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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deep neural operators can predict the real-time response of floating offshore structures under irregular waves

The use of neural operators in a digital twin model of an offshore floating structure holds the potential for a significant shift in the prediction of structural responses and health monitoring, offering valuable real-time control insights. In this work, we investigate the effectiveness of three neural operators, namely the deep operator network (DeepONet), the Fourier neural operator (FNO), and the Wavelet neural operator (WNO), to accurately capture the responses of a floating structure under six different sea state codes (3 − 8) based on the wave characteristics described by the World Meteorological Organization (WMO). To further enhance the accuracy of the vanilla architecture of the neural operators, novel extensions, such as wavelet-DeepONet and self-adaptive WNO, are proposed in this paper. The results demonstrate that these high-precision neural operators can deliver structural responses more efficiently, up to two orders of magnitude faster than a dynamic analysis using conventional numerical solvers. Additionally, compared to gated recurrent units (GRUs), a commonly used recurrent neural network for time-series estimation, neural operators are both more accurate and efficient, especially in situations with limited data availability. Taken together, our study shows that FNO outperforms all other operators for approximating the mapping of one input functional space to the output space as well as for responses that have small bandwidth of the frequency spectrum. Conversely, DeepONet, with historical states, proves most accurate in learning the mapping of multiple input functions to the output space and capturing responses within a broad frequency spectrum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effective sensor location for detection of change in structural dynamic response

This paper investigates the sensitivity of structural system response to the sensor location by investigating consequences of small changes in the location to the structural system response. The paper discusses how maximum observability (based on mode shape and the participation of that mode in the input provided) drives optimal location. The structural responses were investigated in terms of the g-rms response for various low-frequency inputs (pure sinusoids and real-life inputs such as an earthquake and trains). Results were then analyzed in the context of Modal Contributions Factors (MCF) and changes to the Force-to-response Transfer Functions (TRFs). A modal-matching process is first presented using a Matlab TM -based Finite Element Method (FEM) model of a cantilever beam and instrumentation to determine the location of a small mass based on three different criteria. Subsequently, the structural response is investigated using experiments and the FEM model. The accelerometer of small mass (at 1/3 height) was moved up or down to obtain changes in the structural response (TRF) to various realistic low-frequency inputs. Modal Contribution Factor (MCF) and derivative (slope) of the associated mode-shapes were correlated to the observed changes in TRFs. Results show how optimal sensor locations for detecting change in structural response can be based on the MCFs and the associated mode-shapes.

Woodall, J.↗
DOE OSTI2025

Neural operators for stochastic modeling of nonlinear structural system response to natural hazards

Traditionally, neural networks have been employed to learn the mapping between finite-dimensional Euclidean spaces. However, recent research has opened up new horizons, focusing on the utilization of deep neural networks to learn operators capable of mapping infinite-dimensional function spaces. Here, in this work, we employ two state-of-the-art neural operators, the deep operator network (DeepONet) and the Fourier neural operator (FNO) for the prediction of the nonlinear time history response of structural systems exposed to natural hazards, such as earthquakes and windstorms. Specifically, we propose two architectures, a self-adaptive FNO and a fast Fourier transform-based DeepONet (DeepFNOnet), where we employ a FNO beyond the DeepONet to learn the discrepancy between the ground truth and the solution predicted by the DeepONet. To demonstrate the efficiency and applicability of the architectures, two problems are considered. In the first, we use the proposed model to predict the seismic nonlinear dynamic response of a six-story shear building subject to stochastic ground motions. In the second problem, we employ the operators to predict the wind-induced nonlinear dynamic response of a high-rise building while explicitly accounting for the stochastic nature of the wind excitation. In both cases, the trained metamodels achieve high accuracy while being orders of magnitude faster than their corresponding high-fidelity models.

DeepONet↗
DOE OSTI2020

FAST.Farm Development and Validation of Structural Load Prediction Against Large Eddy Simulations

FAST.Farm is a mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on several principles of the dynamic wake meandering (DWM) model, but also addresses limitations of previous DWM implementations. Previous FAST.Farm studies have shown the similarities and differences between FAST.Farm and large eddy simulations for rigid turbine cases. The objective of this work is to quantify the ability of FAST.Farm to accurately predict turbine structural response in a small wind farm. This is done by comparing FAST.Farm structural response to SOWFA-OpenFAST results for three laterally-aligned turbines. The purpose of this study is to characterize the similarities and differences between FAST.Farm and a higher fidelity model for predicting turbine structural response in a wind farm for differing atmospheric inflows. Strong statistical agreement was found between FAST.Farm and SOWFA-OpenFAST structural response for the non-waked upstream turbine, and good agreement was found for the downstream turbines for most structural quantities. Higher differences were seen for downstream turbines with low ambient turbulence intensity or yawed turbines, suggesting areas for FAST.Farm wake dynamics modeling improvements. For all cases and turbines, small statistical differences were seen between blade deflections and bending moments, with larger differences for tower-top and tower-base bending moments. Overall, the results establish confidence for applying FAST.Farm to wind farm power and loads analyses and identify areas where further model validations and model improvements should be targeted.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2022

Operando X-ray Reflectivity Reveals the Dynamical Response of Ti 3 C 2 MXene Film Structure during Electrochemical Cycling

The dynamical structural response of MXenes during electrochemical ion intercalation is critical for their functionality in fast chemical actuation and high-power electrical energy storage but has yet to be observed. Here, the dynamically evolving layer spacing of a Ti 3 C 2 T $x$ MXene film was observed using time-resolved operando X-ray reflectivity during cyclic voltammetry for applied potentials between +0.3 and -0.7 V (vs Ag/AgCl) at sweep rates 1 ≤ $v$ ≤ 500 mV/s. The pseudocapacitive electrochemical MXene response in the aqueous 0.1 M Li 2 SO 4 electrolyte, including both capacitive and redox characteristics, is characterized by kinetically limited lithium intercalation and layer contraction. In conclusion, two types of dynamical responses were observed: slow and fast lattice contraction regimes versus applied potential are correlated with the capacitive and redox features, respectively, with structural relaxation rates that scale as ~$v$ 1/2 and ~$v$, revealing two distinct dynamical structural responses during electrochemical ion intercalation.

25 ENERGY STORAGE↗
DOE OSTI2021

A moving morphable component‐based topology optimization approach considering transient structural dynamic responses

Abstract A novel approach is developed under the moving morphable component (MMC) framework to solve topology optimization problems considering transient structural dynamic responses, where the structure for optimization is constructed with a collection of structural components, and the structural layout can be described explicitly via only a small number of design variables characterizing the positions and geometries of the components. The transient dynamic response of the structure and corresponding sensitivities are computed via step‐by‐step numerical integration and mode reduction technique is also employed to enhance the computational efficiency. Compared with existing works, the numerical instabilities induced by localized vibration modes can be substantially alleviated and the computational effort for direct sensitivity analysis is significantly reduced in the proposed approach. Two and three‐dimensional numerical examples considering the cases of nonproportional damping mechanism and time‐varying mass are also provided to manifest the validity of the proposed approach.

Li, Jialin↗
DOE OSTI2024

Prediction of photodynamics of 200 nm excited cyclobutanone with linear response electronic structure and ab initio multiple spawning

Simulations of photochemical reaction dynamics have been a challenge to the theoretical chemistry community for some time. In an effort to determine the predictive character of current approaches, we predict the results of an upcoming ultrafast diffraction experiment on the photodynamics of cyclobutanone after excitation to the lowest lying Rydberg state (S 2 ). A picosecond of nonadiabatic dynamics is described with ab initio multiple spawning. Herein we use both time dependent density functional theory (TDDFT) and equation-of-motion coupled cluster singles and doubles (EOM-CCSD) theory for the underlying electronic structure theory. We find that the lifetime of the S 2 state is more than a picosecond (with both TDDFT and EOM-CCSD). The predicted ultrafast electron diffraction spectrum exhibits numerous structural features, but weak time dependence over the course of the simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems

Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.

Algorithms↗
DOE OSTI2021

Structural damage response of lanthanum and yttrium aluminate crystals to nuclear collisions and electronic excitation: Threshold assessment of irradiation damage

A comparative analysis is performed on the structural damage response and associated mechanisms in lanthanum aluminate and yttrium aluminate crystals under various irradiation conditions by a combination of experimental and theoretical approaches. Under low-energy Au+ irradiation, the damage accumulation curve shows a higher damage rate for LaAlO 3 crystals than YAlO 3 crystals. The relatively low irradiation tolerance of LaAlO 3 to the action of nuclear collisions is ascribed to the large amorphization cross-section and effective cross-section for defect-stimulated amorphization. Under swift Ar 12+ , Ni 19+ and Kr 17+ irradiation with different ion energies and velocities, the formed highly-disordered/amorphous latent tracks with different morphologies in pristine and predamaged crystals are discussed, and the corresponding electronic energy loss and lattice temperature thresholds are quantitatively determined. Compared to YAlO 3 , LaAlO 3 exhibits lower sensitivity and higher damage tolerance to the electronic energy loss process, attributing to its relatively high recrystallization efficiency during the rapid quenching process. Furthermore, the introduction of lattice defects into LaAlO 3 and YAlO 3 crystals considerably enhances the sensitivity and intensity of thermal spike response to the electronic energy loss, and the induced effective modification of track morphologies demonstrates the synergistic effect between the electronic energy loss and pre-existing defects created by nuclear collisions. In this case, even under the action of electronic energy loss below the threshold, the lattice temperature in the nuclear-collision damaged crystalline system could still meet the criterion for track production. The irradiation energy deposited to atoms and induced lattice temperature evolution discussed in this work provide a deeper insight into the complex processes involved in irradiation-induced latent track behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗
DOE OSTI2025

Feasibility of an Accelerometer-Based Structural Health Monitoring System for the LANL Blast Tube

A modeling- and simulation-based study was conducted on the feasibility of implementing an accelerometer-based SHM system on the Los Alamos National Laboratory blast tube. A blast tube experiment was modeled using the Abaqus explicit finite element solver. A custom user subroutine was written to apply test-like pressure loading to the inside surface of the blast tube. The subroutine applies analytically defined pressure loads derived from tracer output taken from a Compressible Flow Computational Fluid Dynamics Solver model of the blast tube. Five unique versions of the model were created: an undamaged reference model at 65°F was used as the baseline and compared to equivalent models at 10°F and 100°F. These three models were compared to models with small damage at the reference temperature. The two types of damage considered were a radial (circumferential) crack in the main tube body and a longitudinal crack in the supports. Acceleration outputs were extracted from accelerometer bodies included in the model and were post processed using a variety of standard SHM techniques. Different potential features signaling failure were extracted and compared using statistical methods in the time and frequency domains. A method was identified that clearly shows that differences in structural response resulting from the modeled damage can be differentiated from the structural response resulting from changing environmental conditions. However, the amount of damage applied to create observable differences in the accelerometer data was so large that simpler methods of damage detection would be more cost effective in locating damage.

42 ENGINEERING↗
DOE OSTI2023

Molecular-Dynamics Analysis of the Mechanical Behavior of Plasma-Facing Tungsten

We report a systematic computational analysis of the mechanical behavior of plasma-facing component (PFC) tungsten focusing on the impact of void and helium (He) bubble defects on the mechanical response beyond the elastic regime. Specifically, we explore the effects of porosity and He atomic fraction on the mechanical properties and structural response of PFC tungsten, at varying temperature and bubble size. We find that the Young modulus of defective tungsten undergoes substantial softening that follows an exponential scaling relation as a function of matrix porosity and He atomic content. Beyond the elastic regime, our high strain rate simulations reveal that the presence of nanoscale spherical defects (empty voids and He bubbles) reduces the yield strength of tungsten in a monotonically decreasing fashion, obeying an exponential scaling relation as a function of tungsten matrix porosity and He concentration. Our detailed analysis of the structural response of PFC tungsten near the yield point reveals that yielding is initiated by emission of dislocation loops from bubble/matrix interfaces, mainly 1/2<111> shear loops, followed by gliding and growth of these loops and reactions to form <100> dislocations. Furthermore, dislocation gliding on the <111>{211} twin systems nucleates 1/6<111> twin regions in the tungsten matrix. These dynamical processes reduce the stress in the matrix substantially. Subsequent dislocation interactions and depletion of the twin phases via nucleation and propagation of detwinning partials lead the tungsten matrix to a next deformation stage characterized by stress increase during applied straining. Furthermore, our structural analysis reveals that the depletion of twin boundaries (areal defects) is strongly impacted by the density of He bubbles at higher porosities. After the initial stress relief upon yielding, increase in the dislocation density in conjunction with decrease in the areal defect density facilitates the initiation of dislocation-driven deformation mechanisms in the PFC crystal.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hypersonic Fluid–Structure Interaction on a Cone–Slice–Ramp Geometry

In this study, fluid–structure interactions were measured between a representative control surface and the hypersonic flow deflected by it. The control surface is simplified as a spanwise finite ramp placed on a longitudinal slice of a cone. The front surface of the ramp contains a thin panel designed to respond to the unsteady fluid loading arising from the shock-wave/boundary-layer interactions. Experiments were conducted at Mach 5 and Mach 8 with ramps of different angles. High-speed schlieren captured the unsteady flow dynamics and accelerometers behind the thin panel measured its structural response. Panel vibrations were dominated by natural modes that were excited by the broadband aerodynamic fluctuations arising in the flowfield. However, increased structural response was observed in two distinct flow regimes: 1) attached or small separation interactions, where the transitional regime induced the strongest panel fluctuations. This was in agreement with the observation of increased convective undulations or bulges in the separation shock generated by the passage of turbulent spots, and 2) large separated interactions, where shear layer flapping in the laminar regime produced strong panel response at the flapping frequency. In addition, panel heating during the experiment caused a downward shift in its natural mode frequencies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Optically Induced Picosecond Lattice Compression in the Dielectric Component of a Strongly Coupled Ferroelectric/Dielectric Superlattice

Above-bandgap femtosecond optical excitation of a ferroelectric/dielectric BaTiO 3 /CaTiO 3 superlattice leads to structural responses that are a consequence of the screening of the strong electrostatic coupling between the component layers. Time-resolved X-ray free-electron laser diffraction shows that the structural response to optical excitation includes a net lattice expansion of the superlattice consistent with depolarization-field screening driven by the photoexcited charge carriers. The depolarization-field-screening-driven expansion is separate from a photoacoustic pulse launched from the bottom electrode on which the superlattice is epitaxially grown. The distribution of diffracted intensity of superlattice X-ray reflections indicates that the depolarization-field-screening-induced strain includes a photoinduced expansion in the ferroelectric BaTiO 3 and a contraction in CaTiO 3 . The magnitude of expansion in BaTiO 3 layers is larger than the contraction in CaTiO 3 . The difference in the magnitude of depolarization-field-screening-driven strain in the BaTiO 3 and CaTiO 3 components can arise from the contribution of the oxygen octahedral rotation patterns at the BaTiO 3 /CaTiO 3 interfaces to the polarization of CaTiO 3 . The depolarization-field-screening-driven polarization reduction in the CaTiO 3 layers points to a new direction for the manipulation of polarization in the component layers of a strongly coupled ferroelectric/dielectric superlattice.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nickel-rich Nickel Manganese Cobalt (NMC622) Cathode Lithiation Mechanism and Extended Cycling Effects Using Operando X-ray Absorption Spectroscopy

Ni-rich NMC materials are a particularly promising class of Li-ion cathodes for various applications. LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) offers a unique balance of thermal stability and energy density, thus attracting attention for electric vehicle implementation. However, upon extended cycling, capacity fade is prevalent due to structural degradation, which is a major drawback for layered oxide cathodes. Therefore, exploring the underlying phenomena that drive detrimental structural response can lead to future improvements. For the first time, operando X-ray absorption spectroscopy (XAS) was performed on NMC622 pouch cells at three different stages. An extensive description of the first cycle (de)lithiation mechanisms was achieved through X-ray absorption near-edge structure analyses and extended X-ray absorption fine structure modeling. Transition metal specific electrochemical participation and structural variation revealed that much of the delivered capacity and distortion is a result of Ni redox behavior, while the local structure of Co and Mn are impacted due to their interdependencies. Key mechanistic components were identified, as the local structural variation from redox processes and Ni 3+ Jahn–Teller distortion were decoupled. Further, operando XAS was used to investigate the structural response of NMC622 to extended cycling and was supported by X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy analyses. In this work, reduced capacity was found in the cell after 100 cycles and is attributed to structural degradation and cathode–electrolyte interphase buildup from repeated Li (de)insertion processes, which limit the electrochemical reversibility of Ni and Co through increased polarization. These results expand the understanding of a Ni-rich NMC material under extended cycling, which is vital to the future design of electrode materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Interfacial Response and Structural Adaptation of Structured Polyelectrolyte Thin Films

Ionizable block copolymers with distinctive block characteristics display the diversity crucial for the design of macromolecules for targeted applications. In contrast to van der Waals copolymers, their interfaces, which are critical to their function, consist of nanodomains, each of a different nature and thus unique interfacial behavior. Here, the interfacial response of a symmetric block copolymer with a sulfonated polystyrene polyelectrolyte center, tethered to polyethylene-r-propylene and terminated by poly(t-butyl styrene) is probed as polymer films are exposed to three polar solvents, water, propanol, and tetrahydrofuran (THF), using molecular dynamics simulations. Each of the solvents captures a distinctive interaction with the individual blocks. We find that at the film boundary, the interfacial response is initially dominated by that of the hydrophobic blocks to all solvents. At later times, the solvent distribution among the blocks, where water molecules associate predominantly with the sulfonated groups and propanol and THF reside at multiple different sites, determines the chemical composition and the polymer conformation at the interface. Altogether, these simulations provide the first direct molecular insight into the interfacial response of ionizable copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗