The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech

Tactical Reduction In Detection of Electromagnetic and Noise of Naval Transport Signatures

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Executive Summary

Approximately 250-300 words describing your grand challenge problem, your approach, results, and conclusions.

Team Members

Justin Kizer
Program Manager
Planing Craft S&S

Dr. Santiago Balestrini-Robinson
Advisor

David Simmons
Chief Engineer
Acoustic Analysis

Michael Steffens
Electromagnetic Analysis

Kip Johnson
Cost Analysis

William Steiniger
Mine Modeling

Background

Obtaining unrestricted access to regions of interest across the globe is a key requirement for the US Military. Littoral craft are one of the many types of vehicles used to facilitate access to these different areas. These craft are typically utilized for short range (< 500 nm) missions with a small number of personnel (< 20). Such missions may be of a covert nature, where detection may mean failure. Thus, as the US Navy looks to the future, advances must be made in these small craft, both in technology and in operations in order to improve their feasibility, survivability and affordability.

The littoral regions in which these craft operate may be denied through the use of underwater mines. There are a wide variety of different types of sensors and mines employed to detect and damage ships. The two most common mine sensors are acoustic and magnetic, and the more advanced mines often tend to use both to detect and identify target ships. As a craft propels itself through the water, noise is generated both from the hull/water interaction and the propulsion mechanism, usually a water jet or shaft and propeller system. In addition, most craft either have a hull made out of magnetic material, such as steel, or have magnetic onboard equipment (including engines, navigation/communication equipment, etc). Mine designers take advantage of both these signatures to detect and destroy these craft. As mines become increasingly sophisticated, the small craft community is becoming keenly aware of the impact that electromagnetic and acoustic signatures have on both the vulnerability and susceptibility of their assets.

Technology does exist to minimize the electromagnetic signatures of littoral craft. One of these technologies involves a passive process called degaussing in which the permanent signature of the magnetic material on the craft is altered or removed. This process takes some time and involves specialized equipment. Furthermore, this process currently cannot be used during an operation to alter the magnetic signature of a craft. Another technology involves the calculated placement of magnetic coils inside the vehicle. These coils can then be used to actively cancel the magnetic field generated by the craft by generating an equal field in the opposite direction. For maximum cancelation, one coil is needed in each axial direction.

Craft operations may also be altered to reduce the craft signature.. A faster moving craft will generate more noise, but will decrease mission time. If a craft generates more noise the likelihood of mine detection and actuation increases, thus the probability of a mission failure may also increase. On the other hand if a craft moves slowly, the likelihood of being detected by enemy forces increases. In addition, the magnetic signature of a craft also depends on its heading as well as rolling and pitching motion. Both the design and operation of the craft must go hand in hand to facilitate successful missions.

As the US Navy looks into increasing the capability to operate in mined littoral areas, there is a need for a means to assess the capability, feasibility and survivability of new designs as well as modified legacy designs of small watercraft operating in mined littoral areas. The minimization of vehicle signatures (e.g., magnetic, acoustic) as well as vehicle weight and acquisition cost is of key importance to reducing the susceptibility while increasing the feasibility of small craft operations.

Approach

The initial stages of the project entailed a thorough literature review of littoral craft, craft signatures, craft cost, mines and their environments, and how these craft were deployed and operated. The team broke down the problem into 5 sections: craft architecture, electromagnetic signatures, acoustic signatures, mines, and craft cost. The team researched each of these categories individually and developed analysis tools.

There are several different existing littoral craft employed by the US NAVY. They range from around 15 ft (Combat Rubber Raiding Craft) to around 82 ft (Mark V Special Operactions Craft). Other current craft include the SOC Riverine and Rigid Hull Inflatable Boats (RHIBs). In addition to considering existing craft, the team analyzed requirements for the design of new craft operating in littoral regions. These included requirements on craft performance (speed, range…) as well as payload requirements (personnel and smaller insertion craft). A tool was then created based on regressions from existing craft data and physics based analysis to size a craft given certain requirements. This enabled the user to essentially choose a craft based on the mission in mind.

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Littoral craft have many types of signatures. When it comes to mines, two of the most important are the electromagnetic and acoustic signatures. Electromagnetic signatures can be broken down into 4 categories: ferromagnetic, eddy current, corrosion related, and stray fields. The most significant of these is the ferromagnetic signature, which is due to the interaction between iron and other magnetic materials aboard the craft and the earth’s magnetic field. The electromagnetic signature can be estimated using Maxwell’s equations and simplifying assumptions. A tool was created to combine information about the craft architecture and the earth’s magnetic field to generate an overall craft electromagnetic signature. Acoustic signatures are generated as the hull comes in contact with the water and also by any onboard systems that generate noise. Acoustic analysis can become complicated, as the path the vibrations take from the source to the hull must be considered. However, by parametrically varying the location and strength of different sources along the hull an estimate of the overall acoustic signature was obtained.

Understanding the threats to littoral craft was a very important part of analyzing the susceptibility. Mines can be triggered in several different ways, through contact, sensors, or remotely. The scope of this problem focused on sensor mines that detected acoustic and electromagnetic signatures. To analyze the threat posed to a craft by a mine, a specific craft-mine paring was developed. By parametrically varying the mine, the susceptibility of the craft to different types and depths of mines was evaluated.

An overall cost estimate of the craft was considered to enable users to make decisions while trading off craft requirements and cost. The cost estimates were developed using cost estimating relationships. These estimates broke a craft down into different groups based on the Ship Work Breakdown Structure (SWBS groups), and individually assessed the cost of each of the groups.

To get the big picture, each of the 5 problem sections were combined into an overall decision support environment that allows the user to consider craft requirements, signatures, mines and cost at the same time. A user can parametrically define a craft and mine threat and then evaluate how well the craft will be able to avoid detection by the specified threat.

Analysis and Results

The analysis was broken into five different analysis modules. The first was the craft sizing module. Outputs from this module were input to the signature modules (electromagnetic and noise) as well as the cost module. The signature module outputs were input to a mine module. All the relevant information was then fed into a graphical user interface.

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The Craft Architecture tool was designed to model vehicles which are a subset of the US Navy's classification of small craft. Because these vehicles were desired to operate at high speed, a planing craft assumption is made in the creation of each design. In other words, each vehicle design, when at its design speed, develops at least part of its lift through dynamic forces by planing on the surface of the water. Furthermore, each design is sized assuming a "V-shaped" mono-hull planing hullform with a single chine, marine diesel engine(s), and waterjet propulsors.

The sizing and synthesis of each design is weight based and iterative in nature. Using mission discretization and fuel balance techniques, a vehicle is sized based on user requirements. This sizing is initiated with a guess of the maximum craft weight which is ultimately used to calculate the resistance on the planing hullform. Assuming a steady state, the thrust provided by the propulsion system is set to the resistance which allows for the calculation of the required propulsive power. With this value and engine power, weight and fuel consumption regressions derived from contemporary marine diesel engine data, the propulsion system can be sized. The craft is then run through its mission and the required fuel is calculated. This iterative process continues until the fuel is “balanced” hence the fuel available is equal to the fuel required. When combined with small craft weight fractions, or component weight regressions, the craft can be defined and its performance evaluated.

The electromagnetic analysis was performed based on 3 publications by John J. Holmes at the Naval Surface Warfare Center: “Exploitation of a Ship’s Magnetic Field Signatures”, “Modeling a Ship’s Ferromagnetic Signatures”, and “Reduction of a Ship’s Magnetic Field Signatures”. These publications gave an overview of the current threats to ships, methods of decreasing ship signatures, and how to evaluate a ship’s signature using Maxwell’s equations. While this project only dealt with craft (which are smaller than ships) the underlying physics of the problem were still applicable. The first part of the analysis involved estimating the signature of the craft hull. While most fast littoral craft currently employed by the US Navy have non-magnetic hulls, it is important to be able to evaluate craft with ferromagnetic hulls. Ferromagnetic signatures can be broken down into induced and permanent magnetization; the induced magnetization is described first. Assuming a quasi static state (the craft’s magnetic field changes slowly enough to where the time derivatives can be ignored) and a source free environment (no magnetic fields being generated in surrounding medium) Maxwell’s equations can be reduced to Laplace’s equation using a magnetic scalar potential. A prolate spheroidal coordinate system was developed to take advantage of some of the geometric properties of craft hulls. Once this analysis was performed, and results were verified with the publications, the method could be applied to any shipboard system by modifying the geometry and magnetic properties. A total signature was determined by summing up the contributions of each magnetic system. The permanent magnetization is due to the presence of an external magnetic field, such as the earth’s magnetic field. Analysis of permanent magnetization requires a time history of the external field as well as data on the mechanical properties of the system. For simplicity, a percentage factor was included to account for the permanent magnetization as well as any cancellation technologies employed.

The noise module takes in data from the geometry module, the size, shape, and placement, of different components of the ship that would cause a perceived change in the noise level. These components were the engines, the hull, and the water jets. The user would input the frequency of each of the sources, and the resulting decibel level at different ranges and depths would be plotted for each separate component. The noise module used BELLHOP to plot these results. BELLHOP is a tool that propagates the attenuation, or the loss of energy, of a noise source given the original frequency and location, and the results are the attenuation of the source in decibels. By running BELLHOP through a variety of frequencies, a great amount of data for each of the frequencies was created. The amount of data too large to be used by the integrated environment because the time for the environment to calculate the results grew exponentially due to the large amount of data. To increase run time, the data was imported into JMP. Using JMP and Response Surface Methods, a single equation for every frequency was able to be created using the data from BELLHOP. This equation is what is used by the noise module to calculate the noise for each source.

Once a craft was defined and the signature evaluated, the next step was to determine how the craft and mines interacted. Many different types of mines were researched. The final mine analysis was performed using a parametric mine definition. As certain mine data can be sensitive, this allowed users to define any specific mine they want to consider. The analysis also included damage information. This analysis was never validated, but can be used to capture trends, or if data becomes available, the tool can be calibrated and validated. Actuation information, based on the mine definition, was also output, resulting in actuation curves for given depths and maximum actuation depths. In order to be computationally efficient, a symmetry across the longitudinal axis was assumed. Finally, a simulation was developed to evaluate how a craft performed in a given environment. This environment was defined using specific mines and minefield densities, which ultimately produced the number of mines actuated by the craft as it traversed the mine field.

The cost estimation module estimates the acquisition cost of the specified small craft fleet. This is done by using Cost Estimating Relationships (CER), which are parametric equations, regressed from historical data. In this case the equations are split out by the Ship Work Breakdown Structure (SWBS). This structure is used to define the weight of craft. Weight is, with the exception of the propulsion systems group, the main regression variable. In addition to weight the user needs to estimate several other factors. Those include profit margin, growth margin (this accounts for the increase in weight over a craft’s lifecycle), labor rate. The costs are then summed to develop a lead ship cost estimate. Cash flows for the program are then developed using a build schedule, a discount rate curve (based on US Treasury securities), and a learning curve. Once these cash flows are discounted to present dollars they can be summed to create a total fleet acquisition cost. It should be noted that the CERs used in this tool are based on larger ship costs. However, the ship complexity factor was adjusted to account for this fact. Once this was done cost results approximated the acquisition cost of the Mark V SOC, the baseline vehicle for this project.

After all the analysis modules were developed, all the relevant variables and metrics of interest were displayed in dashboard tool that allows users to define a craft parametrically and evaluate its performance with respect to the metrics.

Conclusions

Once the analysis modules were integrated correctly, the analysis phase began. The magnetic signature of the craft behaved curiously at shallow depths. Because of the distinct onboard systems, the signature at shallow depths (~1-10 ft) had distinct peaks. However, as the distance between the mine and the craft increases, the peaks become less and less pronounced, until the individual components onboard are indistinguishable and the craft looks like a point source. This is an interesting result because, while a far distances the shipboard system placement is irrelevant, at shorter distances system placement can be used to modify the craft signature.

The team ran several Latin Hypercube (LHC) design of experiments varying different sets of parameters. Two different sets of parameters were considered. The first consisted of the craft definition, including performance requirements and onboard system permeabilities and acoustic parameters. From this set of data it became obvious that mission requirements, especially craft speed, range, and geometric requirements, were the main drivers of the craft signature. The reason for this was mainly because as any of these requirements varied, the engine size varied. A higher craft speed requires bigger engines. A craft with a increased range requires more fuel, and hence a larger craft. The larger craft encounters more resistance as it moves through the water, and therefore requires larger engines to provide the required speed. Another important signature driver was the magnetic permeability of the engines. The other onboard components did not contribute as significantly to the magnetic signature. It is important to note that because most current small littoral craft have non ferrous hulls, all the analysis done using the integrated tool assumed non ferrous hulls.

The second LHC the team ran varied the mine parameters. The reason this set of experiments was separated from the previous was because changes in the mine parameters could not be distinguished from changes in the craft. For example, if the same craft is paired with two different mines, one with a high actuation threshold and one with a low actuation threshold, the actuation depths and widths will be different, even though the craft signature is identical. Similarly, the craft and mines can be varied in such a way as to have a constant actuation depth and width, even though the craft signatures are different. Because of this confounding, the two sets of parameters were varied separately. Changing the magnetic threshold lead to expected results. As the threshold increased, the firing width decreased. However, at higher thresholds there were some unexpected results at lower depths due to the peaked nature of the signature. Because mine actuation is dependent on the magnetic field as well as the time rate of change of the magnetic field, at lower depths mines with higher actuation thresholds would not actuate. In the same way, as the derivative threshold was varied, the actuation status was very dependent on signature peaks at shallow depths.

There are several other types of experiments and sensitivity studies that can be performed using the integrated modules. These include varying the craft environment or evaluated a craft in a given mine field and varying mine field parameters. In the future, further development is needed to evaluate craft operations and deperming effects. In addition, each module in the tool can be either modified or replace to allow for higher fidelity analysis.

Publications

  • Simmons, David. "Creation and Implementation of an Acoustic Signature Module in Mined Littoral Environments." Special Topic. Georgia Institute of Technology, Spring 2011.