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Results for “Finite Element Simulation”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Thermal-Hydraulic Analysis of the AFIP-7 Irradiation Test in the Advanced Test Reactor - Oxide Growth Prediction and Correlation

Knowing the thickness of the oxide layer on the surface of aluminum fuel cladding is vitally important for predicting fuel temperature due to the low thermal conductivity of the oxide layer. Several correlation models for predicting oxide growth can be found in the literature. In previous research, the correlations were combined with heat transfer simulations in Abaqus, a finite element analysis code, to forecast the oxide growth. However, this approach requires heat transfer coefficients for modeling heat exchanges with the external flow field, and such coefficients were obtained through empirical equations. Since different empirical equations yield varying heat transfer coefficients, the cladding temperature and predicted oxide thickness both carry a high degree of uncertainty. Here, this research develops a new approach that integrates the fluid flow, fluid and solid heat transfer, and oxide growth correlation(s) into a single computational fluid dynamics model. We demonstrate this approach’s ability to predict oxide development on the AFIP-7 plates during two Advanced Test Reactor (ATR) irradiation cycles. The projected oxide thickness falls within the experimental measurements taken during post irradiation examination.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Comprehensive Efficiency Analysis of Current Source Inverter Based SPM Machine Drive System for Traction Applications

A current-source inverter (CSI) has the natural capability of boosting the output voltage which is a notable advantage over voltage source inverter (VSI) in traction drive applications. This paper investigates the voltage boosting feature of the CSI to improve the overall efficiency of the CSI-based surface permanent magnet (SPM) machine drive system in the constant power region. The effects of the boost function on the total system losses, including the machine copper loss, core loss, and magnet loss, as well as the device conduction and switching loss in the CSI and dc/dc converter, are described using analytical models. The operating characteristics of the machine and CSI are validated by 2-D finite-element analysis (FEA) and simulations. Based on the loss model, the effects of the modulation index on the overall drive system losses and power factor have been analyzed. A genetic algorithm has been used to optimize the CSI's boost ratio, demonstrating that the drive system efficiency can be increased by 1% to 2.5% along the constant-power regime envelope by using the boost function.

current source inverter, genetic algorithm, SPM ma↗
DOE OSTI2024

High-Power Polyphase PCB-Type Inductive Coupler for Wireless Electric Vehicle Charging

The cost and manufacturing difficulty of traditionally wound coils for wireless charging of electric vehicles has led to the exploration of alternative manufacturing for scalable deployment at a range of rated powers. A rotating-field polyphase wireless coupler is developed with balanced fully pitched coils which are not possible with conventional Litz wire. The usage of printed circuit board (PCB) technology is proposed for the innovative construction at large dimensions due to reduced cost, increased ease of manufacturability, and potential geometric customization compared to would coils. Design considerations specific to PCBs are detailed for wireless power transfer coils including advantages such as the potential for many turns and transposition with planar interconnections. A design procedure is developed which may be used to investigate the frequency to power to dimension correlation and limits associated with PCB coils. Designs are simulated in 3D electromagnetic finite element analysis (FEA) for the polyphase coil to evaluate the coupling between coils with varying geometric parameters at 100mm and 500mm outer diameters. A discussion is included on methods to increase PCB power ratings through a mixture of layer stacking, connections, and material selection.

Lewis, Donovin D.↗
DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗
DOE OSTI2023

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↗
DOE OSTI2020

Physics-informed neural networks for inverse problems in nano-optics and metamaterials

In this paper, we employ the emerging paradigm of physics-informed neural networks (PINNs) for the solution of representative inverse scattering problems in photonic metamaterials and nano-optics technologies. In particular, we successfully apply mesh-free PINNs to the difficult task of retrieving the effective permittivity parameters of a number of finite-size scattering systems that involve many interacting nanostructures as well as multi-component nanoparticles. Our methodology is fully validated by numerical simulations based on the finite element method (FEM). The development of physics-informed deep learning techniques for inverse scattering can enable the design of novel functional nanostructures and significantly broaden the design space of metamaterials by naturally accounting for radiation and finite-size effects beyond the limitations of traditional effective medium theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Statistical methods for design and testing of 3D-printed polymers

Different statistical methods are used in various fields to qualify processes and products, especially in emerging technologies like Additive Manufacturing (AM) or 3D printing. Since several statistical methods are being employed to ensure quality production of the 3D-printed parts, an overview of these methods used in 3D printing for different purposes is presented in this paper. The advantages and challenges, to understanding the importance it brings for design and testing optimization of 3D-printed parts are also discussed. The application of different metrology methods is also summarized to guide future researchers in producing dimensionally-accurate and good-quality 3D-printed parts. Here, this review paper shows that the Taguchi Methodology is the commonly-used statistical tool in optimizing mechanical properties of the 3D-printed parts, followed by Weibull Analysis and Factorial Design. In addition, key areas such as Artificial Intelligence (AI), Machine Learning (ML), Finite Element Analysis (FEA), and Simulation require more research for improved 3D-printed part qualities for specific purposes. Future perspectives are also discussed, including other methods that can help further improve the overall quality of the 3D printing process from designing to manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process

In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.

Jo, Eonyeon↗
DOE OSTI2025

A stable potential-based time-domain method for wideband elec- tromagnetic analysis

In previous research, the frequency-domain A-ϕ formulation has been validated using the finite element method for electromagnetic simulations of low-frequency and multi- scale problems, demonstrating excellent numerical accuracy, good matrix condition, and high computational efficiency. Time- domain simulations provide significant advantages for modeling wideband problems and are crucial for multiphysics applications. In this paper, the frequency-domain A-ϕ formulation is extended to the time domain. The central difference scheme is employed for temporal discretization to ensure both accuracy and stability. A numerical example is presented to demonstrate the capability of the proposed time-domain method in wideband electromagnetic analysis.

Mekonnen, Minyichil↗
DOE OSTI2022

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

42 ENGINEERING↗
DOE OSTI2026

Numerical-heating effects in atmospheric pressure streamer discharges simulated with a PIC code

Artificial heating in plasma simulations is a well-known phenomenon which occurs when, among other things, the Debye length is poorly resolved by the simulation mesh. Here, in this work, the degree to which numerical-heating occurs during a simulation of a nanosecond atmospheric pressure streamer discharge is examined. The streamer is simulated using a two-dimensional finite-element, particle-in-cell code Empire, which uses direct simulation Monte Carlo for binary particle interactions. Initially, an estimate of the numerical-heating rate applied to Empire is performed using a simple plasma model. Second, a positive atmospheric pressure streamer discharge simulation is performed to study the effects of numerical heating on plasma density, electron temperature, and streamer velocity. The nominal Debye length is approximately 1 μm and the amount of numerical heating introduced in the simulation is varied by using mesh sizes ranging from 2 μm to 20 μm. A measurable numerical heating quantity is proposed that can be used to estimate the appropriate element size and quantify the numerical-heating that can be expected over the simulation time for an atmospheric pressure streamer. In conclusion while Δx/λ D violations can be an issue it is not likely to be an issue with streamer discharges that are temporally short and occur in environments where collision frequencies are high. This result validates the rationale of grid size choices for a large amount of previously published works where Δx/λ D violation was not clearly addressed. Primary finding of this work is that numerical heating is of minor concern for plasma simulations where electron–neutral collisions are numerous such that multiple collisions can occur within a single plasma period.

Nikic, Dejan [University of New Mexico, Albuquerqu↗
DOE OSTI2025

Simulation of Creep Deformation and Failure in Graded AM Microstructures

This report describes modeling tools and techniques developed to simulate the long-term material performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF). A physics-based Crystal Plasticity Finite Element model is used to simulate creep in microstructures and to study the roles of grain morphology, porosity, and texture. We describe our modeling methodology, including an orientation-mapping technique to capture the spatially varying crystallographic orientation that results from the build conditions. Our study of microstructural features shows that AM microstructures produced by LPBF tend to creep faster in the build direction, while texture and grain boundaries strengthen the transverse directions. However, when grain-boundary porosity and the consequent cavity growth are included in the model, the transverse directions begin to creep faster. In examining texture, the results indicate that spatially varying orientation arising from the build conditions increases anisotropy in the material, making it critical to account for orientation gradients in the material to accurately model its mechanical behavior. We also describe a material-model calibration campaign in which we calibrated the constitutive model specifically for LPBF 316H stainless steel at 725℃ for both solution-annealed and as-built conditions. Finally, these tools and techniques are used to model creep in microstructures representing different regions of an LPBF material with graded microstructure, owing to intentional variation in processing conditions. The creep simulation results show good agreement with experimental data across all three microstructures, with future work planned to study rupture in the material.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Frequency Domain Reflectometry (FDR) Simulation Techniques for Digital Twin Representation of an Electrical Cable

Simulation of cable system response to frequency domain reflectometry (FDR) tests can be instrumental to understanding these tests and the nature and influence of various cable anomalies on test signatures. Reflectometry simulations are based upon a finite element representation of cable conductors and insulation to produce an S-parameter at each evaluated frequency. The aggregate collection of cable model S-parameters can simulate the influence on a test signal injected into a physical cable. Such an approach was undertaken in this work to produce a digital twin simulation of a low-voltage electrical cable. The electrical cable digital twin examined the influence of test simulation parameters and the relative influence of cable anomalies, including thermal aging, water or moisture exposure, water or moisture ingress, and other anomalies. The digital twin in this work included modeling of the conductors, insulation, jacket, and surrounding environment (air, water, etc.). The digital twin could be expanded to include cable bends, junctions and splices, branch or T systems, and termination impedances of motors or instruments. Observations and conclusions of this work include: 1. Fully 3D digital twin simulation of an electrical cable using an FDR approach is possible. However, there are tradeoffs between simulation fidelity and solution time, which must be balanced to ensure the simulation solves in an adequate amount of time (e.g., less than 20 minutes). Simulation parameters to balance include frequency bandwidth, number of frequencies, mesh density, connection impedance, and permittivity tolerance. 2. The digital twin simulation can explain FDR sensitivity to various cable anomalies, including entry and exit from an oven or water bath. 3. The digital twin simulation FDR response attenuates with distance along the cable and is further affected by the frequency bandwidth, which is similar to that observed with physical measurements. 4. The resolution of the digital twin FDR peaks increased with increasing bandwidth and with increasing number of frequencies, again similar to physical measurements. 5. The presence of multiple anomalies in the digital twin does not substantially attenuate the FDR response to anomalies located beyond the first encountered anomaly and impedance mismatch. 6. Spectral variation of the permittivity did not have a significant effect on the FDR response compared to a fixed nominal value. 7. Extension of the digital twin to 1000 ft still allowed for detection of distal anomalies near the far end of the electrical cable from the instrument connection point. 8. The ARENA test bed facilitates efficient NDE evaluations of well understood cable anomalies with various NDE methods without risking actual plant damage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

3-D Simulations of earthquakes rupture jumps: 1. Homogeneous pre-stress conditions

SUMMARY Observational and modelling studies indicate that earthquake ruptures can jump between fault sections as large as ∼3 and ∼5 km for compressional and extensional offsets, respectively. Here, we compare characteristics of the rupture jump process on parallel but offset fault sections from traditional 3-D dynamic rupture simulations governed by slip weakening friction using the finite element code, FaultMod, to those from quasi-dynamic simulations governed by rate- and state-dependent friction (rate-state friction) using the code RSQSim. These simulations use spatially uniform initial stresses. For a variety of measures the rupture renucleation position on the offset fault, the rate-state friction and slip weakening friction models produce very similar results. The principal difference is the additional occurrence of delayed rupture jumps that arise from the time- and stress-dependent nucleation that is characteristic of rate-state friction. For immediate rupture jumps, models with slip weakening friction span greater offsets than those with rate-state friction. However the jump distances are nearly identical when delayed rupture jumps are included in the comparisons. We propose that delayed rupture jumps are the likely mechanism for adjacent large-earthquake pairs and clusters. Based on the similarity of renucleation positions with both dynamic and quasi-dynamic models, we conclude that the renucleation positions for rupture initiation on the receiver fault (separated by less than ∼3 km from the source fault) are primarily controlled by static stress changes induced by slip on the initiating fault. However, in light of the slightly greater maximum jump distances (>3 km) seen with the dynamic slip weakening friction model, dynamic stress changes from seismic waves play an increasingly important role as offset distances increase.

, RSQSim↗
DOE OSTI2025

Derivation and verification of the direct-sampling method for simulating Monte Carlo flight paths in tetrahedral meshes with linear finite-element cross sections

This paper provides a derivation of a direct-sampling approach for modeling continuously varying cross sections in tetrahedral-mesh-based Monte Carlo codes. Specifically, cross sections are spatially approximated using linear nodal finite elements. A linearization strategy is provided for non-linearly varying cross sections. The method is verified against seven analytical pure-absorber test problems. These test problems also highlight the benefit of using linear finite elements over element-wise-constant cross sections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Deformation heterogeneity and intragrain lattice misorientation in high strength contrast, dual-phase bridgmanite/periclase

A bridgmanite/periclase aggregate is investigated due to its prevalence in the Earth’s lower mantle and its importance for understanding geodynamic processes. In dual-phase polycrystalline aggregates, both strength contrast between phases and single crystal elastic and plastic anisotropy are known to influence the development of intragrain misorientation, and the evolution of crystallographic texture. In this study, full-field crystal plasticity simulations are performed with a finite element solution method, and applied to an aggregate of a mechanically strong orthorhombic phase with perovskite structure (bridgmanite, MgSiO 3 ), and a relatively weaker cubic phase (periclase, MgO). The relative strengths of the phases are parameterized to elucidate the effect that strength contrast has on texture evolution and single-phase simulations are performed for comparison. Altogether, results indicate that the relative strength between the two phases influences the development of plasticity, and the overall texture evolution. Results are discussed in light of trends related to the evolution of plasticity and misorientation in the aggregate, and their dependence on both the strength contrast between phases as well as the spatial distribution of grains and phases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Numerical Simulation Studies of Ultrasonic De-Icing for Heating, Ventilation, Air Conditioning, and Refrigeration Structures

Ice accumulation on heating, ventilation, air conditioning, and refrigeration (HVACR) structures presents significant operational challenges. These challenges include reduced efficiency, increased energy consumption, and potential damage to equipment. Traditional de-icing methods, such as chemical treatments, mechanical scraping, or heating-based techniques, are often labor-intensive, costly, and environmentally harmful. Here, this study uniquely investigates ultrasonic de-icing as an energy-efficient alternative for HVACR applications, focusing on the specific structural geometries found in these systems. A comprehensive numerical simulation framework was developed using finite element analysis to explore ultrasonic wave propagation across four distinct HVACR structures. Key parameters such as ultrasonic frequency, power levels, and the number and placement of actuators were examined for their impact on ice detachment efficiency. Results from simulations on a plate structure reveal that ultrasonic excitation can propagate effectively across large areas (at least 150 × 150 mm), enhancing the de-icing coverage. Lower frequency (e.g., 30 to 45 kHz) excitation results in greater displacement, improving de-icing performance, while increased actuator numbers with the same total power input also enhance effectiveness. Two actuators seem sufficient for the de-icing of a 300 × 300 mm plate. For tube-and-fin structures, specific high-power ultrasonic frequencies selectively excite the fin plates, demonstrating efficient ice removal when actuated on the tube. However, optimal performance requires careful design of actuator placement and vibration modes to accommodate the irregular shapes of these structures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗