AdvanSES announces that its Testing Laboratory has attained ISO/IEC 17025:2017 accreditation vide NABL certificate No. TC-9168. ISO/IEC 17025:2017 is the highest recognized quality standard in the world for calibration and testing laboratories. Accreditation means the lab consistently produces precise and accurate test data and has implemented a rigorous quality management system. The stringent processes in the audits for the accreditation relate to the operations, efficiency and effectiveness of the laboratory. Test data from the laboratory is benchmarked for accuracy, reliability and consistency.
Receiving the accreditation means that test reports and certificates generated from AdvanSES laboratory can now be generally accepted from one country to another without further testing.
The scope of the accreditation covers tests and properties in the field of rubbers, plastics and composite materials. It is one of the few labs in the world accredited to perform internationally recognized fatigue standards like ASTM D7791.
AdvanSES today is one of the few companies in the world who provide expert problem solving services using Finite element analysis (FEA), provides new product development and material testing and analysis.
The sole purpose of an engineering laboratory is to provide engineering product development and problem solving services to industries by carrying out controlled condition experiments and engineering analysis. These controlled condition experiments are done using testing machines, computational mechanics tools and advanced engineering softwares. At AdvanSES we use state of the art testing equipments to conduct material testing on any kind of metals, polymers and composite materials. Our computational mechanics tools like Abaqus Finite element analysis software, our in-house machine shop aid us in this process.
Testing methodologies are primarily divided into two (2) categories depending upon the test rate; static and dynamic. AdvanSES has both static and dynamic testing capabilities. We are able to provide a full 360 degree view of any material or product’s mechanical characteristics. We can also strength, strain, fatigue, hardness, and lots more.
Our testing methods include the following:
1. ASTM D638 – Standard Test Method for Tensile Properties of Plastic
2. ASTM D882 – Standard Test Method for Tensile Properties of Thin Plastic Sheeting
3. ASTM D412 – Standard Test Methods for Vulcanized Rubber and Thermoplastic Elastomers in Tension
Materials testing helps us to quantify, and understand whether a material or product is suitable to a certain application. Materials testing points us to limits of a material to handle a load or an operating condition. Materials that have not been tested and directly used in a product can be extremely dangerous. The data collected during testing and the final test results can be very useful to engineers, designers, manufacturing engineers and even the marketing department.
Mechanical properties could be determined for all types of materials that are found in aerospace, automotive and biomedical applications. The following mechanical tests could provide more information on the mechanical properties and characteristics of materials, • Ductility and Hardness • Stress and Strain • Elongation at break • Impact Resistance • Fracture Toughness • Fatigue under controlled stress or strain • Creep
Following are some of the reasons material testing is important:
Meeting requirements of regulatory agencies
Evaluating product designs, analyzing a field failure or optimizing a product
Selecting appropriate materials for end use applications
Verifying a production method or conditions
Apart from following a process or procedure to test a mateiral or a product, manufacturers can also make sure that their products conforms to some international test standards like IS, BIS, ISO, ASTM, DIN etc. This is one of the best ways to make sure that the material and product is worth in terms of quality. Regulatory agencies also require that products be tested as per standards before providing the go-ahead to market launch.
1) An Independent, design analysis and mechanical testing laboratory. 2) More than 2 decades of product testing and application expertise in mechanical, and materials engineering. 3) State of the art materials and mechanical testing laboratory with qualified engineers. 4) Innovative design, analysis and testing solutions for a wide range of industries
Quality control refers to the process of systematically detecting errors in the laboratory testing results to ensure both that the accuracy and reliability of test results are maintained and best possible testing results are supplied to customers. Unreliable and inaccurate testing results can result in faulty failures, degraded field performance of engineering materials and products. it is therefore of great importance to ensure all results provided are accurate, reliable and consistent.
Alfort and Beaty define quality control as;
“Quality control is the mechanism by which products are made to measure up to the specifications determined from the customer’s demands and transform into sales, engineering and manufacturing requirements. It is concerned with making things right rather than discovering and rejecting those made wrong. Quality control is a technique by means of which products of uniform acceptable quality are manufactured.”
A mechanical and materials testing laboratory tests all kinds of materials at all stages of product engineering, from the raw material stage to performance characterization and durability testing of finished ready to market products.
The range and types of instruments to test these materials and product range from simplest to complex. Instruments such as density meter and hardness meters are the simple instruments, while SEMs, fatigue test benches, high strain rate equipments etc., are complex instruments that also have a significant learning curve. Only qualified engineers and analysts would be conducting the tests with the help of calibrated instruments to make sure that the data obtained is reliable and accurate.
Achieving quality in a mechanical and materials testing laboratory requires the use of many tools, instruments and machinery. These include UTMs, hardness meters, fatigue testing rigs, and also various custom made test benches. An established maintenance schedule, calibration, quality assurance program, training and quality control are pre-requisites. Calculations and maintenances of QC Statistics for systematic analysis of historical standard deviations, covariances, uncertainty calculations etc., is also required.
Data integrity refers to completeness, consistency and accurateness of the raw data generated in the testing laboratory during the course of its work. It means that the raw data has to be reliable, consistent and accurate and that no modifications, changes or deletions cannot be caried out by any person or machine.
Raw data in the quality control laboratory can be generated by testing machnes, DAQ systems, and computer systems as well as by laboratory staff as paper records and reports. Ensuring integrity of data starts from the proper design of the procedural documents, level of access provided to authorized persons, physical reliablility of the infrastructure and training of laboratory personnel. An appropriately designed procedure is uniquely named and numbered has sufficient leeway for records to be stored comfortably digitally and physically and distribution are strictly controlled at all levels.
Having established all the QC standard protocols at AdvanSES, we take pride in our work and our protocols are available for audit at any time.
Static and dynamic testing of engineering materials and products involves mechanical loading of a material specimen or product up to a pre-determined deformation level or up to the point where the sample fails. The material properties backed out from these tests are further used to characterize the materials and products. Testing is carried out under essentially two conditions viz; Static and Dynamic.
Physical testing of materials as per ASTM D412, ASTM D638, ASTM D624 etc., can be categorized as slow speed tests or static tests. The difference between a static test and dynamic test is not only simply based on the speed of the test but also on other test variables and parameters employed like forcing functions, displacement amplitudes, and strain cycles. The difference is also in the nature of the information we back out from the tests. Static mechanical testing is carried out at lower frequencies, generally less than one Hertz. The associated loads and applied deformation amplitudes are also smaller and the strain rate is much lower as compared to typical engineering applications. Dynamic loading is generally carried out under forcing functions and with high deformation amplitudes. These forcing functions and amplitudes are applied under a very short time period. When related to polymers, composites and elastomers, the information from a conventional test is usually related to quality control aspects of the materials or products, while from dynamic tests we back out data regarding the functional performance of the materials and products. ASTM D5992, D4092 and D5279are some of the dynamic mechanical testing standards. High speed tensile, compression, impact, fracture tests using Split Hopkinson Pressure bars (SHPB), Servo-Hydraulic testing machines and cyclic fatigue tests fall under the category of dynamic testing.
Polymer materials are widely used in all kinds of engineering applications because of their superior performance in vibration isolation, impact resistance, rate dependency and time dependent properties. In some traditional applications they have consistently shown better performance combining with other materials like glass fibres etc., and are now replacing metals and ceramics in such applications. The investigations of polymer properties in vibration, shock, impact and other viscoelastic phenomena is now considered critical, and understanding of dynamic mechanical behaviour of polymers becomes necessary. Static and dynamic testing of engineering materials and components becomes imperative for this purpose.
The absolute values from frequency sweep, strain sweep, temperature sweep dynamic tests are meaningful, but have little utility as isolated data points. They do become valuable data points when compared to each other or some other known variables. A tan delta or damping coefficient value of 0.4 is poor for a natural rubber or EPDM based compound, but very good in FKM materials where the structure of the compound makes it venerable to lower than optimum dynamic properties. Most uncured rubbery compounds start on the viscous side, and as we cure the compound, we shift towards the elastic side.
The importance of dynamic testing comes from the fact that performance of elastomers and elastomeric products such as engine mounts, suspension bumpers, tire materials etc., cannot be fully predicted by using only traditional methods of static testing. Polymer and elastomer tests like hardness, tensile, compression-set, low temperature brittleness, tear resistance tests, ozone resistance etc., are all essentially quality control tests and do not help us understand the performance or the durability of the material under field service conditions. An elastomer is used in all major applications as a dynamic part being able to provide vibration isolation, sealing, shock resistance, and necessary damping because of its viscoelastic nature.
As it stands today, the theory of dynamic properties can be applied judiciously to product development, performance characterization or failure analysis problems. The field of application has evolved over time with availability of highly sophisticated instruments. The problems need to be studied upfront for any time or frequency dependent loading conditions and boundary conditions acting on the components and the theory be suitably applied. Needless to say that dynamic properties have utmost importance when polymeric materials and components show heat generation, and fatigue related field failures. Dynamic characterization relates the molecular structure of the polymeric materials to the manufacturing processes and to the field performance of engineering products. Dynamic properties play an important part in comparing mechanical properties of different polymers for quality, performance prediction, failure analysis and new material qualification. Dynamic testing truly helps us to understand and predict these properties both at the material and component level.
Following are the testing modes that can be implemented in the static and dynamic testing of engineering materials and the results on can back out;
Frequency Sweep, Strain Sweep, Stress Sweep, Temperature Sweep, Fatigue Test
Stress Relaxation, Fatigue, Crack Growth
Stress ramp and Strain ramp
Test Results Data:
1) Storage or Elastic Modulus (E’) versus temperature, frequency, or % strain
2) Loss or Viscous Modulus (E”) versus temperature, frequency, or % strain
3) Damping Coefficient (Tan Delta) versus temperature, frequency, or % strain
4) Stress vs Strain properties at different strain rates.
5) Strain vs Number of Cycles for a material or component under load control fatigue.
6) Load or Stress vs Number of Cycles for a material or component under strain control fatigue.
7) Fatigue crack growth vs Number of Cycles for a material under strain controlled fatigue.
No single testing technique or methodology provides a complete picture of the material quality or component performance. It is always a combination of testing methods and techniques that have to be applied to obtain a 360 degree view of the material quality and performance.
1) Ferry, Viscoelastic Properties of Polymers, Wiley, 1980.
2) Ward et al., Introduction to Mechanical Properties of Solid Polymers, Wiley, 1993.
3) TA Instruments, Class Notes and Machine Manuals, 2006.
4) Lakes, Roderick., Viscoelastic Materials, Cambridge University Press, 2009.
5) Srinivas, K., and Pannikottu, A., Material Characterization and FEA of a Novel Compression Stress Relaxation Method to Evaluate Materials for Sealing Applications, 28th Annual Dayton-Cincinnati Aerospace Science Symposium, March 2003.
Space research and application demands stringent requirements from materials, making it imperative that they are tested rigorously, by multiple methods and techniques to fully characterize their performance and their ability to handle degradation, mechanical fatigue under extreme conditions.
AdvanSES provides full mechanical characterization of specialty polymers, rubber and in-homogeneous materials, for use in demanding atmospheric and space applications. Mechanical fatigue testing is a core area for us and we can test materials for HCF, LCF as well as elevated temperatures.
We can provide the following testing protocols for your rubbery materials;
A thermoplastic, or thermosoftening plastic, is a plastic polymer material that becomes pliable or moldable at a certain elevated temperature and solidifies upon cooling. Most thermoplastics have a high molecular weight. The polymer chains associate by intermolecular forces, which weaken rapidly with increased temperature, yielding a viscous liquid.
1) Hardness (ASTM D2240): The resistance of a plastic material to indentation. It is measured on a durometer machine. Normal specificationa is plus or minus 5 and three scales are used: Shore A for flexible, Shore C for semi rigid and Shore D for rigid. Usually a delayed reading of 10 or 15 seconds is used.
2) Tensile Strength (ASTM D638): The maximum nominal stress sustained by a test specimen being pulled from both ends, at a specific temperature and a specific rate of stretching. Specification is a minimum amount in MegaPascals, (N/mm2).
3) Elongation (ASTM D638): The amount of increased length of a material until breakage. Specification is a minimum percentage.
5) Creep and Stress Relaxation: Creep is the property of a material to expand or deform continuously over a period of time under the application of a constant force. Creep is one of the most widespread failure mechanism of thermoplastic materials.
AdvanSES has a history of completing FEA projects for customers from automotive, aerospace, biomedical and consumer durables background. All our projects are delivered using state of the art commercial FEA softwares.
We offer a complete range of Finite Element Analysis FEA consulting services for solving structural, thermal, fatigue, and fluid flow pressure problems. We work with our customers to analyze product behavior, predict service life, and understand failures. Our FEA engineers help our customers make early design choices. Our proactive approach helps our customers expedite products into the market.
Some our strengths in Finite Element Analysis (FEA) are detailed below;
Non-linear Materials: Our regular work includes characterization and implmentation of complex material models for hyperelasticity, elasto-plasticity and viscoelasticity. We can work on any kind of materials to implement them successfully in FEA models.
2) Verifications and Validations: Any kind of simulation without a strong verification and validation basis will mostly fail on expert scrutiny. We have extensive experience in verifications and validations procedures in our laboratory. We can replicate field service conditions, setup custom test rigs and characterize products under static and dynamic loads.
3) Contact-Impact: We offer implementation of full physics in contact, drops and high speed impact analysis.
The finite element method (FEM) is a numerical method
used to solve a mathematical model of a given structure or system, which are
very complex and for which analytical solution techniques are generally not
possible, the solution can be found using the finite
element method. The finite element
method can thus be said to be a variational formulation method using the principle of minimum potential
energy where the unknown quantities of interests are approximated by continuous piecewise polynomial functions. These quantities
of interest can be different according to the chosen system, as the finite
element method can be and is used in various
different fields such as structural mechanics, fluid mechanics, accoustics, electromagnetics,
etc. In the field of structural mechanics the primary field of interest is the
displacements and stresses in the system.
It is important to understand that FEM only gives an approximate solution of the prob- lem and is a numerical approach to get the real result of the variational formulation of partial differential equations. A finite element based numerical approach gives itself to a number of assumptions and uncertainties related to domain discretizations, mathematical shape functions, solution procedures, etc. The widespread use of FEM as a primary tool has led to a product engineering lifecycle where each step from ideation, design development, to product optimization is done virtually and in some cases to the absence of even prototype testing.
This fully virtual product development and analysis methodology leads to a situation where a misinterpreted approximation or error in applying a load condition may be car- ried out through out the engineering lifecycle leading to a situation where the errors get cumulative at each stage leading to disastrous results. Errors and uncertainties in the ap- plication of finite element method (FEM) can come from the following main sources, 1) Errors that come from the inherent assumptions in the Finite element theory and 2) Errors and uncertainties that get built into the system when the physics we are seeking to model get transferred to the computational model. A common list of these kind of errors and uncertainties are as mentioned below;
Errors and uncertainties from the solver.
Level of mesh refinement and the choice of element type.
Averaging and calculation of stresses and strains from the primary solution variables.
Uncertainty in recreating the geometrical domain on a computer.
Approximations and uncertainties in the loading and boundary conditions of the model.
Errors coming from chosing the right solver types for problems, e.g. Solvers for eigen value problems.
The long list of error sources and uncertainties in the procedure makes it desirable that a framework of rules and criteria are developed by the application of which we can make sure that the finite element method performs within the required parameters of accuracy, reliability and repeatability. These framework of rules serve as verification and validation procedures by which we can consistently gauge the accuracy of our models, and sources of errors and uncertainties be clearly identified and progressively improved to achieve greater accuracy in the solutions. Verifications and Validations are required in each and every development and problem solving FEA project to provide the confidence that the compu- tational model developed performs within the required parameters. The solutions provided by the model are sufficiently accurate and the model solves the intended problem it was developed for.
Verification procedure includes checking the design, the software code and also investigate if the computational model accurately represents the physical system. Validation is more of a dynamic procedure and determines if the computational simulation agrees with the physical phenomenon, it examines the difference between the numerical simulation and the experimental results. Verification provides information whether the computational model is solved correctly and accurately, while validation provides evidence regarding the extent to which the mathematical model accurately correlates to experimental tests.
In addition to complicated
discretization functions, partial differential equations repre- senting physical systema, CFD and FEA both use
complicated matrices and PDE solution algorithms to solve physical systems.
This makes it imperative to carry out verification and validation activities
separately and incrementally during the model building to ensure reliable processes. In order to
avoid spurious results and data contamination giving out false signals, it is
important that the verification process is carried out before the valida- tion
assessment. If the verification process fails the the model building process
should be discontinued further until the verification is established. If the
verification process suc- ceeds, the
validation process can be carried further for comparison with field service and
1.2 Brief History of Standards and Guidelines for Verifi- cations and Validations
Finite element analysis found widespread use with the release of NASA Structural Anal- ysis Code in its various versions and flavous. The early adopters for FEA came from the aerospace and nuclear engineering background. The first guidelines for verification and validation were issued by the American Nuclear Society in 1987 as Guidelines for the Ver- ification and Validation of Scientific and Engineering Computer Programs for the NuclearIndustry.
The first book on the subject was written by Dr. Patrick Roache in 1998 titled Verification and Validation in Computational Science and Engineering, an update of the book appeared in 2009.
In 1998 the Computational Fluid Dynamics Committee on
Standards at the American Institute of Aeronautics and Astronautics released
the first standards document Guide for
the Verification and Validation of Computational Fluid Dynamics Simulations.
The US Depeartment of Defense through Defense Modeling and Simulation Office
releaseed the DoD Modeling and
Simulation, Verification, Validation, and Accreditation Document in 2003.
The American Society of Mechanical Engineers (ASME) V
and V Standards Commit- tee released
the Guide for Verification and Validation in
Computational Solid Mechanics (ASME V and V-10-2006).
In 2008 the National Aeronautics and
Space Administration Standard for Models
and Simulations for the first time developed a set of guidelines that provided a numerical score for
verification and validation efforts.
American Society of Mechanical Engineers
V and V Standards Committee
V and V-20 in 2016 provided
an updated Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer .
1.3 Verifications and Validations :- Process and Procedures
shows a typical product design cycle in a fast-paced industrial product de- velopment group. The product interacts
with the environment in terms of applied loads,
boundary conditions and ambient atmosphere. These factors form the
inputs into the com- putational model
building process. The computational model provides us with predictions and
solutions of what would happen to the product under different service conditions.
is important to note that going from the physical
world to generating a computational model
involves an iterative process where
all the assumptions, approximations and their effects on the the quality of the computational model are iterated
upon to generate the most optimum
computational model for representing the physical world.
Figure 1.1: Variation on the Sargent Circle Showing the Verification and Validation Procedures in a Typical Fast Paced Design Group
The validation process between the
computational model and the physical world also involves an iterative process,
where experiments with values of loads and boundary con- ditions are solved and
the solution is compared to output from the physical world. The computational
model is refined based upon the feedbacks obtained during the procedure.
The circular shapes of the process
representation emphasizes that computational mod- eling and in particular
verification and validation procedures are iterative in nature and require a
continual effort to optimize them.
The blue, red and green colored
areas in Figure(1.3)
highlight the iterative validation and
verification activities in the process. The standards and industrial guidelines
clearly mention the distinctive nature of code and solution
verifications and validations at different levels.
The green highlighted region falls in the domain of the laboratory performing
the experiments, it is equally important
that the testing
laboratory understands both the process and procedure of verification and
Code verification seeks to ensure
that there are no programming mistakes or bugs and that the software
provides the accuracy
in terms of the implementation of the numerical al- gorithms or construction of the solver. Comparing
the issue of code verification and calcu- lation verification of softwares, the main point of difference is that calculation verification
Figure 1.2: Verification and Validation Process
involves quantifying the discretization error in a numerical simulation. Code verification is rather upstream in the process and is
done by comparing numerical results with analytical solutions.
Figure 1.3: Guidance for Verification and Validation as per ASME 10.1
1.4 Guidelines for Verifications and Validations
The first step is the verification of the code or software
to confirm that the software
is work- ing as it was
intended to do. The idea behind code verification is to identify and remove any
bugs that might have been generated
while implementing the numerical algorithms or
because of any programming errors. Code verification is primarily a
responsibility of the code developer and softwares like Abaqus, LS-Dyna
etc., provide example
problems man- uals, benchmark manuals to show the
verifications of the procedures and algorithms they have implemented.
Next step of calculation verification
is carried out to quantify the error in a computer simulation due to factors
like mesh discretization, improper convergence criteria, approxi- mation in material
properties and model generations. Calculation verification provides with an
estimation of the error in the solution because of the mentioned factors.
Experience has shown us that insufficient mesh discretization is the primary
culprit and largest
contributor to errors in calculation verification.
Validation processes for material models, elements, and numerical algorithms are gen- erally part of FEA and CFD software help manuals. However, when it comes to establishing the validity of the computational model that one is seeking to solve, the validation procedure has to be developed by the analyst or the engineering group.
following validation guidelines were developed at Sandia National
Labs[Oberkampf et al.] by experimentalists working on wind tunnel
programs, however these are
applicable to all problems from computational
Guideline 1: The validation experiment
should be jointly designed by the FEA group and the experimental engineers. The
experiments should ideally be designed so that the validation domain falls
inside the application domain.
Guideline 2: The designed experiment
should involve the full physics of the system, including the loading and
Guideline 3: The solutions of the
experiments and from the computational model should be totally independent of each other.
Guideline 4: The experiments and the validation process should start from the system level solution to the component level.
Guideline 5: Care should be taken that operator bias or process bias does not
contami- nate the solution or the validation process.
1.5 Verification & Validation in FEA
1.5.1 Verification Process of an FEA Model
In the case of automotive product development problems, verification of components like silent blocks and bushings, torque rod bushes, spherical bearings etc., can be carried. Fig- ure(1.4) shows the rubber-metal bonded component for which calculations have been carried out. Hill, Horton and have shown that under radial loads the stiffness of the bushing can be given by,
Figure 1.4: Geometry Dimensions of the
Figure 1.5: Geometry of the Silent Bushing
and G= Shear Modulus = 0.117e0.034xHs, Hs = Hardness of the material. Replacing the geometrical values
Krs= 8170.23N/mm, (1.3)
for a 55 durometer
natural rubber compound. The finite element model for the bushing
is shown in Figure(1.9) and the stiffness from the FEA comes to 8844.45
N/mm. The verification and validation quite often recommends that a difference of less than 10% for a
comparison of solutions is a sound basis for a converged value.
For FEA with non-linear materials
and non-linear geometrical conditions, there are
multiple steps that one has to carry out to ensure that the material
models and the boundary
conditions provide reliable solutions.
Element Test: The unit element test
as shown in in Figure(1.7)
shows a unit cube element. The material properties are input and output
stress-strain plots are compared to the inputs. This provides
a first order validation of whether the material
Figure 1.6: Deformed Shape of the Silent Bushing
properties are good enough to provide sensible
outputs. The analyst
him/her self can carry
out this validation procedure.
Experimental Characterization Test: FEA is now carried out on a characterization test such as a tension test or a compression test. This provides a checkpoint of whether the original input material data can be backed out from the FEA. This is a moderately difficult test as shown in Figure(1.8). The reasons for the difficulties are because of unquantified properties like friction and non-exact boundary conditions.
Comparison to Full Scale Experiments: In these validation steps, the parts and com- ponent products are loaded up on a testing rig and service loads and boundary con- ditions are applied. The FEA results are compared to these experiments. This step provides the most robust validation results as the procedure validates the finite ele- ment model as well as the loading state and boundary conditions. Figure(1.9) shows torque rod bushing and the validation procedure carried out in a multi-step analysis.
Experience shows that it is best to go linearly in the validation procedure from step 1 through 3, as it progressively refines one’s material model, loading, boundary conditions. Directly jumping to step 3 to complete the validation process faster adds upto more time with errors remaining unresolved, and these errors go on to have a cumulative effect on the quality of the solutions.
Figure 1.7: Unit Cube Single Element Test
Figure 1.8: FEA of Compression Test
1.5.2 Validation Process of an FEA Model
shows the experimental test setup for validation of the bushing model. Radial loading is chosen to be the primary
deformation mode and load vs. displacement results are compared. The
verification process earlier carried out established the veracity of the FEA model and the current validation analysis applies the loading in multiple Kilonewtons. Results show a close match
between the experimental and FEA results. Figures(1.10) and
Figure 1.9: Experimental Testing and Validation FEA for the Silent
show the validation setup and solutions for a tire model and engine mount. The
complexity of a tire simulation is due to the nature of the tire geometry, and
the presence of multiple rubber compounds, fabric and steel belts. This makes
it imperative to establish the
validity of the simulations.
Figure 1.10: Experimental Testing and
Validation FEA for a Tire Model
Figure 1.11: Experimental Testing and Validation FEA for a Passenger
Car Engine Mount
An attempt was made in the article
to provide information on the verification and validation
processes in computational solid mechanics.
went through the history of adoption of verification and validation processes and
their integration in computational mechanics processes and tools. Starting from
1987 when the first guidelines were issued in a specific field of application, today we are at a stage where the processes have been standardized and all major industries have found their path of adoption.
Verification and validations are now an integral part of computational mechanics processes to increase integrity and reliability of the solutions. Verification is done primarily at the software level and is aimed at evaluating whether the code has the capability to offer the correct solution to the problem, while validation establishes the accuracy of the solution. ASME, Nuclear Society and NAFEMS are trying to make the process more standardized, and purpose driven.
Uncertainty quantification has not included in this current review, the next update of this article will include steps for uncertainty quantification in the analysis.
American Nuclear Society, Guidelines for the Verification and Validation of Scientific and Engineering Computer Programs for the Nuclear Industry 1987.
Roache, P.J, American Nuclear Society, Verification and Validation in Computational Science and Engineering, Hermosa Publishing, 1998.
American Institute of Aeronautics and Astronautics, AIAA Guide for the Verification and Validation of Computational Fluid Dynamics Simulations (G-077-1998), 1998.
U.S. Department of Defense, DoD Modeling and Simulation (M-S) Verification, Validation, and Accreditation, Defense Modeling and Simulation Office, Washington DC.
Thacker, B. H., Doebling S. W., Anderson M. C., Pepin J. E., Rodrigues E. A., Concepts of Model Verification and Validation, Los Alamos National Laboratory, 2004.
Standard for Models And Simulations, National Aeronautics and Space Administration, NASA-STD-7009, 2008.
Oberkampf, W.L. and Roy, C.J., Verification and Validation in Computational Simulation, Cambridge University Press, 2009.
Austrell, P. E., Olsson, A. K. and Jonsson, M. 2001, A Method to analyse the non- Linear dynamic behaviour of rubber components using standard FE codes, Paper no 44, Conference on Fluid and Solid Mechanics.
Austrell, P. E., Modeling of Elasticity and Damping for Filled Elastomers,Lund University.