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Elkarrizketak irakasleen prestakuntzarako bitarteko: irakasle-bideratzaileen jarduna ezaugarritzen
Get PDFLan honen helburua da aztertzea eta ezaugarritzea unibertsitateko irakasle-bideratzaileek zer nolako bidaidetza mota egiten duten etorkizuneko irakasleekin euren praktikaren analisia bideoaren aurreko autokonfrontazio elkarrizketak egiten ari direnean. 5 irakasle-bideratzailek egindako 10 autokonfrontazio elkarrizketak osatutako corpusean,. aztertu da irakasle-bideratzaile horien rola ikasleekin egindako autokonfrontazio elkarrizketen transkribapenetan eta euren jarduna 9 kategoriatan banatu da. Horietatik bi zehaztapenak eskatzea eta kontrobertsia sortzea, dira elkarrizketetan erabilienak. Irakasle-bideratzailearen profilaren arabera, ordea, ezberdintasunak sumatu dira jarduteko moduetan eta, ondorioz, prestakuntza eredua partekatua izan dadin irakasle-bideratzaileen prestakuntzan sakondu beharko litzateke.The aim of the present paper is to analyse and characterise the way in which teacher educators work with student teachers when conducting analyses of their own practice by means of selfconfrontation interviews. The corpus of this work consists of 10 self-confrontation interviews carried out by 5 teacher educators. The role of those teacher educators was analysed using the transcriptions of the interviews and 9 categories were identified. Two categories were found to be the most common: demanding specifications and creating controversy. Differences were also found as regards teacher educators' profile. As a result, in-depth training for teacher educators has been considered as needed
Elkarrekintza didaktikoa eta album ilustratua hezkuntza literariorako giltzarri. Ezagutzak elkarrekin eraikitzen
Get PDFLan hau hezkuntza literarioaren esparruan kokatzen da, eta helburu du
elkarrekintza didaktikoaren estrategietan sakontzea, elkarrekintza diseinatzeko
eta gelaratzeko modu desberdinak aztertuz. Horretarako, album ilustratua izan da
aztertutako gelaratzeetan langai izan den generoa, hain zuzen ere, genero horren
izaera erraztatzailea delako elkarrekintzak eraikitzeko, ikaskuntza dialogikoa
sustatzeko eta literaturaz hitz egiteko. Ildo horretatik, ikertu dira album ilustratuak eta
elkarrekintzak eskaintzen dituzten aukerak gaitasun literarioak nahiz komunikatiboak
lantzeko. Hori guztia prestakuntza ikertuaren barruan egin da Arizmendi Ikastolan,
eta Lehen Hezkuntzako laugarren mailako irakasle baten gelaratzeak analizatu dira;
horietako bakoitzean nagusitu diren elkarrekintza motak eta bakoitzak nola lagundu
duen ezagutzak eraikitzen eta mintzagaietan sakontzenThe present research is situated within literary education and its aim is to take a
closer look at strategies used in a teaching interaction, through the analysis of different forms
of design and interaction. With this purpose in mind, the genre of picture books has been
selected to be analyzed in classrooms as they are a recognized tool for the encouragement
of interaction and the promotion of exploratory talk. It is from this perspective that picture
books have been explored, as well as for the communicative and literary competences that
are achieved by providing interactions. The exploration of these aspects has taken place in
Arizmendi School as part of a training course. The everyday classroom practice of a 4th grade
primary school teacher has been analyzed with specific regard to which types of interaction
have been the most recurrent and how this helps in constructing knowledge and going into
detail about the main topics of conversation
Reduction of distortions in large aluminium parts by controlling machining-induced residual stresses
Get PDFLarge aluminium monolithic parts used in the aeronautic industry frequently show significant geometric distortions after the machining process. These distortions are the consequence of the initial residual stresses of the raw material as well as machining-induced residual stresses. Therefore, to minimise distortions, it is fundamental to understand the effect of the different parameters of the manufacturing process and define the optimum manufacturing strategy. This work studies the effect of initial residual stresses of aluminium plates and the residual stresses generated by the machining process on the final geometric distortions of the part. First, 7175-T7351 aluminium bars (40 mm wide × 38 mm thick × 400 mm long) were face milled at two different cutting conditions reducing the thickness to 6 mm. The distortions were measured in a coordinate measuring machine. The results revealed that the machining strategy significantly influenced the distortions, as a difference of 65% on distortions was found between the two cutting conditions. In addition, an FEM model to predict distortions was developed. This model considers initial residual stresses (measured by the contour method) and residual stresses induced by the machining process (measured by the hole drilling technique). Once the FEM model was validated, the study was extended to more complex geometries. These new studies revealed that final distortions are sensitive to machining-induced residual stresses. Furthermore, this finding indicates that it is possible to define machining conditions which generate desirable residual stress profiles to minimise part distortion
Hardening prediction of diverse materials using the Digital Image Correlation technique
Get PDFIn recent years, due to the introduction of higher resistance materials in the automotive sector, sheet metal-forming tool-makers have been forced to deal with more challenging process designs. Therefore, the optimisation of the manufacturing process has become a key factor in obtaining a part which fits the required tolerances, and the finite element method (FEM) is the most widely used technique to speed up that optimisation time. However, to obtain a numerical result as close as possible to those of industrial conditions, the FEM software inputs must be highly accurate. The present work is focused on the hardening extension of the currently available reduced-formability materials, as it is a key factor in the correct prediction of the stress state and hence, of the springback during a sheet metal-forming process. The objective in this work was the selection of the most appropriate hardening model to extend the flow curve beyond the necking limit for a wide variety of material families currently utilised in the industrial environment. To carry out that analysis, a digital image correlation (DIC) technique was utilised during conventional tensile tests to extend the experimental flow curves of the analysed materials. Commonly used hardening models were fitted to the experimental tensile flow curves with the aim of selecting the model that best predicts the hardening behaviour of each analysed material family. The results showed that the DIC technique was valid for the extension of the hardening curve of the analysed materials and for the final selection of the most suitable hardening model for each analysed material family
Null is Not Always Empty: Monitoring the Null Space for Field-Level Anomaly Detection in Industrial IoT Environments
Get PDFIndustrial environments have vastly changed sincethe conception of initial primitive and isolated networks. Thecurrent full interconnection paradigm, where connectivity be-tween different devices and the Internet has become a businessnecessity, has driven device interconnectivity towards buildingthe Industrial Internet of Things (IIoT), enabling added valueservices such as supply chain optimization or improved processcontrol. However, whereas interconnectivity has increased, IIoTsecurity practices has not evolved at the same pace, due partlyto inherited security practices from when industrial networkswhere not connected and the existence of basic hardware withno security functionalities. In this work, we present an AnomalyDetection System for industrial environments that monitorsphysical quantities to detect intrusions. It is based in the nullspace detection, which is at the same time, based on StochasticSubspace Identification (SSI). The approach is validated usingthe Tennessee-Eastman chemical process
A numerical analysis of multiaxial fatigue in a butt weld specimen considering residual stresses
Get PDFResidual Stress (RS) pattern changes considerably depending on the width of the plates and the welding parameters, having effect on the fatigue strength. Most of the standards do not consider them and in some works, yield stress is taken as residual stressvalue. It results in a very conservative estimation of fatigue life. Authors developed recently a numerical model to predict more properly the value of RS pattern depending on the plate thickness. In a welded joint, considering the RS and alternating axial loads, the evolution of the stresses is multiaxial, becoming necessary its study. Therefore, the aim of this work is to analyse different fatigue indicator parameters (Smith-Watson-Topper, Fatemi-Socie, and Critical Plane implementation of the Basquin equation) in order to predict the fatigue behaviour of butt-weld components. For that purpose, the numerical model to predict the RS pattern in welded joint developed by this research group is used
A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives
Get PDFDuring the last decade, due to the increasing importance of reliability and availability, railway industry is making greater use of fault diagnosis approaches for early fault detection, as well as Condition-based maintenance frameworks. Due to the influence of traction drive in the railway system availability, several research works have been focused on Fault Diagnosis for Railway traction drives. Fault diagnosis approaches have been applied to electric machines, sensors and power electronics. Furthermore, Condition-based maintenance framework seems to reduce corrective and Time-based maintenance works in Railway Systems. However, there is not any publication that summarizes all the research works carried out in Fault diagnosis and Condition-based Maintenance frameworks for Railway Traction Drives. Thus, this review presents the development of Health Assessment and Fault Diagnosis in Railway Traction Drives during the last decade
Field Weakening Characteristics Computed with FEM-Coupled Algorithms for Brushless AC Motors
Get PDFFinite Element Method (FEM) analysis tools are the most adopted in the design of
brushless alternating current motors due to the advantage of considering multi-physics effects
with dependencies of variables such as cross-coupling, saturation and others that are not possible to
be modeled analytically with high precision. During the design process designers compute operation
points such as maximum torque per ampere or flux weakening characteristics that cannot be targeted
directly on the FEM tool. Therefore, designers make a sweep of simulations and post-processed
the data in order to obtain the results, this is repetitive particularly in the conceptual phase of the
design where features of the motor are still not defined. This paper presents nine algorithms as an
alternative to compute with iterative methods operation points that cannot be targeted directly on a
FEM tool. The algorithms must be coupled to the FEM tool and can compute complex points such
as the characteristic current and modes of operations limits within acceptable range of error and
times of execution for practical purposes. Validation of the algorithms using Jython is presented
with results for the three types of brushless motors (non-salient, interior permanent magnet and
reluctance motor)
A case study on the use of machine learning techniques for supporting technology watch
Get PDFTechnology Watch human agents have to read many documents in order to manually categorize and dispatch them to the correct expert, that will later add valued information to each document. In this two step process, the first one, the categorization of documents, is time consuming and relies on the knowledge of a human categorizer agent. It does not add direct valued information to the process that will be provided in the second step, when the document is revised by the correct expert.
This paper proposes Machine Learning tools and techniques to learn from the manually pre-categorized data to automatically classify new content. For this work a real industrial context was considered. Text from original documents, text from added value information and Semantic Annotations of those texts were used to generate different models, considering manually pre-established categories. Moreover, three algorithms from different approaches were used to generate the models. Finally, the results obtained were compared to select the best model in terms of accuracy and also on the reduction of the amount of document readings (human workload)