Planning And Decision Support In Minefield Scenarios Through Simulation
John Marco; Warren Reid; Hai Hoang Tran; Craig Flockhart
Defence Science and Technology Organisation
Abstract. Setting a course through a known mine field is potentially a hazardous operation when little or no knowledge is available of the possible consequences to the ship structure, equipment and personnel on board. Techniques are being developed using a combination of field trials and numerical methods to predict the behaviour of the total ship system when subjected to an underwater shock. A vulnerability knowledge database using the outputs from these techniques can then be produced, which inturn can be accessed for planning and decision support by the Naval personnel during training or operational scenarios. This paper will describe the techniques used to build a knowledge database for any feasible encounter between a naval ship and an exploding underwater mine in the far field environment. The paper will also demonstrate how the knowledge database can be used in a simple simulation of a ship-mine warfare scenario.
- INTRODUCTION
Planning of a specific mine hunting mission can be enhanced through training in a simulated mine warfare environment providing an edge to Navy. A simulated conflict environment would provide naval personnel with a technique to enhance their understanding of the vulnerability of a ship system, including the structure, equipment and personnel, when loaded by any underwater shock, Figure 1. Through this understanding of the ship system response, decisions based on known consequences of actions can be made in relation to pursuing a particular course through or around a minefield.
2.ASSESSMENT TOOLS AND TECHNIQUES
Numerical finite element methods [1] provide a capability to assess the dynamic response of a ship structure when subjected to an underwater shock loading, Figure 2.
The ship structure needs to be modelled to a spatial resolution, such that, it includes all the major structural geometry and mass distribution aspects of the ship for the scenario being investigated.
The fluid model domain surrounding the ship structure needs to be of a sufficient size and element mesh density such that, it can accurately transmit the shock loading through the fluid elements and load the wetted surface of the ship’s hull structure.
A numerical representation of the far-field shock load also needs to be applied to the outer surface of the fluid model, Figure 3. This load propagates through the fluid elements, then onto the ship’s hull structure and then up through the ship superstructure, causing it to oscillate based upon the level of the shock load and stiffness of the vessel.
The stresses that are developed within the ship structure can be compared with known limiting material values, in order to assess the probability of whether the material has survived, failed or its integrity is uncertain.
In the case of equipment and human response, the numerical modeling of the ship structure can only predict the base motion response at their location. However, by applying the Shock Response Spectra method, this information can then be compared with experimental data, Figure 4, to determine the probability [2] that the onboard equipment or human has survived, failed or its damage level is uncertain.
This process can be repeated to cover all feasible ship mine encounters, thus covering a range of charge sizes, depths and ship-mine relative locations, Figure 5.
Full-scale ship shock trials are a necessary part of this process, because they provide an invaluable means of validating a limited number of the scenarios, thus providing some confidence in the predictions for other ship-charge scenario being made.
3.VULNERABILITY DATABASE
Upon completion of all the numerical analyses, a vulnerability database can be assembled from the results of the numerical modeling. These results summarize the probability of each identified ship component (ie ship structure, onboard equipment and personnel), surviving a range of underwater ship-mine encounters (viz charge/vessel scenario details).
Table 1 shows for a single ship component, within the total ship system, the stand-off distance for survivability of that component, when it is subjected to the far-field shock load from a single charge at a range of mine depths.
In this example of a vulnerability database, the probability of survival for the ship component is categorised into one of three fields; pass, fail or uncertain. As an example, consider the mine at a depth of 50 m in Table 1. If the ship had a stand-off distance more than 40 m from the charge, the component will survive the shock load, were the charge to detonate. However, if the stand-off distance is less than 35 m, the component will not survive. If the ship had a stand-off distance between 35 m and 40 m, it is uncertain as to whether the component will survive.
Table 1. Idealised Vulnerability Database
Charge Size 200 Kg
An Item Of Equipment or Part Of A Structure
Charge Depth (m)Ship Stand-off (m)PassFail
25>50<40
50>40<35
100>30<25
4.NAVAL APPLICATION
Navy can use this vulnerability database for both training and for operational scenarios. The database would provide the personnel onboard a ship with the capability of assessing how the structure, equipment and crew are likely to respond when an underwater explosion occurrs in the vicinity of the ship.
For example, the vulnerability database could be incorporated in a simple interactive computer training simulation of a mine warfare scenario environment. The database is not restricted to computer-based simulation software and virtual ships; it can also be included on board an actual ship by integrating it into the ship data information system. In this case the database becomes part of an overall ship management system.
5.TRAINING SIMULATION SOFTWARE
As an example, a simple interactive real time software simulation package was developed to show how the vulnerability database might be used. The software models the main basic functions of a generic mine hunting ship. The scenario simulation components included in the software are,
(i)the coastline,
(ii)seabed topography,
(iii)size, mass and location of both mine and non mine objects,
(iv)ship functions including speed, heading and sonar control,
(v)remotely operated vehicle (ROV) functions including speed, heading and sonar control ,
(vi)the vulnerability database of all identified ship components for a given ship, and
(vii)time.
Figure 6 shows a typical snapshot in time of a screen image during a mock simulation. Highlighted are six windows, identified as,
(i)ROV camera,
(ii)ROV sonar map,
(iii)ship course/speed,
(iv)ship sonar map,
(v)message report and
(vi)the ship route map.
An additional window, called SEES, shown in Figure 7, is the application of the vulnerability database function within the simulation scenario. This window overlays the ROV windows when called into the simulation. All of the above features and window displays are available for assessment and interaction by the operator during the real time simulation.
Figure 7 shows the results of the use of the vulnerability database within the simulation. The display highlights the survivability of selected components (i.e. console, gearbox, drive shaft, etc) on board the ship. This feature within the simulation is simply a module that is called upon by the operator as required during the simulation. The vulnerability database interacts with the sonar module (i.e. to obtain ship-charge relative distances) in order to produce a coloured (i.e. red, grey and green) real time display of the survivability status for each component identified in the window. These components, structure, equipment and personnel are displayed in the simulation after they are identified by the operator. In the window, each component is displayed as a separate horizontal coloured bar graph.
The vulnerability bar graph of the SEES window shows red, grey and green regions indicating the status of an item, if at that point in time a mine in the vicinity of the ship were to explode. These regions will vary in length and move left and right across the window during the simulation, indicating the position of the ship relative to the mine. The colour region next to the right hand side of the window will identify the vulnerability status of the item.
The presence of a green region for a component indicates that the stand-off distance between charge and ship is large enough not to cause any damage. Whereas, if the bar graph showed only red and grey, the survivability of the component is considered to be uncertain because the calculations are not conclusive at this stand off distance. Finally, if the bar graph showed only red for the component, it will fail if the charge detonated. The physical horizontal length of each portion of the red, grey and green colours on the bar graph will change with time during the simulation reflecting the proximity of the ship to the charge.
6.CONCLUSIONS
The techniques described and the example shown in this paper illustrate how the vulnerability database of a ship structure, equipment and personnel can be used to manage threat scenarios based upon performance capabilities of these components.
The use of complementary numerical modeling and field trials can produce a vulnerability database for a range of components within a ship system when subjected to any far-field underwater explosion.
This vulnerability database can be added to mine warfare training simulations to include the consequences of mine detonation on the ship and its systems. By this means the training of naval personnel can include risk assessment in the achievement of mission goals.
REFERENCES
- Marco, J. et al.(1999) ”Development of the Finite Element Models for the Minehunter Coastal Ship Structure and the Explosive Loading Cases for Underwater Explosive Studies”, DSTO-GD-0150.
- Reid, W., et al. (1999) “Calibration of a Shock Platform for Testing COTS Equipment”, DSTO-TR-0776.
Figure 1Ship Structure Subjected to an Underwater Explosion
Figure 2Finite Element Model of a Ship and Fluid
Figure 3Schematic of a Generic Shock Loading Profile
Figure 4Equipment Modelling and Survivability Assessment Using the Shock Response Spectra method
Figure 5Range of Feasible Ship Mine Encounters for Analysis
Figure 6Simulation Modules for Operator Interaction
Figure 7Vessel Database Implementation in the Simulation