7 resultados para Naval aviation

em Deakin Research Online - Australia


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Naval training communities use a systems approach to training. This study considers the question "what is effectiveness in naval training?" Instructor courses of five navies were observed and naval instructors surveyed. Conclusions and recommednations are drawn from the data. It is proposed that most problems of effectiveness identified can be overcome without investment in technology or significant system changes.

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Details the operations of the Victorian Navy for the period 1883 to 1886, including information on ships, training, stores, list of officers on the active and unattached list, list of ships including their armament, and the regulations under which the navy ran.

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This paper describes a novel discrete event simulation (DES) methodology for the evaluation of aviation training tenders where performance is measured against “best performance” criteria. The objective was to assess and compare multiple aviation training schedules and their resource allocation plans against predetermined training objectives. This research originated from the need to evaluate tender proposals for the Australian Defence Aviation Training School that is currently undergoing aviation training consolidation and helicopter rationalization. We show how DES is an ideal platform for evaluating resource plans and schedules, and discuss metric selection to objectively encapsulate performance and permit an unbiased comparison. DES allows feasibility studies for each tender proposal to assure they satisfy system and policy constraints. Consequently, to create an objective and fair environment to compare tendered solutions, what-if scenarios have been strategically examined to consider improved implementations of the proposed solutions.

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This paper describes a multi-level system dynamics (SD) / discrete event simulation (DES) approach for assessing planning and scheduling problems within an aviation training continuum. The aviation training continuum is a complex system, consisting of multiple aviation schools interacting through interschool student and instructor flows that are affected by external triggers such as resource availability and the weather.
SD was used to model the overall training continuum at a macro level to ascertain relationships between system entities. SD also assisted in developing a shared understanding of the training continuum, which involves constructing the definitions of the training requirements, resources and policy objectives. An end-to-end model of the continuum is easy to relate to, while dynamic visualisation of system behaviour provides a method for exploration of the model.
DES was used for micro level exploration of an individual school within the training continuum to capture the physical aspects of the system including resource capacity requirements, bottlenecks and student waiting times. It was also used to model stochastic events such as weather and student availability. DES has the advantage of being able to represent system variability and accurately reflect the limitations imposed on a system by resource constraints.
Through sharing results between the models, we demonstrate a multi-level approach to the analysis of the overall continuum. The SD model provides the school’s targeted demand to the DES model. The detailed DES model is able to assess schedules in the presence of resource constraints and variability and provide the expected capacity of a school to the high level SD model, subjected to constraints such as instructor availability or budgeted number of training systems. The SD model allows stakeholders to assess how policy and planning affect the continuum, both in the short and the long term.
The development of this approach permits moving the analysis of the continuum between SD and DES models as appropriate for given system entities, scales and tasks. The resultant model outcomes are propagated between the continuum and the detailed DES model, iteratively generating an assessment of the entire set of plans and schedule across the continuum. Combining data and information between SD and DES models and techniques assures relevance to the stakeholder needs and effective problem scoping and scaling that can also evolve with dynamic architecture and policy requirements.
An example case study shows the combined use of the two models and how they are used to evaluate a typical scenario where increased demand is placed on the training continuum. The multi-level approach provides a high level indication of training requirements to the model of the new training school, where the detailed model indicates the resources required to achieve those particular student levels.