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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Ground states of nonlinear Schrödinger systems with saturable nonlinearity in R{sup 2} for two counterpropagating beams

Counterpropagating optical beams in nonlinear media give rise to a host of interesting nonlinear phenomena such as the formation of spatial solitons, spatiotemporal instabilities, self-focusing and self-trapping, etc. Here we study the existence of ground state (the energy minimizer under the L{sup 2}-normalization condition) in two-dimensional (2D) nonlinear Schrödinger (NLS) systems with saturable nonlinearity, which describes paraxial counterpropagating beams in isotropic local media. The nonlinear coefficient of saturable nonlinearity exhibits a threshold which is crucial in determining whether the ground state exists. The threshold can be estimated by the Gagliardo-Nirenberg inequality and the ground state existence can be proved by the energy method, but not the concentration-compactness method. Our results also show the essential difference between 2D NLS equations with cubic and saturable nonlinearities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

Here, this work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. These approximate solutions may arise from early termination of an iterative method, a lower-fidelity model, or a projection-based reduced-order model, for example. The proposed statistical model comprises the sum of a deterministic regression-function model and a stochastic noise model. The method constructs the regression-function model by applying regression techniques from machine learning (e.g., support vector regression, artificial neural networks) to map features (i.e., error indicators such as sampled elements of the residual) to a prediction of the approximate-solution error. The method constructs the noise model as a mean-zero Gaussian random variable whose variance is computed as the sample variance of the approximate-solution error on a test set; this variance can be interpreted as the epistemic uncertainty introduced by the approximate solution. This work considers a wide range of feature-engineering methods, data-set-construction techniques, and regression techniques that aim to ensure that (1) the features are cheaply computable, (2) the noise model exhibits low variance (i.e., low epistemic uncertainty introduced), and (3) the regression model generalizes to independent test data. Finally, numerical experiments performed on several computational-mechanics problems and types of approximate solutions demonstrate the ability of the method to generate statistical models of the error that satisfy these criteria and significantly outperform more commonly adopted approaches for error modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Nonlinear luminescence response of CaF{sub 2}:Eu and YAlO{sub 3}:Ce to single-ion excitation

Understanding scintillation physics and nonproportionality is essential to accelerate materials discovery that has been restricted due to the difficulties inherent to large crystal growth and complex nature of gamma-solid interaction. Taking advantage of less restrictive growth and deposition techniques for smaller crystal sizes or thin films and better fundamental understanding of ion-solid interactions, a unique ion approach is demonstrated to effectively screen candidate scintillators with relatively small size and evaluate their nonlinear scintillation response. Response of CaF{sub 2}:Eu and YAlO{sub 3}:Ce scintillators to single ions of H{sup +}, He{sup +}, and O{sup 3+} are measured by the corresponding pulse height over a continuous energy range using a time-of-flight–scintillator–photoelectric multiplier tube apparatus. Nonlinear response of the scintillators under ionizing ion irradiation is quantitatively evaluated by considering the energy partitioning process. In a differential energy deposition region with negligible displacement damage, the low, medium and high excitation energy deposition density (D{sub exci}) can be produced by energetic H{sup +}, He{sup +} and O{sup 3+} ions, respectively, and significantly different impacts on the response characteristics of these two benchmark scintillators are observed. For CaF{sub 2}:Eu, the scintillation efficiency under ion irradiation monotonically decreases with increasing excitation-energy density. In contrast, the response efficiency of YAlO{sub 3}:Ce scintillation initially increases with excitation-energy density at low excitation-energy densities, goes through a maximum, and then decreases with further increasing excitation-energy density. The fundamental mechanism causing these different response behaviours in the scintillators is based on the competition between the scintillation response and the nonradiative quenching process under different excitation densities, which is also the main origin of the nonlinear response of the scintillators to irradiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Enhanced optical nonlinearities in the near-infrared using III-nitride heterostructures coupled to metamaterials

We use planar metamaterial resonators to enhance, by more than two orders of magnitude, the optical second harmonic generation, in the near infrared, obtained from intersubband transitions in III-Nitride heterostructures. The improvement arises from two factors: employing an asymmetric double quantum well design and aligning the resonators’ cross-polarized resonances with the intersubband transition energies. The resulting nonlinear metamaterial operates at wavelengths where single photon detection is available, and represents a new class of sources for quantum photonics related phenomena.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2014

Nonlinear modelling of polymer electrolyte membrane fuel cell stack using nonlinear cancellation technique

Fuel cells are promising new energy conversion devices that are friendly to the environment. A set of control systems are required in order to operate a fuel cell based power plant system optimally. For the purpose of control system design, an accurate fuel cell stack model in describing the dynamics of the real system is needed. Currently, linear model are widely used for fuel cell stack control purposes, but it has limitations in narrow operation range. While nonlinear models lead to nonlinear control implemnetation whos more complex and hard computing. In this research, nonlinear cancellation technique will be used to transform a nonlinear model into a linear form while maintaining the nonlinear characteristics. The transformation is done by replacing the input of the original model by a certain virtual input that has nonlinear relationship with the original input. Then the equality of the two models is tested by running a series of simulation. Input variation of H2, O2 and H2O as well as disturbance input I (current load) are studied by simulation. The error of comparison between the proposed model and the original nonlinear model are less than 1 %. Thus we can conclude that nonlinear cancellation technique can be used to represent fuel cell nonlinear model in a simple linear form while maintaining the nonlinear characteristics and therefore retain the wide operation range.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Giant optical second- and third-order nonlinearities at a telecom wavelength

A material platform that excels in both optical second- and third-order nonlinearities at a telecom wavelength is theoretically and experimentally demonstrated. In this TiN-based coupled metallic quantum well structure, electronic subbands are engineered to support doubly resonant inter-subband transitions for an exceptionally high second-order nonlinearity and provide single-photon transitions for a remarkable third-order nonlinearity within the 1400–1600 nm bandwidth. The second-order susceptibility χ (2) reaches 2840 pm/V at 1440 nm, while the Kerr coefficient n 2 arrives at 2.8 × 10 −10 cm 2 /W at 1460 nm. The achievement of simultaneous strong second- and third-order nonlinearities in one material at a telecom wavelength creates opportunities for multi-functional advanced applications in the field of nonlinear optics.

Chen, Ching-Fu (ORCID:0000000262510722)↗
DOE OSTI2019

Investigation of the nonlinearity of transducer acoustic couplants for nonlinear elastic measurements

The study of nonlinear elasticity of materials often relies on attaching contact transducers to a sample to achieve the required strain amplitudes. When measuring and quantifying the degree of nonlinearity, it is assumed that the nonlinearity of the bond between the material and the transducer is negligible. We aim to characterize the nonlinearity of common acoustic couplants used in nonlinear measurements. Other factors are also reported since bond nonlinearity is not the only important property when choosing an acoustic couplant, i.e., amount of energy transfer, thermal properties, cure time, toxicity, and ease of application and/or removal. Various types of acoustic couplants including, epoxies, glues, thermal adhesives, and coupling agents were studied using Nonlinear Resonance Ultrasound Spectroscopy (NRUS), which is a measure of the hysteretic nonlinearity of a material. Measurements were made on cylindrical samples of acrylic, aluminum alloy 6061-T651, and Crab Orchard sandstone, chosen for their range of sound speeds, attenuation, and nonlinearity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nonlinear Topological Photonics: Capturing Nonlinear Dynamics and Optical Thermodynamics

Combining multiple optical resonators or engineering dispersion of complex media has provided an effective method for demonstrating topological physics controlling photons in unprecedented ways such as unidirectional light propagation and spatially localized modes between an interface or on a corner. Further, adding nonlinear responses to those topological photonic systems has enabled achieving diverse phases of photons in both space and time, allowing for more functionalities in photonic devices that provide a new playground for studying dynamic features of nonlinear topological systems. However, most methods for describing nonlinear topological photonic systems rely on linear topological theories, making it challenging to accurately characterize the topology of nonlinear systems. Thus, substantial efforts have focused on rigorously describing nonlinear topological phases and developing effective tools to analyze nonlinear topological effects. Meanwhile, coupled multimode optical waveguides with nonlinear dynamic responses provide an excellent platform for the statistical description of photons, opening a new paradigm called “optical thermodynamics”. This review will introduce the basic concepts of nonlinear topological photonics and the recent development of theoretical approaches focusing on data-driven approaches for creating phase diagrams as well as the spectral localizer framework and the pseudospectrum method for understanding optical nonlinearities in topological systems. In addition, the new concept of optical thermodynamics will be introduced with some recent theoretical works.

Topological photonics↗
DOE OSTI2019

Microstructure-based model of nonlinear ultrasonic response in materials with distributed defects

Nonlinear ultrasonic technique is one of promising NDE methods for monitoring defect evolution in irradiated nuclear materials. In this work, we have studied the effect of distributed defects on nonlinear ultrasonic response, in particular, the nonlinear parameter ß from the 2nd harmonic wave. A three-dimensional microstructure-based model has been developed for investigating the dynamic interaction between distributed defects and a propagating longitudinal sound wave. Both linear and nonlinear materials are considered. It is known that the 2nd harmonic wave is generated when a monochromatic wave propagates in a nonlinear elastic material. The results show that second phase particles with elastic heterogeneity and lattice mismatch have strong impact on the nonlinear parameter ß. Lattice mismatches have more effect on the nonlinear parameter no matter they are expansion or contraction. The developed model enables one to explore the contributions of different types of defects to the nonlinear ultrasonic signals and shed light on the development of nonlinear ultrasound nondestructive detection of material defects in nuclear reactors.

Second harmonic generation, Scattered distributed ↗
DOE OSTI2021

Transition of a network of nonlinear interactions into a regime of strong nonlinear fluctuations: A paradigm for the edge localized mode onset

We study how a network of nonlinear oscillators transits into a regime of strong nonlinear fluctuations when perturbed by a triad. In this regime, most of the potential energy contained in the waves is made available to the system through strong nonlinear fluctuations. This analysis is motivated by recent experimental observations [Dominski and Diallo, Plasma Phys. Control. Fusion 62, 095011 (2020)] where it was found that magnetic fluctuations trigger the onset of edge localized modes by suddenly exciting a network of nonlinear interactions. In our study, we consider the simplest system of many harmonic oscillators that are organized in a network of nonlinear triads. We model and simulate the sudden transition of this network of triads into a regime of strong nonlinear fluctuations—reminiscent of the onset of edge localized modes in tokamaks. This transition is triggered by the activation of a nonlinear perturbation. An abrupt rise of the system's disorder (an entropy-like quantity) is measured during the transition. This transition from weak to strong nonlinear fluctuations is even more abrupt when these fluctuations are chaotic, i.e., when the timescale of the nonlinear interaction is comparable to the timescale of the wave oscillations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

In-situ fatigue monitoring procedure using nonlinear ultrasonic surface waves considering the nonlinear effects in the measurement system

Second harmonic generation using nonlinear ultrasonic waves have been shown to be an early indicator of possible fatigue damage in nuclear power plant components. This technique relies on measuring amplitudes, making it highly susceptible to variations in transducer coupling and instrumentation. This paper proposes an experimental procedure for in-situ surface wave nonlinear ultrasound measurements on specimen with permanently mounted transducers under high cycle fatigue loading without interrupting the experiment. It allows continuous monitoring and minimizes variation due to transducer coupling. Moreover, relations describing the effects of the measurement system nonlinearity including the effects of the material transfer function on the measured nonlinearity parameter are derived. An in-situ high cycle fatigue test was conducted using two 304 stainless steel specimens with two different excitation frequencies. A comprehensive analysis of the nonlinear sources, which result in variations in the measured nonlinearity parameters, was performed and the effects of the system nonlinearities are explained and identified. In both specimens, monotonic trend was observed in nonlinear parameter when the value of fundamental amplitude was not changing.

42 ENGINEERING↗