Reduction of Petri net maintenance modeling complexity via Approximate Bayesian Computation

This paper is part of the ENHAnCE ITN project (https://www.h2020-enhanceitn.eu/) funded by the European Union's Horizon 2020 research and innovation programme under the Marie SklodowskaCurie grant agreement No. 859957. The authors would like to thank the Lloyd's Register Foundation (LRF), a charitable foundation in the U.K. helping to protect life and property by supporting engineeringrelated education, public engagement, and the application of research. The authors gratefully acknowledge the support of these organizations which have enabled the research reported in this paper.The accurate modeling of engineering systems and processes using Petri nets often results in complex graph representations that are computationally intensive, limiting the potential of this modeling tool in real life applications. This paper presents a methodology to properly define the optimal structure and properties of a reduced Petri net that mimic the output of a reference Petri net model. The methodology is based on Approximate Bayesian Computation to infer the plausible values of the model parameters of the reduced model in a rigorous probabilistic way. Also, the method provides a numerical measure of the level of approximation of the reduced model structure, thus allowing the selection of the optimal reduced structure among a set of potential candidates. The suitability of the proposed methodology is illustrated using a simple illustrative example and a system reliability engineering case study, showing satisfactory results. The results also show that the method allows flexible reduction of the structure of the complex Petri net model taken as reference, and provides numerical justification for the choice of the reduced model structure.European Commission 859957Lloyd's Register Foundation (LRF), a charitable foundation in the U.K

Notas introductorias sobre fiabilidad estructural

Libro de apuntes de apoyo a la docencia para el curso "Fiabilidad y Daño Continuo" del Máster de Estructuras (código M63/56/1​)​.El material que se recoge en este documento está especialmente concebido para sentar las bases teóricas así como para reiterar acerca de los fundamentos matemáticos de la fiabilidad. Al mismo tiempo, los autores pretenden presentar un material que, en un futuro, puede llegar a ser un libro de texto sobre ingeniería de fiabilidad, en el cual se aborde la fiabilidad desde una perspectiva más amplia, con especial atención a la fiabilidad de sistemas. Finalmente, conviene recordar al alumno que debe ampliar y contrastar el contenido a través del material de referencia recomendado en el apartado de bibliografía

Robust optimal sensor configuration using the value of information

This paper is part of the SAFE-FLY project that has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie (Grant Agreement No. 721455). The authors acknowledge the support acquired by the Brazilian National Council of Research CNPq (Grant Agreement ID: 314168/2020-6).Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for (1) uncertainties from updatable and nonupdatable parameters, (2) variability of the objective function with respect to nonupdatable parameters, and (3) the spatial correlation between sensors. The optimal sensor configuration is obtained by maximizing the expected value of information, which leads to a cost-benefit analysis that entails model parameter uncertainties. The proposed methodology is demonstrated on an application of structural health monitoring in plate-like structures using ultrasonic guided waves. We show that accounting for uncertainties is critical for an accurate diagnosis of damage. Furthermore, we provide critical assessment of the role of both the effect of modeling and measurement uncertainties and the optimization algorithm on the resulting sensor placement. The results on the health monitoring of an aluminum plate indicate the effectiveness and efficiency of the proposed methodology in discovering optimal sensor configurations.European Union's Horizon 2020 Research and Innovation Programme 721455Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 314168/2020-

Notas sobre mécanica de materiales compuestos

Estas notas han sido preparadas como apoyo a los estudiantes del Máster en Ingeniería de Estructuras de la Universidad de Granada, con el objetivo de que encuentren en ellas un manual básico para adentrarse en el cálculo de materiales compuestos. También van dirigidos a aquellos estudiantes de ingeniería que deciden basar su proyecto fin de carrera en estos materiales

Curso de introducción a estructuras de fibra de carbono

Material de apoyo a la docencia.Actualmente la utilización de materiales avanzados de alta eficacia, como los composites de fibra de carbono o vidrio originarios de la industria aeronáutica y aeroespacial, se presenta como alternativa viable en el diseño de estructuras de ingeniería civil en las que las exigencias de ligereza, durabilidad y tiempo de construcción se convierten en aspectos críticos del diseño. Desde los últimos 10 años se está asistiendo a un aumento importante a nivel mundial de las aplicaciones de materiales avanzados en construcción, y en particular en estructuras de ingeniería y arquitectura civil: puentes, estructuras de arquitectura singular, estructuras offshore, sistemas de alma- cenamiento energético, etc. Estados Unidos, Japón, Suiza, Reino Unido y Dinamarca ente otros países tecnológicamente avanzados, cuentan ya con numerosos puentes y estructuras de ingeniería realizadas íntegramente con estos materiales. Así mismo, en estos países se ha creado una red empresarial en torno a los nuevos materiales que está suponiendo en ciertos casos un importante impulso económico y una revolución tecnológica en el sector de la construcción.Este curso es una introducción a la tecnología y diseño, y se plantea desde un punto de vista divulgativo y práctico de forma que el alumno no solo conozca una nueva tecnología sino además un novedoso sector de la industria con nuevas oportunidades.

Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme

In this paper, defect detection and identification in aluminium joints is investigated based on guided wave monitoring. Guided wave testing is first performed on the selected damage feature from experiments, namely, the scattering coefficient, to prove the feasibility of damage identification. A Bayesian framework based on the selected damage feature for damage identification of three- dimensional joints of arbitrary shape and finite size is then presented. This framework accounts for both modelling and experimental uncertainties. A hybrid wave and finite element approach (WFE) is adopted to predict the scattering coefficients numerically corresponding to different size defects in joints. Moreover, the proposed approach leverages a kriging surrogate model in combination with WFE to formulate a prediction equation that links scattering coefficients to defect size. This equation replaces WFE as the forward model in probabilistic inference, resulting in a significant enhancement in computational efficiency. Finally, numerical and experimental case studies are used to validate the damage identification scheme. An investigation into how the location of sensors can impact the identified results is provided as well.European Union’s Horizon 2020 Marie Skłodowska-Curie 859957Science and Technology Development Fund, Macau SAR (File No.: FDCT/0101/2021/A2, FDCT/001/2021/AGJ and SKL-IOTSC(UM)-2021-2023

A wind turbine blade leading edge rain erosion computational framework

Blades are one of the most important components, in terms of capital and operational costs, of wind turbines. The experienced acquired by the industry in the latest decades has shown that leading edge erosion is a problem of concern that impacts the reliability of the blade and the power production of the turbine, among others. This study provides a framework to estimate leading edge erosion evolution and energy production degradation throughout time to apply in operation and maintenance decision making. It is based on the generation of synthetic wind and rain data based on observations from the site and ERA5 reanalysis data, whirling arm test data of erosion protection coatings, along with aerodynamic polar curves for clean and eroded airfoils of the blade. Rain erosion is calculated based on impingement, and assumed to be linearly accumulated using the Palmgren–Miner rule. Synthetic wind and rain time series are used to evaluate 25-year erosion degradation and energy production scenarios. A case study using the 5MW NREL’s wind turbine located in the North Sea has been analysed with the proposed framework showing maximum annual energy production losses in the range of 1.6–1.75% and first erosion failure between years 2 and 6.European Commission 859957German Federal Ministry of Economic Affairs and Energy (BMWi

Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

This work was supported by the contract OTRI-4408 between the University of Granada and the Royal Academy of Engineering of Spain financed by Ferrovial S.A. Eugenio Martinez Camara was supported by the Spanish Government fellowship programme Juan de la Cierva Incorporacion (IJC2018-036092-I).The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs) as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial intelligence and other digital technologies have already changed several areas of modern society, and they could be very useful to reach these sustainable goals. In this paper we propose a novel decision making model based on surveys that ranks recommendations on the use of different artificial intelligence and related technologies to achieve the SDGs. According to the surveys, our decision making method is able to determine which of these technologies are worth investing in to lead new research to successfully tackle with sustainability challenges.University of Granada - Ferrovial S.A. OTRI-4408Royal Academy of Engineering of Spain - Ferrovial S.A. OTRI-4408Spanish Government fellowship programme Juan de la Cierva Incorporacion IJC2018-036092-

Lamb wave-based damage indicator for plate-like structures

Structural health monitoring based on ultrasonics typically involves complex data analysis. Ultrasound monitoring based on Lamb waves techniques are extensively used nowadays due to their efficiency in exploring large areas with relatively small attenuation. In recent years, baseline based methods have been developed to identify structural damage based on the mismatch between the measured signal and the baseline one. To this end, complex time-frequency transformations are required to obtain signal features such as the time of arrival or the energy content, as indicators of damage onset and growth. Notwithstanding this, on-board applications require highly efficient processing techniques due to information storage and exchange limitations. This paper proposes a very high efficiency signal processing methodology to obtain a novel cumulative damage factor using Lamb wave raw data. The new methodology has been tested using ultrasonic and damage data from a fatigue test in carbon-epoxy composite laminates. The data is taken from NASA Prognostics data repository. In view of the results, the method is able to efficiently detect the onset and extent of damage from early stages of degradation. Moreover, the results demonstrate a remarkable agreement between the growth of delamination area and the predicted cumulative damage factor

Incorporación del m-learning en el proceso de aprendizaje en enseñanzas técnicas

El documento recoge la memoria del proyecto de innovación docente que ha consistido en la aplicación de metodologías innovadoras de dinamización en las clases teóricas en la asignatura Análisis de Estructuras del Grado en Ingeniería Civil. Esta asignatura, aun habiendo incluido anteriormente proyectos para la mejora de la docencia (tales como la incorporación de técnicas de aprendizaje semipresencial o B-learning) que permitieran a los estudiantes aproximarse a la resolución de problemas complejos y cercanos a la realidad, históricamente ha basado su docencia teórica y de resolución de problemas en métodos tradicionales debido a su elevada complejidad.The project has been designed considering the use of mobile devices in the learning process (mobile learning or m-learning) during the lectures and the practical lessons, and also for communication.Departamento de Mecánica de Estructuras e Ingeniería Hidráulic