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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 OSTI2026

Comparative analysis of plasticity-based GND density estimation methods in crystal plasticity finite element models

In crystal plasticity finite element (CPFE) simulations, accurately quantifying geometrically necessary dislocations (GNDs) is critical for capturing strain gradients in polycrystals. We compare different methods for quantifying GNDs, all of which originate from the Nye tensor, which is computed as the curl of the plastic deformation gradient. The projection technique directly decomposes the Nye tensor onto individual screw and edge dislocation components to compute GNDs. This approach requires converting a nine-component Nye tensor into densities for a larger number of dislocation systems, a fundamentally underdetermined (non-unique) process, which is resolved using L2 minimization. In contrast, when employing CPFE analysis, one could directly compute dislocation densities on each slip system using shear gradients. Projection and slip gradient methods are compared with respect to their prediction of GNDs with changing grain size, strain, and grain neighborhoods, including multigrain junctions. Although these techniques match analytical GND densities for single slip, single crystal deformation, and are consistent with anticipated overall GND trends, we find that the GND densities from projection techniques are significantly lower than those predicted from CPFE-based slip gradients in polycrystals. A suggested improvement of only using the active dislocation systems in the projection technique almost entirely resolved this mismatch.

Crystal plasticity↗
DOE OSTI2022

Finite Element Modeling of Spent Nuclear Fuel in Dry Storage under Seismic Excitation

Spent nuclear fuel (SNF) is currently stored at independent spent fuel storage installations (ISFSIs) at nuclear power plant sites across the US. The US Department of Energy (DOE) Spent Fuel and Waste Science and Technology (SFWST) program is currently working to understand the response of SNF during a seismic event. This investigation is part of a long-term effort by DOE to quantify the external mechanical loads on SNF. The SFWST program has recently completed campaigns evaluating SNF behavior during normal conditions of transport and in 30 cm package drop scenarios; both campaigns included a combination of testing and modeling. Likewise, the investigation into seismic response of SNF will include full-size shake table tests of a vertical storage overpack containing instrumented surrogate fuel assemblies, as well as pre- and post-test finite element modeling. This work focuses on the development of finite element models simulating the planned test configuration. The seismic response is calculated at two scales: at the package level, and at the fuel level. The package level model evaluates the behavior of the storage overpack and its contents in response to the ground motions of a representative earthquake. The motion of the package is input to the fuel level model, which consists of a detailed finite element model of a 17x17 or 16x16 pressurized water reactor (PWR) fuel assembly or of a 10x10 boiling water reactor (BWR) fuel assembly. The stress and strain on individual components such as fuel rods and guide tubes are extracted from this model. This work details the SNF response to various input ground motions, considering representative earthquakes in the Central and Eastern US under various site conditions. Also discussed is the development of a “reduced scope” finite element model of the SNF, which consists of a single fuel rod while retaining the dynamic response of the entire fuel assembly. This reduced scope model addresses the significant computational expense of modeling the SNF under long-duration input ground motions and facilitates simulating additional parameter variations of the model beyond the as-tested configuration. The modeling results provide important insight that will help to inform future testing and modeling efforts by the SFWST program to close the knowledge gap related to external loads on SNF.

Kadooka, Kevin↗
DOE OSTI2023

Finite element modeling of biomass hopper flow

Hoppers are widely used biomass handling devices that channel bulk biomass from storage to subsequent handling equipment. Jenike’s longstanding approach, based on the Mohr-Coulomb model, has been successfully used to design hoppers handling cohesionless granular materials such as grains and other agricultural produces. However, designing a hopper to ensure reliable biomass flow is found to be challenging due to cohesion, irregular particle shape, and bulk material elastoplasticity. This study aims to address the biomass handling engineering challenge with alternative constitutive material models concerning the flow behavior of bulk solids. Finite element modeling is an approach that allows for implementation of different material models, whose underlying constitutive theories assist in investigating the origin and manifestation of bulk mechanical behavior of granular materials. This study focuses on the incipient gravity hopper flow of two types of biomass feedstocks, i.e., ground corn stover and Douglas fir wood. Three widely used constitutive material models, i.e., Mohr-Coulomb model, modified Cam-Clay model, and Drucker-Prager/Cap model, are implemented. Using the flow pattern represented by the volume of biomass exhibiting more than 7% of axial strain (Kamath and Puri, 1999), the finite element model predicts that the bulk corn stover particulate material forms an arch, which represents a hampered transition from the static state to the dynamic flow-state out of the hopper, whereas bulk Douglas fir wood particulate material develops a reliable mass flow pattern. A laboratory scale hopper was used to experimentally determine the biomass flow conditions, which were subsequently compared with the predicted onset of flow by a finite element model (FEM). The developed FEM was found to correctly predict the initiation of mass flow for the milled Douglas fir wood, whereas corn stover was predicted to establish a strong core flow suggesting an unreliable handling characteristic. This observation aligns with the reported poor handling of milled corn stover.

09 BIOMASS FUELS↗
DOE OSTI2020

Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.

42 ENGINEERING↗
DOE OSTI2017

Modal Substructuring of Geometrically Nonlinear Finite Element Models with Interface Reduction

Substructuring methods have been widely used in structural dynamics to divide large, complicated finite element models into smaller substructures. For linear systems, many methods have been developed to reduce the subcomponents down to a low order set of equations using a special set of component modes, and these are then assembled to approximate the dynamics of a large scale model. In this paper, a substructuring approach is developed for coupling geometrically nonlinear structures, where each subcomponent is drastically reduced to a low order set of nonlinear equations using a truncated set of fixedinterface and characteristic constraint modes. The method used to extract the coefficients of the nonlinear reduced order model (NLROM) is non-intrusive in that it does not require any modification to the commercial FEA code, but computes the NLROM from the results of several nonlinear static analyses. The NLROMs are then assembled to approximate the nonlinear differential equations of the global assembly. The method is demonstrated on the coupling of two geometrically nonlinear plates with simple supports at all edges. The plates are joined at a continuous interface through the rotational degrees-of-freedom (DOF), and the nonlinear normal modes (NNMs) of the assembled equations are computed to validate the models. The proposed substructuring approach reduces a 12,861 DOF nonlinear finite element model down to only 23 DOF, while still accurately reproducing the first three NNMs of the full order model.

42 ENGINEERING↗
DOE OSTI2019

Finite-element modeling for an explosively loaded ferroelectric generator

A preliminary finite-element model has been developed using the ALEGRA-FE code for explosive driven depoling of a PZT 95/5 ferroelectric generator. The ferroelectric material is characterized using hysteresis-loop and hydrostatic depoling tests. These characteristics are incorporated into ALEGRA-FE simulations that model the explosive drive mechanism and shock environment in the material leading to depoling, as well as the ferroelectric response and the behavior of a coupled circuit. The ferroelectric-to-antiferroelectric phase transition is captured, producing an output voltage pulse that matches experimental data to within 10% in rise time, and to within about 15% for the final voltage. Both experimental and modeled pulse magnitudes are less than the theoretical maximum output of the material. Observations from materials characterization suggest that unmodeled effects such as trapped charge in the stored FEG material may have influenced the experimentally observed output.

42 ENGINEERING↗
DOE OSTI2015

Finite element model for piles in liquefiable ground

This paper develops a three dimensional finite element modelling method for piles in liquefiable ground and applies it to the analysis of seismic pile responses. A unified plasticity model for large post-liquefaction shear deformation of sand provides the basis for the effective and efficient modelling of liquefiable ground. Special attention is dedicated towards the modelling of piles and soil-pile interface to accurately reflect the behaviour of piles. A staged modelling procedure is adopted to appropriately generate the initial conditions for the soil and piles and achieve hydrostatic pore pressure prior to seismic loading. Three centrifuge shaking table tests on single piles, both with and without pile cap and superstructure, in level and inclined liquefiable ground are conducted and simulated in validation and application of the proposed method. Further studies to investigate the effects of pile cap, lateral spreading, and non-liquefiable surface layer are undertaken numerically using the validated method. The results show these aforementioned factors to be influential in the dynamic and residual response of piles in liquefiable ground.

Centrifuge test↗
DOE OSTI2019

Investigation on Microsegregation of IN718 Alloy During Additive Manufacturing via Integrated Phase-Field and Finite-Element Modeling

In this work, we apply a multi-scale model combining finite-element method (FEM) and phase-field model (PFM) to simulate the evolution of solidification microstructures at different locations within a molten pool of an additively manufactured IN718 alloy. Specifically, the FEM is used to calculate the shape of molten pool and the relative thermal gradient G at the macroscale. Then, the calculated thermal information is input into PFM for microstructure simulation. Finally, the morphology of solidification structures and formation of Laves phase at different sites are studied and compared. We found that the solidification site with a large angle between the temperature gradient and the preferred crystalline orientation could build up a high niobium (Nb) concentration in the liquid during solidification but has less possibility of forming continuous long chain morphology of Laves phase particles. This finding provides an understanding of the microstructure evolution inside the molten pool of IN718 alloy during solidification. Further, the finding indicates that the site with a large misorientation angle will have a good hot cracking resistance after solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2018

In-situ neutron diffraction and crystal plasticity finite element modeling to study the kinematic stability of retained austenite in bearing steels

This work integrates in-situ neutron diffraction and crystal plasticity finite element modeling to study the kinematic stability of retained austenite in high carbon bearing steels. The presence of a kinematically metastable retained austenite in bearing steels can significantly affect the macro-mechanical and micro-mechanical material response. Mechanical characterization of metastable austenite is a critical component in accurately capturing the micro-mechanical behavior under typical application loads. Traditional mechanical characterization techniques are unable to discretely quantify the micro-mechanical response of the austenite, and as a result, the computational predictions rely heavily on trial and error or qualitative descriptions of the austenite phase. In order to overcome this, in the present work, we use in-situ neutron diffraction of a uniaxial tension test of an A485 Grade 1 bearing steel specimen. The mechanical response determined from the neutron diffraction analysis was incorporated into a hybrid crystal plasticity finite element model that accounts for the martensite's crystal plasticity and the stress-assisted transformation from austenite to martensite in bearing steels. Here, the modeling response was used to estimate the single crystal elastic constants of the austenite and martensite phases. Finally, the results show that using in-situ neutron diffraction, coupled with a crystal plasticity model, can successfully predict both the micro-mechanical and macro-mechanical responses of bearing steels while accounting for the martensitic transformation of the retained austenite.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermally anisotropic building envelope for thermal management: finite element model calibration using field evaluation data

The thermally anisotropic building envelope (TABE) is an active building envelope that redistributes thermal loads in response to weather conditions and building energy demand. Conductive layers throughout the TABE distribute low-grade heat among hydronic loops, altering heat flow direction and intensity. Finite element models of TABE roof and wall panels were developed and calibrated using field evaluation data. The calibration results showed that heat flux differences between the experimental data and finite element models averaged –0.42% and 3.57%, with a maximum mean square error of 1.78 and 3.96 for roof and wall panels, respectively. A reduction in heat flux from the environment to the building living space over the entire testing period (weeks in July/August) was found to be 85% for roof panels and 335% (load reversed) for wall panels. Finally, these results indicate TABE can effectively harness low-grade thermal energy sources to achieve high energy efficiency and promote demand-side management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

<i>Finite Element Modeling of Biomass Hopper Flow</i>

The hopper is one of the widely used biomass handling devices that channels the bulk biomass from storage to the subsequent handling systems. Although Jenike's approach has been successfully used for hoppers handling grains and other agricultural produces for decades, designing a hopper, ensuring reliable biomass handling is found to be challenging. This study aims to address this engineering problem with alternative constitutive material models concerning the flow behavior of bulk solids. Finite element modeling is an approach that allows for implementing different material models. Underlying constitutive theories of different material models assist in investigating the mechanical behavior of a particulate system, including the flow characteristics of ground biomass. This study demonstrates hopper flow models of two types of biomass, i.e., ground corn stover and Douglas fir, with the Mohr-Coulomb model, which is based on Jenike's approach, modified Cam-Clay model, and Drucker-Prager/Cap model. The modeling results are compared with hopper flow experiments to highlights the advantages and shortfalls of each constitutive biomass flow model.

09 BIOMASS FUELS↗
DOE OSTI2022

A New Perspective of Post-Weld Baking Effect on Al-Steel Resistance Spot Weld Properties through Machine Learning and Finite Element Modeling

The root cause of post-weld baking on the mechanical performance of Al-steel dissimilar resistance spot welds (RSWs) has been determined by machine learning (ML) and finite element modeling (FEM) in this study. A deep neural network (DNN) model was constructed to associate the spot weld performance with the joint attributes, stacking materials, and other conditions, using a comprehensive experimental dataset. The DNN model positively identified that the post-weld baking reduces the joint performance, and the extent of degradation depends on the thickness of stacking materials. A three-dimensional finite element (FE) model was then used to investigate the root cause and the mechanism of the baking effect. It revealed that the formation of high thermal stresses during baking, from the mismatch of thermal expansion between steel and Al alloy, causes damage and cracking of the brittle intermetallic compound (IMC) formed at the interface of the weld nugget during welding. This in turn reduces the joint performance by promoting undesirable interfacial fracture when the welds were subjected to externally applied loads. The FEM model further revealed that increase in structural stiffness, because of increase in steel sheet thickness, reduces the thermal stresses at the interface caused by the thermal expansion mismatch and consequently lessens the detrimental effect of post-weld baking on the joint performance.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Finite Element Modeling of Orthogonal Machining of Brittle Materials Using an Embedded Cohesive Element Mesh

Machining of brittle materials is common in the manufacturing industry, but few modeling techniques are available to predict materials’ behavior in response to the cutting tool. The paper presents a fracture-based finite element model, named embedded cohesive zone–finite element method (ECZ–FEM). In ECZ–FEM, a network of cohesive zone (CZ) elements are embedded in the material body with regular elements to capture multiple randomized cracks during a cutting process. The CZ element is defined by the fracture energy and a scaling factor to control material ductility and chip behavior. The model is validated by an experimental study in terms of chip formation and cutting force with two different brittle materials and depths of cut. The results show that ECZ–FEM can capture various chip forms, such as dusty debris, irregular chips, and unstable crack propagation seen in the experimental cases. For the cutting force, the model can predict the relative difference among the experimental cases, but the force value is higher by 30–50%. The ECZ–FEM has demonstrated the feasibility of brittle cutting simulation with some limitations applied.

Takabi, Behrouz↗
DOE OSTI2012

Efficient Computation of Info-Gap Robustness for Finite Element Models

A recent research effort at LANL proposed info-gap decision theory as a framework by which to measure the predictive maturity of numerical models. Info-gap theory explores the trade-offs between accuracy, that is, the extent to which predictions reproduce the physical measurements, and robustness, that is, the extent to which predictions are insensitive to modeling assumptions. Both accuracy and robustness are necessary to demonstrate predictive maturity. However, conducting an info-gap analysis can present a formidable challenge, from the standpoint of the required computational resources. This is because a robustness function requires the resolution of multiple optimization problems. This report offers an alternative, adjoint methodology to assess the info-gap robustness of Ax = b-like numerical models solved for a solution x. Two situations that can arise in structural analysis and design are briefly described and contextualized within the info-gap decision theory framework. The treatments of the info-gap problems, using the adjoint methodology are outlined in detail, and the latter problem is solved for four separate finite element models. As compared to statistical sampling, the proposed methodology offers highly accurate approximations of info-gap robustness functions for the finite element models considered in the report, at a small fraction of the computational cost. It is noted that this report considers only linear systems; a natural follow-on study would extend the methodologies described herein to include nonlinear systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Finite element modeling of nanoscale-enabled microinductors for power electronics

Here, this paper focuses on the finite element modeling of toroidal microinductors, employing first-of-its-kind nanocomposite magnetic core material and superparamagnetic iron nanoparticles covalently cross-linked in an epoxy network. Energy loss mechanisms in existing inductor core materials are covered as well as discussions on how this novel core material eliminates them providing a path toward realizing these low form factor devices. Designs for both a 2 μH output and a 500 nH input microinductor are created via the model for a high-performance buck converter. Both modeled inductors have 50 wire turns, less than 1 cm 3 form factors, less than 1 Ω AC resistance, and quality factors, Q’s, of 27 at 1 MHz. In addition, the output microinductor is calculated to have an average output power of 7 W and a power density of 3.9 kW/in 3 by modeling with the 1st generation iron nanocomposite core material.

36 MATERIALS SCIENCE↗