Thermokinetic Modeling in an Aerospace Research and Production Environment
Thermokinetic modeling has proven its value for measuring thermal response and reaction rates of a wide variety of aerospace materials.
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Thermokinetic modeling has proven its value for measuring thermal response and reaction rates of a wide variety of aerospace materials.
Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.
This research investigates the response of a fiberless 13 layer hot isostatically pressed Ti-15-3 laminate to creep, constant strain rate, and cyclic constant strain rate loading at temperatures ranging from 482C to 649C. Creep stresses from 48 to 260 MPa and strain rates of .0001 to .01 m/m/sec were used. Material parameters for three unified constitutive models (Bodner-Partom, Miller, and Walker models) were determined for Ti-15-3 from the experimental data. Each of the three models was subsequently incorporated into a rule of mixtures and evaluated for accuracy and ease of use in predicting the thermoviscoplastic response of unidirectional metal matrix composite laminates (both 0 and 90). The laminates were comprised of a Ti-15-3 matrix with 29 volume percent SCS6 fibers. The predicted values were compared to experimentally determined creep and constant strain rate data. It was found that all three models predicted the viscoplastic response of the 0 specimens reasonably well, but seriously underestimated the viscoplastic response of the 90 specimens. It is believed that this discrepancy is due to compliant and/or weak fiber-matrix interphase. In general, it was found that of the three models studied, the Bodner-Partom model was easiest to implement, primarily because this model does not require the use of cyclic constant strain rate tests to determine the material parameters involved. However, the version of the Bodner-Partom model used in this study does not include back stress as an internal state variable, and hence may not be suitable for use with materials which exhibit a pronounced Baushinger effect. The back stress is accounted for in both the Walker and Miller models; determination of the material parameters associated with the Walker model was somewhat easier than in the Miller model.
A project is underway to develop a consistent set of material properties, impact test data, and failure analysis for a variety of metallic aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the Federal Aviation Administration William J. Hughes Technical Center. Particular features of this set of data are that all material property and impact test data are obtained using traceable material, the test methods and procedures are extensively documented, and all the raw data are available. Four parallel efforts are currently underway: measurement of material deformation and failure response over a wide range of strain rates and temperatures, failure analysis of material property specimens and impact test articles, development of improved numerical modeling techniques for deformation and failure, and impact testing of flat panels and substructures for model validation. This report describes impact testing performed on 410 stainless steel sheet and plate samples of different thicknesses with two different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.
Electrical responses in the vicinity of energized steel-cased well sources offer significant potential for monitoring induced fractures. However, the high complexity of well-fracture-host models spanning multiple length scales compels analysts to simplify their numerical models due to enormous computational costs. This consequently limits our understanding regarding monitoring capabilities and the limitations of electrical measurements on realistic hydraulically fracturing systems. In this paper, we use the hierarchical finite element approach to construct geoelectric models in which geometrically complex fractures and steel-cased wells are discretely represented in 3D conducting media without sacrificing the model realism and computation efficiency. We have discovered systematic numerical analyses of the electrical responses to evaluate the influences of borehole material conductivity and the source type as well as the effects of well geometry, conductivity contrast, source location, fracture growth, and fracture propagation. Furthermore, the numerical results indicate that the borehole material property has a strong control on the electrical potentials along the production and monitoring wells. The monopole source located at a steel-cased well results in a current density distribution that decays away from the source location throughout the well length, whereas the dipole source produces a current density that dominates mainly along the dipole length. Moreover, the conductivity contrast between the fractures and host does not change the overall pattern of the electrical potentials but varies its amplitude. The fracture models near different well systems indicate that the well geometry controls the entire distribution of potentials, while the characteristics of the voltage difference profiles along the wells before and after fracturing are insensitive to the well geometry and the well in which the source is located. Further, the hydraulic-fracturing models indicate that the voltage differences along the production well before and after fracturing have strong sensitivity to fracture growth and fracture set propagation.
The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.
Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive that has successfully been used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also used to bond instrumentation plugs such as temperature and pressure sensors into the heatshields. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Heating RTV has also shown swelling, or intumescence, which can pose unique problems that lead to roughness induced boundary-layer transition, surface oxide formation and contamination of heat shield sensors. Therefore, it is crucial to understand and model the intumescence phenomenon of RTV. As data for RTV material properties is limited, the first step in modeling RTV is to collect material properties such as pyrolysis mass-loss, microstructure change, virgin and char porosity, etc. which was performed in our initial study. Additionally, thermomechanical properties such as Young’s modulus and Poisson ratio are required for modeling the intumescence of RTV, which were taken from literature and the coefficient of thermal expansion was collected using in-situ heating and Micro Computed Tomography (µ-CT) in previous studies. Finally, numerous other properties such as pyrolysis gas properties, virgin and char thermal conductivity and specific heat were compiled from previous experiments and literature into a material database that can be used for simulations. In Porous Material Analysis Toolbox based on OpenFOAM (PATO) [4], structural mechanics coupled with material response was used for simulating the intumescence of RTV as it is heated. However, since the permeability of the material is very low, the pyrolysis gas creates an internal pressure build-up as the material is being heated, significantly contributing to the deformation of the material. To correctly characterize this phenomenon, additional physics models were implemented into PATO's stress analysis solver, and results were compared with RTV dilatometry test data as a preliminary verification case. Future work will include experiments of RTV at the Plasmatron X facility and the in-situ heating cell with µ-CT, and improvement of simulation tools to more accurately model RTV intumescence.
Two sets of finite-rate gas-surface interaction model between air and the carbon surface are studied. The first set is an engineering model with one-way chemical reactions, and the second set is a more detailed model with two-way chemical reactions. These two proposed models intend to cover the carbon surface ablation conditions including the low temperature rate-controlled oxidation, the mid-temperature diffusion-controlled oxidation, and the high temperature sublimation. The prediction of carbon surface recession is achieved by coupling a material thermal response code and a Navier-Stokes flow code. The material thermal response code used in this study is the Two-dimensional Implicit Thermal-response and Ablation Program, which predicts charring material thermal response and shape change on hypersonic space vehicles. The flow code solves the reacting full Navier-Stokes equations using Data Parallel Line Relaxation method. Recession analyses of stagnation tests conducted in NASA Ames Research Center arc-jet facilities with heat fluxes ranging from 45 to 1100 wcm2 are performed and compared with data for model validation. The ablating material used in these arc-jet tests is Phenolic Impregnated Carbon Ablator. Additionally, computational predictions of surface recession and shape change are in good agreement with measurement for arc-jet conditions of Small Probe Reentry Investigation for Thermal Protection System Engineering.
Aging coal-fired power plants are retiring across the United States. Researchers at Pacific Northwest National Laboratory studied coal-fired power plant decommissioning business models to support program development for the Department of Energy’s Office of Energy Efficiency & Renewable Energy (EERE) to engage with communities affected by power plant retirement processes. Evaluating and reducing the impact on coal-dependent communities from phasing out coal production is a crucial piece of nationwide economic development and community-directed engagement in the clean energy future. This report describes the steps in the typical coal-fired power plant decommissioning process, including analysis of the following key factors: Drivers including policy and regulations, competition with other fuels, and corporate responsibility goals; Types of coal plant decommissioning including plant retirement without full decommissioning, repurposing with fuel switch, redeveloping to utilize existing transmission, and decommissioning and repurposing with other commercial activities; and, Costs of coal plant decommissioning, including variations across regulated and deregulated markets and the funding resources to support decommissioning activities. The details described in this report relied heavily on the availability of local news reports and communications regarding plant retirements, as the researchers identified a lack of formal literature surrounding business models for coal plant decommissioning and a need for a more robust source material collection. In addition, a lack of oversight entities responsible for decommissioning processes may have led to this shortfall of information. Future research regarding coal plant decommissioning can include quantitative studies on power plant retirement drivers, procedures, and costs, qualitative assessments on affects decommissioning has on surrounding communities, investors, and other stakeholders, and identifying best practices to engage community stakeholders in the decommissioning process.
Abstract The heterogeneous nature, local presence, and dynamic evolution of defects typically govern the ionic and electronic properties of a wide variety of functional materials. While the last 50 years have seen considerable efforts into development of new methods to identify the nature of defects in complex materials, such as the perovskite oxides, very little is known about defect dynamics and their influence on the functionality of a material. Here, the discovery of the intermittent behavior of point defects (oxygen vacancies) in oxide heterostructures employing X‐ray photon correlation spectroscopy is reported. Local fluctuations between two ordered phases in strained SrCoO x with different degrees of stability of the oxygen vacancies are observed. Ab‐initio‐informed phase‐field modeling reveals that fluctuations between the competing ordered phases are modulated by the oxygen ion/vacancy interaction energy and epitaxial strain. The results demonstrate how defect dynamics, evidenced by measurement and modeling of their temporal fluctuations, give rise to stochastic properties that now can be fully characterized using coherent X‐rays, coupled for the first time to multiscale modeling in functional complex oxide heterostructures. The study and its findings open new avenues for engineering the dynamical response of functional materials used in neuromorphic and electrochemical applications.
Polymer matrix composites are commonly used to fabricate energy-absorbing structures expected to experience impact loading. As such, a detailed understanding of the dynamic response of the constituent materials is necessary. Since the rate, temperature, and pressure dependence of carbon fiber reinforced polymer matrix composites are primarily manifestations of the rate, temperature, and pressure dependence of the polymer matrix, it is crucial that the constitutive behavior of the matrix be accurately characterized. In this work, an existing unified viscoplastic constitutive formulation is extended to ensure thermodynamic consistency and to more accurately account for the tension-compression asymmetry observed in the response of polymeric materials. A new plastic potential function is proposed, and elementary loading conditions are utilized to determine relations between model constants to ensure nonnegative plastic dissipation, a necessary thermodynamic requirement. Expressions for plastic Poisson’s ratios are derived and are bounded by enforcing nonnegative plastic dissipation. The model is calibrated against available experimental data from tests conducted over a range of strain rates, temperatures, and loading cases on a representative thermoset epoxy; good correlation between simulations and experimental data is obtained. Temperature rises due to the conversion of plastic work to heat are computed via the adiabatic heat energy equation. The viscoplastic polymer model is then used as a constitutive model in the generalized method of cells micromechanics theory to investigate the effects of matrix adiabatic heating on the high strain rate response of a unidirectional composite. The thermodynamic consistency of the model ensures plastic dissipation can only cause an increase in temperature. Simulation results indicate that significant thermal softening due to the conversion of plastic work to heat is observed in the composite for matrix dominated deformation modes.
This INFUSE 2023 project between UCLA and Commonwealth Fusion Systems used computer modeling to test whether tungsten materials can survive in CFS's ARC fusion reactor divertor. The team simulated plasma conditions and material responses, finding that tungsten-rhenium alloys resist grain growth better than pure tungsten, and that hydrogen buildup depends more on particle flux than temperature. The work helps CFS design durable plasma-facing components for their fusion power plant.
Accurately modeling fracture of ductile materials poses open challenges in the field of computational mechanics due to the multiphysics nature of their failure processes. Integrating the interplay between thermodynamics and damage into ductile fracture models is vital for predicting critical failure modes. Here, in this paper, we develop a versatile phase-field (PF) framework for modeling ductile fracture, taking into account finite-strain elasto-plasticity. The framework stems from a variational formulation of constitutive relations for generalized standard materials (GSMs), whose response is described by a Helmholtz free energy and a dissipation pseudo-potential. Its variational structure is based on a minimum principle for a functional that expresses the sum of power densities for reversible and irreversible processes. By minimizing this functional with a constraint on a von Mises yield function, we derive the evolution equation for the equivalent plastic strain and an associative flow rule. This constrained optimization problem is analytically solved for a wide class of thermo-viscoplasticity models. The key innovations of the current work include (i) a cubic plastic degradation function that accounts for a non-vanishing damage-dependent yield stress, (ii) closed-form expressions of the Helmholtz free energy and dissipation pseudo-potential for three thermo-viscoplasticity models, (iii) an extended Johnson–Cook plasticity model with a nonlinear hardening law, and (iv) a plastic work heat source that depends on the plastic degradation function and a variable Taylor–Quinney (TQ) coefficient. The capabilities of the proposed framework are tested with the aid of four ductile fracture problems, including the Sandia Fracture Challenge. In each of these problems, we examine the evolution of relevant field variables such as the PF order parameter, the equivalent plastic strain, the temperature, and the internal power dissipation density, in addition to the overall structural response quantified by the force–displacement curve. These numerical studies demonstrate that the proposed framework effectively represents ductile fracture, yielding computational results that exhibit good agreement with experimental data.
The thermochemical response of Coating 313 when exposed to a fuel fire environment was studied to provide a tool for predicting the reaction time. The existing Aerotherm Charring Material Thermal Response and Ablation (CMA) computer program was modified to treat swelling materials. The modified code is now designated Aerotherm Transient Response of Intumescing Materials (TRIM) code. In addition, thermophysical property data for Coating 313 were analyzed and reduced for use in the TRIM code. An input data sensitivity study was performed, and performance tests of Coating 313/steel substrate models were carried out. The end product is a reliable computational model, the TRIM code, which was thoroughly validated for Coating 313. The tasks reported include: generation of input data, development of swell model and implementation in TRIM code, sensitivity study, acquisition of experimental data, comparisons of predictions with data, and predictions with intermediate insulation.
We present a novel microcrack-damage theory for brittle solids under compression. Instead of using internal variables like zeroth, second or fourth rank damage tensors, the state of material damage is represented by an internal function that encapsulates the information of direction, density and size of microcracks. Just like other internal variables, the evolution of this state function must obey the second law of thermodynamics for arbitrary loading paths. This is done by casting the model in the framework of continuous hyperplasticity and enforcing a non-negative dissipation rate functional. The proposed framework offers predictions on the continuous evolution of microcrack density and the induced material anisotropy along with the macroscopic stress-strain curves. The use of continuous damage function grants the model significantly enhanced resolution in characterizing the direction-dependent response of cracked solids compared to classical models that are based on damage tensors. Two scenarios are considered in developing the theory, one assumes frictionless cracks and the other incorporates friction between crack surfaces. The results highlight that inelasticity, pressure dependence, and loading-unloading hysteresis exhibited by brittle solids are natural consequences of frictional microcracks. The proposed theory offers a generic and versatile framework to upscale micromechanical processes operating at individual crack scale to explain the macroscopic behavior of cracked solids.
The objectives of this project are to: (i) Gain fundamental understandings towards the microscopic damage mechanisms, as impacted by pertinent materials properties (e.g. stacking fault energy (SFE) and microstructure (e.g., grain size), leading to high-cycle fatigue (HCF) damage to AM Ni-based superalloy parts; (ii) Provide scientific insight into the effect of testing frequency on damage mechanisms and fatigue life of AM Ni-based superalloy parts under HCF regime, thereby establishing an appropriate correlation between accelerated testing and materials’ true service life; (iii) Devise an accurate, experimentally validated multiscale model across atomic, micro- and meso-scales, to predict the cyclic stress-strain responses and fatigue damage accumulation for AM Ni-based superalloys under various loading frequencies.
The three-year program of research had the following technical objectives: the development of probabilistic methods for micromechanics-based constitutive and failure models, application of the probabilistic methodology in the evaluation of various composite materials and simulation of expected uncertainties in unidirectional fiber composite properties, and influence of the uncertainties in composite properties on the structural response. The first year of research was devoted to the development of probabilistic methodology for micromechanics models. The second year of research focused on the evaluation of the Chamis-Hopkins constitutive model and Aboudi constitutive model using the methodology developed in the first year of research. The third year of research was devoted to the development of probabilistic finite element analysis procedures for laminated composite plate and shell structures.
Non-conservative processes play a fundamental role in plasticity and are behind important macroscopic phenomena such as creep, dynamic strain aging, loop raft formation, etc. In the most general case, vacancy-induced dislocation climb is the operating unit mechanism. While dislocation/vacancy interactions have been modeled in the literature using a variety of methods, the approaches developed rely on continuum descriptions of both the vacancy population and its fluxes. However, there are numerous situations in physics where point defect populations display heterogeneous concentrations and/or non-smooth kinetics. Here, a kinetic Monte Carlo (kMC) approach for modeling vacancy transport in response to arbitrary stress fields is used. Vacancies are treated as point particles and are coupled to the dislocation substructure representing a deformed material via an advection term defined by the local stress gradients. The stress fields and the dislocation substructure are evolved using a discrete dislocation dynamics (DDD) module. To extend the coupled model to the treatment of large systems, we have implemented it in the massively-parallel DDD code ParaDiS. To avoid numerical incompatibilities associated with merging deterministic (DDD) and stochastic (kMC) integration algorithms, we cast the entire elasto-plastic-diffusive problem within a single stochastic framework, taking advantage of a parallel kMC algorithm to evolve the system as a single event-driven process. The large-scale implementation enables the study of the evolution of a variety of dislocation-defect scenarios governed by non-conservative transport kinetics. After carrying out an exhaustive numerical and computational analysis of our parallel algorithm, we show results that emphasize situations where inhomogeneous vacancy dynamics are of relevance, and compare discrete kinetics to continuum solutions for several cases.