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Cost, Schedule, And Performance Elements For Comparison of Hydrodynamic Models of Near-Surface Unmanned Underwater Vehicle Operations.
| 题名： | Cost, Schedule, And Performance Elements For Comparison of Hydrodynamic Models of Near-Surface Unmanned Underwater Vehicle Operations. |
| 作者： | Bartnicki, R.; Bell, A.; Bolen, M.; Rice, N.; Zirkelbach, A. |
| 关键词： | Unmanned underwater vehicles, Acquisition, Decision making, Investment, Computer programs, Costs, Performance(engineering), Scheduling, Military acquisition, Graphical user interface, Application software, Spreadsheet software, Operating systems, Systems engineering, Hydrodynamics, Decision support systems, Software fidelity, Software acquisition, Software cost, Decision support framework, Large amplitude motion program |
| 摘要： | As emerging technology spurs new requirements for the development and acquisition of increasingly advanced military platforms, the defense acquisition community needs a comprehensive decision-support framework to make informed investment decisions for software selection. Through a determination of key characteristics that form the basis of a decision process, this report outlines a framework for software selection that includes cost, schedule, and performance considerations. Furthermore, the resultant software selection criteria are subject to a practical demonstration to compare the following software packages that predict hydrodynamic loads: Standard Ship Motion Program (SMP), SUBMOT, Aegir, and Large Amplitude Motion Program (LAMP). The creation of a uniform set of simulation input data, for use with these four candidate software packages, details this selection process. We present a comparison of the software-generated data with experiment data gathered from tow tank trials as an analysis of tradeoffs between cost, schedule, performance, and simulation fidelity. The practical demonstration showed that Aegir and LAMP were more labor-intensive than the other software packages and that Aegir and LAMP simulation results were typically closer to the scale model experiment results. Resulting recommendations include decision-support framework application and fidelity analysis prior to software selection for most effective program support. |
| 报告类型： | 科技报告 |
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