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Technical Paper

Fuselage and Wing Weight of Transport Aircraft

1996-10-01
965583
A method of estimating the load-bearing fuselage weight and wing weight of transport aircraft based on fundamental structural principles has been developed. This method of weight estimation represents a compromise between the rapid assessment of component weight using empirical methods based on actual weights of existing aircraft, and detailed, but time-consuming, analysis using the finite element method. The method was applied to eight existing subsonic transports for validation and correlation. Integration of the resulting computer program, PDCYL, has been made into the weights-calculating module of the AirCraft SYNThesis (ACSYNT) computer program. ACSYNT has traditionally used only empirical weight estimation methods; PDCYL adds to ACSYNT a rapid, accurate means of assessing the fuselage and wing weights of unconventional aircraft.
Technical Paper

Lunar Base Life Support Failure Analysis and Simulation

2009-07-12
2009-01-2482
Dynamic simulation of the lunar outpost habitat life support was undertaken to investigate the impact of life support failures and to investigate possible responses. Some preparatory static analysis for the Lunar Outpost life support model, an earlier version of the model, and an investigation into the impact of Extravehicular Activity (EVA) were reported previously. (Jones, 2008-01-2184, 2008-01-2017) The earlier model was modified to include possible resupply delays, power failures, recycling system failures, and atmosphere and other material storage failures. Most failures impact the lunar outpost water balance and can be mitigated by reducing water usage. Food solids and nitrogen can be obtained only by resupply from Earth. The most time urgent failure is a loss of carbon dioxide removal capability. Life support failures might be survivable if effective operational solutions are provided in the system design.
Technical Paper

Planning Dynamic Simulation of Space Life Support

2009-07-12
2009-01-2493
Dynamic modeling and simulation of recycling space life support is necessary to determine processing rates, buffer sizes, controls, and other aspects of systems design. A common approach is to develop an overall inclusive model that reflects nominal system operation. A full dynamic simulation of space life support represents many system elements in an inclusive model, but it cannot and should not include everything possible. A model is a simplified, partial, mathematical representation of reality. Including unnecessary elements makes the model complex, costly, and confusing. Models are built to help understand a system and to make predictions and decisions about it. The best and most useful models are developed to answer specific important questions. There are many possible questions about life support design and performance. Different questions are best answered by different models. Static spreadsheet analysis is a good starting point.
Technical Paper

Innovative Concepts for Planetary EVA Access

2007-07-09
2007-01-3245
This study introduces several new concepts for suited EVA astronaut ingress/egress (departure and return) from a pressurized planetary surface habitat, based on use of a rear-entry suit and a suit lock or suitport. We provide insight into key operational aspects and integration issues, as well as the results of a requirements analysis and risk assessment of the concepts. The risk assessment included hazard analysis, hazard mitigation techniques, failure mode assessment, and operational risk assessment. Also included are performance and mass estimates for the egress concepts, and concepts for integration of the egress concepts with potential planetary habitat designs.
Technical Paper

Integrated Use of Data Mining and Statistical Analysis Methods to Analyze Air Traffic Delays

2007-09-17
2007-01-3836
Linear regression is the primary data analysis method used in the development of air traffic delay models. When the data being studied does indeed have an underlying linear model, this approach would produce the best-fitting model as expected. However, it has been argued by ATM researchers [Wieland2005, Evans2004] that the underlying delay models are primarily non-linear. Furthermore, the delays being modeled often depend not only on the observable independent variables being studied but also on other variables not being considered. The traditional regression approach alone may not be best suited to study these type of problems. In this paper, we propose an alternate methodology based on partitioning the data using statistical and decision tree learning methods. We then show the utility of this model in a variety of different ATM modeling problems.
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