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The airworthiness authorities (FAA, JAA, Transport Canada) will be releasing a draft rule in the 2006 timeframe concerning the operation of aircraft in a Supercooled Large Droplet (SLD) environment aloft. The draft rule will require aircraft manufacturers to demonstrate that their aircraft can operate safely in an SLD environment for a period of time to facilitate a safe exit from the condition. It is anticipated that aircraft manufacturers will require a capability to demonstrate compliance with this rule via experimental means (icing tunnels or tankers) and by analytical means (ice prediction codes). Since existing icing research facilities and analytical codes were not developed to account for SLD conditions, current engineering tools are not adequate to support compliance activities in SLD conditions. Therefore, existing capabilities need to be augmented to include SLD conditions.

An overview of enrollment trends and curricular changes in engineering education in the past ten years. Comments are made about the implications of lower enrollment on quality of education and availability of engineers for the employment market. Discussions of curricular variations summarizes changes such as computerization of engineering studies, expansion of high school preparation, and selection of major studies for students.

The Icing Research Tunnel at NASA Glenn follows the recommended practice for calibration outlined in SAE’s ARP5905. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within the stated specifications of variation within +/- 10% of the curve fit equation generated from calibration data. Using past measurements and data trends, IRT characterization engineers wanted to develop methods for the ability to know when data were not within variation. Trends can be observed in the liquid water content measurement process by constructing statistical process control charts. This paper describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, process for rejection of data, and construction of control charts.

Beginning flight students were taught landings in a flight simulator with a visual landing display to examine the effects of scene detail, visual augmented guidance, and the number of landing training trials. Transfer as assessed in a criterion simulator configuration showed advantages for larger numbers of training trials, visual augmented guidance, and moderate scene detail. Transfer of training to the aircraft showed advantages for low-scene detail over moderate-scene detail for the number of landing training sessions. Subjects who received equal simulator time practicing an instrument pattern (control group) performed better than the moderate-scene detail group on student assisted landings and number of landing training sessions.

A high-fidelity simulation model for icing effects flight training was developed from wind tunnel data for the DeHavilland DHC-6 Twin Otter aircraft. First, a flight model of the un-iced airplane was developed and then modifications were generated to model the icing conditions. The models were validated against data records from the NASA Twin Otter Icing Research flight test program with only minimal refinements being required. The goals of this program were to demonstrate the effectiveness of such a simulator for training pilots to recognize and recover from icing situations and to establish a process for modeling icing effects to be used for future training devices.

The removal of over 40 toxic compounds, including heavy metals, synthetic pesticides and organic compounds, by cellulose acetate (CA) and crosslinked-polyethylenimine (C-PEI) membranes were examined. With few exceptions both membranes removed 97+ percent of the heavy metals and pesticides tested; the C-PEI membrane was found to be somewhat more effective than the CA membrane. In addition, the C-PEI membrane removed 70+ percent of 13 of the 19 organic compounds tested; only two compounds were removed less than 50 percent. In contrast, however, the CA membrane removed less than 50 percent of 16 of the 19 organic compounds tested, and three compounds were found to exhibit negative removal. The ability of C-PEI membrane to remove organic compounds and its resistance to high temperature and pH have made reverse osmosis an effective separation process for the removal of toxic compounds from water.

To support NASA's goal to improve aviation safety, the Aircraft Icing Project of the Aviation Safety Program has developed a number of education and training aids for pilots and operators on the hazards of atmospheric icing. A review of aircraft incident and accident investigations has revealed that flight crews have not always understood the effects of ice contamination on their aircraft. To increase this awareness, NASA has partnered with regulatory agencies and pilot trade organizations to assure relevant and practical materials that are focused toward the intended pilot audience. A number of new instructional design approaches and media delivery methods have been introduced to increase the effectiveness of the training materials by enhancing the learning experience, expanding user interactivity and participation, and, hopefully, increasing learner retention rates.

From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.

Air source heat pumps as the heating system for full electric vehicles are drawing more and more attention in recent years. Despite the high energy efficiency, frost accumulation on the heat pump evaporator is one of the major challenges associated with air source heat pumps. The evaporator needs to be actively defrosted periodically and heat pump heating will be interrupted during defrosting process. Proper defrost control is needed to obtain high average heat pump energy efficiency. In this paper, a new method for generating air source heat pump defrost control policy using reinforcement learning is introduced. This model-free method has several advantages. It can automatically generate optimal defrost control policy instead of requiring manually determination of the control policy parameters and logics.

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The microstructure of impact ice has been shown to correlate with the adhesion strength of ice. Machine vision techniques are explored as a method of decreasing analysis time. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods.

NASA is developing and validating technology to incorporate aircraft icing effects into a flight training device concept demonstrator. Flight simulation models of a DHC-6 Twin Otter were developed from wind tunnel data using a subscale, complete aircraft model with and without simulated ice, and from previously acquired flight data. The validation of the simulation models required additional aircraft response time histories of the airplane configured with simulated ice similar to the subscale model testing. Therefore, a flight test was conducted using the NASA Twin Otter Icing Research Aircraft. Over 500 maneuvers of various types were conducted in this flight test. The validation data consisted of aircraft state parameters, pilot inputs, propulsion, weight, center of gravity, and moments of inertia with the airplane configured with different amounts of simulated ice.

Smoke transport and detection were modeled numerically in the ISS Destiny module using the NIST, Fire Dynamics Simulator code. The airflows in Destiny were modeled using the existing flow conditions and the module geometry included obstructions that simulate the currently installed hardware on orbit. The smoke source was modeled as a 0.152 by 0.152 m region that emitted smoke particulate ranging from 1.46 to 8.47 mg/s. In the module domain, the smoke source was placed in the center of each Destiny rack location and the model was run to determine the time required for the two smoke detectors to alarm. Overall the detection times were dominated by the circumferential flow, the axial flow from the intermodule ventilation and the smoke source strength.

During the NASA/FAA Tailplane Icing Program, pilot evaluations of aircraft flying qualities were conducted with various ice shapes attached to the horizontal tailplane of the NASA Twin Otter Icing Research Aircraft. Initially, only NASA pilots conducted these evaluations, assessing the differences in longitudinal flight characteristics between the baseline or clean aircraft, and the aircraft configured with an Ice Contaminated Tailplane (ICT). Longitudinal tests included Constant Airspeed Flap Transitions, Constant Airspeed Thrust Transitions, zero-G Pushovers, Repeat Elevator Doublets, and, Simulated Approach and Go-Around tasks. Later in the program, guest pilots from government and industry were invited to fly the NASAT win Otter configured with a single full-span artificial ice shape attached to the leading edge of the horizontal tailplane.

Research in microgravity (low-gravity) combustion promises innovations and improvements in fire prevention and response for human-crew spacecraft. Findings indicate that material flammability and fire spread in microgravity are significantly affected by atmospheric flow rate, oxygen concentration, and diluent composition. This information can lead to modifications and correlations to standard material-assessment tests for prediction of fire resistance in space. Research on smoke-particle changes in microgravity promises future improvements and increased sensitivity of smoke detectors in spacecraft. Research on fire suppression by extinguishing agents and venting can yield new information on effective control of the rare, but serious fire events in spacecraft.

Understanding the aerodynamic impact of swept-wing ice accretions is a crucial component of the design of modern aircraft. Computer-simulation tools are commonly used to approximate ice shapes, so the necessary level of detail or fidelity of those simulated ice shapes must be understood relative to high-fidelity representations of the ice. Previous tests were performed in the NASA Icing Research Tunnel to acquire high-fidelity ice shapes. From this database, full-span artificial ice shapes were designed and manufactured for both an 8.9%-scale and 13.3%-scale semispan wing model of the CRM65 which has been established as the full-scale baseline for this swept-wing project. These models were tested in the Walter H. Beech wind tunnel at Wichita State University and at the ONERA F1 facility, respectively. The data collected in the Wichita St.

Aerodynamic assessment of icing effects on swept wings is an important component of a larger effort to improve three-dimensional icing simulation capabilities. An understanding of ice-shape geometric fidelity and Reynolds and Mach number effects on iced-wing aerodynamics is needed to guide the development and validation of ice-accretion simulation tools. To this end, wind-tunnel testing was carried out for 8.9% and 13.3% scale semispan wing models based upon the Common Research Model airplane configuration. Various levels of geometric fidelity of an artificial ice shape representing a realistic glaze-ice accretion on a swept wing were investigated. The highest fidelity artificial ice shape reproduced all of the three-dimensional features associated with the glaze ice accretion. The lowest fidelity artificial ice shapes were simple, spanwise-varying horn ice geometries intended to represent the maximum ice thickness on the wing upper surface.

This research compares the responses of a vehicle modeled in the 3D vehicle simulation program SIMON in the HVE simulation operating system against instrumented responses of a 3-axle tractor, 2-axle semi-trailer combination. The instrumented tests were previously described in SAE 2001-01-0139 and SAE 2003-01-1324 as part of a continuous research effort in the area of vehicle dynamics undertaken at the Vehicle Research and Test Center (VRTC). The vehicle inertial and mechanical parameters were measured at the University of Michigan Transportation Research Institute (UMTRI). The tire data was provided by Smithers Scientific Services, Inc. and UMTRI. The series of tests discussed herein compares the modeled and instrumented vehicle responses during quasi-steady state, steady state and transient handling maneuvers, producing lateral accelerations ranging nominally from 0.05 to 0.5 G's.

A new Aircraft Accident Awareness Program (AAAP) was developed, evaluated, and is available to emergency response service provider organizations (firefighters, emergency medical technicians, trauma center personnel, law enforcement, clergy, coroners, and media) who would be called to an aircraft accident scene. Aircraft accident responder training is a critical factor in accident victim crash survivability and successful life-safety outcomes. This program was designed to teach participants about the unique conditions and safety hazards associated with aircraft crashes. A blend of academic classroom investigation, exposure to airworthy/ unairworthy aircraft including operating systems and components, computer accident simulations, “hands-on” (destructive) extrication protocol training, and participation in simulated in-the-field accident scenarios was used as an instructional delivery model.

JSC-1A lunar simulant has been applied to AZ93 and AgFEP thermal control surfaces on aluminum substrates in a simulated lunar environment. The temperature of these surfaces was monitored as they were heated with a solar simulator using varying angles of incidence and cooled in a 30 K coldbox. Thermal modeling was used to determine the solar absorptivity (a) and infrared emissivity (e) of the thermal control surfaces in both their clean and dusted states. It was found that even a sub-monolayer of dust can significantly raise the α of either type of surface. A full monolayer can increase the α/ε ratio by a factor of 3–4 over a clean surface. Little angular dependence of the α of pristine thermal control surfaces for both AZ93 and AgFEP was observed, at least until 30° from the surface. The dusted surfaces showed the most angular dependence of α when the incidence angle was in the range of 25° to 35°.

This paper reports a meta analysis of all studies located in the literature that have compared head up versus head down display of equivalent information, as these displays support both tracking (e.g., flight path control) and discrete event detection. The data clearly indicate a HUD advantage for most tasks, except tracking during cruise flight and event detection during final approach. The latter HUD cost however is observed only when events to be detected are entirely unexpected, reflecting a form of cognitive tunneling. The meta-analysis also reveals an advantage for conformal over non-conformal HUD imagery.