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DOE OSTI2023

Failure analysis of nuclear transient-tested UN tristructural isotropic fuel particles in a 3D printed SiC matrix

Fully ceramic microencapsulated fuel elements containing UN tristructural isotropic (TRISO) fuel particles within a 3D printed SiC matrix were subjected to transient testing with varying energy depositions. Detailed post-irradiation examinations were performed, including leaching in hot HNO3 and post-leaching X-ray computed tomography, to quantify the percentage of failed TRISO particles and crack propagation within the particles and surrounding fuel matrix. In parallel, detailed finite element analyses were performed for comparison with experimental findings and to better evaluate transient failure modes. The lowest transient energy deposition—which still exceeded bounding values for high-temperature gas-cooled reactor applications—resulted in no detectable TRISO particle failures or matrix cracking, which was consistent with the simulations. Simulations of the higher-energy transients for which significant TRISO particle failure was expected were generally able to reproduce the transient temperatures and matrix cracking. Thus, the TRISO particle failures were explained based on the effects of local SiC matrix thickness and porosity. Results generally confirmed the high strength of the additively manufactured SiC matrix but also affirmed the need for a modified UN TRISO architecture to prevent SiC matrix cracks from propagating through TRISO layers. This unique failure mode has not historically been considered for TRISO fuels contained in weaker graphite matrices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2004

Subsurface Stress Fields in FCC Single Crystal Anisotropic Contacts

Single crystal superalloy turbine blades used in high pressure turbomachinery are subject to conditions of high temperature, triaxial steady and alternating stresses, fretting stresses in the blade attachment and damper contact locations, and exposure to high-pressure hydrogen. The blades are also subjected to extreme variations in temperature during start-up and shutdown transients. The most prevalent high cycle fatigue (HCF) failure modes observed in these blades during operation include crystallographic crack initiation/propagation on octahedral planes, and non-crystallographic initiation with crystallographic growth. Numerous cases of crack initiation and crack propagation at the blade leading edge tip, blade attachment regions, and damper contact locations have been documented. Understanding crack initiation/propagation under mixed-mode loading conditions is critical for establishing a systematic procedure for evaluating HCF life of single crystal turbine blades. This paper presents analytical and numerical techniques for evaluating two and three dimensional subsurface stress fields in anisotropic contacts. The subsurface stress results are required for evaluating contact fatigue life at damper contacts and dovetail attachment regions in single crystal nickel-base superalloy turbine blades. An analytical procedure is presented for evaluating the subsurface stresses in the elastic half-space, based on the adaptation of a stress function method outlined by Lekhnitskii. Numerical results are presented for cylindrical and spherical anisotropic contacts, using finite element analysis (FEA). Effects of crystal orientation on stress response and fatigue life are examined. Obtaining accurate subsurface stress results for anisotropic single crystal contact problems require extremely refined three-dimensional (3-D) finite element grids, especially in the edge of contact region. Obtaining resolved shear stresses (RSS) on the principal slip planes also involves considerable post-processing work. For these reasons it is very advantageous to develop analytical solution schemes for subsurface stresses, whenever possible.

Arakere, Nagaraj K.↗

NASA NTRS2005

NASA Structural Analysis Report on the American Airlines Flight 587 Accident - Local Analysis of the Right Rear Lug

A detailed finite element analysis of the right rear lug of the American Airlines Flight 587 - Airbus A300-600R was performed as part of the National Transportation Safety Board s failure investigation of the accident that occurred on November 12, 2001. The loads experienced by the right rear lug are evaluated using global models of the vertical tail, local models near the right rear lug, and a global-local analysis procedure. The right rear lug was analyzed using two modeling approaches. In the first approach, solid-shell type modeling is used, and in the second approach, layered-shell type modeling is used. The solid-shell and the layered-shell modeling approaches were used in progressive failure analyses (PFA) to determine the load, mode, and location of failure in the right rear lug under loading representative of an Airbus certification test conducted in 1985 (the 1985-certification test). Both analyses were in excellent agreement with each other on the predicted failure loads, failure mode, and location of failure. The solid-shell type modeling was then used to analyze both a subcomponent test conducted by Airbus in 2003 (the 2003-subcomponent test) and the accident condition. Excellent agreement was observed between the analyses and the observed failures in both cases. From the analyses conducted and presented in this paper, the following conclusions were drawn. The moment, Mx (moment about the fuselage longitudinal axis), has significant effect on the failure load of the lugs. Higher absolute values of Mx give lower failure loads. The predicted load, mode, and location of the failure of the 1985-certification test, 2003-subcomponent test, and the accident condition are in very good agreement. This agreement suggests that the 1985-certification and 2003- subcomponent tests represent the accident condition accurately. The failure mode of the right rear lug for the 1985-certification test, 2003-subcomponent test, and the accident load case is identified as a cleavage-type failure. For the accident case, the predicted failure load for the right rear lug from the PFA is greater than 1.98 times the limit load of the lugs. I.

Raju, Ivatury S↗

NASA NTRS2010

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗

NASA NTRS2012

Design and Characterization of Thin Stainless Steel Burst Disks for Increasing Two-Stage Light Gas Launcher Efficiency

Laser etched 300 series Stainless Steel Burst Disks (SSBD) ranging between 0.178 mm (0.007-in.) and 0.508mm (0.020-in.) thick were designed for use in a 17-caliber two-stage light gas launcher. First, a disk manufacturing method was selected using a combination of wire electrical discharge machining (EDM) to form the blank disks and laser etching to define the pedaling fracture pattern. Second, a replaceable insert was designed to go between the SSDB and the barrel. This insert reduced the stress concentration between the SSBD and the barrel, providing a place for the petals of the SSDB to open, and protecting the rifling on the inside of the barrel. Thereafter, a design of experiments was implemented to test and characterize the burst characteristics of SSBDs. Extensive hydrostatic burst testing of the SSBDs was performed to complete the design of experiments study with one-hundred and seven burst tests. The experiment simultaneously tested the effects of the following: two SSBD material states (full hard, annealed); five SSBD thicknesses 0.178, 0.254, 0.305, 0.381 mm (0.007, 0.010, 0.012, 0.015, 0.020-in.); two grain directions relative); number of times the laser etch pattern was repeated (varies between 5-200 times); two heat sink configurations (with and without heat sink); and, two barrel configurations (with and without insert). These tests resulted in the quantification of the relationship between SSBD thickness, laser etch parameters, and desired burst pressure. Of the factors investigated only thickness and number of laser etches were needed to develop a mathematical relationship predicting hydrostatic burst pressure of disks using the same barrel configuration. The fracture surfaces of two representative SSBD bursts were then investigated with a scanning electron microscope, one burst hydrostatically in a fixture and another dynamically in the launcher. The fracture analysis verified that both burst conditions resulted in a ductile overload failure indicated by transgranular microvoid coalescence, non-fragmenting rupture and mixed tensile and shear failure modes, regardless of the material states tested. More testing is underway to determine the relationship between SSBD burst pressure and projectile velocity.

Tylka, Jonathan M.↗

NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗

NASA NTRSDate not supplied

arcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

machine learning↗

NASA NTRS2014

Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset

Benchmarking of prognostic algorithms has been challenging due to limited availability of common datasets suitable for prognostics. In an attempt to alleviate this problem several benchmarking datasets have been collected by NASA's prognostic center of excellence and made available to the Prognostics and Health Management (PHM) community to allow evaluation and comparison of prognostics algorithms. Among those datasets are five C-MAPSS datasets that have been extremely popular due to their unique characteristics making them suitable for prognostics. The C-MAPSS datasets pose several challenges that have been tackled by different methods in the PHM literature. In particular, management of high variability due to sensor noise, effects of operating conditions, and presence of multiple simultaneous fault modes are some factors that have great impact on the generalization capabilities of prognostics algorithms. More than 70 publications have used the C-MAPSS datasets for developing data-driven prognostic algorithms. The C-MAPSS datasets are also shown to be well-suited for development of new machine learning and pattern recognition tools for several key preprocessing steps such as feature extraction and selection, failure mode assessment, operating conditions assessment, health status estimation, uncertainty management, and prognostics performance evaluation. This paper summarizes a comprehensive literature review of publications using C-MAPSS datasets and provides guidelines and references to further usage of these datasets in a manner that allows clear and consistent comparison between different approaches.

Uncertainty↗

NASA NTRSDate not supplied

Investigation of the Effect of Etch Pits on the Material Properties of Carbon Fiber Structures

It is well known that etch pits are formed on carbon surfaces during their consumption in reactive gas environments such as during ablation of carbon-based thermal protection system (TPS) materials. These pits start out from atomic defects on the carbon surface, grow in size and then ultimately lead to the complete removal of the solid carbon material. However, the effect of such etch pits on the material properties of carbon ablators such as FiberForm are poorly understood, as the maximum size of pits are on the order of microns in size, which makes them hard to observe experimentally. Hence, we have developed a module within the Porous Microstructure Analysis code PuMA that can generate etch pits on an arbitrary material surface, with a prescribed distribution of pit size and density. We use this newly developed module to calculate material properties of FiberForm, which is the base material for one of the most commonly used TPS materials - Phenolic Impregnated Carbon Ablator (PICA). The detailed microstructure of FiberForm in PuMA will either be generated synthetically or obtained from X-ray microtomography. Our simulations show that material properties such as the thermal conductivity and tortuosity decrease with increasing degree of pitting. This will be helpful to more accurately predict the degradation of carbon-based TPS during ablation, and furthermore may allow us to identify previously unknown TPS failure modes due to pitting.

PuMA↗

DOE OSTI2021

DEM analysis of the effect of interface transition zone on dynamic splitting tensile behavior of high-strength concrete based on multi-phase model

Highlights: • Crushable aggregates with the real geometry shape are generated by using clump-cluster method. • Flat-Joint Model is adopted as the constitutive law. • The tensile strength is almost not affected by ITZ strength when its strength exceeds 0.8 times that of mortar. • A modified formula that can reflect the functional relationship between the ITZ strength and the TDIF is proposed. The tensile strength is one of the main parameters in the design of concrete structures and has an important influence on the cracking performance and durability of concrete materials. As the weak region in concrete, the strength of the interface transition zone (ITZ) directly affects the dynamic mechanical response of concrete. Meanwhile, considering that the tensile performance of concrete is far weaker than its compressive performance, the study of the strength of ITZ is of great significance to the dynamic tensile fracture characteristics and mechanical properties of concrete. In this paper, a method combining 3D scanning technology and Clump-Cluster was proposed to generate a real geometry shape model of crushable aggregate. On this basis, the 3D discrete element model (DEM) of high-strength concrete was constructed using the Flat-Joint Model (FJM). The effects of the ITZ strength on the failure mode, number of microcracks, tensile strength and strain rate effect of high-strength concrete under strain rates from 0.01/s to 100/s were studied by splitting tensile test. The simulation results indicate that the number of microcracks generated decreases with the increase of ITZ strength, and the proportion of ITZ cracks decreases obviously. When the ITZ strength exceeds the critical value of 0.8 times that of mortar, the tensile strength is almost not affected by ITZ strength. In addition, based on the numerical simulation results, a modified formula that can reflect the functional relationship between the ITZ strength and the dynamic increasing factor of the concrete tensile strength (TDIF) is proposed, and the rationality of the TDIF modified formula is verified.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2002

Probabilistic Design Methodology and its Application to the Design of an Umbilical Retract Mechanism

A lot has been learned from past experience with structural and machine element failures. The understanding of failure modes and the application of an appropriate design analysis method can lead to improved structural and machine element safety as well as serviceability. To apply Probabilistic Design Methodology (PDM), all uncertainties are modeled as random variables with selected distribution types, means, and standard deviations. It is quite difficult to achieve a robust design without considering the randomness of the design parameters which is the case in the use of the Deterministic Design Approach. The US Navy has a fleet of submarine-launched ballistic missiles. An umbilical plug joins the missile to the submarine in order to provide electrical and cooling water connections. As the missile leaves the submarine, an umbilical retract mechanism retracts the umbilical plug clear of the advancing missile after disengagement during launch and retrains the plug in the retracted position. The design of the current retract mechanism in use was based on the deterministic approach which puts emphasis on factor of safety. A new umbilical retract mechanism that is simpler in design, lighter in weight, more reliable, easier to adjust, and more cost effective has become desirable since this will increase the performance and efficiency of the system. This paper reports on a recent project performed at Tennessee State University for the US Navy that involved the application of PDM to the design of an umbilical retract mechanism. This paper demonstrates how the use of PDM lead to the minimization of weight and cost, and the maximization of reliability and performance.

Onyebueke, Landon↗

NASA NTRS2006

Ka-Band Wide-Bandgap Solid-State Power Amplifier: Prototype Combiner Spurious Mode Suppression and Power Constraints

Results of prototype hardware activities related to a 120-W, 32-GHz (Ka-band) solid-state power amplifier (SSPA) architecture study are presented. Spurious mode suppression and the power-handling capability of a prototype 24-way radial combiner and a prototype 2-way septum binary combiner were investigated. Experimental data indicate that a commercial absorptive filter, designed to pass the circular TE01 mode, effectively suppressed the higher-order modes generated by a narrowband, flower-petal-type mode transducer. However, the same filter was not effective in suppressing higher-order modes generated by the broadband Marie mode transducer that is used in the prototype waveguide radial combiner. Should greater filtering be required by a particular SSPA application, a broadband mode filter that can suppress specifically those higher-order modes that are generated by the Marie transducer will need to be developed. A back-to-back configuration of the prototype radial combiner was tested with drive power up to approximately 50 W. No anomalous behavior was observed. Power measurements of the septum combiner indicate that up to 10-W radio frequency (RF) can be dissipated in the integrated resistive element before a permanent performance shift is observed. Thus, a given adder (a single-stage, 2-way combiner) can safely combine two 20-W sources, and the adder will not be damaged in the event of a source failure. This result is used to calculate the maximum source power that can be safely combined as a function of the number of sources combined and the number of source failures allowed in a multi-stage combiner. The analysis shows that SSPA power >140 W can be generated by power combining 16 sources producing 10 W each. In this configuration, up to three sources could fail with the guarantee that the combiner would not be damaged. Finally, a modified prototype septum combiner design was verified. The improved design reduced the assembly time from over 2 hours to about 15 minutes per adder.

Khan, P.↗

DOE OSTI2022

Deformation and Fracture Behaviors of Cylindrical Battery Shell During Thermal Runaway

Thermal runaway is one of the catastrophic failure modes of lithium-ion cells. During thermal runaway in cylindrical cells, sidewall shell rupture has been identified as a contributing factor for thermal runaway propagation in battery packs. Herein, the deformation and fracture behaviors of the battery shell during thermal runaway are investigated based on in-situ and ex-situ characterization as well as physics-based modeling. The deformation and fracture modes of the battery shell with/without Carbon Fiber Reinforced Polymer (CFRP) sleeves are identified. In the simulation, the strain introduced by thermal expansion of the system is considered, as well as the thermal and strain rate effects on the plastic stage. The final cell shell modeling is validated by cell thermal runaway tests. Results reveal the quantitative relation between shell deformation behaviors and the pressure and temperature distribution. Both the experiment and model demonstrate the effectiveness of adding a tight-fitting CFRP sleeve around the cell in limiting the side-wall rupture of the shell. The use of CFRP tubes introduces a novel phenomenon in the context of uneven temperature distribution. Results shed light on the mechanistic analysis of a cell side-wall rupture during thermal runaway and provide essential guidance for the next-generation safe battery design.

battery casing↗

DOE OSTI2022

Multiphysics modeling of SOFC performance degradation caused by interface delamination and active layer cracking

In solid oxide device operation, delamination and cracking cause more catastrophic damage to cell life than other degradation mechanisms, leading to more rapid cell failure. The electrochemical performance degradation caused by electrode/electrolyte interface delamination and active layer cracking were investigated through in-house developed three-dimensional multiphysics simulations. Here the multiphysics simulations, fully calibrated against experimental datasets for button cells in a previous study, were extended to quantitatively investigate the effects of electrode/electrolyte interface delamination and active layer cracking. The simulated polarization curves and impedance behavior with various levels of delamination and cracking provided insights of the performance degradation. Furthermore, the local current distributions within the cell were analyzed for three different operating modes: constant voltage, constant current, and constant power. Finally, a practical strategy was proposed to mitigate the performance degradation in the realistic cell operations, extending overall cell lifetime.

08 HYDROGEN↗

NASA NTRSDate not supplied

Investigation of the effect of etch pits on the material properties of carbon fiber structures

It is well known that etch pits are formed on carbon surfaces during their consumption in reactive gas environments such as during ablation of carbon-based thermal protection system (TPS) materials. These pits start out from atomic defects on the carbon surface, grow in size and then ultimately lead to the complete removal of the solid carbon material [1, 2]. However, the effect of such etch pits on the material properties of carbon ablators such as FiberForm are poorly understood, as the maximum size of pits are on the order of microns in size, which makes them hard to observe experimentally. Hence, we have developed a module within the Porous Microstructure Analysis code PuMA [3] that can generate etch pits on an arbitrary material surface, with a prescribed distribution of pit size and density. Figure 1 shows a FiberForm sample with artificially generated pits of varying radii and pit density. We use this newly developed module to calculate material properties of FiberForm, which is the base material for one of the most commonly used TPS materials - Phenolic Impregnated Carbon Ablator (PICA). The detailed microstructure of FiberForm in PuMA will either be generated synthetically or obtained from X-ray microtomography [4]. Our simulations show that material properties such as the thermal conductivity and tortuosity decrease with increasing degree of pitting. This will be helpful to more accurately predict the degradation of carbon-based TPS during ablation, and furthermore may allow us to identify previously unknown TPS failure modes due to pitting.

PuMA↗

DOE OSTI2020

Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Abstract There is a lack of understanding on the root cause of cracking of photovoltaic (PV) backsheets due to the challenge of multilayer characterization and the complicated failure modes at the submodule level. In this work, the in‐depth degradation mapping of field‐exposed polyamide‐based (PA‐based) PV module backsheets was studied, with the major focus on the identification of underlying drivers for the through cracking (in between the solar cells). PV modules were retrieved from five different locations, comprising a variety of climates, including humid subtropical, hot‐summer Mediterranean, tropical savanna climate, and hot arid. A suite of microscale cross‐sectional characterizations, including chemical changes, fluorescence intensity, and modulus as a function of distance from the air surface of the backsheet, was performed. Results showed more advanced signs of degradation of the inner layer than the outer layer in the cracking region. Increases in the modulus were identified as the major indicator for the cracking. Moreover, a rudimentary test by immersion in acetic acid, which forms during photodegradation of the ethylene‐vinyl acetate copolymer (EVA) encapsulant, showed the first‐time direct evidence that acetic acid can largely accelerate the chemical degradation and facilitate the cracking of PA inner layer. This study suggests that the field cracking of PA‐based backsheet can be attributed to the combined effects of chemical degradation and physical reorganization (chemi‐crystallization) under cyclic thermomechanical stresses. Therefore, it is important to consider effects of local microclimates and interlayer infection to understand the heterogeneous nature of backsheet failures.

Lyu, Yadong↗

NASA NTRS2003

Simulating Fatigue Crack Growth in Spiral Bevel Pinion

This project investigates computational modeling of fatigue crack growth in spiral bevel gears. Current work is a continuation of the previous efforts made to use the Boundary Element Method (BEM) to simulate tooth-bending fatigue failure in spiral bevel gears. This report summarizes new results predicting crack trajectory and fatigue life for a spiral bevel pinion using the Finite Element Method (FEM). Predicting crack trajectories is important in determining the failure mode of a gear. Cracks propagating through the rim may result in catastrophic failure, whereas the gear may remain intact if one tooth fails and this may allow for early detection of failure. Being able to predict crack trajectories is insightful for the designer. However, predicting growth of three-dimensional arbitrary cracks is complicated due to the difficulty of creating three-dimensional models, the computing power required, and absence of closed- form solutions of the problem. Another focus of this project was performing three-dimensional contact analysis of a spiral bevel gear set incorporating cracks. These analyses were significant in determining the influence of change of tooth flexibility due to crack growth on the magnitude and location of contact loads. This is an important concern since change in contact loads might lead to differences in SIFs and therefore result in alteration of the crack trajectory. Contact analyses performed in this report showed the expected trend of decreasing tooth loads carried by the cracked tooth with increasing crack length. Decrease in tooth loads lead to differences between SIFs extracted from finite element contact analysis and finite element analysis with Hertz contact loads. This effect became more pronounced as the crack grew.

Ural, Ani↗