• Dependency-based collaborative design: a comparison of modeling methods

      Drabble, Brian (2015-08-10)
      The ability to provide support to a group of designers, analysts and other users who are collaborating on an evolving design requires the dual capabilities of managing options for an individual designer while at the same time managing the dependencies between different sets of designer's options. For example, if designer A is creating a design for a helicopters hydraulics system and this is dependent on electrical power (EP) from a sub-system from designer B then how can the workflows, decisions and options of the two designers be managed so that each can understand the implications of their own design decisions and more importantly the implications and design decisions they force on others? The proposed CAPS system employs two dependency reasoning engines: one handles quantitative values and other qualitative ones. The quantitative engine can identify that a motor with an output of 3000 rpm allows a generator to output 100 V or that a hydraulic pump is dependent on the 240v output of the motor. Alternatively, the qualitative engine could rule out several motors options if the overall design state that the weight of a helicopter's transmission needs to be comparable to that of the engine or the positioning of a sensor makes it susceptible to an EM process that could affect its function. A mapping capability is provided allowing analysis to be passed between the two engines. Three different types of dependency-based quantitative engine designs have been developed and evaluated. The first quantitative engine design focuses on modeling components at their output level and propagating level values from component to component, component to sub-system, etc. The second quantitative engine design focuses on modeling components at the node level so as to identify key components, sub-systems, etc. in terms of their overall dependency to the design. The third engine employs a hybrid of the previous two approaches and was identified through feedback from designers. These engines are designed to be complimentary with the node-based and hybrid approaches being used to identify the key capabilities and dependencies of the design. The output-based approach is then used to explore in greater detail the outputs and dependencies of the components and sub-systems identified as key via the node/hybrid-based approach. The proposed CAPS architecture has been initially evaluated against a large collaborative design task involving the design of a helicopter's electrical, hydraulic, structural and mechanical systems.
    • Modeling C2 Networks as Dependencies: Understanding What the Real Issues Are

      Drabble, Brian (2014)
      This chapter describes an approach to modeling C2 and other types of networks as a series of nodes (people, groups, resources, locations, concepts, etc.). The nodes are linked by one or more weighted arcs describing the type and the strength of the dependency that one node has on another node. This model allows analysts to identify the most important nodes in a network in terms of their direct and indirect dependencies and to rank them accordingly. The same model also supports consequence analysis in which the direct, indirect, cascading, and cumulative effects of changes to node capabilities can be propagated across the networks. The chapter describes the basic modeling technique and two types of dependency propagation that it supports. These are illustrated with two examples involving the modeling and reasoning across insurgent networks and an Integrated Air Defense System. These show how aspects of the networks can be analyzed and targeted. Details are also provided on the mechanisms to link the analysis to a planning system through which plans can be developed to bring about desired effect(s) in the networks.