (20%).
Also I attached a file that can help you do the last two point 3 ad 4
Accident Prevention Plan
(Your Name)
TECH 462 –Industrial Safety Engineering
(Date)
Table of Contents
Introduction
Purpose & Intentions Page x
Company Presidents Statement Page x
Management Responsibilities
Manager Responsibilities Page x
Supervisors Responsibilities Page x
Employee Orientation
How and When Page x
Emergency Action Plan Page x
Emergency Shutdown Procedures Page x
Injury and Illness Procedures
Procedures Page x
Record Keeping Page x
Supervisor Responsibilities Page x
Repo ...
Experiment 4 - Testing of Materials in Tension Object .docxSANSKAR20
Experiment 4 - Testing of Materials in Tension
Object: The object of this experiment is to measure the tensile properties of two polymeric
materials, steel and aluminum at a constant strain rate on the Tension testing machine.
Background: For structural applications of materials such as bridges, pressure vessels, ships,
and automobiles, the tensile properties of the metal material set the criteria for a safe design.
Polymeric materials are being used more and more in structural applications, particularly in
automobiles and pressure vessels. New applications emerge as designers become aware of
the differences in the properties of metals and polymers and take full advantage of them. The
analyses of structures using metals or plastics require that the data be available.
Stress-Strain: The tensile properties of a material are obtained by pulling a specimen of
known geometry apart at a fixed rate of straining until it breaks or stretches to the machines
limit. It is useful to define the load per unit area (stress) as a parameter rather than load to
avoid the confusion that would arise from the fact that the load and the change in length are
dependent on the cross-sectional area and original length of the specimen. The stress,
however, changes during the test for two reasons: the load increases and the cross-sectional
area decreases as the specimen gets longer.
Therefore, the stress can be calculated by two formulae which are distinguished as
engineering stress and true stress, respectively.
(1) = P/Ao= Engineering Stress (lbs/in
2 or psi)
P = load (lbs)
Ao= original cross-sectional area (in
2)
(2) T= P/Ai = True Stress
Ai = instantaneous cross-sectional area (in
2)
Likewise, the elongation is normalized per unit length of specimen and is called strain. The
strain may be based on the original length or the instantaneous length such that
(3) =(lf - lo)/ lo = l / lo = Engineering Strain, where
lf= final gage length (in)
lo= original gage length (in)
(4) T= ln ( li / lo ) = ln (1 +) = True Strain, where
li = instantaneous gage length (in)
ln = natural logarithm
For a small elongation the engineering strain is very close to the true strain when l=1.2 lo,
then = 0.2 and T= ln 1.2 = 0.182. The engineering stress is related to the true stress by
(5) T= (1 + )
The true stress would be 20% higher in the case above where the specimen is 20% longer
than the original length. As the relative elongation increases, the true strain will become
significantly less than the engineering strain while the true stress becomes much greater than
the engineering stress. When l= 4.0 lo then = 3.0 but the true strain =ln 4.0 = 1.39.
Therefore, the true strain is less than 1/2 of the engineering strain. The true stress (T) = (1+
3.0) = 4, or the true stress is 4 times the engineering stress.
Tensile Test Nom ...
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
The present study investigates the creep in a thick-walled composite cylinders made
up of aluminum/aluminum alloy matrix and reinforced with silicon carbide particles. The distribution
of SiCp is assumed to be either uniform or decreasing linearly from the inner to the outer radius of
the cylinder. The creep behavior of the cylinder has been described by threshold stress based creep
law with a stress exponent of 5. The composite cylinders are subjected to internal pressure which is
applied gradually and steady state condition of stress is assumed. The creep parameters required to
be used in creep law, are extracted by conducting regression analysis on the available experimental
results. The mathematical models have been developed to describe steady state creep in the composite
cylinder by using von-Mises criterion. Regression analysis is used to obtain the creep parameters
required in the study. The basic equilibrium equation of the cylinder and other constitutive equations
have been solved to obtain creep stresses in the cylinder. The effect of varying particle size, particle
content and temperature on the stresses in the composite cylinder has been analyzed. The study
revealed that the stress distributions in the cylinder do not vary significantly for various combinations
of particle size, particle content and operating temperature except for slight variation observed for
varying particle content. Functionally Graded Materials (FGMs) emerged and led to the development
of superior heat resistant materials.
• Developed and studied the mechanical behavior of a new biodegradable composite material.
• Conducted Tensile and Flexural analysis of samples to test their properties.
• Genetic algorithm method was used to obtain the maximum tensile and flexural strength.
• The new material was used to make household items such as hangers, trash cans, and holders.
Why electric vehicles need model-based design?
Because of the rising complexity in new vehicles, model-based design & systems engineering is needed to cascade the requirements and trace back any modification along the engineering lifecycle. Find out more in this presentation of a customer case about electric motor optimization.
Keynote of the French Space Agency CNES on the Asteroidlander MASCOT boarding the Hayabusa2 mission in collaboration with the Japanese Space Agency JAXA and the German Aerospace Center DLR
Faster Time to Market using Scilab/XCOS/X2C for motor control algorithm devel...Scilab
Rapid Prototyping becomes very popular for faster algorithm development. With a graphical representation of the algorithm and the possibility to simulate complete designs, engineers can help to reduce the time to market. A tight integration with MPLAB-X IDE allows the combination with standard C-coding to easily get mass production code. This solution was used to optimise a sensorless field oriented controlled PMSM motor driven pump efficiency. A model for closed loop simulation was developed using X2C blocks [1][2] for the FOC algorithm based on the existing application note AN1292 [3]. Enhancements to the original version were implemented and verified with simulation. The X2C Communicator was used to generate code of the new algorithm. With the online debugging capabilities and the scope functionality the algorithm was further tuned and optimized to achieve the highest possible efficiency of the pump.
Scilab and Xcos for Very Low Earth Orbits satellites modellingScilab
Very Low Earth Orbits are orbits in altitudes lower than 450 km. The interaction between the atmosphere particles and the surfaces of the spacecraft is responsible for the aerodynamic torques and forces. Simulating several aspects of the performance of a satellite flying in VLEO is very important to make decisions about the design of the spacecraft and the mission.
X2C -a tool for model-based control development and automated code generation...Scilab
Peter Dirnberger, Stefan Fragner
Nowadays, the market demands compact, stable, easy maintain-and customizable embedded systems. To meet these requirements, afast, simple and reliable implementation of control algorithms is crucial. This paper demonstrateshow model-based design with the help of Scilab/Xcosand X2C, developed by LCM,simplifiesand speedsup the development and implementation of controlalgorithms. As an example, acontrol schemefor a bearingless motoris presented.
A Real-Time Interface for Xcos – an illustrative demonstration using a batter...Scilab
As part of an EU-founded research project, the Scilab based development tool LoRra (Low-Cost Rapid Control Prototyping Platform) was created. This allows the realization of the continuously model based and highly automated Rapid Control Prototyping (RCP) design process for embedded software within the Scilab / Xcos environment (cf. Figure 1). Based on the application battery management system (BMS), this paper presents a Real-Time interface for Scilab.
Aircraft Simulation Model and Flight Control Laws Design Using Scilab and XCosScilab
The increasing demand in the aerospace industry for safety and performance has been requiring even more resourceful flight control laws in all market segments, since the airliners until the newest flying cars. The de facto standard for flight control laws design makes extensive use of tools supporting numerical computing and dynamic systems visual modeling, such that Scilab and XCos can nicely suit this kind of development.
Multiobjective optimization and Genetic algorithms in ScilabScilab
In this Scilab tutorial we discuss about the importance of multiobjective optimization and we give an overview of all possible Pareto frontiers. Moreover we show how to use the NSGA-II algorithm available in Scilab.
Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
Mastering the Concepts Tested in the Databricks Certified Data Engineer Assoc...SkillCertProExams
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Supercharge your AI - SSP Industry Breakout Session 2024-v2_1.pdf
ScilabTEC 2015 - TUM
1. Material testing and hyperelastic material
model curve fitting for Ogden, Polynomial
and Yeoh models
ScilabTEC 2015, Paris, France
Michael Rackl
rackl@fml.mw.tum.de
Technische Universit¨at M¨unchen (TUM)
Institute for Materials Handling, Material Flow, Logistics
Ostbayerische Technische Hochschule Regensburg
Laboratory for Biomechanics
21st
and 22nd
May 2015
2. Outline
1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
3. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 3 / 37
4. Introduction
Background
Static structural investigation on a silicone-suspended fracture
plating system
Modelling by means of finite element method (FEM)
⇒ How to model silicone in FEM?
Answer from literature: hyperelastic material models
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 4 / 37
5. Introduction
Hyperelastic material models
Two types of hyperelastic material models1
Phenomenological models
material constants generated
by curve fitting
Micro-mechanical models
material constants generated
by specific material tests
The use of phenomenological model is suggested, as the physical
significance of micro-mechanical material constants is often unclear2
.
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 5 / 37
6. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 6 / 37
7. Fitting hyperelastic material constants
workflow and material model selection
1 Material tests: stress-stretch curves from e. g. uni- or bi-axial
tensions tests, shear tests.
2 Curve fitting: adapting the material constants based on
analytical models, to closely reproduce the measured curves.
3 Validation by modelling the material tests with FEM and
comparison of the results.
Material models selected for this work:
Ogden Model3
,
Polynomial Model4
(includes the Mooney-Rivlin Model5;6
),
Yeoh Model7
.
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 7 / 37
8. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 8 / 37
9. Problem description and approach
FEM software Ansysa
offers higher-order hyperelastic material model
input, but does not feature curve fitting for each of these models.
Approach:
Create a Scilabb
script and corresponding functions to conduct
non-restrictive curve fitting.
a
ANSYS Inc., Canonsburg, Pennsylvania, USA
b
Scilab Enterprises, Versailles, France
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 9 / 37
10. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 10 / 37
11. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 11 / 37
12. Materials and Methods
Material tests
Bonded compression/tension
test (stress results to be
corrected8
)
12,7
rod
rod
silicone
3
Simple shear test
strip
strip
silicone
A
A
10
10
25,4
0,25
all dimensions in
Millimetres;
“strip” refers to
a steel strip
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 12 / 37
13. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 13 / 37
14. Analytical equation of the Yeoh Model in
tension/compression (example) I
1. Base equation of the Yeoh Model: W = n
i=1 Ci · I1 − 3
i
W : strain energy,
Ci : material constant,
I1: strain invariant,
n: model order.
2. strain invariants I1 for compression/tension9;10
:
I1 = λ2
+ 2λ−1
,
I2 = λ−2
+ 2λ.
λ: stretch due to tensile/compressive stress
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 14 / 37
15. Analytical equation of the Yeoh Model in
tension/compression (example) II
3. relation between engineering stress σe and stretch λ for an
incompressible material under tension/compression6;11
:
σe = 2 · λ − λ−2
· ∂W
∂I1
+ 1
λ
· ∂W
∂I2
.
4. Combining the aforementioned equations yields
σe λ =
n
i=1
2 · Ci · i · λ − λ−2
· λ2
+ 2λ−1
− 3
i−1
for tension/compression of an nth
order Yeoh Model.
Michael Rackl (TUM) Material Testing and (. . . ) 21st
and 22nd
May 2015 15 / 37
16. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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17. Optimisation problem
Scilab script overview
index “M” denotes data from measurement
Material model
functions for
Yeoh Model
tension/
compression
simple shear
σ(λM, C)
τ(γM, C)
εσ
ετ
σM
τM
measurement
data
ε = εσ + ετ
minimise ε!
fminsearch
Material
constants
vector C
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18. Optimisation problem
notes
Error criteria σ and τ may be normalised or unnormalised
(absolute)
norm = 1 −
σ λ, C
σM λ
2
abs = σM λ − σ λ, C
2
Adjusted coefficient of determination12
was computed for
goodness of fit evaluation
Results for lower-order material models were compared
to those from Ansys
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19. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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20. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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21. Results and Discussion
Ogden Model; comparison with ANSYS
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22. Results and Discussion
Ogden Model; curve fitting example
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23. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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24. Results and Discussion
Polynomial Model; comparison with ANSYS
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25. Results and Discussion
Polynomial Model; curve fitting example
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26. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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27. Results and Discussion
Yeoh Model; comparison with ANSYS
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and 22nd
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28. Results and Discussion
Yeoh Model; curve fitting example
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29. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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and 22nd
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30. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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31. Conclusion
General
Curve fitting script for fitting any order Ogden, any order Yeoh
and second as well as first order Polynomial models, plus a three
parameter Mooney-Rivlin Model.
Yeoh and Polynomial Model curve fitting for lower-order models
successfully validated against results from Ansys
Scilab script allows for
curve fitting of higher order models than Ansys,
biasing of one of the material test results possible.
higher order models tend to instabilities at small nominal-strains
(Ansys warning message)
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32. 1 Introduction
Background information
Fitting hyperelastic material constants
Problem description and approach
2 Materials and Models
Material tests
Analytical equation for the Yeoh Model in tension/compression
(example)
Optimisation problem
3 Results and Discussion
Ogden Model
Polynomial Model
Yeoh Model
4 Conclusion
General
Discrepancies with the Ogden Model implementation
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33. Conclusion
Discrepancies with the Ogden Model implementation I
Ogden Model implementation ⇒ difference in material constants
between Ansys and the Scilab script
Results for lower-order models from verification process:
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35. Conclusion
Discrepancies with the Ogden Model implementation III
Ogden Model appears to be implemented correctly within the
Scilab script (cf. previous slide)
Differences could arise from
the nonlinear nature of the problem,
the fact that more than one minimum exists.
Besides: Even identical start values may lead to completely different
material parameter sets13
.
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36. Thank you!
Do you have questions or feedback?
References (two slides)
[1] P. Steinmann, M. Hossain, and G. Possart. Hyperelastic models for rubber-like materials: consistent tangent operators
and suitability for Treloar’s data. Archive of Applied Mechanics, 82(9):1183–1217, 2012.
[2] R. W. Ogden, G. Saccomandi, and I. Sgura. Fitting hyperelastic models to experimental data. Computational Mechanics,
34(6):484–502, 2004.
[3] R. W. Ogden. Large Deformation Isotropic Elasticity - On the Correlation of Theory and Experiment for Incompressible
Rubberlike Solids. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences,
326(1567):565–584, 1972.
[4] R. S. Rivlin and D. W. Saunders. Large Elastic Deformations of Isotropic Materials. VII. Experiments on the Deformation
of Rubber. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences,
243(865):251–288, 1951.
[5] M. Mooney. A Theory of Large Elastic Deformation. Journal of Applied Physics, 11(9):582–592, 1940.
[6] R. S. Rivlin. Large Elastic Deformations of Isotropic Materials. IV. Further Developments of the General Theory.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 241(835):379–397,
1948.
[7] O. H. Yeoh. Some Forms of the Strain Energy Function for Rubber. Rubber Chemistry and Technology, 66(5):754–771,
1993.
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and 22nd
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37. [8] J. M. Horton, G. E. Tupholme, and M. J. C. Gover. Axial Loading of Bonded Rubber Blocks. Journal of Applied
Mechanics, 69(6):836, 2002.
[9] L. R. G. Treloar. The elasticity and related properties of rubbers. Reports on Progress in Physics, 36(7):755–826, 1973.
[10] F. R. Schwarzl. Polymermechanik: Struktur und mechanisches Verhalten von Polymeren. Springer, Berlin, 1990.
p. 298-299.
[11] R. S. Rivlin. Large Elastic Deformations. In F. R. Eirich, editor, Rheology, pages 351–385. Academic Press, New York,
1956.
[12] L. Fahrmeir, T. Kneib, and S. Lang. Regression: Modelle, Methoden und Anwendungen. Statistik und ihre Anwendungen.
Springer, Berlin and Heidelberg, 2nd
edition, 2009. p. 161.
[13] A. Zielesny. From curve fitting to machine learning: An illustrative guide to scientific data analysis and computational
intelligence, volume 18 of Intelligent systems reference library. Springer, Berlin, 2011. p. 146.
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