Search Results

Aviation training has remained largely untouched by decades of development in cognitive science. In aviation, people must be trained to perform complicated tasks and make good operational decisions in complex dynamic environments. However, traditional approaches to professional aviation training are not well designed to accomplish this goal. Aviation training has been based mainly on relatively rigid classroom teaching of factual information followed by on-the-job mentoring. This approach tends to compartmentalize knowledge. It is not optimal for teaching operational decision-making, and it is costly in time and personnel. The effectiveness of training can be enhanced by designing programs that support the psychological processes involved in learning, retention, retrieval, and application. By building programs that are informed by current work in cognitive science and that utilize modern technological advances, efficient training programs can be created.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

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.

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.

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.

How much integrated system level test should be performed on a spacecraft before it is launched? Although sometimes system test is minimized, experience shows that systems level testing should be thorough and complete. Reducing subsystem testing is a less dangerous way to save cost, since it risks finding problems later in system test, while cutting systems test risks finding them even later on orbit. Human-rated spacecraft test planning is informal, subjective, and inconsistent, and its extent is often determined by the decision maker's risk tolerance, decision-making style, and long-term or short-term view. Decisions on what to test should be guided by an overall mission cost-benefit analysis, similar to the risk analysis used to guide development efforts.

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.

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.