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Discussed the preexisting problem of input dependence, interactions with other kinds of observable behavior and lack of debugger support. Also fixed (preexisting) "first" in wording based SGI review.
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The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.
OH and HO2 were measured with the Airborne Tropospheric Hydrogen Oxides Sensor (ATHOS) as part of a large measurement suite from the NASA DC-8 aircraft during the Intercontinental Chemical Transport Experiment - A (INTEX-A). This mission, which was conducted mainly over North America and the western Atlantic Ocean in summer 2004, was an excellent test of atmospheric oxidation chemistry. Throughout the troposphere, observed OH was generally 0.60 of the modeled OH; below 8 km, observed HO2 was generally 0.78 of modeled HO2. If the over-prediction of tropospheric OH is not due to an instrument calibration error, then it implied less global tropospheric oxidation capacity and longer lifetimes for gases like methane and methyl chloroform than currently thought. This discrepancy falls well outside uncertainties in both the OH measurement and rate coefficients for known reactions and points to a large unknown OH loss. If the modeled OH is forced to agree with observed values by introducing of an undefined OH loss that removed HOx (HOx=OH+HO2), the observed and modeled HO2 and HO2/OH ratios are largely reconciled within the measurement uncertainty. HO2 behavior above 8 km was markedly different. The observed-to-modeled ratio correlating with NO. The observed-to-modeled HO2 ratio increased from approximately 1 at 8 km to more than approximately 2.5 at 11 km with the observed-to-modeled ratio correlating with NO. The observed-to-modeled HO2 and NO were both considerably greater than observations from previous campaigns. In addition, the observed-to-modeled HO2/OH, which is sensitive to cycling reactions between OH and HO2, increased from approximately 1.2 at 8 km to almost 4 above 11 km. In contrast to the lower atmosphere, these discrepancies above 8 km suggest a large unknown HOx source and additional reactants that cycle HOx from OH to HO2. In the continental planetary boundary layer, the OH observed-to-modeled ratio increased from 0.6 when isoprene was less than 0.1 ppbv to over 3 when isoprene was greater than 2 ppbv, suggesting that forests throughout the United States are emitting unknown HOx sources. Progress in resolving these discrepancies requires further examinations of possible unknown OH sinks and HOx sources and a focused research activity devoted to ascertaining the accuracy of the OH and HO2 measurements.
In this paper, the diffusion of federally funded aerospace R&D is explored from the perspective of the information-seeking behavior of U.S. aerospace engineers and scientists. The following three assumptions frame this exploration: (1) knowledge production, transfer, and utilization are equally important components of the aerospace R&D process; (2) the diffusion of knowledge resulting from federally funded aerospace R&D is indispensable for the U.S. to remain a world leader in aerospace; and (3) U.S. government technical reports, produced by NASA and DOD, play an important, but as yet undefined, role in the diffusion of federally funded aerospace R&D. A conceptual model for federally funded aerospace knowledge diffusion, one that emphasizes U.S. goverment technical reports, is presented. Data regarding three research questions concerning the information-seeking behavior of U.S. aerospace engineers and scientists are also presented.
Stress corrosion cracking and corrosion fatigue experiments were conducted with the susceptible S-L orientation of AA7075-T651, immersed in acidified and inhibited NaCl solution, to provide a basis for incorporating environmental effects into fatigue crack propagation life prediction codes such as NASA FLAGRO. This environment enhances da/dN by five to ten-fold compared to fatigue in moist air. Time-based crack growth rates from quasi-static load experiments are an order of magnitude too small for accurate linear superposition prediction of da/dN for loading frequencies above 0.001 Hz. Alternate methods of establishing da/dt, based on rising-load or ripple-load-enhanced crack tip strain rate, do not increase da/dt and do not improve linear superposition. Corrosion fatigue is characterized by two regimes of frequency dependence; da/dN is proportional to f(exp -1) below 0.001 Hz and to F(exp 0) to F(exp -0.1) for higher frequencies. Da/dN increases mildly both with increasing hold-time at K(sub max) and with increasing rise-time for a range of loading waveforms. The mild time-dependence is due to cycle-time-dependent corrosion fatigue growth. This behavior is identical for S-L nd L-T crack orientations. The frequency response of environmental fatigue in several 7000 series alloys is variable and depends on undefined compositional or microstructural variables. Speculative explanations are based on the effect of Mg on occluded crack chemistry and embritting hydrogen uptake, or on variable hydrogen diffusion in the crack tip process zone. Cracking in the 7075/NaCl system is adequately described for life prediction by linear superposition for prolonged load-cycle periods, and by a time-dependent upper bound relationship between da/dN and delta K for moderate loading times.
The present exploration of the diffusion of federally-funded R&D via the information-seeking behavior of scientists and engineers proceeds under three assumptions: (1) that knowledge transfer and utilization is as important as knowledge production; (2) that the diffusion of knowledge obtained through federally-funded R&D is necessary for the maintenance of U.S. preeminence in the aerospace field; and (3) that federally-funded NASA and DoD technical reports play an important, albeit as-yet undefined, role in aerospace R&D diffusion. A conceptual model is presented for the process of knowledge diffusion that stresses the role of U.S. government-funded technical reports.
The identification of processes that locally and approximately dominate dynamical system behavior has enabled significant advances in understanding and modeling nonlinear differential dynamical systems. Conventional methods of dominant process identification involve piecemeal and ad hoc (non-rigorous, informal) scaling analyses to identify dominant balances of governing equation terms and to delineate the spatiotemporal boundaries (boundaries in space and/or time) of each dominant balance. For the first time, we present an objective global measure of the fit of dominant balances to observations, which is desirable for automation, and was previously undefined. Furthermore, we propose a formal definition of the dominant balance identification problem in the form of an optimization problem. Here, we show that the optimization can be performed by various machine learning algorithms, enabling the automatic identification of dominant balances. Our method is algorithm agnostic and it eliminates reliance upon expert knowledge to identify dominant balances which are not known beforehand.