Category "Tips & Tricks"

A quick recap of Fluid Mechanics solutions from Dassault Systemes. It’s not a one offering anymore. With recent acquisitions of world class technology such as XFlow, PowerFlow and Exa the offerings span across a wide range of application from Navier-Stokes formulation to Lattice-Boltzmann formulation. Let’s get started:

  • FLA and FMK unite together: FLA has been an analyst role and FMK the designer role till 2018x. Starting 2019 GA, FLA will merge into FMK. That means all the functionalities of FLA will now be available in FMK. As FMK is a designer role with its own assistant panel, using CFD feature would be a much easier starting 2019 GA.

Both on cloud and on-premise options remain available. However, the basic prerequisite will be SEI that can be upgraded to SPI in case of existing customers. The bonus is that FMK role comes with enough tokes to submit an 8 core job 😊. Additional on-premise or on-cloud tokens can be used if needed.

Enhancements in Physics of Flow

  • Radiation solver available: The combination of CFD and thermal is now enhanced by adding one prominent mode of heat transfer that is radiation. The surface to surface radiation module is available in 2019xGA and surface to ambient module will be available in 2019xFD01. Emissivity and ambient temperature are the key inputs.

  • General solver enhancements: Mesh size independent convergence rate, better shock capture for high Mach flows, buoyancy dominated natural convection flow.
  • Comfort and e-cooling: Number of cabin comfort parameters for whole human body have been added for T&M as well as A&D industry. These parameters are based on ASHRAE55 specifications.

Enhancements in Meshing

  • Intelligent feature capture: In case of complicated surfaces with lots of geometry, surface mesher initially created fine mesh over the surface where fine features need to be captured. In conventional approach, the same surface mesh creates extra fine volume mesh inside the fluid domain resulting in extremely large volume mesh. The new intelligent feature capture option allows mesher to obtain coarser volume mesh using fine surface mesh.

  • Partition hex mesher: This application can be of tremendous use in FSI applications on the 3D EXPERIENCE Platform. While Hybrid Hex mesher is still considered a piece of diamond for fluid meshing applications, user may have requirement of hex meshing for the structural counterpart. As a result, hex meshing using partition approach (just like in CAE) has been introduced in the platform as well.

Enhancements in Scenarios and post processing

  • Duplicating scenarios: This feature was requested multiple times by many customers. There is often a requirement for duplicating scenarios in situations where one or more of the scenario parameter should be changed such as mesh parameter or any fluid BC while the user wish to retain previous scenario for sake of comparisons. Earlier, user had to recreate scenario from scratch. Now a duplicate option exists along with option of activating/deactivating scenario.
  • FEM Rep option: When Scenario app is launched, the UI asks the user whether to create a new FEM Rep or use an existing one.
  • Uniformity index: Additional output on scale of 0 to 1 to quantify uniformity of flow across a given section.
  • User Field Expressions: User can now create customized field expressions using standard field expressions with mathematical operators. Our Abaqus CAE buddies know it is a very useful field output capability that is now available in 3DX for fluid applications.

Enhancements in performance and stability

  • Automatic solver configuration: Let CFD engineers perform simulations rather loosing time in juggling with numbers!

The solver has been made increasingly mesh agnostic when it comes to convergence. Earlier with change in mesh, user was expected to manually change solver under relaxation factors to avoid problems of slow convergence or no convergence. Starting 2019x, these factors are updated automatically by the solver with change in mesh. Available in all incompressible steady-state flow.

  • Bad cells treatment: Let’s not penalize the whole model due to presence of only few bad elements!

In case of bad mesh that cannot be fixed, solver parameters need to me modified for the whole mesh and that too manually to obtain a converged solution. Starting 2019x, solver automatically detects such bad cells and simplifies or alter solution parameters only in those cells to obtain a solution.

Enhancements in user documentation

  • Verification guide: Verification guide has been introduced that can be accessed either from the SWYM learning center or from the HELP option of rich client install.
  • Theory guide: Provided for every feature in 3D EXPERIENCE Help starting 2019x GA. In addition to how to set up, information on underlying formulation is available as well.
  • Assistant Panel is an added advantage by default that would provide additional text information as well.

 

 

 

One of the noticeable change that has been made in 2019 solver is its capability to handle large models. SIMULIA has noticed that in recent past customers have shown increased interest in dealing with very large models with 2M degrees of freedom or more. There are multiple reasons for this requirement. First is scalability. More and more customers are interested in large system level simulations compared to part or assembly level. Second is fidelity and accuracy. Mesh size is getting finer to capture behavior at micro level instead of macro level.

When it comes to solving very large models, iterative solver has many advantages compared to direct solver such as less memory consumption, scalability and speed. A new hybrid iterative solver scheme has been introduced that offers more flexibility for choosing number of MPI ranks and number of threads per rank for a given node. These parameters can be defined in the abaqus_v6 environment file. This is equivalent to DMP+SMP allowing efficient memory management.

The iterative solver is available in 3DExperience 2018x FD05 and 2019x FD01 release. It supports many more Abaqus features compared to conventional iterative solver such as gaskets, friction, plasticity, creep, periodic boundary conditions etc.

This blog is a part of series “what’s new in SIMULIA 2019”. Please follow our blog site regularly for next blog article on this topic.

Simulations in Aerospace and Defense companies have a well-defined workflow. They have two separate teams for composites products: one for design and other for simulation. Composites ply design is primarily done by design engineers. These are the folks that determine the composites material as well as ply thicknesses and stackings in different regions of the composites part. CATIA composites design and manufacturing workbench has all sorts of tools to help designers achieve their objectives. We have discussed these workbenches in past.

However, because of FAA and other regulations in place, design has to be validated with FEA simulation and for most of the non linear workflows, Abaqus is the right solver choice. Though CATIA does provide an environment for Abaqus pre-processing, the preferred method in Aerospace industry is to use Abaqus CAE user interface. This is because of two reasons. First reason is better meshing capabilities offered by Abaqus CAE and second is tight coupling of Abaqus CAE with underlying solver. The obvious questions that arises is “how to move the ply information from CATIA to Abaqus CAE.”

The answer is composites link in collaboration with composites modeler for Abaqus CAE. The composites link exports the ply data from CATIA in form of layup file. Based on workflow, three options are possible.

  • Export only the ply data: When mesh is already in Abaqus CAE environment.
  • Export ply data with CATIA mesh: When meshing has been done in CATIA Analysis environment.
  • Export ply with external mesh file: When Abaqus input file needs to be merged with ply data.There are further options to export data either with or without taking change in orientations due to wrinkling into account as done by composites fiber modeler. Once the mesh and layup comes in Abaqus CAE environment, it is possible to explode the shell data based on ply thickness and create solid elements from shells. Abaqus CAE automatically creates section properties and assignments based on modified ply orientations. It is further possible to visualize ply orientations on each ply as well as ply stack plots on element by element bases. Once the data transfer and visualization is complete, the entire advanced analysis set up such as bird strike, fracture or delamination can be defined in Abaqus for analysis.

Computational fluid dynamics role of 3DX is the one going through tremendous enhancements compared to other roles available on the platform. In this blog article, I am going to highlight a few key enhancements with respect to the scenario modeling and the underlying solver.

Multiple reference frames

Most of CFD users are familiar with concept of moving fluid boundaries. Traditionally these problems have been solved using coupled Eularian – Lagrangian (CEL) techniques. In simple words this technique can be defined as a combination of two fluid spaces: one near the boundary in which fluid moves with the mesh and other away from the boundary in which fluid moves through the mesh. A whole new concept has been introduced in 3DX CFD to solve such problems. It is moving reference frames that can either translate or rotate with respect to a global reference frame. Either entire fluid domain or a portion of it can be assigned to this frame of reference. The governing equations are solved in this reference frame. Interfaces are created between moving and stationary frames to maintain motion continuity.

 

Compressible flows

Compressible flows become a concern when speed of flow is high. While this may not be relevant for companies designing exhaust manifolds or valves, an analyst trying to study the exterior air flow drag on a fighter jet moving at one tenth the speed of sound would feel the need of compressible air flow. The new release can simulate transonic flows up-to Mach number of 1.2.

Modeling of porous media

Are you looking to model components such as catalytic converters or air filters? Well, these products have a permeable medium that allows restrictive flow of air through it. Modeling such flows require porous media functionality that is now supported in 3DX CFD.

These along with many other enhancements are now a part of 3D experience 2018x platform. If you wish to know more, please feel free to contact us.

When it comes to Abaqus structural solver, picture is clear. There is a standard (implicit) solver as well as an explicit solver. Each of these has its own merits and demerits that we have discussed in previous blog articles. However, in CFD there appears to be only one solver. So…

Is it implicit or explicit!!

Well, if you look at the underlying parameters of the solver, it appears to be hybrid. The solver talks about inner loop and outer loop convergence. That makes user feel that solver is implicit and it requires matrix based calculations. This is true for both steady state as well as transient flows. But then when we talk about transient flow parameters, solver mentions CFL number that primarily governs the step size of transient flow. Higher CFL number results in larger step sizes but beyond a certain value of CFL, the flow may become unstable. This looks more like an explicit scheme where stability plays a role. But then, the transient flow also requires convergence that is not an explicit property. So where do we stand.

The answer is somewhat mixed. The CFD solver of Abaqus is implicit by nature. However, it does not follow all the traits of structural implicit solver. One big difference is that CFD implicit solver is not unconditionally stable. While the explicit structural solver just exits if time increment exceeds its critical value, the CFD solver continues at larger than desired CFL numbers but it may give non-realistic flow results. The other big difference is the physical quantities involved. The structural implicit solver looks at force and displacement residuals for convergence. The CFD solver looks at momentum, pressure and velocity residuals.

SIMULIA has made good efforts in 2018x release of CFD solution on the 3D Experience platform in terms of making the solver fully implicit so that it can handle large time increments. There have been other solver enhancements to improve accuracy and reduce solution time. Wish to know more about SIMULIA CFD techniques! Please get in touch.

In recent blog article on friction, I discussed about a new Abaqus functionality that allows user to define friction as surface property and Abaqus computes contact pair friction coefficients from corresponding surface friction properties. In this blog article we discuss yet another nice and recent functionality in Abaqus explicit called anisotropic friction.

The anisotropic behavior may arise from number of scenarios the most common of which is composite material that has longitudinal and transverse fiber directions. In such a scenario, the coefficient of friction between contact pair depends on the relative direction of sliding between the contact surfaces. Looking for a real-life example!!!

“The interaction of seat belt with the occupant body is an example of anisotropic friction”

he above figure shows the concept pictorially. Blue arrows indicate the direction of relative sliding. Hence these arrows are always at an angle of 180 degrees. The red lines show the direction of primary material axis. Theta is the angle between blue arrows and red lines per surface. The directional friction stress is computes as:

Both anisotropic friction as well as estimation of friction interaction from surface property are in the category of “combinatorial rules” and both are controlled by same keyword entry as follows in the .inp file.

If both the nominal friction and directional preferences are to be determined from surface property, it is not necessary to define *friction keyword.

 

In this article we are going to discuss an advanced friction modeling technique in Abaqus. It is based on combination rules that allows solver to compute effective friction interaction based on two contacting surfaces with different coefficients of friction. As an example, look at the following table:

If someone asks: “what is the coefficient of friction of steel?” There really is no answer to this question. The answer really depends on the other object with which steel interacts. The table shows two different values, one for steel-steel interaction and other with steel-teflon interaction. If the user has NXM matrix of materials interacting with each other and each cell of that matrix has a friction coefficient assigned to it, then modeling in Abaqus is trivial. Define surface interaction with friction coefficient for each cell and use it with corresponding surface pair in the contact property assignment. The example below highlights it.

 

But this straightforward approach is possible only if friction values for all cells are available. However, at times only the diagonal values are available. That means all the non-diagonal cell values are unknown. In that case contact property assignment is not possible.

Abaqus now allows users to define friction as surface property as well. For two different surfaces (A,B) with individual coefficient of friction, the effective friction for pair is computed as follows:

The default value of alpha is 0.3. In case of mixed problems, where surface property and contact property methods co-exist, either method can take precedence. Look at following example.

The approach is an approximation but its worth in situations where user has no access to friction coefficients values for all the contact material pairs. This friction algorithm is available in Abaqus explicit 2018 release and beyond.

 

This topic has always been very popular and this problem has always been very complicated in FEA user community since the inception of Abaqus, or any non-linear FEA code in general. In this brief article, I will highlight few simulation situations where Abaqus standard may not be a good candidate from convergence perspective. Identifying these situations early during pre-processing and working in Explicit right away may save lots of time and efforts that otherwise would be wasted in trying Abaqus Standard.

  • Look at the motion aspect: We always say that simulation is not the complete replacement of physical testing right away. In the beginning physical tests play a critical role in identifying right approach for simulation as well as in data correlation between physical and virtual tests. Look closely at the physical test. Is there a large relative motion between different parts involved? If yes, then Standard is very likely to face convergence problems, even if problem is static by nature. Standard has an option of “small sliding” and “finite sliding”. But user should remember the difference between “finite sliding” and “large sliding”. Attached is the video of wire crimping simulation that ideally is a static problem but numerically not a good candidate for Standard, primarily because of motion.
  • Clock time matters: Apart from magnitude of motion, the duration of motion matters as well. While looking at physical test, closely look at the time in which motion is completed. If too much of motion is covered in too less time, problem is indeed dynamic instead of static as inertia effects cannot be ignored. In such a situation either Standard dynamics or Explicit would be the right way to go. Which one to choose really depends on event duration. If a lot of dynamic phenomenon happens in the order of milliseconds or microseconds, Explicit is only option for this candidate.
  • Is there a severe discontinuous contact: In the status file of Abaqus Standard, there is an undesirable column called SDI’s. It’s called severe discontinuous iterations and too many of these often always leads to convergence nightmare. The reason of SDI’s is discontinuous contact, also known as “chattering”. It’s a phenomenon in which nodes between two bodies in contact continuously change their contact status from OPEN to CLOSE from one iteration to the other as analysis proceeds. If chattering occurs due to modeling errors, it can be corrected but at times discontinuous contact is the nature of problem itself. In such a situation, explicit is the only approach to be taken, even for long duration events with respect to physical time. The attached video is an example of a dynamic event that would only solve in explicit or multi body dynamics, primarily because of severe discontinuous contact.
  • Is there too much Plasticity: Abaqus has material models to capture plasticity but there is a limit on the magnitude of Plasticity Abaqus Standard can handle. If the permanent deformation becomes so high that underlying part completely loses its load carrying capacity then Newton Raphson method of Abaqus Standard would not be able to establish equilibrium and further leading to non-convergence. Ideally, there is no further need to perform simulation as it’s a classic situation of part failure but if further simulation is needed, it should be continued in Explicit using Restart options.

In previous blog articles on 3D Experience simulation roles, we primarily discussed platform configurations, concept of personas and roles as well as simulation capacity of the platform. In this blog article contains detailed information about three primary structural simulation roles: MDS, DRD and SMU.

To begin with, lets recapitulate that simulation roles are categorized in groups based on personas of users working on such roles. In terms of complexity and functionality, offerings range from based to intermediate to advanced.

 

Engineer profile: The is the simplest and easiest to use simulation offering primarily meant for designers with low to intermediate simulation knowledge. Their primary job is product design and they perform simulations very occasionally. Roles for this profile are CAD centric and are associated with a guided workflow. Simulation tokens are embedded in the role.

Analysis engineer profile: This profile is one level above the engineer profile and is suitable for structural analysis engineers associated with product engineering. Their simulation knowledge is of intermediate level which means they understand simulation process in terms of meshing, BC, Loads, result visualization etc. but don’t have any hands-on experience of advanced simulation tools. Usually there is no guided workflow. Simulation tokens are embedded in the role.

Analyst profile: This role is for full time analysts who primarily perform intermediate to advanced level simulations. They have in depth expertise in at-least one simulation domain and often hold Masters or Doctorate level credentials. This role requires extensive knowledge of pre-processing, solver terminologies such as statics, dynamics, non-linearity, convergence schemes, as well as post processing etc. There is no guided workflow. Simulation tokens are procured separately.

 Research Specialist profile: This is a complex simulation offering primarily for experts who develop novel simulation workflows and processes. The simulation requirements often span across multiple physical domains and involves advanced Physics such as vibrations and noise. The pre-processing aspect may include complex meshing of assemblies and assemblies of meshes.

Let’s look at one role from each of first three profiles:

Stress Engineer role (MDS)

 

It’s a role from engineer profile and has a guided workflow. The snapshot shows apps available in MDS role. It performs routine strength and deflection calculations under static loading conditions. It can also compute product fatigue life for very simple loads. The CATIA and SOLIDWORKS associativity is well maintained. Local solver execution up to 4 cores is included.

Structural analysis Engineer role (DRD)

 

It’s a role from analysis engineer profile that has no guided workflow. It is used to access the structural integrity of products subjected to wide range of loading conditions. The snapshot above shows available apps in this role. It works on MSR concept available in advanced simulation tools i.e.  Model-Scenario-Results. Many advanced settings are exposed to the user. This role can perform multi step simulations. Local job execution of up to 8 cores is available.

Mechanical Analyst role (SMU)

 

It’s a role from analyst profile and it does not include a guided workflow. The snapshot above shows available apps in this role.  It uses advanced finite element techniques to simulate and validate complex engineering problems. It offers multiple advanced meshing techniques such as Octree, surface, sweep and RBM. Both single step as well as multi step scenarios are included. Supported analysis steps include static perturbation, non-linear static, frequency, buckling, implicit dynamics, explicit dynamics, steady state heat transfer, transient heat transfer etc. Most of the non-linear materials and complex engineering connections are included.

While we discussed one prominent role from each profile, the south quadrant of 3D Experience platform offers numerous simulation roles. To know more, please contact us.

Organizations invest huge sums of money in simulation software to avoid expensive and disruptive physical testing processes. But how long it really takes to make this transformation happen! One thing is sure; it does not happen in a day. The flow chart below explains the reason pictorially. The last two blocks “compare and improve model” and “compare and improve theory” make this transformation a longer process than expected.

 

Let’s explore the reasons behind it. Comparison is needed to make sure that simulation results mimic the physical testing results before latter can be discarded, partially or fully. The difference in results can be due to three main factors: lack of user competency, limitation of software used, lack of sufficient input data.

Lack of user competency: FEA analysts are not born in a day. The subject is complex to learn and so are the software associated with it. The ramp up time really depends on analyst background along with complexity of problem being simulated. Organizations usually make a choice between hiring expert and expensive analysts who can deliver the results right away or producing analysts of its own through class room and hands on trainings. First option saves time while the second saves money. CAE software development companies are also making big stories these days by introducing CAD embedded simulation tools that require nominal user competency. Nevertheless, the competency builds up over time.

Limitation of software used: Initial investment in simulation domain is usually small. It means two things: either number of users are less or software functionality is limited. With time, complexity of problems goes up but the software remains the same. A common example I have seen is of a customer starting with simple linear simulation workbench in CATIA and over period trying to simulate finite sliding contact problems with frictional interfaces in the same workbench. Users don’t realize that their problem complexity has exceeded the software capacity to handle and it’s time to upgrade. It’s always recommended that analysts get in touch with their software vendors whenever they anticipate an increase in simulation software capacity or functionality. A certified simulation software vendor is a trusted advisor who can really help.

Lack of sufficient input data: “Garbage in – Garbage out” is a very common phrase in simulation world. However, at times it is very difficult to get the right input for software in use. The complexity of input data can arise either from complex material behavior or from complex loading conditions. Example of complex material may be hyper-elasticity or visco-elasticity observed in elastomeric materials. Examples of complex loading may be real time multi block road load data to estimate fatigue life. Sometimes simple metallic structures exhibit complex behavior due to complex loading. Examples are high speed impact or creep loading. With time many material testing labs have come into existence that can perform in house testing to provide right input data for simulation.

Conclusion: You will come out of the vicious loop of physical and simulation results comparison after couple of iterations if you have three things in place: right people, right software product and right input data. If you need help in any of the three aspects, we are always available.

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