Symmetry in Structural Health Monitoring

In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment

LM-PAFOG - a new three-dimensional fog forecast model with parametrised microphysics

The presence of fog and low clouds in the lower atmosphere can have a critical impact on both airborne and ground transports and is often connected with serious accidents. An improvement of fog forecasts in terms of localisation, duration and variations in visibility therefore holds an immense operational value for the field of transportation in conditions of low visibility. However, fog is generally a small scale phenomenon which is mostly affected by local advective transport, turbulent mixing at the surface as well as its microphysical structure. Therefore, a detailed description of the microphysical processes within the three-dimensional dynamical core of the forecast model is necessary. For this purpose, a new microphysical parametrisation based on the one-dimensional fog forecast model, PAFOG, was implemented in the “Lokal Modell” (LM), the nonhydrostatic mesoscale model of the German Meteorological Service. The implementation of cloud water droplets as a new prognostic variable allows a detailed definition of the sedimentation processes and the variations in visibility. A horizontal resolution of 2.8 km and a vertical resolution of 4 m describe the boundary layer processes, forecasted by LM-PAFOG. In the framework of the COST 722 intercomparison campaign, the evaluation of the LM-PAFOG forecasts, based on statistical study and case studies, points out the variability of the model performance between day and night time periods. Moreover, the comparisons with other fog forecast systems highlight the decisive influence of an adapted data assimilation scheme for the high grid resolution model, as well as the necessary calibration of a visibility parametrisation. Finally, due to the lack of information concerning the observed fog spatial extension, a verification scheme with MSG satellite products for fog and low stratus is tested.LM-PAFOG: ein neues dreidimensionales Nebelvorhersagemodell mit parametrisierter Mikrophysik Nebel und tief hängende Wolken beeinträchtigen häufig den Luft- und Straßenverkehr; schwere Unfälle sind immer wieder die Folge. Vor diesem Hintergrund leistet eine verbesserte Nebelvorhersage, bezüglich der Lokalisierung von Nebelereignissen, der Vorhersage von der Nebeldauer sowie der Schwankungen der Sichtweite, einen immensen Beitrag zur Effizienz im Transportwesen. Nebel als ein kleinräumiges Phänomen wird durch advektiven Transport, turbulente Durchmischung an der Erdoberfläche, sowie mikrophysikalische Prozesse beeinflusst. Daher ist für eine realistische Nebelvorhersage eine detaillierte Beschreibung der mikrophysikalischen Prozesse unerlässlich. Eine verbesserte Beschreibung der mikrophysikalischen Prozesse wurde durch die Kopplung des eindimensionalen Nebelmodells PAFOG mit parametrisierter Nebelmikrophysik mit dem mesoskaligen numerischen Wettervorhersagemodell des Deutschen Wetterdienstes, erreicht. Durch die Einführung einer neuen prognostischen Variable, die Wolkenkondensationskerne, werden die Sedimentationsprozesse sowie die Sichtweitenschwankungen besser beschrieben. Neben der erweiterten Mikrophysik zeichnet sich das Nebelmodell LM-PAFOG vor allem durch eine höhere horizontale Auflösung von 2.8 km und eine feine vertikale von 4 m aus, wodurch eine bessere Beschreibung der Grenzschichtprozesse erreicht wird. Mit Hilfe der im Rahmen der COST 722 durchgeführten Vergleichsstudie wurde LM-PAFOG evaluiert. Eine statistische Analyse sowie einige Fallstudien zeigen die Modellvariabilität zwischen Tag und Nacht. Auch der Vergleich mit anderen europäischen Nebelvorhersagemodellen zeigt die herausragende Bedeutung eines adaptiven Datenassimilationsschemas für hoch aufgelöste Modelle. Des weiteren hat die Kalibrierung der Sichtweitenparametrisierung einen großen Einfluss auf die Nebelvorhersage. Da es nur wenig Beobachtungen gibt, die die Nebelausbreitung beschreiben, wurde ein Verifikationsschema auf Grundlage von MSG-Satelliten für Nebel und tief hängenden Stratus getested.LM-PAFOG: un nouveau modèele tridimensionnel de prévision du brouillard à microphysique parametréeeLa présence de brouillard et de nuages bas occasionne des perturbations des transports aériens et routiers et peut être à l'origine d'accidents graves. Une amélioration des prévisions de brouillard en termes de localisation, durée de l'épisode et des variations de visibilité serait un apport considérable pour la gestion des transports et la sécurité en condition de visibilité réduite. Cependant, le brouillard est en général un phénomène de petite échelle, influencé aussi bien par les transports advectifs locaux, les échanges turbulents à la surface ainsi que par sa structure microphysique. Une description détaillée des processus microphysiques dans une dynamique atmosphérique tridimensionnelle est essentielle. Une paramétrisation microphysique basée sur le modèle unidimensionnel de prévision du brouillard, PAFOG, a été introduite dans le modèle méso-échelle tridimensionnel non-hydrostatique, "Lokal Modell". L'introduction de la concentration en goutte d'eau nuageuse comme nouvelle variable pronostique donne une description detaillée des processus de sédimentation et des variations de la visibilité. De plus, une résolution horizontale de 2.8 km et une résolution verticale de 4 m décrivent les processus de la couche limite simulés par LM-PAFOG. Dans le cadre de la campagne d'intercomparaison COST 722, l'évaluation des prévisions de LM-PAFOG, basée sur une étude statistique et des études de cas, montre la dispersion des performances du modèle entre les périodes de jour et de nuit. De plus, des comparaisons avec d'autres systèmes de prévision du brouillard pointent l'influence d'un schéma d'assimilation adapté pour un modèle ayant une haute résolution, ainsi que celle de la calibration nécessaire de la paramétrisation de la visibilité. Enfin, à cause d'un manque d'informations concernant l'extention spatial du brouillard observé, un schéma de verification utilisant des produits satellites pour le brouillard et les stratus bas a été testé. Mots clés: brouillard, visibilité, modélisation tridimensionnelle, microphysique paramétrée, "Lokal Modell", PAFOG, projet COST 722, inter-comparaison de modèles, vérification satellite

Landing site reachability and decision making for UAS forced landings

After a huge amount of success within the military, the benefits of the use of unmanned aerial systems over manned aircraft is obvious. They are becoming cheaper and their functions advancing to such a point that there is now a large drive for their use by civilian operators. However there are a number of significant challenges that are slowing their inevitable integration into the national airspace systems of countries. A large array of emergency situations will need to be dealt with autonomously by contingency management systems to prevent potentially deadly incidences. One such emergency situation that will need autonomous intervention, is the total loss of thrust from engine failure. The complex multi faceted task of landing the stricken aircraft at a potentially unprepared site is called a forced landing. This thesis presents methods to address a number of critical parts of a forced landing system for use by an unmanned aerial system. In order for an emergency landing site to be considered, it needs to be within glide range. In order to find a landing site s reachability from the point of engine failure the aircraft s glide performance and a glide path must be known. A method by which to calculate the glide performance, both from aircraft parameters or experiments is shown. These are based on a number of steady state assumptions to make them generic and quick to compute. Despite the assumptions, these are shown to have reasonable accuracy. A minimum height loss path to the landing site is defined, which takes account of a steady uniform wind. While this path is not the path to be flown it enables a measure of how reachable a landing site is, as any extra height the aircraft has once it gets to the site makes a site more reachable. It is shown that this method is fast enough to be run online and is generic enough for use on a range of aircraft. Based on identified factors that make a landing site more suitable, a multi criteria decision making Bayesian network is developed to decide upon which site a unmanned aircraft should land in. It can handle uncertainty and non-complete information while guaranteeing a fast reasonable decision, which is critical in this time sensitive situation. A high fidelity simulation environment and flight test platform are developed in order to test the performance of the developed algorithms. The test environments developed enable rapid prototyping of algorithms not just within the scope of this thesis, but on a range of vehicle types. In simulation the minimum height loss paths show good accuracy, for two completely different types of aircraft. The decision making algorithms show that they are capable of being ran online in a flight test. They make a reasonable decision and are capable of quickly reacting to changing conditions, enabling redirection to a more suitable landing site

Smart Cities: Inverse Design of 3D Urban Procedural Models with Traffic and Weather Simulation

Urbanization, the demographic transition from rural to urban, has changed how we envision and share the world. From just one-fourth of the population living in cities one hundred years ago, now more than half of the population does, and this ratio is expected to grow in the near future. Creating more sustainable, accessible, safe, and enjoyable cities has become an imperative

2nd International Conference on Numerical and Symbolic Computation

The Organizing Committee of SYMCOMP2015 – 2nd International Conference on Numerical and Symbolic Computation: Developments and Applications welcomes all the participants and acknowledge the contribution of the authors to the success of this event. This Second International Conference on Numerical and Symbolic Computation, is promoted by APMTAC - Associação Portuguesa de Mecânica Teórica, Aplicada e Computacional and it was organized in the context of IDMEC/IST - Instituto de Engenharia Mecânica. With this ECCOMAS Thematic Conference it is intended to bring together academic and scientific communities that are involved with Numerical and Symbolic Computation in the most various scientific area

Intelligent deployment strategies for passive underwater sensor networks

Passive underwater sensor networks are often used to monitor a general area of the ocean, a port or military installation, or to detect underwater vehicles near a high value unit at sea, such as a fuel ship or aircraft carrier. Deploying an underwater sensor network across a large area of interest (AOI), for military surveillance purposes, is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors. Moreover, monetary constraints, arising from the high cost of these sensors and their deployment, limit the number of available sensors. As a result, sensor deployment must be done as efficiently as possible. The objective of this work is to develop a deployment strategy for passive underwater sensors in an area clearance scenario, where there is no apparent target for an adversary to gravitate towards, such as a ship or a port, while considering all factors pertinent to underwater sensor deployment. These factors include sensing range, communications range, monetary costs, link redundancy, range dependence, and probabilistic visitation. A complete treatment of the underwater sensor deployment problem is presented in this work from determining the purpose of the sensor field to physically deploying the sensors. Assuming a field designer is given a suboptimal number of sensors, they must be methodically allocated across an AOI. The Game Theory Field Design (GTFD) model, proposed in this work, is able to accomplish this task by evaluating the acoustic characteristics across the AOI and allocating sensors accordingly. Since GTFD considers only circular sensing coverage regions, an extension is proposed to consider irregularly shaped regions. Sensor deployment locations are planned using a proposed evolutionary approach, called the Underwater Sensor Deployment Evolutionary Algorithm, which utilizes two suitable network topologies, mesh and cluster. The effects of these topologies, and a sensor\u27s communications range, on the sensing capabilities of a sensor field, are also investigated. Lastly, the impact of deployment imprecision on the connectivity of an underwater sensor field, using a mesh topology, is analyzed, for cases where sensor locations after deployment do not exactly coincide with planned sensor locations

Variant-Depth Neural Networks for Deblurring Traffic Images in Intelligent Transportation Systems

Intelligent transportation systems (ITS) with surveillance cameras capture traffic images or videos. However, images or videos in ITS often encounter blurs due to various reasons. Considering resource limitations, although recent technologies make progress in image-deblurring, there are still challenges in applying image-deblurring models in practical transportation systems: the model size and the running time. This work proposes an artful variant-depth network (VDN) to address the challenges. We design variant-depth sub-networks in a coarse-to-fine manner to improve the deblurring effect. We also adopt a new connection namely stack connection to connect all sub-networks to reduce the running time and model size while maintaining high deblurring quality. We evaluate the proposed VDN with the state-of-the-art (SOTA) methods on several typical datasets. Results on Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) show that the VDN outperforms SOTA image-deblurring methods. Furthermore, the VDN also has the shortest running time and the smallest model size

Realistic simulation and animation of clouds using SkewT-LogP diagrams

Nuvens e clima são tópicos importantes em computação gráfica, nomeadamente na simulação e animação de fenómenos naturais. Tal deve-se ao facto de a simulação de fenómenos naturais−onde as nuvens estão incluídas−encontrar aplicações em filmes, jogos e simuladores de voo. Contudo, as técnicas existentes em computação gráfica apenas permitem representações de nuvens simplificadas, tornadas possíveis através de dinâmicas fictícias que imitam a realidade. O problema que este trabalho pretende abordar prende-se com a simulação de nuvens adequadas para utilização em ambientes virtuais, isto é, nuvens com dinâmica baseada em física que variam ao longo do tempo. Em meteorologia é comum usar técnicas de simulação de nuvens baseadas em leis da física, contudoossistemasatmosféricosdeprediçãonuméricasãocomputacionalmente pesados e normalmente possuem maior precisão numérica do que o necessário em computação gráfica. Neste campo, torna-se necessário direcionar e ajustar as características físicas ou contornar a realidade de modo a atingir os objetivos artísticos, sendo um fator fundamental que faz com que a computação gráfica se distinga das ciências físicas. Contudo, simulações puramente baseadas em física geram soluções de acordo com regras predefinidas e tornam-se notoriamente difíceis de controlar. De modo a enfrentar esses desafios desenvolvemos um novo método de simulação de nuvens baseado em física que possui a característica de ser computacionalmente leve e simula as propriedades dinâmicas relacionadas com a formação de nuvens. Este novo modelo evita resolver as equações físicas, ao apresentar uma solução explícita para essas equações através de diagramas termodinâmicos SkewT/LogP. O sistema incorpora dados reais de forma a simular os parâmetros necessários para a formação de nuvens. É especialmente adequado para a simulação de nuvens cumulus que se formam devido ao um processo convectivo. Esta abordagem permite não só reduzir os custos computacionais de métodos baseados em física, mas também fornece a possibilidade de controlar a forma e dinâmica de nuvens através do controlo dos níveis atmosféricos existentes no diagrama SkewT/LogP. Nestatese,abordámostambémumoutrodesafio,queestárelacionadocomasimulação de nuvens orográficas. Do nosso conhecimento, esta é a primeira tentativa de simular a formação deste tipo de nuvens. A novidade deste método reside no fato de este tipo de nuvens serem não convectivas, oque se traduz nocálculodeoutrosníveis atmosféricos. Além disso, atendendo a que este tipo de nuvens se forma sobre montanhas, é também apresentadoumalgoritmoparadeterminarainfluênciadamontanhasobreomovimento da nuvem. Em resumo, esta dissertação apresenta um conjunto de algoritmos para a modelação e simulação de nuvens cumulus e orográficas, recorrendo a diagramas termodinâmicos SkewT/LogP pela primeira vez no campo da computação gráfica.Clouds and weather are important topics in computer graphics, in particular in the simulation and animation of natural phenomena. This is so because simulation of natural phenomena−where clouds are included−find applications in movies, games and flight simulators. However, existing techniques in computer graphics only offer the simplified cloud representations, possibly with fake dynamics that mimic the reality. The problem that this work addresses is how to find realistic simulation of cloud formation and evolution, that are suitable for virtual environments, i.e., clouds with physically-based dynamics over time. It happens that techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems based on physics laws are computationally expensive and provide more numerical accuracy than the required accuracy in computer graphics. In computer graphics, we often need to direct and adjust physical features, or even to bend the reality, to meet artistic goals, which is a key factor that makes computer graphics distinct from physical sciences. However, pure physically-based simulations evolve their solutions according to pre-set physics rules that are notoriously difficult to control. In order to face these challenges we have developed a new lightweight physically-based cloudsimulationschemethatsimulatesthedynamicpropertiesofcloudformation. This new model avoids solving the physically-based equations typically used to simulate the formation of clouds by explicitly solving these equations using SkewT/LogP thermodynamic diagrams. The system incorporates a weather model that uses real data to simulate parameters related to cloud formation. This is specially suitable to the simulation of cumulus clouds, which result from a convective process. This approach not only reduces the computational costs of previous physically-based methods, but also provides a technique to control the shape and dynamics of clouds by handling the cloud levels in SkewT/LogP diagrams. In this thesis, we have also tackled a new challenge, which is related to the simulation oforographic clouds. From ourknowledge, this isthefirstattempttosimulatethis type of cloud formation. The novelty in this method relates to the fact that these clouds are non-convective, so that different atmospheric levels have to be determined. Moreover, since orographic clouds form over mountains, we have also to determine the mountain influence in the cloud motion. In summary, this thesis presents a set of algorithms for the modelling and simulation of cumulus and orographic clouds, taking advantage of the SkewT/LogP diagrams for the first time in the field of computer graphics

Approach for reducing the computational cost of environment classification systems for mobile robots

Disertační práce se věnuje problému změny prostředí v úlohách mobilní robotiky. Zaměřuje se na využití jednodimenzionálních nevizuálních senzorů za účelem redukce výpočetních nároků. V práci je představen nový systém pro detekci a klasifikaci prostředí robota založený na datech z kamery a z nevizuálních senzorů. Nevizuální senzory zde slouží jako prostředek detekce probíhající změny, která iniciuje klasifikaci prostředí pomocí kamerových dat. To může významně snížit výpočetní nároky v porovnání se situací, kdy je zpracováván každý a nebo každý n-tý snímek obrazu. Systém je otestován na případu změny prostředí mezi vnitřním a venkovním prostředím. Přínosy této práce jsou následující: (1) Představení systému pro detekci a klasifikaci prostředí mobilního robota; (2) Analýzu state-of-the-art v oblasti Simultánní Lokalizace a Mapování za účelem zjištění otevřených problémů, které je potřeba řešit; (3) Analýza nevizuálních senzorů vzhledem k jejich vhodnosti pro danou úlohu. (4) Analýza existujících metod pro detekci změny ve 2D signálu a představení dvou jednoduchých přístupů k tomuto problému; (5) Analýza state-of-the art v oblasti klasifikace prostředí se zaměřením na klasifikaci vnitřního a venkovního prostředí; (6) Experiment porovnávající metody studované v předchozím bodu. Jedná se dle mých znalostí o nejrozsáhlejší porovnání těchto metod na jednom jediném datasetu. Navíc jsou do experimentu zahrnuty také klasifikátory založené na neuronových sítích, které dosahují lepších výsledků než klasické přístupy; (7) Vytvoření datasetu pro testování navrženého systému na sestaveném 6-ti kolovém mobilním robotu. Podle mých znalostí do této doby neexistoval dataset, který by kromě dat potřebných k řešení úlohy SLAM, naíc přidával data umožňující detekci a klasifikaci prostředí i pomocí nevizuálních dat; (8) Implementace představného systému jako open-source balík pro Robot Operating System na platformě GitHub; (9) Implementace knihovny pro výpočet globálního popisovače Centrist v C++, taktéž dostupná jako open-source na platformě GitHub.ObhájenoThis dissertation thesis deals with the problem of environment changes in the tasks of mobile robotics. In particular, it focuses on using of one-dimensional non-visual sensors in order to reduce computation cost. The work presents a new system for detection and classification of the robot environment based on data from the camera and non-visual sensors. Non-visual sensors serve as detectors of ongoing change of the environment that initiates the classification of the environment using camera data. This can significantly reduce computational demands compared to a situation where every or every n-th frame of an image is processed. The system is evaluated on the case of a change of environment between indoor and outdoor environment. The contributions of this work are the following: (1) Proposed system for detection and classification of the environment of mobile robot; (2) State-of-the-art analysis in the field of Simultaneous Localization and Mapping in order to identify existing open issues that need to be addressed; (3) Analysis of non-visual sensors with respect to their suitability for solving change detection problem. (4) Analysis of existing methods for detecting changes in 2D signal and introduction of two simple approaches to this problem; (5) State-of-the-art analysis in the field of environment classification with a focus on the classification of indoor vs. outdoor environments; (6) Experiment comparing the methods studied in the previous point. To my best knowledge, this is the most extensive comparison of these methods on a single dataset. In addition, classifiers based on neural networks, which achieve better results than classical approaches, are also included in the experiment. (7) Creation of a dataset for testing the designed system on an assembled 6-wheel mobile robot. To the best of my knowledge, there has been no dataset that, in addition to the data needed to solve the SLAM task, adds data that allows the environment to be detected and classified using non-visual data. (8) Implementation of the proposed system as an open-source package for the Robot Operating System on the GitHub platform. (9) Implementation of a library for calculating the Centrist global descriptor in C++ and Python. Library is also available as open-source on the GitHub platform