Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “nonlinear response”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Time-Resolved Ultrafast Transient Polarization Spectroscopy to Investigate Nonlinear Processes and Dynamics in Electronically Excited Molecules on the Femtosecond Time Scale

Here, we report a novel experimental technique to investigate ultrafast dynamics in photoexcited molecules by probing the third-order nonlinear optical susceptibility. A non-colinear 3-pulse scheme is developed to probe the ultrafast dynamics of excited electronic states using the optical Kerr effect by time-resolved polarization spectroscopy. Optical heterodyne and optical homodyne detection are demonstrated to measure the third-order nonlinear optical response for the S 1 excited state of liquid nitrobenzene, which is populated by 2-photon absorption of a 780 nm 35 fs excitation pulse.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Perspectives and progress on wurtzite ferroelectrics: Synthesis, characterization, theory, and device applications

Wurtzite ferroelectrics are an emerging material class that expands the functionality and application space of wide bandgap semiconductors. Promising physical properties of binary wurtzite semiconductors include a large, reorientable spontaneous polarization, direct band gaps that span from the infrared to ultraviolet, large thermal conductivities and acoustic wave velocities, high mobility electron and hole channels, and low optical losses. The ability to reverse the polarization in ternary wurtzite semiconductors at room temperature enables memory and analog type functionality and quasi-phase matching in optical devices and boosts the ecosystem of wurtzite semiconductors, provided the appropriate combination of properties can be achieved for any given application. In this article, advances in the design, synthesis, and characterization of wurtzite ferroelectric materials and devices are discussed. Highlights include: the direct and quantitative observation of polarization reversal of ~135 μC/cm 2 charge in Al 1-x B x N via electron microscopy, Al 1-x B x N ferroelectric domain patterns poled down to 400 nm in width via scanning probe microscopy, and full polarization retention after over 1000 h of 200 °C baking and a 2× enhancement relative to ZnO in the nonlinear optical response of Zn 1-x Mg x O. In conclusion, the main tradeoffs, challenges, and opportunities in thin film deposition, heterostructure design and characterization, and device fabrication are overviewed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

MASTODON: An Open-Source Software for Seismic Analysis and Risk Assessment of Critical Infrastructure

Seismic analysis and risk assessment of safety-critical infrastructure like hospitals, nuclear power plants, dams, and facilities handling radioactive materials involve computationally intensive numerical models and coupled multiphysics scenarios. They are also performed in a strict regulatory environment that requires high software quality assurance standards, and in the case of safety-related nuclear facilities, a conformance to the American Society of Mechanical Engineers Nuclear Quality Assurance (NQA-1) standard. This paper introduces the open-source finite-element software, MASTODON (Multi-hazard Analysis of Stochastic Time-Domain Phenomena), which implements state-of-the-art seismic analysis and risk assessment tools in a quality-controlled environment. MASTODON is built on MOOSE (Multi-physics Object-Oriented Simulation Environment), which is a highly parallelizable, NQA-1 conforming, coupled multiphysics, finite-element framework developed at Idaho National Laboratory. MASTODON is capable of fault rupture and source-to-site wave propagation using the domain reduction method, nonlinear site response, and soil-structure interaction analysis, implicit and explicit time integration, automated stochastic simulations, and seismic probabilistic risk assessment. When coupled with other MOOSE applications, MASTODON can also solve strongly and weakly coupled multiphysics problems. This paper presents a summary of the capabilities of MASTODON and some demonstrative examples.

42 ENGINEERING↗
DOE OSTI2022

Neural net modeling of equilibria in NSTX-U

Neural networks (NNs) offer a path towards synthesizing and interpreting data on faster timescales than traditional physics-informed computational models. In this work we develop two NNs relevant to equilibrium and shape control modeling, which are part of a suite of tools being developed for the National Spherical Torus Experiment-Upgrade for fast prediction, optimization, and visualization of plasma scenarios. The networks include Eqnet, a free-boundary equilibrium solver trained on the EFIT01 (Equilibrium FITtting 01) reconstruction algorithm, and Pertnet, which is trained on the Gspert code and predicts the non-rigid plasma response, a nonlinear term that arises in shape control modeling. The NNs are trained with different combinations of inputs and outputs in order to offer flexibility in use cases. In particular, Eqnet can use magnetic diagnostics as inputs and act as an EFIT-like reconstruction algorithm, or, by using pressure and current profile information the NN can act as a forward Grad–Shafranov equilibrium solver. This forward-mode version is envisioned to be implemented in the suite of tools for simulation of plasma scenarios. The reconstruction-mode version gives some performance improvements compared to the online reconstruction code real-time EFIT, especially when vessel eddy currents are significant. Here, we report strong performance for all NNs indicating that the models could reliably be used within closed-loop simulations or other applications. Some limitations are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Identification and control of the exhaust using gas perturbations in the DIII-D tokamak

This paper presents perturbative experiments that enable the validation and development of control-oriented models for exhaust control. We identify the response of the divertor plasma and scrape-off layer in the DIII-D tokamak to deuterium and nitrogen multi-sine perturbations, in favorable and unfavorable field directions for H-mode access. We obtained good signal-to-noise ratios in the 1–10 Hz frequency range by measuring Balmer-alpha, Lyman-alpha, and N 4+ line emission, radiated power, and neutral pressure. We find a similar phase response across gas species and magnetic field directions, while the gain response is nonlinear. With these experiments, we identify a control-oriented model to design a divertor radiated power controller to track specified reference waveforms in conjunction with resonant magnetic perturbations. Although the physics basis for compatibility between detachment and resonant magnetic perturbation edge-localized mode suppression remains to be demonstrated, the present results provide a robust controller that represents a promising step toward future joint control strategies.

detachment control↗
DOE OSTI2023

High harmonic generation governed by edge states in triangular graphene quantum dots

Here, we study theoretically interaction of short optical pulses with triangular graphene quantum dots. If such quantum dots have zigzag edges then there are in-gap degenerate edge states, the number of which depends on the size of the system. We show that the nonlinear optical response, such as high harmonic generation, of triangular quantum dots is sensitive to the initial electron population of their edge states. In general, the emission spectra of quantum dots have weak dependence on the number of occupied edge states, but if half of the edge states are initially occupied, which can be realized only in the quantum dots with even number of edge states, then the even high harmonics are strongly suppressed. The suppression is the strongest when the frequency of the pulse is well below the band gap and it is weak when the pulse frequency becomes comparable to the band gap of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Characteristic terahertz emissions induced by optically excited collective orbital modes

Here, we study the generation of collective orbital modes, their evolution, and the characteristic nonlinear optical response induced by them in a photoinduced orbital-ordered correlated oxide using real-time simulations based on an interacting multiband tight-binding (TB) model. The d-d optical transitions under femtoseconds light-pulse in an orbital-ordered state excite collective orbital modes, also known as “orbitons”. Consistently incorporating electronic interactions and the interplay between charge, spin, and lattice degrees of freedom in the TB-model provides a clearer understanding of how these factors influence the generation and evolution of collective orbital modes. The dynamics of Jahn-Teller vibrational modes in the photoinduced state modify the intersite orbital interaction, which further amplifies these orbital modes. In the presence of weak ferroelectricity, the excitation of collective orbital modes induces a strong THz oscillatory photocurrent, which is long-lived. This suggests an alternative way to experimentally detect low-energy collective modes through THz-emission studies in the photoinduced state. Our study also elucidates that quasiparticle dynamics in improper ferroelectric oxides can be exploited to achieve highly interesting and nontrivial optoelectronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Unconventional Photocurrents from Surface Fermi Arcs in Topological Chiral Semimetals

The nonlinear optical responses from topological semimetals are crucial in both understanding the fundamental properties of quantum materials and designing next-generation light sensors or solar cells. However, previous work focused on the optical effects from bulk states only, disregarding the responses from topological surface states. Here, we propose a new surface-only photocurrent response from chiral Fermi arcs. Using the ideal topological chiral semimetal RhSi as a representative, we quantitatively compute the photogalvanic currents from Fermi arcs on different surfaces. By rigorous crystal symmetry analysis, we demonstrate that Fermi arc photogalvanic currents can be perpendicular to the bulk injection currents regardless of the choice of materials surface. We then generalize this finding to other cubic chiral space groups and predict material candidates. Our theory reveals a powerful notion where common crystalline symmetry can be used to completely disentangle bulk and surface optical responses in many conducting material families.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Collective Modes in Multilayer Graphene/𝛼−RuCl 3 Heterostructures

Collective modes in multilayer graphene, such as plasmons and phonons, exhibit sensitivity to displacement fields and interlayer coupling, distinguishing them from their counterparts in single-layer graphene. Here, we engineer collective modes in charge-transfer heterostructures composed of multilayer graphene and 𝛼−RuCl 3 . In heterostructures with a single 𝛼−RuCl 3 interface, the charge transfer generates displacement fields up to 7 V/nm at the interface between 𝛼−RuCl 3 and the adjacent graphene layer—the highest value achieved through charge-transfer methods. As a result of the broken inversion symmetry, we discover enhanced nonlinear optical response and modified phonon selection rules. Conversely, we find that multilayer graphene sandwiched between two 𝛼−RuCl 3 flakes causes displacement fields to cancel. There, we achieve carrier densities as high as 8 ×10 13 cm −2 in multilayer graphene and restore the phonon selection rules to their unperturbed state. Meanwhile, we demonstrate that plasmonic properties derive from the depletion of multiple valence bands. As a result of the quasilinear band dispersion, these “Dirac multiband plasmons” are relatively unaffected by displacement fields. On the other hand, the inverted heterostructure sequence—two multilayer graphene sheets encapsulating 𝛼−RuCl 3 —activates significant alteration of the plasmons via interlayer plasmon-plasmon coupling. Hence, multilayer graphene and 𝛼−RuCl 3 heterostructures offer a gate-free platform for engineering collective modes derived from inversion symmetry and interlayer coupling.

Moore, Samuel L. [Columbia University, New York, N↗
DOE OSTI2020

Nonlinear drought plasticity reveals intraspecific diversity in a dominant grass species

Abstract Intraspecific diversity of dominant species in native plant communities can modulate ecosystem function under both optimal and stressful conditions. Yet, few genotype by environment interaction studies quantify differences in the shape of plasticity functions or phenotypic breakpoints across genotypes in natural populations. Using three genotypes with a history of drought selection, we performed a greenhouse study on the dominant tallgrass prairie species Andropogon gerardii . We investigated phenotypic plasticity and recovery differences among genotypes across a water availability gradient, measuring growth‐related, instantaneous and cumulative phenotypes. To further understand genotype by environment effects, we quantified plasticity functions and breakpoints among genotypes. Like other studies, we found strong evidence for phenotypic and plasticity differences among genotypes. However, we also found nonlinear plasticity functions and breakpoints were common across phenotypes, especially relative growth rates, biomass allocation and root architecture. Drought selected genotypes were also more likely to flower during recovery, but all genotypes were resilient to drought across treatments. We demonstrate that plasticity functions may help explain intraspecific diversity, patterns of selection and nonlinear community responses to more variable rainfall within an experimental population. In particular, plasticity functions can help disentangle drought/variability tolerance versus acquisitive strategies. A better understanding of intraspecific diversity in this grass species will provide more mechanistic insight into its ability to buffer ecosystem changes and provide resiliency in the tallgrass prairie under future droughts. A free Plain Language Summary can be found within the Supporting Information of this article.

Hoffman, Ava M.↗
DOE OSTI2023

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗
DOE OSTI2022

Coupled diffusion-deformation-damage model for polymers used in hydrogen infrastructure

The soft materials used in the infrastructure of hydrogen storage and distribution systems are vulnerable because exposure to high-pressure hydrogen can lead to mechanical damage and property degradation. Some materials, such as polymers, can undergo mechanical failure due to a phenomenon wherein hydrogen gas diffuses through the polymer chains and occupies preexisting cavities or voids inside the polymer material. If the hydrogen gas pressure is reduced more quickly than hydrogen can diffuse back out of the polymer which is necessary for some applications, the trapped hydrogen gas instead escapes by rupturing the material, causing surface blistering or permanent damage. In this study, a continuum mechanics-based fully coupled diffusion-deformation model with damage is developed to predict the stress distribution and damage propagation while the polymer undergoes rapid decompression failure. The hyperelastic material model, along with the maximum principal strain failure theory, was chosen for this study as it represents the nonlinear material response with brittle failure observed in uniaxial tensile tests perfectly. EPDM polymer was chosen for this study because of its commercial availability and common use in hydrogen storage and distribution system. It has superior mechanical properties, high and low temperature resistance, and certain compounds work well in hydrogen gas. This work is useful for design engineers to alter the parameters while manufacturing polymer composites to increase their performance in a high-pressure hydrogen environment.

Kulkarni, Shank S.↗
DOE OSTI2024

Revealing a distortive polar order buried in the Fermi sea

Polar metals are challenging to identify spectroscopically because the fingerprints of electric polarization are often obscured by the presence of screening charges. Here, we unravel unambiguous signatures of a distortive polar order buried in the Fermi sea by probing the nonlinear optical response of materials driven by tailored terahertz fields. We apply this strategy to investigate the topological crystalline insulator Pb 1–x Sn x Te, tracking its soft phonon mode in the time domain and observing the occurrence of inversion symmetry breaking as a function of temperature. By combining measurements across the material’s phase diagram with ab initio calculations, we demonstrate the generality of our approach. These results highlight the potential of terahertz driving fields to reveal polar orders coexisting with itinerant electrons, thus opening additional avenues for material discovery.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet

We consider the scientifically challenging and policy-relevant task of understanding the past and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has shown a highly nonlinear threshold response to past climate forcings. Triggering such a threshold response through anthropogenic greenhouse gas emissions would drive drastic and potentially fast sea level rise with important implications for coastal flood risks. Previous studies have combined information from ice sheet models and observations to calibrate model parameters. These studies have broken important new ground but have either adopted simple ice sheet models or have limited the number of parameters to allow for the use of more complex models. These limitations are largely due to the computational challenges posed by calibration as models become more computationally intensive or when the number of parameters increases. Here, we propose a method to alleviate this problem: a fast sequential Monte Carlo method that takes advantage of the massive parallelization afforded by modern high-performance computing systems. We use simulated examples to demonstrate how our sample-based approach provides accurate approximations to the posterior distributions of the calibrated parameters. The drastic reduction in computational times enables us to provide new insights into important scientific questions, for example, the impact of Pliocene era data and prior parameter information on sea level projections. These studies would be computationally prohibitive with other computational approaches for calibration such as Markov chain Monte Carlo or emulation-based methods. We also find considerable differences in the distributions of sea level projections when we account for a larger number of uncertain parameters. For example, based on the same ice sheet model and data set, the 99th percentile of the Antarctic ice sheet contribution to sea level rise in 2300 increases from 6.5 m to 13.1 m when we increase the number of calibrated parameters from three to 11. With previous calibration methods, it would be challenging to go beyond five parameters. Here, this work provides an important next step toward improving the uncertainty quantification of complex, computationally intensive and decision-relevant models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of K-factor on Short Circuit Program Convergence for Inverter-Based Resources during Faults

Classical short-circuit programs that linearize the power network are no longer applicable for inverter based resources (IBRs), necessitating an iterative approach. Phasor domain programs can model the IBRs using an iterative approach considering nonlinear fault responses. In phasor domain models, the IBR can be modeled as a voltage controlled current source (VCCS) in tabular form with positive, negative, and zero sequence information for balanced and unbalance short-circuit faults. In the VCCS modeling of the IBR, positive and negative incremental reactive current, also known as the k-factor, plays an important role in short circuit program convergence. In this work, a few approaches: conventional VCCS modeling with a k-factor of 2, conventional VCCS modeling with a k-factor of 2 with modified pre-fault voltages, VCCS characteristics based on the power flow solution with a k-factor of 2, and VCCS characteristics based on the power flow solution with a k-factor of 1 are investigated for short circuit program convergence under higher IBR penetration. The IEEE 39 bus New England Test System is taken as the test system, and simulations are carried out in PSS®CAPE 15.0.26 simulation software. Simulation results demonstrate that IBR penetration is higher for the VCCS model, which corresponds to the power flow solution with k-factor 1, compared to other approaches.

42 ENGINEERING↗