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This week, guest Richard Kehn, Principal Engineer Mixing Technology at SPX Flow, joins John to talk about his experience as an engineer, large scale CFD workflow, and advice for engineers just starting out.
“Mixing is quantitative. There are things you can calculate . . . but there’s also a flow pattern occurring. You got to make sure whatever you’re modeling, you’re getting that right.
Seeing lots of tanks mix both in plants, in a laboratory set up at multiple scales—it really grounds you to make sure that whatever you’re doing on paper makes sense.”
– Rich Kehn
In this episode, John and Rich discuss:
- Rich’s career trajectory
- SPX Flow’s CFD workflow and orders of magnitude range of fluid flow volume
- Advice for CFD and other engineers just graduating college
John Thomas: Hi, everybody. Thanks for joining the podcast today. Today we have the privilege of speaking to Rich Kehn, a principal engineer of mixing technology at SPX Flow. Rich, thanks so much for being here.
Rich Kehn: No problem. Thanks for having me on.
John Thomas: So Rich, how does one become a principal engineer of mixing technology at SPX Flow? How did you get to today based on whatever origin point you chose to start at?
Rich Kehn: So like, my career started as an application engineer where, you know, I was working with clients and, you know, mixing problems and whatnot. Process design is a fair amount of mechanical design knowledge that makes you a good application engineer because you’re obviously dealing with a mechanical piece of equipment.
So knowing kind of both aspects, I think, is important. And then, you know, I kind of moved into the research and development area, did a lot of experimentation. And at the time, you know, it was asked, you know, can you learn CFD? I went back to get my Master’s degree, took me a number of years doing this part time, but I learned CFD, you know, concentration CFD, where I went back for my Master’s, and it kind of all went into this space here where you kind of now are marrying together, you know, an application side where the research and development kind of put all this together, and you bring simulation into, you know, experimentation and then, you really can help clients out on mixing problems by looking at it from a lot of different aspects, basically. So for me, it’s a, you know, I’m in my 18th year of doing fluid mixing. So a long time doing a lot of different things, you know, in the area.
John Thomas: And so tell me when you got started. I mean, are you going to client sites? Are you diagnosing problems? Are you flying around the country, going to different locations, understand their needs as an application engineer? Or is it, are you more staying at home base, getting data from the field? Or what’s it like as an application engineer early on in your career?
Rich Kehn: So, you know, I’ve been in SPX Flow for the longest about my career, but I did work for two other companies as an application engineer. So for all the companies that I’ve worked for, a common theme is that a mixture of obviously doing the work in the office and working with clients over the phone, but really going to sites, seeing installations. What are your problems and whatnot? I’ve done that at all throughout my whole career, basically as an application engineer. And that is really where you take that aspect of seeing things in real life, being able to talk to operators of the plans, being able to talk to process engineers, being able to talk to maintenance personnel. You bring all that together with the work that you do back to the office and then in applications, it’s really kind of like that person that’s going to help you apply the knowledge to solve the problem or whatever product that you’re obviously an application engineer for.
John Thomas: Yeah. And that’s what’s always struck me about you, so I kind of ask that probing question. You always seem to bring things back to the physical equipment, right? The actual installation and whatnot. And it just seems to me that, you know, one of the keys to becoming a good CFD engineer is a strong ground in physical reality. Right? Having seen the equipment operate, having seen the process happen or whatnot, that it sounds like that’s been kind of a thread through your career as well, going to sites, watching the process and then whether they’re CFD or not, that kind of reaching out and touching the equipment has a pretty immeasurable benefit in terms of understanding the process going on inside it.
Rich Kehn: It does. I think, you know, there was a presentation I did at an AIChE conference in 2015 where I remember you specifically were struck when I said, you know, “the first thing I do in a CFD of anything you’re modeling is, have you seen this piece of equipment? Have you actually looked inside a mix tank? Have you seen a pump?” I think it’s really key to be able to understand, you know, what you’re modeling to that level. So for someone like me who’s been doing CFD now for twelve years, if somebody asked me to model a centrifugal pump, I honestly would be somewhat, let’s say, apprehensive of doing the model myself and just assuming it’s correct because I have never really looked or done a lot of work with pumps. I’ve got looks inside of pumps. I would actually question whether I’m actually qualified to do that right on my own without a fair amount of validation. But yeah, that visual seeing is believing. Like I said, mixing is quantitative. There are things you can calculate like, you know, just suspended speed, the gas handling of an impeller, KLA for mass transfer coefficient. But there’s also a flow pattern occurring. You got to make sure whatever you’re modeling, you’re getting that right. And so being grounded in seeing all this and seeing lots of tanks mix both in plants, in a laboratory set up at multiple scales, it really grounds you to make sure that whatever you’re doing on paper makes sense.
John Thomas: Yeah, and I’ve always kind of distilled this as, don’t run simulations in a vacuum. What I mean by that is like, get to the plant, right? You see it, as it were. There are so many subtle things that you see in an actual process that you realize may strongly inform so many things in your model that you realize have no bearing on the process outcomes because, quite frankly, it might not be relevant to the actual physical process.
Rich Kehn: What’s interesting is, so like working on a new application or whatnot, one of the first things I’ll even start with has nothing to do with fluid mechanics or anything. It’s OK, what’s the size of the hole that we got to get the impeller into this vessel?
I mean, it sounds simple, but it’s something that you have to think about when you’re coming to solve an application. And sometimes the ideal, let’s say, set up, maybe the perfect set up from a power standpoint – but maybe it’s hard to maintain. Maybe it’s not something that the plant can get fast enough and stuff. So you have to kind of consider all these things before you jump right in to doing the modeling.
John Thomas: Yep, that makes a lot of sense. Now, with respect to modeling, SPX Flow, in particular, your operations up in Rochester, you have really, really good experimental characterization capabilities and expertise. You know how to characterize the physical process. You have a lot of instrumentation. You have a lot of ways to analyze what’s going on inside an experiment. For a firm like yours that can generate so much natural data, why do you even use CFD to generate synthetic data? What’s the point, when you can measure it? Why not just measure? Why do you generate synthetic CFD data?
Rich Kehn: Well, I mean, obviously SPX Flow Mixing Solutions, which now is Lightning Mixers, it’s Philadelphia Mixing Solutions, it’s Stelzer Mixers. We all use CFD, right? And essentially, we’re talking about large tanks. So obviously you can’t test something that large. You’re going to have to demonstrate mixing on the larger scale. And CFD is really good at doing that, obviously. But you know, if you’re looking at what the mix time you’re getting in the full scale prediction is, you have to ground that with, you know, both correlation based predictions and also what happens experimentally since, you know, mixing, especially in the turbulence scale in a turbulent flow regime, is scalable. What we can do is, is we can essentially, you know, link what we’re seeing in a smaller scale version with what we’re seeing in the full scale, then bring both those things together.
But I mean, you know, CFD does get you, as one of my colleagues says, you know, an answer that’s obviously not perfect because it’s a model, right? You know, but the thing is, is that if you base all of your experimentation background on this, you can really link these things together, then feel confident that the direction CFD is telling you is correct.
John Thomas: Got it, that makes sense.
Rich Kehn: Right, dowe worry – Do we worry about like the absolute answer from it? Not necessarily. What we worry about is, is the direction of the design correct? Am I getting the flow over the jacket inside the vessel like I should be?
John Thomas: Yeah, yeah.
Rich Kehn: Are the components blending like they should be? Is the feed location where it should be so it blends readily? That’s what you really want to get out of the CFD, and CFD is a great way to visualize that for the client and also provide a quantitative basis for it.
John Thomas: You know, I’ve always thought that SBX Flow has a unique role because in some sense, they can generate knowledge, right? Like you can go into your lab with your tools and do research to generate new knowledge, but you’re also very much on the application side. We have to convert that knowledge into kind of actionable engineering insights for a client. Right? And so how does CFD become a tool for that kind of communication and teaching side? How do you use CFD – I know you can use it for research purposes as discussed – but does it have utility in that kind of sales and technical teaching side of the house as well?
Rich Kehn: It does. We’ve done some tech talks on YouTube, and some of our colleagues at Philadelphia Mixing Solutions, have and essentially being able to visualize a flow pattern, and you can show concepts such as, you know, off bottom suspension of a particle of a hydrofoil versus a Russian impeller computation. You can show, you know, if I have stacked Russian impellers in a tall vessel, they’re going to stage, and you can show that visually through a CFD or a video of an actual experiment, basically. So we can bring in these concepts into our training of basic mixing principles by using not only, you know, small tanks or medium sized tanks in our lab, but we can bring it in computationally. So showing those visuals become an integral part of marrying all the theory, all of the practice that you see in sites, bringing it all together into like, you know, basic mixer training.
John Thomas: Yeah, that makes a lot of sense. Just to kind of explain complicated concepts through a video can really be useful as it were.
Let’s talk about systems of scale and size. Whenever I go to visit you guys, I’m always amazed at the scale that you operate at, not just in terms of volume of sales, as it were, a number of clients you have, but scale of these impellers or whatnot. Right. There aren’t many firms that can make things as big as you make them as it were. How does that type of scale – We’re talking about – Rich, give me a breadcrumb here in terms of volume. What are some of the bigger volumes that you’re operating at from an engineering design, implementation analysis standpoint? Because we’re not talking about, you know, grandma’s blender anymore. We’re talking about nation state resources, right?
Rich Kehn: Mm hmm. Yes. I mean, if you think about, you know, let’s say, in a field such as minerals processing, I mean, vessels that hold these slurries can get as big as 19 to 20 meters in diameter. OK, so you’re talking, you know, upwards of about 5500 to 6200 cubic meters of slurry.
John Thomas: Wow.
Rich Kehn: Right. So obviously, if you look at that in imperial units, I mean, you’re talking, you know, millions of gallons of slurry. So tanks readily get this big. So, yeah, so essentially you see mixtures all the way down to the portable size that are going to be small scale, you know, so down into the twenty hundred liters range right up to these large scales. Yeah, I mean, it’s an area where fluid mixers are needed.
John Thomas: Yeah, absolutely. Does it ever give you pause that the fluid mechanics is reasonably self-consistent, going from a few liters to millions of gallons? Is that just kind of amazing? Just on its face?
Rich Kehn: I mean, especially if you look at, you know, turbulent flow fields. Look at something simple like water. One thing that I would do when I would be running simulations early on in my career was I might get a – And this was back, you know, using time average flow fields prior to really using a dynamic modeling tool – I would get an answer that, I would look at it, and I’d say that seems a little odd. The shape that I’m getting, like this impeller seems to bypass system power.
John Thomas: Right, right.
Rich Kehn: And what I was able to do was I was able to say, OK, if I take that same model and I do it now turbulent flow field bigger scale, turbulent flow field and a decent sized tank in the vessel in our lab. I could turn it on and look. And sure enough, I’m like, Wow, that’s the shape that I’m getting.
John Thomas: That’s interesting.
Rich Kehn: That I didn’t actually necessarily believe the first time I got it. So I think, yeah, it is. It is something how you can really look at the shape of the flow field, and it does seem to scale relatively well. As long as you keep your geometries all the same, and that becomes important, an important aspect, not the only aspect of scale up.
John Thomas: It’s just interesting to me. You know, your vantage point and SPX Flow vantage point in particular in the technology world. You know, you legitimately work on systems that go from one gallon to a million gallons. And there’s not many people that in their engineering practice, I’d say, work across six orders of magnitude of volume. And that’s kind of cool. You got admit that’s kind of cool.
Rich Kehn: Yeah, it is. It has been an area that I’ve enjoyed over the last 18 years and you learn something new every day. I mean, even work that I’m doing now, you look at that something like, Hey, I didn’t really know that, you know, the day before. So it’s something where you’re constantly learning because, you know, fluid mixing is in everything. Everything you look at in your house. If you just start looking around at every product and whatnot like I’m doing now in my home office, everything has been touched by a mixer in some aspect.
John Thomas: Yeah, yeah, it has. It’s just stark to me. And just because it’s stark, I’ll say it again. Like, you work on problems Rich, that have volumes that span six orders of magnitude. Like, that’s nuts. Like, I don’t think there are many fields where you do that, as it were.
Rich Kehn: No, it is a very unique feel.
John Thomas: It’s cool. So tell me a lot of the people that listen to this podcast I’m learning are young engineers, you know, finishing up college, just beginning their career. And, you know, obviously the topic of this podcast focused on CFD and whatnot. But outside of that, you know, what do you say to someone coming out, some 22 or 23 newly minted degree engineer? What’s the advice you give to that person in terms of, you know, you’ve navigated your career well. What should they be thinking about as they enter the workforce?
Rich Kehn: I think a couple things. One, you got to do something that you like doing.
John Thomas: True.
Rich Kehn: You have to make sure that you consider that. I would say always consider further education. I really got a lot out of getting my master’s degree. Now I waited probably about, I say, ten years or so when I actually went back to get my masters. For me, I actually I think I got a lot more out of my master’s by not going right after I got my bachelor’s.
John Thomas: That’s good perspective.
Rich Kehn: I had ten years of industrial experience, and then I could look at it in a practical way of what I had to learn to basically make myself more successful. So I think I got a lot out of that. But higher education, continuing learning is important. So staying up with, you know, what are the tools that are out there? Going to conferences and hearing what people are researching on. You learn a lot by doing that. So I think look at constantly learning, I think it’s important as people develop.
I would say the third thing is, whatever you generally do, it definitely results in something physically being built. Usually, right, not everything, you know, but especially when I think chemical engineers and whatnot. So I think the other thing too is appreciate the other engineering disciplines.
John Thomas: Oh interesting.
Rich Kehn: So if you’re a mechanical engineer, appreciate the chemical engineering side. If you’re a chemical engineer, appreciate the mechanical engineering side. The reason I say that is because having received my bachelor’s in chemical engineering and my master’s in mechanical engineering, it’s a really good marriage of different disciplines that really touch plant design, equipment, design, whatever. There’s two sides of it. And being able to understand both to a good level, I think will make you a better engineer.
John Thomas: That’s interesting. I forgot that you had had two different degrees. Write your bachelors was in ChemE and your masters was in MechE. That’s kind of a neat trajectory. I love other engineer disciplines. I particularly like, I’m a mechanical engineer, and I do like similar engineers because we kind of play a game of cat and mouse.
Rich Kehn: Mm-Hmm.
John Thomas: I kind of like that kind of symbiotic relationship now. I spent the first few years of my life kind of working in that weaponeering space, so it’s an ongoing joke.
Rich, this was great. I really appreciate you being on here to chat through just some of your experiences and kind of some of your workflow and some of your perspectives on how to be beyond just a good CFD engineer, how to be a good practice engineer. So I really appreciate you taking the time.
Rich Kehn: Thanks a lot, John, for having me on.
John Thomas: Sounds great, Rich. So again, if people want to reach out, I know you’re discoverable and active on LinkedIn, they can find you there and talk shop as needed. Thanks again for tuning in and we’ll see you next time.
About M-Star
M-Star Simulations, LLC, is a software company focused on the development of computational tools for modeling momentum, energy and mass transport within engineering and biological systems. By pairing modern algorithms with graphical processing card (GPU) architectures, this software enables users to quickly perform calculations with predictive fidelity that rivals physical experiment. These outcomes are achieved using a simple graphical interface that requires minimal user specification and setup times. Founded in Maryland in 2014, M-Star Simulations has grown to include commercial, government and academic users across North America, South America, Europe and Asia.
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