This paper presents a comparative study of the tensile mechanical behaviour of pieces produced using the Fused Deposition Modelling (FDM) additive manufacturing technique with respect to the two ...types of thermoplastic material most widely used in this technique: polylactide (PLA) and acrylonitrile butadiene styrene (ABS). The aim of this study is to compare the effect of layer height, infill density, and layer orientation on the mechanical performance of PLA and ABS test specimens. The variables under study here are tensile yield stress, tensile strength, nominal strain at break, and modulus of elasticity. The results obtained with ABS show a lower variability than those obtained with PLA. In general, the infill percentage is the manufacturing parameter of greatest influence on the results, although the effect is more noticeable in PLA than in ABS. The test specimens manufactured using PLA perform more rigidly and they are found to have greater tensile strength than ABS. The bond between layers in PLA turns out to be extremely strong and is, therefore, highly suitable for use in additive technologies. The methodology proposed is a reference of interest in studies involving the determination of mechanical properties of polymer materials manufactured using these technologies.
In this article we study the possible Morita equivalence classes of algebras in three families of fusion categories (pointed, near-group and (A1,l)12) by studying the Non-negative Integer Matrix ...representations (NIM-reps) of their underlying fusion ring, and compare these results with existing classification results of algebra objects. Also, in an appendix we include a test of the exponents conjecture for modular tensor categories of rank up to 4.
One of the challenges in additive manufacturing (AM) of metallic materials is to obtain workpieces free of defects with excellent physical, mechanical, and metallurgical properties. In wire and arc ...additive manufacturing (WAAM) the influences of process conditions on thermal history, microstructure and resultant mechanical and surface properties of parts must be analyzed. In this work, 3D metallic parts of mild steel wire (American Welding Society-AWS ER70S-6) are built with a WAAM process by depositing layers of material on a substrate of a S235 JR steel sheet of 3 mm thickness under different process conditions, using as welding process the gas metal arc welding (GMAW) with cold metal transfer (CMT) technology, combined with a positioning system such as a computer numerical controlled (CNC) milling machine. Considering the hardness profiles, the estimated ultimate tensile strengths (UTS) derived from the hardness measurements and the microstructure findings, it can be concluded that the most favorable process conditions are the ones provided by CMT, with homogeneous hardness profiles, good mechanical strengths in accordance to conditions defined by standard, and without formation of a decohesionated external layer; CMT Continuous is the optimal option as the mechanical properties are better than single CMT.
In metal forming, the plastic behavior of metallic alloys is directly related to their formability, and it has been traditionally characterized by simplified models of the flow curves, especially in ...the analysis by finite element simulation and analytical methods. Tools based on artificial neural networks have shown high potential for predicting the behavior and properties of industrial components. Aluminum alloys are among the most broadly used materials in challenging industries such as aerospace, automotive, or food packaging. In this study, a computer-aided tool is developed to predict two of the most useful mechanical properties of metallic materials to characterize the plastic behavior, yield strength and ultimate tensile strength. These prognostics are based on the alloy chemical composition, tempers, and Brinell hardness. In this study, a material database is employed to train an artificial neural network that is able to make predictions with a confidence greater than 95%. It is also shown that this methodology achieves a performance similar to that of empirical equations developed expressly for a specific material, but it provides greater generality since it can approximate the properties of any aluminum alloy. The methodology is based on the usage of artificial neural networks supported by a big data collection about the properties of thousands of commercial materials. Thus, the input data go above 2000 entries. When the relevant information has been collected and organized, an artificial neural network is defined, and after the training, the artificial intelligence is able to make predictions about the material properties with an average confidence greater than 95%.
Abstract In this paper we study the computational feasibility of an algorithm to prove orbifold equivalence between potentials describing Landau–Ginzburg models. Through a comparison with ...state-of-the-art results of Gröbner basis computations in cryptology, we infer that the algorithm produces systems of equations that are beyond the limits of current technical capabilities. As such the algorithm needs to be augmented by ‘inspired guesswork’, and we provide examples of applying this approach.
The Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020) has been launched as a joint issue of the journals "
" and "
". The 17 contributions published in this Special Issue of ...Materials present cutting-edge advances in the field of Manufacturing Engineering, focusing on additive manufacturing and 3D printing; advances and innovations in manufacturing processes; sustainable and green manufacturing; manufacturing of new materials; manufacturing systems: machines, equipment and tooling; robotics, mechatronics and manufacturing automation; metrology and quality in manufacturing; Industry 4.0; design, modeling and simulation in manufacturing engineering. Among them, this issue highlights that the topic "advances and innovations in manufacturing processes" has collected a large number of contributions, followed by additive manufacturing and 3D printing; sustainable and green manufacturing; metrology and quality in manufacturing.
The lack of specific standards for characterization of materials manufactured by Fused Deposition Modelling (FDM) makes the assessment of the applicability of the test methods available and the ...analysis of their limitations necessary; depending on the definition of the most appropriate specimens on the kind of part we want to produce or the purpose of the data we want to obtain from the tests. In this work, the Spanish standard UNE 116005:2012 and international standard ASTM D638-14:2014 have been used to characterize mechanically FDM samples with solid infill considering two build orientations. Tests performed according to the specific standard for additive manufacturing UNE 116005:2012 present a much better repeatability than the ones according to the general test standard ASTM D638-14, which makes the standard UNE more appropriate for comparison of different materials. Orientation on-edge provides higher strength to the parts obtained by FDM, which is coherent with the arrangement of the filaments in each layer for each orientation. Comparison with non-solid specimens shows that the increase of strength due to the infill is not in the same proportion to the percentage of infill. The values of strain to break for the samples with solid infill presents a much higher deformation before fracture.
We construct a separable Frobenius monoidal functor from $\mathcal{Z}\big(\mathsf{Vect}_H^{\omega|_H}\big)$ to $\mathcal{Z}\big(\mathsf{Vect}_G^\omega\big)$ for any subgroup $H$ of $G$ which ...preserves braiding and ribbon structure. As an application, we classify rigid Frobenius algebras in $\mathcal{Z}\big(\mathsf{Vect}_G^\omega\big)$, recovering the classification of étale algebras in these categories by Davydov-Simmons J. Algebra 471 (2017), 149-175, arXiv:1603.04650 and generalizing their classification to algebraically closed fields of arbitrary characteristic. Categories of local modules over such algebras are modular tensor categories by results of Kirillov-Ostrik Adv. Math. 171 (2002), 183-227, arXiv:math.QA/0101219 in the semisimple case and Laugwitz-Walton Comm. Math. Phys., to appear, arXiv:2202.08644 in the general case.
The COVID-19 outbreak has ravaged all societal domains, including education. Home confinement, school closures, and distance learning impacted students, teachers, and parents' lives worldwide. In ...this study, we aimed to examine the impact of COVID-19-related restrictions on Italian and Portuguese students' academic motivation as well as investigate the possible buffering role of extracurricular activities. Following a retrospective pretest-posttest design, 567 parents (
= 173,
= 394) reported on their children's academic motivation and participation in extracurricular activities (grades 1 to 9). We used a multi-group latent change score model to compare Italian and Portuguese students': (1) pre-COVID mean motivation scores; (2) rate of change in motivation; (3) individual variation in the rate of change in motivation; and (4) dependence of the rate of change on initial motivation scores. Estimates of latent change score models showed a decrease in students' motivation both in Italy and in Portugal, although more pronounced in Italian students. Results also indicated that the decrease in students' participation in extracurricular activities was associated with changes in academic motivation (i.e., students with a lower decrease in participation in extracurricular activities had also a lower decrease in motivation). Furthermore, students' age was significantly associated with changes in motivation (i.e., older students had lower decrease). No significant associations were found for students' gender nor for parents' education. This study provides an important contribution to the study of students' academic motivation during home confinement, school closures, and distance learning as restrictive measures adopted to contain a worldwide health emergency. We contend that teachers need to adopt motivation-enhancing practices as means to prevent the decline in academic motivation during exceptional situations.
The stygofaunal family of Bathynellidae, is an excellent group to study the processes that shape diversity and distribution, since they have unknown surface or marine relatives, high level of ...endemism, and limited dispersal abilities. Recent research on Bathynellidae in Western Australia (Pilbara) has uncovered new taxa with unexpected distributions and phylogenetic relationships, but the biogeographical processes that drive their diversification on the continent are still unclear. By exploring the diversity, distribution, and divergence time of Bathynellidae in a setting such as the perched and isolated aquifers of the Cleaverville Formation in the north of the De Grey River catchment (Pilbara), we aim to test the hypothesis that vicariance has shaped the distribution of this family, specifically if one or multiple vicariant events were involved. We analysed the specimens collected from perched water in different plateaus of the Cleaverville Formation, combining morphological and molecular data from mitochondrial and nuclear genes. We described two new species and genera (Anguillanella callawaensis gen. et sp. nov. and Muccanella cundalinensis gen. et sp. nov.), and two additional taxa are recognised using morphology and/or Automatic Barcode Gap Discovery and Poisson Tree Processes species delimitation methods. New genera and species result restricted to isolate perched aquifers on single plateaus and their distributions, phylogenetic relationships, and divergence time estimates support multiple vicariant events and ancient allopatric speciation.
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