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Results for “conditional generative models”

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 307 records · Page 17

Investigation of high-speed shaft bearing loads in wind turbine gearboxes through dynamometer testing

Many wind turbine gearboxes require repair or replacement well before reaching the end of their design life. The most common failure is bearing axial cracks, commonly called white etching cracks (WECs), which typically occur in the inner raceways of the high-speed parallel-stage rolling element bearings. Although the root causes of WECs are debated, one theory is that they are related to routine dynamic operating conditions and occasional transient events prevalent in wind turbines that can result in high bearing stress and sliding of the rolling elements. Here, this paper examined wind turbine gearbox high-speed shaft bearing loads and stresses through modeling and full-scale dynamometer testing. Bearing outer race loads were directly measured and predicted using a variety of modeling tools in normal operations, misaligned conditions, and transient events particularly prone to bearing sliding. Test data and models of bearing loads were well correlated. Neither operational misalignment due to rotor moments nor static generator misalignment affected the bearing loads when compared with pure-torque conditions. Thus, it is not likely that generator misalignment is a causal factor of WECs. In contrast, during transient events, the bearings experienced alternating periods of high stress, torque reversals, and loads under the minimum requisite at high rotating speeds while showing indications of sliding, all of which could be related to the formation of WECs.

17 WIND ENERGY↗

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↗

One‐Pot Synthesis of Xanthone by Carbonylative Suzuki Coupling Reaction

Abstract Xanthone derivatives have a dibenzo‐y‐pyrone scaffold which has gained great interest in Medicinal Chemistry due to their diverse biological activities. Usually, its synthesis requires multi‐step synthetic routes using harsh conditions and high catalyst loadings. In this communication, we report for the first time a one‐pot synthesis of the xanthone scaffold based on a carbonylative Suzuki coupling. Iodophenol and (2‐methoxyphenyl)boronic acid were coupled under carbon monoxide, generated from a carbon monoxide surrogate. An experimental data‐based model was built to guide the reaction optimization. The optimized conditions were 1 mol% of a pincer complex as palladium catalyst, 5 equivalents of K 2 CO 3 as base, and DMF:water (7 : 3) as solvent. The robustness of the synthetic method, namely in terms of the reactants scope, was also evaluated. This approach provided the xanthone scaffold in high yields and provided a deep insight into the carbonylative Suzuki couplings.

Loureiro, Daniela R. P.↗

Demonstrating non-isothermal vacuum membrane air dehumidification for efficient next-generation air conditioning

Vacuum membrane air dehumidification has gained significant interest in recent years as a highly efficient means of air dehumidification. Prior theoretical modeling work by the authors introduced the Active Membrane Energy Exchanger (AMX) concept, which combines active heat exchange and vacuum membrane dehumidification into one non-isothermal system, and found that it could outperform other air conditioning technologies under many conditions. However, no experimental literature exists on combining active heat exchangers and vacuum membrane dehumidification. Here, the goal of the present study is to evaluate the dehumidification (mass transfer) performance of the AMX concept relative to isothermal membrane dehumidification through three main methodologies: (1) membrane material-level characterization, (2) experimental prototype development and testing, and (3) computational fluid dynamics (CFD) simulations. The dense membranes used in this work showed up to a 40% increase in water vapor permeance at cooler temperatures, and the prototype system showed up to a 6% increase in humidity removal when the air was simultaneously cooled. Furthermore, the membrane module-integrated heat exchange tubes provided additional mixing and turbulence, leading to a 4–8% increase in humidity removal. The upper limit coefficient of performance was equal to approximately 2.2, necessitating advanced system designs to improve efficiency. This study is the first to highlight that combining the cooling and vacuum dehumidification processes can improve dehumidification performance.

30 DIRECT ENERGY CONVERSION↗

Generation and Validation of the iKp1289 Metabolic Model for Klebsiella pneumoniae KPPR1

Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibiotic-resistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. pneumoniae and of 99% in predicting nonessential genes in rich media. We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

bacteria↗

High scale flavor alignment in two-Higgs doublet models and its phenomenology

The most general two-Higgs doublet model (2HDM) includes potentially large sources of flavor changing neutral currents (FCNCs) that must be suppressed in order to achieve a phenomenologically viable model. The flavor alignment ansatz postulates that all Yukawa coupling matrices are diagonal when expressed in the basis of mass-eigenstate fermion fields, in which case tree-level Higgs-mediated FCNCs are eliminated. In this work, we explore models with the flavor alignment condition imposed at a very high energy scale, which results in the generation of Higgs-mediated FCNCs via renormalization group running from the high energy scale to the electroweak scale. Using the current experimental bounds on flavor changing observables, constraints are derived on the aligned 2HDM parameter space. In the favored parameter region, we analyze the implications for Higgs boson phenomenology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Predicting failure parameters of semiconductor devices subjected to stress conditions

A method for predicting failure parameters of semiconductor devices can include receiving a set of data that includes (i) characteristics of a sample semiconductor device, and (ii) parameters characterizing a stress condition. The method further includes extracting a plurality of feature values from the set of data and inputting the plurality of feature values into a trained model executing on the one or more processors, wherein the trained model is configured according to an artificial intelligence (AI) algorithm based on a previous plurality of feature values, and wherein the trained model is operable to output a failure prediction based on the plurality of feature values. Further, the method includes generating, via the trained model, a predicted failure parameter of the sample semiconductor device due to the stress condition.

Ahmed, Moinuddin↗

Deep-learning-enhanced assessment of wellbore barrier effectiveness in geologic storage systems with intermediate aquifers

For geologic systems where carbon dioxide (CO 2 ) is injected underground, existing wells represent potential pathways for fluid migration. Here, this study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO 2 leakage rates and CO 2 saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO 2 would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.

CO2 leakage↗

TEM characterization of two variants of fuel cladding chemical interaction in a HT-9 Clad U-10Zr Fuel. Variant 1: FCCI with a Zr Rind

Here, this study investigated the fuel cladding chemical interaction (FCCI), a key factor that limits operational temperature and burnup, in an HT-9 clad U-10Zr nuclear fuel sample irradiated to a high burnup of 13.1 at.% at a time-averaged peak inner cladding temperature (PICT) of 530 °C. Previous results showed this fuel sample exhibited two distinct levels of FCCI at d. This paper analyzed the FCCI at an azimuthal position showing an interdiffusion layer of <10 µm using transmission electron microscopy to examine chemical and crystallographic nature of phases at the fuel-cladding interface at the nanoscale level. A ZrC layer and a Zr 3 Si phase were identified at the interface; these, along with the relatively low local temperature, potentially contributed to limit interdiffusion, behaving as inhibitors for deleterious interactions. Lanthanides (Ln) partially consumed the ZrC layer and interacted with Fe, forming a Zr-Ln compound and a (Zr,Ce)Fe 2+x phase while also infiltrating up to 4 µm into the cladding. Neither U nor Zr were observed in the cladding, whereas Fe diffused up to 3–5 µm in the fuel. Fe infiltration formed a ternary U-Zr-Fe ε-phase and likely promoted the precipitation of a Cr-rich α’ phase on the cladding interface. Additionally, a Cr-rich χ-phase, likely formed by the dissociation of pre-existing M 23 C 6 carbide precipitates, was identified about 2–5 µm from the fuel-cladding interface. Irradiation-induced nano-voids were also observed in the HT-9 bulk. These findings provide critical insights into FCCI mechanisms at representative irradiation conditions, essential for developing models simulating in-pile metallic fuel behaviors for next-generation reactors.

36 - MATERIALS SCIENCE↗

Jet cone radius dependence of R AA and v 2 at PbPb 5.02 TeV from JEWEL+T R ENTo+v-USPhydro

We combine, for the first time, event-by-event T R ENTo initial conditions with the relativistic viscous hydrodynamic model v-USPhydro and the Monte Carlo event generator JEWEL to make predictions for the nuclear modification factor R AA and jet azimuthal anisotropies v n { 2 } in $\sqrt{s_{NN}}$ = 5.02 TeV PbPb collisions for multiple centralities and values of the jet cone radius R. The R-dependence of R AA and v 2 { 2 } strongly depends on the presence of recoiling scattering centers. We find a small jet v 3 { 2 } in mid-central collisions and consistent results in wide jet p T regions and centralities with ATLAS data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Elasto-viscoplastic fast Fourier transform modeling framework for assessing microstructural effects on stress intensity factors characterizing fracture toughness

A large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) model with non-periodic (NP) velocity-based boundary conditions is adapted to simulate the sensitivity of stress intensity factors on microstructure for 304L stainless steel. The material was characterized via electron backscattered diffraction (EBSD) serial-sectioning to obtain a measured 3-D microstructural cell to perform simulations. The NP-LS-EVPFFT model, including the simulation setup and boundary conditions, was verified using a crystal plasticity finite element (CPFE) model. To this end, the generation of meshes of notched specimens was developed, which involved creating Python scripts for mesh “cutting” in Abaqus, and Sculpt scripts in Cubit for meshing of the measured microstructural cell processed with DREAM.3D. The complexity of the mesh preparation highlighted the advantages of the FFT-based model, which circumvents the mesh generation process. Given the efficiency of the FFT-based model, statistical distribution of stress intensity factors in function of crystal orientation at the crack tip, grain structure, and crystallographic texture surrounding the crack tip were predicted. Further, the distributions reveal about 10% variation of stress intensity factors with microstructure with the most significant sensitivity found to be the crystal orientation at the crack tip. The methodology developed in this work is discussed as a practical simulation tool for predicting the sensitivity of stress intensity factors on microstructural variability in metallic materials.

36 MATERIALS SCIENCE↗

Higher-order correlations between different moments of two flow amplitudes in Pb-Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV

The correlations between different moments of two flow amplitudes, extracted with the recently developed asymmetric cumulants, are measured in Pb-Pb collisions at $\sqrt {s_{NN}}$ = 5.02 TeV recorded by the ALICE detector at the CERN Large Hadron Collider. The magnitudes of the measured observables show a dependence on the different moments as well as on the collision centrality, indicating the presence of nonlinear response in all even moments up to the eighth. Furthermore, the higher-order asymmetric cumulants show different signatures than the symmetric and lower-order asymmetric cumulants. Comparisons with state-of-the-art event generators using two different parametrizations obtained from Bayesian optimization show differences between data and simulations in many of the studied observables, indicating a need for further tuning of the models behind those event generators. These results provide new and independent constraints on the initial conditions and transport properties of the system created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Large-scale parametric modeling of spent nuclear fuel dynamics in the 30 cm package drop scenario

Packages used to transport spent nuclear fuel (SNF) are required by the U.S. Code of Federal Regulations 10 CFR 71.71 to demonstrate satisfactory performance during a drop scenario. While the CFR is meant to ensure safe package function, it does not evaluate survival of the SNF within. The U.S. Department of Energy Spent Fuel and Waste Science and Technology program is working on closing the knowledge gap related to the response of SNF to external mechanical loads, including the hypothetical 30 cm package drop scenario in the CFR. In support of this effort, LS-DYNA finite element simulations were developed by Pacific Northwest National Laboratory (PNNL) to model generic drop scenarios at both the package and fuel assembly level. The models were validated against one-third scale package and full scale fuel assembly drop test data and were exercised to predict fuel cladding strains in a narrow range of model configurations. This work describes a large-scale parametric study conducted by PNNL using the previously developed and validated PWR finite element model, with the addition of a new generic BWR assembly model. The motivation for the parametric study was to characterize the broad range of SNF responses in the 30 cm package drop scenario. This was accomplished by varying the drop orientation, fuel assembly type (17x17 PWR and 10x10 BWR), burnup, cladding temperature, spacer grid buckling load, package mass, impact limiter stiffness, and mechanical gap conditions within the basket. A MATLAB framework was developed to automate LS-DYNA model generation and execution on PNNL institutional computing resources. In total, over 2000 simulations were performed. For each simulation, the SNF response was quantified in terms of permanent grid deformation, fuel rod contact pressure, and strains within the fuel rods, guide tubes, and water rods. The results provide valuable insight into the range of responses that could be reasonably expected from SNF in the hypothetical drop scenario, as well as the sensitivity to each input parameter. The results of this parametric study are a key component of the testing and modeling strategy the Spent Fuel and Waste Science and Technology program is using to close the external loads knowledge gap.

Kadooka, Kevin↗

COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS

SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a random-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport properties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior. Traditional approaches either use effective medium approximations (closed mathematical expressions that are approximation for certain conditions) or continuum simulation models such as finite element or finite volume, which require the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian or heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of first sojourn times of a random walker moving through the composite material. This allows us to directly define a composite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute the intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on the GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is not included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be released as part of cowalker.

YANGUAS-GIL, ANGEL↗

Fuel-air mixing in motored CFR engine at research octane number (RON) relevant condition

This paper presents a three-dimensional (3-D) computational fluid dynamics (CFD) study of a motored cooperative fuel research (CFR) engine at research octane number (RON) relevant condition. The boundary conditions for 3-D simulations were generated with a one-dimensional GT-Power model. For the first time in literature, a carburetor was added to a virtual CFR engine model with 3-D CFD. Therefore, the proposed setup can simulate the fuel and thermal stratifications inside the engine cylinder with realistic detail. The transient simulations in this work were performed within the Reynolds-averaged Navier-Stokes (RANS) framework with a Realizable k-ε turbulence model. Major conclusions from the present work are: (1) The in-cylinder flow of the CFR engine is swirl-dominated due to the existence of the intake valve shroud. (2) There is a significant amount of liquid droplets entering the cylinder during the intake stroke. The maximum instantaneous amount of liquid for 50% PRF 87 (containing 87% iso-octane and 13% n-heptane (v/v)) and 50% ethanol mixture is indicated to be around 26% of total injected fuel mass. (3) The heat of vaporization (HoV) of the fuel is responsible for creating both temperature and charge stratification inside the cylinder.

33 ADVANCED PROPULSION SYSTEMS↗

Interactions between Surface Chemistry and Gas-Phase Combustion: New Optical Tools for Probing Flame-Wall Interactions and the Heterogeneous Chemistry of Soot Growth and Oxidation in Flame. Final report

Some of the most stubborn and technologically critical problems in combustion are dominated by heterogeneous processes. While purely gas-phase combustion systems have been the subject of intense theoretical and experimental study, combustion phenomena occurring at interfaces are far less understood. This is partly caused by the lack of experimental approaches capable of probing locations very close to an interface, especially in the hostile environment of combustion. For laser-based optical techniques, measurements taken near interfaces are often complicated by laser scattering from the surface interfering with relatively weak signals. Further, for measurements intended to probe molecular species adsorbed at the interface between a gas-phase combustion reaction and a condensed phase material, signals are generally overwhelmed by contributions from the bulk phases, causing the small contribution from the interfacial molecular species to be undetectable. Our goal in this project has been to develop new optical tools for imaging chemical species, temperature, and surface species at and near surfaces or interfaces of relevance to combustion. We have placed focus on the development and refinement of ultrafast techniques such as femtosecond coherent Raman imaging and femtosecond/picosecond sum-frequency generation (SFG) scattering, as well as the models used to simulate such spectra under differing conditions of pressure and chemical speciation. The two physical phenomena initially targeted for study in this project were flamewall interactions, and the growth of particulates in flames.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PV Stormwater Management Research and Testing (PV-SMaRT) (Final Technical Report)

The objective of the Photovoltaic Stormwater Management Research and Testing (PV-SMaRT) project was to develop and disseminate research-based, solar-specific resources for estimating stormwater runoff at ground-mounted PV facilities and detail stormwater management and water quality best practices. The intended use of stormwater management and water quality best practices and stormwater runoff estimation resources is to reduce balance of system soft costs associated with stormwater infrastructure requirements and improve water quality through research-tested best practices. Currently, stormwater regulations and guidelines vary by jurisdiction and can lead to regulatory uncertainty and increased compliance costs for managing stormwater runoff at solar sites. To address these concerns, the NREL team and its partners (University of Minnesota, Great Plains Institute, and Fresh Energy) established and engaged an advisory Water Quality Task Force (WQTF); conducted field research on stormwater infiltration and runoff at five ground-mounted PV sites; validated a 3-D hydrologic model to predict water runoff and generate stormwater runoff coefficients for a range of site conditions and PV designs; developed a stormwater management and water quality best practices document; and engaged with local jurisdictions and other stakeholders to disseminate best practices, stormwater runoff coefficients, and other tools. Key outputs of this project were a PV-SMaRT Runoff Calculator developed by University of Minnesota, a webinar detailing project outcomes and how to use the PV-SMaRT runoff calculator, and a document on Best Practices for regulators and developers regarding stormwater runoff at PV sites.

14 SOLAR ENERGY↗

Hydrodynamic Analysis of a Suspended Cylinder Under Regular Wave Loading Based on Computational Fluid Dynamics: Preprint

An investigation into the computation of hydrodynamic loads on a suspended cylinder in regular waves is presented. The primary goal was to perform a three-way-validation of the loads between experimental measurements and simulations from two computational methods. Experimental measurements of the longitudinal inline force on a cylinder suspended at a fixed po- sition were available from the Offshore Code Comparison Col- laboration, Continued, with Correlation (OC5) project, Phase Ia. These measurements were compared to Computational Fluid Dynamics (CFD) simulations based on the solution of Reynolds- averaged Navier-Stokes (RANS) equations, as implemented in STAR-CCM plus. The study encompassed a sensitivity analysis of the loads computed in STAR-CCM plus based on wave modeling, boundary conditions, turbulence modeling, and spatial and tem- poral discretization. The analysis was supplemented by results generated with the offshore wind turbine engineering software OpenFAST, based on a hybrid combination of second-order po- tential flow and viscous drag fromMorison's equation. The focus of the investigation was on the assessment of the accuracy of the computation of first- and higher-order hydrodynamic loads. Sub- stantial differences were observed in the numerical prediction of the second and third harmonic force contribution. Local flow field analysis with CFD was applied to study the physics of wave run-up and diffraction dynamics to identify the causes.

16 TIDAL AND WAVE POWER↗