Bridging the Gap Between Industry and Academia in Simulation Technology

By margaretfox

Simulation technology has come a long way in recent years. Once the idea of science fiction stories, today they have become an everyday reality. Simulation plays an important role in revolutionizing many industries. And the aerospace industry is among the sectors that have benefited from the success of simulation applications to date. 

Joining us today is Jonas Edman, business development consultant of Simcenter academic solutions, and Dr. Tom Stoumbos, simulation and test leader at Northrop Grumman, a pioneering company responsible for some of the world’s most advanced products. They will share with us the role of simulation technology in aerospace engineering, comparing past, present, and future advancements. They will also help us understand the importance of partnering with academia and other industry partners when it comes to innovation.

In this episode, you will learn about the comparison of the tech of the past to the tech of today, and also the tech of the future. You will also get to hear about the transformative power of collaboration, innovation, and the integration of academia, industry, and government agencies in driving the future of simulation technology and space exploration.

In this episode, you will learn:

  • The evolution of simulation technology
  • The importance of innovation in industry
  • How industry can positively impact academia
  • Northrop Grumman and Siemens collaboration
  • The future of simulation technology
Lightbulb graphic on the left. Quote on the right: "Siemens is a collection of great minds put together, creating these outstanding, elaborate tools." Dr. Tom Stoumbos, Simulation & Test Leader, Northrop Grumman

Connect with Jonas Edman:

Connect with Tom Stoumbos:

Podcast Transcript

Dora Smith: Welcome to Innovation In The Classroom by the Siemens Empowers Education Team. I’m Dora Smith. Simulation technology uses data to measure the potential outcome of any given situation. It has a myriad of applications and the potential to revolutionize the world of technology. To help us talk about this today, we’ve invited a business development consultant of Simcenter Academic Solutions, Jonas Edman. Welcome to the show, Jonas.

Jonas Edman: Thank you, Dora. As you just heard, my name is Jonas Edman, and I work at the intersection of business development and technology. My professional goals include equipping engineers of the future with the means to leverage simulation, as well as helping universities increase the industrial impact of their research. Today, I’ll be speaking with Tom Stombous, the simulation and test leader at Northrop Grumman, a pioneering company responsible for some of the world’s most advanced products. Tom has a PhD in Aerospace Engineering from Virginia Tech and a master’s degree in Mechanical Engineering from the University of Manchester. In this episode, we’re going to hone in on Tom’s Aerospace Engineering experience and compare the tech of the past to the tech of today, and also the tech of the future. We also talk about the role of simulation in today’s world, what it can do, what it can’t do, and what it has the potential to do. Lastly, we discuss the importance of partnering with academia and other industry partners when it comes to innovation.

Tom Stombous: We have the ability to push the updates in real-time, it doesn’t need to be a serial based on hardware process that takes time. So you gain some and you lose some with the explosive evolution of technology and the simulation. But in the virtual world is where things are more possible than the real world. So it’s great to be able to work together, and that’s where academia comes into the picture because they’re also free to develop those more complex algorithms, higher degrees of freedom, and take advantage of the early stages of high-power computers. And, of course, they’re not bound by delivering products on time to market.

Jonas: Considering that we landed on the moon in a pre-simulation era, the advancements that have since been made in tech are quite astonishing. So what has progression in simulation technology changed about the industry and the way it operates?

Tom: I think it was amazing what they managed to do with the capacity and the power of the computers back then because in order to launch a vehicle, and in order to have an engine operate, of course, we didn’t have that much software involved in our everyday life and in all our mechanical components. So, I think back then people were somewhat more innovative because they didn’t have the power of the computers and the simulation tools. Now you have at your fingertips, all these tools that allow you to innovate. Back then, you had to go to the drawing board, you had to caucus with people. Today, we also are slowly getting away from face-to-face interaction, which I think helps people come closer together and exchange ideas in a more creative way. I am hoping that this exponential increase in computational power and the ability for people to easily access these complex tools doesn’t make people think that they’ve mastered everything without the need of going back to the textbooks and studying and understanding math, physics, and chemistry. Because I think that the proper user needs to be educated behind it. So, it’s amazing what we did back then. I think we kind of thought that once we landed on the moon, it was gonna be easy to do it again. It was more of a milestone target and it didn’t have a roadmap in the government’s mind. The same thing I think with the space shuttle. I thought that was an amazing vehicle and I’m surprised, in the meantime, it took them 30 years to realize it’s too expensive instead of working on the means to make the fabrication of the space shuttle cheaper, which, instead of stopping it, we have all the technological advancements today with materials, with mechanisms, with manufacturing and predictability, and of course, the additional improvements we have on the navigation systems and the propulsion systems, to have made the same launch vehicle. Because, originally, it wasn’t just going to the space station. It had robotic arms, it had a base, and it was supposed to go grab a space vehicle, a space device, repair it, and all the things that we’re devising today. We’re here today talking about the space era that besides orbiting satellites, we’re talking about manufacturing in space, refueling in space, space depots, going to the moon, and creating an infrastructure that allows us to go beyond.

Jonas: So if this is one of the visions of today’s space era, how will modern simulation technology, like the digital twin, allow us to achieve what was otherwise out of reach when we first landed on the moon?

Tom: They started programming the algorithms that they did by hand, putting it in the computer, but of course, they had to recalculate as they were going. Right now, with a digital twin, which I think is an amazing concept that we try to realize every day, you have real-time calculations on your little personal device that helps you make decisions on hardware that are actively being used for complex operations, from medical, all the way to space.

Jonas: As useful as this new technology is, this application is not limitless and there are certain things that will never be able to replace.

Tom: The human creativity, I don’t think it will be ever replaced by AI. AI needs to be respected for what it is and be used as a tool for humans to be creative and be able to accomplish whatever the roadmap is between improving health, extending life, improving social conditions, and all the explorations we tried to do through space and beyond. It’s amazing. I always consider the analyst an artist because the same way the artist has the correct interpretation of the painting, although sometimes it’s up to the admirer of the art to interpret it any way they want. But in the engineering world, a good artist creates a model that really replicates the mathematical and physical entity. With the new pre- and post-processors, the elaborate 3D rendering with high-definition models we have now, the analysts can be easily deceived, like, “Oh, it looks like the real part, that means I modeled it correctly.” That’s why you need to understand what you’re creating. It looks artistic. Any simulation work, any model, any rendering of the result, I find it artistic. So, it’s hard, but the artist is the one that really appreciates what he created and also can verify that it is really the true representation of the physical entity, because behind all those nice pictures, there are mathematical equations and physical models. That’s why I tell the engineers if you’re looking at somebody else’s model, don’t look at it as to how well does it represent the picture of the parts you’re trying to analyze. You’ve got to go beyond the picture and understand how it was put together, which is the same way as appreciating an artist’s rendering.

Jonas: The introduction of AI into the industry should not be used as an excuse to undermine the value of education or human creativity. Instead, it should be viewed as a tool to boost innovation and bring us closer to our goals. With this in mind, I asked Tom to take me back to 23 years ago, when simulation was first injected into industry. What does his industry experience look like since then?

Tom: Back then, it was more the engineers’ creativity, put it on paper, let’s make some prototypes and start testing them. And simulation was more of a side thing; just quickly verify to make sure that approximately we were okay. But everything is going to be verified and validated on the test field and through testing. So, incrementally, simulation became part of the effort to extrapolate over the experimental data and over the design information and introduce more data points in the decision process. So when engineers are reviewing a design, they can look at sensitivity studies and additional information that was produced. Just because you don’t have time to create all these different prototypes and you don’t have time to get information from one test to the next, we are doing it in parallel. While the test is taking place, the simulation keeps on running with all the different options and then it will allow us at frequent instances to go back and review the test results without having to go through expensive and extensive testing and provide the information in real-time as these concepts or even products are being produced to interject into the process of manufacturing and predictability and introduce changes incrementally to the final product. So, time to market or time to launch is so much faster. In addition to that, simulation, being run in parallel, continues to give information such that it reduces the risk of having an issue, having a failure, or having a fatal mission failure once in space.

Jonas: So a vital contribution of simulation is its ability to provide real-time information, bypassing the need for extensive testing and shortening the product development times. Yet another boost in innovation comes in the form of private enterprise.

Tom: The culture takes time to change. And because a lot of these space innovations are driven by government agencies, it’s a slower path to change from the government side as opposed to the private industry. So I think we see this explosion in space applications from communication to exploration to mining to the infrastructure we want to build in space to go beyond and explore because there has been a lot of private funding that allows people to be a little bit more innovative than being bound by the requirements that the government imposes to the contractors. So that’s why we have so many new companies and people are seeing this as a great era to put their money where they think it’s going to grow into something scientifically possible. You can say we define possible through these private efforts. Of course, there’s an enormous amount of knowledge and the information we obtained from the government work. But the combination between the government efforts requires a little bit more validation, verification, and testing. And of course, because the systems are becoming more complex, there are more things to test. And at the same time, because our testing equipment and our computational power is increasing, it allows people to push for more testing. But we also need to verify and validate the simulation that we create. So that also needs to take some time. And we see that often when we try to push out products, whether it’s mechanical products or virtual products through simulation, they’re often bugs that can be detrimental to the development or sometimes fatal. For example, in the auto industry, we see how all the recalls just because they try to push software now every six months, every three months. When I started working, we get new versions of simulation tools every two years.

Jonas: Of course, as in the nature of this pod, we can’t talk about innovation and industry without talking about the contributions of academia. Tom described why he thinks these contributions are valuable and how they shaped the overall picture of innovation.

Tom: It’s great to always have access and collaborate with academia, because they’re going to try to go forward with whatever ideas and concepts they have, they don’t want to be bound by your product constraints or requirements. But at the same time, there are a lot of things that develop that you can infuse into your product and improve it. So it’s good to have them go off free and not be constrained by the industry or the requirements of the product. And on the simulation side, just because they’re always trying to get a better approximation of real life, we’re trying to go to the infinite degrees of freedom of physical entities through mathematical and physical models and we’re getting there. 20 years ago, our pre- and post-processors were black and white, 2D stick models, now we have a full physical digital twin that to some people, it looks real. That’s where artificial intelligence and machine learning come into the picture. And of course, the explosion of data. It’s another struggle to contain, be able to process timely, and of course, archive it properly, be able to retrieve the data when you need it, and retrieve the right data. There is always a chance of having incorrect data infused into your problem and then create other problems.

Jonas: So, as academia does not adhere to the constraints present in the industry, it allows for the greatest flexibility when it comes to innovation. Tom expanded a bit more on why this flexibility exists.

Tom: There are obviously technological advancements every day, every month, every year, and year after year. If you assume that engineers graduate from universities and then work for 30 years, if they work 20-30 years ago, they typically were dedicated to a company, the company took care of them, and they just did the same thing, and there was a slow evolution of the product. And unless they go back to do this continuing education, interfacing with academia, learning about the new concepts, and also being exposed to what the world is producing, they will be biased because, after school, which was all engineering textbooks, they went to some hardware that stayed with them for decades. Typical defense or engineering government programs last 5, 10,  20 years sometimes. So there’s a lot of information technology in those years. So if you’re not continuing your education, going back to school, the curriculum, when we were in school, is not the same as what it is now, it’s adjusted to the technology that has been developed now, including the simulation tools. Also, the computational power goes back to being able to use algorithms to solve higher-order problems, which increases the fidelity of the problems we have. So, the students bring their youth and their creative minds into the group that has a senior people that are a little bit wiser, they have experience with the hardware, while the engineers are more recent with the technology, the higher order algorithms, and what they’ve been exposed to through the university projects, bringing the real-life reality and problems along with the creativity of the youthful minds, I think it’s a recipe for great success. For example, we produce satellites for customers and their schedules, so we need to do specific analysis to develop these systems. We have the universities in parallel tackle design challenges we have based on requirements, but we allow them to go off and solve their problem with their own algorithms and run it through our simulation tools. We have them use simulation tools to see how different the result will be and understand where the difference is coming from. While we focus on continuing with the product design manufacturing test, we have that frequent interaction with the students telling us what they think, what kind of solution the problem we gave them have, and then we collect them to decide if it’s something we need to introduce to the product and when is the right time. So this greatly enhances not only the quality of our product but also the fact that it has a high probability of being successful.

Jonas: You’ve just heard the ways in which Tom believes academia can make a valuable contribution to innovation in the industry. Now, what about the ways that industry can positively impact academia?

Tom: From the academia, there are a lot of textbooks to read, there’s a lot of theories that you need to study, maybe there are some case studies you’re looking at. But you don’t really fully appreciate what is the real-life engineering environment where different disciplines come together to create a project. You wait until the senior project to work on something that may be realized, maybe not. During your academic years, if you have the opportunity, besides working with the students and the professors, to work in a real-life engineering environment, you develop that appreciation, not only in the other functional areas that allow you to go and explore those functional areas to better understand how the system works together as opposed to isolating yourself and that specialty, but also teaches you how to work with other people. And it gives you that energy to go back to the university and try to be a better engineer and a better team person. Because it’s not only developing engineering skills, you need to develop the social skills, which is another great thing, I think. 

Jonas: Tom has been working with Northrop Grumman to simulate and test complex space vehicles. Just recently, Siemens was selected as a top supplier for the company. I asked Tom about the Northrop Grumman and Siemens collaboration, and what the important lessons he’s learned through it. 

Tom: The one thing I found with Siemens is that they have the same mindset that I and my team have in the sense that there’s always a partner out there that you can gain from. The same way we see value in interfacing with universities, engineers and professors, or engineers in training and professors, the same way Siemens interfaces with the universities and have that same energy. In addition to that, Siemens, from the simulation side, developing tools, perfecting algorithms or exploring algorithms that will improve their simulation. Going from all the way the early design stages, to performing the various analysis, to the final product, as a partner allows us to talk about the various tools and how they can be used in our engineering problems, because there’s not one way you can apply all simulation tools to all the products, there are analysis-specific parameters you need to focus on. And, of course, if the models and the process is not set up correctly, you will get results, but they may not be correct. So, that’s why I see Siemens as a partner because they are always there for any questions we have with the tools. And of course, by default, everything else becomes more complex in our life, the same thing with the tools themselves, they give us great power in developing designs that are very innovative, and also can be successful in the mission we have for the customer. But we need to be able to understand how to use them. So by working with Siemens and academia, from the academia side, our engineers get a better appreciation of the mathematics, the physics, the algorithms. And with Siemens, how those algorithms come together, and the tools that Siemens creates to be able to run our simulations and be able to create these space vehicles.

Jonas: Circling back to the first moon landing, it’s certainly amazing to see how far technology and innovation have progressed. Looking forward, leveraging the tools we have now and taking into account lessons learned, what does the future of simulation technology look like?

Tom: With all this evolution, we see, in not only simulation, the power of tools, data analytics, artificial intelligence, and exploration of space and beyond, where do we go? Because you cannot be successful by operating in the same way in 20 years like we do today with all the technology and also the need for the shifting in the workforce specialty and training. So, where I see us being in 20 years with the rapid advancements we had over the last decade, is being able to launch individual parts in space and have a space like we have the International Space Station, we have a space manufacturing facility, where you don’t even need to enclose it. It’s designed with innovative materials such that in space, you can take and grab parts floating in space together and assemble them and put your space station together out of floating parts. Go to the moon and do the same thing, be able to launch and we see the evolution, even on the launch vehicles, going from what the launch vehicle engines’ power used to be a few decades ago, and now we have launch vehicles that can lift more payload than ever. But we’re more efficient if we’re able, instead of building the space vehicles or the complex exploration space vehicles on Earth and try to launch beyond Earth gravity into space, is launching and deploying sub-assemblies and have an innovative manufacturing and predictability infrastructure in space and then take off from there. So that would allow us to have much more complex space vehicles exploring the universe than having to assemble it and create it on Earth and then launch the whole system into space. I mean, everything goes back to Moore’s law; he predicted with respect to the power of the computer chips. Look at where we are now. Of course, sometimes things do not evolve, develop, or are successful that quickly but human innovation and creativity and going back again to combining the experience and the termination of the industry with the creativity of the academia and also the expertise of the academia and the innovative companies that make digital transformation through because if we don’t go fully into the virtual world, a lot of these things will not be able to be realized just because the data we produce to improve the decisions we make reside in the virtual world.

Jonas: The creativity of academia combined with experience and determination of industry is no doubt a winning combination. There’s one particular part of the industry that Tom wanted to highlight.

Tom: The small business. We have the transition from the universities, what is created in the lab, to some innovative minds starting with a small business, innovative research, then all that combined into the big industry. I mean, Siemens is a collection of great minds from the small industry putting it together and creating these outstanding, elaborate tools.

Jonas: To wrap up our conversation, Tom shared some final thoughts on the industry’s increasing collaboration with academia and the benefits that come along with it.

Tom: A recent visit we had at ASU a few weeks back with some of our Siemens partners, Jerry, Darren, Andrew, and Mia were there. We found out that the universities now are creating these specialties collaborating with government agencies, where they try to bring also within the universities this, I would say, smaller scale engineering workshop where they work with agencies and companies besides just being interns. It’s a funded work that they do to develop subsystems or components for the space industry, which is, I think, also innovative, creating these small entities within the university that use university resources, allow the students to do real-life applications that also apply to both government agencies and companies. So I think the concepts we’re discussing are being realized by universities. Not all the universities have developed that kind of environment, but I think we’re in the process that in a few years, it’s going to be at the majority of the universities, and that will make it easier for these smaller agencies, the larger companies, small companies, and universities to collaborate and exchange ideas and help each other grow. And it’s exciting to walk out of your lecture class to go into your own little lab with your students and co-workers and industry mentors, and feel that suddenly you walk across the aisle there and you’re in a production environment.

Dora: Thank you to Tom for taking the time to speak with Jonas about the advancements we’re seeing in simulation technology, and how building bridges between industry and academia can expedite the furthering of these advancements. Stay tuned to Innovation In The Classroom, wherever you do podcasts. I’m Dora Smith. Thanks so much for listening.

Leave a Reply

This article first appeared on the Siemens Digital Industries Software blog at