Engineering simulations and testing by atoast

Engineering Simulations and Testing
Raj C Thiagarajan, PhD
The Engineering process is the
conversion of material into useful
product. The need for both simulation
and experiments for reliable and
rapid development of new products is
outlined. This report provides a brief
overview of the simulation based
engineered product development and
testing for the first time right product
development. The interplay between
simulation and testing are highlighted.

ATOA Scientific Technologies
Engineering Simulation For Innovation

Table of Contents
1. The Engineering Process
2. The Simulation for the First time right
3. Simulation Based Engineering (SBE)
4. Simulation based Engineering Design (SBED)
5. Type of Failure and Examples
6. Reliability of Simulations
7. Testing of Materials
8. Why do we Test?
9. Simulation and Testing + Validation & Verification
10. What Material Properties are Tested?
11. What is Measured?
12. Type of Mechanical Testing
13. Virtual Testing
14. The Four Stages of Complimentary Simulation and Testing

© ATOA Scientific Technologies www.atoastech.com Multiphysics CAE For Innovation TM 2

The Engineering Process

MATERIAL ENGINEERING PROCESS PRODUCT

The Traditional Engineered Process
Conceptual Design Fabrication Assembly Testing

The Simulation Based Engineered Process
Mathematical Virtual Testing for
Predictive
Computational product/ Validation &
Processing
Design system verification

Transformation of
Material into Useful Products
FIRST TIME RIGHT


The Simulation for the First time right
MATHEMATICAL MODEL
•Captures the THE PHYSICS EMBEDDED IN THE ENGINEERING SCIENCES Real product/
•Simple closed-form solutions to establish essential relationships, Numerical solutions for complex system
problems
•Properties of different types of differential and integral equations
•Closed-form solutions only available for very simple problems
Mathematical
•The mathematical model only transforms the available information about the real problem into a
model
predictable quantity of interest

COMPUTATIONAL MODEL
Computational
•Computers have revolutionized techniques for solving differential and integral equations
model
•Finite element methods,
•Availability of Fast and cheap computing power
•Accurate numerical solutions to complex problems
•Nonlinearities easily handled
Prediction
(Output)
•The purpose of computation to model the real system to output the quantities of interest on
which a decision can be made
• NEW PARADIGM: Simulation based engineering Design (SBED) with Multiphysics and Multiscale depth

It is a must to incorporate all the known Scientific and or Engineering knowledge for a
given problem solving or new product design.
Failure by not integrating the known knowledge is not professionally acceptable.

Simulation Based Engineering (SBE)

• Engineering is the profession in which a
knowledge of the mathematical and natural
sciences gained by study experience, and
practice is applied with judgment to develop
ways to utilize, economically, the materials
and forces of nature for the benefit of the
society -Accreditation Board for Engineering and Technology

• SBE to develop Virtual Innovative Products for unique
customer experience with highest performance and
reliability at lowest cost .

• Studies shows that the Simulation based Product
development, reduced the prototyping by 50% and
increased the lead time ~60 days ahead of the
competition.


Simulation based Engineering Design
(SBED)
• SBED provides unparalleled access to real-world
conditions
• SBED is credited with numerous success story
• SBED can be used to Predict unknown product
performance for first time right
• Eventually can be used to predict the future outcome

• Simulations has none of the following limitations of
experimental designs /tests,
– Cost constraints
– harsh/unrealistic parameter ranges, and
– Environment, Health and Safety concerns.

• It has become indispensable for
– Weather prediction
– Medical diagnosis (Virtual human)
– Material modeling
– Drug synthesis From: Research Directions In Computational Mechanics, A Report of the United States National
Committee on Theoretical and Applied Mechanics, September 2000

– Auto design for crashworthiness Ref: Jaroslav Mackerle Finite-element analysis and simulation of machining: a bibliography (1976–
1996), Journal of Materials Processing Technology 86 (1999) 17–44


Type of Failure and Examples
A. Modeling Problem/ Unknown Phenomenon
The Tacoma Narrows Bridge. The suspension bridge across Puget-Sound
(Washington State) collapsed November 7, 1940.
Reason: the model did not properly describe the aerodynamic forces and the
effects of the Von Karman vortices. In addition, the behavior of the cables was
not correctly modeled.
• The Columbia Shuttle Accident June 2003. It was caused by a piece of foam
broken off the fuel tank. After it was observed, the potential of the damage
was judged, upon computations, as nonserious. Reason: the model used did
not take properly into consideration the size of the foam debris.
B. Numerical Treatment Problem
• The Sleipner Accident. The gravity base structure of Sleipner, an offshore
platform made of reinforced concrete, sank during ballast test operation in
Gandsfjorden, Norway, August 23, 1991. Reason: finite element analysis gave a
47% underestimation of the shear forces in the critical part of the base
structure.
C. Computer Science Problem
• Failure of the ARIANE 5 Rocket, June 1996. Reason: problem of computer
science, implementation of the round offs.
D. Human Problem
• Mars Climate Orbiter. The Orbiter was lost September 23, 1999, in the Mars
Atmosphere. Reason: unintended mixture of Imperial and metric units.

Simulations helps to avoid failure & From: Babuška, F. Nobile, R. Tempone, Reliability of

make it first time right. Computational Science, Numerical Methods for Partial
Differential Equations, DOI 10.1002/num 20263,
www.interscience.wiley.com


Reliability of Simulations
Engineering accidents can happen due to,
– Modeling Error,
– the numerical treatment,
– computer science problems, and
– human errors.

Reliability of simulation depends on
• The Mathematical model.
• Resources vs performance
• Deterministic/ Probabilistic
• Prediction/quantification
– Failure probability
– Confidence level/ Factor of safety
• Simulations are moving from Trend prediction to
actual and accurate performance prediction
Objective is to increase the reliability of simulations.


Testing of Materials
• Simulation and Testing are complimentary
• Similar to Theory vs Experiments.
• Testing are generally used to verify simulations.
• Simulation also includes virtual material testing.
• Faster and cheaper new product Development
• Prediction of anisotropic, complex, costly and time
consuming experimental properties.
• Simulation helps to cut the cost and time
• But Final, limited Testing is a must for new product
Development and Introduction into the
Market.


Why do we test?
• Avoid Premature Failure
• Testing is part of the engineering Process
• To augment Computational Simulation based
Engineering for Virtual product development .
• To provide inputs to simulation
• Validation and Verification
• Material, product, process, system development
• Characterization of Material properties
• Part performance prediction
• Quality control/assurance, Long term reliability

Simulation and Testing + V&V
Real product/ Mathematical Computational Prediction
Simulation
system model model (Output)

Testing Validation Verification

• The interplay between Simulation and Testing.
• Testing is a process to help validation and verification
for first time right.
• Validation is a process determining if the mathematical
model describes sufficiently well the reality
• Verification is a process of determining whether the
computational model and the implementation lead to
the prediction with sufficient accuracy.
• V&V concepts are applicable to all stages of testing….

Reference: Leszek A. Dobrza´nski, Significance of materials science for the future development of
societies, Journal of Materials Processing Technology 175 (2006) 133–148


What Material Properties are Tested?
Mechanical:
• Strength, stiffness, elasticity, plasticity,
ductility, brittleness, hardness, wear
resistance, Impact strength, fatigue life.
Thermal:
• Expansion, specific heat, thermal
conductivity, Thermal diffusivity
Electrical & magnetic:
• Conductivity, permeability, permittivity,
dielectric properties.
Acoustical:
• Sound transmission, Attenuation.
Optical:
• light transmission/reflection, haze,
absorption, Color.

What is Measured?
• In a Typical mechanical testing:
• Force and pressure
• Deflection and displacement
• Hardness
• Velocity, acceleration,
• Temperature, humidity

• Variation due to 5M (People, Machine, Methods, Material,
Mother Nature).
• Specification, Quality control , Gauge R&R, Data transfer
• International standards (ASTM, ISO..) guide Testing Process


Type of Mechanical testing
• Load type : Tension, Compression, shear, torsion, flexure,
• Loading rate/time/ Repetition :
Steady state/ Static/ Short Transient/ dynamic/ Long term /
term/ Monotonic cyclic

Mechanics: Mechanics:
Fixed geometry, loads Variable geometry, loads
Continuum Discontinuous
Dominated by final failure Dominated by micro mechanical
events events

Physics: Physics:
Equilibrium state Variable state of material
Constant properties Variable properties
Only Mechanical testing is referred. Watch out this space for more on Thermal,
Electrical, Magnetic, Acoustical, Opticals...

Virtual Testing
• Simulation to predict the experimental properties
of systems.
• For example, It is difficult to characterize all the
anisotropic properties of composites. Numerical
models is used to predict the complimentary
anisotropic properties.
• Simulation to mimic the testing is performed to
zoom into the inner working mechanism of
materials and products.
• The progressive growth, failure, damage mechanics
can help to reverse engineer the materials for
improved and optimal performance.
• Virtual Testing are used to simulate and predict
high risk and costly experimental tests for cost
effective product development.


Four Stages of Complimentary Simulation and
Testing for the Engineering Design of First Time
Right Product Development


ATOA Scientific Technologies Pvt Ltd (LLC)

ATOA Scientific Technologies is an engineering simulation
service provider, with a specialty on Multiphysics, Multiscale
and Multimaterials, for innovative material, product,
process and system development to cut cost and cycle time
for our clients.
For all your Engineering CAD, CAE, CFD, CAPD, CAI
Contact:
ATOAST.HQ@atoastech.com

Engineering simulations and testing by atoast

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