Advanced ANSYS Functionality

Just like any other marketplace, there are a lot of options in simulation software.  There are custom niche-codes for casting simulations to completely general purpose linear algebra solvers that allow you to write your own shape functions.  Just like with most things in life, you truly get what you pay for.

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For basic structural and thermal simulations pretty much any FE-package should suffice.  The difference there will be in how easy it is to pre/post process the work and the support you receive from the vendor.  How complicated is the geometry to mesh, how long does it take to solve, if you can utilize multiple cores how well does it scale, how easy is it to get reactions at interfaces/constraints…and so on.  I could make this an article about all the productivity enhancements available within ANSYS, but instead I’ll talk about some of the more advanced functionalities that differentiate ANSYS from other software out there.

  • Radiation

You can typically ignore radiation if there isn’t a big temperature gradient between surfaces (or ambient) and just model your system as conduction/convection cooled.  Once that delta is large enough to require radiation to be modeled there are several degrees of numerical difficulty that need to be handled by the solver.

First, radiating to ambient is fairly basic but the heat transfer is now a function of T^4.  The solver can also be sensitive to initial conditions since large DT results in a large heat transfer, which can then result in a large change in temperature from iteration to iteration.  It’s helpful to be able to run the model transiently or as a quasi-static to allow the solver to allow some flexibility.

Next, once you introduce surface to surface radiation you now have to calculate view factors prior to starting the thermal solution. If you have multiple enclosures (surfaces that can’t see each other, or enclosed regions) hopefully there are some processes to simplify the view factor calculations (not wasting time calculating a ‘0’ for elements that can’t radiate to each other).  The view factors can sometimes be sensitive to the mesh density, so being able to scale/modify those view factors can be extremely beneficial.

Lastly you run into the emissivity side of things.  Is the emissivity factor a function of temperature?  A function of wavelength?  Do you need to account for absorption in the radiation domain?

Luckily ANSYS does all of this.  ANSYS Mechanical allows you to easily define radiation to ambient or surface-to-surface.  If you’re using symmetry in your model the full radiating surface will be captured automatically.  You can define as many enclosures as possible, each with different emissivity factors (or emissivity vs Temperature).  There are more advanced features that can help with calculating view factors (simplify the radiating surface representation, use more ray traces, etc) and there is functionality to save the calculated view factors for later simulations.  ANSYS fluid products (CFX and Fluent) can also account for radiation and have the ability to capture frequency-based emissivity and participating media.


Automatic expansion of radiating surfaces across symmetry planes


Different enclosures to simplify view factor calculations

Long story short…you don’t have to know what the Stefan-Boltzman constant is if you want to include radiation in your model (bonus points if you do).  You don’t have to mess with a lot of settings to get your model to run.  Just insert radiation, select the surface, and run.  Additional options and technical support is there if necessary.

  • Multiple/Multi-physics

I’d expect that any structural/thermal/fluids/magnetics code should be able to solve the basic fundamental equations for the environment it simulates.  However, what happens when you need to combine physics, like a MEMs device.  Or maybe you want to take some guess-work/assumptions out of how one physics loads another, like what the actual pressure load is from a CFD simulation on a structural model.  Or maybe you want to capture the acoustic behavior of an electric motor, accounting for structural prestress/loads such as Joule heating and magnetic forces.


ANSYS allows you to couple multiple physics together, either using a single model or through data mapping between different meshes.  Many of the data mapping routines allow for bi-directional data passing so the results can converge.  So you can run an magnetic simulation on the holding force between a magnet and a plate, then capture the deflected shape due to an external load, and pass that deformed shape back to the magnetic simulation to capture the updated force (and repeat until converged).


If you have vendor-supplied data, or are using another tool to calculate some other results you can read in point cloud data and apply it to your model with minimal effort.


To make another long story short…you can remove assumptions and uncertainty by using ANSYS functionality.

  • Advanced Material Models


Any simulation tool should be able to handle simple linear material models.  But there are many different flavors of ‘nonlinear’ simulation.  Does the stiffness change due to deflection/motion (like a fishing rod)?  Are you working with ductile metals that experience plastic deformation?  Does the stiffness change due to parts coming into/out-of contact?  Are surfaces connected through some adhesive property that debonds under high loads?  Are you working with elastomers that utilize some polynomial form hyper-elasic formulation?  Are you working with shape memory alloys?  Are you trying to simulate porous media through some geomechanical model?  Are you trying to simulate a stochastic material variation failure in an impact/explosive simulation?


Large deflection stiffness calculations, plasticity, and contact status changes are easy in ANSYS.  Debonding has been available since ANSYS 11 (reminder, we’re at release 18.0 now).  ANSYS recently integrated some more advanced geomechanical models for dam/reservoir/etc simulations.  The explicit solver allows you to introduce stochastic variation in material strengths for impact/explosive simulations.


ANSYS also has all the major flavors of hyper-elastic material models.  You can choose from basic Neo-Hookean, Arruda-Boyce, Gent, all the way through multiple variations of Mooney-Rivlin, Yeoh, Ogden, and more.  In addition to having these material models available (and the curve fitting routines to properly extract the constants from test data) ANSYS also has the ability to dynamically remesh a model.  Most of the time when you’re analyzing the behavior of a hyperelastic part there is a lot of deformation, and what starts out as a well-shaped mesh can quickly turn into a bad mesh.  Using adaptive meshing, you can have the solve automatically pause the solution, remesh the deformed shape, map the previous stress state onto the new nodes/elements, and continue with the solution.  I should note that this nonlinear adaptive remesh is NOT just limited to hyperelastic simulations…it is just extremely helpful in these instances.

The ending of this story is pretty much the same as others.  If you have a complicated material response that you’re trying to capture you can model it in ANSYS.  If you already know how to characterize your material, just find the material model and enter the constants.  We’ve worked with several customers in getting their material tested and properly characterized.  So while most structural codes can do basic linear-elastic, and maybe some plastic…very few can capture all the material responses that ANSYS can.

  • MEMs/Piezo/Etc

I know I’ve already discussed multiple physics and advanced materials, but once you start making parts smaller you start to get coupling between physics that may not work well for vector-based coupling (passing load vectors/deformations from one mesh to another).  Luckily ANSYS has a range of multi-physics elements that can solve use either weak or strong coupling to solve a host of piezo or MEM-related problems (static, transient, modal, harmonic).  Some codes allow for this kind of coupling but either require you to write your own governing equations or pay for a bunch of modules to access.

If you have the ANSYS Enterprise-level license you can download a free extension that exposes all of these properties in the Mechanical GUI.  No scripting, no compiling, just straight-up menu clicks.


Using this extension you can define the full complex piezoelectric matrix, couple it with an anisotropic elasticity matrix, and use frequency dependent losses to capture the actual response of your structure.  Or if you want you can use simplified material definitions to get the best approximation possible (especially if you’re lacking a full material definition from your supplier).


Long story short…there are a lot of simulation products out there.  Pretty much any of them should be able to handle the basics (single part, structural/thermal, etc).  What differentiates the tools is in how easy it helps you implement more real-world conditions/physics into your analysis.  Software can be expensive, and it’s important that you don’t paint yourself into a corner by using a single point-solution or low-end tool.

On the Functions of Cellular Structures in Nature

WHY did nature evolve cellular structures?

In a previous post, I laid out a structural classification of cellular structures in nature, proposing that they fall into 6 categories. I argued that it is not always apparent to a designer what the best unit cell choice for a given application is. While most mechanical engineers have a feel for what structure to use for high stiffness or energy absorption, we cannot easily address multi-objective problems or apply these to complex geometries with spatially varying requirements (and therefore locally optimum cellular designs). However, nature is full of examples where cellular structures possess multi-objective functionality: bone is one such well-known example. To be able to assign structure to a specific function requires us to connect the two, and to do that, we must identify all the functions in play. In this post, I attempt to do just that and develop a classification of the functions of cellular structures.

Any discussion of structure in nature has to contend with a range of drivers and constraints that are typically not part of an engineer’s concern. In my discussions with biologists (including my biochemist wife), I quickly run into justified skepticism about whether generalized models associating structure and function can address the diversity and nuance in nature – and I (tend to) agree. However, my attempt here is not to be biologically accurate – it is merely to construct something that is useful and relevant enough for an engineer to use in design. But we must begin with a few caveats to ensure our assessments consider the correct biological context.

1. Uniquely Biological Considerations

Before I attempt to propose a structure-function model, there are some legitimate concerns many have made in the literature that I wish to recap in the context of cellular structures. Three of these in particular are relevant to this discussion and I list them below.

1.1 Design for Growth

Engineers are familiar with “design for manufacturing” where design considers not just the final product but also aspects of its manufacturing, which often place constraints on said design. Nature’s “manufacturing” method involves (at the global level of structure), highly complex growth – these natural growth mechanisms have no parallel in most manufacturing processes. Take for example the flower stalk in Fig 1, which is from a Yucca tree that I found in a parking lot in Arizona.

Figure 1. The flower stalk (before bloom) of a Yucca plant in Arizona with overlapping surface cellular structure (Author’s image)

At first glance, this looks like a good example of overlapping surfaces, one of the 6 categories of cellular structures I covered before. But when you pause for a moment and query the function of this packing of cells (WHY this shape, size, packing?), you realize there is a powerful growth motive for this design. A few weeks later when I returned to the parking lot, I found many of the Yucca stems simultaneously in various stages of bloom – and captured them in a collage shown in Fig 2. This is a staggering level of structural complexity, including integration with the environment (sunlight, temperature, pollinators) that is both wondrous and for an engineer, very humbling.

Figure 2. From flower stalk to seed pods, with some help from pollinators. Form in nature is often driven by demands of growth. (Author’s images)

The lesson here is to recognize growth as a strong driver in every natural structure – the tricky part is determining when the design is constrained by growth as the primary force and when can growth be treated as incidental to achieving an optimum functional objective.

1.2 Multi-functionality

Even setting aside the growth driver mentioned previously, structure in nature is often serving multiple functions at once – and this is true of cellular structures as well. Consider the tessellation of “scutes” on the alligator. If you were tasked with designing armor for a structure, you may be tempted to mimic the alligator skin as shown in Fig. 3.

Figure 3. The cellular scutes on the alligator serve more than just one function: thermal regulation, bio-protection, mobility, fluid loss mitigation are some of the multiple underlying objectives that have been proposed (CCO public domain, Attr. Republica)

As you begin to study the skin, you see it is comprised of multiple scutes that have varying shape, size and cross-sections – see Fig 4 for a close-up.

Figure 4. Close-up of alligator scutes (Attr: Hans Hillewaert, Flickr, Creative Commons)

The pattern varies spatially, but you notice some trends: there exists a pattern on the top but it is different from the sides and the bottom (not pictured here). The only way to make sense of this variation is to ask what functions do these scutes serve? Luckily for us, biologists have given this a great deal of thought and it turns out there are several: bio-protection, thermoregulation, fluid loss mitigation and unrestricted mobility are some of the functions discussed in the literature [1, 2]. So whereas you were initially concerned only with protection (armor), the alligator seeks to accomplish much more – this means the designer either needs to de-confound the various functional aspects spatially and/or expand the search to other examples of natural armor to develop a common principle that emerges independent of multi-functionality specific to each species.

1.3 Sub-Optimal Design

This is an aspect for which I have not found an example in the field of cellular structures (yet), so I will borrow a well-known (and somewhat controversial) example [3] to make this point, and that has to do with the giraffe’s Recurrent Laryngeal Nerve (RLN), which connects the Vagus Nerve to the larynx as shown in Figure 5, which it is argued, takes an unnecessarily long circuitous route to connect these two points.

Figure 5. Observe how the RLN in the giraffe emerges from the Vagus Nerve far away from the thorax: a sub-optimal design that was likely carried along through the generations in aid of prioritizing neck growth (Attr: Vladimir V. Medeyko)

We know that from a design standpoint, this is sub-optimal because we have an axiom that states the shortest distance between two points is a straight line. And therefore, the long detour the RLN makes in the giraffe’s neck must have some other evolutionary and/or developmental basis (fish do not have this detour) [3]. However, in the case of other entities such as the cellular structures we are focusing on, the complexity of the underlying design principles makes it hard to identify cases where nature has found a sub-optimal design space for the function of interest to us, in favor of other pressing needs determined by selection. What is sufficient for the present moment is to appreciate that such cases may exist and to bear them in mind when studying structure in nature.

2. Classifying Functions

Given the above challenges, the engineer may well ask: why even consider natural form in making determinations involving the design of engineering structures? The biomimic responds by reminding us that nature has had 3.8 billion years to develop a “design guide” and we would be wise to learn from it. Importantly, natural and engineering structures both exist in the same environment and are subject to identical physics and further, are both often tasked with performing similar functions. In the context of cellular structures, we may thus ask: what are the functions of interest to engineers and designers that nature has addressed through cellular design? Through my reading [1-4], I have compiled the classification of functions in Figure 6, though this is likely to grow over time.

Figure 6. A proposed classification of functions of cellular structures in nature (subject to constant change!)

This broad classification into structural and transport may seem a little contrived, but it emerges from an analyst’s view of the world. There are two reasons why I propose this separation:

  1. Structural functions involve the spatial allocation of materials in the construction of the cellular structures, while transport functions involve the structure AND some other entity and their interactions (fluid or light for example) – thus additional physics needs to be comprehended for transport functions
  2. Secondly, structural performance needs to be comprehended independent of any transport function: a cellular structure must retain its integrity over the intended lifetime in addition to performing any additional function

Each of these functions is a fascinating case study in its own right and I highly recommend the site [1] as a way to learn more on a specific application, but this is beyond the scope of the current post. More relevant to our high-level discussion is that having listed the various reasons WHY cellular structures are found in nature, the next question is can we connect the structures described in the previous post to the functions tabulated above? This will be the attempt of my next post. Until then, as always, I welcome all inputs and comments, which you can send by messaging me on LinkedIn.

Thank you for reading!


  2. Foy (1983), The grand design: Form and colour in animals, Prentice-Hall, 1st edition
  3. Dawkins (2010), The greatest show on earth: the evidence for evolution, Free Press, Reprint of 1st edition
  4. Gibson, Ashby, Harley (2010), Cellular Materials in Nature and Medicine, Cambridge University Press; 1st edition
  5. Ashby, Evans, Fleck, Gibson, Hutchinson, Wadley (2000), Metal Foams: A Design Guide, Butterworth-Heinemann, 1st edition