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At least 1,027 records · Page 57

A Multiscale, Nonlinear, Modeling Framework Enabling the Design and Analysis of Composite Materials and Structures

A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.

Bednarcyk, Brett A.↗

Real-Time Onboard Global Nonlinear Aerodynamic Modeling from Flight Data

Flight test and modeling techniques were developed to accurately identify global nonlinear aerodynamic models onboard an aircraft. The techniques were developed and demonstrated during piloted flight testing of an Aermacchi MB-326M Impala jet aircraft. Advanced piloting techniques and nonlinear modeling techniques based on fuzzy logic and multivariate orthogonal function methods were implemented with efficient onboard calculations and flight operations to achieve real-time maneuver monitoring and analysis, and near-real-time global nonlinear aerodynamic modeling and prediction validation testing in flight. Results demonstrated that global nonlinear aerodynamic models for a large portion of the flight envelope were identified rapidly and accurately using piloted flight test maneuvers during a single flight, with the final identified and validated models available before the aircraft landed.

Brandon, Jay M.↗

Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability margins. At each time point, the system was linearized about the current operating point using Simulink's built-in solver. Each linearized system in time was evaluated for its rigid-body gain margin (high frequency gain margin), rigid-body phase margin, and aero gain margin (low frequency gain margin) for each control axis. Using the stability margins derived from the baseline linearization approach, the time domain derived stability margins were determined by executing time domain simulations in which axis-specific incremental gain and phase adjustments were made to the nominal system about the expected neutral stability point at specific flight times. The baseline stability margin time histories were used to shift the system gain to various values around the zero margin point such that a precise amount of expected gain margin was maintained throughout flight. When assessing the gain margins, the gain was applied starting at the time point under consideration, thereafter following the variation in the margin found in the linear analysis. When assessing the rigid-body phase margin, a constant time delay was applied to the system starting at the time point under consideration. If the baseline stability margins were correctly determined via the linear analysis, the time domain simulation results should contain unstable behavior at certain gain and phase values. Examples will be shown from repeated simulations with variable added gain and phase lag. Faithfulness of margins calculated from the linear analysis to the nonlinear system will be demonstrated.

Kiefer, J. M.↗

Stabilization of Hypersonic Boundary Layers by Linear and Nonlinear Optimal Perturbations

The effect of stationary, finite-amplitude, linear and nonlinear optimal perturbations on the modal disturbance growth in a Mach 6 axisymmetric flow over a 7 deg. half-angle cone with 0:126 mm nose radius and 0:305 m length is investigated. The freestream parameters (M = 6, Re(exp 1) = 18 x 10(exp. 6) /m) are selected to match the flow conditions of a previous experiment in the VKI H3 hypersonic tunnel. Plane-marching parabolized stability equations are used in conjunction with a partial-differential equation based planar eigenvalue analysis to characterize the boundary layer instability in the presence of azimuthally periodic streaks. The streaks are observed to stabilize nominally planar Mack mode instabilities, although oblique Mack mode and first-mode disturbances are destabilized. Experimentally measured transition onset in the absence of any streaks correlates with an amplification factor of N = 6 for the planar Mack modes. For high enough streak amplitudes, the transition threshold of N = 6 is not reached by the Mack mode instabilities within the length of the cone; however, subharmonic first-mode instabilities, which are destabilized by the presence of the streaks, do reach N = 6 near the end of the cone. The highest stabilization is observed at streak amplitudes of approximately 20 percent of the freestream velocity. Because the use of initial disturbance profiles based on linear optimal growth theory may yield suboptimal control in the context of nonlinear streaks, the computational predictions are extended to nonlinear optimal growth theory. Results show that by using nonlinearly optimal perturbation leads to slightly enhanced stabilization of plane Mack mode disturbances as well as reduced destabilization of subharmonic first-mode disturbances.

Incompressible boundary layer↗

Parameterization of Mixed Layer and Deep-Ocean Mesoscales Including Nonlinearity

In 2011, Chelton et al. carried out a comprehensive census of mesoscales using altimetry data and reached the following conclusions: "essentially all of the observed mesoscale features are nonlinear" and "mesoscales do not move with the mean velocity but with their own drift velocity," which is "the most germane of all the nonlinear metrics." Accounting for these results in a mesoscale parameterization presents conceptual and practical challenges since linear analysis is no longer usable and one needs a model of nonlinearity. A mesoscale parameterization is presented that has the following features: 1) it is based on the solutions of the nonlinear mesoscale dynamical equations, 2) it describes arbitrary tracers, 3) it includes adiabatic (A) and diabatic (D) regimes, 4) the eddy-induced velocity is the sum of a Gent and McWilliams (GM) term plus a new term representing the difference between drift and mean velocities, 5) the new term lowers the transfer of mean potential energy to mesoscales, 6) the isopycnal slopes are not as flat as in the GM case, 7) deep-ocean stratification is enhanced compared to previous parameterizations where being more weakly stratified allowed a large heat uptake that is not observed, 8) the strength of the Deacon cell is reduced. The numerical results are from a stand-alone ocean code with Coordinated Ocean-Ice Reference Experiment I (CORE-I) normal-year forcing.

Baroclinic flows; Mesoscale processes; Mixing; Sub↗

The Salience of Nonlinearities in the Boreal Winter Response to ENSO: Arctic Stratosphere and Europe

The salience of nonlinearities in the Arctic stratospheric response to El Niño - Southern Oscillation (ENSO) is evaluated in a 41 member ensemble of the period 1980 to 2009 in the NASA Goddard Earth Observing System Chemistry-Climate Model. Central Pacific El Niño (CP EN) events preferentially increase zonal wavenumber 2, while Eastern Pacific El Niño (EP EN) events preferentially increase zonal wavenumber 1, though these nonlinearities become statistically robust only after more than 45 events are considered. This leads to a difference in the morphology of SSW events preferentially forced by each ENSO flavor. While the zonal-mean Arctic stratospheric response is little different between EP and CP EN once one accounts for the relative weakness of CP events, the tropospheric subpolar negative North Atlantic Oscillation response is stronger for CP events. Other nonlinearities are even less salient: there is no indication of any nonlinearities in the wave driving between moderate EP EN and extreme EP EN, nor between EN and La Niña (LN). However in approximately 15% of the integrations within our ensemble, there is no difference in SSW frequency between EN and LN, suggesting that a similar SSW frequency for both EN and LN, as has occurred over the past 60 years, can occur by chance. The intra-ensemble variability in LN SSW frequency can be related back to intra-ensemble variability in the tropospheric response to LN.

Arctic↗

Preliminary Nonlinear Structural Analysis of Advanced Composite Tow-Steered Shells with Large Geometric Imperfections

The structural performance of two advanced composite tow-steered shells with and without tow overlaps, and with large geometric imperfections, are predicted using linear and geometrically nonlinear finite element analyses. These shells, 35 in. long and approximately 16.3 in. diameter, are fabricated using automated fiber placement from IM7/8552 graphite/epoxy prepreg. The 8-ply,[±45/±Θ]s. shell layup incorporates a steered fiber angle Θ that varies from 10 deg. to 45 deg. periodically over the shell circumference. Shell analysis models are evaluated using geometric imperfections normalized to ±1 shell wall thickness (±0.040 in.), which are then superposed and rotated incrementally around the shell longitudinal axis. Using these nominal imperfections, the shell prebuckling axial stiffnesses and buckling loads predicted with linear and nonlinear analyses are close to reference values from linear analyses with no imperfections. The linear and nonlinear analyses are then repeated for scaled imperfections that are larger by up to a factor of 10. For these larger imperfections, linear analyses predict reductions in axial stiffnesses and buckling loads of up to 5 and 30 percent, respectively, from reference values. The nonlinear analyses predict even larger reductions in axial stiffnesses and buckling loads of up to 10 and 55 percent, respectively.

Dobrin, Calvin P.↗

Nonlinear Analysis of a Two-Parachute System Undergoing Pendulum Motion

Motion resembling that of a pendulum undergoing large-amplitude limit cycle oscillation was observed during a series of flight tests of an unoccupied Orion Capsule Parachute Assembly System (CPAS) comprised of two parachutes and a capsule payload. Large excursions away from vertical by the capsule could cause it to strike the ground or ocean at a large angle with respect to vertical, or at a large horizontal speed. These conditions are undesirable because they would endanger the occupants of the capsule in an actual mission. A simplified planar dynamics model in conjunction with a nonlinear normal force coefficient vs. angle of attack model serves as the basis of an analytical investigation of the fundamental dynamics of this pendulum motion. Output error methodology from system identification theory was used to identify the parameters of the nonlinear aerodynamics model. The identified model yielded excellent comparison with portions of flight test data where the pendulum motion occurred. Due to the inherent nonlinear nature of the pendulum motion limit cycle, traditional nonlinear analysis techniques were applied to gain further insight into the system. Lyapunov’s direct method provided mathematical proof in the absolute stability of the pendulum mode. Describing Function method was used to predict the amplitude and frequency of the limit cycle oscillation. Finally, phase plane analysis allowed easy visualization on the size and shape of the limit cycle with respect to variations in key aerodynamic parameters.

Pei, Jing↗

Observations on Dynamic Qualification Testing of a Component with Nonlinear Deadband Interfaces

Typical flight hardware dynamic qualification tests exhibit nearly linear structural response when exposed to acceleration inputs from low to full qualification levels. Even in these “linear” cases, there is typically a trend of increasing damping with test levels. The nonlinear mechanism behind this increase in energy dissipation well understood – typically stick/slip hysteresis at joint connections. This paper is concerned with a different type of nonlinearity: deadbands at structural interfaces. Deadband nonlinearities can have a significant influence on structural response and modal/spectral characteristics which can present difficulties in test, analysis, and structural certification. This subject nonlinear behaviour is observed during flight qualification testing of the AQUARIUS instrument and discussed here. Simple physical reasoning and analytical model is utilized to explain the behaviour which is consistent with the test findings.

Majed, Arya↗

Mechanics of Structure Genome-Based Nonlinear Shell Analysis

In this paper, a mechanics of structure genome (MSG)-based nonlinear shell theory is introduced. The theory uses an implicit algorithm combining the Euler’s and Newton’s method that can be applied for shell modeling as well as 3D homogenization. This theory has been implemented into the general-purpose constitutive modeling code SwiftComp, which was originally developed for linear analyses. For the convenience of implementing different nonlinear material models, the SwiftComp user material (SCUMAT), which has a similar interface to the Abaqus user subroutine UMAT, is developed. The capability of the MSG-based nonlinear shell is validated with numerical examples with different material models. A 2-step nonlinear homogenization, with a micromechanics step and a shell analysis step, is demonstrated.

Yufei Long↗

Quantification of Numerical Uncertainty via Nonlinear Dynamical Approach

Motivations (Ensure a Higher Level of Confidence in the Predictability & Reliability of Numerical Simulation for Multiscale Complex Nonlinear Fluid Problems) - The last two decades have been an era when computation is ahead of analysis & when very large scale practical computations are increasingly used in poorly understood multiscale complex nonlinear physical problems & non-traditional fields (Especially when computations offer the ONLY way of generating this type of data limited simulations). - At present some of the numerical uncertainties can be explained and minimized by traditional numerical analysis and standard CFD practices. However, such practices, usually based on linearized analysis, MIGHT NOT be sufficient for strongly nonlinear and/or stiff problems. - We need a good understanding of the nonlinear behavior of numerical schemes being used as an integral part of code verification, validation and certification.

HEC↗

Reconstruction of nonlinear wave propagation

Disclosed are systems and methods for characterizing a nonlinear propagation environment by numerically propagating a measured output waveform resulting from a known input waveform. The numerical propagation reconstructs the input waveform, and in the process, the nonlinear environment is characterized. In certain embodiments, knowledge of the characterized nonlinear environment facilitates determination of an unknown input based on a measured output. Similarly, knowledge of the characterized nonlinear environment also facilitates formation of a desired output based on a configurable input. In both situations, the input thus characterized and the output thus obtained include features that would normally be lost in linear propagations. Such features can include evanescent waves and peripheral waves, such that an image thus obtained are inherently wide-angle, farfield form of microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Detonator comprising a nonlinear transmission line

Detonators are described herein. In a general embodiment, the detonator includes a nonlinear transmission line that has a variable capacitance. Capacitance of the nonlinear transmission line is a function of voltage on the nonlinear transmission line. The nonlinear transmission line receives a voltage pulse from a voltage source and compresses the voltage pulse to generate a trigger signal. Compressing the voltage pulse includes increasing amplitude of the voltage pulse and decreasing length of the voltage pulse in time. An igniter receives the trigger signal and detonates an explosive responsive to receipt of the trigger signal.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Nonlinear interferometer systems and methods

Nonlinear interferometers include a nonlinear optical medium that is situated to produce a conjugate optical beam in response to a pump beam and a probe beam. The pump, probe, and conjugate beams propagate displaced from each other along a common optical path. One of the beams is selectively phase shifted, and the beams are then returned to the nonlinear medium, with the selectively phase shift beam phase shifted again. The nonlinear medium provides phase sensitive gain to at least one of the probe or conjugate beams, and the amplified beam is detected to provide an estimate of the phase shift.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Gain balanced nonlinear optical interferometer

A nonlinear fiber interferometer is disclosed suitable for fiber sensor and other applications. A first nonlinear fiber section amplifies probe and conjugate sidebands of a pump through four-wave mixing. A second section introduces a phase shift to be measured, for example from a sensor. A third nonlinear fiber section amplifies with phase-sensitive gain to increase signal-to-noise ratio. Based on phase-sensitive output power of probe and/or conjugate components, the phase shift can be measured. Superior performance can be obtained by balancing gain between the (first and third) nonlinear sections. Non-fiber, for example photonic integrated circuit, embodiments are disclosed. Differential sensing, alternative detection schemes, sensing applications, associated methods, and other variations are disclosed.

42 ENGINEERING↗

Learning nonlinear level sets for dimensionality reduction in function approximation

We developed a Nonlinear Level-set Learning (NLL) method for dimensionality reduction in high-dimensional function approximation with small data. This work is motivated by a variety of design tasks in real-world engineering applications, where practitioners would replace their computationally intensive physical models (e.g., high-resolution fluid simulators) with fast-to-evaluate predictive machine learning models, so as to accelerate the engineering design processes. There are two major challenges in constructing such predictive models: (a) high-dimensional inputs (e.g., many independent design parameters) and (b) small training data, generated by running extremely time-consuming simulations. Thus, reducing the input dimension is critical to alleviate the over-fitting issue caused by data insufficiency. Existing methods, including sliced inverse regression and active subspace approaches, reduce the input dimension by learning a linear coordinate transformation; our main contribution is to extend the transformation approach to a nonlinear regime. Specifically, we exploit reversible networks (RevNets) to learn nonlinear level sets of a high-dimensional function and parameterize its level sets in low-dimensional spaces. A new loss function was designed to utilize samples of the target functions' gradient to encourage the transformed function to be sensitive to only a few transformed coordinates. The NLL approach is demonstrated by applying it to three 2D functions and two 20D functions for showing the improved approximation accuracy with the use of nonlinear transformation, as well as to an 8D composite material design problem for optimizing the buckling-resistance performance of composite shells of rocket inter-stages.

Zhang, Guannan↗

Gain balanced nonlinear optical interferometer

A nonlinear fiber interferometer is disclosed suitable for fiber sensor and other applications. A first nonlinear fiber section amplifies probe and conjugate sidebands of a pump through four-wave mixing. A second section introduces a phase shift to be measured, for example from a sensor. A third nonlinear fiber section amplifies with phase-sensitive gain to increase signal-to-noise ratio. Based on phase-sensitive output power of probe and/or conjugate components, the phase shift can be measured. Superior performance can be obtained by balancing gain between the (first and third) nonlinear sections. Non-fiber, for example photonic integrated circuit, embodiments are disclosed. Differential sensing, alternative detection schemes, sensing applications, associated methods, and other variations are disclosed.

Lukens, Joseph M.↗

Gain balanced nonlinear optical interferometer

A nonlinear fiber interferometer is disclosed suitable for fiber sensor and other applications. A first nonlinear fiber section amplifies probe and conjugate sidebands of a pump through four-wave mixing. A second section introduces a phase shift to be measured, for example from a sensor. A third nonlinear fiber section amplifies with phase-sensitive gain to increase signal-to-noise ratio. Based on phase-sensitive output power of probe and/or conjugate components, the phase shift can be measured. Superior performance can be obtained by balancing gain between the (first and third) nonlinear sections. Non-fiber, for example photonic integrated circuit, embodiments are disclosed. Differential sensing, alternative detection schemes, sensing applications, associated methods, and other variations are disclosed.

Lukens, Joseph M.↗