When running on a machine with a Linux operating system, it is not uncommon for users to want to run from the command line or with a shell script. To do this you need to know where the actual executable files are located. Based on a request from a customer, we have tried to coalesce the major ANSYS product executables that can be run via command line on Linux into a single list:
In this post, I discuss six challenges that make the modeling of 3D printed cellular structures (such as honeycombs and lattices) a non-trivial matter. In a following post, I will present how some of these problems have been addressed with different approaches.
At the outset, I need to clarify that by modeling I mean the analytical representation of material behavior, primarily for use in predictive analysis (simulation). Here are some reasons why this is a challenging endeavor for 3D printed cellular solids – some of these reasons are unique to 3D printing, others are a result of aspects that are specific to cellular solids, independent of how they are manufactured. I show examples with honeycombs since that is the majority of the work we have data for, but I expect that these ideas apply to foams and lattices as well, just with varying degrees of sensitivity.
1. Complex Geometry with Non-Uniform Local Conditions
I state the most well-appreciated challenge with cellular structures first: they are NOT fully-dense solid materials that have relatively predictable responses governed by straightforward analytical expressions. Consider a dogbone-shaped specimen of solid material under tension: it’s stress-strain response can be described fairly well using continuum expressions that do not account for geometrical features beyond the size of the dogbone (area and length for stress and strain computations respectively). However, as shown in Figure 1, such is not the case for cellular structures, where local stress and strain distributions are non-uniform. Further, they may have variable distributions of bending, stretching and shear in the connecting members that constitute the structure. So the first question becomes: how does one represent such complex geometry – both analytically and numerically?
2. Size Effects
A size effect is said to be significant when an observed behavior varies as a function of the size of the sample whose response is being characterized even after normalization (dividing force by area to get stress, for example). Here I limit myself to size effects that are purely a mathematical artifact of the cellular geometry itself, independent of the manufacturing process used to make them – in other words this effect would persist even if the material in the cellular structure was a mathematically precise, homogeneous and isotropic material.
It is common in the field of cellular structure modeling to extract an “effective” property – a property that represents a homogenized behavior without explicitly modeling the cellular detail. This is an elegant concept but introduces some practical challenges in implementation – inherent in the assumption is that this property, modulus for example, is equivalent to a continuum property valid at every material point. The reality is the extraction of this property is strongly dependent on the number of cells involved in the experimental characterization process. Consider experimental work done by us at PADT, and shown in Figure 2 below, where we varied both the number of axial and longitudinal cells (see inset for definition) when testing hexagonal honeycomb samples made of ULTEM-9085 with FDM. The predicted effective modulus increases with increasing number of cells in the axial direction, but reduces (at a lower rate) for increasing number of cells in the longitudinal direction.
This is a significant challenge and deserves a full form post to do justice (and is forthcoming), but the key to remember is that testing a particular cellular structure does not suffice in the extraction of effective properties. So the second question here becomes: what is the correct specimen design for characterizing cellular properties?
3. Contact Effects
In the compression test shown in the inset in Figure 2, there is physical contact between the platen and the specimen that creates a local effect at the top and bottom that is different from the experience of the cells closer the center. This is tied to the size effect discussed above – if you have large enough cells in the axial direction, the contribution of this effect should reduce – but I have called it out as a separate effect here for two reasons: Firstly, it raises the question of how best to design the interface for the specimen: should the top and bottom cells terminate in a flat plate, or should the cells extend to the surface of contact (the latter is the case in the above image). Secondly, it raises the question of how best to model the interface, especially if one is seeking to match simulation results to experimentally observed behavior. Both these ideas are shown in Figure 3 below. This also has implications for product design – how do we characterize and model the lattice-skin interface? As such, independent of addressing size effects, there is a need to account for contact behavior in characterization, modeling and analysis.
4. Macrostructure Effects
Another consideration related to specimen design is demonstrated in an exaggerated manner in the slowed down video below, showing a specimen flying off the platens under compression – the point being that for certain dimensions of the specimen being characterized (typically very tall aspect ratios), deformation in the macrostructure can influence what is perceived as cellular behavior. In the video below, there is some induced bending on a macro-level.
5. Dimensional Errors
While all manufacturing processes introduce some error in dimensional tolerances, the error can have a very significant effect for cellular structures – a typical industrial 3D printing process has tolerances within 75 microns (0.003″) – cellular structures (micro-lattices in particular) very often are 250-750 microns in thickness, meaning the tolerances on dimensional error can be in the 10% and higher error range for thickness of these members. This was our finding when working with Fused Deposition Modeling (FDM), where on a 0.006″ thick wall we saw about a 10% larger true measurement when we scanned the samples optically, as shown in Figure 4. Such large errors in thickness can yield a significant error in measured behavior such as elastic modulus, which often goes by some power to the thickness, amplifying the error. This drives the need for some independent measurement of the manufactured cellular structure – made challenging itself by the need to penetrate the structure for internal measurements. X-ray scanning is a popular, if expensive approach. But the modeler than has the challenge of devising an average thickness for analytical calculations and furthermore, the challenge of representation of geometry in simulation software for efficient analysis.
6. Mesostructural Effects
The layerwise nature of Additive Manufacturing introduces a set of challenges that are somewhat unique to 3D Printed parts. Chief among these is the resulting sensitivity to orientation, as shown for the laser-based powder bed fusion process in Figure 5 with standard materials and parameter sets. Overhang surfaces (unsupported) tend to have down-facing surfaces with different morphology compared to up-facing ones. In the context of cellular structures, this is likely to result in different thickness effects depending on direction measured.
For the FDM process, in addition to orientation, the toolpaths that effectively determine the internal meso-structure of the part (discussed in a previous blog post in greater detail) have a very strong influence on observed stiffness behavior, as shown in Figure 6. Thus orientation and process parameters are variables that need to be comprehended in the modeling of cellular structures – or set as constants for the range of applicability of the model parameters that are derived from a certain set of process conditions.
Modeling cellular structures has the above mentioned challenges – most have practical implications in determining what is the correct specimen design – it is our mission over the next 18 months to address some of these challenges to a satisfactory level through an America Makes grant we have been awarded. While these ideas have been explored in other manufacturing contexts, much remains to be done for the AM community, where cellular structures have a singular potential in application.
In future posts, I will discuss some of these challenges in detail and also discuss different approaches to modeling 3D printed cellular structures – they do not always address all the challenges here satisfactorily but each has its pros and cons. Until then, feel free to send us an email at email@example.com citing this blog post, or connect with me on LinkedIn so you get notified whenever I write a post on this, or similar subjects in Additive Manufacturing (1-2 times/month).
There is nothing better than seeing the powerful and interesting way that other engineers are using the same tools you use. That is why ANSYS, Inc. and PADT teamed up on Thursday to hold an “ANSYS Arizona Innovation Conference” at ASU SkySong where users could come to share and learn.
The day kicked off with Andy Bauer from ANSYS welcoming everyone and giving them an update on the company and some general overarching direction for the technology. Then Samir Rida from Honeywell Aerospace gave a fantastic keynote sharing how simulation drive the design of their turbine engines. As a former turbine engine guy, I found it fascinating and exciting to see how accurate and detailed their modeling is.
Next up was my talk on the Past, Present, and Future of simulation for product development. The point of the presentation was to take a step back and really think about what simulation is, what we have been doing, and what it needs to look at in the future. We all sort of agreed that we wanted voice activation and artificial intelligence built in now. If you are interested, you can find my presentation here: padt-ansys-innovation-az-2016.pdf.
After a short break ANSYS’s Sara Louie launched into a discussion on some of the new Antenna Systems modeling capabilities, simulating multiple physics and large domains with ANSYS products. The ability to model the entire interaction of an antenna including large environments was fascinating.
Lunchtime discussions focused on the presentations in the morning as well as people sharing what they were working on.
The afternoon started with a review by Hoang Vinh of ANSYS of the ANSYS AIM product. This was followed by customer presentations. Both Galtronics and ON Semiconductor shared how they drive the design of their RF systems with ANSYS HFSS and related tools. Then Nammo Talley shared how they incorporated simulation into their design process and then showed an example of a projectile redesign from a shoulder launched rocket that was driven by simulation in ANSYS CFX. They had the added advantage of being able to show something that blows up, always a crowd pleaser.
Another break was followed by a great look at how Ping used CFD to improve the design of one of their drivers. They used simulation to understand the drag on the head through an entire swing and then add aerodynamic features that improved the performance of the club significantly. Much of the work is actually featured in an ANSYS Advantage article.
We wrapped things up with an in depth technical look at Shock and Vibration Analysis using ANSYS Mechanical and Multiphysics PCB Analysis with the full ANSYS product suite.
The best part of the event was seeing how all the different physics in ANSYS products were being used and applied in different industries. WE hope to have similar events int he future so make sure you sign up for our mailings, the “ANSYS – Software Information & Seminars” list will keep you in the loop.
September is here and it is a jam packed month of events, many of them related to BioMedical engineering. We are continuing with ANSYS webinars and talking about 3D Printing as well. See what we have below:
September 13: Salt Lake City, UT Manufacturing Promotes Innovation Summit
The UMA Summit is a day long event filled with networking, guest speakers and informative information. In between speakers network with our vendor booths and see the latest products and services available for the Manufacturing Industry. PADT will be there with lots of example of 3D Printing and ready to engage on how manufacturing really does drive innovation. Check out the event page for times and an agenda.
September 15: Scottsdale, AZ ANSYS Arizona Innovation Conference
ANSYS and PADT are pleased to announce that we be holding a user meeting in Scottsdale for the entire ANSYS use community. Join us for an informative conference on how to incorporate various productivity enhancement tools and techniques into your workflow for your engineering department. ANSYS Applications Engineers and local customers like Honeywell, Galtronics, On Semi, Ping, and Nammo Talley, will discuss design challenges and how simulation-driven product development can help engineers rapidly innovate new products. See the agenda and register here.
September 19: Phoenix, AZ Seminar: Medical Device Product Development for Startups – The Bitter Pill
We will be kicking off our Arizona Bioscience Week with this a free seminar at CEI in Phoenix with a sometimes brutally honest discussion on the reality of medical device product development.
No one wants to discourage a good idea, and entrepreneurs make it a long way before someone sits them down and explains how long and expensive the engineering of a medical device product is. In this one hour seminar PADT will share the hard and cold realities of the process, not to discourage people, but to give them the facts they need.
September 21-22: Minneapolis, MN Medical Design & Manufacturing Minneapolis
PADT Medical will have a booth with our partner Innosurg at this premier event for medical device development. For 22 years, Medical Design & Manufacturing Minneapolis has been the medtech innovation, communication, and solution epicenter of the Midwest. Now over 600 suppliers strong, and with more than 5,000 industry professionals in attendance, the event provides the solutions, education, and partnerships you simply won’t find anywhere else. Learn more here. And if you are attending, please stop by and say hello, we are in booth 1643.
September 21: Phoenix, AZ AZBio Awards
Join PADT and others for this annual event that recognizes those that contribute to the growing AZ BioTech community. The awards will be made by PADT’s 3D Printing team again this year. Stop by our table to say hello. Register here.
September 21 & 22: Phoenix, AZ White Hat Investor Conference
The West was won by innovators, investors, and prospectors who understood the value of discovery and accepted the challenge of investing in new frontiers. PADT will be joining others in the investment community to meet with and hear from companies (32 are signed up to present right now) in the Bioscience space and to also share ideas and network. Registration for this special event can be found here.
September 30: Albuquerque, NM New Mexico Tech Council: Experience IT NM Conference
Geek out on all things technology. The New Mexico Tech community will gather the best and the brightest entrepreneurs, technicians, hackers, and tech fans for presentations, talks, meet-ups, and parties; all to highlight the vibrant tech community in our city. The Conference takes place on the final day of a week of events, and will focus on HR, CRM, Manufacturing, and Creative concerns of the tech community with panels and presentations. PADT’s Eric Miller will be presenting in two “MakeIT” sessions.
We are pleased to announce the new Flownex Training Course for Flownex SE, the world’s best (we think) thermal-fluid modeling tool. The Flownex course is aimed at new users with a desire to quickly equip themselves in the basics of system modelling as well as enabling one to visually refresh one’s memory on the various capabilities and applications within the Flownex suite.
If you are not a user already but want to check this tool out by going through the training course, go to the login page and simply click “Don’t have an account?” and register. This will get you access and we will follow up with a temp key so you can try it out. This is actually the best way for you to get a feel for why we like this program so much.
Here is a list of the sessions:
Session 1: Background to Flownex
Session 2: Page navigation
Session 3: Boundary values
Session 4: Pumps & Fixed mass flow functionality
Session 5: Flow restrictions
Session 6: Exercise 1
Session 7: Designer functionality
Session 8: Heat Exchangers
Session 9: Containers
Session 10: Exercise 2
Session 11: Excel component
Session 12: Visualization
As always, If you have any questions or want to know more, reach out to us at firstname.lastname@example.org or 1.800.293.PADT.
This is a common question that we get, particularly those coming from APDL – how to get nodal and element IDs exposed in ANSYS Mechanical. Whether that’s for troubleshooting or information gathering, it was not available before. This video shows how an ANSYS developed extension accomplishes that pretty easily.
Updated (8/30/2016): Two corrections made following suggestions by Gilbert Peters: the first corrects the use of honeycomb structures in radiator grille applications as being for flow conditioning, the second corrects the use of the Maxwell stability criterion, replacing the space frame example with an octet truss.
Within the design element, the first step in implementing cellular structures in Additive Manufacturing (AM) is selecting the appropriate unit cell(s). The unit cell is selected based on the performance desired of it as well as the manufacturability of the cells. In this post, I wish to delve deeper into the different types of cellular structures and why the classification is important. This will set the stage for defining criteria for why certain unit cell designs are preferable over others, which I will attempt in future posts. This post will also explain in greater detail what a “lattice” structure, a term that is often erroneously used to describe all cellular solids, truly is.
Honeycombs are prismatic, 2-dimensional cellular designs extruded in the 3rd dimension, like the well-known hexagonal honeycomb shown in Figure 1. All cross-sections through the 3rd dimension are thus identical, making honeycombs somewhat easy to model. Though the hexagonal honeycomb is most well known, the term applies to all designs that have this prismatic property, including square and triangular honeycombs. Honeycombs have a strong anisotropy in the 3rd dimension – in fact, the modulus of regular hexagonal and triangular honeycombs is transversely isotropic – equal in all directions in the plane but very different out-of-plane.
1.2 Design Implications The 2D nature of honeycomb structures means that their use is beneficial when the environmental conditions are predictable and the honeycomb design can be oriented in such a way to extract maximum benefit. One such example is the crash structure in Figure 2 as well as a range of sandwich panels. Several automotive radiator grilles are also of a honeycomb design to condition the flow of air. In both cases, the direction of the environmental stimulus is known – in the former, the impact load, in the latter, airflow.
2. Open-Cell Foam
Freeing up the prismatic requirement on the honeycomb brings us to a fully 3-dimensionalopen-cell foam design as shown in one representation of a unit cell in Figure 3. Typically, open-cell foams are bending-dominated, distinguishing them from stretch-dominated lattices, which are discussed in more detail in a following section on lattices.
2.2 Design Implications Unlike the honeycomb, open cell foam designs are more useful when the environmental stimulus (stress, flow, heat) is not as predictable and unidirectional. The bending dominated mechanism of deformation make open-cell foams ideal for energy absorption – stretch dominated structures tend to be stiffer. As a result of this, applications that require energy absorption such as mattresses and crumple zones in complex structures. The interconnectivity of open-cell foams also makes them a candidate for applications requiring fluid flow through the structure.
3. Closed-Cell Foam
3.1 Definition As the name suggests, closed cell foams are open-cell foams with enclosed cells, such as the representation shown in Figure 6. This typically involves a membrane like structure that may be of varying thickness from the strut-like structures, though this is not necessary. Closed-cell foams arise from a lot of natural processes and are commonly found in nature. In man-made entities, they are commonly found in the food industry (bread, chocolate) and in engineering applications where the enclosed cell is filled with some fluid (like air in bubble wrap, foam for bicycle helmets and fragile packaging).
3.2 Design Implications
The primary benefit of closed cell foams is the ability to encapsulate a fluid of different properties for compressive resilience. From a structural standpoint, while the membrane is a load-bearing part of the structure under certain loads, the additional material and manufacturing burden can be hard to justify. Within the AM context, this is a key area of interest for those exploring 3D printing food products in particular but may also have value for biomimetic applications.
Lattices are in appearance very similar to open cell foams but differ in that lattice member deformation is stretch-dominated, as opposed to bending*. This is important since for the same material allocation, structures tend to be stiffer in tension and/or compression compared to bending – by contrast, bending dominated structures typically absorb more energy and are more compliant.
So the question is – when does an open cell foam become stretch dominated and therefore, a lattice? Fortunately, there is an app equation for that.
Maxwell’s Stability Criterion
Maxwell’s stability criterion involves the computation of a metric M for a lattice-like structure with b struts and j joints as follows:
In 2D structures: M = b – 2j + 3
In 3D structures: M = b – 3j + 6
Per Maxwell’s criterion, for our purposes here where the joints are locked (and not pinned), if M < 0, we get a structure that is bending dominated. If M >= 0, the structure is stretch dominated. The former constitutes an open-cell foam, the latter a lattice.
There are several approaches to establishing the appropriateness of a lattice design for a structural applications (connectivity, static and kinematic determinism etc.) and how they are applied to periodic structures and space frames. It is easy for one (including for this author) to confuse these ideas and their applicability. For the purposes of AM, Maxwell’s Stability Criterion for 3D structures is a sufficient condition for static determinancy. Further, for a periodic structure to be truly space-filling (as we need for AM applications), there is no simple rigid polyhedron that fits the bill – we need a combination of polyhedra (such as an octahedron and tetrahedron in the octet truss shown in the video below) to generate true space filling, and rigid structures. The 2001 papers by Deshpande, Ashby and Fleck illustrate these ideas in greater detail and are referenced at the end of this post.
Video: The octet truss is a classic stretch-dominated structure, with b = 36 struts, j = 14 joints and M = 0 [Attr. Lawrence Livermore National Labs]
4.2 Design Implications Lattices are the most common cellular solid studied in AM – this is primarily on account of their strong structural performance in applications where high stiffness-to-weight ratio is desired (such as aerospace), or where stiffness modulation is important (such as in medical implants). However, it is important to realize that there are other cellular representations that have a range of other benefits that lattice designs cannot provide.
Conclusion: Why this matters
It is a fair question to ask why this matters – is this all just semantics? I would like to argue that the above classification is vital since it represents the first stage of selecting a unit cell for a particular function. Generally speaking, the following guidelines apply:
Honeycomb structures for predictable, unidirectional loading or flow
Open cell foams where energy absorption and compliance is important
Closed cell foams for fluid-filled and hydrostatic applications
Lattice structures where stiffness and resistance to bending is critical
Finally, another reason it is important to retain the bigger picture on all cellular solids is it ensures that the discussion of what we can do with AM and cellular solids includes all the possibilities and is not limited to only stiffness driven lattice designs.
Note: This blog post is part of a series on “Additive Manufacturing of Cellular Solids” that I am writing over the coming year, diving deep into the fundamentals of this exciting and fast evolving topic. To ensure you get each post (~2 a month) or to give me feedback for improvement, please connect with me on LinkedIn.
 Ashby, “Materials Selection in Mechanical Design,” Fourth Edition, 2011
 Gibson & Ashby, “Cellular Solids: Structure & Properties,” Second Edition, 1997
 Gibson, Ashby & Harley, “Cellular Materials in Nature & Medicine,” First Edition, 2010
 Ashby, Evans, Fleck, Gibson, Hutchinson, Wadley, “Metal Foams: A Design Guide,” First Edition, 2000
 Deshpande, Ashby, Fleck, “Foam Topology Bending versus Stretching Dominated Architectures,” Acta Materialia 49, 2001
 Deshpande, Fleck, Ashby, “Effective properties of the octet-truss lattice material,” Journal of the Mechanics and Physics of Solids, 49, 2001
* We defer to reference  in distinguishing lattice structures as separate from foams – this is NOT the approach used in  and  where lattices are treated implicitly as a subset of open-cell foams. The distinction is useful from a structural perspective and as such is retained here.
After three years on the market and signs that sales were increasing year over year, we decided it was time to go through our popular training book “Introduction to the ANSYS Parametric
Design Language (APDL)” and make some updates and reformat it so that it can be published as a Kindle e-book. The new Second Edition includes two additonal chapters: APDL Math and Using APDL with ANSYS Mechanical. The fact that we continue to sell more of these useful books is a sign that APDL is still a vibrant and well used language, and that others out there find power in its simplicity and depth.
This book started life as a class that PADT taught for many years. Then over time people asked if they could buy the notes. And then they asked for a real book. The bulk of the content came from Jeff Strain with input from most of our technical staff. Much of the editing and new content was done by Susanna Young and Eric Miller.
Here is the Description from Amazon.com:
The definitive guide to the ANSYS Parametric Design Language (APDL), the command language for the ANSYS Mechanical APDL product from ANSYS, Inc. PADT has converted their popular “Introduction to APDL” class into a guide so that users can teach themselves the APDL language at their own pace. Its 14 chapters include reference information, examples, tips and hints, and eight workshops. Topics covered include:
– User Interfacing
– Program Flow
– Retrieving Database Information
– Arrays, Tables, and Strings
– Importing Data
– Writing Output to Files
– Menu Customization
– APDL Math
– Using APDL in ANSYS Mechanical
At only $75.00 it is an investment that will pay for itself quickly. Even if you are an ANSYS Mechanical user, you can still benefit from knowing APDL, allowing you to add code snippets to your models. We have put some images below and you can also learn more here or go straight to Amazon.com to purchase the paperback or Kindle versions.
ANSYS Mechanical allows you to specify settings for load steps one at a time. Most users don’t know that you can change settings for any combination of load steps using the selection of the load step graph. PADT’s Joe Woodward shows you how in this short but informative video.
I am writing this post after visiting the 27th SFF Symposium, a 3-day Additive Manufacturing (AM) conference held annually at the University of Texas at Austin. The SFF Symposium stands apart from other 3D printing conferences held in the US (such as AMUG, RAPID and Inside3D) in the fact that about 90% of the attendees and presenters are from academia. This year had 339 talks in 8 concurrent tracks and 54 posters, with an estimated 470 attendees from 20 countries – an overall 50% increase over the past year.
As one would expect from a predominantly academic conference, the talks were deeper in their content and tracks were more specialized. The track I presented in (Lattice Structures) had a total of 15 talks – 300 minutes of lattice talk, which pretty much made the conference for me!
In this post, I wish to summarize the research landscape in AM cellular solids at a high level: this classification dawned on me as I was listening to the talks over two days and taking in all the different work going on across several universities. My attempt in this post is to wrap my arms around the big picture and show how all these elements are needed to make cellular solids a routine design feature in production AM parts.
Classification of Cellular Solids
First, I feel the need to clarify a technicality that bothered me a wee bit at the conference: I prefer the term “cellular solids” to “lattices” since it is more inclusive of honeycomb and all foam-like structures, following Gibson and Ashby’s 1997 seminal text of the same name. Lattices are generally associated with “open-cell foam” type structures only – but there is a lot of room for honeycomb structures and close-cell foams, each having different advantages and behaviors, which get excluded when we use the term “lattice”.
The AM Cellular Solids Research Landscape
The 15 papers at the symposium, and indeed all my prior literature reviews and conference visits, suggested to me that all of the work in this space falls into one or more of four categories shown in Figure 2. For each of the four categories (design, analysis, manufacturing & implementation), I have listed below the current list of capabilities (not comprehensive), many of which were discussed in the talks at SFF. Further down I list the current challenges from my point of view, based on what I have learned studying this area over the past year.
Over the coming weeks I plan to publish a post with more detail on each of the four areas above, summarizing the commercial and academic research that is ongoing (to the best of my knowledge) in each area. For now, I provide below a brief elaboration of each area and highlight some important research questions.
1. Representation (Design)
This deals with how we incorporate cellular structures into our designs for all downstream activities. This involves two aspects: the selection of the specific cellular design (honeycomb or octet truss, for example) and its implementation in the CAD framework. For the former, a key question is: what is the optimum unit cell to select relative to performance requirements, manufacturability and other constraints? The second set of challenges arises from the CAD implementation: how does one allow for rapid iteration with minimal computational expense, how do cellular structures cover the space and merge with the external skin geometry seamlessly?
2. Optimization (Analysis)
Having tools to incorporate cellular designs is not enough – the next question is how to arrange these structures for optimum performance relative to specified requirements? The two most significant challenges in this area are performing the analysis at reasonable computational expense and the development of material models that accurately represent behavior at the cellular structure level, which may be significantly different from the bulk.
3. Realization (Manufacturing)
Manufacturing cellular structures is non-trivial, primarily due to the small size of the connecting members (struts, walls). The dimensions required are often in the order of a few hundred microns and lower, which tends to push the capabilities of the AM equipment under consideration. Additionally, in most cases, the cellular structure needs to be self-supporting and specifically for powder bed fusion, must allow for removal of trapped powder after completion of the build. One way to address this is to develop a map that identifies acceptable sizes of both the connecting members and the pores they enclose. For this, we need robust ways of monitoring quality of AM cellular solids by using in-situ and Non-Destructive techniques to guard against voids and other defects.
4. Application (Implementation)
Cellular solids have a range of potential applications. The well established ones include increasing stiffness-to-weight ratios, energy absorption and thermal performance. More recent applications include improving bone integration for implants and modulating stiffness to match biological distributions of material (biomimicry), as well as a host of ideas involving meta-materials. The key questions here include how do we ensure long term reliability of cellular structures in their use condition? How do we accurately identify and validate these conditions? How do we monitor quality in the field? And how do we ensure the entire life cycle of the product is cost-effective?
I wrote this post for two reasons: I love to classify information and couldn’t help myself after 5 hours of hearing and thinking about this area. But secondly, I hope it helps give all of us working in this space context to engage and communicate more seamlessly and see how our own work fits in the bigger picture.
A lot of us have a singular passion for the overlapping zone of AM and cellular solids and I can imagine in a few years we may well have a conference, an online journal or a forum of some sort just dedicated to this field – in fact, I’d love to assess interest in such an effort or an equivalent collaborative exercise. If this idea resonates with you, please connect with me on LinkedIn and drop me a note, or send us an email (email@example.com) and cite this blog post so it finds its way to me.
At PADT we provide help to many of our customers who have trouble with their ANSYS simulations. At the top level, though, there are some computer skills for Windows that we consider basics that every engineer should know. If these are skills you already have in your tool belt, fantastic! If not, hopefully this information will help you be more effective in your simulation tasks.
Also, since most of us have been or are currently being updated to Windows 10, I’m providing the instructions for Windows 10. Windows 7 is similar, though.
1. Run as Administrator
This allows us to run programs, a.k.a. “apps” with administrator privilege, even if our login credentials don’t allow this level of usage. This is the case for most users of engineering software. Certain components of ANSYS, including the CAD Configuration Manager and the Client ANSLIC_ADMIN Utility require changes to your computer that non-admin rights won’t allow. By running as administrator, we allow the program to make the needed changes.
To do this, click the Start Menu, then find the program (app) you need to run in the resulting list, such as the Client ANSLIC_ADMIN Utility. Next, right click on that program, select More with the left mouse button, then select Run as Administrator with the left mouse button. If you are prompted to allow changes to your system, click Yes. Here is what it will look like:
2. View File Extensions
When using Windows Explorer, now known as File Explorer in Windows 10, by default you probably won’t see file extensions. Instead, you’ll see the prefix of files, but won’t see the endings of the file names. This will be the case when browsing for files to open or save as well. Sometimes you can rely on the icons associated with a file to know which program it’s associated with or the Type field in the list view, but sometimes there are conflicts. For example, an ANSYS Mechanical APDL macro file will have the extension .mac. You can probably guess that there is at least one other major company that can have software that uses that extension. By viewing the file extensions, even if the icons are wrong, we can more easily identify the files we need. Here is how it’s done:
Click Start, then File Explorer:
The default view using “Details” in File Explorer will look something like this (file names don’t include extensions):
To view the extensions, we click on the View menu in File Explorer, then Options, then Change Folder and Search Options.
The way I set this option for all folder on my computer is to then click on the View tab in the resulting small window, then uncheck the box for Hide extensions for known file types, then click Apply to Folders, then click OK.
Now the list view (using Details under the View menu) in File Explorer looks like this, with each file showing its extension in the list:
3. Define and Edit Environment Variables
Environment Variables are values that are used by certain programs to define settings. For example, an environment variable can be used to specify the license server for certain programs. It’s good to know how to define and edit these if needed. To do this, we bring up the control panel. In Windows 10, click on the Start button, then Settings:
A quick way to get there is to type “environment” in the search window in the resulting Settings window:
The search should find Edit the System Environment Variables. Click on that:
In the resulting System Properties window, click on the Environment Variables button in the Advanced tab:
A new window will open with a list of currently defined User variables (just for your login) and System variables (for anyone who is logged in), like this:
You can click on an environment variable to edit it using the Edit… button, or you can click on the New… button to create a new one. One ANSYS-related environment variable that occasionally needs to be set is ANSYSLMD_LICENSE_FILE. This is only needed if the default license server specifications aren’t working for some reason. You won’t need to set this under normal circumstances. Just in case, here is how to define it, using the New… button under System variables. We type in the Variable Name, in this case ANSYSLMD_LICENSE_FILE and then the Variable Value, which in this example is 1055@myserver.
When done defining and editing environment variables, we click on the OK button to complete the action and get out of that environment variable-related windows.
4. Check Usage of Your Computer Resources
As simulation experts, we are often pushing the limits of our computer resources. It’s good to know how to check those. First is disk space. An easy way to check disk space is to bring up File Explorer again. Click on This PC on the left side. This will give you a snapshot of the available space on each hard drive that is accessible on this computer:
Next, we may want to check CPU or memory utilization. Perhaps we want to make sure that our solution is running on multiple cores as we have requested.
To do this, hold down the Alt, Control, and Delete keys on the keyboard, all at the same time. Then click on Task Manager in the resulting window (it will look for a second like your computer is going to restart – it won’t actually do that).
In the resulting Task Manager window, click on More details:
In the resulting window, we can click on the Performance tab and view, for example, the current memory utilization, or we can click on Open Resource Monitor and get even more details, including utilization on each CPU:
5. Search for Large Files
It’s very common in the simulation world to end up filling up your disk drives. Therefore, it’s good to be able to find large files so we can delete them if they are no longer needed. For a simple way to do this, we’ll start with File Explorer again. This time, we’ll click in the search window at upper right, but won’t actually type in anything. We just want the search tools menu to appear:
Next, click on Search under Search Tools, followed by Size, then Gigantic (I will argue that 128 MB isn’t all that gigantic in the simulation world, but Microsoft hasn’t caught up with us yet):
Windows will now perform a search for files larger than 128 GB. If any of these are no longer needed, you can right click and delete them. Just make sure you don’t delete any files that are truly needed!
That completes our discussion on 5 computer skills every engineer should know. In conclusion, these basic skills should help you be more productive over time as you perform your simulation tasks. We hope you find this information useful.
We are pleased to announce that PADT has been awarded a grant from America Makes to further our research into combining our three favorite things: Simulation, 3D Printing, and Product Development. We will work with our partners at ASU, Honeywell Aerospace, and LAI International to study lattice structures created in 3D Printing, how to model them in ANSYS simulation software, and then how to use that information to drive product design.
A copy of the press release is below. Or read the official press release or download a PDF .
Innovative Additive Manufacturing Research Project Led by PADT Approved as Part of America Makes Multi-Million Dollar Grants
Arizona State University, Honeywell Aerospace and LAI International join PADT in technical research and educational outreach in 3D Printing
TEMPE, Ariz., July 25, 2016 — In one of the most critically needed areas of research in Additive Manufacturing, Phoenix Analysis & Design Technologies (PADT), the Southwest’s largest provider of numerical simulation, product development and 3D Printing services and products, today announced its project proposal titled “A Non-Empirical Predictive Model for Additively Manufactured Lattice Structures,” has been accepted as part of a multi-million dollar grant from the National Additive Manufacturing Innovation Institute, America Makes. PADT’s proposal was one of only seven selected, and one of only two where the leading organization was a small business.
To complete the deliverables, Arizona State University (ASU), Honeywell Aerospace and LAI International are assisting PADT in technical research with contributions from Prof. Howard Kuhn, a Professor at the University of Pittsburgh and a leading educator in Additive Manufacturing, for workforce and educational outreach.
“While there are several efforts ongoing in developing design and optimization software for lattice structures in additive manufacturing, there has been little progress in developing a robust, validated material model that accurately describes how these structures behave,” said Dhruv Bhate, PhD, senior technologist, PADT and author and principal investigator of the proposal. “We are honored to be chosen to research this important issue and provide the tools to enable entrepreneurs, manufacturers and makers to integrate lattice structures in their designs.”
One of the most definitive benefits of additive manufacturing is the ability to reduce weight while maintaining mechanical performance. A way to achieve this is by adding lattice structures to parts before manufacturing. The advantages are crucial and can result in increased design flexibility, lower material costs and significant reductions in production time for industries such as aerospace and automotive.
Another aspect of PADT’s winning proposal is the development of a first-of-a-kind online, collaborative living textbook on Additive Manufacturing that seeks to provide comprehensive, up-to-date and structured information in a field where over 50 papers are published worldwide every day. In addition, the team will develop a training class that addresses manufacturing, testing, theory and simulation as well as how they are combined together to deliver robust predictions of lattice behavior.
“We have identified Additive Manufacturing as a key lever of innovation in our company and recognize lattice structures as an important design capability to reduce mass, improve performance and reduce costs,” said Suraj Rawal, Technical Fellow, Advanced Technology Center at Lockheed Martin Space Systems Company – a leader in implementing Additive Manufacturing. “We also recognize the significance of this work in lattice behavior modeling and prediction as an important contribution to help implement the design, manufacturing, and performance validation of structures in our innovative designs.”
The award of this grant is another example of the leadership role that Arizona is playing in advancing the practical application of Additive Manufacturing, better known as 3D Printing. PADT’s leadership role in the Arizona Technology Council’s Arizona Additive Manufacturing Committee, support of basic research in the area at ASU, and involvement with educating the next generation of users underscores PADT’s contribution to this effort and furthers the company’s commitment to “Make Innovation Work.”
About Phoenix Analysis and Design Technologies
Phoenix Analysis and Design Technologies, Inc. (PADT) is an engineering product and services company that focuses on helping customers who develop physical products by providing Numerical Simulation, Product Development, and Rapid Prototyping solutions. PADT’s worldwide reputation for technical excellence and experienced staff is based on its proven record of building long term win-win partnerships with vendors and customers. Since its establishment in 1994, companies have relied on PADT because “We Make Innovation Work.” With over 80 employees, PADT services customers from its headquarters at the Arizona State University Research Park in Tempe, Arizona, and from offices in Torrance, California, Littleton, Colorado, Albuquerque, New Mexico, and Murray, Utah, as well as through staff members located around the country. More information on PADT can be found at http://www.PADTINC.com.
If you have used or are using CFD tools like ANSYS Fluent or ANSYS CFX, then you already know how much of a pain extracting the fluid volume can be from a CAD model. Whether the extraction fails because of geometry issues, or if you’ve forgotten to create capping surfaces for all your openings it can be quite frustrating when you get the “non-manifold body” error.
We’ve done it the same way for a long time – create some super solid and do a Boolean subtract or try to close everything off and try to use a cavity function to fill in the model. Both can have headache inducing issues.
CLICK HERE for a PDF that shows how ANSYS SpaceClaim uses a different approach which can make the fluid volume extraction much easier for engineers.