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NASA NTRS2000

Contributions of the Transonic Dynamics Tunnel to the Testing of Active Control of Aeroelastic Response

By the 1960s, researchers began to investigate the feasibility of using active controls technology (ACT) for increasing the capabilities of military and commercial aircraft. Since then many researchers, too numerous to mention, have investigated and demonstrated the usefulness of ACT for favorably modifying the aeroelastic response characteristics of flight vehicles. As a result, ACT entered the limelight as a viable tool for answering some very difficult design questions and had the potential for obtaining structural weight reductions optimizing maneuvering performance, and satisfying the multimission requirements being imposed on future military and commercial aircraft designs. Over the past 40 years, the NASA Langley Research Center (LaRC) has played a major role in developing ACT in part by its participation in many wind-tunnel programs conducted in the Transonic Dynamics Tunnel (TDT). These programs were conducted for the purposes of: (1) establishing concept feasibility; (2) demonstrating proof of concept; and (3) providing data for validating new modeling, analysis, and design methods. This paper provides an overview of the ACT investigations conducted in the TDT. For each program discussed herein, the objectives of the effort, the testing techniques, the test results, any, signIficant findings, and the lessons learned with respect to ACT testing are presented.

Perry, Boyd, III↗

NASA NTRS2012

Studying the Formation and Development of Molecular Clouds: With the CCAT Heterodyne Array Instrument (CHAI)

Surveys of all different types provide basic data using different tracers. Molecular clouds have structure over a very wide range of scales. Thus, "high resolution" surveys and studies of selected nearby clouds add critical information. The combination of large-area and high resolution allows Increased spatial dynamic range, which in turn enables detection of new and perhaps critical morphology (e.g. filaments). Theoretical modeling has made major progress, and suggests that multiple forces are at work. Galactic-scale modeling also progressing - indicates that stellar feedback is required. Models must strive to reproduce observed cloud structure at all scales. Astrochemical observations are not unrelated to questions of cloud evolution and star formation but we are still learning how to use this capability.

heterodyne sub-millimeter arrays↗

NASA NTRS2011

Flight Simulation Model Exchange

The NASA Engineering and Safety Center Review Board sponsored an assessment of the draft Standard, Flight Dynamics Model Exchange Standard, BSR/ANSI-S-119-201x (S-119) that was conducted by simulation and guidance, navigation, and control engineers from several NASA Centers. The assessment team reviewed the conventions and formats spelled out in the draft Standard and the actual implementation of two example aerodynamic models (a subsonic F-16 and the HL-20 lifting body) encoded in the Extensible Markup Language grammar. During the implementation, the team kept records of lessons learned and provided feedback to the American Institute of Aeronautics and Astronautics Modeling and Simulation Technical Committee representative. This document contains the results of the assessment.

Murri, Daniel G.↗

NASA NTRS2011

Flight Simulation Model Exchange: Appendices - Volume 2

Murri, Daniel G.↗

NASA NTRS2008

What Might We Learn About Magnetospheric Substorms at the Earth from the MESSENGER Measurements at Mercury?

Satellite observations at the Earth, supported by theory and modeling, have established a close connection between the episodes of intense magnetospheric convection termed substorms and the occurrence of magnetic reconnection. Magnetic reconnection at the dayside magnetopause results in strong energy input to the magnetosphere. This energy can either be stored or used immediately to power the magnetospheric convection that produces the phenomena that collectively define the 'substorm.' However, many aspects of magnetic reconnection and the dynamic response of the coupled solar wind - magnetosphere - ionosphere system at the Earth during substorms remain poorly understood. For example, the rate of magnetic reconnection is thought to be proportional to the local Alfven speed, but the limited range of changes in this solar wind parameter at 1 AU have made it difficult to detect its influence over energy input to the Earth's magnetosphere. In addition, the electrical conductance of the ionosphere and how it changes in response to auroral charged particle precipitation are hypothesized to play a critical role in the development of substorms, but the nature of this electrodynamic interaction remain difficult to deduce from Earth observations alone. The amount of energy the terrestrial magnetosphere can store in its tail, the duration of the storage, and the trigger(s) for its dissipation are all thought to be determined by not only the microphysics of the cross-tail current layer, but also the properties of the coupled magnetosphere - ionosphere system. Again, the separation of microphysics effects from system response has proved very difficult using measurements taken only at the Earth. If MESSENGER'S charged particle and magnetic field measurements confirm the occurrence of terrestrial-style substorms in Mercury's miniature magnetosphere, then it may be possible to determine how magnetospheric convection, field-aligned currents, charged particle acceleration, reconnection, and tail energy storage are influenced by the intense magnetic reconnection expected to be associated with solar wind conditions at 0.3 - 0.5 AU from the Sun and the simplified electrodynamic feed-back anticipated for a planet lacking an ionosphere. MESSENGER observations from its 14 January 2008 Mercury flyby relevant to the occurrence of magnetic reconnection and substorms at Mercury will be discussed.

Slavin, James A.↗

NASA NTRS1993

The NASA/industry Design Analysis Methods for Vibrations (DAMVIBS) program: McDonnell-Douglas Helicopter Company achievements

This paper presents a summary of some of the work performed by McDonnell Douglas Helicopter Company under NASA Langley-sponsored rotorcraft structural dynamics program known as DAMVIBS (Design Analysis Methods for VIBrationS). A set of guidelines which is applicable to dynamic modeling, analysis, testing, and correlation of both helicopter airframes and a large variety of structural finite element models is presented. Utilization of these guidelines and the key features of their applications to vibration modeling of helicopter airframes are discussed. Correlation studies with the test data, together with the development and applications of a set of efficient finite element model checkout procedures, are demonstrated on a large helicopter airframe finite element model. Finally, the lessons learned and the benefits resulting from this program are summarized.

Toossi, Mostafa↗

NASA NTRS1975

What we have learned from the magnetosphere

Three significant discoveries resulting from recent studies of earth's magnetosphere are discussed: (1) the central role of magnetic-field-line reconnection in determining the topology, geometry, and dynamics of the magnetosphere; (2) the realization that auroral arcs result from coupling of solar-wind stresses to the ionosphere and neutral atmosphere; and (3) the role of plasma turbulence in affecting both the microscopic state and macroscopic observables of the magnetospheric plasma. Magnetic-field-line reconnection is described in terms of Dungey's (1961) model of the magnetosphere, a simple picture of magnetic-substorm evolution is outlined, and questions concerning the reconnection rate are considered. The production of aurorae by field-aligned electron beams is examined, and an analogy is made between earth's magnetosphere and that of a pulsar with aligned dipole and spin axes. Plasma-turbulence problems are reviewed which concern anomalously fast electron and proton losses from the Van Allen belts, whistler-electron interactions, and anomalous resistance in auroral arcs. The Pioneer 10 encounter with Jupiter's magnetosphere is briefly noted.

Kennel, C. F.↗

NASA NTRS1997

Collaborating Fuzzy Reinforcement Learning Agents

Earlier, we introduced GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

Berenji, Hamid R.↗

NASA NTRS1993

The Mini-Mast CSI testbed: Lessons learned

The Mini-Mast testbed was one of the first large scale Controls-Structure-Interaction (CSI) systems used to evaluate state-of-the-art methodology in flexible structure control. Now that all the testing at Langley Research Center has been completed, a look back is warranted to evaluate the program. This paper describes some of the experiences and technology development studies by NASA, university, and industry investigators. Lessons learned are presented from three categories: the testbed development, control methods, and the operation of a guest investigator program. It is shown how structural safety margins provided a realistic environment to simulate on-orbit CSI research, even though they also reduced the research flexibility afforded to investigators. The limited dynamic coupling between the bending and torsion modes of the cantilevered test article resulted in highly successful SISO and MIMO controllers. However, until accurate models were obtained for the torque wheel actuators, sensors, filters, and the structure itself, most controllers were unstable. Controls research from this testbed should be applicable to cantilevered appendages of future large space structures.

Tanner, Sharon E.↗

NASA NTRS2009

Finite-difference simulation and visualization of elastodynamics in time-evolving generalized curvilinear coordinates

Modeling and simulation of free and forced structural vibrations is essential to an overall structural health monitoring capability. In the various embodiments, a first principles finite-difference approach is adopted in modeling a structural subsystem such as a mechanical gear by solving elastodynamic equations in generalized curvilinear coordinates. Such a capability to generate a dynamic structural response is widely applicable in a variety of structural health monitoring systems. This capability (1) will lead to an understanding of the dynamic behavior of a structural system and hence its improved design, (2) will generate a sufficiently large space of normal and damage solutions that can be used by machine learning algorithms to detect anomalous system behavior and achieve a system design optimization and (3) will lead to an optimal sensor placement strategy, based on the identification of local stress maxima all over the domain.

Kaul, Upender K.↗

NASA NTRS1992

Functional expansion representations of artificial neural networks

In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

Gray, W. Steven↗

NASA NTRS1987

Dynamics of long period comets

The appearance of Halley's Comet in 1985 to 1986 and the related emphasis on research on physical models of cometary nuclei, led to a more moderate pace for the dynamical studies of the Oort cloud and the motion of long-period comets this year. Specific areas studied included the dynamical evolution of cometary showers as a result of stars passages through the inner Oort cloud and the possible relationship to observed stepwise mass extinctions at geological boundaries, revised estimates for the total mass of comets in the Oort cloud as a result of lessons learned from the spacecraft encounters with Halley's Comet, and study of the possible dynamical sources for the short-period comets in the solar system as part of a wider study of physical processing of cometary nuclei prior to their becoming visible comets. The work on cometary showers used a Monte Carlo simulation of the evolution of cometary orbits under a combination of planetary, nongravitational, and stellar perturbations, and with physical removal by disruption, sublimation of all volatiles, and collision.

Weissman, Paul R.↗

NASA NTRS1989

Machine learning in motion control

The existing methodologies for robot programming originate primarily from robotic applications to manufacturing, where uncertainties of the robots and their task environment may be minimized by repeated off-line modeling and identification. In space application of robots, however, a higher degree of automation is required for robot programming because of the desire of minimizing the human intervention. We discuss a new paradigm of robotic programming which is based on the concept of machine learning. The goal is to let robots practice tasks by themselves and the operational data are used to automatically improve their motion performance. The underlying mathematical problem is to solve the problem of dynamical inverse by iterative methods. One of the key questions is how to ensure the convergence of the iterative process. There have been a few small steps taken into this important approach to robot programming. We give a representative result on the convergence problem.

Su, Renjeng↗

NASA NTRSDate not supplied

Detecting And Characterizing Archetypes of Unintended Consequences in Engineered Systems

When designing engineered systems, the potential for unintended consequences of design policies or design decisions exists despite best intentions. Conditions that might cause the formation of unintended consequences are often known only in hindsight. However, since these conditions are associated with a single event, it is difficult to uncover the general patterns of conditions leading to unintended consequences. In this research, patterns of conditions associated with unintended consequences are learned from historical data and represented in the form of archetypes. While previous work using systems theoretic modeling has identified high-level archetypes, this work leverages a self-organizing map to learn archetypes of unintended consequences from human-tagged risk factors in a large data set of lessons learned from adverse events at NASA. The sixty-six identified archetypes contain patterns of conditions such as complexity and human-machine interaction associated with the formation of unintended consequences. To validate the archetypes, a sample of the archetypes is represented using system dynamics in order to illustrate that the identified archetypes are specialized versions of known high-level archetypes of unintended consequences. While the research is based upon a specific dataset, the archetypes apply to any engineered system and the pattern of leading indicators open a new path to manage unintended consequences and mitigate the magnitude of potentially adverse outcomes.

Hannah S Walsh↗

NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

Risk detection↗

NASA NTRS2010

Dynamically Evolving Sectors for Convective Weather Impact

A new strategy for altering existing sector boundaries in response to blocking convective weather is presented. This method seeks to improve the reduced capacity of sectors directly affected by weather by moving boundaries in a direction that offers the greatest capacity improvement. The boundary deformations are shared by neighboring sectors within the region in a manner that preserves their shapes and sizes as much as possible. This reduces the controller workload involved with learning new sector designs. The algorithm that produces the altered sectors is based on a force-deflection mesh model that needs only nominal traffic patterns and the shape of the blocking weather for input. It does not require weather-affected traffic patterns that would have to be predicted by simulation. When compared to an existing optimal sector design method, the sectors produced by the new algorithm are more similar to the original sector shapes, resulting in sectors that may be more suitable for operational use because the change is not as drastic. Also, preliminary results show that this method produces sectors that can equitably distribute the workload of rerouted weather-affected traffic throughout the region where inclement weather is present. This is demonstrated by sector aircraft count distributions of simulated traffic in weather-affected regions.

Drew, Michael C.↗

NASA NTRSDate not supplied

The NASA Turbulent Heat Flux Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds- averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗