Judges’ Queries and Presenter’s Replies

  • Icon for: Qiaobing Xu

    Qiaobing Xu

    Faculty
    May 20, 2013 | 09:53 p.m.

    Excellent work, Geoffrey. what other model has been used to describe the failure of metal during stretching? how to use your model to describe the different mechanical property between hard metal e.g. tungsten, and soft metal e.g. gold?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 21, 2013 | 12:13 p.m.

    Greetings Qiaobing Xu,

    Thank you!

    My model is aimed specifically at describing the ductile failure mechanism. This mechanism is characterized by large amounts of plasticity and is common for many structural metals (e.g., aluminum and steel). However, some metals (e.g., tungsten) are more brittle and do not fail by the same mechanism, which means that my model would not describe its failure well. For the range of metals that do undergo ductile failure, my model is simply applied by changing the matrix properties and initial void volume fraction of the micro-scale model.

    There are many models used to describe the failure of metals:
    -Models that specifically tackle ductile failure include: the Brown-Embury model, the Thomason (limit load) model, and modifications to the Gurson model to account for failure (most notably the work by Nahshon and Hutchinson). The advantage to using my model instead of the aforementioned models is that my model offers a robust and complex description of failure that does not use any fitting parameters (i.e., my model makes predictions based solely on the observable microstructure).
    -Other models, such as the Mohr-Coulomb failure model, could be used for more brittle materials.

    Additionally, the entire field of fracture mechanics is devoted to these type of problems. Specifically, linear elastic fracture mechanics are commonly used for brittle materials. Non-linear fracture mechanics are more complex and are needed for applications to ductile materials.

    Let me know if you are interested in knowing more about any of the models in a more specific context,
    -Geoffrey

  • Icon for: Aparna Baskaran

    Aparna Baskaran

    Faculty
    May 21, 2013 | 11:18 a.m.

    Interesting work Geoffrey. In the model that you present here, we are looking at a macroscopic elasticity theory simulation with inclusions (voids) in the bulk material. I am wondering if you can give me a feeling for the scales at which this approach is relevant and the dominant cause for failure. Presumable at some short scale, the polycrystalline nature of the material becomes relevant and I will have to take into account disclinations and quantum effects and so forth. Also, why is the simulation “multiscale”?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 21, 2013 | 01:48 p.m.

    Hello Aparna Baskaran,

    Thanks!

    To clarify, the macroscopic model does also include an elastic-plastic material response (based on the Gurson constitutive model).

    The large scale model in general is relevant for elements on the “structural component” level. More exactly, the notched bar I show in my video and poster has dimensions in the millimeter range. Larger sizes are also relevant here. Because an underlying assumption in my macro-scale model is that many voids contribute to failure, the macro-scale model must be much larger than the void size.

    The size of the micro-scale model is on the order of 10s of microns. Yes, you are indeed correct that as we approach smaller scales other atomistic effects become important. In fact, other members of my research group have investigated this more closely. They found, through atomistic simulations, that sub-micron sized voids are resistant to growth until very high stresses or temperatures are reached.

    On the scale of my void models, however, other effects may be still be important. Because my micro-scale models are on the order of the grain size (at least for my test material), the isotropic plasticity model I use may be too simple. Other researchers have shown that anisotropic plasticity affects the growth and coalescence of voids. Therefore, we may consider the use of a plasticity model, which can better account for crystal orientation in the future.

    Finally, I use the word ‘multiscale’ to mean that I am using simulations conducted at a micro-scale to inform my simulation at the macro-scale. In essence, my model uses information from two different simulations, each of which corresponds to a different scale. This is what I meant by ‘multiscale.’

    Let me know if I can further clarify anything,
    -Geoffrey

  • May 21, 2013 | 05:33 p.m.

    Geoffrey, this is interesting work and very nice presentation. Different colors in metal correspond to a different strain, right? Do you take into account of a possible self-heating? Or other temperature effects?
    In principle, will the testing results depend on how fast do you break the metal?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 22, 2013 | 07:52 p.m.

    Hi Natalia Noginova,

    The colors in the videos of the macro-scale model (like the cover image of my video) represent damage i.e., how close an element is to failure. You’ll notice that at the beginning of loading all elements are blue (undamaged) and that just before each element fails it is red.

    We do not take into account the possibility of self heating or any other temperature effects. Our assumption is that at our slow strain rates (quasi-static) and at stresses on the order of 100MPa that temperature effects will be small.

    Finally, because the plasticity models we chose for our micro- and macro-scale models are rate independent, our results assume a quasi static loading. In order for us to match experimental results that show the rate sensitivity of failure, we could change our plasticity models to a rate dependent formulation. Inertial effects of void growth would already be included in our model because of our use of an explicit dynamic FE framework. This is an option for future refinement of the model, though we hope to better match results at quasi-static rates before we venture down that path.

    Thanks,
    -Geoffrey

  • Icon for: Qi-Huo Wei

    Qi-Huo Wei

    Faculty
    May 21, 2013 | 08:09 p.m.

    Geoffrey: nice presentation. For the FE simulations, do you assume that the elastic property of the material does not change under different loading? In addition, do defects in the materials play any role in the ductile faillure?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 22, 2013 | 12:54 p.m.

    Hello Qi-Huo Wei,

    Yes, we do assume that elastic properties of the material is independent of loading (i.e., that the material response is elastically isotropic). On the macro-scale model we base this assumption on the fact that the grain size is small compared to our elements and that the grains would be randomly oriented. On the micro-scale this assumption does not hold because the size our entire micro-scale model is about the same as the grain size (specifically for our aluminum test material). But because our test material is aluminum and the elastic anisotropy factor is relatively close to 1, the assumption is still valid. The role of anisotropic plasticity is believed to be much more important; I addressed this briefly in my response to Aparna Baskaran’s question in case you are interested.

    Defects do play a role in ductile failure. It is from micro-scale defects such as inclusions, precipitates, and even grain boundaries that voids nucleate. Larger scale defects, such as cracks, also effect ductile failure based on how they change loading (e.g., stress concentrations).

    Thank you for the questions,
    -Geoffrey

  • Icon for: Hyunjoon Kong

    Hyunjoon Kong

    Faculty
    May 21, 2013 | 10:35 p.m.

    Very nice work. What is the size of voids considered in your modeling? Can you modify your modeling to estimate effects of heterogeniety in void size on material ductility?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 22, 2013 | 01:17 p.m.

    Greetings Hyunjoon Kong,

    The voids considered in our model are on the order of 10 microns.

    I sure hope so! Because lack of material heterogeneity is the main source of error in our model, we hope to tackle this first.
    We have done tests on unit cells with different sized voids and saw that we would need to increase the size of the voids by 400% in order to match experimental results. These tests still assumed a constant void size (for each simulation) but we think it represents a rough estimate of the effect of void size.

    There are some experimental and a few computational works in the literature that lead us to believe the heterogeneous spacing of the voids is actually more important that void size effects.

    We may at some point try to model cells with multiple voids (of varying sizes) at once and see how this effects our results. But first, we would like to look more closely at void spacing effects.

    Thanks and let me know if you have any more questions,
    -Geoffrey

  • Further posting is closed as the competition has ended.

Poster Discussion

  • Icon for: Eamonn Walker

    Eamonn Walker

    Trainee
    May 20, 2013 | 11:28 a.m.

    Hi, Geoffrey.
    Great video!
    I was wondering, what is the range of sizes of microvoids that you simulate? Are you assuming at the start of your simulation that most of the dislocations and microfissures have already coalesced into large-scale features (at least, well above the scale where you have to worry about molecular effects)?
    *Are you assuming constant microvoid size/distribution throughout your macro-scale model?
    *Also, are the FE models of the periodic cells somehow coupled to the model of the notched rod you show? Or do you simulate the void cells beforehand and establish a set of criteria for determining when the elements will fail?
    *It makes sense to me that using a perfectly regular array of voids would prevent them from merging as they might in reality. Have you tried simulating a slightly larger cell with a few more randomly placed voids, to see if and how they interact with each other under different stress conditions?

    - Sorry for all the questions. I just thought it was an interesting topic, and it got me curious about your model and methods.

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 20, 2013 | 01:30 p.m.

    Thanks Eamonn!

    -The sizes of the microvoids I simulate are on the order of 10s of microns. And yes, I assume that the voids are ‘pre-existing’ in the material; this assumption is based on the fact that voids normally nucleate from inclusions/precipitates and that they nucleate early in loading. At this scale we do not have to worry about molecular effects.

    -Yes, I assume constant microvoid size/distribution in the macro-scale model.

    -The latter case. I use the micro-scale models to construct a failure criterion which relates stress state to failure.

    -I have done a few simulations on cells with 2 and 3 voids, but I have not done a systematic comparison. There are two main problems with increasing the number of voids: 1) the computations become computationally demanding, and 2) the methods needed for these larger simulations add an element of error (which grows with number of voids) to the results.

    -I’m happy to answer questions. Please let me know if there is anything else you are curious about.

  • Small_default_profile

    Asal Albayati

    Guest
    May 20, 2013 | 07:21 p.m.

    Hi Geoffrey

    I’ve never studied this area of science, so as a common person I was just wondering :

    Is it possible to make pipes that are free from voids?
    What does the metal industry today do to minimize voids?
    How do these voids grow over the years? Only by stretch or heat too?

    Thanks

    Asal

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 21, 2013 | 02:47 p.m.

    Hey Asal,

    So the first thing to understand is that the voids often initiate from particles in the material. For instance in some aluminum alloys you might add magnesium, but as you load the material, included magnesium particles can create voids (either by particle cracking or by separation from the aluminum matrix).

    The addition of these alloying particles can improve many mechanical properties of the metal (such as increasing yield stress) but may decrease its resistance to failure. So we actually have to strike a balance between the positive and negative effects of the particles. I believe my research will be useful in finding this balance.

    And yes, temperature as well as deformation will affect void growth. Creep and fatigue will contribute to void evolution as well.

    Thanks for the questions!

  • Icon for: Tie Bo Wu

    Tie Bo Wu

    Trainee
    May 20, 2013 | 07:44 p.m.

    Hi Geoffrey. I just wanted to let you know that I really enjoyed the video and I think it was very well done. You’ve won my community vote.

  • Icon for: Stephanie Luff

    Stephanie Luff

    Trainee
    May 21, 2013 | 12:18 a.m.

    You’ve done a splendid job at breaking down your research for those not in the field!

  • May 21, 2013 | 07:31 a.m.

    Great job at explaining and presenting your work.
    Question: Why are there voids? do they have to do with the intrinsic structure of the metal? have their numbers per volume unit been estimated for different metal types in their natural state? are the voids a byproduct of the manufacturing process?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 21, 2013 | 03:02 p.m.

    Hello Elizabeth,

    I believe my response to Asal’s question above will be helpful in answering some of your questions.

    In general, voids can initiate at any place in the material that is not homogeneous. The voids initiate because deformation of the material is not constant. This usually comes in the form of particle inclusions that are harder or softer than the material around them.

    Yes, their number has been investigated in several materials, but it is most often referred to by the volume fraction. Volume fractions of .5% to a 5% would be normal for many structural metals. One of the newer ways to find this information is by use of X-ray tomography, which is similar to giving a chunk of metal a CT scan.

    Thank you for the interest in the topic, and let me know if you are still curious about anything else.

  • May 21, 2013 | 07:54 p.m.

    thanks! it is very clear. Fascinating stuff to attract students and encourage them to go into materials science and related topics. Hope that you get an award!

  • Icon for: Gloria Aguirre

    Gloria Aguirre

    Trainee
    May 21, 2013 | 01:07 p.m.

    Hi Geoffrey:

    Great job with the video and poster! I really enjoyed learning about your work. It is very interesting and very well done.

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 21, 2013 | 03:04 p.m.

    Thanks everyone for the support so far!

  • Small_default_profile

    Tim Ironman

    Guest
    May 21, 2013 | 05:59 p.m.

    Geoffrey,
    Great Video! I just showed this to my best and brightest high school students. Not only did they enjoy it, but it sparked their curiosity for future studies. Thanks alot.
    Tim

  • Icon for: Carlos Dostal

    Carlos Dostal

    Trainee
    May 21, 2013 | 10:30 p.m.

    Hi Geoffrey, great video.

    I took one or two materials classes as an undergrad, and as you mention failure initiating as a crack in the center of the member and propagating outward, i am reminded of the characteristic cup-and-cone fracture surface— but i didn’t see this in your video or on your poster. Is the cup-and-cone fracture surface due to some sort of heat-induced plasticity near the outer diameter of the fracturing surface or some other phenomena? Or is it also related to voids (like less voids near the OD)?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 22, 2013 | 02:23 p.m.

    Good question Carlos,

    The traditional cup-cone fracture surface occurs for many reasons. One of which is that as the crack propagates, the stress state in the remaining material changes dramatically. This effect is specifically what my research hopes to quantify. In essence, you see two failure modes occurring: one occurring due to normal stresses (near the center) and the other due to shear stresses (on the ‘sides’ of the cup). Based on the specific material in question the amount of the material that fails due to each mode changes.

    The material that I model in my video/poster will exhibit cup cone behavior; however, due to the geometry (i.e., the notch) in the test specimen I show, it occurs only slightly very near the surface. In my research I am more concerned with the initiation of the crack, but in theory if I were to try to capture this phenomenon I could simply refine my mesh in that surface region.

  • Icon for: Carlos Dostal

    Carlos Dostal

    Trainee
    May 22, 2013 | 02:46 p.m.

    Very cool, thank you for the edification!

  • Icon for: Carlos Dostal

    Carlos Dostal

    Trainee
    May 22, 2013 | 02:50 p.m.

    Another quick materials question… are voids synonymous with dislocations? or are they a special case where a dislocation results in a gap in the solid that is greater than some threshold in volume? or are they something else altogether? haha

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 22, 2013 | 05:10 p.m.

    Voids, as I refer to them, here are regions of empty space on the order of 10 microns large.
    Dislocations, which are defects in the crystal structure, are much much smaller (approximately 100,000 times smaller). And while it is possible for many dislocations to pile up and create larger voids, it is unlikely to see that play a part on the scales I look at.

  • Icon for: Terri La Count

    Terri La Count

    Trainee
    May 23, 2013 | 09:02 a.m.

    Very interesting video and research; your capacity to explain a complicated subject is amazing! I agree with Eamonn Walker that modeling with varying size voids is probably more realistic, but understand the limitations one faces in computational modeling. Good luck!

  • Icon for: Jeffrey Bunn

    Jeffrey Bunn

    Trainee
    May 23, 2013 | 05:27 p.m.

    Geoffrey

    Great presentation. Are you or anyone else in your group working on any in-situ characterization of voids with applied load?

    Also, I know the high energy xray imaging community would love to work with you by giving you real world inputs for your model. Have you had any collaborations in that regard?

  • Icon for: Geoffrey Bomarito

    Geoffrey Bomarito

    Presenter
    May 24, 2013 | 11:10 a.m.

    No, Jeffrey, unfortunately no one in my group currently works on in-situ characterization of voids. Some of the data that I have used in setting up my model has come from published works using xray imaging; however, the published data is usually quite limited. For this reason I also believe that a collaboration with that field would be invaluable and I may start looking for collaborators in the near future.

  • Further posting is closed as the competition has ended.

Icon for: Geoffrey Bomarito

GEOFFREY BOMARITO

Presenter’s IGERT
Cornell
Years in Grad School: 3

Judges’
Choice

A Physics Based Model for the Ductile Failure of Metals

From the millions of miles of aging pipelines to the intricate workings of a wind turbine, metals are ubiquitous. Of paramount importance in both the design and upkeep of these materials is a predictive capability for their failure. An improved understanding of ductile failure will offer increases in efficiency, reliability, and applicability of metals and their alloys. The use of computational testing is quickly becoming a viable alternative to experimental testing procedures. These computational testing methods, besides being much cheaper, offer complete control of testing parameters and greater insight into the inner workings of the material. This work investigates one such computational model for the ductile failure of metals. The model is based on a multi-scale approach, which means that the microstructure of the material is modeled and subsequently related to larger scales of interest. The results illustrate the importance of specific microstructural phenomena and confirm that their incorporation into the model will greatly enhance its predictive capabilities.