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Results for “finite element (FE) 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 19 records

Uncertainty quantification in elastic constants of SiC f /SiC m tubular composites using global sensitivity analysis

Silicon carbide fiber and silicon carbide matrix (SiC f /SiC m ) tubes produced through the chemical vapor infiltration process have become a candidate cladding material in nuclear applications. The performance of this composite is influenced by many variables such as braiding angle, porosity, material properties, etc., which vary over a range of values due to the inherent fluctuations in the manufacturing process. In this study, the variability in elastic constants of SiC f /SiC m composite has been quantified through multiscale finite element (FE) simulations, variable screening, and high-fidelity surrogate modeling. The key variables dominantly affecting the elastic constants of SiC f /SiC m tubes were identified using global sensitivity analysis. A surrogate to the high-fidelity FE-based model was used in Monte Carlo simulations to generate a hundred thousand samples from which the uncertainty in elastic constants was assessed. It turned out that the coefficient of variation was less than 10%.

Materials Science↗

An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Response to Community-Scale Geothermal Energy Production

Geothermal heat, as renewable energy, shows great advantage with respect to its environmental impact due to its significantly lower CO2 emissions than conventional fossil fuel. Open and closed-loop geothermal heat pumps, which utilize shallow geothermal systems, are an efficient technology for cooling and heating buildings, especially in urban areas. Integrated use of geothermal energy technologies for district heating, cooling, and thermal energy storage can be applied to optimize the subsurface for communities to provide them with multiple sustainable energy and community resilience benefits. The utilization of the subsurface resources may lead to a variation in the underground environment, which might further impact local environmental conditions. However, very few simulators can handle such a highly complex set of coupled computations on a regional or city scale. We have developed high-performance computing (HPC) based hydrothermal finite element (FE) simulator that can simulate the subsurface and its hydrothermal conditions at a scale of tens of km. The HPC simulator enables us to investigate the subsurface thermal and hydrologic response to the built underground environment (such as basements and subways) at the community scale. In this study, a coupled hydrothermal simulator is developed based on the open-source finite element library deal.II. The HPC simulator was validated by comparing the results of a benchmark case study against COMSOL Multiphysics, in which Aquifer Thermal Energy Storage (ATES) is modeled and a process of heat injection into ATES is simulated. The use of an energy pile system at the Treasure Island redevelopment site (San Francisco, CA, USA) was selected as a case study to demonstrate the HPC capability of the developed simulator. The simulator is capable of modeling multiple city-scale geothermal scenarios in a reasonable amount of time.

Sun, Xiang↗

Simulation for the fault current limiting operation of REBCO CORC superconducting cables with different core materials

With high power density and low loss, CORC superconducting cables composed of RE- Ba 2 Cu 3 O 7–δ (REBCO) coated conductors are of great interest for power transmission applications. They can also effectively be designed to serve as fault current limiters, thanks to their sharp superconducting-to-normal transition. Coupled electromagnetic-thermal finite element (FE) simulations implemented in COMSOL Multiphysics were developed and validated against the published results for the fault current limiting performance of two CORC cables of REBCO coasted conductors wound on either copper or stainless steel cores. For improved accuracy, temperature dependencies of electrical and thermal properties of all component materials were considered in the simulations. The simulations were performed in the cross-sections of the cables for every individual layer of each REBCO tape to deliver comprehensive understanding of evolution of the current distribution and temperature rise in those layers. Furthermore, the studies can suggest approaches to optimize cable design for fault current limiting (FCL) applications by assessing the role of individual components. In the paper, possible computational errors, challenges and improvements are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Influence of Initial fabric and water-wetting on particle fracture and force chain evolution in natural silica sand

Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.

Finite element analysis↗

A Gaussian Process-Based extended Goldak heat source model for finite element simulation of laser powder bed fusion additive manufacturing process

In this study, laser powder bed fusion (L-PBF) additive manufacturing (AM) is a key enabling technology to manufacture highly complex and integrated metallic structures. In L-PBF AM process, the melting of the metal powders and the layers underneath can be governed by either “conduction mode” or “keyhole mode”, with the keyhole mode reportedly leading to porosity and decreased strength and ductility by many studies. In part scale simulations, finite element (FE) model is often used to study the temperature distribution during printing and to predict the residual stress, where a volumetric heat flux with a Gaussian or a double ellipsoidal (Goldak) distribution is often applied as the laser heat source. However, the above heat source models can only capture the melt pool shape in the conduction mode, and fail to capture the transition to keyhole melting mode when the process parameters change. To overcome this inaccuracy, an extended Goldak heat source model is proposed by introducing a laser penetration term as a function of laser parameters obtained from a Gaussian-Process (GP) model. The model is validated by “2D pad” AlSi10Mg L-PBF experiments under a wide range of laser power, scan speed, and laser focus offset, and the results show the model successfully captures the measured melt pool shape in all conditions.

36 MATERIALS SCIENCE↗

Reduction of baseplate distortion during directed energy deposition using compliant features

Distortion in additive manufacturing (AM) remains a barrier to its adoption in precision industries. Baseplate warpage is one such issue which compromises the feasibility of post-process precision machining. The restriction to thermal contraction of the deposited part, imposed by the baseplate, generates bending moments, that in turn causes warpage. A novel distortion mitigation strategy using baseplates with integrated compliant features, which enables thermal contraction of the build is presented. Six unique design concepts are evaluated, including a solid reference, using two deposition geometries. A laser, hot-wire, directed energy deposition (DED) process is used to deposit a symmetric cylindrical part (C-part) and a T-shaped asymmetric part (T-part). Flatness deviation of baseplates is measured using structured light 3D scanning. Measurements reveal a reduction in net flatness deviation of 58.8% for the C-part and 40.9% for the T-part, compared to the solid reference. While most designs yielded reductions exceeding 30% and 20% for the C- and T-parts, respectively, one configuration resulted in increased deviation. Finite element (FE) simulations are performed to elucidate the underlying mechanisms affecting distortion of compliant baseplates during DED. Despite variations between predictions and measurements, agreement in the general trend is observed. It also revealed that initial flatness errors in baseplates significantly affect its deviation during deposition. Predictions indicate that compliant features significantly affect the thermal distribution as well as the evolution of flatness deviation in the baseplate during deposition. Notably, one design exhibited a reduction in distortion during cooling, following its initial increase during deposition. FE predictions show a maximum reduction of 60.9% and 38.8% in net flatness deviation for the C- and T-parts, respectively. The performance of compliant baseplates is found to be governed by both its the thermal and mechanical characteristics, which are crucial factors to be considered during design.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗

Co-training of multiple neural networks for simultaneous optimization and training of physics-informed neural networks for composite curing

This paper introduces a Physics-Informed Neural Network (PINN) technique that co-trains neural networks (NNs) that represent each function in a system of equations to simultaneously solve equations representing an out-of-autoclave (OOA) cure process while conducting optimization in adherence to process requirements. Specifically, this co-training approach benefits from using NNs to represent OOA inputs (air temperature profile) and outputs (part and tool temperature profiles and degree of cure). Production requirements can then be levied on the inputs, such as maximum air temperature and minimum cure cycle, and simultaneously on the outputs, such as degree of cure, maximum part temperature, and part temperature rate limits. The technique is validated with finite element (FE) simulations and physical experiments for curing a Toray T830H-6 K/3900-2D composite panel. Furthermore, this novel approach efficiently models and optimizes the OOA cure process.

Composite curing↗

A Physically-Based Model for Thermo-Oxidative and Hydrolytic Aging of Elastomers

A computationally efficient model is proposed to capture the loss of mechanical performance due to chemical aging that are formed as the competition of chain scission and cross-link formation/dissolution, such as thermo-oxidative aging or hydrolytic aging. The model should be considered an extension of our recent models [1, 2, 3] which further simplifies the matrix behavior based on the assumption of independence of environmental and mechanical damage. The model uses this assumption to reduce the necessary material parameters needed to model constitutive and inelastic behavior of elastomers during aging. To this end, the model can provide accurate predictions of the material performance with the significantly fewer number of fitting parameters. The model is relevant for all decay mechanisms formed by the occurrence of two simultaneous micro-mechanisms; (i) formation/reduction of the cross-links, and (ii) chain scission, both of which are present in thermo-oxidation and hydrolytic aging. Assuming the alteration of the chain density along the aging trajectory is identical to the peroxide cross-link density for thermo-oxidation, and the change of the average molecular weight for hydrolysis, the strain energy of polymer matrix can be rewritten as a function of deformation, deformation history, storage time and aging temperature. Next, the modified network alteration model is formulated for implementation into Finite Element (FE) simulations. The model is built on the presumption of homogeneous and consistent oxygen/water absorption and thus is mainly relevant for relatively thin samples exposed to environmental loads for a long time. The proposed model includes only six physically inspired material parameters. Therefore, while it is computationally efficient, it shows good agreement with own experimental data, which performed on various range of accelerated aging temperatures and times. With respect to its computational efficiency, simplicity, accuracy, and interpret-ability, the model is the right choice for advanced implementations in FE programs.

42 ENGINEERING↗

An active learning framework for the rapid assessment of galvanic corrosion

The current present in a galvanic couple can define its resistance or susceptibility to corrosion. However, as the current is dependent upon environmental, material, and geometrical parameters it is experimentally costly to measure. To reduce these costs, Finite Element (FE) simulations can be used to assess the cathodic current but also require experimental inputs to define boundary conditions. Due to these challenges, it is crucial to accelerate predictions and accurately predict the current output for different environments and geometries representative of in-service conditions. Machine learned surrogate models provides a means to accelerate corrosion predictions. However, a one-time cost is incurred in procuring the simulation and experimental dataset necessary to calibrate the surrogate model. Therefore, an active learning protocol is developed through calibration of a low-cost surrogate model for the cathodic current of an exemplar galvanic couple (AA7075-SS304) as a function of environmental and geometric parameters. The surrogate model is calibrated on a dataset of FE simulations, and calculates an acquisition function that identifies specific additional inputs with the maximum potential to improve the current predictions. This is accomplished through a staggered workflow that not only improves and refines prediction, but identifies the points at which the most information is gained, thus enabling expansion to a larger parameter space. The protocols developed and demonstrated in this work provide a powerful tool for screening various forms of corrosion under in-service conditions.

36 MATERIALS SCIENCE↗

Mechanism-Based Energy Regularization in Computational Modeling of Quasibrittle Fracture

Abstract Quasibrittle materials are featured by a strain-softening constitutive behavior under many loading scenarios, which could eventually lead to localization instability. It has long been known that strain localization would result in spurious mesh sensitivity in finite element (FE) simulations. Previous studies have shown that, for the case of fully localized damage, the mesh sensitivity can be mitigated through energy regularization of the material constitutive law. However, depending on the loading configuration and structural geometry, quasibrittle structures could exhibit a complex damage process, which involves both localized and diffused damage patterns at different stages of loading. This study presents a generalized energy regularization method that considers the spatial and temporal evolution of damage pattern. The method introduces a localization parameter, which describes the local damage pattern. The localization parameter governs the energy regularization of the constitutive model, which captures the transition from diffused to localized damage during the failure process. The method is cast into an isotropic damage model, and is further extended to rate-dependent behavior. The energy regularization scheme is directly incorporated into the kinetics of damage growth. The model is applied to simulate static and dynamic failures of ceramic specimens. It is shown that the present model is able to effectively mitigate the spurious mesh sensitivity in FE simulations of both types of failure. The present analysis demonstrates the essential role of mechanism-based energy regularization of constitutive relation in FE simulations of quasibrittle fracture.

Mechanics↗

Design and Scoping Tests on Alloy 617 Using Notched Specimen Geometry to Validate Methods for Multiaxial Stress Relaxation

In FY 2022, a development effort was initiated at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) to examine the multiaxial stress-relaxation behavior and multiaxial stress-state effect on the creep-fatigue (CF) performance for Alloy 617 at elevated temperatures. This effort supported the development of the design rules in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 5. In this work, two types of the notch specimen geometries were designed. An inelastic constitutive model was used to investigate the stress triaxiality and elastic follow-up effects on the notch specimens under CF deformation in the finite element (FE) simulations. The numerical study demonstrated that the stress triaxiality and elastic follow-up caused by the notches both play significant roles in the stress-relaxation behavior. In addition, Alloy 617 CF experiments were designed, and the testing on the notch specimens is ongoing. CF test failure data will be generated on the specimens with notches under various conditions in FY 2023, and the results will be used to validate methods for accounting for the multiaxial stress relaxation effect in the design code.

36 MATERIALS SCIENCE↗

Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks

Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.

Sun, Yixuan (ORCID:0000000311093380)↗

Toolpath Optimization of Polymer Composite Additive Manufacturing AM Printed Mold to Improve Performance for Compression Molding Applications

This study explores the optimization of toolpaths for short fiber polymer composite additive manufacturing (AM) printed molds in compression molding applications, an emerging trend driven by advancements in 3D printing technology. AM printed molds offer reduced tooling costs and greater design flexibility, particularly for prototyping and low-volume production. The proposed optimization approach evaluates mold performance using two key metrics: deformation and shape accuracy. Multiple toolpaths are generated, and finite element (FE) simulations capture fiber orientation and material properties, which are then integrated into a mechanical performance model. Shape accuracy is assessed by comparing the deformed mold shape with the original using surface normals as a descriptor. The analysis identifies the toolpath that delivers the best overall performance, establishing it as the most suitable option for achieving optimal mold characteristics in compression molding applications.

Limaye, Madhura [ORNL]↗

Simulation of the PBX 9501 Self-Ignited Heavily Confined Cookoff Test

The PBX 9501 self-ignited thermally damaged explosive (SITX) test was carried out by Holmes et al. A 6-inch diameter sphere made of the PBX 9501 was heated inside a steel confinement vessel until it underwent a thermal explosion. This test provided measured temperature data that was used to define a boundary condition to carry out post-experiment finite element (FE) thermal simulations and comparisons of the FE thermal response with the experimental time to thermal ignition and internal temperature measurements at the center of the PBX 9501 sphere. Finite element models of this experiment were constructed using the heat transfer code Aria. A cookoff model for PBX 9501 was used to simulate the thermal decomposition of PBX 9501 and to predict the time to thermal ignition. An inverse heat conduction scheme was designed and applied to estimate a 1D temperature boundary condition.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Multi-scale characterization and simulation of impact welding between immiscible Mg/steel alloys

Vaporizing foil actuator spot welding method is used in this paper to join magnesium alloy AZ31 and uncoated high-strength steel DP590, which are typically considered as un-weldable due to their high physical property disparities, low mutual solubility, and the lack of any intermetallic phases. Characterization results from scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) of the weld interface indicate that the impact creates an Mg nanocrystalline interlayer with abundant Fe particles. The interlayer exhibits intact bonding with both DP590 and AZ31 substrates. To investigate the fundamental bond formation mechanisms at the interface, a finite element (FE)-based process simulation is first performed to calculate the local temperature and deformation at the interface under the given macroscopic experimental condition. Finally, taking the FE results at the interface as inputs, molecular dynamics (MD) simulations are conducted to study the interlayer formation at the Mg/Fe interface during the impact and cooling. The results found a high velocity shearing-induced mechanical mixing mechanism that mixes Mg/Fe atoms at the interface and creates the interlayer, leading to the metallurgical bond between Mg/steel alloys.

36 MATERIALS SCIENCE↗

Stress Relaxation Cracking of Alloys at Temperatures Higher Than 540°C

Type 347H stainless steel (347H SS), used in commercial concentrating solar power (CSP) thermal energy storage to store solar-salt at a temperature of 565°C, has been reported in the literature to be susceptible to stress-relaxation cracking (SRC). The welded heat-affected zone (HAZ) and fusion zone (FZ) of 347H SS, particularly in thick sections, are known to be susceptible to failure during post-weld heat treatment (reheat cracking). SRC could also occur after months or years under an elevated-temperature service environment. Two conditions must be present for failure to occur in the HAZ and/or FZ: 1) a modified or sensitized microstructure and 2) sufficiently high tensile residual stresses present at the elevated service temperature. The overarching goal of this project is to recommend SRC mitigation protocols to avoid susceptibility to fail through SRC at temperatures relevant for CSP. Post weld heat treatment conditions and alternative alloys are investigated as potential mitigation solutions to SRC. We used Gleeble thermomechanical simulation tests and finite element (FE) models to understand the susceptibility of 347H SS to SRC as a function of temperature, stress, and microstructure. We started with a literature review of weldability issues with 347H SS and techniques to mitigate SRC in 347H SS weldments. Next, we used Gleeble experiments to determine reheat cracking susceptibility in the simulated HAZ of 347SS weldments and an alternative alloy, 316L SS (NUCL 167 SPH) with boron added. We also performed Gleeble experiments to compare the reheat cracking susceptibility of 347H cross welded with two different fillers: E347, which is used in some commercial CSP TES tanks, and E16.8.2. We validated the experimental results with FE models of the residual stresses. We found that although the 316L (NUCL 167 SPH) is less susceptible to reheat cracking, it is slightly weaker than 347H and ASME BP&V codes limit its use to a service condition of 565°C. We also found that welds using E16.8.2 as the weld filler are less susceptible to failure than those using E347, likely due to the higher creep ductility of E16.8.2, and that it may be used as an alternative filler for repair welding of 347H welds or as the primary choice of filler for newly developed weld joints. We also found that post weld heat treatment could be a viable solution for mitigating stress in E347-347H SS thick, constrained welds, like those found in CSP tanks, and propose several options for mitigating SRC in existing and future TES tanks.

14 SOLAR ENERGY↗

Mesh objective stochastic simulations of quasibrittle fracture

Continuum finite element (FE) modeling of damage and failure of quasibrittle structures suffers from the spurious mesh sensitivity due to strain localization. Here this issue has been addressed for deterministic analysis through the development of localization limiters. Here this study proposes a mechanism-based model to mitigate the mesh sensitivity in stochastic FE simulations of quasibrittle fracture. The interest is placed on the analysis of large-size structures, where the mesh size is conveniently chosen to be larger than the width of the fracture process zone as well as the correlation length of the random fields of constitutive properties. The present model is formulated within the framework of continuum damage mechanics. Two localization parameters are introduced to describe the evolution of the damage pattern of each finite element. These parameters are used to guide the energy regularization of the constitutive law, as well as to formulate the mesh-dependent probability distributions of constitutive properties. Depending on the prevailing damage pattern, different energy regularization schemes and mesh dependence of the probability distribution functions are used in the constitutive law. The model is applied to simulate the stochastic failure behavior of quasibrittle structures of different geometries featuring different failure processes including damage initiation, localization, and propagation. It is shown that using fixed probability distribution functions of constitutive properties could lead to strong mesh dependence of the prediction of the mean and variance of the structural load capacity. The probability distribution functions of constitutive properties must be linked to the damage pattern, which may evolve during the failure process. Such a mechanism-based modeling of the probability distributions of constitutive properties is essential for mitigating the spurious mesh sensitivity in stochastic FE analysis of quasibrittle fracture.

42 ENGINEERING↗