The Ewey-Gooey Side of Human Simulation

By Tim
Courtesy Argonne Labs

Courtesy Argonne Labs

Yep, it had to come to this. If you’re a bit squeamish, you may want to stop reading now. But if you want to know what it takes to accurately simulate the human body and develop innovative medical treatments, then read on… at your own risk.

As I mentioned in my previous posts, bioengineers must accurately model human body tissue in order to perform realistic simulation of medical devices and treatments. So, what is human body tissue? Here’s a simple definition of biological tissue from www.dictionary.com: “An aggregate of similar cells and cell products forming a definite kind of structural material with a specific function, in a multicellular organism”.

Still with me? This blog is going to get gooey really fast.

Check out how engineers at Argonne Labs along with researchers as the University of Chicago Medical School are using Abaqus FEA to simulate the effect of cooling kidneys with ice slurry to prolong surgery procedures. Their innovative coolant enables surgeons to nearly triple the time allotted for laparoscopic procedures. Take a peak at their animation of the kidney cooling analysis here.

Courtesy University of Frankfurt

Courtesy University of Frankfurt

Who wants bedsores? Not me, nor the patients who experience prolonged periods of bed rest. Unfortunately, this painful and health-threatening problem strikes thousands of patients every year. Researchers at the University of Frankfurt are working to solve this problem by using Abaqus to analyze how patient contact with hospital beds cause internal stress and strain on human tissue. Check out their case study at Product Design and Development’s website.

Prefer some more cerebral images? Check out the analysis and visualization being peformed by bioengineers at Boston University.

Courtesy Boston University
Courtesy Boston University

They are using Abaqus to study how electrodes perform when implanted into a patient’s brain to monitor epileptic activity for surgical pre-evaluation. You can read details of their brain EEG study in this related Abaqus Tech Brief.

So, if you’re not completely grossed out by all the human tissue flying around, then do a Google search using the key words human tissue simulation with Abaqus.

Let me know if you find some good, ‘ewey-gooey’ realistic simuation examples.

Enjoy

Tim
ps – In future posts I will continue our medical journey, but for now I need some fresh air.

More VIRTUAL Better REAL Engines

By Jonathan

We hear lots of examples of how VIRTUAL simulation can save time and costs and improve quality, well…I’m going to give you another one!

I’ve been talking recently to two REAL engine manufacturers:

Manufacturer A uses virtual simulation in their engine development process (for structural limits, NVH, fatigue, dynamics, lubrification, etc.). They have a big analysis department, but strangely the engine engineers still do a vast majortiy of their simulation on physical prototypes – they just don’t have enough confidence in their virtual simulation processes. Today’s economic situation is cripling this company where teams are much smaller (contractors have been fired), budgets are even tighter BUT better products need to get out of the door faster than ever to stay competitive.

Manufacturer B also uses virtual simulation but it is much more of an integral part of their product development, EVERY engineer or designer has bought in. They are nearly at a point where they can virtually simulate the whole engine, using physical prototypes for the final sign off before going in to production. They have been able to reduce their previous 6 validation cycles, i.e. design + FEA + physical prototype, to 5 or 4 cycles. The first thing that comes to mind is “great, they’ve been able to make significant cost & time savings in removing 2 physical prototypes” and yes they have reduced costs on product development. But what’s interesting is that they have chosen to keep the overall development time as before and use the “extra” time to improve product quality and more importantly improve their ability to bring new ideas to market with greater confidence, i.e. reducing risks.

So what’s the difference between these two manufacturers? Well, to put it plainly, Manufacturer B is using Dassault Systèmes’ products and Manufacturer A isn’t!

Now that I’ve got that out of my system, let’s look closer as to why there are differences and how our software has really helped Manufacturer B.

Manufacturer B suffered from the situation below (as Manufacturer A still does). Physical testing would start without sufficient enginering maturity, i.e. new ideas would get modelled in 3D based off the experience of engineers, the parts got made and tested on dynos. Engines are very complex, the engineers can’t think of everything many problems would be found on the dyno, the next cycle would involve some heavy re-design. In other words,

Difficult to reduce program timing because a minimum of physical validations are necessary for a required quality

Now let’s have a look at the same development process but now using tools that allow engineering to be much more mature before physical prototypes are built and tested. So how do these tools provide these values?

  • Integration between disciplines is key to enable cycle times to be reduced. By greatly reducing the need for data preparation and conversion, engineers & analysts can simply get on with defining boundary condition and use cases – reducing pre-processing from weeks to days.
  • Collaboration between disciplines is obviously required and now it’s a whole lot easier when the all data is stored in the same database under the same reference numbers. This means any one can find the information associated with the parts they are interested in, and even push the data to colleagues for their review.
  • Extensive portfolio of quality simulation tools from linear, non-linear, NVH, MBD, System Engineering, fatigue. There’s no point having simulation tools if they don’t accuractely simulate real life…

Thus, integrated simulation tools can now be an integral part of the engineering process by providing early input into the feasibility of new ideas and continous validation of detailed designs right up to the moment when physical prototypes are needed for final validation. This may all happen so much quicker that the prototypes can be built earlier!

On-time engineering maturity per prototype provides the opportunity to reduce the number of total validation steps


I hope this post has given you an idea of just how simulation can and does help product development today and will be very much part of all future development.

Let me know your thought…

Sustainably yours,

Jonathan

Social Networks and Visualization

By Oleg

Despite summer relaxing time, I’m continuing to explore different dimensions of information visualization on 3D Perspectives. Social networks became a hot topic for the last few months or years and thought they can provide very interesting source of information to be presented in visual form. I decided to find a tool, I can use easy and in comfortable environment. So far, I found it…

Everybody likes Excel, right? So, let me show what is possible to visualize a social network using NodeXL (project developed by Microsoft Research). This application, so called .NetMap, can be used for viewing and analyzing of network graphs. Data can be prepared in Excel or imported from any applications. Use this link to download detailed presentation of NodeXL. You can download NodeXL code from Codeplex.

Sample images generated with NodeXL.

You can ask me, if I see any connection to word of Product Lifecycle Management? Yes, I do. The power to visualize and graphically represent information, solutions, ideas in multiple dimensions, as well as manipulate and collaborate with others is the next big revolution in technology. Since PLM is making social turn and focus on people, I think visualization of social communication together with 3D product visualization can provide very powerful turn in development efficient 3D Social Network Collaboration Tools.

Best, Oleg.



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