Airborne Four-Dimensional Flight Management in a Time-based Air Traffic Control Environment

Advanced Air Traffic Control (ATC) systems are being developed which contain time-based (4D) trajectory predictions of aircraft. Airborne flight management systems (FMS) exist or are being developed with similar 4D trajectory generation capabilities. Differences between the ATC generated profiles and those generated by the airborne 4D FMS may introduce system problems. A simulation experiment was conducted to explore integration of a 4D equipped aircraft into a 4D ATC system. The NASA Langley Transport Systems Research Vehicle cockpit simulator was linked in real time to the NASA Ames Descent Advisor ATC simulation for this effort. Candidate procedures for handling 4D equipped aircraft were devised and traffic scenarios established which required time delays absorbed through speed control alone or in combination with path stretching. Dissimilarities in 4D speed strategies between airborne and ATC generated trajectories were tested in these scenarios. The 4D procedures and FMS operation were well received by airline pilot test subjects, who achieved an arrival accuracy at the metering fix of 2.9 seconds standard deviation time error. The amount and nature of the information transmitted during a time clearance were found to be somewhat of a problem using the voice radio communication channel. Dissimilarities between airborne and ATC-generated speed strategies were found to be a problem when the traffic remained on established routes. It was more efficient for 4D equipped aircraft to fly trajectories with similar, though less fuel efficient, speeds which conform to the ATC strategy. Heavy traffic conditions, where time delays forced off-route path stretching, were found to produce a potential operational benefit of the airborne 4D FMS

Piloted simulation of an air-ground profile negotiation process in a time-based Air Traffic Control environment

Historically, development of airborne flight management systems (FMS) and ground-based air traffic control (ATC) systems has tended to focus on different objectives with little consideration for operational integration. A joint program, between NASA's Ames Research Center (Ames) and Langley Research Center (Langley), is underway to investigate the issues of, and develop systems for, the integration of ATC and airborne automation systems. A simulation study was conducted to evaluate a profile negotiation process (PNP) between the Center/TRACON Automation System (CTAS) and an aircraft equipped with a four-dimensional flight management system (4D FMS). Prototype procedures were developed to support the functional implementation of this process. The PNP was designed to provide an arrival trajectory solution which satisfies the separation requirements of ATC while remaining as close as possible to the aircraft's preferred trajectory. Results from the experiment indicate the potential for successful incorporation of aircraft-preferred arrival trajectories in the CTAS automation environment. Fuel savings on the order of 2 percent to 8 percent, compared to fuel required for the baseline CTAS arrival speed strategy, were achieved in the test scenarios. The data link procedures and clearances developed for this experiment, while providing the necessary functionality, were found to be operationally unacceptable to the pilots. In particular, additional pilot control and understanding of the proposed aircraft-preferred trajectory, and a simplified clearance procedure were cited as necessary for operational implementation of the concept

Cluster, Classify, Regress: A General Method For Learning Discountinous Functions

This paper presents a method for solving the supervised learning problem in which the output is highly nonlinear and discontinuous. It is proposed to solve this problem in three stages: (i) cluster the pairs of input-output data points, resulting in a label for each point; (ii) classify the data, where the corresponding label is the output; and finally (iii) perform one separate regression for each class, where the training data corresponds to the subset of the original input-output pairs which have that label according to the classifier. It has not yet been proposed to combine these 3 fundamental building blocks of machine learning in this simple and powerful fashion. This can be viewed as a form of deep learning, where any of the intermediate layers can itself be deep. The utility and robustness of the methodology is illustrated on some toy problems, including one example problem arising from simulation of plasma fusion in a tokamak.Comment: 12 files,6 figure

Flight Evaluation of Center-TRACON Automation System Trajectory Prediction Process

Two flight experiments (Phase 1 in October 1992 and Phase 2 in September 1994) were conducted to evaluate the accuracy of the Center-TRACON Automation System (CTAS) trajectory prediction process. The Transport Systems Research Vehicle (TSRV) Boeing 737 based at Langley Research Center flew 57 arrival trajectories that included cruise and descent segments; at the same time, descent clearance advisories from CTAS were followed. Actual trajectories of the airplane were compared with the trajectories predicted by the CTAS trajectory synthesis algorithms and airplane Flight Management System (FMS). Trajectory prediction accuracy was evaluated over several levels of cockpit automation that ranged from a conventional cockpit to performance-based FMS vertical navigation (VNAV). Error sources and their magnitudes were identified and measured from the flight data. The major source of error during these tests was found to be the predicted winds aloft used by CTAS. The most significant effect related to flight guidance was the cross-track and turn-overshoot errors associated with conventional VOR guidance. FMS lateral navigation (LNAV) guidance significantly reduced both the cross-track and turn-overshoot error. Pilot procedures and VNAV guidance were found to significantly reduce the vertical profile errors associated with atmospheric and airplane performance model errors

Running-mass models of inflation, and their observational constraints

If the inflaton sector is described by softly broken supersymmetry, and the inflaton has unsuppressed couplings, the inflaton mass will run strongly with scale. Four types of model are possible. The prediction for the spectral index involves two parameters, while the COBE normalization involves a third, all of them calculable functions of the relevant masses and couplings. A crude estimate is made of the region of parameter space allowed by present observation.Comment: Latex file, 20 pages, 11 figures, uses epsf.sty. Comment on the observation of the spectral index scale dependence added; Fig. 3-6 improve

Ultra-calcic Magmas Generated from Ca-depleted Mantle: an Experimental Study on the Origin of Ankaramites

Ultra-calcic ankaramitic magmas or melt inclusions are ubiquitous in arc, ocean-island and mid-ocean ridge settings. They are primitive in character (XMg > 0·65) and have high CaO contents (>14 wt %) and CaO/Al2O3 (>1·1). Experiments on an ankaramite from Epi, Vanuatu arc, demonstrate that its liquidus surface has only clinopyroxene at pressures of 15 and 20 kbar, with XCO2 in the volatile component from 0 to 0·86. The parental Epi ankaramite is thus not an unfractionated magma. However, forcing the ankaramite experimentally into saturation with olivine, orthopyroxene and spinel results in more magnesian, ultra-calcic melts with CaO/Al2O3 of 1·21-1·58. The experimental melts are not extremely Ca-rich but high in CaO/Al2O3 and in MgO (up to 18.5 wt %), and would evolve to high-CaO melts through olivine fractionation. Fractionation models show that the Epi parent magma can be derived from such ultra-calcic experimental melts through mainly olivine fractionation. We show that the experimental ultra-calcic melts could form through low-degree melting of somewhat refractory mantle. The latter would have been depleted by previous melt extraction, which increases the CaO/Al2O3 in the residue as long as some clinopyroxene remains residual. This finding corrects the common assumption that ultra-calcic magmas must come from a Ca-rich pyroxenite-type source. The temperatures necessary for the generation of ultra-calcic magmas are ≥1330°C, and their presence would suggest melting regimes that are at the upper temperature end of previous interpretations made on the basis of picritic magma