Disseny d'un simulador d'aviònica per a una cabina de DC9/A320 basat en flight simulator

Aquest projecte tracta sobre el desenvolupament d’un software que permeti enllaçar un simulador de vol i una cabina real de DC9, situada al Institut de la Illa dels Banyols al Prat de Llobregat - Barcelona. Mitjançant una llibreria externa al simulador, s’estableix una comunicació entre aquest i el programa en qüestió. Per una banda s’aconsegueix extreure les dades que es necessiten mostrar en la cabina del DC9 i per l’altra es poden generar certes fallades en el simulador a mode de pràctica per als estudiants que utilitzin el software. El programa ha estat desenvolupat mitjançant el llenguatge C# a través de la plataforma Microsoft Visual Studio 2010, versió 10.0.30319.1 RTMRel de ©2010 Microsoft Corporation.Anglès: This project is developing software capable of binding a flight simulator and a real DC9 cabin, located on the Island Institute of Banyols in Prat de Llobregat - Barcelona. Using an external library, it establishes a communication between the simulator and the program. On one hand, it extracts the data needed to show in the cabin of the DC9. On the other hand, certain faults can be generated in the simulator as a practice for students using the software. The program has been developed with C# language, through Microsoft Visual Studio 2010 platform, version 10.0.30319.1 RTMRel of ©2010 Microsoft Corporation

Planificació basada en escenaris i sumulacions del Model Operatiu Dirigit per la Demanda

El món de la gestió empresarial és un món que està en constant evolució, i és per aquest motiu que s'ha d'estar al dia de les novetats. En tot moment emergeixen noves metodologies disruptives que canvien la forma del joc. En aquest cas, el projecte s'enquadra en un nou model de negoci dirigit per la demanda. Aquest model de negoci canvia el paradigma convencional centrat en subministrament i costos, per un altre centrat en la demanda i flux d'informació i materials. A través d'un estudi de factors com: la llista de materials dels productes, la variabilitat de la demanda i subministrament que rep l'empresa, els temps de moviment de productes o la complexitat en les operacions internes; s'aconsegueix crear un disseny que desacobla en diferents parts tota la logística interna. Així, l'empresa és capaç d'adaptar-se contínuament a una cadena de subministrament cada vegada més complexa i volàtil. El Demand Driven Institute, institució formadora d'aquest nou model, marca uns criteris per definir si una companyia compleix els requisits per a ser totalment guiada per la demanda. Un d'aquests requisits és la capacitat de realitzar projeccions o simulacions de l'estat d'inventari en un període futur. Aleshores, a partir d'aquesta projecció és possible extreure diverses conclusions sobre les necessitats del negoci a més a més d'un pla previ d'actuació. Així doncs, aquest document detalla el procés d'implementació d'un conjunt de millores en un simulador de negoci dirigit per la demanda. La implementació és en Odoo, un ERP de codi obert utilitzat per milers d'empreses arreu del món.The world of business management is a world that is constantly evolving, and it is for this reason that you must be up to date with what is new. New disruptive methodologies are emerging at all times, changing the shape of the game. In this case, the project is part of a new business model driven by demand. This business model changes the conventional paradigm focused on supply and costs, for another focused on the demand and flow of information and materials. Through a study of factors such as: the list of materials of the products, the variability of the demand and supply received by the company, product lead times or complexity in internal operations; it is possible to create a design that decouples all the internal logistics in different parts. Thus, the company can continuously adapt to an increasingly complex and volatile supply chain. The Demand Driven Institute, the institution that created this new model, establishes criteria to define whether a company meets the requirements to be fully demand-driven. One of these requirements is the ability to make projections or simulations of the inventory status in a future period. Then, from this projection it is possible to draw various conclusions about the needs of the business, in addition to a previous plan of action. Thus, this document details the implementation process of a set of improvements in a demand-driven business simulator. The implementation is in Odoo, an open source ERP used by thousands of companies around the world

La formación profesional en Derecho mediante el Aprendizaje Basado en Problemas

Training professionals in Law has been traditionally developed according to different frames and kinds of learning experiences. Nevertheless, such span of learning potential and different professional frames has not been historically assumed by the Spanish universities who conducted a common curricular model, both centralized and focused mainly to a content memorization, according to a dogmatic interpretation of them. Despite the former, there are different qualitatively contrasted teaching strategies, which can be implemented in Law professional training. PBL is one of the best known approaches among them. In this paper different relevant issues giving teaching such approach are reviewed. The article analyzes the student’s positive opinions and values rising from an experience of PBL. Such values reflect its significant contribution to a deep learning and as a strategic way for enhancing their sense of professionalism. The students’ empirical data shows how the PBL strategy improves  their capacities in learning and solving out professional problems. Thus, it seems to exert a positively impact in how manage their learning autonomy as students. The collected data shows how this happen due to the facilitation of the peer-interaction and the possibility of having a clear action-oriented approach.La formación en Derecho ha sido tradicionalmente una formación que puede orientarse y resolverse en un abanico de posibilidades profesionales muy elevado. Sin embargo esta amplitud y diversidad de referentes profesionales no ha sido históricamente asumido por el modelo de formación general seguido por las universidades españolas, centralizado y orientado a un aprendizaje fundamentalmente memorístico de los contenidos a los que se somete a un tratamiento muy dogmático. No obstante existen enfoques estratégicos distintos, de calidad y contrastados, para la formación profesional en Derecho. Entre ellos, destaca el enfoque conocido como el Aprendizaje Basado en Problemas (ABP). En este artículo se analizan los referentes que aportan sentido y valor a esta opción estratégica, se validan en datos empíricos las opiniones de los estudiantes y se analizan aquellos aspectos susceptibles de atención en su implementación y desarrollo en las aulas. Los estudiantes consideran que adquieren conocimientos y competencias que les ayudarán en la práctica profesional futura, valorando positivamente el reforzamiento de su autonomía, la interacción con los compañeros y con el profesor y el poder disponer de una “orientación hacia la acción” más o menos clara

Vocational training in law by the Problem-Based Learning (PBL)

La formación en Derecho ha sido tradicionalmente una formación que puede orientarse y resolverse en un abanico de posibilidades profesionales muy elevado. Sin embargo esta amplitud y diversidad de referentes profesionales no ha sido históricamente asumido por el modelo de formación general seguido por las universidades españolas, centralizado y orientado a un aprendizaje fundamentalmente memorístico de los contenidos a los que se somete a un tratamiento muy dogmático. No obstante existen enfoques estratégicos distintos, de calidad y contrastados, para la formación profesional en Derecho. Entre ellos, destaca el enfoque conocido como el Aprendizaje Basado en Problemas (ABP). En este artículo se analizan los referentes que aportan sentido y valor a esta opción estratégica, se validan en datos empíricos las opiniones de los estudiantes y se analizan aquellos aspectos susceptibles de atención en su implementación y desarrollo en las aulas. Los estudiantes consideran que adquieren conocimientos y competencias que les ayudarán en la práctica profesional futura, valorando positivamente el reforzamiento de su autonomía, la interacción con los compañeros y con el profesor y el poder disponer de una “orientación hacia la acción” más o menos clara.Training professionals in Law has been traditionally developed according to different frames and kinds of learning experiences. Nevertheless, such span of learning potential and different professional frames has not been historically assumed by the Spanish universities who conducted a common curricular model, both centralized and focused mainly to a content memorization, according to a dogmatic interpretation of them. Despite the former, there are different qualitatively contrasted teaching strategies, which can be implemented in Law professional training. PBL is one of the best known approaches among them. In this paper different relevant issues giving teaching such approach are reviewed. The article analyzes the student’s positive opinions and values rising from an experience of PBL. Such values reflect its significant contribution to a deep learning and as a strategic way for enhancing their sense of professionalism. The students’ empirical data shows how the PBL strategy improves  their capacities in learning and solving out professional problems. Thus, it seems to exert a positively impact in how manage their learning autonomy as students. The collected data shows how this happen due to the facilitation of the peer-interaction and the possibility of having a clear action-oriented approach

Active flow control for three-dimensional cylinders through deep reinforcement learning

This paper presents for the first time successful results of active flow control with multiple independently controlled zero-net-mass-flux synthetic jets. The jets are placed on a three-dimensional cylinder along its span with the aim of reducing the drag coefficient. The method is based on a deep-reinforcement-learning framework that couples a computational-fluid-dynamics solver with an agent using the proximal-policy-optimization algorithm. We implement a multi-agent reinforcement-learning framework which offers numerous advantages: it exploits local invariants, makes the control adaptable to different geometries, facilitates transfer learning and cross-application of agents and results in significant training speedup. In this contribution we report significant drag reduction after applying the DRL-based control in three different configurations of the problem.Comment: ETMM14 2023 conference proceeding pape

A data-driven wall-shear stress model for LES using gradient boosted decision trees

With the recent advances in machine learning, data-driven strategies could augment wall modeling in large eddy simulation (LES). In this work, a wall model based on gradient boosted decision trees is presented. The model is trained to learn the boundary layer of a turbulent channel flow so that it can be used to make predictions for significantly different flows where the equilibrium assumptions are valid. The methodology of building the model is presented in detail. The experiment conducted to choose the data for training is described. The trained model is tested a posteriori on a turbulent channel flow and the flow over a wall-mounted hump. The results from the tests are compared with that of an algebraic equilibrium wall model, and the performance is evaluated. The results show that the model has succeeded in learning the boundary layer, proving the effectiveness of our methodology of data-driven model development, which is extendable to complex flows.SR acknowledges the financial support by the Ministerio de Ciencia y Innovación y Universidades, for the grant, Ayudas para contratos predoctorales para la formación de doctores (Ref: BES-2017-081982). OL has been partially supported by a Ramon y Cajal postdoctoral contract (Ref: RYC2018-025949-I). We also acknowledge the Barcelona Supercomputing Center for awarding us access to the MareNostrum IV machine based in Barcelona, Spain.Peer ReviewedPostprint (author's final draft

Active flow control for three-dimensional cylinders through deep reinforcement learning

This paper presents for the first time successful results of active flow control with multiple independently controlled zero-net-mass-flux synthetic jets. The jets are placed on a three-dimensional cylinder along its span with the aim of reducing the drag coefficient. The method is based on a deep-reinforcement-learning framework that couples a computational-fluid-dynamics solver with an agent using the proximal-policy-optimization algorithm. We implement a multi-agent reinforcement- learning framework which offers numerous advantages: it exploits local invariants, makes the control adaptable to different geometries, facilitates transfer learning and cross-application of agents and results in significant training speedup. In this contribution we report significant drag reduction after applying the DRL-based control in three different configurations of the problem.Ricardo Vinuesa acknowledges funding by the ERC through Grant No. “2021-CoG-101043998, DEEPCONTROL”.Peer ReviewedPostprint (published version

Deep reinforcement learning for flow control exploits different physics for increasing Reynolds-number regimes

Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. This technique has been recently used to solve problems related to flow control. In this work, an ANN trained through a DRL agent is used to perform active flow control. Two-dimensional simulations of the flow around a cylinder are conducted and an active control based on two jets located on the walls of the cylinder is considered. By gathering information from the flow surrounding the cylinder, the ANN agent is able to learn effective control strategies for the jets, leading to a significant drag reduction. In the present work, a Reynolds-number range beyond those previously considered is studied and compared with results obtained using classical flow-control methods. Significantly different nature in the control strategies is identified by the DRL as the Reynolds number Re increases. For Re <= 1000 the classical control strategy based on an opposition control relative to the wake oscillation is obtained. For Re = 2000 the new strategy consists of an energisation of the boundary layers and the separation area, which modulate the flow separation and reduce drag in a fashion similar to that of the drag crisis, through a high frequency actuation. A cross-application of agents is performed for a flow at Re = 2000, obtaining similar results in terms of drag reduction with the agents trained at Re = 1000 and 2000. The fact that two different strategies yield the same performance make us question whether this Reynolds number regime (Re = 2000) belongs to a transition towards a nature-different flow which would only admit a high-frequency actuation strategy to obtain drag reduction. This finding allows the application of ANNs trained at lower Reynolds numbers but comparable in nature, saving computational resources.Comment: 26 pages, 5 figures, submitted to MDP

Highly sensitive MLH1 methylation analysis in blood identifies a cancer patient with low-level mosaic MLH1 epimutation

Constitutional MLH1 methylation (epimutation) is a rare cause of Lynch syndrome. Low-level methylation (<= 10%) has occasionally been described. This study aimed to identify low-level constitutional MLH1 epimutations and determine its causal role in patients with MLH1-hypermethylated colorectal cancer. Eighteen patients with MLH1-hypermethylated colorectal tumors in whom MLH1 methylation was previously undetected in blood by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) were screened for MLH1 methylation using highly sensitive MS-melting curve analysis (MS-MCA). Constitutional methylation was characterized by different approaches. MS-MCA identified one patient (5.6%) with low-level MLH1 methylation ( 1%) in blood and other normal tissues, which was confirmed by clonal bisulfite sequencing in blood. The patient had developed three clonally related gastrointestinal MLH1-methylated tumor lesions at 22, 24, and 25 years of age. The methylated region in normal tissues overlapped with that reported for other carriers of constitutional MLH1 epimutations. Low-level MLH1 methylation and reduced allelic expression were linked to the same genetic haplotype, whereas the opposite allele was lost in patient's tumors. Mutation screening of MLH1 and other hereditary cancer genes was negative. Herein, a highly sensitive MS-MCA-based approach has demonstrated its utility for the identification of low-level constitutional MLH1 epigenetic mosaicism. The eventual identification and characterization of additional cases will be critical to ascertain the cancer risks associated with constitutional MLH1 epigenetic mosaicism