Numerical modelling of cold crucible induction melting (CCIM) process and fabrication of high value added components of titanium and its alloys

This dissertation concerns the development of a numerical modelling of cold crucible induction melting (CCIM) and the fabrication of high value added components of titanium and its alloys. Titanium and its alloys have emerged as a very attractive metal for numerous applications: medical prostheses, aerospace industry, automotive industry, power generation, sport equipment, and marine engineering. The reason lie in their attractive properties, such as excellent biocompatibility, high specific strength, excellent corrosion resistance, excellent high temperature creep resistance, and good fracture toughness. However, the application of titanium is often limited by its relatively high cost. This high cost of titanium makes casting very attractive route. However, is it difficult to cast these alloys by conventional casting techniques because of the titanium reactivity at high temperatures, which reacts with the crucible and mould components. The CCIM process is currently the most effective means of melting these alloys. The CCIM is an innovative process to melt high melting point reactive materials such as titanium alloys. The melting and casting of the material is performed in vacuum or in a protective atmosphere in order to prevent any contamination of the charge. Moreover, a water cooled segmented crucible is used instead of a ceramic crucible to avoid any kind of reaction among the charge and the crucible. The magnetic field generated by an external coil penetrates through the slits of the crucible and generates induced currents in the charge, which are responsible of melting it due to Joule heating. The drawbacks of this process are the poor efficiency due to great percentage of heat that is removed by the cooling system and the small superheat of the melt, which can cause solidification problems. In this dissertation, we have selected the CCIM process to melt and cast titanium alloys. The aim of this dissertation consists on increasing the scientific knowledge about the CCIM process by means of both a numerical and an experimental approach. The main part of the dissertation focuses on the development of a numerical modelling of CCIM to optimize of the main parameters of the process. The task of optimizing melt superheat faces the challenge of finding optimal combination of crucible height to diameter ratio, number of inductor turns, crucible design, current strength, and frequency. Variation of any of the after mentioned factors influences the shape of melt meniscus and, as a result, flow pattern and energy balance. The second part deals with the set-up of an installation of CCIM and the fabrications of titanium components. As a result of the present work some goals have been achieved, being the most important: a) Development of numerical modelling of CCIM, b) setting up of a CCIM installation, and c) casting of titanium parts.Tesi honek “Cold crucible induction melting (CCIM)” prozesuaren simulazio numerikoaren gainean eta prozesu honen bidez titaniozko balio erantsi altuko osagaiak ekoizteko modua tratatzen du. Titanioak eta bere aleazioek interes handia sortu dute aplikazio industrial askotan: mediku protesiak, aeronautika, automozioa, energia generazioa, kirol ekipamendua eta itsas ingeniaritza. Arrazoia bere ezaugarri erakargarrietan errotzen da: biokonpatibilitate bikaina, erresistentzia espezifiko altua, korrosioaren aurkako erresistentzia ezin hobea, tenperatura alturako isurpenaren aurkako erresistentzia paregabea eta hausturaren aurkako erresistentzia. Hala ere, bere kostu altuak bere aplikazioak murrizten ditu. Galdaketa-prozesuek kostu txikiagoko produktuetara daramate. Hala ere, zaila da aleazio hauek galdaketa prozesu konbentzionalekin urtzea, tenperatura handitan erreaktibotasun handia daukate eta. CCIM prozesua aleazio hauek galdatzeko prozesu eraginkorren arten dago gaur egun. CCIM prozesua material erreaktiboak urtzeko prozesu berritzailea da. Bai urtze bai galdaketa hutsean edo atmosfera babesle baten egiten da materialaren erreakzioa saihesteko. Gainera, ohiko zeramikozko arragoen ordez segmentudun kobrezko arragoa erabiltzen da. Kanpoko harilak sortutako kanpo magnetikoa arragoaren arteketatik barneratzen da eta indukziozko korronteak sortzen ditu kargan, karga bera urtuz Joule beroketagatik. Prozesu honen arazoak efizientzia eskasa (hozte sistemak xurgatzen duen beroagatik) eta solidotzearazoak eragin ditzakeen gainberotze txikia dira. Tesi honetan, CCIM prozesua aukeratu dugu titaniozko aleazioak galdaketa prozesuaren bidez fabrikatzeko. Tesi honen helburua CCIM prozesuaren gaineko ezaguera zientifikoa handitzean datza bai ikuspegi teorikoa bai ikuspegi esperimentala erabiliz. Tesiko alderdi nagusia prozesuaren parametro nagusiak optimizatzeko CCIM prozesuaren zenbakizko modelizazioaren garapenaran gainean tratatzen du. Gainberotze tenperatura optimizatzeko zeregina arragoaren altura diametro ratioa, harilaren espira kopurua, arragoaren diseinua, korrontea eta frekuentziaren balio optimoa aurkitzean datza. Aipatutako faktoreen edozein aldaketek meniskoaren egoeran eragiten du, eta ondorioz, jariakinaren patroian eta energi balantzean. Tesiaren bigarren atalak CCIM instalazio bat abiarazteaz eta titaniozko osagaiak fabrikatzeaz dihardu. Lan honen emaitz garrantzitsuenak hurrengokoak dira: a) CCIM prozesuaren modelo numerikoaren garapena. b) CCIM prozesuaren instalazio baten abiaraztea. c) Titaniozko piezen galdaketa.Esta tesis trata sobre el desarrollo de un modelo numérico del “cold crucible induction melting (CCIM)” y la fabricación de componentes de alto valor añadido de titanio y sus aleaciones mediante este proceso. El titanio y sus aleaciones se han convertido en un metal muy atractivo para numerosas aplicaciones: prótesis médicas, industria aeroespacial, industria de automoción, generación de energía, deporte e ingeniería marina. La razón radica en sus propiedades atractivas, tales como excelente biocompatibilidad, alta resistencia específica, excelente resistencia a la corrosión, excelente resistencia a la fluencia a alta temperatura y buena resistencia a la fractura. Sin embargo, la aplicación de titanio es a menudo limitada por su coste relativamente alto. Los procesos de fundición conducen a productos de menores costes. Sin embargo, es difícil fundir estas aleaciones por técnicas de moldeo convencionales, debido a la reactividad de titanio a altas temperaturas, que reacciona con el crisol y molde. El proceso CCIM es actualmente el medio más eficaz de fusión de estas aleaciones. El CCIM es un proceso innovador en la que la fusión y colada del material se realiza bajo vacío o dentro de una atmósfera protectora y donde se utiliza un crisol refrigerado segmentado de cobre en vez de los habituales crisoles cerámicos para evitar cualquier tipo de reacción entre la carga y el crisol. El campo magnético generado por una bobina externa penetra a través de las ranuras del crisol y genera corrientes inducidas en la carga, las cuales son las responsables de la fusión debido al calentamiento Joule. Los inconvenientes de este proceso son la baja eficiencia debido al gran porcentaje de calor que se elimina por el sistema de refrigeración y el pequeño sobrecalentamiento del metal fundido, que puede causar problemas de solidificación. En esta tesis, hemos seleccionado el proceso CCIM para fundir y colar las aleaciones de titanio. El objetivo de esta tesis consiste en aumentar el conocimiento científico sobre el proceso CCIM tanto de un modo numérico como un modo experimental. La parte principal de la tesis se centra en el desarrollo de un modelo numérico de CCIM para optimizar de los principales parámetros del proceso. La tarea de optimizar sobrecalentamiento se enfrenta al reto de encontrar la combinación óptima de la altura del crisol a diámetro, número de espiras del inductor, diseño del crisol, intensidad de corriente y frecuencia. La variación de cualquiera de los factores mencionados influye en la forma del menisco del metal líquido y, como resultado, el patrón del fluido y el balance de energía. La segunda parte trata de la puesta en marcha de una instalación de CCIM y la fabricación de componentes de alto valor añadido de titanio. Como resultado de este trabajo se han logrado algunos objetivos, siendo los más importantes: a) Desarrollo de modelos numéricos del CCIM. b) Puesta a punto de una instalación CCIM. c) Fundición de piezas de titanio

A new navigation paradigm for virtual reality: the guided visit through a virtual world

The three main navigation paradigms for virtual worlds, i.e., free navigation, automatic tours, and multiuser navigation show important limitations when dealing with guided visits that involve interactive cooperation among several users in 3D virtual worlds over the Internet. In this paper, we present our research into this issue and some important results. We propose a new navigation paradigm denominated guided visit through a virtual world, where the capacity of a user guiding several remote users through the virtual world is enriched with the capacity to dynamically interchange the role of guiding between the connected users. The user that acts as a guide moves freely through the virtual world, and his/her movements are reproduced by the browsers of the other guided users. We also present the architecture and the system we developed that implements this paradigm, as well as its integration in a working realworld application that demonstrates its use

Hizkuntzaren prozesamendurako teknikak irakaskuntza arloan: galdera sortzaile automatikoa

Proiektu honen helburua hizkuntzaren prozesamendurako tresnek irakaskuntza arloan izan dezaketen erabilgarritasuna aztertzea da. Konkretuki, irakaskuntza materialen sorkuntzan laguntza handia eskaini dezake gaur egun hizkuntzaren prozesamenduak. Ariketak automatikoki prestatzeko sistemak, testu idatzien kalitatea hobetzen laguntzeko sistemak, laburpengintza sistemak... denetarik sortu da azken aldian. Baina, beste hizkuntzetarako buruturiko lana handia den arren euskararako buruturiko lana oso murritza da. Honek bultzatuta, proiektu honetan euskararako ariketak automatikoki sortzeko sistemetan azterketa bat burutuko da, galdera ariketak automatikoki sortzeko zehazki. Galdera hauen helburua ikasleek testuen ulermena lantzea izango da, horretarako testuko alderdi esanguratsuenei buruz galdetzen saiatuko direlarik. Ataza hau burutzeko bi ikerketa lerrotan sakonduko da: Alde batetik, testuko zati esanguratsuenak bilatzen lagunduko duen modulu bat inplementatuko da. Modulu honen helburua testuan agertzen diren termino garrantzitsuenak markatzea eta pisatzea izango da. Termino esanguratsuak bilatuz testuan garrantzitsu diren kontzeptuak zein izan daitezkeen jakin dezakegu. Hau abiapuntu egokia izan daiteke testu baten ulermena lantzen hasteko. Termino hauek markatzeko metodoa probabilitatean oinarriturikoa izango da, hizkuntzaren prozesamenduko alderdi estatistikoa jorratuz. Beste alde batetik, testuan bilaturiko termino garrantzitsuenen inguruan galderak automatikoki eraikiko dituen modulu bat inplementatuko da. Honen helburua esaldi bat eman eta ahalik eta galdera zentzuzko eta zuzenenak sortzea izango da. Honetarako erregeletan oinarrituriko modulu bat inplementatuko da, hizkuntzaren prozesamenduko alderdi linguistikoa jorratuz. Bi modulu hauekin probak burutu ahal izateko euskararako existitzen diren hainbat corpusen azterketa burutuko da. Proiekturako interesgarriak izan daitezkeen corpusak eskuratu eta beharrezko bada corpus berriak biltzeko helburua izango du azterketa honek. Amaitzeko, modulu bakoitzean modu independentean burutuko diren ebaluazioez gain ebaluazio orokor bat ere burutuko da. Bertan bi moduluak elkarrekin lotu eta eszenatoki erreal batean sorturiko aplikazioak izan dezakeen erabilgarritasuna aztertuko da

2D Image Features Detector And Descriptor Selection Expert System

Detection and description of keypoints from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for. We demonstrate that this method performs better than using just one method like ORB, SIFT or FREAK, despite being fairly slower.Comment: 10 pages, 5 figures, 5 table

3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts

Deep learning methods have been successfully applied to image processing, mainly using 2D vision sensors. Recently, the rise of depth cameras and other similar 3D sensors has opened the field for new perception techniques. Nevertheless, 3D convolutional neural networks perform slightly worse than other 3D deep learning methods, and even worse than their 2D version. In this paper, we propose to improve 3D deep learning results by transferring the pretrained weights learned in 2D networks to their corresponding 3D version. Using an industrial object recognition context, we have analyzed different combinations of 3D convolutional networks (VGG16, ResNet, Inception ResNet, and EfficientNet), comparing the recognition accuracy. The highest accuracy is obtained with EfficientNetB0 using extrusion with an accuracy of 0.9217, which gives comparable results to state-of-the art methods. We also observed that the transfer approach enabled to improve the accuracy of the Inception ResNet 3D version up to 18% with respect to the score of the 3D approach alone.This paper has been supported by the project ELKARBOT under the Basque program ELKARTEK, grant agreement No. KK-2020/00092

Histogram-Based Descriptor Subset Selection for Visual Recognition of Industrial Parts

This article deals with the 2D image-based recognition of industrial parts. Methods based on histograms are well known and widely used, but it is hard to find the best combination of histograms, most distinctive for instance, for each situation and without a high user expertise. We proposed a descriptor subset selection technique that automatically selects the most appropriate descriptor combination, and that outperforms approach involving single descriptors. We have considered both backward and forward mechanisms. Furthermore, to recognize the industrial parts a supervised classification is used with the global descriptors as predictors. Several class approaches are compared. Given our application, the best results are obtained with the Support Vector Machine with a combination of descriptors increasing the F1 by 0.031 with respect to the best descriptor alone.This paper has been supported by the project SHERLOCK under the European Union’s Horizon 2020 Research & Innovation programme, grant agreement No. 820689

Ensemble of 6 DoF Pose estimation from state-of-the-art deep methods.

Deep learning methods have revolutionized computer vision since the appearance of AlexNet in 2012. Nevertheless, 6 degrees of freedom pose estimation is still a difficult task to perform precisely. Therefore, we propose 2 ensemble techniques to refine poses from different deep learning 6DoF pose estimation models. The first technique, merge ensemble, combines the outputs of the base models geometrically. In the second, stacked generalization, a machine learning model is trained using the outputs of the base models and outputs the refined pose. The merge method improves the performance of the base models on LMO and YCB-V datasets and performs better on the pose estimation task than the stacking strategy.This paper has been supported by the project PROFLOW under the Basque program ELKARTEK, grant agreement No. KK-2022/00024

Influence of magnetic relaxation on magnetoelastic resonance-based detection

The phenomenon of magnetic relaxation in amorphous ferromagnetic alloys can result in an undesired time evolution of the magnetization that produces serious drawbacks in the use of these materials in sensor applications. The present work studies, at room temperature, the influence of magnetic relaxation on the performance of an amorphous ferromagnetic ribbon as the main element of a magnetoelastic resonance (MER)-based sensor. The time evolution was observed through the evolution of the MER signal, in particular through the variation experienced by the resonance frequency fr, which is the main parameter used for sensing. It is found that, after the bias field is changed to a given value, and under constant excitation conditions, fr increases with time in a typical relaxation behavior with a relaxation amplitude ∆fr and a relaxation time τ that depend on the excitation conditions. The amplitude of the excitation h turned out to be a key factor on the relaxation, since larger excitation field amplitudes (h ⩾ 100 mOe) result in a considerable decrease of relaxation times (τ < 460 s) and a reduction of the variation of the resonance frequency (∆fr < 77 Hz). The influence of this relaxation on the sensor performance and the possible approaches to overcome this problem are evaluated and applied to the case of a magnetoelastic sensor, operating as mass sensor, for monitoring a chemical precipitation reaction.The authors would like to thank the financial support from the Basque Government under μ4IIOT project (KK-2021/00082, Elkartek program) and the University Basque Research Groups Funding under Grant IT1479-22. Beatriz Sisniega acknowledges the financial support from the Basque Government through FPI Grant PRE_2021_2_0145

EuReCa ONE—27 Nations, ONE Europe, ONE Registry A prospective one month analysis of out-of-hospital cardiac arrest outcomes in 27 countries in Europe

AbstractIntroductionThe aim of the EuReCa ONE study was to determine the incidence, process, and outcome for out of hospital cardiac arrest (OHCA) throughout Europe.MethodsThis was an international, prospective, multi-centre one-month study. Patients who suffered an OHCA during October 2014 who were attended and/or treated by an Emergency Medical Service (EMS) were eligible for inclusion in the study. Data were extracted from national, regional or local registries.ResultsData on 10,682 confirmed OHCAs from 248 regions in 27 countries, covering an estimated population of 174 million. In 7146 (66%) cases, CPR was started by a bystander or by the EMS. The incidence of CPR attempts ranged from 19.0 to 104.0 per 100,000 population per year. 1735 had ROSC on arrival at hospital (25.2%), Overall, 662/6414 (10.3%) in all cases with CPR attempted survived for at least 30 days or to hospital discharge.ConclusionThe results of EuReCa ONE highlight that OHCA is still a major public health problem accounting for a substantial number of deaths in Europe.EuReCa ONE very clearly demonstrates marked differences in the processes for data collection and reported outcomes following OHCA all over Europe. Using these data and analyses, different countries, regions, systems, and concepts can benchmark themselves and may learn from each other to further improve survival following one of our major health care events

Hizkuntzaren prozesamendurako teknikak irakaskuntza arloan: galdera sortzaile automatikoa

Proiektu honen helburua hizkuntzaren prozesamendurako tresnek irakaskuntza arloan izan dezaketen erabilgarritasuna aztertzea da. Konkretuki, irakaskuntza materialen sorkuntzan laguntza handia eskaini dezake gaur egun hizkuntzaren prozesamenduak. Ariketak automatikoki prestatzeko sistemak, testu idatzien kalitatea hobetzen laguntzeko sistemak, laburpengintza sistemak... denetarik sortu da azken aldian. Baina, beste hizkuntzetarako buruturiko lana handia den arren euskararako buruturiko lana oso murritza da. Honek bultzatuta, proiektu honetan euskararako ariketak automatikoki sortzeko sistemetan azterketa bat burutuko da, galdera ariketak automatikoki sortzeko zehazki. Galdera hauen helburua ikasleek testuen ulermena lantzea izango da, horretarako testuko alderdi esanguratsuenei buruz galdetzen saiatuko direlarik. Ataza hau burutzeko bi ikerketa lerrotan sakonduko da: Alde batetik, testuko zati esanguratsuenak bilatzen lagunduko duen modulu bat inplementatuko da. Modulu honen helburua testuan agertzen diren termino garrantzitsuenak markatzea eta pisatzea izango da. Termino esanguratsuak bilatuz testuan garrantzitsu diren kontzeptuak zein izan daitezkeen jakin dezakegu. Hau abiapuntu egokia izan daiteke testu baten ulermena lantzen hasteko. Termino hauek markatzeko metodoa probabilitatean oinarriturikoa izango da, hizkuntzaren prozesamenduko alderdi estatistikoa jorratuz. Beste alde batetik, testuan bilaturiko termino garrantzitsuenen inguruan galderak automatikoki eraikiko dituen modulu bat inplementatuko da. Honen helburua esaldi bat eman eta ahalik eta galdera zentzuzko eta zuzenenak sortzea izango da. Honetarako erregeletan oinarrituriko modulu bat inplementatuko da, hizkuntzaren prozesamenduko alderdi linguistikoa jorratuz. Bi modulu hauekin probak burutu ahal izateko euskararako existitzen diren hainbat corpusen azterketa burutuko da. Proiekturako interesgarriak izan daitezkeen corpusak eskuratu eta beharrezko bada corpus berriak biltzeko helburua izango du azterketa honek. Amaitzeko, modulu bakoitzean modu independentean burutuko diren ebaluazioez gain ebaluazio orokor bat ere burutuko da. Bertan bi moduluak elkarrekin lotu eta eszenatoki erreal batean sorturiko aplikazioak izan dezakeen erabilgarritasuna aztertuko da