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The pandemic caused by the SARS-CoV-2 virus has claimed more than 6.5 million lives worldwide. This global challenge has led to accelerated development of highly effective vaccines tied to their ability to elicit a sustained immune response. While numerous studies have focused primarily on the spike (S) protein, less is known about the interior of the virus. Here we propose a methodology that combines several experimental and simulation techniques to elucidate the internal structure and mechanical properties of the SARS-CoV-2 virus. The mechanical response of the virus was analyzed by nanoindentation tests using a novel flat indenter and evaluated in comparison to a conventional sharp tip indentation. The elastic properties of the viral membrane were estimated by analytical solutions, molecular dynamics (MD) simulations on a membrane patch and by a 3D Finite Element (FE)-beam model of the virion's spike protein and membrane molecular structure. The FE-based inverse engineering approach provided a reasonable reproduction of the mechanical response of the virus from the sharp tip indentation and was successfully verified against the flat tip indentation results. The elastic modulus of the viral membrane was estimated in the range of 7-20 MPa. MD simulations showed that the presence of proteins significantly reduces the fracture strength of the membrane patch. However, FE simulations revealed an overall high fracture strength of the virus, with a mechanical behavior similar to the highly ductile behavior of engineering metallic materials. The failure mechanics of the membrane during sharp tip indentation includes progressive damage combined with localized collapse of the membrane due to severe bending. Furthermore, the results support the hypothesis of a close association of the long membrane proteins (M) with membrane-bound hexagonally packed ribonucleoproteins (RNPs). Beyond improved understanding of coronavirus structure, the present findings offer a knowledge base for the development of novel prevention and treatment methods that are independent of the immune system.
Maintaining dimensional accuracy is a major challenge of laser powder bed fusion (L-PBF) preventing its application for more complex and filigree L-PBF structures in industrial practice. Previous studies have shown that residual stresses and distortion of benchmark L-PBF components may be predicted by sequential thermo-mechanical analyses. However, the reliability of these analyses for more complex structures must be critically questioned, as comprehensive validation and sensitivity analyses are scarce. In this paper, we present a calibrated and validated low-fidelity sequential thermo-mechanical finite element analysis (FEA) of a tubular L-PBF lattice structure, i.e., an aortic stent, where pronounced local deformation is expected. As a first step, the finite element model was extensively calibrated using experimental data to ensure reproducibility of the simulation results. Thereupon, geometric features critical to the distortion of L-PBF lattice structures and measures to compensate for the distortion, such as inversion of the distorted L-PBF structure, were investigated. It was found that the distortion of the L-PBF lattice structures can be reduced, but not completely prevented, by increasing the strut angles, increasing the strut thickness, and decreasing the transition radius in the area of merging struts. FEA-based inversion of the numerically predicted deformed structure minimized distortion, resulting in the L-PBF aortic stent approximating the intended CAD geometry even with a small strut thickness. This work shows that low-fidelity sequential thermo-mechanical FEA can be used not only for the analysis and deformation compensation of reference structures, but also for the analysis of more complex filigree structures with pronounced local deformation.
Data-driven models are developed to predict the mechanical properties of polycrystalline materials. The case study is the prediction of the yield strength of a 3D-printed 316L steel from morphological and crystallographic features. Three different artificial intelligence models including feed-forward (FNN), convolution (CNN), and graph (GNN) neural networks are employed to train the data-driven models and are compared in terms of performance and computational requirements. The dataset required for training is generated by performing crystal plasticity finite element simulations. The FNN model has the smallest input size and takes in some statistical parameters describing the material microstructure, but its accuracy is relatively low. The CNN approach inputs voxel-based realizations of the microstructure and is able to give accurate estimations; however, its training process is time-consuming and computationally expensive. In the GNN approach, the polycrystalline material is represented by a graph whose nodes and lines represent the grains and adjacency between grains. It is observed that GNN yields a better performance compared to the other two approaches and has the capability of handling complex tasks.
A comprehensive experimental program is carried out to determine material parameters for fracture initiation and propagation in X100 pipeline steels. The quadratic Hill’48 yield function along with an isotropic hardening are used to describe plastic flow at large deformation and a phenomenological fracture criterion to predict fracture initiation. Fracture mechanics SENT specimens are used to calibrate post-initiation softening parameters necessary for ductile crack propagation in thick components. Once the material model parameters set is complete a final comparison is conducted with ring expansion test on same material.
Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenge relies on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5-68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti-6Al-4V sheet under both quasi-static and modest-rate dynamic loading (failure in 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. Additional shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the 'state-of-the-art' in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods.
Abrasive wear limits the lifetime of many machine components. Most empirical models relate the abrasive wear resistance to material hardness. In reality, however, other material properties are also influencing as scratch abrasion damage follows from a highly complex stress trajectory upon scratching. Numerical (finite element) simulation of scratch abrasion requires the use of a material damage model, which translates this stress trajectory into material degradation and removal. Most damage models include the first two stress invariants. However, fully incorporating the complex stress trajectories that occur during scratch abrasion may require damage models with dependence of the third deviatoric parameter (Lode angle). This paper serves as an a-priori study to evaluate the stress states that may occur during scratch abrasion. Three mechanisms (ploughing, wedging, cutting) are considered. Hereto, the results of an extensive parametric study using elastic-plastic finite element simulations of a scratch indentation process are discussed. Complex, non-proportional variations in stress state values are observed to occur during scratch abrasion. Distinct stress state trajectories are identified for the three abovementioned mechanisms. These variations are critically discussed to motivate a selection of suitable damage models for rigorous finite element analysis of the wear processes associated with scratch abrasion.
The current analyses present results of running ductile fracture propagation in high strength X100 line pipe steels under the influence of anisotropy. Mechanical anisotropy is commonly available in pipe products as a result of the manufacturing process, especially, those subjected to hot/cold-worked deformation. The outcomes of the present analyses show that its effect on the behavior of running ductile fracture in cracked pipes undergoing depressurization is meaningful. For instance, the Crack-Tip Opening Angle (CTOA) not only exhibits a strong dependence to the pipe's diameter size, but also to the material's anisotropy nature when compared to a hypothetical isotropic material. Moreover, laboratory scale tests such as those performed on Battelle Drop Weight Tear (BDWT) samples provide useful information about initiation of ductile crack propagation when the anisotropy features are taken into account in the material description.
Advances in additive manufacturing enable the production of tailored lattice structures and thus, in principle, coronary stents. This study investigates the effects of process-related irregularities, heat and surface treatment on the morphology, mechanical response, and expansion behavior of 316L stainless steel stents produced by laser powder bed fusion and provides a methodological approach for their numerical evaluation. A combined experimental and computational framework is used, based on both actual and computationally reconstructed laser powder bed fused stents. Process-related morphological deviations between the as-designed and actual laser powder bed fused stents were observed, resulting in a diameter increase by a factor of 2-2.6 for the stents without surface treatment and 1.3-2 for the electropolished stent compared to the as-designed stent. Thus, due to the increased geometrically induced stiffness, the laser powder bed fused stents in the as-built (7.11 ± 0.63 N) or the heat treated condition (5.87 ± 0.49 N) showed increased radial forces when compressed between two plates. After electropolishing, the heat treated stents exhibited radial forces (2.38 ± 0.23 N) comparable to conventional metallic stents. The laser powder bed fused stents were further affected by the size effect, resulting in a reduced yield strength by 41% in the as-built and by 59% in the heat treated condition compared to the bulk material obtained from tensile tests. The presented numerical approach was successful in predicting the macroscopic mechanical response of the stents under compression. During deformation, increased stiffness and local stress concentration were observed within the laser powder bed fused stents. Subsequent numerical expansion analysis of the derived stent models within a previously verified numerical model of stent expansion showed that electropolished and heat treated laser powder bed fused stents can exhibit comparable expansion behavior to conventional stents. The findings from this work motivate future experimental/numerical studies to quantify threshold values of critical geometric irregularities, which could be used to establish design guidelines for laser powder bed fused stents/lattice structures.
Customized additively manufactured (laser powder bed fused (L-PBF)) stents could improve the treatment of complex lesions by enhancing stent-artery conformity. However, geometric irregularities inherent for L-PBF stents are expected to influence not only their mechanical behavior but also their interaction with the artery. In this study, the influence of geometrical irregularities on stent-artery interaction is evaluated within a numerical framework. Thus, computed arterial stresses induced by a reconstructed L-PBF stent model are compared to those induced by the intended stent model (also representing a stent geometry obtained from conventional manufacturing processes) and a modified CAD stent model that accounts for the increased strut thickness inherent for L-PBF stents. It was found that, similar to conventionally manufactured stents, arterial stresses are initially related to the basic stent design/topology, with the highest stresses occurring at the indentations of the stent struts. Compared to the stent CAD model, the L-PBF stent induces distinctly higher and more maximum volume stresses within the plaque and the arterial wall. In return, the modified CAD model overestimates the arterial stresses induced by the L-PBF stent due to its homogeneously increased strut thickness and thus its homogeneously increased geometric stiffness compared with the L-PBF stent. Therefore, the L-PBF-induced geometric irregularities must be explicitly considered when evaluating the L-PBF stent-induced stresses because the intended stent CAD model underestimates the arterial stresses, whereas the modified CAD model overestimates them. The arterial stresses induced by the L-PBF stent were still within the range of values reported for conventional stents in literature, suggesting that the use of L-PBF stents is conceivable in principle. However, because geometric irregularities, such as protruding features from the stent surface, could potentially damage the artery or lead to premature stent failure, further improvement of L-PBF stents is essential.
The Sandia Fracture Challenges provide a forum for the mechanics community to assess its ability to predict ductile fracture through a blind, round-robin format where mechanicians are challenged to predict the deformation and failure of an arbitrary geometry given experimental calibration data. The Third Challenge (SFC3) required participants to predict fracture in an additively manufactured (AM) 316L stainless steel bar containing through holes and internal cavities that could not have been conventionally machined. The volunteer participants were provided extensive data including tension and notched tensions tests of 316L specimens built on the same build-plate as the Challenge geometry, micro-CT scans of the Challenge specimens and geometric measurements of the feature based on the scans, electron backscatter diffraction (EBSD) information on grain texture, and post-test fractography of the calibration specimens. Surprisingly, the global behavior of the SFC3 geometry specimens had modest variability despite being made of AM metal, with all of the SFC3 geometry specimens failing under the same failure mode. This is attributed to the large stress concentrations from the holes overwhelming the stochastic local influence of the AM voids and surface roughness. The teams were asked to predict a number of quantities of interest in the response based on global and local measures that were compared to experimental data, based partly on Digital Image Correlation (DIC) measurements of surface displacements and strains, including predictions of variability in the resulting fracture response, as the basis for assessment of the predictive capabilities of the modeling and simulation strategies. Twenty-one teams submitted predictions obtained from a variety of methods: the finite element method (FEM) or the mesh-free, peridynamic method; solvers with explicit time integration, implicit time integration, or quasi-statics; fracture methods including element deletion, peridynamics with bond damage, XFEM, damage (stiffness degradation), and adaptive remeshing. These predictions utilized many different material models: plasticity models including J2 plasticity or Hill yield with isotropic hardening, mixed Swift-Voce hardening, kinematic hardening, or custom hardening curves; fracture criteria including GTN model, Hosford-Coulomb, triaxiality-dependent strain, critical fracture energy, damage-based model, critical void volume fraction, and Johnson-Cook model; and damage evolution models including damage accumulation and evolution, crack band model, fracture energy, displacement value threshold, incremental stress triaxiality, Cocks-Ashby void growth, and void nucleation, growth, and coalescence. Teams used various combinations of calibration data from tensile specimens, the notched tensile specimens, and literature data. A detailed comparison of results based of these different methods is presented in this paper to suggest a set of best practices for modeling ductile fracture in situations like the SFC3 AM-material problem. All blind predictions identified the nominal crack path and initiation location correctly. The SFC3 participants generally fared better in their global predictions of deformation and failure than the participants in the previous Challenges, suggesting the relative maturity of the models used and adoption of best practices from previous Challenges. This paper provides detailed analyses of the results, including discussion of the utility of the provided data, challenges of the experimental-numerical comparison, defects in the AM material, and human factors.