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Results for “Finite element analysis (FEA)”

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NASA NTRS2000

Challenges in Integrating Nondestructive Evaluation and Finite Element Methods for Realistic Structural Analysis

Capabilities and expertise related to the development of links between nondestructive evaluation (NDE) and finite element analysis (FEA) at Glenn Research Center (GRC) are demonstrated. Current tools to analyze data produced by computed tomography (CT) scans are exercised to help assess the damage state in high temperature structural composite materials. A utility translator was written to convert velocity (an image processing software) STL data file to a suitable CAD-FEA type file. Finite element analyses are carried out with MARC, a commercial nonlinear finite element code, and the analytical results are discussed. Modeling was established by building MSC/Patran (a pre and post processing finite element package) generated model and comparing it to a model generated by Velocity in conjunction with MSC/Patran Graphics. Modeling issues and results are discussed in this paper. The entire process that outlines the tie between the data extracted via NDE and the finite element modeling and analysis is fully described.

Abdul-Aziz, Ali↗

NASA NTRS2020

Stochastic Simulation of Mudcrack Damage Formation in an Environmental Barrier Coating

The FEAMAC/CARES program, which integrates finite element analysis (FEA) with the MAC/GMC (Micromechanics Analysis Code with Generalized Method of Cells) and the CARES/Life (Ceramics Analysis and Reliability Evaluation of Structures / Life Prediction) programs, was used to simulate the formation of mudcracks during the cooling of a multilayered environmental barrier coating (EBC) deposited on a silicon carbide substrate. FEAMAC/CARES combines the MAC/GMC multiscale micromechanics analysis capability (primarily developed for composite materials) with the CARES/Life probabilistic multiaxial failure criteria (developed for brittle ceramic materials) and Abaqus (Dassault Systèmes) FEA. In this report, elastic modulus reduction of randomly damaged finite elements was used to represent discrete cracking events. The use of many small-sized low-aspect-ratio elements enabled the formation of crack boundaries, leading to development of mudcrack-patterned damage. Finite element models of a disk-shaped three-dimensional specimen and a twodimensional model of a through-the-thickness cross section subjected to progressive cooling from 1,300 °C to an ambient temperature of 23 °C were made. Mudcrack damage in the coating resulted from the buildup of residual tensile stresses between the individual material constituents because of thermal expansion mismatches between coating layers and the substrate. A two-parameter Weibull distribution characterized the coating layer stochastic strength response and allowed the effect of the Weibull modulus on the formation of damage and crack segmentation lengths to be studied. The spontaneous initiation of cracking and crack coalescence resulted in progressively smaller mudcrack cells as cooling progressed, consistent with a fractal-behaved fracture pattern. Other failure modes such as delamination, and possibly spallation, could also be reproduced. The physical basis assumed and the heuristic approach employed, which involves a simple stochastic cellular automaton methodology to approximate the crack growth process, are described. The results ultimately show that a selforganizing mudcrack formation can derive from a Weibull distribution that is used to describe the stochastic strength response of the bulk brittle ceramic material layers of an EBC.

Nemeth, Noel N.↗

NASA NTRSDate not supplied

Improved Plate and Beam Models for Thermoviscoelastic Constitutive Modeling of Composites

The effective properties of composites are influenced by the time-dependent behavior of polymer matrices very sensitive to changes in temperature. Improved plate and beam models are required to efficiently design, and simulate composite structures when the long-term performance of large anisotropic composite structures is the matter of interest. In this work, mechanics of structure genome (MSG) is used to con-struct linear thermoviscoelastic plate and beam models that can homogenize three-dimensional heterogeneous materials made of constituents with time- and temperature-dependent behavior. The formulation derives the transient strain energy based on integral formulation for thermorheologically simple materials subject to finite temperature changes with the restriction that the strain is small. The reduced time parameter is introduced to relate the time-temperature dependency of the anisotropic material by means of master curves at reference conditions. The new formulation has been implemented in SwiftCompTM, a general-purpose multiscale constitutive modeling code based on MSG. Experimental data and three-dimensional direct numerical simulations of thin-ply high-strain composites (TP-HSC) using a commercial finite element analysis (FEA) package are conducted to verify the accuracy of SwiftCompTM results. The paper also analyzes the relationship between the shift factor of the polymer matrix and the temperature dependencies of the effective beam properties.

Finite element analysis↗

DOE OSTI2024

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Automating FEA programming

In this paper we briefly describe a combined symbolic and numeric approach for solving mathematical models on parallel computers. An experimental software system, PIER, is being developed in Common Lisp to synthesize computationally intensive and domain formulation dependent phases of finite element analysis (FEA) solution methods. Quantities for domain formulation like shape functions, element stiffness matrices, etc., are automatically derived using symbolic mathematical computations. The problem specific information and derived formulae are then used to generate (parallel) numerical code for FEA solution steps. A constructive approach to specify a numerical program design is taken. The code generator compiles application oriented input specifications into (parallel) FORTRAN77 routines with the help of built-in knowledge of the particular problem, numerical solution methods and the target computer.

Sharma, Naveen↗

NASA NTRS1990

EZDESIT: A Computer Program for Structural Element Sizing and Vehicle Weight Prediction

A method is presented for formulating stiffness terms and thermal coefficients of fiber reinforced composite, stiffened panels for input to finite element analysis (FEA). The method is robust enough to handle panels with general cross sectional shapes, including those which are unsymmetric and/or unbalanced. New thermal coefficients are introduced to quantify panel response from through-the-thickness temperature gradients. Equations are defined for stiffness, thermal expansion, and thermal bending that consider the full complement of membrane, bending, membrane-bending coupling, and transverse shear behavior. A technique of implementing this capability with a single plane of shell finite elements using the MSC/NASTRAN™ FEA program is revealed. Finally, an example of a composite, hat-stiffened panel is included to demonstrate errors that occur when an unsymmetric panel is symmetrically formulated as traditionally done. These erroneous values and the correct ones produced from the presented method are listed for the panel's stiffness matrices, thermal expansion and bending vectors, and the forces and moments that are thermally induced from in-plane and through-the-thickness temperature gradients.

Jeffrey A Cerro↗

NASA NTRS1992

Composite Stiffened Panels: Part I - Stiffness, Thermal Expansion, and Thermal Bending Formulation for Finite Element Analysis

A method is presented for formulating stiffness terms and thermal coefficients of fiber-reinforced composite, stiffened panels for input to finite element analysis (FEA). The method is robust enough to handle panels with general cross sectional shapes, including those which are unsymmetric and/or unbalanced. New thermal coefficients are introduced to quantify panel response from through-the-thickness temperature gradients. Equations are defined for stiffness, thermal expansion, and thermal bending that consider the full complement of membrane, bending, membrane-bending coupling, and transverse shear behavior. A technique of implementing this capability with a single plane of shell finite elements using the MSC/NASTRAN(TradeMark) FEA program is revealed. Finally, an example of a composite, hat-stiffened panel is included to demonstrate errors that occur when an unsymmetric panel is symmetrically formulated as traditionally done. These erroneous values and the correct ones produced from the presented method are listed for the panel's stiffness matrices, thermal expansion and bending vectors, and the forces and moments that are thermally induced from in-plane and through-the-thickness temperature gradients.

Craig S Collier↗

DOE OSTI2024

Fabrication, Modeling, and Testing of a Prototype Thermal Energy Storage Containment

Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output year round; lithium-ion batteries are uneconomical at these durations. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (>1100 degrees C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A laboratory-scale silo prototype was built and validated the congruent transient finite element analysis (FEA) model. The performance of a commercial-scale silo was then characterized using the validated model. The commercial-scale model predicted a storage efficiency above 95% after 5 days of storage with a design storage temperature of 1200 degrees C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

clean energy↗

NASA NTRS2007

Precise Determination of the Zero-Gravity Surface Figure of a Mirror without Gravity-Sag Modeling

The zero-gravity surface figure of optics used in spaceborne astronomical instruments must be known to high accuracy, but earthbound metrology is typically corrupted by gravity sag. Generally, inference of the zero-gravity surface figure from a measurement made under normal gravity requires finite-element analysis (FEA), and for accurate results the mount forces must be well characterized. We describe how to infer the zero-gravity surface figure very precisely using the alternative classical technique of averaging pairs of measurements made with the direction of gravity reversed. We show that mount forces as well as gravity must be reversed between the two measurements and discuss how the St. Venant principle determines when a reversed mount force may be considered to be applied at the same place in the two orientations. Our approach requires no finite-element modeling and no detailed knowledge of mount forces other than the fact that they reverse and are applied at the same point in each orientation. If mount schemes are suitably chosen, zero-gravity optical surfaces may be inferred much more simply and more accurately than with FEA.

measurements↗

DOE OSTI2023

Observation and Modeling of the Thermal Runaway of High-Capacity Pouch Cells Due to an Internal Short Induced by an Indenter

Owing to the complexity of coupling mechanical and electrical solvers for finite element analysis (FEA) of mechanical abuse of a battery, the simulation should be performed by incorporating a local short circuit model activated based on the status of battery elements. However, the approach should also consider various other conditions of the battery simulated, such as the initial state of charge (SOC), for precise simulations of the internal short. This study proposes an approach developed with a mechanical model and single-particle battery model, along with a reaction kinetics model for thermal abuse using LS-DYNA. Several key parameters were selected, such as the activation criteria, kinetic abuse and element integration points during the internal short circuit induced by the indenter. The impact of these key parameters in the FEA on thermal runaway response for various initial SOCs from 25 to 100 % were analyzed. The FEA results obtained were compared against experimental results with various parameters such as activation criterion of internal short, kinetic abuse based on accelerating rate calorimetry (ARC) data. Finally, the root causes of the discrepancy between the FEA and experimental results are discussed regarding integration point what solver can make difference during calculation.

ENERGY STORAGE↗

DOE OSTI2023

Fabrication, Modeling, and Testing of a Prototype for Particle Thermal Energy Storage Containment

Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output throughout the year. Conventional electrochemical batteries (e.g., lithium-ion) are uneconomical in this role due to high energy capacity costs. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (> 1100 degrees C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A containment silo prototype was built at a laboratory scale and used to validate a congruent transient finite element analysis (FEA) model. The validation compared the actual and predicted temperature profile through the prototype over six days as the particles cooled from their initial temperature. The performance of a commercial scale (> 5 GWhth) was then characterized using the validated model. The transient FEA model was subject to several charge-discharge cycles to mimic a possible operating schedule. The commercial-scale model predicted a storage efficiency in excess of 95% after five days of storage with a design storage temperature of 1200 degrees C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

ENERGY STORAGE↗

DOE OSTI2024

Finite Element Analysis and Machine Learning Guided Design of Carbon Fiber Organosheet-Based Battery Enclosures for Crashworthiness

Carbon fiber composite can be a potential candidate for replacing metal-based battery enclosures of current electric vehicles (E.V.s) owing to its better strength-to-weight ratio and corrosion resistance. However, the strength of carbon fiber-based structures depends on several parameters that should be carefully chosen. Here, in this work, we implemented high throughput finite element analysis (FEA) based thermoforming simulation to virtually manufacture the battery enclosure using different design and processing parameters. Subsequently, we performed virtual crash simulations to mimic a side pole crash to evaluate the crashworthiness of the battery enclosures. This high throughput crash simulation dataset was utilized to build predictive models to understand the crashworthiness of an unknown set. Our machine learning (ML) models showed excellent performance (R 2 > 0.97) in predicting the crashworthiness metrics, i.e., crush load efficiency, absorbed energy, intrusion, and maximum deceleration during a crash. We believe that this FEA-ML work framework will be helpful in down select process parameters for carbon fiber-based component design and can be transferrable to other manufacturing technologies.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Modeling the Effective Elasticity of Anisotropic Porous Materials

The development and optimization of composite materials designed for thermal protection of NASA’s spacecraft require understanding their physical response to high-enthalpy environments. To predict their macro-scale properties and behavior, high-fidelity 3D simulations are performed at the microscale on realistic representations of these composites. The digital microstructures are generated either synthetically or through X-ray micro-computed tomography reconstructions. One of the main challenges in the prediction of the structural response of heatshield materials is the computation of the effective elasticity of the fibrous composite, as well as the understanding of the deformation and stresses generated at the microscale. These are driven by the fiber layout within the microstructure and the distribution of the infused matrix. In this effort, the micro-mechanical linear elastic behavior of fibrous ablators is modeled using a numerical method based on the Multi-Point Stress Approximation (MPSA) finite volume scheme, a generalization of the more commonly used Multi-Point Flux Approximation (MPFA) that was presented at the 10th Ablation Workshop. To predict the behavior of fibrous and woven architectures, algorithms that compute the local fiber orientation are used. The implementation of the MPSA was verified using analytical solutions, engineering test cases, and compared against legacy Finite Element Analysis (FEA) software. The stress analysis models were then applied to real geometries used by NASA in thermal protection systems such as fibrous preforms and woven materials and the results were compared to experimental data.

Elasticity↗

DOE OSTI2023

A parametric finite element study for determining burst strength of thin and thick-walled pressure vessels

To accurately predict the burst strength of both thin and thick-walled pressure vessels (PVs), a parametric study of PV burst strength was performed for a wide range of vessel geometries and materials using elastic-plastic finite element analysis (FEA). A valid FEA model was established through a detailed study of 2D versus 3D FEA models, the critical stress failure criterion versus the limit load criteria, and the thick-wall effect on the FEA simulations. Here, the results show that the stresses and strains at the mean diameter, rather than outside diameter, determines a more accurate burst strength for both thin and thick-walled PVs. On this basis, a parametrized FEA script using the ABAQUS Python application programming interface (API) was used to create a large database of PV burst strengths for a variety of vessel geometries and materials, demonstrating that Python scripting is a powerful technique for performing parametric studies or generating large databases. From the FEA results, using the regression method, a new burst pressure model was developed as a function of the vessel geometry (D/t ratio) and material properties (UTS and n). As validated by a large number of full-scale burst test data, the proposed burst model can very accurately predict the burst strength for both thin and thick-walled PVs.

42 ENGINEERING↗

DOE OSTI2026

A meshing framework for digital twins for extrusion based additive manufacturing

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard manufacturing practices. The internal microstructure of AM components has a significant impact on mechanical, vibrational, and shock properties and permits richer design space when this is controllable. Due to complex interactions of internal geometry of an extrusion-based AM component, it is common practice to assume homogeneous behavior or to perform characterization testing on specific toolpath configurations. To avoid testing or material waste, it is necessary to develop a consistently accurate numerical simulation framework with relevant boundary value problems that can handle the complicated geometry of internal material microstructure present in AM components. Herein, a framework is proposed to directly create computational meshes suitable for finite element analysis (FEA) of the fine-scale features generated from extrusion-based AM tool paths to maintain a strong process–structure–property-performance linkage. This mesh can be manually or automatically analyzed using standard FEA simulations such as quasi-static preloading or modal analysis. The framework allows an in-silico assessment of a target AM geometry where fine-scale features greatly impact quantities of design interest such as in soft elastomeric lattices where toolpath infill can greatly influence the self-contact of a structure in compression, which we use as a motivating exemplar. This approach greatly reduces both time and resource waste present in traditional build and test design cycles for non-intuitive design spaces, and acts as a tool for use in the production of a key component of a digital twin, a mesh suitable for finite element analysis. In conclusion, it also further allows for the exploration of toolpath infill to optimize component properties beyond simple linear properties such as density and stiffness.

Additive manufacturing↗

DOE OSTI2023

Computational design of isotropic and anisotropic ultralow thermal conductivity polymer foams

Current state-of-the-art commercial polymer thermal insulation foam exhibits a thermal conductivity of 24 mW·m -1 ·K -1 (equivalently thermal resistivity of R-6/in.), similar to that of static air. To further optimize building energy efficiency, achieving even lower thermal conductivity is needed, which is, however, highly challenging. This paper presents computational evidence that demonstrates the feasibility of achieving an ultra-low thermal conductivity of less than 14.4 mW·m -1 ·K -1 (equivalently R-10/in.) using isotropic and anisotropic foam cell designs. For the isotropic design, we have identified analytical effective medium approximation (EMA) models within the accuracy of ±5% as finite element analysis (FEA) in predicting the effective thermal conductivity of foams with various porosities and filler gases. For the anisotropic design, we have developed and validated new EMA models against FEA in predicting the effective thermal conductivity of general anisotropic cuboids and Voronoi foams. For both isotropic and anisotropic designs, the design spaces for 18, 16, and 14.4 mW·m -1 ·K -1 (equivalently R-8, R-9 and R-10/in.) using various filler gases are obtained. It is found that polymer foams can be improved to achieve ultralow thermal conductivity by reducing CO 2 concentration, reducing radiation, increasing porosity, and using anisotropic pore geometry. In conclusion, these findings contribute to the development of highly efficient thermal insulation materials, enhancing building energy efficiency and promoting sustainable construction practices.

42 ENGINEERING↗

DOE OSTI2022

Modeling interconnections of safety and financial performance of nuclear power plants, part 3: Spatiotemporal probabilistic physics-of-failure analysis and its connection to safety and financial performance

Here, this paper is a byproduct of a line of research by the authors to analyze interrelationships of safety and financial performance of nuclear power plants (NPPs). The result of this line of research is summarized in three parts: Part 1 covers a categorical review of relevant literature and the theoretical bases that support the methodological developments in Part 2. Part 2 introduces an Integrated Enterprise Risk Management (I-ERM) methodological framework to quantify the interconnections of safety and financial performance with a focus on operation and maintenance (O&M) of NPPs. Part 2 has also demonstrated the applicability and values of the I-ERM methodology through an NPP case study. This paper is Part 3, where detailed development and implementation of one of the I-ERM modules, i.e., probabilistic physics-of-failure (PPoF) analysis, and its connection with safety and financial performance is reported. In this article, the physical failure modeling for hardware components is advanced by incorporating finite element analysis (FEA) into PPoF analysis and coupling the FEA-based PPoF with the maintenance performance through a renewal process model. This article covers two scientific contributions: (i) first-of-its-kind incorporation of FEA into the PPoF model of thermal fatigue for NPP components; and (ii) advancing the interface between the PPoF analysis and the renewal process model in order to deal with spatiotemporal FEA outputs and to efficiently estimate the physical transition rates even when the PPoF outputs are dominated by success data. Through the incorporation of FEA, the resolution of the PPoF analysis is enhanced as spatiotemporal conditions such as stress and temperature can be considered explicitly instead of relying on simplified assumptions or analytical models with reduced spatiotemporal dimensions. To demonstrate an application of the FEA-based PPoF analysis and its coupling with maintenance through the renewal process model, a case study is conducted using excess letdown elbow piping in the chemical and volume control system of a Pressurized Water Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Development of Lightweight Structural Materials with Improved Properties for Fission Batteries

The notion of a “fission battery” conveys a vision focused on realizing very simple “plug-and-play” nuclear systems that can be integrated into a variety of applications requiring affordable, reliable energy in the form of electricity and/or heat and function without operations and maintenance staff. Fission batteries require lightweight structural materials to increase their mobility, and the lightweight materials must demonstrate structural resilience under various conditions. The objective of this work is to develop lattice structured lightweight structural material featuring a good combination of mechanical properties using advanced modeling and simulation together with an advanced additive manufacturing technique such as laser powder bed fusion. The preliminary results show that different lattice structures and types can be successfully meshed using nTopology software, and the lattice structure data can be successfully transformed to Multiphysics Object-Oriented Simulation (MOOSE) Environment input. Finite Element Analysis (FEA) displays that, at macro/engineering scale simulation, the weight saving design has an obvious effect on tensile behavior such as effective elastic modulus and yield stress. The novel approaches of this work are (1) development of lattice structures for improved mechanical properties using advanced simulation and modeling techniques; and (2) model predictions of the mechanical properties (e.g., strength and stress distribution) of macroscopic materials in order to preliminarily select a lattice structure for additive manufacturing.

36 MATERIALS SCIENCE↗