Accurate prediction of melt pool shapes in laser powder bed fusion by the non-linear temperature equation including phase changes - isotropic versus anisotropic conductivity

In this contribution, we validate a physical model based on a transient temperature equation (including latent heat) w.r.t. the experimental set AMB2018-02 provided within the additive manufacturing benchmark series, established at the National Institute of Standards and Technology, USA. We aim at predicting the following quantities of interest: width, depth, and length of the melt pool by numerical simulation and report also on the obtainable numerical results of the cooling rate. We first assume the laser to posses a double ellipsoidal shape and demonstrate that a well calibrated, purely thermal model based on isotropic thermal conductivity is able to predict all the quantities of interest, up to a deviation of maximum 7.3\% from the experimentally measured values. However, it is interesting to observe that if we directly introduce, whenever available, the measured laser profile in the model (instead of the double ellipsoidal shape) the investigated model returns a deviation of 19.3\% from the experimental values. This motivates a model update by introducing anisotropic conductivity, which is intended to be a simplistic model for heat material convection inside the melt pool. Such an anisotropic model enables the prediction of all quantities of interest mentioned above with a maximum deviation from the experimental values of 6.5\%. We note that, although more predictive, the anisotropic model induces only a marginal increase in computational complexity

Suitably graded THB-spline refinement and coarsening: Towards an adaptive isogeometric analysis of additive manufacturing processes

In the present work we introduce a complete set of algorithms to efficiently perform adaptive refinement and coarsening by exploiting truncated hierarchical B-splines (THB-splines) defined on suitably graded isogeometric meshes, that are called admissible mesh configurations. We apply the proposed algorithms to two-dimensional linear heat transfer problems with localized moving heat source, as simplified models for additive manufacturing applications. We first verify the accuracy of the admissible adaptive scheme with respect to an overkilled solution, for then comparing our results with similar schemes which consider different refinement and coarsening algorithms, with or without taking into account grading parameters. This study shows that the THB-spline admissible solution delivers an optimal discretization for what concerns not only the accuracy of the approximation, but also the (reduced) number of degrees of freedom per time step. In the last example we investigate the capability of the algorithms to approximate the thermal history of the problem for a more complicated source path. The comparison with uniform and non-admissible hierarchical meshes demonstrates that also in this case our adaptive scheme returns the desired accuracy while strongly improving the computational efficiency.Comment: 20 pages, 12 figure

An Ontology for Defect Detection in Metal Additive Manufacturing

A key challenge for Industry 4.0 applications is to develop control systems for automated manufacturing services that are capable of addressing both data integration and semantic interoperability issues, as well as monitoring and decision making tasks. To address such an issue in advanced manufacturing systems, principled knowledge representation approaches based on formal ontologies have been proposed as a foundation to information management and maintenance in presence of heterogeneous data sources. In addition, ontologies provide reasoning and querying capabilities to aid domain experts and end users in the context of constraint validation and decision making. Finally, ontology-based approaches to advanced manufacturing services can support the explainability and interpretability of the behaviour of monitoring, control, and simulation systems that are based on black-box machine learning algorithms. In this work, we provide a novel ontology for the classification of process-induced defects known from the metal additive manufacturing literature. Together with a formal representation of the characterising features and sources of defects, we integrate our knowledge base with state-of-the-art ontologies in the field. Our knowledge base aims at enhancing the modelling capabilities of additive manufacturing ontologies by adding further defect analysis terminology and diagnostic inference features

Impact of interaction forces in first order many-agent systems for swarm manufacturing

We study the large time behavior of a system of interacting agents modeling the relaxation of a large swarm of robots, whose task is to uniformly cover a portion of the domain by communicating with each other in terms of their distance. To this end, we generalize a related result for a Fokker-Planck-type model with a nonlocal discontinuous drift and constant diffusion, recently introduced by three of the authors, of which the steady distribution is explicitly computable. For this new nonlocal Fokker-Planck equation, existence, uniqueness and positivity of a global solution are proven, together with precise equilibration rates of the solution towards its quasi-stationary distribution. Numerical experiments are designed to verify the theoretical findings and explore possible extensions to more complex scenarios

The Effects of Language Background and Foreign Accent on Listening Comprehension

The act of listening to a linguistic signal is an involved process, and, rarely occurs in absolute silence. A person trying to listen and comprehend speech is likely in an environment that has some sort of additional noise: white noise from a fan, passing traffic, construction, or just other talkers. Each of these additional auditory signals creates an unfavorable environment for the listener who is trying to capture the target signal. Research has been able to quantify and describe the effects of noise on the comprehension of linguistic signals, and has also shown that that bilinguals and monolinguals — though their performance is indistinguishable in quiet conditions — are known to be differentially affected by noise: bilinguals perform significantly worse in adverse listening conditions when tasked with comprehend a linguistic signal. What is yet to be established is how a signal with intrinsic, phonological variation differentially affects monolinguals and bilinguals. This study is a small-scale pilot that investigates this question: what bearing does bilingualism have on the comprehension of foreign-accented speech in quiet and in noise? Stimuli include sentences spoken in English, with five different accents: Neutral English (the English typical of the NYC area), Latin American Spanish English, Mandarin English, Italian English, and Indian English. A true-false verification task is used to assess the participants’ comprehension of the sentences, which are auditorily delivered such that no two sentences with the same accent are heard consecutively. All five accents are heard in both quiet and in noise, in two separate blocks. Accuracy and reaction times are analyzed

Simultaneous Bilinguals’ Comprehension of Accented Speech

L2-accented speech recognition has typically been studied with monolingual listeners or late L2-learners, but simultaneous bilinguals may have a different experience: their two phonologies offer flexibility in phonological-lexical mapping (Samuel and Larraza, 2015), which may be advantageous. On the other hand, the two languages cause greater lexical competition (Marian & Spivey, 2003), which may impede successful L2-accented speech recognition. The competition between a bilinguals’ two languages is the oft-cited explanation, for example, as to why bilinguals underperform monolinguals in native-accented speech-in-noise tasks (Rogers et al., 2006). To investigate the effect of bilingualism on L2-accented speech recognition, the current studies compare monolingual and simultaneous bilingual listeners in three separate experiments. In the first study, both groups repeated sentences produced by speakers of Mandarin-accented English whose English proficiencies varied. In the second study, the stimuli were presented in varying levels and types of noise, and a native-accented speaker was included. In each of these first two studies, the sentences were semantically anomalous (i.e., nonsensical). In the third study, the stimuli were meaningful sentences, presented in a single noise condition, and spoken by either a native speaker or an L2-accented speaker. Mixed effects models revealed differences in L2-accented speech recognition measures driven by listeners’ language backgrounds only in Experiments 2 and 3; in Experiment 1, performance between groups was statistically identical. Results in Experiments 2 and 3 also replicated the prior finding that bilinguals perform worse for native-accented speech in noise. We propose that neither a flexible phonological-lexical mapping system nor increased lexical competition can alone sufficiently explain the deficit (relative to monolinguals) that simultaneous bilinguals exhibit when faced with L2-accented speech in real-world listening conditions. We discuss the possible implications of processing capacity and cognitive load, and suggest that these two factors are more likely to contribute to experimental outcomes. Future studies with pupillometry to explore these hypotheses are also discussed

Cost-effective and accurate interlaminar stress modeling of composite Kirchhoff plates via immersed isogeometric analysis and equilibrium

The interest for composites has constantly grown in recent years, especially in the aerospace and automotive industries, as they can be moulded in complex form and geometry, as well as exhibit enhanced engineering properties. Nevertheless, despite the accelerated diffusion of laminated composites, the design of these materials is often restrained by the lack of cost-effective modeling techniques. In fact, the existing numerical strategies allowing for cheap simulations of laminated structures usually fail to directly capture out-of-plane through-the-thickness stresses, which are typically responsible for failure modes such as delamination. In this context, a stress recovery approach based on equilibrium has been recently shown to be an efficient modeling strategy in the framework of isogeometric analysis. Since immersed approaches like the finite cell method have been proven to be a viable alternative to mesh-conforming discretization for dealing with complex/dirty geometries as well as trimmed surfaces, we herein propose to extend the stress recovery approach combining the finite cell method, isogeometric analysis and equilibrium to model the out-of-plane behavior of Kirchhoff laminated plates. Extensive numerical tests showcase the effectiveness of the proposed approach

Sparse-grids uncertainty quantification of part-scale additive manufacturing processes

The present paper aims at applying uncertainty quantification methodologies to process simulations of powder bed fusion of metal. In particular, for a part-scale thermomechanical model of an Inconel 625 super-alloy beam, we study the uncertainties of three process parameters, namely the activation temperature, the powder convection coefficient and the gas convection coefficient. First, we perform a variance-based global sensitivity analysis to study how each uncertain parameter contributes to the variability of the beam displacements. The results allow us to conclude that the gas convection coefficient has little impact and can therefore be fixed to a constant value for subsequent studies. Then, we conduct an inverse uncertainty quantification analysis, based on a Bayesian approach on synthetic displacements data, to quantify the uncertainties of the two remaining parameters, namely the activation temperature and the powder convection coefficient. Finally, we use the results of the inverse uncertainty quantification analysis to perform a data-informed forward uncertainty quantification analysis of the residual strains. Crucially, we make use of surrogate models based on sparse grids to keep to a minimum the computational burden of every step of the uncertainty quantification analysis. The proposed uncertainty quantification workflow allows us to substantially ease the typical trial-and-error approach used to calibrate power bed fusion part-scale models, and to greatly reduce uncertainties on the numerical prediction of the residual strains. In particular, we demonstrate the possibility of using displacement measurements to obtain a data-informed probability density function of the residual strains, a quantity much more complex to measure than displacements

Additive manufacturing graded-material design based on phase-field and topology optimization

In the present work we introduce a novel graded-material design for additive manufacturing based on phase-field and topology optimization. The main novelty of this work comes from the introduction of an additional phase-field variable in the classical single-material phase-field topology optimization algorithm. This new variable is used to grade the material properties in a continuous fashion. Two different numerical examples are discussed, in both of them we perform sensitivity studies to asses the effects of different model parameters onto the resulting structure. From the presented results we can observe that the proposed algorithm adds additional freedom in the design, exploiting the higher flexibility coming from additive manufacturing technology

Graded-material Design based on Phase-field and Topology Optimization

In the present work we introduce a novel graded-material design based on phase-field and topology optimization. The main novelty of this work comes from the introduction of an additional phase-field variable in the classical single-material phase-field topology optimization algorithm. This new variable is used to grade the material properties in a continuous fashion. Two different numerical examples are discussed, in both of them we perform sensitivity studies to asses the effects of different model parameters onto the resulting structure. From the presented results we can observe that the proposed algorithm adds additional freedom in the design, exploiting the higher flexibility coming from additive manufacturing technology