Welcome

Welcome to my informational blog on modeling and simulation of reactive flows.

I am thrilled that we can offer a place where industry professionals can come to find and share information on the latest techniques and theories on this topic.

Why MVP Modeling Solutions and why this Blog:

When I worked as a sales engineer at Reaction Design, everyday I would talk to customers or potential clients looking for engineering solutions. After a few dozen of such conversations I began to see a pattern in the types of problems that engineers from companies like Toyota, GE, Tokyo Electron, Shell and many others were trying to solve. After hundreds of these conversations the pattern solidified and I was basically being asked the same question:

“I am designing a new engine / power plant / CVD process. I have some experimental data to use as input. I want to run your program with my data and have the new engine / power plant / CVD process specifications come up on the screen. Can you help?”

I wanted to help.

Having worked in both research and industry myself, I knew how hard it would be to navigate through the pool of free and commercial software only to find out that a single answer did not exist. Many engineers calling me were at the beginning of a long road of computer simulation. Some of them would drop out almost immediately, choosing to stay with well known, although much more expensive, laboratory experiments. Some would stick it out and convince their manager to purchase the software package from one of the vendors, only to find out that it did not have the capabilities they needed…

But every once in a while I would get a success story. These success stories would always involve a group that had just the right combination of a well-defined problem and a detailed software evaluation process. In those cases, many laboratory experiments were converted into computer experiments. New discoveries were made which could not have been achieved in the lab. Hundreds of man-hours and hundreds of thousands of dollars were saved.

I wondered – when it came to computer modeling – how did some organizations turn this process into a success while others did not?

So I began to carefully observe how various companies, big and small, went about:

1) defining their R&D or production problem
2) conducting a software evaluation and
3) selecting a modeling tool

I spoke with customers who succeeded in establishing computer modeling as integral part of their everyday workflow, as well as with companies who concluded that computer modeling was of no use to them. I spoke with organizations that chose software from competitor vendors as well as with companies who had large networks created mainly out of freeware and open source codes. I met with distributors in Asia and Europe and spoke with competitors at trade shows and researchers at technical conferences.

Each of those conversations brought me closer to answering a crucial question:

Exactly how does an organization implement a successful computer modeling process into their R&D and engineering operations? (Where “successful process” is defined as saving significant money and time as well as producing reliable results that could not otherwise have been achieved)

The more I listened, the more I became convinced that the major issue that reactive flow community was faced with was the lack of a central place that would offer guidance and information on variety of computer simulation options.

There are many questions that need to be answered before a successful model of a combustion process, atomic layer deposition or catalysis can be implemented.

Questions like:

- What turbulence model do I use and do I even need one?

- Where do I get the chemical-kinetic mechanism for isobutane and do I really need all of the 7,000 reaction steps that are in it?

- Which one of my researchers can I pull of an important research project for a month, so that they can learn to run open-source FlameMaster code and compare it to COSILAB and CHEMKIN software?

As well as:

- Do I really need to look into modeling just because every one else is doing it? (The answer is yes, you need to look into it, unless you want your company to be stuck in the dark ages and eventually be crushed by competition –more on this in future posts).

- Would freeware be good enough for my project or do I need to buy a license? How many license seats would I need?

And of course the ultimate question and the reason for existence of this blog:

- How do I implement a successful modeling program that would save my company money and time while improving the quality and innovation of our products?

I decided that it was time to create a central location where engineers could come to exchange ideas, ask questions and gather information that would save them money, time and the headache when it came to choosing software tools.

I created MVP Modeling Solutions, an independent company, whose goal is to provide unbiased expert-based training and information to researchers and engineers looking for guidance in matching various available software to the problems that they need to solve.

Enjoy reading and feel free to comment on any of the posts. I look forward to having you as a frequent guest to this site.

Masha Petrova
Founder and CEO of MVP Modeling Solutions

One Response to “Welcome”

  1. Lipa Roitman Says:

    Hi Masha,

    You can design most of the mechanical parts of the automobile in the computer, and when you actually build it all could fit together right away. Not so when it comes to chemistry. It is still not an exact science, and I doubt it will be in the near future. A 0.1 percent error in one of the kinetics equations will amplify to a large and unpredictable error, if that process is running concurrently or consecutively with others. This results in a chaotic behavior, which can be predictable to some extent. There is also enormous amount of variables, such as as the location of the fuel inlet in your example. The trick to designing a stable process is to have a good model and design your process with such parameters where the small error does not matter.
    All this requires experimentation.

    That’s my five cents worth.

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