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At least 487 records · Page 27

Concept of Operations for Interval Management Arrivals and Approach

This paper presents the concept of operations for interval management operations to be deployed in the US National Airspace System (NAS) by the Federal Aviation Administration (FAA) Interval Management Program. The arrivals and approach operations are explored in detail including the primary operation and variations. The use of interval management operations is described that begin in en route airspace and continue to a termination point inside the arrival terminal area in the highly automated terminal environment that includes other arrival management tools such as arrival metering, Ground-based Interval Management - Spacing (GIM-S), and Terminal Sequencing and Spacing (TSAS). The roles of Air Traffic and Pilots and the ground automation tools that are used by Air Traffic Controllers to enable the operations are explored.

Hicok, Daniel S.↗

Gradient Field Imploding Liner Fusion Propulsion System: NASA Innovative Advanced Concepts Phase I Final Report

The advancement of human deep space exploration requires the continued development of energetic in-space propulsion systems, from current chemical engines to nuclear thermal rockets to future high energy concepts such as nuclear fusion. As NASA embarks on a program to develop near-term nuclear thermal propulsion, this NASA Innovative Advanced Concepts (NIAC) Phase I activity was funded to investigate the feasibility of an innovative approach toward highly energetic pulsed fusion propulsion. Previous concept studies have proposed the conversion of fusion energy for in-space propulsion, ranging from laser-ignited fusion systems such as Gevaltig and VISTA, to the British Interplanetary Society's Daedalus concept and its more recent incarnation under Project Icarus, to steady-state spherical torus fusion systems. Recent NIAC studies have also evaluated several innovative fusion concepts, including the acceleration and compression of field reversed configuration plasmas in time-changing magnetic fields, magnetically driven liners imploding onto plasma targets, and high current z-pinch compression of material liners onto fission-fusion fuel targets. While each of these studies firmly established the potential benefits of fusion systems for interplanetary travel, they also identified significant challenges in successfully engineering such systems for spacecraft propulsion. The concept outlined in this Technical Publication (TP) builds on the lessons learned from these prior activities, approaching the quest for fusion-powered propulsion through an innovative variation of magneto-inertial fusion concepts developed for terrestrial power applications.

Lapointe, M. R.↗

Numerical Study of the Turbulent Prandtl Number in Supersonic Plane-Channel Flow – the Effect of Thermal Boundary Conditions

Direct numerical simulation is used to investigate the turbulent Prandtl number Prt above cold (isothermal) and hot (adiabatic) walls in a family of supersonic channel flows. A range of Reynolds numbers and mean temperature/density variations is considered. The value of Prt away from the wall approaches 0.85 above both the isothermal and adiabatic walls, with the width of the Prt = 0.85 region increasing with wall-variable-based Reynolds number Reτw (the latter strongly affected by the thermal boundary condition). The variable, near-wall Prt profiles from both the present and previous, passive-scalar simulations collapse as a function of the semilocal y∗ wall scaling proposed by Huang et al., with the y∗-dependence weakly parameterized by Reτw.

Turbulence↗

Physical characteristics of cometary dust from dynamical studies - A review

Progress made in the determination of the physical characteristics of cometary dust particles from studies of dust tail dynamics is reviewed. Applications of the combined dynamical photometric approach of Finson and Probstein (1968) to studies of cometary tails exhibiting continuous light intensity variations are discussed, with attention given to determinations of the particle-size-related distribution function of the solar radiation pressure exerted on the particles, the contribution of comets to the interplanetary dust, calculations of dust ejection rates and a Monte Carlo approach to the analysis of dust tails. Investigations of dust streamers and striae, which are believed to be related to comet outbursts entailing brief but sharp enhancements of dust production, are then reviewed, with particular attention given to observations of Comet West 1976 VI. Finally, the question of cometary particle type is addressed, and it is pointed out that the presence of submicron absorbing particles in the striae of Comet West is not incompatible with the presence of micron-size dielectric particles in the inner coma.

Sekanina, Z.↗

Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.

Mengshoel, Ole J.↗

Dynamics of the outer radiation belts in relation to polar substorms and hot plasma injections at geostationary altitude

Geostationary satellite and ground measurements of dynamic variations of the outer radiation belts and their relations with the development of auroral structures during magnetospheric substorms are analyzed. A comparison of measurements of the H or X geomagnetic field components made by seven auroral stations with ATS-6 low-energy and high-energy particle measurements during the multiple-onset substorm of Aug. 16, 1974 is presented which demonstrates that while the decrease in energetic particle fluxed ends only at the time of a strong substorm onset, rapid motions of the outer radiation belts may occur during the flux decrease. All-sky photographs of auroral phenomena taken at Fort Yukon and College, Alaska are then compared with ATS-1 energetic particle flux measurements in order to demonstrate the relation between flux decreases and increases and distinct substorm phases. Results support the hypothesis of a magnetospheric substorm precursor which appears to be an instability growing at the inner boundary of the plasma layer and approaching the earth, and underline the importance of current and magnetic field variations in charged particle dynamics.

Sauvaud, J. A.↗

Improving Grasp Skills Using Schema Structured Learning

Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.

Platt, Robert↗

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

Robust Control Methodology Via Loop Shaping, Root Locus, and Model Reference Control

The paper describes the development of a robust control methodology that can tolerate large uncertainties in plant dynamics in terms of proportional gain variations as well as frequencies and damping. For this to be accomplished, the methodology starts by designing a feedback controller based on a loop shaping technique. The design is then improved by employing a root locus control design approach. Finally, the response of the feedback system is further improved by augmenting the control design using model reference control. The design approach also takes into consideration the speed of the process actuator for a fast response and for high disturbance rejection. Results from two control design examples covered in the paper show that this control approach can tolerate plant proportional gain uncertainty of approximately ± two orders of magnitude with relatively large variations in plant frequencies and damping.

Control Systems↗

Variation of sodium on Mercury with solar radiation pressure

It has been suggested that nonthermal Na atoms with velocities in excess of 2.1 km/sec in the Mercury atmosphere can be accelerated off the planet by solar radiation pressure; Na abundance may accordingly be expected to decrease with increasing radiation pressure. While this is confirmed by the present measurements, high resolution line profile measurements on Na emission indicate that very little, if any, of the Na is nonthermal, while the bulk is at a temperature approaching that of the planetary surface. Attention is given to explanations for the observed variation.

Potter, A. E.↗

Dissipative rendering and neural network control system design

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.

Gonzalez, Oscar R.↗

The Orbiting Carbon Observatory Mission: Watching the Earth Breathe Mapping CO2 from Space

Approach: Collect spatially resolved, high resolution spectroscopic observations of CO2 and O2 absorption in reflected sunlight. Use these data to resolve spatial and temporal variations in the column averaged CO2 dry air mole fraction, X(sub CO2) over the sunlit hemisphere. Employ independent calibration and validation approaches to produce X(sub CO2) estimates with random errors and biases no larger than 1-2 ppm (0.3-0.5%) on regional scales at monthly intervals.

three channel grating spectrometry↗

Thermal Conductivity Measurements of Helium 4 Near the Lambda-Transition Using a Magnetostrictive Low Gravity Simulator

There has been a recent increase in interest both experimentally and theoretically in the study of liquid helium very near the lambda-transition in the presence of a heat current. In traditional ground based experiments there are gravitationally induced pressure variations in any macroscopic helium sample that limit how closely the transition can be approached. We have taken advantage of the finite magnetic susceptibility of He 4 to build a magnetostrictive low gravity simulator. The simulator consists of a superconducting magnet with field profile shaped to counteract the force of gravity in a helium sample. When the magnet is operated with B x dB/dz = 21T(exp 2)/cm at the location of the cell, the gravitationally induced pressure variations will be canceled to within 1% over a volume of 0.5 cm in height and 0.5 cm in diameter. This technique for canceling the pressure variations in a long sample cell allows the lambda-transition to be studied much closer in reduced temperature and under a wider range of applied heat currents than is possible using other ground based techniques. Preliminary results using this low gravity simulator and the limitations of the magnetostrictive technique in comparison to doing space based experiments will be presented.

superconductive magnet heat current↗

Data Assimilation of Photosynthetic Light-use Efficiency using Multi-angular Satellite Data: II Model Implementation and Validation

Spatially explicit and temporally continuous estimates of photosynthesis will be of great importance for increasing our understanding of and ultimately closing the terrestrial carbon cycle. Current capabilities to model photosynthesis, however, are limited by accurate enough representations of the complexity of the underlying biochemical processes and the numerous environmental constraints imposed upon plant primary production. A potentially powerful alternative to model photosynthesis through these indirect observations is the use of multi-angular satellite data to infer light-use efficiency (ε) directly from spectral reflectance properties in connection with canopy shadow fractions. Hall et al. (this issue) introduced a new approach for predicting gross ecosystem production that would allow the use of such observations in a data assimilation mode to obtain spatially explicit variations in ε from infrequent polar-orbiting satellite observations, while meteorological data are used to account for the more dynamic responses of ε to variations in environmental conditions caused by changes in weather and illumination. In this second part of the study we implement and validate the approach of Hall et al. (this issue) across an ecologically diverse array of eight flux-tower sites in North America using data acquired from the Compact High Resolution Imaging Spectroradiometer (CHRIS) and eddy-flux observations. Our results show significantly enhanced estimates of ε and therefore cumulative gross ecosystem production (GEP) over the course of one year at all examined sites. We also demonstrate that ε is greatly heterogeneous even across small study areas. Data assimilation and direct inference of GEP from space using a new, proposed sensor could therefore be a significant step towards closing the terrestrial carbon cycle.

Hilker, Thomas↗

Wake Encounter Analysis for a Closely Spaced Parallel Runway Paired Approach Simulation

A Monte Carlo simulation of simultaneous approaches performed by two transport category aircraft from the final approach fix to a pair of closely spaced parallel runways was conducted to explore the aft boundary of the safe zone in which separation assurance and wake avoidance are provided. The simulation included variations in runway centerline separation, initial longitudinal spacing of the aircraft, crosswind speed, and aircraft speed during the approach. The data from the simulation showed that the majority of the wake encounters occurred near or over the runway and the aft boundaries of the safe zones were identified for all simulation conditions.

Mckissick,Burnell T.↗

Flight evaluation of the STOL flare and landing during night operations

Simulated instrument approaches were made to Category 1 minimums followed by a visual landing on a 100 x 1700 ft STOL runway. Data were obtained for variations in the aircraft's flare response characteristics and control techniques and for different combinations of aircraft and runway lighting and a visual approach slope indication. With the complete aircraft and runway lighting and visual guidance no degradation in flying qualities or landing performance was observed compared to daylight operations. elimination of the touchdown zone floodlights or the aircraft landing lights led to somewhat greater pilot workload; however, the landing could still be accomplished successfully. Loss of both touchdown zone and aircraft landing lights led to a high workload situation and only a marginally adequate to inadequate landing capability.

Franklin, J. A.↗

Complementary variational principle and duality in mathematical programming.

The relationship between the complementary variational principle and duality in mathematical programming is demonstrated through a geometric approach in a Hilbert space setting. A necessary and sufficient condition for the existence of such a principle is given in the case of a convex functional constrained by linear dynamics. Its relationship to the Kuhn-Tucker saddle point theory is indicated. Applications to various programming and control problems are discussed.

Chan, W. L.↗

Space shuttle entry and landing navigation analysis

A navigation system for the entry phase of a Space Shuttle mission which is an aided-inertial system which uses a Kalman filter to mix IMU data with data derived from external navigation aids is evaluated. A drag pseudo-measurement used during radio blackout is treated as an additional external aid. A comprehensive truth model with 101 states is formulated and used to generate detailed error budgets at several significant time points -- end-of-blackout, start of final approach, over runway threshold, and touchdown. Sensitivity curves illustrating the effect of variations in the size of individual error sources on navigation accuracy are presented. The sensitivity of the navigation system performance to filter modifications is analyzed. The projected overall performance is shown in the form of time histories of position and velocity error components. The detailed results are summarized and interpreted, and suggestions are made concerning possible software improvements.

Jones, H. L.↗