Acoustic characterization of absorbing materials using dynamic mode decomposition techniques

[Abstract] In general, the simulation of physical phenomena through numerical methods tends to be a computationally intensive task, but this is particularly true in the eld of acoustics. Due to the fast changing derivatives and the innately second order formulation, a ne mesh needs to be used, and in order for the time discretization to be well behaved, a small time step needs to be chosen as well. In addition to this, the testing of acoustic propagation in a single domain is rarely of interest, since most applications involve the design of acoustic barriers or transmitters, which means that most problems solved in the eld involve couplings. One of the coupled mediums is usually a uid, and it is common for the other to be a porous material since they are the most e ective sound absorbers. It is in fact because of this absorption that the porous models can get very complex. Time convolutions are usually needed for the modeling of high frequency noise, which makes the simulation process very costly. It becomes apparent that a reduced order method that is able to cut the computation time down is a worthwhile tool to have. Among the reduced order methods (ROMs) the chosen one is a method that is able to make predictions into the future from a reduced amount of snapshots. Dynamic Mode Decomposition (DMD) is a technique developed in 2010 by Peter Schmid [47]. It is based on a Singular Value Decomposition (SVD) into which dynamics are added, making it able to not only reconstruct available data using a reduced order representation, but also able to expand the dimensionality in the time dimension in order to make predictions about the future. This means that a simulation spanning a shorter time can be run and the remaining sector of the time domain can be predicted by DMD, which adds up to a signi cantly faster process. DMD is a data-driven method, which means that no information about the dynamic model is needed, only a series of snapshots are used. It has been used in the uid dynamics community, where it originated, and a number of elds including video processing [21, 14], epidemiology [41] and neuroscience [5]. A number of acoustic models are developed in this work, and then, they are used to test the capabilities of DMD in acoustic problems and to nd its limitations. The motivation of this problem arises from a collaboration between the Technological Institute for Industrial Mathematics (ITMATI) and Micro own Technologies through the ROMSOC project. Together they started a project that became Ashwin Nayak's PhD thesis, in which the objective is to design a multilayer windshield for an acoustic probe by modeling the acoustic eld both inside and outside of the windshield considering acoustic and other physical phenomena such as uid, thermal and poro-elastic e ects in an unbounded domain. The present master thesis project reduces Nayak's problem to a 1D simpli ed problem and attempts to develop a method that could be, in the future, generalized to his problem and reduce the computation time needed.Traballo fin de mestrado (UDC.INF). Matemática industrial. Curso 2019/202

Simulation-driven engineering for the management of harmful algal and cyanobacterial blooms

Harmful Algal and Cyanobacterial Blooms (HABs), occurring in inland and maritime waters, pose threats to natural environments by producing toxins that affect human and animal health. In the past, HABs have been assessed mainly by the manual collection and subsequent analysis of water samples and occasionally by automatic instruments that acquire information from fixed locations. These procedures do not provide data with the desirable spatial and temporal resolution to anticipate the formation of HABs. Hence, new tools and technologies are needed to efficiently detect, characterize and respond to HABs that threaten water quality. It is essential nowadays when the world's water supply is under tremendous pressure because of climate change, overexploitation, and pollution. This paper introduces DEVS-BLOOM, a novel framework for real-time monitoring and management of HABs. Its purpose is to support high-performance hazard detection with Model Based Systems Engineering (MBSE) and Cyber-Physical Systems (CPS) infrastructure for dynamic environments

Enhancing EJsS with extension plugins

Easy JavaScript Simulations (EJsS) is an open-source tool that allows teachers with limited programming experience to straightforwardly bundle an interactive computer science or engineer simulation in an HTML+ JavaScript webpage. Its prominent place in Physics (where it has won several prizes) should not hinder its application in other fields (such as building the front-end of remote laboratories or learning analytics) after having adapted part of the functionality of EJsS to them. To facilitate the future inclusion of new functionalities in EJsS, this paper presents a new version of this tool that allows the enhancement of EJsS, letting it incorporate new tools and change its graphical user interface, by means of extension plugins (special software libraries). To illustrate the benefits of this distributable self-contained non-intrusive strategy, the paper (a) discusses the new methodological possibilities that the Plugins bring to EJsS developers and users, and (b) presents three plugins: one to support the plugin management and the others to easily set up a streamlined remote laboratory. Moreover, the paper also presents the main characteristics of that remote lab to allow readers take advantage of EJsS and the three plugins to set up new online experiments for their students quickly

Fluid simulation methods applied to lakes and reservoirs

[Resumen] Existe una gran variedad de m´etodos para simular un fluido incompresible como el agua. Estos se pueden clasificar en diferentes tipos según utilicen partículas, una malla o una combinación de ambos como soporte de la simulación; o según el enfoque en que se aborde la incompresibilidad del fluido (débilmente compresible o realmente incompresible). Con esta variedad de opciones, es necesario comparar los métodos para asegurar la utilización del más adecuado, considerando las ventajas y desventajas de cada uno. Por ello, se analizan de manera general algunos de estos métodos con un escenario específico en mente: un lago con una entrada y una salida de agua en régimen estacionario. El objetivo es discernir cuál de estos métodos es mejor para llevar a cabo dicha simulación, o tiene el menor número de problemas en cuanto a las condiciones de contorno, aplicación de fuerzas externas, o inestabilidades numéricas. Finalmente, se presenta un caso de prueba sencillo empleando la opción considerada más adecuada. Los resultados de este artículo se emplearán en futuros trabajos en el estudio de blooms de cianobacterias en dichos cuerpos acuáticos.[Abstract] There are various methods to simulate an incompressible fluid such as water. These can be grouped into different types according to their simulation framework (grid-based, particle-based, or mixed) or how they approach the fluid’s incompressibility (weakly compressible or truly incompressible). Facing such variety to choose from, a comparison between them becomes a must to ensure the method used in the simulation scenario is adequate, considering their advantages and disadvantages in the different aspects of the simulation. A general analysis of some of these methods will be done with a specific scenario in mind: a stationary lake with one water entrance and one exit. The aim will be to discern which of the studied methods is better suited to carry out this simulation with the minor problems regarding boundary conditions, external forces treatment, or numerical instabilities. Finally, a simple test case for the more adequate method is presented. This work will be ultimately used in the study of lake cyanobacteria blooms.Gobierno de la Comunidad de Madrid; Y2020/TCS-6420Ministerio de Ciencia e Innovación; TED2021-130123B-I0

Development of an eIOT Framework Using DEVS: Cyanobacterial Bloom Alert and Management System

[Resumen] Se utiliza Discrete Event System Specification (DEVS) como herramienta para modelar, simular, desarrollar y desplegar un proyecto acorde al paradigma Internet de la Cosas Medioambiental (EIoT). El software/hardware se diseña y desarrolla con una arquitectura típica de IoT, por capas: Cloud, Fog, Edge y Things. Se presenta como caso de aplicación un sistema para monitorizar y controlar Unmaned Surface Vehicles (USVs) que toman medidas en masas de agua dulce con el objetivo de monitorizar y predecir Blooms de cianobacterias. Modelar un proyecto EIoT utilizando DEVS permite un diseño software progresivo, que a su vez facilita mezclar elementos simulados y reales. Este diseño dirigido por modelos permite refinar los modelos mediante simulaciones, para facilitar el despliegue final del sistema real.[Abstract] The Discrete Event System Specification (DEVS) is used to model, simulate, develop and deploy a project according to the Environmental Internet of Things (EIoT) paradigm. The software and hardware are designed and developed following a typical IoT architecture, with layers: Cloud, Fog, Edge and Things. As an application case, a system to monitor and control unmanned surface vehicles (USVs) that perform measurements in freshwater bodies to monitor and predict cyanobacteria blooms is presented. Modeling an EIoT project using DEVS enables a progressive design of the software/hardware, which in turn facilitates the coexistence of simulated and real elements. This model-based design allows the models to be refined through simulations, facilitating the final deployment of the real system.Este trabajo ha sido financiado a través de los proyectos IA-GES-BLOOM-CM (Ref: Y2020/TCS6420) y AMPBAS RETOSINVESTIGACIÓN (Ref: RTI2018-098962-B-C21)https://doi.org/10.17979/spudc.978849749841