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  • Writer's pictureDavid Wood

Qubits: New Era M&S

Updated: Jun 1, 2022

Recently, Davidson Creative Services Manager, David Wood, interviewed Davidson Systems Engineer, Matt Donvito, for episode 3 of our Qubits Thought Leadership video series. In this episode, we discuss modeling and simulation and the paradigm shift from legacy simulation engines to gaming engines; and how the next generation of simulators are leveraging these platforms toward the defense of our Nation.

DAVID: Matt, thank you for joining us for this episode of Qubits. Start off by introducing yourself to us and telling us about what you do.

MATT: Okay, my name is Matt Donvito. I’ve been with Davidson for about 9 years now. My primary role is to manage and lead Modeling and Simulation Development teams. I’ve been on a couple programs here with Davidson, mostly within the Missile Defense Agency. I worked on end-to-end simulation there that represented the entire Ballistic Missile Defense System; including Integrated Air and Missile Defense.

From there, I moved on to a new program here at the Colorado Springs Davidson Office called the Active Protection Systems Simulation. It’s intended to provide a simulation of an Army Active Defense System that you typically place on a vehicle or a tank in order to negate threats that come at RPGs or things like that. I’ve been working on that for about a year now, making great progress and excited to see where that goes in the future.

DAVID: We know that Modeling and Simulation is one of Davidson’s core competencies and capabilities, but when you say Modeling and Simulation, tell us what you mean.

MATT: Okay, so Modeling and Simulation is the process of taking a physical thing and turning it into something digital that a computer would represent instead. So, it could be as simple as a 3-D model of a real thing. For instance, a 3-D model of a desk or a conference room and how the layout would be. That’s kind of like a model or a computer-rated design. All the way to simulating the physics and the way things act in the real world. Such as, a plane flying or a missile flight. All those things you represent digitally within the simulation environment and you do that because it’s expensive to fly these things in real life. If you want to do a missile test or blow up a car to see what happens or a crash test or anything like that, you would need to actually produce a piece of hardware, create a test site, do all the safety protocols that are required to do this in the real world – and then actually perform the test.

So, all the months of lead- up, all the people required, all the safety concerns and the physical pieces you need to do this test. Whereas in a digital environment, none of that stuff is really a factor. You could run a missile flight pretty much anywhere in a simulated world that you want. You don’t have to worry about if it going to hit anything or anything like that. You can run things that are outside the bounds of what’s possible in a test range. It’s also significantly cheaper. So, once you develop the simulation, and you have trust that it provided you with accurate information, pretty much it’s wide open as to what you do with that simulation. And the results that you get can inform you as to how that system would actually work in the real world.

DAVID: Matt, how do we generate reliable Modeling and Simulation that players want to use and use for big decisions?

MATT: So that’s a very tough problem in the Modeling and Simulation world. There’s something called accreditation. That’s the goal. What accreditation does is, it tells you that, from the user’s perspective, they have full trust in the simulation and the results it provides. So, there’s a long road up to accreditation and there’s a lot of ways to provide evidence to show that the simulation that you’re developing and the data it provides is credible, it’s reliable, and it is a good representation of the real world. And a lot of the ways we do that are things called ‘benchmarking’ and ‘anchoring.’ So, if you have a trusted source of data such as a flight test, if you run the same scenario on the same conditions simulated as you did in the real world with the flight test, you can compare the data output you get. And if you compare them and they’re favorably compared and they’re close, then you can make a reasonable expectation that your simulation is good at representing that specific case.

So if your simulation is good at representing that specific case, you have a set of evidence that your simulation is accurate to the real world data you have. Where it gets difficult is where you’re asking a simulation to do things beyond what you have source data for. And a lot of times, that’s the case. So what you do there is a more rigorous validation of the algorithms and equations you use. They’re all checked to make sure they’re running correctly; that they are, in fact, representing the things in the world you want them to represent. The physics all check out, all things like that. So you do have to take a leap of faith when you’re operating outside of the range of the data you have to benchmark or anchor your simulation.

Another big part of this is when you’re making a simulation, it has a specific intended use. So it’s like any other tool. If you have a hammer and you have a screw, the hammer is not the right tool to operate a screw. Simulations are the same thing; there’s one for training, one for performance assessment, there’s one for war gaming. So when you’re designing a simulation, it has to do certain things well enough to meet those intended uses. So if you’re doing a training simulation, it may not need to be as accurate as one that you’re doing for performance assessment. So intended use is a large part of the simulation development. Making sure you’re doing what the customer wants, what the user wants, you’re doing the accuracy that’s needed. You’re not going above or below the accuracy that’s required by your user.

DAVID: What’s next when it comes to Modeling and Simulation?

MATT: So one big switch that we’ve made is from these legacy simulation engines that are mainly used in the scientific or engineering areas is moving that to gaming engines. Gaming engines like Unreal or Unity, typically they’re used for games like Fortnite or online gaming. We’ve started to use those within DoD to create our simulations. They provide a lot of the same capability that the scientific frameworks would give us. But they give us a lot more utility out of the box so we can develop these simulations a lot faster. The 3-D capability, the built-in physics, built in time management; all those things are built into these gaming engines where you don’t need to build that into another framework.

That allows us to really build initial capability very quickly. We provide that to the user, let them poke holes in it, tell us what they like and what they don’t like. Then we can quickly develop on top of that with more fidelity, better graphics and things like that. We get the basics out the way, the basics that would take you a year or 2 with the old, normal framework, all the things getting you up and running are right out of the box with a gaming engine.

So that’s been a big leap forward for us, in the past couple years. We’re leveraging these gaming engines, and really getting us off the starting line quickly so within a few months, we can deliver something to the customer. We provide an avenue for them to get feedback to us.

DAVID: It’s fascinating, really. Imagine Julian Davidson 25 years ago being told that we would be using video game infrastructure. 20 or 30 years ago, if you would have said that to someone, they would have laughed at you.

MATT: That’s true, yeah. And I think part of that was because these gaming companies wouldn’t put these engines out to the public. Unreal has been around a while, Unity is fairly new. But they were mainly held by the companies as heir own internal development engines. Once they started making those open to the public, which was a good financial decision on their part because they could charge a fee, or things like that to a commercial user. Once they bought those out in the public, they because a viable option because DoD didn’t have to develop the gaming engine. That would be very tough and a very big job for the DoD to develop a gaming engine.

Now that these are out in the public, it’s easy for companies like us to leverage those engines because it’s just a matter of downloading them off their website, learning how to use that framework, and just go ahead and start developing on top of it. What I really like about this area is that you’re building something tangible. It’s something that someone needs. There’s a lot of challenges. A big part of engineering is solving problems. You can typically run into problems when you’re developing these types of simulations. It’s great that they’re a huge cost and time saver to our customers. The current customer we work with now was more in the mindset of physical testing was kind of the way to do it. And they've been doing that for years and years and they trusted it and it was a reliable way to get data.

It's great. Being able to see their mentality shift that maybe simulations are an area we should focus on more because we save so much more money. And because if we trust these simulations, they provide us good data. Maybe not as good as a flight test, but definitely a more diverse set of data than we would get from shooting an object to another object. Seeing that mentality come around, even to the more hesitant customers has been a huge benefit, I think of this whole simulation program. It's exciting, you know, learning new technologies, such as gaming engines, learning how to adapt concepts we've used in the past to this new engine and two new gaming type concepts.

It's really exciting. It really makes the job interesting day to day because you never really know what you're going to run into. I grew up with Nintendo and games like that. There was never really a possibility when I was growing up to build my own games. Right. The people we're hiring now fresh out of college, they grew up not only playing games, but also figuring out to make their own. Because they had these tools available to them. So it's an easy switch for them to go from, you know, kind of a hobby that they were doing as growing up something they were interested in, just, you know, just a normal interest of growing up.

And so they get to translate those skills into something that's useful for the defense of our nation. They'll bring those skills of developing games and translate that into something we can build as part of a defense simulation. And so what we're noticing with the younger generation is, they already have the base concepts of how do you add objects to a scenario.

How do you add objects to a game? How do you make them behave the way you want? And it's just taking those generic gaming concepts and framing them into more defense or DOD type concepts. Right. How you fly a missile? How does a defense system react according to these inputs? So they're already well ahead of the game I think.

Another good thing is that a lot of the development languages that I learned growing up or in college are kind of being phased out for these other development engines and development languages. These new grads know a lot of these gaming engines are using those new languages.

As things mature in development and in software development languages, come and go. So these, this new generation is up to speed on these new languages they're used by these engines. And that's just kind of the normal flow of how technology works, right? Some come obsolete, some new ones come in and the younger generation is the one that helps us move ahead with those.

DAVID: Matt, thank you for joining us today. We certainly appreciate it.

MATT: Thank you. It was a good discussion.



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