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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Hamilton-Jacobi formalism for inflation with non-minimal derivative coupling

In inflation with nonminimal derivative coupling there is not a conformal transformation to the Einstein frame where calculations are straightforward, and thus in order to extract inflationary observables one needs to perform a detailed and lengthy perturbation investigation. In this work we bypass this problem by performing a Hamilton-Jacobi analysis, namely rewriting the cosmological equations considering the scalar field to be the time variable. We apply the method to two specific models, namely the power-law and the exponential cases, and for each model we calculate various observables such as the tensor-to-scalar ratio, and the spectral index and its running. We compare them with 2013 and 2015 Planck data, and we show that they are in a very good agreement with observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Overcoming the Technical Challenges of Coordinating Distributed Load Resources at Scale (Final Report)

Significant recent research has investigated the potential for loads to provide balancing services to the grid. However, this research has not addressed key issues that may arise when such schemes are applied at scale including: 1. Distribution Network Issues. Coordination of large numbers of loads could result in power flows that violate distribution network constraints; 2. Stability Issues. Certain strategies to control loads can exhibit nonlinearity in the form of period-adding bifurcations and chaos. Other control strategies can potentially synchronize the behavior of large numbers of loads. In both cases, the outcome can be power oscillations and instability; 3. Communication Network Issues. Bidirectional low-latency communication channels between a central controller (or several distributed controllers) and each resource are expensive and likely not necessary for effective coordination. Our research questions were: What network, stability, and communication issues might arise in practice when we coordinate large aggregations of loads? How can we coordinate loads to achieve performance objectives in a cost effective manner while avoiding these issues? The ultimate technical goal of the project was the development of network-aware, communication-constrained, non-disruptive load control strategies with stability guarantees that achieve the performance requirements of typical balancing services at a sufficiently low cost to enable the load aggregator and customer to profit. The overall goal was to establish credibility for load control at scale and contribute to U.S. energy security and environmental goals. The team succeeded in answering these research questions and developing these control strategies. The overall approach was based on the development of three testing environments: a simulation testbed, an experimental testbed (20 physical model houses with window-box air conditioners) coupled with the simulation testbed, and a field testbed (100 actual homes in Austin, TX) coupled with the simulation testbed, which enabled controller testing, identification of issues, controller development, and controller validation. The resulting controller was used to demonstrate fast timescale grid balancing (frequency regulation) by aggregations of physical and virtual air conditioners, with sufficient quality to participate in the electricity market. Cost benefit analysis showed overall benefits to the participating households, load aggregators, and the grid, especially if the control technology was integrated directly into existing programmable communicating thermostats. The project provides a variety of wider benefits. Our technology transfer and outreach activities lead us to choose an open-source licensing commercialization pathway, enabling the project results to be available to researchers, industry, and the public. Furthermore, new grid balancing technologies will increase grid flexibility and will enable higher penetrations of intermittent renewable energy resources, such as wind and solar, to be connected to the grid, reducing its environmental impact, and mitigating climate change to the benefit of society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Electrochemically induced fracture in LLZO: How the interplay between flaw density and electrostatic potential affects operability

Fracture and short circuit in the Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte are two key issues that prevent its adoption in battery cells. In this paper, we utilize phase-field simulations that couple electrochemistry and fracture to evaluate the maximum electric potential that LLZO electrolytes can support as a function of crack density. In the case of a single crack, we find that the applied potential at the onset of crack propagation exhibits inverse square root scaling with respect to crack length, analogous to classical fracture mechanics. Here, we further find that the short-circuit potential scales linearly with crack length. In the realistic case where the solid electrolyte contains multiple cracks, we reveal that failure fits the Weibull model. The failure distributions shift to favor failure at lower overpotentials as areal crack density increases. Furthermore, when flawless interfacial buffers are placed between the applied potential and the bulk of the electrolyte, failure is mitigated. When constant currents are applied, current focuses in near-surface flaws, leading to crack propagation and short circuit. We find that buffered samples sustain larger currents without reaching unstable overpotentials and without failing. Our findings suggest several mitigation strategies for improving the ability of LLZO to support larger currents and improve operability.

25 ENERGY STORAGE↗
DOE OSTI2014

Microscopic model for exchange bias from grain-boundary disorder in a ferromagnet/antiferromagnet thin film with a nanocrystalline microstructure

Monte Carlo spin simulations were coupled to a Voronoi microstructure-generator to predict the magnitude and behavior of exchange bias in a ferromagnet/antiferromagnet (AF) thin film bilayer with a nanocrystalline microstructure. Our model accounts for the effects of irregular grain-shapes, finite-sized particles, and the possible presence of local random-fields originating from the antiferromagnet's grain-boundary regions. As the grain-boundary represents a crystal-structure distortion, we model the local effect on the exchange constants in the Gaussian approximation which can cause regions resembling a spin glass confined to an unusual 2D topology. Although an ensemble of completely disconnected AF grains isolated by non-magnetic barriers provides a small exchange bias, the introduction of a spin-glass network at the boundaries causes a four-fold enhancement in the magnitude of the loop-shift. This implies the importance of local grain-boundary behavior in defect-engineered antiferromagnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Temperature dependence of exciton-surface plasmon polariton coupling in Ag, Au, and Al films on In{sub x}Ga{sub 1−x}N/GaN quantum wells studied with time-resolved cathodoluminescence

The optical properties and coupling of excitons to surface plasmon polaritons (SPPs) in Ag, Au, and Al-coated In{sub x}Ga{sub 1−x}N/GaN multiple and single quantum wells (SQWs) were probed with time-resolved cathodoluminescence. Excitons were generated in the metal coated SQWs by injecting a pulsed high-energy electron beam through the thin metal films. The Purcell enhancement factor (F{sub p}) was obtained by direct measurement of changes in the temperature-dependent radiative lifetime caused by the SQW exciton-SPP coupling. Three chosen plasmonic metals of Al, Ag, and Au facilitate an interesting comparison of the exciton-SPP coupling for energy ranges in which the SP energy is greater than, approximately equal to, and less than the excitonic transition energy for the InGaN/GaN QW emitter. A modeling of the temperature dependence of the Purcell enhancement factor, F{sub p}, included the effects of ohmic losses of the metals and changes in the dielectric properties due to the temperature dependence of (i) the intraband behavior in the Drude model and (ii) the interband critical point transition energies which involve the d-bands of Au and Ag. We show that an inclusion of both intraband and interband effects is essential when calculating the ω vs k SPP dispersion relation, plasmon density of states (DOS), and the dependence of F{sub p} on frequency and temperature. Moreover, the “back bending” in the SPP dispersion relation when including ohmic losses can cause a finite DOS above ω{sub sp} and lead to a measurable F{sub p} in a limited energy range above ω{sub sp}, which can potentially be exploited in plasmonic devices utilizing Ag and Au.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Extreme confinement of hydrogen gas within fullerenelike nanoporous carbon

Nanoporous carbons and carbon nanostructures can store hydrogen at cryogenic temperatures but lack the volumetric and gravimetric capacity to be industrially significant. Recent inelastic neutron scattering experiments suggest a highly dense phase of hydrogen at temperatures well above the melting point of solid hydrogen. However, it remains unclear how pore geometry and intermolecular interactions enable these dense phases to exist, with dispersion (van der Waals) or electrostatic/induction suggested to be the key effects in slit and curved pores but their relative contributions have yet to be quantified. In this paper, we perform benchmark electronic structure calculations allowing the interactions between planar and curved aromatic molecules with hydrogen to be accurately determined. Dispersion was found to dominate over electrostatic and inductive effects with some many-body charge transfer (Dobson type-A) effects needed to capture the most highly curved structures. Density functional methods that include type-A many-body effects were found to accurately describe the intermolecular interactions at a fraction of the cost of coupled-cluster simulations and these approaches were used to calculate the energies inside large carbon bowl and slit pores. The interaction energies inside the bowl pores were found to depend on the orientation of the hydrogen molecule. This rotational barrier, modeled as a quantum hindered rotor, could reproduce the peak splitting observed in inelastic neutron scattering experiments, with weak splitting arising from bowl-like fullerene pores and strong splitting from highly confining nanotubelike pores. Increasing the fraction of such curved pores in nanoporous carbons may therefore offer a pathway to enhance their hydrogen-storage capacity. Moreover, the preferential adsorption of ortho hydrogen on nanotubelike pores could enable the storage of high-density hydrogen without the need to remove heat produced during the ortho-para hydrogen conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2017

AZTRAN and AZKIND verification with a BWR study case

The AZTLAN Platform project is a national initiative led by the National Institute of Nuclear Research which gather the main public institutions of higher education in Mexico: the National Polytechnic Institute, the National Autonomous University of Mexico and the Autonomous Metropolitan University. It consists in the development of a modeling platform for the analysis and design of nuclear reactors. This project aims to modernize, improve and integrate the neutronic, thermohydraulics and thermomechanical codes, developed in the national institutions, in a platform integrated and developed by Mexican experts. The development of AZTLAN Platform is divided technically into four working groups: neutronics, thermohydraulics, coupling and uncertainty analysis, and users group. The present work is the result of the activities of the Users Group focused on the follow-up, testing and use of the different codes (modules) being developed under the AZTLAN project; with the objective of providing feedback and to suggest development priorities to the team of developers, as well as to promote collaboration and synergy between the participating institutions. In particular, in this work, the AZTRAN and the AZKIND modules were verified and tested against the results of well-known codes of the nuclear industry for boiling water reactor (BWR) models. AZTRAN is a 3D transport code which solves numerically the multi-group time independent neutron transport equation in Cartesian geometry, based on the discrete ordinates (SN) method and the RTN-0 nodal scheme. AZKIND is a 3D diffusion code that solves numerically the time dependent neutron diffusion equations in Cartesian geometry, based on a Galerkin Finite Element Method using the RTN-0 polynomial nodal approximation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Climate Modeling and Causal Identification for Sea Ice Predictability

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments in which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.

"Sea ice" uncertainty↗
DOE OSTI2018

Electrons to Reactors Multiscale Modeling: Catalytic CO Oxidation over RuO 2

First-principles kinetic Monte Carlo (1p-kMC) simulations for CO oxidation on two RuO 2 facets, RuO 2 (110) and RuO 2 (111), were coupled to the computational fluid dynamics (CFD) simulations package MFIX, and reactor-scale simulations were then performed. 1p-kMC coupled with CFD has recently been shown as a feasible method for translating molecular scale mechanistic knowledge to the reactor scale, enabling comparisons to in situ and online experimental measurements. Only a few studies with such coupling have been published. This work incorporates multiple catalytic surface facets into the scale-coupled simulation, and three possibilities were investigated: the two possibilities of each facet individually being the dominant phase in the reactor, and also the possibility that both facets were present on the catalyst particles in the ratio predicted by an ab initio thermodynamics-based Wulff construction. When lateral interactions between adsorbates were included in the 1p-kMC simulations, the two surfaces, RuO 2 (110) and RuO 2 (111), were found to be of similar order-of-magnitude in activity for the pressure range of 1 × 10 –4 bar to 1 bar, with the RuO 2 (110) surface-termination showing more simulated activity than the RuO 2 (111) surface-termination. Coupling between the 1p-kMC and CFD was achieved with a lookup table generated by the error-based modified Shepard interpolation scheme. Isothermal reactor scale simulations were performed and compared to two separate experimental studies, conducted with reactant partial pressures of ≤0.1 bar. Simulations without an isothermality restriction were also conducted and showed that the simulated temperature gradient across the catalytic reactor bed is <0.5 K, which validated the use of the isothermality restriction for investigating the reactor-scale phenomenological temperature dependences. The approach with the Wulff construction based reactor simulations reproduced a trend similar to one experimental data set relatively well, with the (110) surface being more active at higher temperaures; in contrast, for the other experimental data set, our reactor simulations achieve surprisingly and perhaps fortuitously good agreement with the activity and phenomenological pressure dependence when it is assumed that the (111) facet is the only active facet present. Lastly, the active phase of catalytic CO oxidation over RuO 2 remains unsettled, but the present study presents proof of principle (and progress) toward more accurate multiscale modeling from electrons to reactors and new simulation results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerated coupled Monte Carlo-Thermal hydraulic calculations using a hybrid GTF-diffusion-based prediction block: first results

Accurate predictions of spatial power and temperature distributions require the coupling of a neutron transport solver with a thermal-hydraulic (TH) feedback. Nowadays, Monte Carlo (MC) codes are widely coupled to TH solvers, typically via a Picard iteration (PI) method, due to the higher fidelity that such frameworks can produce. To speed up a PI, a prediction step can produce an improved initial guess for a source distribution and feed it to the MC code. Recent work investigated a prediction step that uses generalized transfer functions (GTFs) to predict the macroscopic cross sections' variations following a perturbation in TH properties, such as coolant density. The previous method also relied on first order perturbation (FOP) theory to predict perturbed power profiles, rather than using an expensive MC iterate. The implemented FOP method relied on generating a fission matrix from which the forward and adjoint Eigenmodes were extracted and later used to for power calculations. The generation of the fission matrix can introduce a significant computational overhead, therefore undermining the performance of the proposed hybrid technique when applied to high-dimensional problems, e.g., full core calculations. This work attempts to improve the GTF-FOP prediction step by replacing the FOP solver with a nodal diffusion solver, thus eliminating the need to calculate a fission matrix. The GTF-diffusion step was tested for various moderator density perturbations. In each case, the predicted power distribution showed good agreement with the reference case. The latter is attributed to the generally good prediction of most spatially distributed macroscopic cross sections, except the transport cross section, which will become the focus of future work. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Simulation study of LEBT for transversely coupled beam from an ECR ion source

A Low-Energy intense-highly charged ion Accelerator Facility (LEAF) program has been launched at Institute of Modern Physics. This accelerator facility consists of a superconducting Electron Cyclotron Resonance (ECR) ion source, a Low Energy Beam Transport (LEBT) system, and a Radio Frequency Quadrupole (RFQ). It is especially of interest for the extracted ion beam from the ECR ion source, which is transversely coupled, and this property will significantly affect the beam transmission in the LEBT line and the matching with the downstream RFQ. In the beam transport design of LEAF, beam decoupling in the LEBT is considered to lower down the projection emittances and the feasibility of the design has been verified by beam simulation with a transversely coupled beam from the ECR ion source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Midlatitude atmospheric responses to Arctic sensible heat flux anomalies in Community Climate Model, Version 4: Atmospheric Response to Arctic SHFs

Possible linkages between Arctic sea ice loss and midlatitude weather are strongly debated in the literature. We analyze a coupled model simulation to assess the possibility of Arctic ice variability forcing a midlatitude response, ensuring consistency between atmosphere, ocean, and ice components. We work with weekly running mean daily sensible heat fluxes with the self-organizing map technique to identify Arctic sensible heat flux anomaly patterns and the associated atmospheric response, without the need of metrics to define the Arctic forcing or measure the midlatitude response. We find that low-level warm anomalies during autumn can build planetary wave patterns that propagate downstream into the midlatitudes, creating robust surface cold anomalies in the eastern United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The underestimated magnitude and decline trend in near-surface wind over China

This study reports the magnitude, spatial pattern and temporal trend of near-surface wind speed (NWS) by comparing 20th century simulations in Coupled Model Intercomparison Project phase 5 (CMIP5) and 3 (CMIP3) and the climate reanalyses with measurements at 563 weather stations in China over 1961–2005. Both CMIP5 and CMIP3 agree quite well with observations in reproducing the spatial pattern of annual mean NWS. CMIP5 models are superior to CMIP3 models in hindcasting the magnitude and spatial pattern of seasonal mean NWS, the temporal trend in annual and seasonal mean NWS. Although both CMIP3 and CMIP5 reproduced the decline trend in the annual and seasonal mean NWS, the hindcasted decline rate is smaller than observed decline trend by the magnitude of one order. The ensemble of optimal models that are better correlated to observations in both NWS and temporal trend possesses advantages over individual model hindcast and reanalyses. The reanalyzed data are not able to represent the observed either the spatial pattern or the decline trend of NWS. The analyses presented here reveal the uncertainties in the current wind field products including reanalyses and model outputs and highlight the benefits of parameterization development and increased horizontal resolution in the new-generation CMIP models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Prediction of Feasibility of Polaronic OER on (110) Surface of Rutile TiO 2

The polaronic effects at the atomic level hold paramount significance for advancing the efficacy of transition metal oxides in applications pertinent to renewable energy. The lattice–distortion mediated localization of photoexcited carriers in the form of polarons plays a pivotal role in the photocatalysis. This investigation focuses on rutile TiO 2 , an important material extensively explored for solar energy conversion in artificial photosynthesis, specifically targeting the generation of green H 2 through photoelectrochemical (PEC) H 2 O splitting. By employing Hubbard-U corrected and hybrid density functional theory (DFT) methods, we systematically probe the polaronic effects in the catalysis of oxygen evolution reaction (OER) on the (110) surface of rutile TiO 2 . Theoretical understanding of polarons within the surface, coupled with simulations of OER at distinct titanium (Ti) and oxygen (O) active sites, reveals diverse polaron formation energies within the lattice sites with strong preference for bulk and surface bridge (O b ) oxygen sites. Moreover, we provide the evidence for the facilitative role of polarons in OER. Here, we find that hole polarons situated at the equatorial oxygen sites near the Ti–active site, along with bridge site hole polarons distal from the O b active site yield a small reduction in OER overpotential by ~0.06 eV and ~0.12 eV, respectively. However, subsurface, equatorial, and bridge site hole polarons significantly reduce the Ti-active site OER overpotential by ~0.4 eV through the peroxo–type oxygen pathway. We also observe that the presence of hole polarons stabilizes the *OH, *O, and *OOH intermediate species compared to the scenario without hole polarons. Overall, this study provides a detailed mechanistic insight into polaron–mediated OER, offering a promising avenue for improving the catalytic activity of transition metal oxide-based photocatalysts catering to renewable energy requisites.

14 SOLAR ENERGY↗
DOE OSTI2022

CO 2 zonal injection rate allocation and plume extent evaluation through wellbore temperature analysis

Temperature analysis during a pause in injection operations, known as warmback analysis, has been used in the petroleum industry for evaluating the injection conformance and estimating the location of the flooded front in applications, such as waterflooding oil reservoirs. Here in this work, methods are introduced to extend the application of temperature warmback analysis to estimate the zonal CO 2 injection rate and zonal CO 2 plume extent during geologic CO 2 storage in a saline aquifer. First, novel analytical solutions are developed to model transient temperature in the aquifer during the injection and subsequent shut-in periods considering two-phase flow (gaseous CO 2 and aqueous brine) conditions in the aquifer. The solution involves a discretization of the aquifer into regions; the energy and mass conservation equations for the regions are solved simultaneously considering appropriate boundary conditions at the interfaces. Two solutions techniques are presented: multi-region and three-region solutions. Inverse models are developed accordingly to evaluate the injection profile and estimate the extent of the plume front in the reservoir during the injection period. The multi-region solution results in an inversion approach that requires regression analysis. However, the three-region formulation results in a simple graphical technique for inverse modeling. The analytical solutions are validated against a thermally coupled reservoir simulation tool using different synthetic cases for CO 2 injection in deep saline aquifers. The results of the developed solutions provide a good match with numerical results during forward and inverse modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Woven ceramic matrix composite surrogate model based on physics-informed recurrent neural network

A recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear constitutive behavior of woven ceramic matrix composites (CMCs) driven by matrix damage at multiple length scales. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the multiscale generalized method of cells (MSGMC) approach coupled with a matrix damage model. This coupling permits simulating the nonlinear behavior of woven CMCs based on constituent response at the micro-, meso-, and macroscales. The multiscale repeating unit cell is loaded under non-monotonic conditions including multiple load / unload cycles and tension / compression. The fiber volume fraction as well as the intra- and intertow void volume fractions are also varied in the generation of training data. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input strain sequence and fiber and void volume fractions, the resulting stress versus strain response while satisfying physical constraints such as positive semi-definiteness of the tangent stiffness matrix and linear elastic unloading. Further, the trained surrogate model effectively matches the stress versus strain response and successfully predicts the tangent modulus throughout the loading regime. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex architectures, nonlinear multiaxial material response, and under non-monotonic loading conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗