Static loading test methods to characterize the resistance against slow crack growth use surfactants to shorten testing times. In comparison, the cracked round bar test method uses cyclic loading but no accelerating media and/or temperatures. To allow for a comprehensive knowledge on the effect of media influence, this research investigates the effect of air as well as deionized water with and without surfactant on the crack growth performance of blow-molding polyethylene in cracked round bar experiments at various temperatures. As also seen in literature, first test results show a crack growth decelerating effect of surfactant in cyclic tests at an elevated temperature. Ongoing tests will show the temperature dependency of these effects.
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Keywords: Keynote
COMPUTATIONAL PREDICTIONS OF HYDROGEN ASSISTED FRACTURES [Keynote]
Hydrogen significantly reduces the ductility, toughness and fatigue crack growth resistance of metals, which leads to premature failures across many industrial sectors and compromises the role of hydrogen as energy carrier in the transition to a low carbon economy. This paper provides an overview of the efforts by the author and his collaborators in developing a computational framework capable of predicting hydrogen-assisted failures by providing a mechanistic description of hydrogen uptake, transport and embrittlement. Phase field and multi-physics (electro-chemo-mechanical) modelling are combined to resolve the physical processes at play. The ability of the computational models developed to deliver predictions in agreement with laboratory experiments and over scales relevant to engineering practice is showcased.
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ROLE OF INTERFACE ON FRACTURE BEHAVIOR OF POLYMER NANOCOMPOSITES [Keynote]
The interfacial region between nanoparticles and polymer matrix can play a significant role in influencing mechanical behavior of polymer nanocomposites. In this research, the fracture behaviors of three sets of model nanocomposite systems with variation in interfacial properties were prepared and investigated. It is found that rigid nanoparticles can serve both as a reinforcing agent and a toughening agent for polymers if the nanoparticle surface is functionalized appropriately.
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PROGRESSIVE DAMAGE IN CMC MINICOMPOSITES WITH THICK INTERPHASES UNDER TENSILE LOADING [Keynote]
In this work, a composite cylinder assemblage (CCA) model has been used to model the progressive damage behavior under tensile loading of a three-phase ceramic matrix single-tow mini-composite composed of carbon fiber, silicon carbide (SiC) matrix and boron nitride (BN) interphase. A 3-phase shear lag model has been used to capture the matrix crack-driven stress redistribution in the presence of a finite thickness interphase. A probabilistic progressive modeling approach has been proposed to predict the tensile response of ceramic matrix composite (CMC) minicomposites. Multiple matrix cracking, interfacial debonding, and fiber failure have been considered as the damage modes. The predicted tensile response of CMCs from the progressive damage modeling approach agrees with experimental results obtained with C/BN/SiC minicomposites. Finally, the influence of volume fractions, constituent properties, and interfacial properties on the mechanical behavior of CMC minicomposites has been presented.
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MATERIALS PROPERTY CHANGES AFTER IRRADIATION EVLAUATED USING SMALL SCALE MECHANICAL TESTING. [Keynote]
Radiation damage can lead to significant property changes in structural materials. Radiation induced swelling, embrittlement or increase in yield strength are just a few. The dose, dose rate and temperature together determine the effect on the material which can have significant engineering impact. Therefore, it is key to understand how a material changes under radiation and being able to predict the property changes. Small scale mechanical testing offers a wide range of benefits especially when working with materials in nuclear application. The reduced size allows to handle highly radioactive materials while also enabling ion beam irradiations as a surrogate to quantify radiation damage. In this work we will provide examples on how small-scale mechanical testing provided deep insight into the mechanical deformation of materials after irradiation. We investigate how the properties change due the radiation induced dissolution of precipitates or due to the formation of new features such a cavities, dislocation loops or precipitates. We will highlight how the plasticity and associated mechanical property values change. Last but not least we will introduce scaling studies performed in order to extract bulk properties from small scale tests. Mesoscale mechanical tests enabled using laser fabrications are shown.
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IN SITU X-RAY TOMOGRAPHY IMAGING OF CRACK INITATION AND PROPAGATION IN NUCLEAR GRAPHITE AT 1000°C [Keynote]
Nuclear-grade graphite is a critically important high-temperature structural material for current and potentially next generation of fission reactors worldwide. It is imperative to understand its damage-tolerant behaviour and to discern the mechanisms of damage evolution under in-service conditions. Here we perform in situ mechanical testing with synchrotron X-ray computed micro-tomography at temperatures between ambient and 1,000 °C on a nuclear-grade Gilsocarbon graphite. We find that both the strength and fracture toughness of this graphite are improved at elevated temperature. Whereas this behaviour is consistent with observations of the closure of microcracks formed parallel to the covalent-sp2-bonded graphene layers at higher temperatures, which accommodate the more than tenfold larger thermal expansion perpendicular to these layers, we attribute the elevation in strength and toughness primarily to changes in the residual stress state at 800–1,000 °C, specifically to the reduction in significant levels of residual tensile stresses in the graphite that are ‘frozen-in’ following processing. A range of other nuclear grade graphite materials were tested and compared with Gilsocarbon graphite.
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IN-SILICO QUALIFICATION OF MATERIALS [Keynote]
Material qualification is an important pre-requisite for design substantiation of any power plant. Historically, this is achieved through large experimental programmes that are eventually collated to support design standards (e.g. ASME) or later in assessment codes (e.g. UK’s R5 and R6). This process is slow and expensive but low risk. In parallel, computer simulations have expanded their roles in the design and assessment process. Advanced physics-based simulations techniques such as crystal plasticity frameworks are increasingly being used to inform the engineering practices. However, they require extensive research to validate and substantial training for the practitioner to ensure the validity of their results. They are therefore considered to be expensive techniques that are deployed at exceptional circumstances. In this paper, a road map to use recent advances in machine learning is proposed that can simplify the complex physics-based simulations and produce high fidelity surrogate models that can be used cheaper, faster, with less stringent training. The surrogate models, because are based on rigorous physics-based simulations, can form part of the material qualification thus accelerating the process and making it more efficient.
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DEVELOPMENT AND APPLICATION OF THE HYPERCOMPLEX FINITE ELEMENT METHOD FOR LINEAR AND NONLINEAR ENERGY RELEASE RATE CALCULATIONS [Keynote]
The augmentation of existing finite element codes to use complex and hypercomplex variables and algebras provides an accurate and straightforward method to compute the energy release rate for linear and nonlinear solids. The basic concept is to introduce complex nodes defined by real and imaginary nodes. The real nodes define the geometry and the imaginary nodes define the perturbation to the real mesh. The crack is extended using imaginary coordinates surrounding the crack tip. The solution of the complex system of equations then yields a complex displacement with the imaginary displacement equal to the derivative of the displacement with respect to the crack length. Subsequently, the energy release rate (the derivative of the strain energy with respect to the crack length) can be determined using from the complex strains and stresses. The results indicate that the ERR results are as accurate as the J integral but the method has several advantages: there are no contours to interrogate – only one result is provided, the method works for both linear and nonlinear materials with loading and unloading, unlike the J integral, and no integral formulation must be developed and implemented. Numerical examples demonstrate the accuracy of the method.
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PROBABILISTIC CRITICAL FLAW SIZE ASSESSMENTS IN THE CIRCUMFERENTIAL WELDS OF LAYERED PRESSURE VESSELS [Keynote]
The National Aeronautics and Space Administration (NASA) operates approximately 300 aging, carbon steel, layered pressure vessels (LPVs) that were designed and manufactured prior to ASME Boiler and Pressure Vessel (B&PV) code requirements. Fitness-for-service assessments and traditional evaluations of these non-code vessels is a challenge due to unique uncertainties that are not present in code vessels, such as missing construction records and the use of proprietary materials in construction. Furthermore, many of the steels used in these non-code vessels are at a risk of cleavage fracture at low temperatures within the operating temperature ranges of the NASA sites where these vessels are installed. Additionally, the stress state in critical regions of the LPVs, such as the longitudinal seam welds and circumferential welds, is uncertain due to weld residual stresses (WRS), geometric discontinuities, and stress concentrations in weld connections. In order to guide non-destructive evaluation (NDE) and assessment of the circumferential welds and account for uncertainties in these non-code LPVs, probabilistic critical initial flaw size (CIFS) and critical crack size (CCS) analyses were performed for eleven locations of interest within the head-to-shell and shell-to-shell circumferential welds of three demonstration LPVs.
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ADVANCED CRACK TIP FIELD QUANTIFICATION USING DIGITAL IMAGE CORRELATION, MACHINE LEARNING, AND INTEGRAL EVALUATION [Keynote]
We use higher-order Williams coefficients from full-field displacement data obtained by digital image
correlation (DIC) to approximate complex crack tip fields with simpler expressions. The methodology is
based on invariant path integrals and machine-learned crack detection. We demonstrate the framework for
fatigue crack growth experiments of aluminium alloys and compare the results to matching finite element
simulations.
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