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All ordnance systems must be classified for hazards that are often coupled with insensitive munitions in order to lower development costs and ensure that the ordnance performs as intended, but are less prone to violent reaction when subjected to external hazards. Traditionally, large-scale liquid hydrocarbon pool fire, often referred to as the fast-cook-off test, raises the ordnance temperature very quickly and evaluates how it reacts when engulfed in fire. Currently, the liquid fuel external fire is used to determine the type of reaction and time to reaction of the ordnance when exposed to a thermal insult. The test requires the complete ordnance package be completely engulfed within a liquid pool fire. The allowable hydrocarbons fuels have relatively high soot yields and therefore generate highly-radioactive thermal environments to objects immersed within the fire plume. There has been an international push to develop alternative fuel fire exposures due to lack of control over the current fire scenario and the environmental implications associated with the hydrocarbon pool fire. The alternative methods are more environmentally sustainable than the baseline test method, produce less soot, do not use HAPs, and pose a lower risk for occupational and environmental exposures. This report summarizes alternative fuel fire exposures and additional benefits over the existing liquid fuel fire exposure. The benefits considered in this work were with respect to cost of operation, added control over exposure, and environmental impact.

The collaborative work of Hughes Associates, Inc. (HAI), the Naval Research Laboratory (NRL) and a group at Mississippi State University resulted in developing a simulation system including Graphical User Interface (GUI) and Visualization. The simulation environment provides a runtime environment for a third-party simulation package, Fire and Smoke Simulation (FSSIM) developed by HAI. This updated user's manual for the viewer provides documentation of the GUI layout and detailed discussion of features of the output display. This revision allows ships with aluminum infrastructure and allows the user to load out compartments for generic use types fuel load., The original document contains color images. Prepared in collaboration with Miss State Univ., under contract no. N00173-07-2-C008, Hughes Assoc. Inc., under contract no. N00173-05-C-2009, and Nova Research Inc.

New ship manning concepts have resulted in new demands and changing roles for personnel assigned to damage control. The changing force structure requires that designers and operators understand the capabilities of damage control teams. This includes the design, equipment, and doctrinal requirements needed for an acceptable level of ship recoverability. Limited formal structures and validated methods for assessing such capabilities exist. Methods to assess readiness and training requirements suffer from a lack of quantitative or validated approaches. This paper describes the use of manned damage control modeling techniques and readiness assessments to provide a more rational basis to assess damage control manning., Prepared in collaboration with Hughes Associates, Inc. Baltimore, MD.

Several computational tools exist for examining fire effects that can be applied to a ship and its crew. Hand calculations can be used to examine simple scenarios in single compartments. Zone models are also suitable for more complex, time-dependent scenarios involving multiple compartments and levels, but stability can be a problem for multilevel scenarios, scenarios with Heating, Ventilation, and Air Conditioning (HVAC) systems, and for post-flashover conditions. Computational fluid dynamics (CFD) models can yield detailed information about temperatures, heat fluxes, and species concentrations; however, the time penalty of this approach currently makes using CFD unfeasible for long periods of real time or large computational domains. Another class of models has traditionally played supporting roles in fire modeling. This class is constituted by a variety of network models, which are used for ventilation systems in buildings or fluid flow in piping networks. These models lack specific physics required for fire modeling. Therefore, to meet the computational speed and algorithm requirements, it was decided to develop Fire and Smoke Simulator (FSSIM) as a network fire model. This document (User's Guide) discusses creation of FSSIM input files, including guidance in transforming a prototype structure to a network representation, and explains the available outputs., Prepared in collaboration with Hughes Associates, Inc., Baltimore, MD and ITT Industries, Advanced Engineering Sciences, Alexandria, VA.

There currently exists a number of computational tools for examining the effects of a fire that can be applied to a ship and its crew. One could use hand calculations for examining simple scenarios in single compartments. Simple rules can be used to extend this approach to multiple compartments. Zone models are suitable for examining somewhat more complex, time-dependent scenarios involving multiple compartments and levels, but stability can be a problem for multi-level scenarios with Heating, Ventilation, and Air Conditioning (HVAC) systems, and for post- flashover conditions. Computational fluid dynamics (CFD) models can yield detailed information about temperatures, heat fluxes, and species concentrations; however, the time penalty of this approach currently makes using CFD unfeasible for long periods of real time or large computational domains. There is another class of models that have traditionally played supporting roles in fire modeling. This class is constituted by a variety of network models, which are used for ventilation systems in buildings or fluid flow in piping networks. These models, however, lack specific physics required for fire modeling. To meet the computational speed and algorithm requirements, it was decided to develop Fire and Smoke Simulator (FSSIM) as a network fire model. This document (Theory Manual) describes the equations solved, and the solution algorithm for the heat and mass transfer along with the equations and algorithms for FSSlM sub-models.