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The specific activities summarized include: verification experiments (base program); thermomechanical cycling model; multiaxial stress state model; cumulative loading model; screening of potential environmental and protective coating models; and environmental attack model.
The objectives of this program are to determine the predominant modes of degradation of a plasma sprayed thermal barrier coating system, and then to develop and verify life prediction models accounting for these degradation modes. The program is divided into two phases, each consisting of several tasks. The work in Phase 1 is aimed at identifying the relative importance of the various failure modes, and developing and verifying life prediction model(s) for the predominant model for a thermal barrier coating system. Two possible predominant failure mechanisms being evaluated are bond coat oxidation and bond coat creep. The work in Phase 2 will develop design-capable, causal, life prediction models for thermomechanical and thermochemical failure modes, and for the exceptional conditions of foreign object damage and erosion.
The governing differential equations are developed to model the thermomechanical behavior of chemically decomposing, polymeric materials. These equations account for thermal and gaseous diffusion through a poroelastic, transversely isotropic solid. The Bubnov-Galerkin finite element method is applied to the governing equations to cast the coupled set into a single matrix equation. A method for solving these equations simultaneously at each time step is discussed.
The optimum performance design of composite microstructures is discussed. The forces driving progress in fiber composites are examined, and recent developments in the mechanics of laminated composites are surveyed, emphasizing thick laminates, hygrothermal effects, and thermal transient effects. The strength of continuous-fiber composites is discussed, presenting analyses of local load redistribution due to fiber breakages and treatments of statistical tensile strength theories. Modes of failure of laminated composites are examined. Elastic, physical, and viscoelastic properties as well as the strength and fracture behavior of short-fiber composites are studied, and it is shown how the performance of composites can be controlled by selecting material systems and their geometric distributions. 2D textile structural composites based on woven, knitted, and braided preforms are considered, and techniques for analyzing and modeling the thermomechanical behavior of 2D textile composites are presented. Recent developments in the processing of 3D textile preforms are introduced and the processing-microstructure relationship is demonstrated. Finite elastic deformation of flexible composites is addressed.
The present work aims to derive a set of thermomechanical relaxation rate parameters and chemical reaction rate coefficients relevant to future interplanetary missions. It also attempts to assess the impact of thermochemical nonequilibrium phenomena on radiative heating rates for the stagnation point of the Martian entry vehicle.
In order to understand and model the thermomechanical behavior of fiber-reinforced composites, stress-rupture, fast-fracture, and warm-up rupture studies were conducted on various advanced SiC and Al2O3-based fibers in the,temperature range from 20 to 1400 C in air as well as in inert environments. The measured stress-rupture, fast fracture, and warm-up rupture strengths were correlated into a single master time/temperature-dependent strength plot for each fiber type using thermal activation and slow crack growth theories. It is shown that these plots are useful for comparing and selecting fibers for CMC and MMC reinforcement and that, in comparison to stress rupture tests, the fast-fracture and warm-up tests can be used for rapid generation of these plots.
The global increase in air travel will require commercial vehicles to be more efficient than ever before. Advanced turbine hot section materials are a key technology required to keep fuel consumption and emission to a minimum. Ceramic matrix composites (CMCs) are the most promising material to revolutionize turbine hot section materials because of their excellent high‐temperature properties. Rapid surface recession due to volatilization by water vapor is the Achilles heel of CMCs. Environmental barrier coatings (EBCs), which protect CMCs from water vapor, is an enabling technology for CMCs. The first CMC component entered into service in 2016 in a commercial engine, and more CMC components are scheduled to follow within the next few years. One of the most difficult challenges to CMC components is EBC durability because failure of EBC leads to a rapid reduction in CMC component life. Novel EBC chemistries, creative EBC designs, and robust processes are required to meet EBC durability challenges. Engine-relevant testing, characterization, and lifing methods need to be developed to improve EBC reliability. The aim of this Special Issue is to present recent advances in EBC technology to address current EBC challenges.
An analytical approach is presented for the modeling of the thermomechanical interactions which occur in high speed sliding situations. These sliding contact problems which are characterized by active and interrelated thermal and mechanical phenomena could be called 'rub energetics' problems. Analytical models were developed to simulate two different rub situations: high energy braking of disk brakes and high speed rubs of gas path seals in turbine engines. The models proved to be particularly useful in predicting the severe temperatures and deformations near hot contact patches on the rubbing surfaces. The size of the hot patches is generally determined by normal load and the properties of the contacting materials. Temperatures at the contact patches can approach the melting point of the materials, especially at high sliding velocities. These high temperatures can lead to large amounts of near-surface deformation and high wear rates. Decreased contact temperatures can result from using materials with increased thermal conductivity and increased heat capacity or choosing mechanical properties (decreased stiffness, yield stress or coefficient of thermal expansion) which give larger hot spot size.
Geometry deformation due to thermal expansion influences neutron transport in many systems. Studying this phenomenon involves coupling models for neutronics, thermal hydraulics, and solid mechanics. To enable high fidelity modeling of these coupled physics, new capabilities were introduced in Cardinal, coupling OpenMC Monte Carlo particle transport models with MOOSE thermomechanical physics on unstructured moving-mesh geometries. In this work, we present a fully open-source capability leveraging on-the-fly mesh skinning to automatically regenerate OpenMC geometry, which allows multiphysics feedback from temperature, density, and geometry changes. The new capability is verified using an analytic benchmark slab problem, which couples S 2 neutron transport with thermal conduction, convective boundary conditions, Doppler-broadened cross sections, and nonlinear thermal expansion effects along the heated slab. Cardinal reproduces the analytic solutions for the neutron flux, heating, k eff , and temperature with demonstrated convergence in various error terms including mesh resolution and cross section temperature library spacing. For the nominal benchmark conditions and with a fine mesh, maximum relative errors for neutron flux, temperature, and heating are lower than 1%, while errors in integral quantities such as k eff and slab length are within 1 pcm and 48 µm, respectively. This work (i) presents a new numerical approach to thermomechanics coupling with OpenMC models, (ii) is the first (to our knowledge) to utilize a mechanical partial differential equation (PDE) solution to solve the (Griesheimer and Kooreman, 2022) analytic benchmark, and (iii) develops this verified capability within an open-source package.
This report describes the development of a preliminary inelastic constitutive model for the thermomechanical behavior of Alloy 800H. The objective is to develop a model suitable for incorporating into Nonmandatory Appendix Z to Section III, Division 5 of the ASME Boiler & Pressure Vessel Code, which provides guidance and reference constitutive models for the ASME design by inelastic analysis rules for Class A components. The report describes the process of collecting experimental data, developing a mathematical form for the model, and training the model against the test data. The initial version of the model captures most of the relevant material deformation mechanisms, including dynamic strain aging effects. However, further development of the model form will be required to develop a final model suitable for ASME use.
Using a partitioned-energy thermodynamic framework which assigns energy to that of atomic configurational stored energy of cold work and kinetic-vibrational, in this study we derive an important constraint on the Taylor-Quinney coefficient, which quantifies the fraction of plastic work that is converted into heat during plastic deformation. Associated with the two energy contributions are two separate temperatures – the ordinary temperature for the thermal energy and the effective temperature for the configurational energy. We show that the Taylor-Quinney coefficient is a function of the thermodynamically defined effective temperature that measures the atomic configurational disorder in the material. Finite-element analysis of recently published experiments on the aluminum alloy 6016-T4 [1], using the thermodynamic dislocation theory (TDT), shows good agreement between theory and experiment for both stress-strain behavior and temporal evolution of the temperature. The simulations include both conductive and convective thermal energy loss during the experiments, and significant thermal gradients exist within the simulation results. Computed values of the differential Taylor-Quinney coefficient are also presented and suggest a value which differs between materials and increases with increasing strain.
The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.
The present paper describes a transient translating elastoplastic thermomechanical finite element model to study two-dimensional frictional rolling contact. Frictional two-dimensional contact is simulated by repeatedly translating a nonuniform thermomechanical distribution across the surface of an elastoplastic half space. The half space is represented by a two-dimensional finite element mesh with appropriate boundaries. Calculations are for an elastic-perfectly plastic material and the selected thermophysical properties are assumed to be temperature independent. The paper presents temperature variations, stress and plastic strain distributions and deformations. Residual tensile stresses are observed. The magnitude and depth of these stresses depends on (1) the temperature gradients and (2) the magnitudes of the normal and tangential tractions.
The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.
In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.
Shape memory alloys (SMAs) have enormous potential for a wide variety of applications. A large body of work exists on the characterization of the microstructure and stress-strain behavior of these alloys, Nitinol (NiTi) in particular. However, many attributes of these materials are yet to be fully understood. Previous work at NASA Langley Research Center (LaRC) has included fabrication of hybrid composite specimens with embedded Nitinol actuators and modeling of their thermomechanical behavior. An intensive characterization effort has been undertaken to facilitate fundamental understanding of this alloy and to promote implementation of Nitinol in aerospace applications. Previous work revealed attributes of the Nitinol ribbon that were not easily rationalized with existing data in the literature. In particular, tensile behavior at ambient temperature showed significant dependence on the thermomechanical history prior to testing. The present work is focused on characterizing differences in the microstructure of Nitinol ribbons exposed to four different thermomechanical histories and correlation of the microstructure with tensile properties. Differential scanning calorimetry (DSC) and x-ray diffraction (XRD) analysis were employed to rationalize the microstructures present after exposure to various thermomechanical histories. Three of the Nitinol ribbon conditions were reversible upon heating (in the DSC) through the reverse transformation temperature (A(sub f) to transform the microstructure to austenite. However, the prior thermomechanical conditioning for the Nitinol ribbon that reflected the entire fabrication procedure (4% thermal cycle condition) was found to have an irreversible effect on the microstructure, as it remained unchanged after repeated complete thermal cycles. Tensile tests were conducted to determine the effect of prior thermomechancal conditioning on both the tensile behavior of the Nitinol ribbons and the stress state of the microstructure. The stress-strain behavior of the Nitinol actuators appears to be governed by the interplay between two major variables: namely, microstructural constituents such as the R-phase and the martensite; and the stress state of these constituents (whether twinned with low residual stresses, or detwinned with high residual stresses). The most significant difference in the stress-strain behavior of the four conditions, the critical stress required to achieve an initial stress plateau, was found to depend on both the amount and stress state (twinned or detwinned) of R-phase present in the initial microstructure. Thus, the effect of prior thermomechanical processing is critical to the resulting tensile behavior of the Nitinol actuator. For numerical modeling inputs one must take into account the entire fabrication process on the Nitinol actuator.
This work investigates the effects of model parameters on thermomechanical simulations of a metal additive manufacturing process. The first half of this work explores the sensitivity and effects of the two porosity parameters used in the evolving constitutive model of the simulation. Varying the two parameters of the model show that for the simulations conducted here, the linear coefficient drives the predicted residual stress results while the constant term has little impact. The second half of the work considers the size, order, and the number of element layers in the finite element mesh. The stress distribution plots show that second-order elements along with a dense mesh marginally improve mesh convergence at a significant cost.