 Hello my name is Oriel Adpo and I'm Shaila Wilson. Today we're going to be discussing a methodology for using dynamic simulations in the military with particular applications for the Marine Corps. Our simulation is going to focus on the targeting process and artillery. We're well aware that a lot of people don't know what artillery is so this picture is a demonstration. This is a cannon, the base unit of artillery which provides indirect fire against enemy combatants. The purpose of this exercise to show that dynamic simulation is a relevant tool for operational leaders on the battlefield. We will go over in the future how simulation is currently used in the military. However it is not used in the operational level. Specifically the people making the decisions do not have access to manipulate these simulations. We want to show a simple and reasonable tool that these operational leaders with no simulation experience can make a model to help them make better decisions. The decisions they might make include the unit capacity, how much work can they do, how fast can they respond so they can make better decisions when they're talking about support, and in an operation how much more support can they provide for other operational leaders. So first of all a background simulation. Simulations have been used in the military for a really long time and simulations in general in the military are divided into two categories. Man-man simulations and man-machine simulations. Man-man simulations run through operations on the ground mainly through training and practice exercises. While man-machine simulations include the marine tactical warfighting simulation, these occur mainly through dynamic simulations run on large computers. The military has been doing this for a really long time. An example of this would be USA Come which is a joint training analysis and simulation center run by DARPA. Another example of this is the STO 97 which is the synthetic death of war operation that was run in 1997. Our model is going to focus on the targeting process but to make that make sense we need to define some terms. In artillery the base unit similar to if you're if you're familiar with an infantry company is an artillery battery which consists of six firing guns. There are three batteries which compose up in artillery battalion. The battalion's responsibility is command and control the batteries. There are three battalions which form an artillery regiment and the regiment similarly commands and controls the battalions. Generally a target is going to either go to the regiment or the battalion and then they will delegate to subordinate units until it eventually reaches a gun that will fire upon it. So some of the assumptions that we made for our model include the target generation. For this we estimated a random target generation process following an exponential distribution of targets entering the system at about every 15 seconds on average. We also tried to simulate the delays for each step of the process. So from when an infantry unit gives the battalion the target all the way down to when the target arrives at the battery and is fired upon. We got the data that we used for our delays from the marine training in redness. From the marine training in redness manual. In our model the battery makes the firing decision and then accepts and sends the targets to guns to reject or dispose of the target. This is how we use the disposal. So when the gun shoots the target the gun is the last process it's disposed. We then modeled everything from a battalion down. So in this case the battalion is either receiving a target from the regiment or they're receiving it from an infantry unit. It doesn't make a difference in our simulation. So to give you an idea of what our general simulation looks like this showcases what the what the simulation would look like all the way from target generation from target generation from the infantry unit all the way down to when the target is fired on by a gun under the battery unit. But then this is a sub model showing what occurs within each battery unit from when it's accepted or rejected to the guns that receive the target and when it's fired upon. But first let's actually show you what the entire model looks like and then open it up in an arena so we can run through a simulation process. This is our target operating where targets are currently entering the system. As you can see decisions are being made in which unit to test them to. In this case it's just a preferred order system. In that way it's going to rotate through the batteries and evenly disposed. Okay now let's get to the results. In this case we modeled for only one hour and the reason we did that was deliver it. In combat generally there's a lot of downtime followed by small periods of highly kinetic activity. We're simulating that period of highly kinetic activity and seeing how well we respond to targets generating that fast. So one of the things we could get is how long the target remains within the system from when it's generated by the infantry unit to when it's fired upon. We can also figure out what batteries are more likely to be used, what the utilization rates are and how quickly our responses are compared to what the ideal standard is by a set by the Marine Train Mental. This is drastically important because target information decays fairly rapidly depending on the situation. In some cases saying when you're going against a fixed enemy, you do have time to fire. Seven minutes might be good. In other cases say in Afghanistan, you might need to figure out a way to get that fire rate in under seven minutes and you can't make someone work faster. You can't make it less safe so you have to figure out ways to manipulate the process so that the target gets fired in less than seven minutes. And that's what this highlights and this lets them make decisions. Additionally they can change the amount of guns per battery. They say increase guns or decrease guns or they can decide to split batteries up and see how that affects the targeting. Okay, so some of the challenges we face while building our model include the following. For me, O-Ray, one major challenge was domain knowledge, common to terms of some of the factors and some of the specific terminology used within military operations and figuring out what was the right term to use within a particular field as well as not knowing how the Marines run through a targeting process. So for this particular field, I defer to Shiloh who has on the ground knowledge of this particular area. For me, a big challenge was data sources. There's no statistical test or statistical studies conducted on specifically targeting. The data is just not collected. It's not available. We know what we're supposed to do. We know how fast that they're supposed to respond. We don't know how they actually respond. And that's a huge limitation in the accuracy. That's why our scope is a method that can be used, obviously with appropriate data. There's also technological limitations in arena's capabilities. We can only have 150 entities. That's why we're doing the study at the battalion level. Additionally, arena is not facilitated for a military process in terms of there are some things that we could not model with arena. So how exactly do we predict our model could be used? We think our model might be useful in determining the force organization, figuring out what battalion level choices to be made and whether or not a battalion can exist as either direct for providing direct or general support for infantry elements or for other battalions and other regiments on the ground. To lay person, the choice of director general support is it seems transparent. You want to be able to tell however as huge implications in a general support model, all targets go to the regiment first where they're delegated. That extra step adds information to the regimental commander to help him make choices, but it slows down the targeting process. Whereas in a direct support model, individual infantry units send their targets directly to an artillery unit. Now this allows them to get rapid response, but that artillery unit is no longer flexible to support other battles. Another issue will be figuring out the resource requirements of each operations. As an operational lead for battalions, you need to know how many guns you require for each battery and how many guns you require as a whole for an operation. This would also help you in preparing for instance, for seen circumstances. If there are instances of gun failures or maintenance activities going on during the operation, how exactly, how prepared is your operational unit to respond to such targets? In this case, the way it's currently conducted is if a gun goes down, there's kind of a guess of what our current capabilities are. And a lot of times that's an over prediction that puts a lot of strain on the Marines and it creates mistakes. In a model like this, we can directly look at it and say, okay, we're missing two guns. And this is a quantified measure of how we expect our performance to be deteriorated. So based on this model, we'll be able to provide advice and knowledge to commanders to better support the operational activities in varying fire conditions. These are some citations we rely on to build our model and to build our report. Thank you very much. Thank you.