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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Control of optical bistability and third-order nonlinearity via tunneling induced quantum interference in triangular quantum dot molecules

The optical bistability of a triangular quantum dot molecules embedded inside a unidirectional ring cavity is studied. The type, the threshold and the hysteresis loop of the optical bistability curves can be modified by the tunneling parameters, as well as the probe laser field. The linear and nonlinear susceptibilities of the medium are also studied to interpret the corresponding results. The physical interpretation is that the tunneling can induce the quantum interference, which modifies the linear and the nonlinear response of the medium. As a consequence, the characteristics of the optical bistability are changed. The scheme proposed here can be utilized for optimizing and controlling the optical switching process.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2000

Synthesis Methods for Robust Passification and Control

The research effort under this cooperative agreement has been essentially the continuation of the work from previous grants. The ongoing work has primarily focused on developing passivity-based control techniques for Linear Time-Invariant (LTI) systems. During this period, there has been a significant progress made in the area of passivity-based control of LTI systems and some preliminary results have also been obtained for nonlinear systems, as well. The prior work has addressed optimal control design for inherently passive as well as non- passive linear systems. For exploiting the robustness characteristics of passivity-based controllers the passification methodology was developed for LTI systems that are not inherently passive. Various methods of passification were first proposed in and further developed. The robustness of passification was addressed for multi-input multi-output (MIMO) systems for certain classes of uncertainties using frequency-domain methods. For MIMO systems, a state-space approach using Linear Matrix Inequality (LMI)-based formulation was presented, for passification of non-passive LTI systems. An LMI-based robust passification technique was presented for systems with redundant actuators and sensors. The redundancy in actuators and sensors was used effectively for robust passification using the LMI formulation. The passification was designed to be robust to an interval-type uncertainties in system parameters. The passification techniques were used to design a robust controller for Benchmark Active Control Technology wing under parametric uncertainties. The results on passive nonlinear systems, however, are very limited to date. Our recent work in this area was presented, wherein some stability results were obtained for passive nonlinear systems that are affine in control.

Kelkar, Atul G.↗
DOE OSTI2019

Fitting local, low-dimensional parameterizations of optical turbulence modeled from optimal transport velocity vectors

This work exploits a connection between optimal transport theory and the physics of image propagation to yield a locally low-dimensional model of turbulence-corrupted imagery. Optimal transport produces an invertible, pixel-wise linear trajectories to approximate the globally nonlinear turbulence between a clean and turbulence corrupted image pair. We use the low-dimensional model to fit subsets of the optimal transport vector fields and stitch the local models into a surrogate for the global map to be used for image cleaning. Experiments are performed on laboratory generated data of beam propagation using different values of the Fried parameter (a scale measuring turbulence coherence) as well as a toy data set. The results suggest this is a fruitful direction, and first step, towards using multiple realizations of turbulence corrupted images to learn a blind surrogate for the optimal transport vector field for image cleaning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Energy-Optimal Vehicle Longitudinal Motion Control via Pontryagin’s Minimum Principle and Ultra-Local Model

Longitudinal vehicle motion control is essential for enhancing performance and optimizing a vehicle’s energy usage. However, it remains a challenging task due to the nonlinear and uncertain nature of vehicle dynamics, along with varying driving conditions. This paper presents a novel ultra-local optimal control approach based on Pontryagin’s Minimum Principle (PMP) that circumvents the need for detailed system identification by employing an ultra-local model. The control objective is to minimize the total energy consumption under boundary conditions while ensuring smooth traction force generation. The proposed approach is evaluated using a high-fidelity vehicle model in three representative scenarios: (i) nominal driving, (ii) a change in tire road friction coefficient (TRFC) from 0.5 to 0.65 and road slope from 0% to 5% during the maneuver, with target velocity unchanged, and (iii) a change in target velocity from 20 m/s to 0 m/s during the maneuver, while maintaining nominal TRFC and slope conditions. The simulation results demonstrate that the proposed method delivers robust performance, effectively balancing consumption and tracking accuracy in all tested scenarios.

Waleed khan, Muhammad [The University of Texas at ↗
NASA NTRS1971

Analytical methods for performance evaluation of nonlinear filters.

In the investigation, the filtering problem is considered in the continuous time domain. The postulated simple suboptimal nonlinear filter structure closely parallels the structure of the Kalman-Bucy optimal linear filter algorithm. Two filter performance evaluation methods are developed based on the Kolmogorov equations for the transition density of Markov processes. The expansions in the approximations for the nonlinear system and observation functions are in effect carried out up to second-order terms in both methods. The description of the filter's performance is sought in terms of second-order statistics in both methods.

Bejczy, A. K.↗
DOE OSTI2022

Deterministic modeling of hybrid nonlinear effects in epsilon-near-zero thin films

In nonlinear optics, significant effort is concentrated on improving the strength and efficiency of interactions; however, experimentally investigating nonlinear materials is a complex, time-consuming, and costly investment. Moreover, it is often challenging to isolate, study, and optimize material parameters in an experiment due to complexities in the growth process. Recently, epsilon-near-zero materials have received a great deal of attention as promising nonlinear optical materials, but like many up-and-coming materials, the ability to explore and optimize their properties has been challenging. Here, we establish a framework to rapidly evaluate the performance of nonlinear epsilon-near-zero materials for both inter- and intraband effects in silico, requiring only an energy-momentum (E-k) diagram, linear optical properties, and experimental conditions. Measured nonlinear reflection and transmission in gallium-doped zinc oxide films are compared to the numerical framework for both intra- and interband excitation to verify accuracy across wavelength and irradiance while two figures of merit (FoMs) are introduced to quickly evaluate the performance of films without a full numerical framework. This capability is used to predict the performance of highly doped gallium nitride, cadmium oxide, zinc oxide, and indium tin oxide films, and efficient intra- and interband operation conditions are identified. Through this numerical framework and the FoMs, the exploration of unstudied epsilon-near-zero materials is enabled without the need for a nonlinear experiment, thereby accelerating the search for more efficient nonlinear materials and excitation conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Topology optimization of 3D photonic crystals with complete bandgaps

The design of photonic crystals with complete bandgaps has recently received considerable research focus for numerous reasons. This work leverages well-known nonlinear programming techniques to alleviate the non-smoothness caused by degenerate eigenvalues such that topology optimization problems can be solved with the open-source IPOPT software. A fully-vectorial plane wave expansion technique is used with an iterative eigensolver to efficiently predict dispersion properties of candidate structures. Nonlinear programming is employed to solve the inverse problem of designing three-dimensional periodic structures that exhibit complete two-dimensional (2D) and three-dimensional (3D) photonic bandgaps. Mesh refinement is performed to alleviate the large computational burden of designing and analyzing photonic crystals, and a periodic density filter is implemented to impose a minimum feature size for manufacturability considerations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

H–J–B Equations of Optimal Consumption-Investment and Verification Theorems

We consider a consumption-investment problem on infinite time horizon maximizing discounted expected HARA utility for a general incomplete market model. Based on dynamic programming approach we derive the relevant H–J–B equation and study the existence and uniqueness of the solution to the nonlinear partial differential equation. By using the smooth solution we construct the optimal consumption rate and portfolio strategy and then prove the verification theorems under certain general settings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Field of view extension and truncation correction for MR-based human attenuation correction in simultaneous MR/PET imaging

Purpose: In quantitative PET imaging, it is critical to accurately measure and compensate for the attenuation of the photons absorbed in the tissue. While in PET/CT the linear attenuation coefficients can be easily determined from a low-dose CT-based transmission scan, in whole-body MR/PET the computation of the linear attenuation coefficients is based on the MR data. However, a constraint of the MR-based attenuation correction (AC) is the MR-inherent field-of-view (FoV) limitation due to static magnetic field (B{sub 0}) inhomogeneities and gradient nonlinearities. Therefore, the MR-based human AC map may be truncated or geometrically distorted toward the edges of the FoV and, consequently, the PET reconstruction with MR-based AC may be biased. This is especially of impact laterally where the patient arms rest beside the body and are not fully considered. Methods: A method is proposed to extend the MR FoV by determining an optimal readout gradient field which locally compensates B{sub 0} inhomogeneities and gradient nonlinearities. This technique was used to reduce truncation in AC maps of 12 patients, and the impact on the PET quantification was analyzed and compared to truncated data without applying the FoV extension and additionally to an established approach of PET-based FoV extension. Results: The truncation artifacts in the MR-based AC maps were successfully reduced in all patients, and the mean body volume was thereby increased by 5.4%. In some cases large patient-dependent changes in SUV of up to 30% were observed in individual lesions when compared to the standard truncated attenuation map. Conclusions: The proposed technique successfully extends the MR FoV in MR-based attenuation correction and shows an improvement of PET quantification in whole-body MR/PET hybrid imaging. In comparison to the PET-based completion of the truncated body contour, the proposed method is also applicable to specialized PET tracers with little uptake in the arms and might reduce the computation time by obviating the need for iterative calculations of the PET emission data beyond those required for reconstructing images.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Multi-objective optimization of peel and shear strengths in ultrasonic metal welding using machine learning-based response surface methodology

Ultrasonic metal welding (UMW) is a solid-state joining technique with varied industrial applications. Despite of its numerous advantages, UMW has a relative narrow operating window and is sensitive to variations in process conditions. As such, it is imperative to quantitatively characterize the influence of welding parameters on the resulting joint quality. The quantification model can be subsequently used to optimize the parameters. Conventional response surface methodology (RSM) usually employs linear or polynomial models, which may not be able to capture the intricate, nonlinear input-output relationships in UMW. Furthermore, some UMW applications call for simultaneous optimization of multiple quality indices such as peel strength, shear strength, electrical conductivity, and thermal conductivity. To address these challenges, this paper develops a machine learning (ML)-based RSM to model the input-output relationships in UMW and jointly optimize two quality indices, namely, peel and shear strengths. The performance of various ML methods including spline regression, Gaussian process regression (GPR), support vector regression (SVR), and conventional polynomial regression models with different orders is compared. A case study using experimental data shows that GPR with radial basis function (RBF) kernel and SVR with RBF kernel achieve the best prediction accuracy. The obtained response surface models are then used to optimize a compound joint strength indicator that is defined as the average of normalized shear and peel strengths. In addition, the case study reveals different patterns in the response surfaces of shear and peel strengths, which has not been systematically studied in the literature. While developed for the UMW application, the method can be extended to other manufacturing processes.

42 ENGINEERING↗
NASA NTRS1988

Fuel-optimal trajectories for aeroassisted coplanar orbital transfer problem

The optimal-control problem arising in coplanar orbital transfer using aeroassist technology is addressed. The maneuver involves the transfer from high earth orbit to low earth orbit with minimum fuel consumption. Simulations are carried out to obtain a corridor of entry conditions which are suitable for flying the spacecraft through the atmosphere. A highlight of the present work is the application of an efficient multiple shooting method for handling the difficult nonlinear two-point boundary value problem resulting from the optimization procedure.

Naidu, D. S.↗
DOE OSTI2014

Terahertz generation by two cross focused Gaussian laser beams in magnetized plasma

This paper presents a theoretical model for terahertz (THz) radiation generation by two cross-focused Gaussian laser beams in a collisionless magnetoplasma. The plasma is redistributed due to the ponderomotive nonlinearity which leads to the cross focusing of the laser beams. The focusing of the copropagating laser beams increases with increasing the externally applied static magnetic field which is perpendicular to the wave propagation direction. The nonlinear current at THz frequency arises on account of nonlinear ponderomotive force as a result of beating of the two lasers. The generated THz radiation amplitude increases significantly with increasing magnetic field. The cross focusing of two laser beams enhances the THz yield. Optimization of laser-plasma parameters gives the radiated normalized THz power of the order of 10 kW.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Competing effects of Kerr nonlinearity and K-photon absorptions on continuous-wave laser inscriptions

Material processing with laser offers a reliable tool in a large variety of micromachining technology, ranging from on-disc inscriptions to cell ablations through DNA combing and imprinting for fabrications of micro and nanofluidic devices. In these applications lasers are designed to operate in specific regimes characterized by their powers and wavelengths, so understanding characteristic properties of the distinct possible laser operation regimes turns out to be a relevant step toward optimization of their uses as well as improvement of the technology. In this work we examine the stability of a model of femtosecond laser intended for laser inscriptions in nonlinear transparent media, taking into consideration the laser-induced material damage and multiphoton ionization. The model approximates the laser dynamics by a complex Ginzburg–Landau equation with a Kerr plus a high-order nonlinear term accounting for K-photon ionization, coupled to a Drude equation for time evolution of the electron plasma density. Following the Benjamin–Feir instability theory it is shown that depending on characteristic parameters of the model, multiphoton ionization processes can stabilize continuous-wave or pulse regimes. These parameters include the group-delay dispersion, the linear and nonlinear gains, the phase shift per roundtrip and the plasma ionization rate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Spatial properties of entangled photon pairs generated in nonlinear layered structures

A spatial quantum model of spontaneous parametric down-conversion in nonlinear layered structures is developed expanding the interacting vectorial fields into monochromatic plane waves. A two-photon spectral amplitude depending on the signal- and idler-field frequencies and propagation directions is used to derive transverse profiles of the emitted fields as well as their spatial correlations. Intensity spatial profiles and their spatial correlations are mainly determined by the positions of transmission peaks formed in these structures with photonic bands. A method for geometry optimization of the structures with respect to efficiency of the nonlinear process is suggested. Several structures composed of GaN/AlN layers are analyzed as typical examples. They allow the generation of photon pairs correlated in several emission directions. Photon-pair generation rates increasing better than the second power of the number of layers can be reached. Also, structures efficiently generated photon pairs showing antibunching and anticoalescence can be obtained. Three reasons for splitting the correlated area in photonic-band-gap structures are revealed: zig-zag movement of photons inside the structure, spatial symmetry, and polarization-dependent properties. Also, spectral splitting can be observed in these structures.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Design and optimization of a bi-axial vibration-driven electromagnetic generator

To scavenge energy from ambient vibrations with arbitrary in-plane motion directions and over a wide frequency range, a novel electromagnetic vibration energy harvester is designed and optimized. In the harvester, a circular cross-section elastic rod, not a traditional thin cantilever beam, is used to extract ambient vibration energy because of its capability to collect vibration from arbitrary in-plane motion directions. The magnetic interaction between magnets and the iron core contributes to a nonlinear oscillation of the rod with increased frequency bandwidth. The influences of the structure configurations on the electrical output and the working bandwidth of the harvester are investigated using Ansoft's Maxwell 3D to achieve optimal performance. The experimental results show that the harvester is sensitive to vibrations from arbitrary in-plane directions and it exhibits a bandwidth of 5.7 Hz and a maximum power of 13.4 mW at an acceleration of 0.6 g (with g=9.8 ms⁻²).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently compute the sensitivities of the model predictive control (MPC) objective function and constraints penalties. To guarantee safety upon deployment, we derive probabilistic guarantees on closed-loop stability and constraint satisfaction based on indicator functions and Hoeffding’s inequality. We empirically demonstrate that the proposed method can learn neural control policies for various parametric optimal control tasks. In particular, we show that the proposed DPC method can stabilize systems with unstable dynamics, track time-varying references, and satisfy nonlinear state and input constraints. Our DPC method has practical time savings compared to alternative approaches for fast and memory-efficient controller design. Specifically, DPC does not depend on a supervisory controller as opposed to approximate MPC based on imitation learning. We demonstrate that, without losing performance, DPC is scalable with greatly reduced demands on memory and computation compared to implicit and explicit MPC while being more sample efficient than model-free reinforcement learning (RL) algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Determination of natural frequencies by coupled method of homotopy perturbation and variational method for strongly nonlinear oscillators

In this paper a new approach combining the features of the homotopy concept with variational approach is proposed to find accurate analytical solutions for nonlinear oscillators with and without a fractional power restoring force. Since the first-order approximation leads to very accurate results, comparisons with other results are presented to show the effectiveness of this method. The validity of the method is independent of whether or not there exist small or large parameters in the considered nonlinear equations; the obtained results prove the validity and efficiency of the method, which can be easily extended to other strongly nonlinear problems. At the end we compare our procedure with the optimal homotopy perturbation method.

97 MATHEMATICS AND COMPUTING↗