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DOE OSTI2019

Statistically informed upscaling of damage evolution in brittle materials

The presence and growth of micro-cracks degrade the strength of brittle solids, greatly impacting the overall material response. Hence, the evolution of these micro-cracks must be accounted for in models describing the relationship between stress and strain so that accurate predictions of material failure can be made. The evolution of individual cracks and crack networks can be simulated with high-fidelity microscale models utilizing highly resolved meshes that can be computationally expensive to a point in which it limits the simulation scale. Hence, for many engineering applications that require simulations of large components, continuum-scale models, which cannot explicitly resolve individual cracks and thus lose important physical information, are required. In this work, we bridge these two scales by developing and implementing a continuum-scale effective moduli constitutive model that is informed by crack statistics generated from a high-fidelity model resolved using a finite-discrete element method (FDEM) implementation. Using statistical information describing the evolution of crack lengths and orientations, this model can capture the effects of brittle damage evolution without the need to resolve individual cracks. We have successfully captured the stress-strain behavior of the high-fidelity simulations using the statistics-based constitutive model shown through direct comparison of stress-strain curves. The curves match within error bars present in the strain-softening portions of the stress-strain curve of the high-fidelity results due to the statistical variation of the initial pre-existing crack network. In conclusion, the stress-strain curves are also compared to experimental results for similar loading conditions and show good qualitative agreement.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Grain2Mesh: Mesh Generation for Grain-Scale Nonlinear Elasticity Modeling

The nonlinear hysteretic behavior of rocks under cyclic loading is a crucial area of study in geomechanics. The macroscopic response of a variety of materials has been found to be contingent upon the behavior of the micro-scale structure. This project aims to develop a functional and maintainable software package for generating a multi-phase numerical mesh and accompanying simulation files for finite element modeling used in computational mechanics solvers. Meshes generated from images often lack key preprocessing that reduces noise and prevents mesh element distortion that can increase computational cost. By incorporating user feedback throughout, grain2mesh ensures a high-fidelity mesh that can be used to model grain-scale interactions such as shearing, crack propagation, and interfacial material contrast. Scientific applications of this software include material fracturing, stress-strain analysis for natural and engineered materials, and nonlinear meso-scale analysis.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

MAC/GMC 4.0 User's Manual: Keywords Manual

This document is the second volume in the three volume set of User's Manuals for the Micromechanics Analysis Code with Generalized Method of Cells Version 4.0 (MAC/GMC 4.0). Volume 1 is the Theory Manual, this document is the Keywords Manual, and Volume 3 is the Example Problem Manual. MAC/GMC 4.0 is a composite material and laminate analysis software program developed at the NASA Glenn Research Center. It is based on the generalized method of cells (GMC) micromechanics theory, which provides access to the local stress and strain fields in the composite material. This access grants GMC the ability to accommodate arbitrary local models for inelastic material behavior and various types of damage and failure analysis. MAC/GMC 4.0 has been built around GMC to provide the theory with a user-friendly framework, along with a library of local inelastic, damage, and failure models. Further, applications of simulated thermo-mechanical loading, generation of output results, and selection of architectures to represent the composite material have been automated in MAC/GMC 4.0. Finally, classical lamination theory has been implemented within MAC/GMC 4.0 wherein GMC is used to model the composite material response of each ply. Consequently, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. This volume describes the basic information required to use the MAC/GMC 4.0 software, including a 'Getting Started' section, and an in-depth description of each of the 22 keywords used in the input file to control the execution of the code.

Bednarcyk, Brett A.↗

NASA NTRS2002

MAC/GMC 4.0 User's Manual: Example Problem Manual

This document is the third volume in the three volume set of User's Manuals for the Micromechanics Analysis Code with Generalized Method of Cells Version 4.0 (MAC/GMC 4.0). Volume 1 is the Theory Manual, Volume 2 is the Keywords Manual, and this document is the Example Problems Manual. MAC/GMC 4.0 is a composite material and laminate analysis software program developed at the NASA Glenn Research Center. It is based on the generalized method of cells (GMC) micromechanics theory, which provides access to the local stress and strain fields in the composite material. This access grants GMC the ability to accommodate arbitrary local models for inelastic material behavior and various types of damage and failure analysis. MAC/GMC 4.0 has been built around GMC to provide the theory with a user-friendly framework, along with a library of local inelastic, damage, and failure models. Further, application of simulated thermo-mechanical loading, generation of output results, and selection of architectures to represent the composite material, have been automated in MAC/GMC 4.0. Finally, classical lamination theory has been implemented within MAC/GMC 4.0 wherein GMC is used to model the composite material response of each ply. Consequently, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. This volume provides in-depth descriptions of 43 example problems, which were specially designed to highlight many of the most important capabilities of the code. The actual input files associated with each example problem are distributed with the MAC/GMC 4.0 software; thus providing the user with a convenient starting point for their own specialized problems of interest.

Bednarcyk, Brett A.↗

NASA NTRS2003

Application of Probabilistic Analysis to Aircraft Impact Dynamics

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stressstrain behaviors, laminated composites, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the uncertainty in the simulated responses. Several criteria are used to determine that a response surface method is the most appropriate probabilistic approach. The work is extended to compare optimization results with and without probabilistic constraints.

Lyle, Karen H.↗

NASA NTRS2006

Probabilistic Design of Composite Structures

A formal procedure for the probabilistic design evaluation of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, and service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the evaluation. The probabilistic evaluation consists of: (1) design criteria, (2) modeling of composite structures and uncertainties, (3) simulation methods, and (4) the decision-making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically evaluated with accuracy and efficiency.

Chamis, Christos C.↗

NASA NTRS2003

Finite-Element Methods for Real-Time Simulation of Surgery

Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.

Basdogan, Cagatay↗

NASA NTRS2023

Finite Element Simulation of Three Full-Scale Crash Tests for Cessna 172 Aircraft

The NASA Emergency Locator Transmitter Survivability and Reliability project was initiated in 2013 to assess the crash performance standards for the next generation of emergency locator transmitter (ELT) systems. Three Cessna 172 aircraft were acquired to perform crash testing at the NASA Langley Research Center Landing and Impact Research Facility. Full-scale crash tests were conducted in the summer of 2015 and each test article was subjected to severe, but survivable, impact conditions including a flare-to-stall during emergency landing, and two controlled-flight-into-terrain scenarios. Finite element analyses were performed to numerically simulate the aircraft response to the crash tests. The first test simulated impacting a concrete surface represented analytically by a rigid plane. Tests 2 and 3 simulated impacting a dirt surface represented analytically by an Eulerian grid of bric k elements using a Mohr-Coulomb material model. The objective of this paper is to summarize the test and analysis results for the three full-scale crash tests. Simulation models of the airframe which correlate well with the tests are needed for future studies of alternate ELT mounting configurations.

Finite Element Analysis↗

DOE OSTI2015

Reactor Pressure Vessel Integrity Assessments with the Grizzly Aging Simulation Code

Grizzly is a simulation tool being developed at Idaho National Laboratory (INL) as part of the US Department of Energy’s Light Water Reactor Sustainability program to provide improved safety assessments of systems, components, and structures in nuclear power plants subjected to age-related degradation. Its goal is to provide an improved scientific basis for decisions surrounding license renewal, which would permit operation of commercial nuclear power plants beyond 60 years. Grizzly is based on INL’s MOOSE framework, which enables multiphysics simulations in a parallel computing environment. It will address a wide variety of aging issues in nuclear power plant systems, components, and structures, modelling both the aging processes and the ability of age-degraded components to perform safely. The reactor pressure vessel (RPV) was chosen as the initial application for Grizzly. Grizzly solves tightly coupled equations of heat conduction and solid mechanics to simulate the global response of the RPV to accident conditions, and uses submodels to represent regions with pre-existing flaws. Domain integrals are used to calculate stress intensity factors on those flaws. A physically based empirical model is used to evaluate material embrittlement, and is used to evaluate whether crack growth would occur. Grizzly can represent the RPV in 2D or 3D, allowing it to evaluate effects that require higher dimensionality models to capture. Work is underway to use lower length scale models of material evolution to inform engineering models of embrittlement. This paper demonstrates an application of Grizzly to RPV failure assessment, and summarizes on-going work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Overview of Additively Manufactured TPS Proposed Flight Test and Earth Re-Entry Capsule Design

A flight mechanics overview is presented of an Earth flight test designed to investigate a novel, 3D printed thermal protection system (TPS) that is currently in development at NASA as part of the Additive Manufacturing of Thermal Protection Systems project. The project is pioneering a method to print a thermal protection system onto an entry vehicle forebody one layer at a time. This method reduces labor and complexity as compared to traditional manufacturing methods while increasing mission-dependent customization of through-depth materials properties. The flight test has three objectives. First, subject the forebody stagnation point of a capsule equipped with additively manufactured TPS (AMTPS) material to peak heat fluxes in excess of 100 $W/cm^2$. Second, capture in-flight data to enable flight reconstruction and AMTPS material thermal response model improvement. Third, recover the capsule with data storage and forebody AMTPS intact to enable post-flight inspection and analysis of AMTPS performance. The flight test trajectory is designed to achieve a peak stagnation point, cold-wall, entry heat flux of 135~$W/cm^2$. Flight mechanics simulations are performed using the Program to Optimize Simulated Trajectories II (POST2) and Monte-Carlo analysis yields statistical percentiles on vehicle performance at key points along the trajectory. Based on the flight mechanics analysis presented in this paper, a prototype capsule was designed, partially fabricated, and underwent preliminary component stress testing in preparation for fabrication of the flight unit capsule. The capsule outer mold line is a modified version of the heritage Mars Microprobe geometry. The capsule has a 0.356~m diameter, a 30~kg mass, and a hypersonic ballistic coefficient of 300~$kg/m^2$. Sensor selection is guided by flight dynamics simulations with the goal of resolving the re-entry heating pulse. On-board instrumentation include forebody and aftbody pressure sensors and thermocouples, a 9-axis IMU, a GPS receiver, and an Iridium satellite modem, all of which collect and store data throughout flight via on-board avionics systems. A two-stage parachute system is designed to decelerate the capsule to touchdown velocities that will not result in significant fracture or deformation of the charred AMTPS material at ground impact.

Flight Mechanics↗

DOE OSTI2026

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Bismuthene is a heavy 2D material whose strong spin–orbit coupling and recently observed single-element ferroelectricity have intensified interest in its structural, vibrational, and transport properties. Accurate modeling of these behaviors requires a short-range interatomic potential that can reproduce the underlying bonding physics at a fraction of the computational cost of first-principles methods. However, such a potential is currently unavailable. Here, in this work, we construct a Tersoff bond-order potential for β-bismuthene using a reinforcement-learning framework that integrates a continuous Monte Carlo Tree Search with a simplex-based local optimizer. The optimized parameter sets reproduce first-principles lattice constants, cohesive energy, the equation of state, elastic constants, and phonon dispersion. We validate the models by performing thermal-conductivity calculations and uniaxial fracture simulations our findings confirm the reliability of the resulting models across multiple thermomechanical regimes. Comparison of the three best solutions reveals how differences in pairwise interactions, angular terms, and bond-order behavior govern phonon features and mechanical responses. We demonstrate an interpretable and computationally efficient potential for bismuthene and demonstrate a general reinforcement-learning strategy for developing bond-order models in emerging 2D materials.

deformation↗

DOE OSTI2018

Ultra-thin and strong formvar-based membranes with controlled porosity for micro- and nano-scale systems

Here, we present a methodology for developing ultra-thin and strong formvar-based membranes with controlled morphologies. Formvar is a thin hydrophilic and oleophilic polymer inert to most chemicals and resistant to radiation. The formvar-based membranes are viable materials as support structures in micro- and macro-scale systems depending on thinness and porosity control. Tunable sub-micron thick porous membranes with 20%–65% porosity were synthesized by controlling the ratios of formvar, glycerol, and chloroform. This synthesis process does not require complex separation or handling methods and allows for the production of strong, thin, and porous formvar-based membranes. An expansive array of these membrane characterizations including chemical compatibility, mechanical responses, wettability, as well as the mathematical simulations as a function of porosity has been presented. The wide range of chemical compatibility allows for membrane applications in various environments, where other polymers would not be suitable. Our formvar-based membranes were found to have an elastic modulus of 7.8 GPa, a surface free energy of 50 mN m -1 and an average thickness of 125 nm. Stochastic model simulations indicate that formvar with the porosity of ~50% is the optimal membrane formulation, allowing the most material transfer across the membrane while also withstanding the highest simulated pressure loadings before tearing. Development of novel, resilient and versatile membranes with controlled porosity offers a wide range of exciting applications in the fields of nanoscience, microfluidics, and MEMS.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Nuclear Astrophysics through simulations of neutron star mergers using Monte‐Carlo neutrino radiation transport (DE-SC0020435 Final Technical Report)

Neutron star mergers are an important source of information for nuclear physics. Except for black holes, neutron stars are the densest macroscopic objects known to exist in the Universe. They provide us with a remarkable laboratory to study the poorly understood high-density states of matter, complementing the study of heavy nuclei performed by nuclear physics experiments on Earth. Collisions of neutron stars are of particular interest. They are among the most energetic events observable in the Universe, powering a broad range of signals across the electromagnetic spectrum as well as gravitational wave signals. These signals contain important information about the properties of extremely dense matter. Colliding neutron stars additionally eject large amounts of neutron-rich material into the surrounding interstellar medium -- material that then undergoes rapid neutron-capture (r-process) nucleosynthesis, the mechanism thought to be responsible for the production of about half of the heavy nuclei. In order to understand current and future observations of neutron star mergers, we need reliable models for the signals that they power. An important component in the construction of such models are numerical simulations of colliding neutron stars. These simulations are costly, running for multiple months on supercomputers, and require the inclusion of complex physics (general relativity, magnetohydrodynamics, neutrino physics, nuclear reactions). In this document, we describe the development of new methods for the treatment of neutrinos in merger simulations, as well as the first simulations capable of evolving the equations of neutrino radiation transport directly and their impact on our understanding of neutron star mergers and more broadly in nuclear astrophysics. We also discuss additional work performed in the study of nucleosynthesis and neutrino physics in neutron star mergers as part of Early Career Award DE-SC0020435.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2000

Turbine Airfoil With CMC Leading-Edge Concept Tested Under Simulated Gas Turbine Conditions

Silicon-based ceramics have been proposed as component materials for gas turbine engine hot-sections. When the Navy s Harrier fighter experienced engine (Pegasus F402) failure because of leading-edge durability problems on the second-stage high-pressure turbine vane, the Office of Naval Research came to the NASA Glenn Research Center at Lewis Field for test support in evaluating a concept for eliminating the vane-edge degradation. The High Pressure Burner Rig (HPBR) was selected for testing since it could provide temperature, pressure, velocity, and combustion gas compositions that closely simulate the engine environment. The study focused on equipping the stationary metal airfoil (Pegasus F402) with a ceramic matrix composite (CMC) leading-edge insert and evaluating the feasibility and benefits of such a configuration. The test exposed the component, with and without the CMC insert, to the harsh engine environment in an unloaded condition, with cooling to provide temperature relief to the metal blade underneath. The insert was made using an AlliedSignal Composites, Inc., enhanced HiNicalon (Nippon Carbon Co. LTD., Yokohama, Japan) fiber-reinforced silicon carbide composite (SiC/SiC CMC) material fabricated via chemical vapor infiltration. This insert was 45-mils thick and occupied a recessed area in the leading edge and shroud of the vane. It was designed to be free floating with an end cap design. The HPBR tests provided a comparative evaluation of the temperature response and leading-edge durability and included cycling the airfoils between simulated idle, lift, and cruise flight conditions. In addition, the airfoils were aircooled, uniquely instrumented, and exposed to the exact set of internal and external conditions, which included gas temperatures in excess of 1370 C (2500 F). In addition to documenting the temperature response of the metal vane for comparison with the CMC, a demonstration of improved leading-edge durability was a primary goal. First, the metal vane was tested for a total of 150 cycles. Both the leading edge and trailing edge of the blade exhibited fatigue cracking and burn-through similar to the failures experienced in service by the F402 engine. Next, an airfoil, fitted with the ceramic leading edge insert, was exposed for 200 cycles. The temperature response of those HPBR cycles indicated a reduced internal metal temperature, by as much as 600 F at the midspan location for the same surface temperature (2100 F). After testing, the composite insert appeared intact, with no signs of failure on either the vane s leading or trailing edge. Only a slight oxide scale, as would be expected, was noted on the insert. Overall, the CMC insert performed similarly to a thick thermal barrier coating. With a small air gap between the metal and the SiC/SiC leading edge, heat transfer from the CMC to the metal alloy was low, effectively lowering the temperatures. The insert's performance has proven that an uncooled CMC can be engineered and designed to withstand the thermal up-shock experienced during the severe lift conditions in the Pegasus engine. The design of the leading-edge insert, which minimized thermal stresses in the SiC/SiC CMC, showed that the CMC/metal assembly can be engineered to be a functioning component.

Robinson, R. Craig↗

DOE OSTI2021

A Continuum Dislocation Dynamics Crystal Plasticity Approach to Irradiated Body-Centered Cubic α-Iron

Radiation-induced embrittlement of reactor pressure vessel (RPV) steels can potentially limit the operating life of nuclear power plants. Over extended exposure to radiation doses, these body-centered cubic (BCC) irons demonstrate irradiation damage. Here, we present a continuum dislocation density (CDD) crystal plasticity model to capture the interaction among dislocations and self-interstitial atom (SIA) loops in α-iron. We demonstrate the importance of modeling cross slip using a combined stochastic Monte Carlo approach and the role of slip system strength anisotropy in capturing stochastic cross slip interactions. Through these captured interactions, the CDD crystal plasticity model can capture both the stress response and the physical evolution of dislocations on different slip system planes. Single-crystal verification experiments are used to calibrate the CDD crystal plasticity model, and a set of simplified polycrystalline simulations demonstrates the model’s ability to capture the stress response from tensile experiments on α-iron.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning

One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipulation tends to increase the computational load imposed on existing simulation tools employed in AM. The goal of the present work is to construct a fast and accurate reduced-order model (ROM) for an AM model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, ultimately reducing the time/cost of AM control and optimization processes. Our adoption of the operator learning (OL) approach enabled us to learn a family of differential equations produced by altering process variables in the laser’s Gaussian point heat source. More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses. Furthermore, we benchmarked the performance of these OL methods against a conventional deep neural network (DNN)-based ROM. Ultimately, we found that OL methods offer comparable performance and, in terms of accuracy and generalizability, even outperform DNN at predicting scalar model responses. The DNN-based ROM afforded the fastest training time. Furthermore, all the ROMs were faster than the original MOOSE model yet still provided accurate predictions. FNO had a smaller mean prediction error than DeepONet, with a larger variance for time-dependent responses. Unlike DNN, both FNO and DeepONet were able to simulate time series data without the need for dimensionality reduction techniques. Finally, the present work can help facilitate the AM optimization process by enabling faster execution of simulation tools while still preserving evaluation accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2016

WE-FG-207B-02: Material Reconstruction for Spectral Computed Tomography with Detector Response Function

Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelity based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification

This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.

36 MATERIALS SCIENCE↗